fesn.ranepa.ru · C M H C Online reviews: are they useful for consumers? David D`Acunto . . . . . ....

I , Q M C

– A,

Publishing House “Delo”Moscow ·

C

M H C

Online reviews: are they useful for consumers?David D`Acunto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Machine learning for marketing: trends, perspectives and an evaluation of three methodsDaniel Sonnet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

The contemporary marketing classifi cations: distinctions sections and metricsIvan Novitskii, Nikita Tsyplakov, Alexander Leonow . . . . . . . . . . . . 36

The emigration issue of citizens from regions of the Russian FederationKirill Darchev, Maxim Khlystalov, Igor Yarmomedov, Svetlana Ovsiannikova . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

On the uneven population density problemsElizaveta Makarova, Erik Salikhov, Svetlana Ovsiannikova . . . . . . . . 55

Research on the number of orphans in the subjects of RFusing methods of econometric analysisEkaterina Boloban, Daria Lipina, Maria Zinovieva, Svetlana Ovsiannikova . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

Expected life expectancyand factors aff ecting itAnna Tselischeva, Anastasia Сhebotar, Svetlana Ovsiannikova . . . . . 71

Analysis of generation Z life satisfactionEkaterina Ademasova, Valeriya Gorokhova, Pavel Zhokhovsky, Svetlana Ovsiannikova . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

A multifactor analysis of fl u incidencePolina Gryaznova, Polina Tarnovskaya, Svetlana Ovsiannikova . . . . . 82

Analysis of the factors infl uencing life expectancyVictoria Pshenichnykh, Alice Stetsenko, Svetlana Ovsiannikova . . . . . 92

Analysis of road traffi c accidents in RussiaDaria Peshnikova, Svetlana Ovsiannikova . . . . . . . . . . . . . . . . . 108

УДК 330ББК 65 Editorial Board:

Katalin Dióssi, PhD, Russian Academy of National Economy and Public Administration, Russia

Svetlana Ovsiannikova, PhD, Russian Academy of National Economy and Public Administration, Russia

Andrea Mikáczó, PhD, Szent István University, Hungary

nd International management, Quality and Marketing Conference –th April, . (Вторая Международная конференция по менеджменту, качеству и маркетингу, – апреля года: на англ. языке). — М.: Издательский дом «Дело» РАНХиГС, . — с.

ISSN -

The scientifi c works collection contains the results of researches presented at the inter-national scientifi c-practical nd International “Management, Quality and Marketing” conference. The collection is formed from the articles of professors and undergraduate, graduate and postgraduate students of studies of Faculty of economic and social scien-ces of Russian Presidential Academy of National Economy and Public Administration, Nanyang Technological University (Singapore), University of Pisa (Italy), University of Applied Sciences Hochschule Fresenius (Germany), Szent István University (Hungary), Budapest Business School (Hungary), “Dunărea de Jos” University of Galaţi (Romania).

The content of the collection refl ects the current theoretical and practical issues on the following topics: modern management and marketing, environmental issues, human capital, national economy, business education, quality management and lean production, effi ciency of business processes based on the use of modern technologies and capabili-ties of the digital economy.

For researchers, teachers, students, graduate students, managers-practitioners, as well as anyone interested in management, quality and marketing.

УДК 330ББК 65

ISSN -

© Russian Presidential Academy of the National Economy and Public Administration,

An empirical study of factors aff ecting suicide ratein the Russian FederationAleksandr Semenov, Dmitry Tikhonov, Svetlana Ovsiannikova . . . . 116

N E E I

The refl ection of tradition at the 100th anniversary of Romania. The way the tradition helps at forming the identity of the nationOana Andreea Nae, Patricia-Alexandra Nae . . . . . . . . . . . . . . . 125

Research on the subsidy level in the Russian Federation: correlation-regression analysisVladislav Beliaev, Evgeniia Kalinina, Svetlana Ovsiannikova . . . . . 137

Factors infl uencing technology innovations costsSofi ya Vdovenko,Renata Mikhailova, Svetlana Ovsiannikova . . . . . . 145

Investigating potential tourism strategies for promotingthe rich cultural heritage of the Republic of DagestanDorobăţ Dragoș, Makhach M. Vagabov, Raziyat Akhmedova, Hajara Amaeva, Yanev Etien . . . . . . . . . . . . . . . . . . . . . . . . . 152

An empirical study of water pollution in the regionsof the Russian FederationKristina Bodrova, Vidana Sizonenko, Svetlana Vasilevich, Svetlana Ovsiannikova . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177

Research on the incidence rate in regions of the Russian FederationNatalia Nalivayko, Svetlana Ovsiannikova . . . . . . . . . . . . . . . . 185

The problem of deforestation in RussiaElizaveta Volskaya, Valeriya Lesnyak, Svetlana Ovsiannikova . . . . . 193

M E

Data management for business intelligence: collection, storage and processing issuesEvgeny Itsakov . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201

Project risk management: a case of developing an innovative manufacturing enterpriseAnastasiia Lazarenko, Marylou Sarah Lucille Dupuis . . . . . . . . . . 207

A new approach for manufacturer to improve traditional price negotiation at the retailer`s market monopolyPolina Sintyurihina, Anastasia Zhuravleva, Evgeny Itsakov. . . . . . . 216

Herfendahl — Hirshman index calculation problemfor diff erent marketsAnastasia Petryaeva, Alexandra Stepanova, Ilya Davydov, Aleksander Leonow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226

Process mining as an advanced tool for process analysis:logistics department case studyAndrey Cherevets, George Blinov, Zemfi ra Aybedullova, Evgeny Itsakov . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234

Comparative study of certain factors determining qualityassurance in higher education between Hungary and RussiaBoglárka Herczeg, Katalin Dióssi, Tibor Miskolczi, Margarita Kozlova, Andrea Mikáczó . . . . . . . . . . . . . . . . . . . . 245

Quality and Responsibility — Lessons learnt from the ESG2015 based institute accreditation for higher educational institutionsAndrea Mikáczó, Boglárka Herczeg, Tibor Miskolczi, Katalin Dióssi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 258

Managing Educational Projects: Cloud Solutions for Workfl ow AutomationOlga Makarova, Anna Olkova . . . . . . . . . . . . . . . . . . . . . . . . 269

Online reviews: are they useful for consumers?

D DADepartment of Economics and ManagementUniversity of Pisa

A

This paper focuses on the language used by con-sumers in a sample of TripAdvisor online reviews. We investigate, by means of automated text analy-sis, how the language infl uences the reviews’ useful-ness perception, i. e. the number of times the review has been marked as helpful by others.

Our overall dataset consists of over million Tr-ipAdvisor hotel reviews from the top six European destinations (GDCI, ), Amsterdam, Barcelona, Istanbul, Paris, London, Rome and covering the – period. In this paper we focus on a sam-ple of reviews about Amsterdam.

Results suggest that word count and some lin-guistic features of reviews have an infl uence on re-views’ usefulness perception. Implications for man-agers are provided.

Key words: online reviews’ usefulness; automat-ed text analysis; hospitality industry; eWOM

I

Consumers’ online reviews represent one of the main sources of electronic word-of-mouth (eWOM)

I. M, Q M C O :

(Del Chiappa et al., ) and play a critical role particularly in the tourism and hospitality industry (Schuckert et al., ). Managing online reviews eff ectively improves room occupancy (De Pelsmacker et al., ), online booking transaction average value (Torres et al., ), and consumers’ willingness to pay (Ni-eto-Garcia et al., ). When communicating about the compa-ny’s products and services customers become “objective voices” (Vermeulen and Seegers, ), and over % of consumers take into account other peers reviews when planning a holiday (Xie et al., ) and to inform their decision-making processes (Zhu & Zhang, ). Online reviews are indeed perceived as more trust-worthy and credible compared to company-generated informa-tion (Filieri et al., ; Park, Lee and Han, ).

The main features of consumer reviews are the score (e. g., stars) and the content of the review. Review content are unstruc-tured user-generated contents (Zhang et al., ) and they re-fl ect customers’ consumption experience and their perceptions in more detail than mere ratings (Xu and Li, ). Therefore, the text-based analysis of consumer reviews has attracted consider-able attention in the recent marketing literature (e. g. Berger et al., , Ludwig et al., ; Villarroel et al., , van Laer et al. ) suggesting, for instance, that customers tend to use more words to express their dissatisfaction and anger towards a prod-uct or service (Berezina et al. ). In addition, some linguistic attributes have been investigated to understand how they infl u-ence customer ratings (Zhao et al. ).

This paper focuses on the language used by consumers in a sample of TripAdvisor online reviews and in particular we inves-tigate how the language infl uences the reviews’ usefulness per-ception, i. e. number of times the review has been marked as use-ful by others, which is an important information for consumers to facilitate decision-making as it increases readers’ choice of the product/service in question.

Therefore, in this research we focus on the following major is-sues:

RQ: How do consumers evaluate online reviews’ usefulness?RQ: How reviews’ content aff ects usefulness?

D//

Data

Our overall dataset consists of over million TripAdvisor hotel reviews from the top six European destinations (GDCI, ), Amsterdam, Barcelona, Istanbul, Paris, London, Rome and cover-ing the – period (Table ). The dataset considers the to-tal amount of available hotels in the TripAdvisor platform for the selected cities.T . Descriptive statistics: sample

City N. of reviews % N. of hotels %London . ,% . ,%Paris . ,% . ,%Rome . ,% . ,%Barcelona . ,% ,%Amsterdam . ,% ,%Istanbul . ,% . ,%Total .. ,% . ,%

For the specifi c purpose of this study, we downloaded only the reviews originally written in English, in order to avoid any data loss due to mistakes in translation or misinterpretation when ap-plying the dictionaries developed for the content analysis soft-ware. Cultural biases are minimized as guests come from all over the world in the selected tourist destinations, as shown in Fig. .

Europe; 58,0%North America; 25,0%

Asia; 7,7%

Oceania; 6,4% AfricaLatin America

and The Carribean

F. . Reviewers’ Continent of origin

I. M, Q M C O :

The dataset includes i) hotel details, ii) reviewer details, iii) re-view details, and iv) the text content. Table summarizes the dataset fi elds downloaded for the purposes of this study.T . Dataset structure

Field name DescriptionHotel name Listing nameReviewer name Reviewer identityN° of contributions N° of reviews released by the reviewerN° of helpful votes N° times the review has been marked as useful

by othersReviewer age –, –, –, –, +Reviewer gender Man, womanReviewer from (City) Free fi eldReviewer from (Country) Free fi eldReview score (bubble rating) to Review date dd/mm/yy Date of review releasing — dd/mm/yyyStayed date Date of stay — mm/yyyyTraveled as Couple, business, solo, family, friendsReview header Text fi eldReview text Text fi eldAnswer text Text fi eld — Company answer

In this paper we focus only on the city of Amsterdam. From the original dataset made by . reviews we excluded records with incomplete information, and we performed our exploratory study on a fi nal sample consisting of . online reviews (Tabl e ).

T . Amsterdam sample

Rating N. of reviews % % % % % %Total . %

Methodology

Consumers’ reviews were fi rstly analyzed through LIWC (Penne-baker et al., ) already used in psychology (e. g. Bazarova et al., , Boyd and Pennebaker, ) marketing (e. g. Cruz et al.,

; Hewett et al., ) and consumer behaviour (e. g. Hum-phreys & Thomson, ; Humphreys & Wang, ). We ana-lysed reviews content by using the four LIWC ‘summary variables’ that refl ect psychological constructs (i. e. analytical thinking, clout, authenticity, emotional tone) which have been used in pre-vious studies (Akpinar et al. , Hwong et al. , Yoon et al. , Margolin and Markowitz , Parkinson et al. ).

Second, we used R software to perform sentiment analysis of textual content and in order to compute the i) subjectivity (Giat-soglou et al., ; Saif et al., ), ii) polarity (Cho et al., ; Deng et al., ; Giatsoglou et al., ; Saif et al., , iii) di-versity (Lahuerta-Otero and Cordero- Gutié rrez, ; Zhang et al., a), and iv) readability (Gunning, ; Fang et al., , Li et al., ) scores for each review.

F

When looking at the perceived usefulness and rating of reviews, preliminary results show signifi cant diff erences among the char-acteristics of reviewers in terms of age, gender, country, year, trip purpose.

Reviewer’s age plays an important role in terms of reviews’ use-fulness perception. In fact, the highest level of usefulness per-ceived by the other community members is detected within the + age class (,); moreover, the distribution recalls a positive relationship between usefulness and reviewer’s age. That is, the older the reviewer, the higher the average perception of useful-ness of his/her review. This fi nding can be ascribable to a sort of expertise which travellers tend to attribute to the older reviewers.

In terms of gender, men’s reviews tend to be associated with a signifi cant higher level of usefulness (.) compared to wom-en ones (.) by other travellers.

Signifi cant diff erences in terms of travel occasions are also ev-ident. In particular, business travelers (,) and solo travelers (,) are the most useful reviewers, according to the other com-munity members. Conversely, people travelling with friends (,) tend to release the reviews considered as the least useful by others. As a possible explanation, people who travel alone or

I. M, Q M C O :

for business purposes tend to be more analytic and precise in their reviewing process.

When looking at the reviewer’s origin, north Americans (,) and Oceanians (,) travelers are considered the most useful re-viewers, while Africans are the least (,).

Table reports the Anova results of usefulness and ratings per reviewer’ features.

T . Characteristics of reviews and reviewers: usefulness and ratings

N Mean values Anova

Usefulness Rating(–)

Usefulness Rating(–)

Age – , , F=, F=,– . . p<. p<.– . ,– , ,+ . ,Total , ,

Gender Woman , , F=, F=,Man , , p<, p<,Total , ,

Year – , , F=, F=,– , , p<, p<,– , ,Total , ,

Trip purpose Couple , , F=, F=,

On business , , p<, p<,Solo . ,With family . ,With friends . ,Total , ,

Reviewer’s origin Africa , , F=, F=,

Asia , , p<, p<,Europe , ,South/Cen. Ame , ,North America , ,Oceania , ,Totale , ,

By the mean of regression analysis, we then investigate the ef-fect of language metrics on the reviews’ usefulness, fi nding that there is a signifi cant eff ect of several variables. The main results of the regression indicate that word count signifi cantly predict-ed useful votes ( = ., p<.) that is, the longer the review the more it is marked as useful by other community members. The rating has a negative impact on usefulness perception (= –., p<.) suggesting that reviews with higher rates are considered less useful than reviews with negative rates. These two results are in line with Filieri et al. () who found how reviews with extremely negative ratings tend to be longer and more likely to be voted as helpful by consumers.

Moreover, and in line with Zhang et al. () and Xu and Li (), consumers appreciate the details provided by reviewers and this result is confi rmed also by the analytical variable which reports a positive and signifi cant parameter ( = ., p<.) and by the subjectivity variable which is positive as well (=., p<.).

We fi nally obtained a counter-intuitively result regarding the readability of the review which seems to impact in a negative but small way the number of useful votes (= –., p<.). Table reports the regression results.

T . Regression model

B Dev std Beta t pConstant 1,700 0,047 35,817 0,000Word count (ln) 0,288 0,008 0,156 34,894 0,000Rating (1–5) -0,013 0,006 -0,011 -2,431 0,015Analytic (std) 0,067 0,005 0,053 12,211 0,000Readable (std) -0,036 0,005 -0,028 -6,609 0,000Subjective (std) 0,025 0,006 0,019 4,370 0,000R = 0,162; R2 = 0,026; adj R2 = 0,026 dev std = 1,252704Excluded variables: Authentic, Diversity, PolarizedDV: Usefulness

D

This research contributes to the electronic word-of-mouth literature in the hospitality industry by showing an application of text mining

I. M, Q M C O :

tools (e. g. subjectivity, diversity), as review usefulness antecedents are still relatively understudied (Filieri, ). Understanding the factors that infl uence the evaluation of a review as useful is an im-portant yet relatively understudied topic in marketing. Analyzing the text content enable managers to exploit consumer insights em-bedded in textual data. These preliminary fi ndings off er insights for hotel managers, consumers, and for review platforms.

First, hotel managers should take care of longer and analyti-cal reviews since they are considered more useful by consumers. Moreover, knowing which characteristics lead to higher useful-ness allow hotels to motivate satisfi ed customers in writing more helpful reviews. The number of useful votes can infl uence, in an indirect way, the reputation and the revenue of the reviewed fi rm. It is therefore an indicator to be considered by managers in ad-dition to the number of stars (i. e. rating) a review receives.

Second, consumers can predict the potential most useful re-views among the new ones, and therefore shortlist them for their future purchase decision making. Also, consumers who know how to write good and useful reviews, can use this knowledge for their review-writing or blogging activities in order to become more re-warding.

Third, review platforms can assess review usefulness in a more eff ective way, and they should better highlight the most useful reviews, as they represent a quality indicator for the platform among its competitors.

R

. Akpinar, E., & Berger, J. (). Valuable Virality. Journal of Mar-keting Research, (), –. doi:./jmr..

. Berezina, K., Bilgihan, A., Cobanoglu, C., & Okumus, F. (). Understanding satisfi ed and dissatisfi ed hotel customers: text mining of online hotel reviews. Journal of Hospitality Marketing & Management, (), –.

. Berger, J., Sorensen, A. T., & Rasmussen, S. J. (). Positive eff ects of negative publicity: When negative reviews increase sales. Marketing Science, (), –.

. Cho, H., Kim, S., Lee, J., Lee, J.S. (). Data-driven integration of multiple sentiment dictionaries for lexicon-based sentiment classification of product reviews. Knowledge-Based Sys-tems , –.

. De Pelsmacker, P., van Tilburg, S., & Holthof, C. (). Digital marketing strategies, online reviews and hotel performance. In-ternational Journal of Hospitality Management, , –.

. Del Chiappa, G., Lorenzo-Romero, C., & Alarcón-del-Amo, M. D. C. (). Profi ling tourists based on their perceptions of the trustworthiness of diff erent types of peer-to-peer applications. Current Issues in Tourism, (), –.

. Deng, S., Sinha, A. P., & Zhao, H. (). Adapting sentiment lexicons to domain-specifi c social media texts. Decision Support Systems, , –.

. Fang, B., Ye, Q., Kucukusta, D., & Law, R. (). Analysis of the perceived value of online tourism reviews: Infl uence of reada-bility and reviewer characteristics. Tourism Management, , –.

. Filieri, R., Alguezaui, S., & McLeay, F. (). Why do travelers trust TripAdvisor? Antecedents of trust towards consumer-gen-erated media and its infl uence on recommendation adoption and word of mouth. Tourism Management, , –.

. Filieri, R., Raguseo, E., & Vitari, C. (). What moderates the infl uence of extremely negative ratings? The role of review and reviewer characteristics. International Journal of Hospitality Management, , –.

. GDCI, (). Mastercard global worldwide insights. Retrieved October , , from https://newsroom.mastercard.com/wp-content/uploads///MasterCard-GDCI--Final-Re-port.pdf

. Giatsoglou, M., Vozalis, M. G., Diamantaras, K., Vakali, A., Sari-giannidis, G., & Chatzisavvas, K. C. (). Sentiment analysis leveraging emotions and word embeddings. Expert Systems with Applications, , –.

. Gunning, R. (). The fog index after twenty years. Journal of Business Communication, (), –.

I. M, Q M C O :

. Humphreys, A. (). Megamarketing: The creation of markets as a social process. Journal of Marketing, (), –.

. Humphreys, A., & Wang, R. J. H. (). Automated text analy-sis for consumer research. Journal of Consumer Research, (), –.

. Hwong, Y. L., Oliver, C., Van Kranendonk, M., Sammut, C., & Se-roussi, Y. (). What makes you tick? The psychology of so-cial media engagement in space science communication. Com-puters in Human Behavior, , –.

. Lahuerta-Otero, E., & Cordero-Gutiérrez, R. (). Looking for the perfect tweet. The use of data mining techniques to fi nd in-fl uencers on Twitter. Computers in Human Behavior, , –.

. Li, H., Zhang, Z., Meng, F., & Janakiraman, R. (). Is peer evaluation of consumer online reviews socially embedded?–An examination combining reviewer’s social network and social identity. International Journal of Hospitality Manage-ment, , –.

. Ludwig, S., De Ruyter, K., Friedman, M., Brüggen, E. C., Wetzels, M., & Pfann, G. (). More than words: The infl uence of af-fective content and linguistic style matches in online reviews on conversion rates. Journal of Marketing, (), –.

. Margolin, D., & Markowitz, D. M. (). A multitheoretical ap-proach to big text data: comparing expressive and rhetorical logics in Yelp reviews. Communication Research, (), –.

. Newman, M. L., Pennebaker, J. W., Berry, D. S., & Richards, J. M. (). Lying words: Predicting deception from linguistic styles. Personality and social psychology bulletin, (), –.

. Nieto-García, M., Muñoz-Gallego, P. A., & González-Benito, Ó. (). Tourists’ willingness to pay for an accommodation: The eff ect of eWOM and internal reference price. International Jour-nal of Hospitality Management, , –.

. Park, D. H., Lee, J., & Han, I. (). The eff ect of on-line con-sumer reviews on consumer purchasing intention: The moder-ating role of involvement. International journal of electronic commerce, (), –.

. Parkinson, J., Schuster, L., Mulcahy, R., & Taiminen, H. M. (). Online support for vulnerable consumers: a safe place?. Journal of Services Marketing, (/), –.

. Pennebaker, J. W., Booth, R. J., & Francis, M. E. (). Linguis-tic inquiry and word count: LIWC [Computer software]. Austin, TX: liwc. net, .

. Pennebaker, J. W., Chung, C. K., Frazee, J., Lavergne, G. M., & Beaver, D. I. (). When small words foretell academic suc-cess: The case of college admissions essays. PloS one, (), e.

. Saif, H., He, Y., Fernandez, M., & Alani, H. (). Contextual semantics for sentiment analysis of Twitter. Information Pro-cessing & Management, (), –.

. Schuckert, M., Liu, X., & Law, R. (). Hospitality and tourism online reviews: Recent trends and future directions. Journal of Travel & Tourism Marketing, (), –.

. Torres, E. N., Singh, D., & Robertson-Ring, A. (). Consum-er reviews and the creation of booking transaction value: Les-sons from the hotel industry. International Journal of Hospitali-ty Management, , –.

. Van Laer, T., Escalas, J. E., Ludwig, S., & van den Hende, E. A. (). What happens in Vegas stays on TripAdvisor? Comput-erized text analysis of narrativity in online consumer reviews. Journal of consumer research

. Vermeulen, I. E., & Seegers, D. (). Tried and tested: The im-pact of online hotel reviews on consumer consideration. Tour-ism management, (), –.

. Villarroel Ordenes, F., Ludwig, S., De Ruyter, K., Grewal, D., & Wetzels, M. (). Unveiling what is written in the stars: Ana-lyzing explicit, implicit, and discourse patterns of sentiment in social media. Journal of Consumer Research, (), –.

. Xu, X., & Li, Y. (). The antecedents of customer satisfaction and dissatisfaction toward various types of hotels: A text min-ing approach. International Journal of Hospitality Management, , –.

I. M, Q M C O :

. Yoon, G., Li, C., Ji, Y., North, M., Hong, C., & Liu, J. (). At-tracting comments: digital engagement metrics on Facebook and fi nancial performance. Journal of Advertising, (), –.

. Zhang, D., Zhou, L., Kehoe, J. L., & Kilic, I. Y. (). What on-line reviewer behaviors really matter? Eff ects of verbal and nonverbal behaviors on detection of fake online reviews. Jour-nal of Management Information Systems, (), –.

. Zhang, X., Yu, Y., Li, H., & Lin, Z. (). Sentimental interplay between structured and unstructured user-generated contents: an empirical study on online hotel reviews. Online Information Review, (), –.

. Zhao, Y., Xu, X., & Wang, M. (). Predicting overall customer satisfaction: big data evidence from hotel online textual reviews. International Journal of Hospitality Management, , –.

. Zhu, F., & Zhang, X. (). Impact of online consumer reviews on sales: The moderating role of product and consumer char-acteristics. Journal of marketing, (), –.

. Akpinar, E., & Berger, J. (). Valuable Virality. Journal of Mar-keting Research, (), –. doi:./jmr..

. Berezina, K., Bilgihan, A., Cobanoglu, C., & Okumus, F. (). Understanding satisfi ed and dissatisfi ed hotel customers: text mining of online hotel reviews. Journal of Hospitality Marketing & Management, (), –.

. Berger, J., Sorensen, A. T., & Rasmussen, S. J. (). Positive eff ects of negative publicity: When negative reviews increase sales. Marketing Science, (), –.

. Cho, H., Kim, S., Lee, J., Lee, J.S. (). Data-driven integration of multiple sentiment dictionaries for lexicon-based sentiment classification of product reviews. Knowledge-Based Sys-tems , –.

. De Pelsmacker, P., van Tilburg, S., & Holthof, C. (). Digital marketing strategies, online reviews and hotel performance. In-ternational Journal of Hospitality Management, , –.

. Del Chiappa, G., Lorenzo-Romero, C., & Alarcón-del-Amo, M. D. C. (). Profi ling tourists based on their perceptions of the

trustworthiness of diff erent types of peer-to-peer applications. Current Issues in Tourism, (), –.

. Deng, S., Sinha, A. P., & Zhao, H. (). Adapting sentiment lexicons to domain-specifi c social media texts. Decision Support Systems, , –.

. Fang, B., Ye, Q., Kucukusta, D., & Law, R. (). Analysis of the perceived value of online tourism reviews: Infl uence of reada-bility and reviewer characteristics. Tourism Management, , –.

. Filieri, R., Alguezaui, S., & McLeay, F. (). Why do travelers trust TripAdvisor? Antecedents of trust towards consumer-gen-erated media and its infl uence on recommendation adoption and word of mouth. Tourism Management, , –.

. Filieri, R., Raguseo, E., & Vitari, C. (). What moderates the infl uence of extremely negative ratings? The role of review and reviewer characteristics. International Journal of Hospitality Management, , –.

. GDCI, (). Mastercard global worldwide insights. Retrieved October , , from https://newsroom.mastercard.com/wp-content/uploads///MasterCard-GDCI--Final-Re-port.pdf

. Giatsoglou, M., Vozalis, M. G., Diamantaras, K., Vakali, A., Sari-giannidis, G., & Chatzisavvas, K. C. (). Sentiment analysis leveraging emotions and word embeddings. Expert Systems with Applications, , –.

M : ,

Machine learning for marketing: trends, perspectivesand an evaluation of three methods

D SUniversity of Applied Science, Hochschule Fresenius, Hamburg/Germany

A

Machine learning methods have gained popularity among marketers in recent years. This article dis-cusses the trends and perspectives of machine learning approaches in marketing applications. In the present time, big data and machine learning are topics that are on everyone’s lips. However, wheth-er or not this hype is justifi ed remains to be seen. This paper summarizes relevant examples and sur-veys to derive possible chances and changes for marketers. Furthermore, it compares the perfor-mances of three machine learning methods that have been applied on a well-known Portuguese di-rect marketing dataset. All three procedures will be assessed based on their performance and suitability in direct marketing campaigns.

Key words: machine learning, marketing, big data, neural net, decision tree, logistic regression

I

Machine learning is a branch of artifi cial intelli-gence that focusses on the design and development

of algorithms, which allows computer to develop behaviours based on data . Machine learning algorithms currently aff ect var-ious areas of economic activities, including marketing. Here, spe-cifi cally, the trend of automated analysis of customer behaviour based on data becomes apparent. Marketing has a tradition of implementing new methods, and the current form of marketing has been formed as a result of many researchers’ suggested solu-tions from a wide range of disciplines and new insights into mar-keting problems .

The aim of this paper is threefold. First, a literature review will list some positive practice approaches wherein marketing man-agers have successfully used machine learning. Second, the most important results from surveys on how artifi cial intelligence and machine learning will change marketing in the future will be pre-sented. For example, a survey conducted among German, Swiss and Austrian marketing managers revealed that % of the marketing managers fi nd artifi cial intelligence important for marketing. However, currently, every third marketing department spends less than % of their resources on analysis, data science or customer insights . This ratio is assumed to increase in the fu-ture. Possible implications concerning the resulting constellation on marketing teams will also be summarised.

Machine learning is a broad fi eld. It comprises various meth-ods and approaches. However, it remains unclear which are the methods or algorithms best suitable for particular marketing tasks in marketing applications. Because of this, thirdly, this pa-per will also evaluate the three machine learning methods on a well-known banking direct marketing dataset. The data is real-world data ( variables and observations) gathered from a Portuguese marketing campaign on bank deposit subscriptions . Logistic regression, neural network and decision trees will be compared and evaluated based on their applicability and perfor-mance in this direct marketing dataset.

Russell and Norvig , p. . Chintagunta et al. , p. . Bünte a, p. . Moro et al. , p. .

I. M, Q M C M : ,

The International Data Corporation (IDC) has forecasted that the global data sphere will grow from the zettabytes in to zettabytes in . Many authors have been creating a hype about big data and the attractiveness of using this data that it has begun to sound unreal. Some authors have also promised that big data in combination with machine learning is going to enable marketers to identify the right customers for campaigns. It is indeed correct that having more data is valuable ; however, maintaining a critical distance from the real options these pro-cedures off er is also important. In order to outline the current options machine learning off ers to marketers, a few positive practices have been summarised fi rst.

C —

Consumer perceptions are necessary for brand managers in order to derive a marketing strategy. Culotta and Cutler developed an automated procedure to monitor brand-related messages on Twitter . Twitter was also used by Liu et al. for their research. They argued that reliable sale forecasts are important for market-ing decision makers as this information aff ects marketing budg-et allocations as well as the overall marketing strategy. Social on-line platforms constantly deliver a great amount of data on con-sumer behaviour. Based on this, Liu et al. suggested a method to use Twitter messages in order to forecast sales .

New technology (cameras, computer etc.) are often complex to consumers. Consequently, it becomes more diffi cult to under-stand consumers’ preferences. Because of this, Huang and Luo developed a method of preference elicitation for complex prod-ucts . Ringel and Skiera suggested another solution that helped reduce complexity. They proposed mapping procedure methods that helps visualize complex market structures (more than ,

David Reinsel, John Gantz and John Rydning , p. . Dean , p. . Culotta and Cutler , p. . Liu et al. , p. . Huang and Luo , p. .

products). Afterwards, they applied their procedure to the LED-TV market and proved that their method outperforms tradition-al approaches .

Individual user profi ling methods have been on marketers’ dream list for a long time. Consequently, Trusov et al. proposed a modelling approach that enables marketers to uncover individ-ual user profi les from consumers’ web-surfi ng behaviour . This approach might possibly be combined with Jocobs et al.’s solu-tion. They used a latent Dirichlet allocation (LDA) to identify sets of products that are likely to be purchased together. This is espe-cially interesting among online retailers who sell large assort-ments, where the scalability of the forecasts is as valuable as ac-curacy .

Lu et al. proposed a recommendation system for new garment purchases by applying real time in-store videos. They suggested that these might increase product sales . Often, fi rms’ advertise-ments are costly experiments conducted to determine their ef-fectiveness. In order to reduce these costs, Schwartz et al. sug-gested a method to identify the banner-advertising characteris-tics that are most probable to be attractive to consumers .

Green marketing has become a trend in modern marketing be-cause of a rise in consumer awareness about the environment. Building on this, Chowdhury and Samuel used a neural network approach to explain the behavioural pattern of the gap between actually purchased and intended but not bought green products .

Knowledge about relevant competitors is important for mar-keting managers as it is necessary for developing a strategy and allocating resources. Guo et al. suggested a method that does not engage in traditional competitor analysis methods such as fi nd-ing rival products. Rather, they aimed to enable marketing man-agers to monitor their fi rm’s market position and competitors in

Ringel and Skiera , p. . Trusov et al. , p. . Jacobs et al. , p. . Lu et al. , p. . Schwartz et al. , p. . Chowdhury and Samuel , p. .

I. M, Q M C M : ,

real time. For this, they combined web crawler, natural language processing and machine learning .

Moro et al. applied a real-world data set from a Portuguese bank marketing campaign. Their overall aim was to derive a mod-el that is suffi ciently able to explain a successful consumer con-tact, i. e. whether or not the client has subscribed to a deposit .

Though the specifi ed positive practices (examples) are not exhaustive, it is not possible to list them all. It has been a con-scious choice to exclude machine learning examples of big com-panies such as Amazon, Alibaba, Tencent, Facebook or Google. Nevertheless, the variety of examples given reveals that ma-chine learning is applied in diff erent areas of marketing, and the tendency for the same is rising. This will aff ect marketing, and the next section will summarise the trends and changes in mar-keting.

T

In order to benefi t from big data, marketing needs to incorporate disciplines such as data science and machine learning , and mar-keting decision makers are aware of this. ITSMA conducts an an-nual survey on the “Services Marketing Budget Allocations and Trends Study”. Marketing technology and automation systems are ranked st in the ITSMA survey when compared to the eighth priority given to marketers in the ITSMA survey. It is, thus, no wonder that the top-ranked areas in terms of data are marketing automation, social media and data analytics .

Ransbotham et al. conducted a survey, wherein they collected opinions from individuals from countries and industries in spring . When the researchers asked survey participants

“What areas within your organization do you anticipate AI (big data and machine learning) will aff ect the most? Select three,” the following industries mentioned marketing to be among the

Guo et al. , p. . Moro et al. , p. . Chintagunta et al. , p. . Rousselet , p. .

three: industries technology, media, telecom, consumer, and pro-fessional services .

Bünte questioned marketing managers from Germany, Austria and Switzerland regarding their understanding about how artifi cial intelligence (AI) will aff ect marketing in the future. It is important to mention that Bünte stresses how there is no common defi nition for artifi cial intelligence. According to her, every support system that can self-learn is considered artifi cial intelligence . Based on her defi nition, machine learning is there-fore a prerequisite. Moreover, all of her survey results can conse-quently be applied to machine learning.

The details of the survey are as follows:Currently, there are big diff erences between the perceived

benefi ts of AI in marketing and the actual use of AI .

• % of the marketing decision makers believe AI to be im-portant in marketing

• .% of the study participants stated that they aimed to in-crease the use of AI in marketing

However:

• Only % currently use AI in marketing applications• Almost % of all marketing departments have less than %

employees who deal with consumer data and insights

Marketing managers see in AI the (positive) future of marketing. They expect signifi cant changes in the team constellation .

• Nearly % of respondents attest that AI has great impor-tance in marketing tasks in the near future

• A majority of marketing experts see very positive eff ects of AI related to the Marketing core tasks and the team constel-lation

• % believe that AI will considerably change marketing• % expect that these changes will be stronger than the

Ransbotham et al. , p. . Bünte a, p. . Bünte b, p. . Bünte b, p. .

I. M, Q M C M : ,

changes made through social media• % see AI to be decisive in the future competitiveness of

companies• The largest area of application is expected to be in consum-

er data and insights and Consumer Interaction• % believe that the number of employees in marketing

teams will remain the same or even grow• % of respondents expect an increasing number of data

scientists in Marketing• % do not believe that this will reduce the number of cre-

ative people in the team

To summarise, a majority of survey participants expect changes in team constellations. Specifi cally, the number of data scientists is expected to increase. However, data scientists in a marketing environment currently face new challenges. It is not obvious which machine learning procedure is best suited for a specifi c data set. The next section is hence going to evaluate the three methods that can be used on a direct marketing data set.

E

The used data set has observations and diff erent attrib-utes (= variables): The data observations are the outcome of a di-rect marketing campaign of a Portuguese bank wherein the call agents called the customers. The agents had to contact the cus-tomers often more than once to know if the product (bank term deposit) would be subscribed to or not. The data set is available online and has been fully described by Moro . The variables are:

. Age (numeric),. Type of job (categorical),. Marital status (categorical),. Education (categorical),. Has credit in default? (binary),

https://archive.ics.uci.edu/ml/datasets/bank+marketing, last checked .. Moro et al. .

. Average yearly balance, in euros (numeric),. Has housing loan? (binary),. Has personal loan? (binary),. Contact communication type (categorical),. Last contact day of the month (numeric),. Last contact month of year (categorical),. Last contact duration, in seconds (numeric),. Number of contacts performed during this campaign and

for this client (numeric),. Number of days that passed by after the client was last

contacted from a previous campaign (numeric),. Number of contacts performed before this campaign and

for this client (numeric),. Outcome of the previous marketing campaign (categori-

cal), and. Target variable: Has the client subscribed to a term depo-

sit? (binary).

.% () of the called customers did not subscribe to a term deposit, while .% () chose to subscribe. The goal of the predictive machine learning application is to build models that are able to forecast if a customer who was contacted subscribed to a term deposit or not. If this target variable could be accurate-ly forecasted, the bank would need to contact only the custom-ers who are likely to subscribe to a term deposit. For this purpose, we will apply

• logistic regression,• deep learning (neural network), and• decision tree

within a machine learning concept. For further information con-cerning logistic regression, the reader is asked to refer to Hosmer and Lemeshow . Deep learners are particular multi-layer neural networks that are trained using back-propagation. The interest-ed reader is asked to refer to the online book by Nielsen . Deci-sion trees are a popular method when it comes to classifi cation

Hosmer and Lemeshow . http://neuralnetworksanddeeplearning.com/, checked on //

I. M, Q M C M : ,

but also in regression tasks. The reader is asked to refer to Rokach and Maimon .

All three methods are allowed to use all observations. However, the observations are split into two groups. In to-tal, % () of the observations are used to build the models while only % () of the observations are used to test the model (evaluate the performance). All three models engage in cross-validation and parameter optimisation.

Rokach and Maimon .

All calculations and visualisations are done using RapidMin-er . The main criterion to evaluate the diff erent methods is the achieved forecasted accuracy of the test observations. The following fi gure summarises the accuracy achieved by the diff er-ent methods.

The last fi gure reveals that at fi rst sight all three models per-formed evenly. All three methods are able to predict the outcome of the binary target variable with an accuracy of %. It is worth mentioning that the training of the deep learning method took signifi cantly more time ( seconds). However, it seems advisable to take a closer look at the accuracy of each method. This is be-cause, in the population of all observations, only .% of the to-tal customers decided to take the off er. In other words, an accu-racy of % could be achieved even if the methods completely failed to predict the cases of the off er taker.

The comparison of the last three fi gures clearly shows that only deep learning is able to reveal the pattern about whether the contacted customers will accept the bank’s off er. + = observations out of the test sample represent the case when con-sumers accepted the off er. Only deep learning has a “class accu-racy” of .%. Both other methods delivered values less than %, which is a poor performance.

For further information concerning RapidMiner: https://rapidminer.com

F. . Comparison of the three methods

F. . Accuracy details for Logistic Regression

F. . Accuracy details for Deep Learning

F. . Accuracy details for Decision Tree

1.00

0.90

0.80

0.70

0.60

0.50

0.40

0.30

0.20

0.10

0.000.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

Logistic RegressionDecision TreeDeep Learning

F. . Receiver-Operating-Characteristic-Curve

I. M, Q M C M : ,

For the evaluation of binary classifi er, ROC–Curves (Receiver-Operating-Characteristic-Curves) are popular. It is a probability curve that shows how much a model is able to distinguish be-tween the classes (customers accept or do not accept the off er). Figure compares the ROC–Curves of all the three methods. Since Deep Learning has the steepest curve, it underpins that this method is to be preferred.

In summary, it can be stated that only deep learning seems suitable to predict the customers who are likely to accept the bank’s off er.

C

This paper discusses the trends and perspectives of machine learning in marketing. Building on this, it further evaluates three machine learning methods for creating predictive models in di-rect marketing campaigns. The trends and perspectives were ad-dressed by listing the positive practices of machine learning in marketing. These encouraging examples come from a wide range of applications. It is remarkable that besides big companies such as Google, Amazon and Facebook etc., smaller companies also developed marketing supporting tools by engaging in machine learning. Marketing managers seemed to perceive the potential of applying machine learning in marketing. This is also refl ected in the three surveys, which are summarised in the section con-cerning the trends and changes in marketing. All three surveys stress on the trend of automation in marketing. It seems very likely that this trend will aff ect the constellation of marketing teams in the near future. A relevant survey among marketing managers reveals that they believe that the proportion of data scientists in marketing departments will increase. However, cur-rently, the job requirements of a marketing data scientist are not clear. This person needs to be able to understand marketing needs and be capable of connecting this with practical machine learning knowledge in order to derive relevant models. Specifi -cally, the fact that many models and procedures have been devel-oped in machine learning makes it diffi cult to fi nd the best work-ing models for a certain task. The third aspect of this paper there-

fore aims to compare the three machine learning methods, namely logistic regression, deep learning, decision trees, regard-ing their ability to realise a model that could be helpful for a bank within a direct marketing campaign. At fi rst glance, all three models performed the same way. However, a deeper analysis re-vealed that only deep learning delivers reliable results.

R

. Bünte, Claudia (a): Künstliche Intelligenz — die Zukunft des Marketing. Ein praktischer Leitfaden für Marketing-Manag-er. Wiesbaden: Springer Gabler (essentials).

. Bünte, Claudia (b): Studie: KI — Die Zukunft des Market-ings . SRH Hochschule Berlin. Berlin, /. Online available: https://www.srh-hochschule-berlin.de/fi leadmin/user_upload/_Studie_Kuenstliche_Intelligenz_-__Die_Zukunft_des_Marketings.pdf, checked //.

. Chintagunta, Pradeep; Hanssens, Dominique M.; Hauser, John R. (): Editorial — Marketing Science and Big Data. In: Mar-keting Science (), pp. –.

. Chowdhury, Prajita; Samuel, Mercy S. (): Artifi cial neural networks. A tool for anderstanding green consumer behavior. In: Marketing intelligence & planning (), pp. –.

. Culotta, Aron; Cutler, Jennifer (): Mining Brand Percep-tions from Twitter Social Networks. In: Marketing Science (), pp. –.

. David Reinsel, John Gantz and John Rydning (): The Digi-tization of the World From Edge to Core. Online available: htt-ps://www.seagate.com/fi les/www-content/our-story/trends/fi les/idc-seagate-dataage-whitepaper.pdf, checked //.

. Dean, Jared (): Big data, data mining, and machine learn-ing. Value creation for business leaders and practitioners. Hoboken: Wiley (Wiley and SAS Business Series).

. Guo, Liang; Sharma, Ruchi; Yin, Lei; Lu, Ruodan; Rong, Ke (): Automated competitor analysis using big data analytics. In: Business process management journal (), pp. –.

I. M, Q M C M : ,

. Hosmer, David W.; Lemeshow, Stanley (): Applied logistic regression. . ed. New York: Wiley (Wiley series in probability and statistics Texts and references section).

. Huang, Dongling; Luo, Lan (): Consumer Preference Elici-tation of Complex Products Using Fuzzy Support Vector Ma-chine Active Learning. In: Marketing Science (), pp. –.

. Jacobs, Bruno J. D.; Donkers, Bas; Fok, Dennis (): Model-Based Purchase Predictions for Large Assortments. In: Market-ing Science (), pp. –.

. Liu, Xiao; Singh, Param Vir; Srinivasan, Kannan (): A Struc-tured Analysis of Unstructured Big Data by Leveraging Cloud Computing. In: Marketing Science (), pp. –.

. Lu, Shasha; Xiao, Li; Ding, Min (): A Video-Based Automat-ed Recommender (VAR) System for Garments. In: Marketing Sci-ence (), p. –.

. Moro, Sérgio; Cortez, Paulo; Laureano, Raul (): Using Data Mining for Bank Direct Marketing: An Application of the CRISP-DM Methodology. In: Paulo Novais, José Machado, Cesar Ana-lide and António Abelha (Hg.): Modelling and Simulation . The European Simulation and Modelling Conference ; ESM

‘: October –, , Guimarães, Portugal. Ostent: EURO-SIS-ETI, pp. –.

. Ransbotham, Sam; Kiron, David; Gerbert, Philipp; Reeves, Mar-tin (): Reshaping Business With Artifi cial Intelligence: Closing the Gap Between Ambition and Action. In: MIT sloan management review ().

. Ringel, Daniel M.; Skiera, Bernd (): Visualizing Asymmet-ric Competition Among More Than , Products Using Big Search Data. In: Marketing Science (), pp. –.

. Rokach, Lior; Maimon, Oded (): Data mining with deci-sion trees. Theory and applications. Singapore: World Scien-tifi c (Series in machine perception and artifi cial intelli-gence, ).

. Rousselet, Vincent (): The rise of the machines. In: Market Leader (Q), pp. –..

. Russell, Stuart J.; Norvig, Peter (): Artifi cial intelligence. A modern approach. . edition. Global edition. Upper Saddle Riv-er: Pearson (Prentice Hall Series in Artifi cial Intelligence).

. Schwartz, Eric M.; Bradlow, Eric T.; Fader, Peter S. (): Cus-tomer Acquisition via Display Advertising Using Multi-Armed Bandit Experiments. In: Marketing Science (), pp. –.

. Trusov, Michael; Ma, Liye; Jamal, Zainab (): Crumbs of the Cookie: User Profi ling in Customer-Base Analysis and Behavio-ral Targeting. In: Marketing Science (), pp. –.

T

The contemporary marketing classifi cations: distinctions sections and metrics

I N, N TStudentsRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

A LAssociate Professor Russian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

A

The article makes a distinction between marketing terms and metrics. Conducted the analysis of the market on the subject classifi cation. Carried out the certain market segmentation and the view of the signifi cance of each term is created. The modern consideration of the digital marketing includes main divisions, such as: SEO marketing, SEM mar-keting, Email marketing, Social media marketing, Website marketing, Free trials & funnel marketing, Content marketing. Every division has its own met-ric to calculate and analyze to provide the right marketing analysis.

Key words: traditional marketing, internet mar-keting, e-commerce, m-commerce, digital market-

ing, online marketing, offl ine marketing, SEO marketing, SEM marketing, inbound marketing, SMM marketing, ORM marketing, affi liate marketing, SMO marketing, SMA marketing, celebrity marketing, CTR, Conversion Rate from the Organic search to the Raw Lead, Conversion Rate from the Organic Search to the Form Submits, CPC, Paid search to sales conversion rate, Gross Open Rate, CTOR, CPM, Promoted Tweets Follow Rate

I

Marketing is a creative area, an integral part of a company. As such it is inevitable for all businesses to understand how it func-tions in order to better utilize the benefi ts of contemporary mar-keting.

R

First of all, let’s consider the classical defi nition of marketing. Kotler told that marketing is “The set of human activities direct-ed at facilitating and consummating exchanges”. The short ver-sion of this defi nition is «Marketing is the profi table satisfaction of needs». Our personal view is that marketing is the creation/de-tection of human needs and its satisfaction. You should under-stand the meaning and signifi cant of it and if you will, you can create your own vision.

On the second step we will divide marketing into four spheres:

• traditional marketing,• e-commerce marketing,• internet marketing and• digital marketing.

Let’s consider these terms by step. So, the st one is traditional marketing. We can tell that it’s the marketing before the internet creation.

The next one is e-commerce marketing. This is a large area of the economy, which includes all fi nancial and trade operations. We can include e-cash (for instance, payments by card), e-marketing, electronic data interchange (EDI), electronic funds transfer (EFT),

I. M, Q M C T

e-trade, e-banking, e-insurance. E-commerce can be classifi ed into types. The fi rst one it’s a commercial organization that includes BB (Business-to-Business), BC (Business-to-Consumer), BG (Business-to-Government), BE (Business-to-Employee), BO (Business-to-Operator). The second segment — consumers: CC (Consumer-to-Consumer), CB (Consumer-to-Business), CA (Consumer-to-Administration). The third part is an administration that involves AA (Administration-to-Administration), AB (Ad-ministration-to-Business), AC (Administration-to-Consumer). The fi nal one is the other business models such as DC (Decentral-ized-to-Consumer), GB (Government-to-Business), PP (Peer-to-Peer). These are the main marketing sections. E-commerce mar-keting can be included in this sphere and can exist as the separate part. It’s fi nancial and trade operations throw the mobile devices.

The rd term is Internet marketing that is online marketing — the marketing via internet resources. Internet marketing, online marketing, marketing in a virtual environment — all these terms are synonyms. The antonyms will be online and offl ine mg. I will talk about this further.

The fi nal sector from the classifi cation is the digital market-ing. It is more than just internet marketing. As mentioned before, it consists of online and offl ine sections.

Online marketing involves lots of diff erent items. Let’s begin from contextual advertising that as well can be named as Search Engine Advertising (SEA). This is for example when you want to buy shoes and search numerous sites, then POPs up a window with an announcement of the purchase of this thing with an at-tractive off er, that is, this advertising is based on the content of the Internet page that you were interested in earlier or are inter-ested in.

Media advertising based on diverse electronic resources.E-mail-sending that includes the advertising by e-mail.Viral advertising. This tool acts like a virus. For instance, when

someone looks at an advertisement and he want to share this in-formation with his friends, family, send somewhere, etc.

Affi liate marketing is a big tool for using. This type includes lots of subspecies such as CPC (Cost-Per-Click), CPV (Cost-Per-View), CPA/PPA (Cost-Per-Action/Pay-Per-Acquisition), CPL

(Cost-Per-Lead), CPI (Cost-Per-Install), CPS (Cost-Per-Sale) and more others. As well the Landing page included in this section. The customer hires a webmaster and pays him when the visitor makes a concrete action on the site. The purpose of this tool is to urge the user to make a specifi c target action. This page should answer three following questions: what is off ered here, why it is important and how to get it.

SEO (Search Engine Optimization) marketing lifts your site position in the search, but SEM (Search Engine Marketing) is a series of marketing activities aimed at the promotion of the por-tal, that increases the number of visitors (traffi c) on the site. It combines search engine optimization, i. e. SEO and contextual advertising.

SMM promote your site through the social media. This is not an open advertisement. This is a hidden, unobtrusive advertising that attracts the target audience to the promoted product. Users should not understand that they are openly off ered the product — they should want to buy/order the service due to the presented information. We can refer to this a hidden or so-called guerrilla marketing. Sometimes guerilla marketing also means hidden marketing — a type of advertising in which consumers do not un-derstand that it is advertising. When the information is delivered through artifi cially created discussions, comments, reviews, etc. Forums, blogs, social networks, the comment area of almost any site and even a street can act as platforms for hidden marketing. SMM includes SMO (Search Media Optimization) — website pro-motion in social networks, that raise a publicity and product awareness.

Infl uence marketing/celebrity marketing promote the product/service due to famous person attraction. The perception of the goods by the audience changes, therefore the customers them-selves are looking for the product.

ORM (Online Reputation Marketing) is the practice of devel-oping strategies where an organization can infl uence on individ-uals or others on the Internet. It helps to form a positive public opinion about the business, its products and services. Using ORM, the company can try to mitigate the eff ects of negative viral vid-eo, create proactive marketing strategies that predict the actions

I. M, Q M C T

of competitors and make eff orts to be ahead of them. Also, the zone of infl uence in the Internet can be expanded to improve the perception of the company in the online area.

We shouldn’t forget about content creation because interest-ing content is very important for the involvement. Lots of busi-nessmen and sharks of the world market use this to attract po-tential clients.

Inbound marketing is not to make people to acquire a product or service it is for notify them about this, about the brand, about the company through diff erent digital tools. Inbound marketing is a technique for drawing customers to products and services via content marketing, social media marketing, search engine opti-mization and branding. It can be integrated as in the online as in the offl ine sector.

So, digital marketing includes the internet marketing, howev-er internet marketing can exist separately.

Offl ine marketing uses a variety of means that do not involve the Internet. Some of tools are QR (Quick Response) Code, SMS and MMS, distribution through the diff erent messengers such as WhatsApp, Instagram, Twitter etc, Interactive screens that help in making a purchase like in McDonald’s when you’re entering and see the e-screen with menu and make an order, Radio and TV, Electronic billboards, Phone marketing (cold and warm call-ing).

Let’s continue our article with the diff erent metrics. So, con-sideration of the SEO marketing which is the fi rst in the list.

SEO marketing is the methodology of strategies, techniques and tactics used to increase the number of visitors to a website by obtaining a high-ranking placement in the search results page of a search engine.

SEO shows the percentage of recipients that have clicked on any link in your email message.

SEO marketing includes diff erent metrics, such as:

• СTR (click through rate)• CTR, st result through organic search• CTR, nd result through organic search• CTR, rd result through organic search

• Conversion Rate from the Organic search to the Raw Lead• Conversion Rate from the Organic Search to the Form Sub-

mits

First of all, we start with the equation of the CTR metric. It can be measured as:

ClicksCTR (click through rate) = *100%Impression

CTR shows the rate of clickability of banners or other advertise-ments, which determines the eff ectiveness of the advertising contextual campaign carried out in the network.

While calculating CTR, it is important to take into account the method of division into indicators from the fi rst, second and third query (CTR of the st, nd, rd results through organic search of the Organic Search) in search resources using organic search. Organic search — can be defi ned as a method of entering one or more search terms as a single line of text in the search en-gine. Organic search results, presented as paginated lists, are based on the relevance of search terms.

Moreover, it also important to consider the Conversion Rates from simple organic search and to the Raw Lead and from the or-ganic search to the Form submits. All of those rates can give an understanding of important content and show us the company the auditory of the website.

The next topic is SEM marketing. In this division of digital marketing, the following metrics can be distinguished as:

• CTR• CPC (cost per click)• Conversion rate from organic search to form submits• Paid search to sales conversion rate.

CTR in this marketing section can be presented and used for var-ious online platforms such as Google Display and Google Net-work. As well as to determine the eff ectiveness of mobile adver-tising and banners in applications.

The second most important metric for search marketing is CPC (cost per click).

I. M, Q M C T

CPC helps company calculate the actual cost per click that a fi rm or organization pays for each click in its own marketing campaigns and it refers to refers to the actual price you pay for each click in your pay-per-click.

CPC is calculated by the formula:

Total ad. SpendCPC = Total measured clicks

It is also important to consider what percentage of organic search should be converted to potential customers and regular subscribers.

The next topic is needed to be focused on is the Email marketing.For analyzing the email marketing, we can use following met-

rics:

• Gross Open Rate• Bounce Rate• CTR• CTOR

Gross Open Rate shows the percentage of recipients who opened the email compared to how many contacts were sent the email.

GOR is calculated by the following formula:

Email OpenedGross Open Rate = Email sent — bounces

The bounce rate is the percentage of people who landed on your website, but instead of browsing further, they exited your website.

BR is calculated by the following formula:

Total one — page visitsBR = Total entries to the page

CTOR (click-to-open rate) is a metric that compares the num-ber of people that opened the email to the number that actually clicked.

CTOR usually calculated in the terms of viewing the perfor-mance of the content of the email.

CTOR is calculated by the following formula:

Number of unique clicksCTOR = Number of unique opens

The next topic from the division list is the Social Media Mar-keting.

For analyzing the SMM we can use following metrics:

• CTR• CPM• CPC• Promoted Tweets Follow Rate• Promoted Tweets cost per follower• Like Rate• Raw Lead conversion rate

Firstly, let’s start with the Promoted Tweets Follow Rate that is calculated in as it shows the amount of people who actually keen on the companies’ content or the group in social media platforms. As more likes the company accumulate, the more attention and feedbacks the fi rm gets from. That’s emphasize the integral part of like rate for many SM platforms.

Moreover, every Promoted Tweet has its price and the total amount can be measured with the help of Promoted Tweets per Follower. Every social media has their own price list and subor-dination rules, but the price from promoted tweet per follower is always necessary to consider.

Let’s move on the Website Marketing division.For analyzing the Website marketing we can use the following

metrics:

• Traffi c from organic search• Traffi c from paid search & referral• Drop-off rate• Page views per visit• Minutes spent on per visit

First of all, the whole website marketing facing the problem of inside traffi c. To calculate this, we use the metrics of the Traf-fi c from organic search and the Traffi c from paid search & re-ferral.

I. M, Q M C T

Secondly, in the Website marketing division we meet the drop-off rate. Drop-off rate simply identifi es users who went out of the fl ow from your google analytics. This means that viewers left your site, or that they simply left the fl ow of pages you’ve defi ned.

Drop-off rate is calculated by the following formula:

Number of impressionsDrop-off rate = *100%Matched requests

In addition, during the Website Research we also need to fi g-urate the Page views per visit metric and the Minutes spent on per visit metric, because market demanded the fast-operation service.

For analyzing the Content marketing, we can use following metrics:

• Companies Using content syndication• Webinar Attendance (the percentage of registrants)• White paper conversion rate• Webinar conversion rate

White paper is a document that helps your potential customer make an informed decision in favor of your company or a particu-lar product. If the document is NOT conducive to a certain deci-sion, it could be anything but WP.

C

To sum it all up, the classifi cation research shows lots of metrics that can be used in the diff erent sphere of marketing but as well it has its own value and many of them can fl ow into another part of market. The true way would be to fi gure out the specifi c of the business and decide in which sphere of the marketing it exist and what metrics can be used to improve the situation or reach the goal. As well should be understood the digital marketing is still developing in the high speed and there is no doubt that will be lots of extra metrics and classifi cation can be added in the near-est time.

R

. Philip Kotler, Kevin Lane Keller (), Marketing Management, th ed., Saint Petersburg

. Philip Kotler, Hermawan Kartajaya, Iwan Setiawan (), Mar-keting .: Moving from Traditional to Digital

. Yurasov A.V. (), Fundamentals of E-Commerce, Moscow

. Manufacturing Marketing Group, , Louisville, Colorado, viewed March , https://www.mmmatters.com/blog/di-gital-marketing-online-offi ne

. Blog ‘Internet marketing’, –, viewed March , https://internet-marketings.ru/digital-marketing

. Constant Contanct, , viewed March , https://knowl-edgebase.constantcontact.com/articles/KnowledgeBase/-view-a-campaign-email-s-open-rate?lang=en_US

T

The emigration issue of citizens from regions of the Russian Federation

K D, M K, I YStudentsRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

S OAssociate ProfessorRussian Presidential Academy of National Economy and Public Administration Faculty of Economic and Social Sciences

A

An analysis of the factors that infl uence the emigra-tion of citizens from the territory of the Russian Federation is given. In the course of the study, a pairwise sensitivity analysis of the response varia-ble (the percentage of emigrating citizens to the population) to the selected explanatory variables was carried out. Consequently, this enabled to build a nonlinear dependence and analyze the response variable. Additionally, the correlation between the response variable and the most infl uencing inde-pendent variable was studied. Along with this, trends over time were considered as well. On the ba-sis of the data obtained and the results, it was felt

that progress was needed towards regulation of the emigration in Russia by infl uencing the chosen factors.

Key words: regression and correlation analysis, emigration, nonlinear regression model, socio-economic factors, time series, trend, constituent territories of the Russian Federation

I

By virtue of historical circumstances, Russia today owns a truly impressive territory, where a huge amount of resources is locat-ed. According to the estimates of experts, the preliminary cost of mineral reserves in Russia was $ trillion. Nevertheless, excel-ling in terms of surface area, it is only the world’s ninth largest population. The best example here is the north-eastern part of the country. The population density in the region barely reaches inhabitants per square kilometer.

A demographic policy is one of the key areas in the develop-ment of Russia. Indeed, without human intervention, the devel-opment of sparsely populated territories is impossible in spite of the robotization and other innovations. In addition, the pop-ulation itself contributes to the extensive development of the economy. Not to mention that the emigration rate refl ects citi-zens’ attitude towards socio-economic conditions of the coun-try. Apart from this, the fact that the mortality rate prevails over birth rate is peculiar to the Russian Federation. That is why the state should regulate controlled population growth by all nec-essary means.

R

This work is based on the fi ndings obtained in the fi rst part of the study. The following are the key fi ndings:

. The number of emigrants is normally distributed;. The location of constituent territories does not infl uence the

percentage of emigration.

To determine the reasons for emigration initially socio-eco-nomic explanatory variables, which could potentially infl uence

I. M, Q M C T

the response variable, were selected. The data were obtained from offi cial sources. The principal selection criteria were:

. The degree of correlation between the response variable and the independent variable is higher than among independ-ent variables;

. Logical justifi cation.

Initial check narrowed down the number of the variables ( in-dependent variables with a correlation coeffi cient of less than .). The second check, in turn, enabled to exclude a part of the variables ( independent variables with a correlation coeffi cient of less than .).T

Y X X X X X X X X X X

Y

X -.

X . .

X . . .

X . -. . .

X . -. . -. .

X . . . . . .

X . -. . -. . . .

X . . . . . . . .

X . -. . . . . . . .

X -. . -. -. -. -. . -. -. -.

Thus, it was decided to remain the variable X (the number of concluded marriages) on the ground that there is a consistent correlation over time. Further studies were carried out with the remaining variables (Table ).

Notably, each variable responds to the specifi c regions of the Russian Federation. Along with this, independent variables for were used in the study. A great majority of the gathered data is expressed as a percentage of the population by regions. These are:

. The number of concluded marriages (X). The average wage (X)

. The percentage of the labor force (X). The per capita GRP (gross regional product) (X). The homicide rate (X). The percentage of doctors (X). The percentage of offi cials (X). The outlays on environmental protection per capita (X). The percentage of children attending nursery school (X). The percentage of students (X)

T

Regression Statistics

Multiple R .

R Square .

Adjusted R Square .

Standard Error .

Observations

Further study was carried out by applying the regression anal-ysis to the linear model (Table ). In addition, the exponential model was built; however, it was not included due to its inaccu-racy. The following fi gures refl ect the soundness of the linear model. The multiple correlation ratio (Multiple R) equals .. The statistic indicates a high level of predictability of the de-pendent variable from the independent variables. Also, the de-termination ratio (R-squared) is .. Hence, in . percent of cases, the variation in the response variable (the number of em-igrants) is ‘explained by’ the variation in the independent varia-bles. Based on the results, it appears that the model is sound and operable, but it needs to be slightly improved.

It was decided to build a two-factor model for each explanato-ry variable to improve the model. Thereafter, it found that the fi rst independent variable (the number of concluded marriages) is better described by the logarithmic function. The third inde-pendent variable (the percentage of the labor force) is described by a second-degree polynomial. Editing and modifi cation of the other variables were unsuccessful due to the weak correlation with the trend. Hence, the determination ratio (R-squared) in-creased to . due to the improvements.

I. M, Q M C T

The model took a non-linear shape, however it enabled to have a better correlation between the response variable (the number of emigrants) and the independent variables.

Nonetheless, certain coeffi cients had low values due to their nearness and lack of logic compared to the percentage ratio. Con-sequently, it was decided to exclude the variable X (the per cap-ita GRP) and recast the variable X (the average wage) to obtain a more accurate model. The updated independent variable X shows the average wage per hour in US dollars. This adjustment also enabled to compare the independent variable with variables of other countries, taking working hours into account (Table ).

Y = . – Ln(X) + .X + .X+ .X+ .X+

+ .X+ .X – .X+ .XT

Intercept .

The number of concluded marriages -.

The percentage of the labor force .

The homicide rate .

The percentage of doctors .

The percentage of offi cials .

The outlays on environmental protection per capita .

The percentage of children attending nursery school .

The percentage of students -.

The average wage per hour in US dollars .

T

Regression Statistics

Multiple R .

R Square .

Adjusted R Square .

Standard Error .

Observations

A model sensitivity was analyzed during the next phase of the study. The fi rst and second independent variables were analyzed using this method. Thus, the mean values were used in the equa-

tion as unknown variables. For variables X and X, the series was taken within limits of the standard deviations (Table .). The mean of the equation was also found Y_M= . (Table .). The table does not include the last two similar negative val-ues for logarithm due to the negative deviation exceeds the mean. There is a noteworthy correlation between the independent var-iables. For instance, doubling the variable X results in an ap-proximate % reduction of the response variable. Simultaneous-ly, halving the variable X results in a % increase in the re-sponse variable. The reversed situation there occurs with the variable X, however the diff erence is not signifi cant (% while increasing and % while decreasing).T .

The number of concluded marriages

The percentage of the labor force

Mean . .

Standard deviation . .

T .

Sensitivity for LnX Sensitivity for X

. . .

. . .

… … … …

. . .

. .

- . -.

… … … …

. - . -.

. - . -.

Furthermore, in the fi nal phase of the study, a time series analysis was carried out. Initially, the interdependence between the emigration and the average wage was studied. Accordingly, the correlation of . was found. Nevertheless, the study re-vealed a spurious (false) correlation. For that reason, an irregu-lar (random) variation for relevant independent variables was found. Along with this, the correlation between them was studie d

I. M, Q M C T

(Graph and Graph ). Thereafter, the interdependence was ex-tinct, since the correlation was .. Hence, it was decided to study it with a one-year time lag (Graph ).

The model thus obtained a suffi ciently high determination ra-tio of .. As a result, a positive dependence is observed. These fi ndings cast some doubt on the preliminary proposition that in-dividuals emigrate to high wages countries. Presumably, the pop-ulation saves part of their incomes suffi cient for further emigra-tion.

10 2 7 54 10 5 10 8 10y x x

Additionally, the overall variation in the response variable over time was studied both nation-wide and in specifi c regions. This encompasses the administrative centers of the Federal Districts and regions that have maximum and minimum emigration per-centage (the Chukotka Autonomous Region and the Chechen Re-

public respectively). In accordance with the obtained data and trends, there is a general trend towards an increasing number of emigrants from each region (Graph ). Notably, exponential growth is seen in Moscow and Rostov regions, whereas a stepwise increase is in the other regions. The only exception is the emi-gration peak in St. Petersburg in – since current emigra-tion level at almost the same level as in – (Graph ).

C

In summary, it should be emphasized that emigration is a com-plex issue. The state has eff ective control policies towards eco-nomic diffi culties; however, it does not have a strategy for the emigration issue. The model shows that all explanatory variables do not contribute substantially to the emigration issue. High homicide rate, in turn, is due to that it depends upon the num-ber of people in the respective areas. It implies that a one per-cent increase results in a huge increase in crime in the region. Notably, negative coeffi cients are related to the fact that the per-centage of students is associated with the number of concluded marriages. In the long term, married people plan that their chil-dren will study at universities. Thus, an emphasis should be put on the words ‘long term’ due to the percentage of students is a more signifi cant indicator. On the other hand, the percentage of children attending nursery school has a positive dependence. Nevertheless, it is quite complicated to explain this phenomenon logically. Presumably, this is due to young families are non-loca-

X = 2612.3t + 13646

R² = 0.9940

10000

20000

30000

40000

50000

0 5 10 15

The average wage

G G

G

-0,0020

0,0020,0040,0060,008

0,010,0120,014

2006 2008 2010 2012 2014 2016 2018 2020

St. Petersburg

y = 0.0003t - 0.5721

R² = 0.888

-0,0005

0

0,0005

0,001

0,0015

0,002

0,0025

0,003

2005 2010 2015 2020

Russian Federation

G G

I. M, Q M C

tion dependent and can eff ortlessly change their place of resi-dence. Other independent variables are not of particular interest; however, they have a signifi cant impact altogether.

Therefore, the study yet again approved that math cannot solve issues pertaining to human behavior. Nor can it be assumed that by infl uencing certain variables it would be possible to keep the emigration under control. The emigration rate refl ects the overall socio-economic situation in the region. Consequently, it is needed to target each aspect of it. One could, therefore, be con-fi dent that economic incentive is not a push factor when choos-ing a place of residence.

R

. Russian Federal State Statistics Service — http://www.gks.ru

. Ovsiannikova, S. () Statistics: Student Book. Econ-form, Moscow.

On the uneven population density problems

E M, E S StudentsRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

S OAssociate Professor Russian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

A

As the title implies the article describes the uneven population density in the Russian Federation, the largest problem now aff ecting the world. The most essential factors on inequality distribution are clearly recognized and the most infl uencing factors are selected with the correlation analysis method. During the work, the regression power law model is formulated and the estimation of the sensibility of resulting sign with the modifi cation of factors is made. Moreover, the dynamics of the resulting indi-cation is investigated and the dependence on the most signifi cant factors is analyzed. Finally, at-tempts are made to give a recommendation on how to regulate the population density.

Key words: density of population, inequality, correlation analysis, regression analysis, the Rus-sian Federation, socio- economic determinants

I. M, Q M C O

I

Each unit of land has limited capacity to support people living on it. Hence, it is necessary to understand the ratio between the numbers of people to the size of land. This ratio is the density of population. It is usually measured in persons per km.

PopulationDensity of Population=Area

R

The population density of Russia in made up . people per km. If we compare the average Russian indicator with (. people per km), it can be concluded that in all regions of the Russian Federation the population density grew by . people per km. According to forecasts, in the average population density of the Russian Federation will be . people per km. During the population density is expected to be increased by ,% in the Russian Federation.

The population of the Asian part of Russia is peo-ple, and people live in its European territory. The shortage of people in the Asian part of Russia aff ects the small cities as well as huge cities growth.

Even if we take into account that about % of Russian lands are unfavorable for permanent life, the remaining % is about million km, where more than % of the population of Russia lives, is unevenly developed. In the most densely populated fed-eral districts — Central and North Caucasus — the population density is at least twice lower than in the EU ( people per km), roughly corresponding to the population density of North-ern Europe ( people per km).

The European part of the country as a whole may be compared in terms of population with the United States ( people per km), and the Asian — with Australia and Canada (about people per km). Almost half of the inhabitants of Russia live in two federal districts — Central and Volga Federal regions, and less than % of the population live in the Far Eastern and Siberian districts (/ of the territory of Russia).

The demographic potential of Siberia and the Far East is clearly insuffi cient for the development of the natural resourc-es located here and the creation of a developed, continuous eco-nomic and settlement structure. In addition, the population of the Asian part of Russia decreases even faster, and in – it grew more slowly than the entire country, which also refl ects the general limitations of the Russian demographic potential. In the internal Russian migration fl ows, the so-called “western drift” has formed, the population is shifting to the west of the country.

Population density depends on many factors that characterize the socio-economic sphere, the health care system, and the en-vironment. For the study based on logical analysis, factors were preliminarily selected that could potentially aff ect popula-tion density in the regions of the Russian Federation. After that, the correlation model was formed in order to select the most in-fl uential factors. Consequently, in the regression model were in-cluded such factors as:

• Number of victims in the road traffi c accidents for thou-sand people (X)

• The average cost of one square meter of housing (X)• Inequality coeffi cient Gini(X)• Life expectancy (men)(X)• Life expectancy (women)(X)• The average monthly income (X)

T

Y X X X X X X

Y

X -,

X , -,

X , -, ,

X , -, , -,

X , -, -, -, ,

X , -, , , -, -,

I. M, Q M C O

As can be seen from the table, there is a correlation between the pairs of the studied measure, and the nature of all the iden-tifi ed links is diff erent and consists of the following:

• Communication “Population density” — “The number of people injured in road accidents per thousand people” is noticeable (according to the Cheddoc scale) and reverse, that is, with an increase in population density, the number of people aff ected in road accidents decreases.

• Communication “Population density” — “The average cost of m of housing” is high and direct, that is, with an in-crease in population density, the average cost of m in-creases.

• Communication “Population density” — “Gini wage ine-quality ratio” is noticeable and direct, that is, with an in-crease in population density, the wage inequality ratio in-creases.

• Communication “Population density” — “Male life expec-tancy” is noticeable and direct, that is, with an increase in population density, male life expectancy increases

• Communication “Population density” — “Per capita income” is moderate and direct, that is, with an increase in popula-tion density, per capita income increases.

Furthermore, the regression analysis was put into practice due to determination of analytical expression of resulting indicator re-lation’s with factors. To a high accuracy, the multitude regression as well as paired were investigated. From the data obtained, an equation was derived describing the relationship between the re-sultant feature and the factors, which took the following form:

13 3 31 2 3

13 34 5 6

0,0001 0,003 462,09

10134,71 32,72 1,37 3800,8

Y X X X

X X X

The results of regression statistics were generated (Table ), these results correspond to the following statistical indicators: the coeffi cient of multiple correlation R = .. This indicator in-dicates a close relationship of features in the equation. The coef-

fi cient of determination R = ., which indicates that in % of cases, the change in population density can be explained by a change in the factors included in the model.T

Regression statisticsMultiple R ,R ,Adjusted R ,Standard Error ,Observations

Each indicator has an impact on the resultant feature. To as-sess this eff ect, the values of each factor were individually re-duced (Table ) and increased (Table ) within the standard de-viation by % with all other conditions being equal. Thus, as each factor increases and decreases, the resultant attribute will increase by the following values:T

Decreasing of the factors by % other factors being equal

Changing Y

X–% ,%X–% ,%X–% -,%X–% -,%X–% -,%X–% -,%

T

Increasing of the factors by % other factors being equal

Changing Y

X+% -,%

X+% -,%

X+% ,%

X+% ,%

X+% ,%

X+% ,%

Therefore, the greatest impact on the performance of the re-sulting indicator has the following factors: per capita income and

I. M, Q M C O

the number of victims of road accidents per one hundred thou-sand people. With a decrease in per capita income by %, the population density decreases by .%, in quantitative terms — people. With an increase in per capita income of %, the popu-lation density increases by .%, in quantitative terms — peo-ple. With a decrease in the number of injured in road accidents by %, the population density increases by .%, in quantita-tive terms- people. With an increase in the number of injured in road accidents by %, the population density decreases by .%, in quantitative terms- people.

At the fi nal stage, an analysis of time series was conducted, where the relationship between population density and average per capita income in Moscow and the Chechen Republic was in-vestigated. At the fi rst stage, time series of baseline data were built, a close relationship was found between the resultant indi-cator and a factor, which was confi rmed by a high coeffi cient of determination.

In addition, the change in the eff ective attribute in Moscow and the Chechen Republic since was studied. According to the obtained data and trends, it is possible to reveal the fact that there is a general trend towards an increase in population densi-ty in the Russian Federation.

C

Summing up, the population of Russia is unevenly distributed across the territory. The overwhelming majority of the Russian population — percent — live in the so-called “main settlement zone” of about a third of the country’s territory.

Uneven population density is caused by a number of interre-lating factors: social, demographic and economic. It should be noted that the uniform allocation of the population on the terri-tory of the constituents entities of the Russian Federation is im-possible. Low average income, lack of a developed transport net-work, lack of jobs makes some regions of the Russian Federation inaccessible for living.

For the attracting people to the constituents entities of the Russian Federation with the least density, the level of the income should be increased, since the resulting indicator is most re-sponse to the per capita income. Furthermore, it is essential to improve the quality of roads in order to prevent population from road traffi c accidents and, as a result, decrease number of victims.

R

. Ovsiannikova S. N. Econometrics. A study guide for students of the nd year of special economic sciences. — M.: Business, – p.

F. . Changes of the population density and the average income in Moscow starting from

F. . Changes of the population density and the average income in Chechen Republic starting from

I. M, Q M C

. Stokols, D. ‘On the distinction between density and crowding: Some implications for future research’, Psychological Review, vol , no , pp–

. Kremer N. Sh. Econometrics: Textbook for universities. — M.: UNITY-DANA, . — p.

. Ivanov Yu. N. Economic statistics. Moscow: INFRA-M, , p.

. Orlov A. I. Applied statistics / Orlov A. I. — Moscow: “Exam”, . . Statistical data: http://www.gks.ru/

. Estimated dynamic population density datasets. [Online]. Avail-able: https://zenodo.org/record/

Research on the number of orphans in the subjects of RFusing methods of econometric analysis

E B, D L, M ZStudents Russian Presidential Academy of National Economy and Public Administration Faculty of Economic and Social Sciences

S OAssociate Professor Russian Presidential Academy of National Economy and Public Administration Faculty of Economic and Social Sciences

A

In this article the analysis of the number of orphans in the regions of Russian Federation is provided. Based on the collected statistical data by the meth-ods of correlation and regression analysis, a linear multivariate model was built. The factors that have the strongest impact on the resulting factor are re-vealed. Moreover, a dynamic model of the relation-ship between the resulting factor and the most sig-nifi cant factor was developed. A dynamic seasonal-ity model was created for the selected factor. According to the results of the study, recommenda-tions are made to take into account signifi cant fac-tors that aff ect the number of orphans.

Key words: orphans, regression and correlation analysis, time series

I. M, Q M C R RF

I

Social protection of orphans and children left without parental care is one of the most important tasks of the state and society. Most orphans are unable to successfully adapt to life and solve many problems, as well as experiencing great diffi culties with employment, housing, arrangement of their life, preparation and observance of the budget, defending their legal rights.

The problem of orphan hood can be caused by the diffi cult economic situation in families, demographic factors, such as birth rate and age composition of the population of the region. In regions with a higher birth rate and a correspondingly higher proportion of children, social norms can be more focused on the education of children, for example, unemployed women who are raising children are more respected in society. Presumably, the level of divorce in the region is signifi cant, because it is easier to raise children in full families. The problem of orphanhood can also be caused by the lack of social infrastructure. The regional legislation that regulates the issues of child abandonment also has a signifi cant impact as well as the policies and motives of bodies of guardianship.

C

To conduct the study, an econometric model was compiled on the basis of open data classifi ed by the subjects of the Russian Feder-ation, where the number of orphans and children left without pa-rental care under the age of years (Y) acted as a resulting factor. As the factors were taken: the population (X); the number of un-employed (x); the population with monetary income below the subsistence minimum (X); the number of births(X); the number of divorced people (X); the number of crimes committed against minors(X); the number of bachelors, specialists, masters(X); the number of pre-school educational institutions(X); monthly child support (guardianship, foster family)(X); the number of chil-dren’s hospitals (X); the number of children (– years) with cerebral palsy(X); the number of guardianship authorities (X); the number of adults with mental and behavioral disorders (X).

YY

X

,

X

,

,

X

,

,

,

X

,

,

,

,

X

,

,

,

,

,

X

,

,

,

,

,

,

X

,

,

,

,

,

,

,

X

,

,

,

,

,

,

,

,

X

-

,

,

-

,

-,

-

,

,

-

,

,

-

,

X

,

,

,

,

,

,

,

,

,

-,

X

,

,

,

,

,

,

,

,

,

-

,

,

X

,

,

,

,

,

,

,

,

,

-

,

,

,

X

,

,

,

,

,

,

,

,

,

-,

,

,

,

F

. . C

orre

lati

on m

atri

x

I. M, Q M C R RF

The correlation matrix is constructed (Fig. ). Factors X, X were excluded due to too low correlation coeffi cient. In order to get rid of multicollinearity factors X, X, X, X were removed, since the correlation between them is bigger than with the re-sulting factor. Next, the factors that demonstrate the strongest relationship with the resulting factor were selected: X, X, X, X.

The tool of Excel “Regression” was used to build a multiple lin-ear regression model. The equation of regression dependence has the form:

Y= –, + .x + ,x + ,x + ,x

Standardized coeffi cient of determination of the model: R= .. Thus, about % of the variation of the dependent vari-able (number of orphans) in the constructed model is due to the infl uence of the included factors X, X, X, X.

The signifi cance of the regression equation based on Fisher’s F — test is verifi ed. Ffact =.. The tabulated value F — test is Ftable =,. Considering Ffact>Ftable., then the model should be considered meaningful.

The signifi cance of the regression equation coeffi cients a, a, a, a was estimated using Student’s t-test: ta=, ta=, ta=, ta= ,.

The tabulated value of Student’s t-test is ttable = ,. As tfact>ttable, the hypothesis of statistical insignifi cance of the coeffi -cients of the regression equation a, a, a, a is rejected.

However, directly using regression coeffi cients, it is impossi-ble to compare the factors by degree of infl uence on the depend-ent variable due to the diff erence in units of measurement. To eliminate these diff erences, elasticity coeffi cients were used.

E= , E =, E = , E = ,.Thus, if the number of unemployed persons changes by %, the

number of orphans will change by approximately .%; if the number of crimes committed against minors changes by %, the number of orphans will change by approximately .%; if the number of children (– years) with cerebral palsy changes by %, the number of orphans will change by approximately .%; if the number of adults with mental and behavioral disorders

changes by %, the number of orphans will change by approxi-mately .%.

Summarizing the analysis, it should be noted that the use of correlation and regression analysis allows to fi nd the best ways to solve the problem of orphan hood in Russia. The constructed linear model revealed and proved the importance of the studied factors. The most signifi cant factor requiring the attention of the state in order to reduce the number of orphans is the number of crimes committed against minors. Also, the state should pay at-tention to the health aspects, as they are signifi cant barriers in working with the identifi ed problem. It is noteworthy that ac-cording to the results of the correlation analysis, economic fac-tors are insignifi cant in determining the state of orphan hood in the subjects of the Russian Federation.

A

The relationship is described between the resulting factor above (Y) and one of the factors included in the model, which change over time (–). The number of unemployed persons was taken as a factor (X). Sverdlovsk region was chosen for the study of time series because of the outstanding indicators.

Building a model of the relationship of time series is carried out by correlation and regression analysis. However, the applica-tion of this method will not allow to obtain correct results due to the specifi city of time series.

Each level of the time series contains three main components: trend (T), seasonal component (S) and random component (E). When checking for a relationship between two time series, the possibility of a false correlation showing that a relationship ex-ists when it does not exist should be considered.

At the preliminary stage, seasonal fl uctuations should be ex-cluded. Applied approach: the calculation of the values of the seasonal component should be done by the method of moving average and creating the additive and multiplicative models (Fig. ).

I. M, Q M C R RF

F. . Seasonal component

Number of unemployedSeasonal componentjanuary ,february ,march ,april ,may ,june ,july ,august -,september -,october -,november -,december -,

The dynamic series of the seasonal component was approxi-mated by Fourier series, which led to the detection of noticeable periodic fl uctuations (Fig. ). Furthermore, we can say that the repetition of processes occurs approximately every periods. This distribution of seasonal components allows to make a con-clusion about the presence of a clearly expressed seasonal unem-ployment.

According to the created additive model based on the data cleared of the seasonal component, and the identifi ed trend, it is possible to predict the number of unemployed (Fig. ).

According to calculations, there is a falling trend (Fig. ).F. : Forecast of the number of unemployed in

Forecast of the number of unemployedjanuary ,february ,march ,april ,may ,june ,july ,august ,september ,october ,november ,december ,

Further, to analyze the relationship between the studied time series, the method of regression analysis was used (Fig. ).

Normalized coefficient of determination of the model is: R=,. Thus, only in % of cases the change of the result-ing factor is explained by changes of factors included in the model.F. . Dynamic series

tNumber of orphans Number of unemployed

У Х F. . Graph of seasonal component

F. . Additive model of the number of unemployed

-4000

-3000

-2000

-1000

0

1000

2000

3000

0 2 4 6 8 10 12 14

Seasonal component

Series1 Fourier series

y = 0,001t4 - 0,620t3 + 81,41t2 - 4037t + 96099R² = 0,977

0100002000030000400005000060000700008000090000

100000

0 20 40 60 80 100 120

Additive model

Series1 Полиномиальная (Series1)

I. M, Q M C

tNumber of orphans Number of unemployed

У Х

R

On the basis of the work done, it is possible to give some recom-mendations aimed at reducing the number of orphans. The state should consider strengthening the law on domestic violence to en-sure the safety of children in the home environment and to pre-serve their mental and physical health. It is also promising to in-troduce additional loyalty programs for adoptive parents/guardi-ans of children with serious diseases. In addition, raising public awareness of the availability of psychological support services through the media, the Internet and other information channels can have a positive impact on reducing the number of orphans.

R

. Family code of the Russian Federation of .. № -FZ (the last edition from ..).

. Levina, I. A. (). The problem of orphan hood in Russia: anal-ysis of cultural, economic and political aspects.[Online]. Available at: http://pe.cemi.rssi.ru/pe___–.pdf.

. The administration of the Bokovskiy district of Rostov region. (). Social orphan hood as a social problem. [Online]. Available at: http://bokovskaya.donland.ru/EventScheduler/EventSchedul-erViewPost.aspx?pageid=&ItemID=&mid=.

. gks.ru — offi cial website of the Federal state statistics service.

. sverdl.gks.ru — offi cial website of the Federal state statistics service of the Sverdlovsk region and Kurgan region.

Expected life expectancy and factors aff ecting it

A T, A СStudentsRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

S OAssociate Professor Russian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

A

In the article on the basis of statistics of indicators of life expectancy in regions of Russia the law of dis-tribution of probabilities of values is constructed. An assessment of averages and dispersion around an average by years is given. The factors modeling the received values for diff erent regions are analysed. On the basis of the selected factors by methods of the correlation and regression analysis constructed multiple-factor nonlinear model. The analysis of the constructed model revealed the most signifi cant factors aff ecting life expectancy. An assessment of sensitivity of eff ective sign to changes of factorial signs is given. The most signifi cant factor aff ecting average life expectancy was analysed in dynamics.

I. M, Q M C E

Existence of seasonality is revealed and values of the research data for the next period are predicted. In the work the tendency to increase life expectancy in the Russian Federation in various regions with diff erent rates is revealed.

Key words: correlation matrix, eff ective sign, factorial signs expected life expectancy, regression model

I

Life expectancy (LE) is one of the key indicators for assessing the level and quality of life of people. Life expectancy is examined from various perspectives, including such areas of life as medical, social, economic, and many others. The factors aff ecting the life expectancy of the population by regions of the Russian Federa-tion were selected: average monthly wages, population morbidi-ty, weather conditions, mortality, emissions of pollutants into the atmosphere, the ratio of men and women, food consumption (meat, eggs, vegetables and melons, milk, sugar and bread), the number of people with higher education, the incidence of obesi-ty and the use of strong alcoholic beverages.

R

In the course of the study, a correlation matrix was constructed, with the help of which the interrelations of the eff ective and fac-tor signs were revealed (Table ).

To build the model, factors having a weak correlation with the resultant attribute (less than .) were excluded. To exclude mul-ticollinearity, factors out of originally selected were includ-ed in the model.

Below is a brief description of the factors included in the model.

. The average monthly salary (x), which is an economic characteristic.

. Incidence (x) as the main characteristic of health care is also inextricably linked with LE. It should be noted that this factor has a high correlation with the consumption of veg-etables and melons and gourds. So, by increasing their in-

take of these foods, people will be able to lead a healthier lifestyle and stick to a healthy diet.

. The incidence of obesity (x) is inversely related to life ex-pectancy, which again proves that people’s health is inex-tricably linked to nutrition.

. Air emissions of pollutants (x). The relationship of this factor with the resultant attribute explains how important it is to take care of the environment in order to maintain a high quality of life of the population

. The ratio of women to men (x) was examined in a study in each region of Russia, as a result of which it was noted that women live longer than men. This issue at-tracts many scientists interested in studying the factors aff ecting life expectancy. However, the diff erence in the life expectancy of men and women remains stable to this day.

. Consumption of food (x, x, x). It is worth noting that

T . Correlation matrix

Y (Life Expectancy)Y (Life Expectancy) x (Average Salary per month/roubles) ,x (Morbidity rate among people per year) -,x (Average Weather) ,x (Mortality Rate) -,x (Emissions of pollutants in the atmosphere/rainfall) -,

x (Number of Women to men) ,x (Consumption of meat pet year/kg) ,x (Consumption of eggs per year/kg) -,x (Consumption of vegetables and melon crops per year/kg) ,

x (Number of people with higher education per year) ,

x (Consumption of sugar per year/kg) ,x (Consumption of bread per year/kg -,x (Consumption of vegatable oil per year/kg) -,x (Number of obesity desease among people per year) -,

x (Consumption of strong alcoholic beverages per year/litre) -,

x (Consumption of milk per year/litre) ,

I. M, Q M C E

the study analyzed the consumption of food products that form the consumer basket of a person, which indicates the close relationship of these factors among themselves. Each product is useful in its own way and harmful in its own way. For example, milk is a unique product in which proteins, fats and carbohydrates are perfectly balanced. As for meat, this product contains amino acids that contribute to the ac-tive work of the body, proteins, fats and carbohydrates, and % consists of water, but scientists often say that red meat is harmful to human health and advised to exclude this product from the diet in order to maintain proper power supply.

. Consumption of strong alcoholic (x) drinks. Based on the correlation matrix, high alcohol consumption aff ects the health of the population, because the more people drink al-cohol, the lower their life expectancy and the higher their incidence.

Using the regression analysis method, a linear model was ob-tained.

у=,+,х–,х–,х+,х+,х––,х–,х+,х

The quality of the model was verifi ed using the following factors (Table ):T . Regression statistics

Regression StatisticsPlural R ,R-square ,Normalized R-square ,Standard error ,Observations

The coeffi cient of determination is %. This means that in % of cases, the resultant feature can be described as a change in factor characteristics. The Fisher coeffi cient (F value) is equal to ., which suggests that this model is signifi cant and de-scribes the resulting relationship better than the average.

D

The study shows the dependence of life expectancy in Russia on the consumption of strong alcoholic beverages (Fig. ).

So, during the analysis of data of time series, the presence of seasonality was revealed. Analysis of the seasonal component showed a reduction in the consumption of alcoholic beverages in the fi rst three quarters compared with the trend, and in the fourth quarter, the demand for alcoholic products is growing in anticipation of the New Year holidays in Russia.

quarter -, quarter -, quarter -, quarter ,

Moreover, the dependence of the studied time series was iden-tifi ed with a one-year lag, which means that the consumption of alcoholic beverages in the previous period has an impact on the expected life expectancy in a future period.

X-consumption of strong alcoholic beverages

y = -0.0399t2 + 0.1726t + 14.965R2 = 0.9762

1816141210

86420

0 2 4 6 8 10 12 14 16 18

y = -0.616t + 62.054R2 = 0.8848

Y-life expectancy

0 2 4 6 8 10 12 14 16 18

8070605040302010

0

F.

Additive Model

y = -0.0007t2 + 0.0106t + 3.7367R2 = 0.9473

5

4

3

2

1

00 10 20 30 40 50 60 70 80

F.

I. M, Q M C

y/х — the deviation of the empirical data from the theoreti-cal, since a linear trend was identifi ed.

C

Thus, based on the study, it was possible to predict life expectan-cy and alcohol consumption so that LE will be . years, and alcohol consumption will be reduced to litres per year per cap-ita.

R

. Ovsiannikova S. N. Econometrics. A study for students of the nd year of special economic sciences. ()

. Federal State Statistics Service [electronic resource], URL: http://www.gks.ru/

. Federal Statistics [electronic resource], URL: https://fedstat.ru/indicator/

. Statistics for Russia [electronic resource], URL: https://russia.duck.consulting/

Lag in 1 year

y = -0.03876Ex + 0.2029R2 = 0.1382

1,5

1

0,5

0

-0,5

-1-0,8 -0,6 -0,4 -0,2 0 0,2 0,4 0,6 0,8 1 1,2

F.

Analysis of generation Z life satisfaction

E A, V G, P ZStudentsRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

S O Associate Professor Russian Presidential Academy of National Economy and Public Administration Faculty of Economic and Social Sciences

AThis research work includes analysis of the factors that aff ect life satisfaction of people aged between and . Statistics were gathered from the results of the questionnaire and the most relevant factors were assessed using correlation analysis methods. A linear regression model that describes eff ective feature was created. The sensitivity of the re-searched objects which are included in the model was assessed. Interrelationships among determi-nates were analyzed. Recommendations and correc-tion values of variables that have an impact on the life satisfaction decrease were also provided.

Key words: generation Z, life satisfaction

I. M, Q M C A Z

I

Obviously, one of the most important aspect of rapidly develop-ing society is life satisfaction. Making political, economic, social forecasts a lot of attention should be paid to the public sentiment. That is why nowadays the score of life satisfaction is an essential issue to focus on, this score is aff ected by diff erent social factors.

This research work includes analysis of the correlation be-tween life satisfaction (rated on a scale of to ) and the factors that can aff ect it.

D

Questionnaires included diff erent social topics were prepared by our team and mostly distributed between bachelor and master stu-dents of Moscow (aged between and ). Thus, statistics of dai-ly life, hobbies, entertainment of this focus group were gathered.

The model included questions.

D S

Having collected the data and having completed comparative as-sessment some factors were eliminated by analyzing the pair cor-relation coeffi cients.

The factors having correlation coeffi cient in absolute value less than . were eliminated. Thus, there were factors left that had the strongest connection with the performance indicator (with the assessment of life satisfaction rated on a scale of to ). There were such factors as: “number of trips per year”, “the number of days spent traveling per year”, “the number of hours spent on sports per week”, “amount of time spent on friends per week”,

“regularity of social events”, “the number of hours spent on com-puter per day “ and “the number of hours spent sleeping”.

D

А multivariate model was chosen in this study.Model type selection:

The analysis of the matrix of pair correlation coeffi cient showed that the dependent variable, i. e. the level of life satisfac-tion has a close relationship with:

• how often people travel: the correlation coeffi cient of X = .;• how many days a year a person spends traveling: the corre-

lation coeffi cient of X= .• how much time is spent on the computer (inverse relation-

ship): the correlation coeffi cient of X = .• how many hours a person sleeps per day: the correlation

coeffi cient of X = .

Factors X and X are closely related: rXX = ., this indicates about the collinearity, therefor, just one of these two variables — X (the number of trips per year) was left.

The coeffi cient . demonstrates how variable X infl uenc-es Y. That is, the number of trips per year within this model af-fects the life satisfaction with a weight of .; dependence is di-rect — the more a person travels, the happier he/she is.

The inverse relationship was identifi ed in relation to the time spent on the computer: –.. The more time a person spends at the computer, the less he/she is satisfi ed with life.

Having analyzed the linear, polynomial, logarithmic depend-ence, it was found that the linear model is the most suitable, so a linear equation was used.

• Multiple correlation coeffi cient is ..• The coeffi cient of determination is .. This means that

calculated parameters of the model explain the relationship between the studied parameters by %.

Y X Y X

X . X . X . . X . .X -. . X -. .X -. -. X -. -.X . . X . .X -. -. X -. -.X . . X . .

P. Pic.

I. M, Q M C A Z

A test was performed using the signifi cance of “alpha” with an approximate value of .; this shows that a stable depend-ence between the function and the factors is in-deed detec ted.

Based on the least squares method, the regression parameters were estimated using the formula:

Y = . × X–. × X + . × X + .

Where: X — the number of trips per yearX — amount of time spent at the computerX — amount of time spent sleepingAlso, considering the pairwise dependencies between the fac-

tors, a few interesting relationships were identifi ed, such as:

• the amount of alcohol consumed directly aff ects the num-ber of cigarettes smoked .

• the number of friends that people have on social networks does not aff ect the number of friends who they communi-cate in real life with ..

C

The study examined a fairly big number of social factors, but upon further analysis it was revealed that only a few of them have a signifi cant eff ect on life satisfaction. We list them: “the number of trips per year”, “time spent sleeping”, “time spent at the computer”.

Interesting dependencies between the factors were also re-vealed, such as: the eff ect of the amount of alcohol consumed on the number of cigarettes smoked; lack of infl uence of the num-ber of friends in social networks on the number of friends who people communicate in their real life with.

R

. Michael R. R. Berthold (Author), Christian Borgelt (Contribu-tor), Frank Höppner (Contributor) Guide to Intelligent Data Analysis: How to Intelligently Make Sense of Real Data. -nd edition pub. Germany: Springer, .

. Thomas Hills University of Warwick Eugenio Proto University of Warwick, CAGE and IZA Daniel Sgroi University of Warwick, CAGE Historical Analysis of National Subjective Wellbeing. Ger-many: IZA, .

. What’s the secret of life satisfaction? // www.bbc.com/news/business- URL: https://www.bbc.com/news/busi-ness- (date of the application: ..).

Regression statisticsMultiple R .R — squared .Normalized R-squared .Standard mistake .

P.

A

A multifactor analysis of fl u incidence

P G, P TStudentsRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

S O Associate ProfessorRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

A

The article deals with the problem of fl u on the ter-ritory of the Russian Federation. The most signifi -cant factors having impact on fl u incidence rate are as follows: the number of people using public trans-port, the number of autoimmune diseases per people, an average temperature, an average humid-ity, cost of lemons per kg.

We constructed a multiple regression model of fl u incidence rate and tested its statistical signifi -cance. The eff ect of the seasonal component on the number of fl u patients and the relationship of the investigated trait with the average of air tempera-ture in the territory of the Russian Federation is

shown. Data were taken monthly date in the period from to . Constructed equation for correlation of dynamic series al-lows to predict the level of fl u patients in the following periods based on the factors score, included in the model.

Key words: incidence of ARVI and infl uenza, Russian Federa-tion territory, regression analysis method, linear model, the in-fl uence of each selected factor on the resultative feature, season-al factor, dynamic series.

D

The purpose of this project is to identify factors that have an im-pact on the response variable namely incidence of ARVI and in-fl uenza in the regions of Russia. According to calculations, the total number of infected during the past year was .

Incidence of ARVI and infl uenza is one of the most common problems during the whole year, which covers most of the popu-lation and prevents people from living a normal life.

This problem is related to the fact that the working capacity of the population during the periods of epidemics falls dramati-cally and this eff ects on the economic situation of the country as a whole.

This research is relevant, since a qualitative analysis is likely to reduce the number of infected.

Data were collected for subjects of the Russian Federation and factors were selected:

• Average salary (х);• The number of people using public transport (х);• The number of medical workers per , people (х);• The number of pregnant womenн (х);• The number of autoimmune diseases per , people

(х);• Average air temperature (х);• Average air humidity (х);• The cost of lemons per kg (х);• Average annual rainfall (х).

All data were taken for .

I. M, Q M C A

T

YY X ,X ,X ,X ,X ,X ,X ,X -,X ,

The analysis of the correlation matrix allowed to identify factors that have the greatest interconnection with the response variable, these are factors Х, Х, Х, Х, Х. The remaining fac-tors were removed because they have a weak correlation with the response variable. During the analysis, the multicollinearity of factors X and X (.) was revealed. In this regard, one of the factors, namely X, was excluded from the model.

This interconnection can be explained by the fact that with in-creasing birth rates, the number of people using public transport also increases.

In addition to the above factors, factors that show the number of medical workers per , people (correlation coeffi cient .), average salary (correlation coeffi cient .), average annu-al rainfall (mm) (correlation coeffi cient .) were also not in-cluded in the model. They were removed from the model due to a weak interconnection with the response variable.

The fi nal model includes factors, each of which is closely re-lated to the response variable.

For further research use the tool “Regression”.T

Regression statisticsMultiple R ,R square ,Adjusted R square ,Standard Error ,Observations

A linear model was constructed, because the multiple correla-tion coeffi cient is ..T

Coeffi cientsY -,Х ,Х ,Х -,Х ,Х -,

Based on the values of the coeffi cients, presented in Table , the equation of linear multiple regression is derived:

Y = .*X + .*X + .*X – .*X – .

The response variable equation shows the relationship between the selected factors, namely the number of people using public transport, the number of autoimmune diseases per , pop-ulation, average temperature, average humidity, cost of products improving immune system

Based on the data obtained in the model, follows these con-clusions:

• If the values of factor X (the number of people using public transport) change by unit, the response variable Y (the num-ber of people with ARVI and infl uenza) changes by . units.

• If the values of factor X (the number of autoimmune dis-eases per , people) change by unit, the response v ariable Y changes by . units.

• If the values of factor X (average temperature) change by unit, the response variable of Y is ,. units.

• If the values of factor X (average humidity) change by unit, the response variable Y changes to . units.

• If the values of factor X (cost of lemons per kg) change by unit, the response variable Y changes by . units.

Based on the values of the coeffi cient of determination (R-square), it can be argued that in % of cases a change in the response variable is due to variations in the selected factors.

I. M, Q M C A

To identify the infl uence of factors, standardized coeffi cients were calculated.T

Regression statisticsMultiple R ,R square ,Adjusted R square ,Standard Error ,Observations

T

Coeffi cientY-intersection ,X” ,X’’ -,X’’ -,X’’ ,X’’ -,

While comparing standardized coeffi cients, was found that the number of people using public transport has the greatest impact on the number of people with ARVI and infl uenza, due to the fact that it signifi cantly exceeds the remaining indicators.

In addition, trend lines were constructed to describe the patterns contained in investigated time series. Modeling trend and function parameters were determined using the least squares method, where time (months from to ) was used as an independent vari-

able, and actual levels of time series y (the number of cases) and x (air temperature) were used as the dependent variable.

Fig. shows the result of trend building y = .x–.x + and trend forecasting for the time series “The incidence of ARVI and Infl uenza”. A second-order polynomial, a parabola, was chosen as the approximating function, using which the predic-tion was made two steps ahead. The value of the coeffi cient of determination is R = ., which indicates that a small fraction of the variation of the attribute Y is taken into account in the model. While studying the graph, it was found that the largest surge of diseases falls to January-March, then the data stabilize.

Also an analysis of the infl uence of the seasonal factor on the number of infected with ARVI and infl uenza throughout Russia for – was made.

For a more accurate analysis, data for this period were taken by month.

Smoothing of values was performed using the moving average method. As a result, smoothed levels were obtained, refl ecting real indicators with a canceled eff ect of seasonality.

The following conclusions were highlighted, based on the sea-sonally adjusted data in Table :

. Every year in the period from May to November there is a stagnation of indicators. The number of cases does not ex-ceed the norm.

y = 22,759t2 - 1169,3t + 16350R = 0,165

0

10000

20000

30000

40000

50000

60000

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37

F.

y = -5210,1t + 23850R = 0,2612

y = 89,238t + 4447,8R = 0,5059

y = -2474,7t + 40247R = 0,5904 y = 94,39t + 3220,6

R = 0,4668

y = -2222,4t + 56244R = 0,9997

y = 3825t - 93889R = 0,9974

y = -269,35t + 13881R = 0,6058

y = 1516t - 54307R = 0,9931

0

5000

10000

15000

20000

25000

30000

35000

0 5 10 15 20 25 30 35 40 45

F. . The number of infected with ARVI and infl uenza

I. M, Q M C A

. The period from January to April indicates that among the population of Russia there is a clear deviation from the norm.

T

, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

T

Fall interval Fall rate Growth interval Growth rateFall interval Fall rate -, Growth interval -, , Growth rate -, -, -,

Next task of our research was to fi nd out whether the subse-quent prediction of the number of cases is possible. This decision was made because the general nature of the processes is not de-scribed by a single trend and because of this we could not make a prediction. Thus, based on the correlation matrix derived in Ta-ble , it is possible to draw the following conclusions:

. Intervals of falling and growth rates have a high inverse relationship between themselves, that is, the greater the growth rate of the diseased is, the lower is the interval of falling and vice versa. The longer the recovery interval, the slower people get sick

. The growth interval and the growth rate of patients have an inverse relationship, that is, the incidence rate is re-cruited in a shorter period.

. The rate of fall and the interval of fall are in inverse rela-tionship with each other, that is, the longer the period of decline in incidence, the faster people recover.

. Growth intervals and rates of fall have a high direct rela-tionship between themselves, that is, the longer the inci-dence interval, the faster people fall ill

Thus, having the data of the next period at a turning point, it is possible to predict the rate of change of the value and the peri-od of time during which this occurs.

To identify the dependence of the infl uence of the average temperature on the number of infected with ARVI and infl uenza, an analysis, which showed a high correlation and the inverse de-pendence of time series, was carried out.

For further analysis, the number of infected with ARVI and in-fl uenza was indicated as Y, and the average temperature — as X.T

x yx y -,

Table shows the correlation of the dynamic series, the result of which was the conclusion that with an increase in the average

y = -530,75x + 6526,6R = 0,1949

-10000

0

10000

20000

30000

40000

50000

60000

-15 -10 -5 0 5 10 15 20

F.

I. M, Q M C A

monthly air temperature, the number of infected becomes less and vice versa. This dependence is manifested in % of cases.T

Regression statisticsMultiple R ,R square ,Adjusted R square ,Standart Error ,Observations

T Coeffi -cient

Standard error

t-sta-tistics

P-valueLower %

Top %Lower ,%

Top ,%

Y-inter-section

, , , , , , , ,

t -, , -, , -, -, -, -,

x -, , -, , -, -, -, -,

Dynamic Series Relationship Equation: y=,–,x-t

C

Thus, based on the results of the study, it was found that the use of people by public transport has the greatest impact on the number of people with infl uenza and ARVI in the regions of Rus-sia. These diseases are transmitted by airborne droplets, and in public transport people have constant contact with others, in-cluding those, who are sick.

Such factors as the number of autoimmune diseases per , people, the average air temperature, the average air humidity, and the cost of lemons per kg have a lower impact on the num-ber of infected. The lowest infl uence on the response variable has a factor that shows the average humidity of the air, other factors have an equivalent eff ect on the number of people who have fl u and ARVI in Russia.

It is worth noting that the largest number of infected were found in Moscow, Moscow Region, St. Petersburg, the Republic of Tatarstan, the Sverdlovsk Region and the Chelyabinsk Region.

To reduce the infl uence of these factors on the response vari-able, conclusions were made on the following measures:

. Hand disinfection after being in public transport. Wearing a protective mask for the sick to prevent airborne

transmission of the disease to other citizens.. If possible, greater use of personal transport. Lower prices for citrus products during epidemics. Active use of agents that increase immunity at a time

when the air temperature is low and its humidity is high.. Vaccination of people with anti-fl u drugs. Reducing the price of vitamin preparations

R

. https://www.rosminzdrav.ru

. http://rospotrebnadzor.ru/activities/statistical-materials/

. http://ab-centre.ru/news/ceny-na-l imony-v-rossi i-v--godu-dannye-na-oktyabr

. https://russia.duck.consulting/maps//

. http://investorschool.ru/srednyaya-zarplata-v-rossii-po-re-gionam-v--godu

A

Analysis of the factors infl uencing life expectancy

V P, A SStudentsRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

S O, Associate ProfessorRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

A

The factors infl uencing life expectancy have been analyzed in this work. Correlation and regression analysis and the analysis of the relationship be-tween a dependent variable and independent varia-bles (suggested factors) have been conducted and the regression equation has been constructed to identify the main factors infl uencing the life expec-tancy. The level of signifi cance of the factors includ-ed in the multiple regression model has been esti-mated. The factors mostly infl uencing life expectan-cy have been identifi ed. The dependent variable has been considered in dynamics. The results for vari-ous countries have been compared and the reasons for the diff erences identifi ed have been analyzed.

Key words: life expectancy, correlation and regression analy-sis, multiple regression model, the level of signifi cance, correla-tion co-effi ciency.

R

Life expectancy considerably refl ects life conditions in a certain country. As for world statistics, Russia falls behind many devel-oped countries and the essential fact that should be paid attention to is that this gap does not narrow (project «The latest trends in demographic development of Russia and their consideration in so-cio-economic forecasting. According to the UN (), Russia is on the th position in the international life-expectancy ranking.

In addition to the macroeconomic indicator, it is essential to consider the situation within the country itself. Regarding Rus-sia, high intraregional diff erences can be noticed and, according to the data for , reach years.

The most positive trends can be noted for the Republic of the Northern Caucasus as well as for such huge cities as Moscow and Saint-Petersburg. At the top of the list is the Republic of Ingushe-tia with life-expectancy of , years on average. Nevertheless, a signifi cant number of the territories of the Russian Federation is characterized by rather low coeffi cients and the lowest of them equals to , and belongs to the Republic of Tuva.

The data collection and the analysis of the problems raised can be complicated by underreporting of deaths and the existence of religious and sociocultural traditions within each ethnic group.

Despite the fact that, according to the Max Plank Institute for demographic Research (“factors of life expectancy”) no factors were revealed except for hereditary ones that could have an im-pact on life expectancy, the consideration of the problem is still worth paying special attention to and additional research.

Hence, the identifi cation of the factors that infl uence life ex-pectancy rates most signifi cantly as well as the determination of the strength of relationship of the numerical factors with the re-sulting factor will give an idea of what measures can be taken in order to increase life expectancy rates in the Russian Federation.

In this research the factors aff ecting the average life expectan-cy in the regions of the Russian Federation were analyzed and the

I. M, Q M C A

assessment of the impact of each of them on the resulting factor was conducted.

In order to carry out the analysis of the reasons for such a sit-uation in Russia, factors were selected:

• factors — crimes of various severity levels• factors — diseases• factors — socio-economic factors• factors — ecology• factors — consumption of alcohol, tobacco and drugs

Furthermore, by using the method of correlation analysis, the factors that most strongly infl uence the dependent variable were selected. Multicollinearity was got rid of.

Hence, the following factors were left:

• x (the number of crimes of the second degree);• x (the number of alcohol addicts);• x (the number of people suff ering from tuberculosis);• x

(divorce rates);• x (the number of diseases revealed during pregnancy);• x (the number of minors (under-aged youngsters) having

suff ered from criminal actions)

Other factors were not used for the reason of low correlation with the resulting factor (life expectancy) or for the reason of multi-collinearity.T . Correlation analysis

Y — average life expectancy

y — the average life expectancy x — the number of crimes of the second degree per population

-,

x–the number of alcohol addicts per population -,x–the number of people suff ering from tuberculosis per population

-,

x –divorce rates per population -,x –diseases revealed during pregnancy per population

-,

х — the number of minors having suff ered from criminal actions

-,

In the table there are coeffi cients of the relationship with life expectancy. They all have a negative sign, which indicates the ex-istence of an inverse relationship. The situation is entirely consist-ent with logical assumptions. Nonetheless, numerical confi rma-tions are required. Therefore, the next step is regression analysis.T . Regression statisticsSUMMARY OUTPUT

Regression statisticsMultiple R ,R-square ,Adjusted R-square ,Standard error ,Observations

ANOVA

df SS MS F Signifi cance FRegression , , , ,Residual , ,Total ,

Based on the data obtained, it can be concluded that the linea r model is working as the coeffi cient of determination equals to , R and shows that % of the variance in y is predictable form the selected factors. In addition, the diff erence between the coeffi cient of determination and adjusted coeffi cient of determination is not signifi cant, which also confi rms the viability of the model.T . Regression

Coeffi cients Standard error

t–statistics

P-Value

y–intercept , , , ,x –the number of crimes of the second degree

-, , -, ,

x–the number of alcohol addicts

-, , -, ,

x–the number of people suff ering from tuberculosis

-, , -, ,

х –divorce rates -, , -, ,х –diseases revealed during pregnancy

-, , -, ,


-, , -, ,

I. M, Q M C A

Hence, after making all the required calculations, the linear multiple model was constructed:

y=,–,х–,х–,х–,х–,х–,х

In order to exclude the probability of unnecessary factors being added to the model, a stepwise regression was made. With the addition of each successive factor all indicators improve, which means that all the factors considered have an impact on the de-pendent variable y.

SUMMARY OUTPUT х SUMMARY OUTPUT х, хRegression statistics Regression statisticsMultiple R , Multiple R ,R-square , R-square ,Adjusted R-square , Adjusted R-square ,Standard error , Standard error ,Observations Observations

SUMMARY OUTPUT х, х, х SUMMARY OUTPUT х, х, х, хRegression statistics Regression statisticsMultiple R , Multiple R ,R-square , R-square ,Adjusted R-square , Adjusted R-square ,Standard error , Standard error ,Observations Observations

SUMMARY OUTPUT х, х, х,х, х

SUMMARY OUTPUT х, х, х, х, х, х

Regression statistics Regression statisticsMultiple R , Multiple R ,R-square , R-square ,Adjusted R-square , Adjusted R-square ,Standard error , Standard error ,Observations Observations

In order to increase the accuracy of the research, it was decided to improve the model. The construction of the exponential model is impossible due to the presence of zeroes among the empirical data.

Therefore, it makes sense to create a mixed model. The next step is to determine the form of connection of the dependent variable (life expectancy) with independent variables (factors).

As the result of work with trend lines, it was found that factors and have logarithmic trend while all the remaining ones have linear trend.

In order to improve the model, the factors were logarithmed in accordance with the form of connection, regression analysis was conducted.T

SUMMARY OUTPUTRegression statisticsMultiple R ,R-square ,Adjusted R-square ,Standard error ,Observations

y = -0,4235x30 + 73,49R = 0,3945

60

65

70

75

80

0 5 10 15 20 25 30

x30

P

y = -0,1892x2 + 74,755R = 0,422

60

65

70

75

80

85

0 10 20 30 40 50 60 70

X2

P

I. M, Q M C A

Coeffi cients Standard error

t-statistics P-Value

y-intercept , , , ,

x- the number of crimes of the second degree

-, , -, ,

x-the number of alcohol addicts

-, , -, ,

x-the number of people suff ering from tuberculosis

-, , -, ,

х –divorce rates -, , -, ,

х –diseases revealed during pregnancy

-, , -, ,


-, , -, ,

It can be noticed that the coeffi cient of determination has in-creased in comparison with the linear model. Nevertheless, fac-tor x has P-value more than , which indicates the absence of statistical signifi cance.

Consequently, there necessity of including the factor into the model is questioned.

The, a stepwise regression was made in order to exclude the probability of adding unnecessary factors to the model.

SUMMARY OUTPUT х, х SUMMARY OUTPUT хRegression statistics Regression statisticsMultiple R , Multiple R ,R-square , R-square ,Adjusted R-square , Adjusted R-square ,Standard error , Standard error ,Observations Observations

SUMMARY OUTPUT х, х, х, х, х

SUMMARY OUTPUT х, х, х, х, х, х

Regression statistics Regression statisticsMultiple R , Multiple R ,R-square , R-square ,Adjusted R-square , Adjusted R-square ,Standard error , Standard error ,Observations Observations

SUMMARY OUTPUT х, х, х SUMMARY OUTPUT х, х, х, хRegression statistics Regression statisticsMultiple R , Multiple R ,R-square , R-square ,Adjusted R-square , Adjusted R-square ,Standard error , Standard error ,Observations Observations

y=,–,х–,х–,х–,lnх–,lnx–,x

As it can be noticed, with the addition of each subsequent factor both R and R improve, which means that all factors are impor-tant. Factor x also improves the model, therefore, it has not been excluded. In addition, the diff erence between R and adjust-ed R is not more than ,%, which also confi rms the effi ciency of the model.

Furthermore, the sensitivity analysis of the model was carried out. The average value of the data for each factor was taken. Then the value was increased by %, %, % and put into the mod-el in order to see how much the value of the resulting factor (life expectancy) will change.

Thus, analyzing the sensitivity of the dependent variable to fac-tor x (diseases revealed during pregnancy per population), it was noted that an increase in the value of the factors by % will lead to a decrease in the resulting factors by ,% and an increase of the same factor by % and % will lead to a decrease in the factor value of the resulting factor by ,% and % respectively.

As for the sensitivity of the resulting factor to factor x (the number of minors having suff ered from criminal actions), it was found that a change (increase) in the average value of the factors by %, % and % will lead to a decrease in the value of the resulting factor by ,%, ,% and ,% respectively.

Furthermore, the factors that have a linear relationship with the resulting factor were analyzed.

Thus, an increase in the average value of the factor x(the number of crimes of the second degree) by %, % and % will lead to a decrease in life expectancy by ,%, ,% and ,% respectively.

I. M, Q M C A

As for the factor х (the number of alcohol addicts), the in-crease in the value of the factor by %, % and % will lead to a decrease in life expectancy by ,%, % and % respectively.

When checking the sensitivity of the model to factor x (the number of people suff ering from tuberculosis), it was found that an increase in the average value of the factor by %, % and % will lead to a decrease in life expectancy by ,%, % and % respectively.

As for the factor x (divorce rates), its increase by %, % and % will result in a decrease of life expectancy by ,%, ,% and ,% respectively.

The second part of the research is dedicated to the factor anal-ysis in dynamics. There were chosen two factors in dynamics (x- alcohol consumption, y-life expectancy) in the period from to .

The same factors were analyzed for countries: Great Britain, Germany, Italy, Hungary and Romania.T . Factors in dynamics

Life expectancy

Year Alcohol consumption per person a year

, ,, ,, , ,, ,, ,, ,, ,, ,, ,, ,, , ,, ,, ,, ,, ,, , ,

, ,, ,, ,, ,, ,, ,, ,, ,, ,, ,

Furthermore, the graphs of the dependence of each factor on time were constructed. Based on the data, the forecast was made for each country.

The fi rst graph shows life expectancy in Russia.

y = 0,86x - 1651R = 0,9732

y = 0,0738x2 - 295,6x + 296023R = 0,9121

y = 0,4832x - 902,16R = 0,9812

y = -1,37x + 2796,1R = 0,8541

63

64

65

66

67

68

69

70

71

72

73

74

1985 1990 1995 2000 2005 2010 2015 2020

y = -0,6082x + 1236,9R = 0,8649

y = 0,296x - 581,71R = 0,8235

6

8

10

12

14

16

18

1985 1990 1995 2000 2005 2010 2015 2020

L R

A R

I. M, Q M C A

The absence of a linear trend on both graphs can be clearly seen. It can be noticed that there was a sharp decline in life ex-pectancy in the s, which is connected to the crisis that took place in Russia after the collapse of the Soviet Union.

Nevertheless, life expectancy has been increasing over the past years and the growth is expected in the nearest future. Accord-ing to the forecast based on the graphs, in life expectancy will be , years and in people in Russia will reach the age of , on average. As for alcohol consumption, there were con-siderable increases and decreases due to the same reasons. None-theless, over the past years alcohol consumption has been de-creasing though there is a slight increase in . Anyway, ac-cording to the forecast, in the nearest future alcohol consumption will be on decrease and in it will be , liters per person and in it will decrease to , liters per person.

Furthermore, these factors (life expectancy and alcohol con-sumption) were analyzed for European countries.

The fi rst one is Great Britain.

In Great Britain there was a stable growth in life expectancy, though during the last years the average life expectancy has been at approximately the same level. There is no linear trend in this part of the graph and no other trend can be constructed. For this reason, the average for these years was calculated, and it amounts to ,, which means that in the nearest future the av-erage life expectancy will be around years.

As far as alcohol consumption is concerned, since it has been gradually decreasing. According to the forecast for and years, it will be approximately at the same level. In peo-ple are expected to drink , liters per person and in –, .

The next country is Germany.In Germany the situation is similar to Great Britain. Life ex-

pectancy was on the rise but during the last years it has re-mained approximately at the same level. Therefore, the average was calculated as a trend cannot be constructed here. The aver-age equals ,, which means that in the nearest future people will leave up to – years in general. The fi gure is close to that

y = 0,2153x - 352,72R = 0,9834

75

76

77

78

79

80

81

82

1985 1990 1995 2000 2005 2010 2015 2020

Great Britain - life expectancy

y = 0,3593x - 708,69R = 0,9542

y = -0,2595t + 531,75R = 0,9429

y = 0,2114x - 416,4R = 0,7875

6

7

8

9

10

11

12

1985 1990 1995 2000 2005 2010 2015 2020

Great Britain - alcohol consumption

y = 0,2754t - 472,83R = 0,9879

y = 0,2407t - 403,67R = 0,9882

74

75

76

77

78

79

80

81

82

1985 1990 1995 2000 2005 2010 2015 2020

Germany - life expectancy

y = -0,161t + 334,76R = 0,8756

y = -0,1488t + 310,42R = 0,922

y = 0,0952t - 180,58R = 0,8758

10

11

12

13

14

15

1985 1990 1995 2000 2005 2010 2015 2020

Germany - alcohol consumption

I. M, Q M C A

of Great Britain. As for alcohol consumption, it has been decreas-ing throughout almost the whole period, although during the last years it has been at the same level. According to the forecast, it will be like that in the nearest future: in alcohol consump-tion will be , while in it will be ,.

The next country is Italy.In Italy the situation is also similar to the previous two coun-

tries. There is no linear trend, life expectancy has been on in-crease for a long time, though during the last fi ve years fi gures there is neither increase not decrease. Hence, similar to Great Britain and Germany the average fi gure was also calculated. It ac-counts for ,, which means that in the nearest future Italians will live till years on average.

Alcohol consumption has been on decrease, though there is no linear trend on the graph: there were decreases, then slight in-creases and then decreases again. Within the last several years alcohol consumption per person has not changed signifi cantly and remained at the same level. According to the forecast, in it will amount to , and in –,.

The next country is Romania.In Romania the situation with life expectancy is a bit diff erent

from that in all the previous countries. There is a decline in the s and then life expectancy has been increasing. According to the forecast, the growth in life expectancy is anticipated: in it will be , on average and by this fi gure will increase to ,.

Alcohol consumption in Romania has been diff erent through-out the period and there is no linear trend on the whole graph similar to the previous countries. Nevertheless, alcohol consump-tion is expected to be on the rise. According to the forecast, in it will amount to , liters per person and in it will be ,.

The next country is Hungary.In Hungary there has been a stable growth in life expectancy

and it is likely to remain this way in the nearest future. Accord-ing to the forecast, in Hungarian will reach the age of , on average and by this fi gure will increase to ,.

y = 0,2713x - 463,05R = 0,98

y = 0,2052x - 330,55R = 0,9696

76

77

78

79

80

81

82

83

84

85

1985 1990 1995 2000 2005 2010 2015 2020

Italy - life expectancy

y = -0,2612t + 530,84R = 0,9598

y = -0,2718t + 553,62R = 0,9582

y = 0,0567t - 106,84R = 0,4292

6

7

8

9

10

11

1985 1990 1995 2000 2005 2010 2015 2020

Italy - alcohol consumption

y = -0,1142t + 297,1R = 0,8733

y = 0,2457t - 420,72R = 0,9279

y = 0,2211t - 370,6R = 0,8224

68

69

70

71

72

73

74

75

76

1985 1990 1995 2000 2005 2010 2015 2020

Romania - life expectancy

y = 0,2067t - 406,39R = 0,7861

6

7

8

9

10

11

12

13

14

1985 1990 1995 2000 2005 2010 2015 2020

Romania – alcohol consumption

I. M, Q M C A

Alcohol consumption in Hungary is higher than in other countries, although there is a decrease. According to the fore-cast, in it will amount to , and in it will be , per person.

Both Romania and Hungary are closer to Russia then Great Britain, Germany and Italy in terms of life expectancy.

C

Summing up, the main factors infl uencing life expectancy are the number of diseases revealed during pregnancy, alcohol consump-tion and the number of young people who have suff ered from criminal actions.

Life expectancy in Russia will be on the rise in the nearest fu-ture, in people will reach the age of ,. Nevertheless, de-spite the fact that the average life expectancy in Russia has been increasing, it is still lower than in other countries. As for alcohol consumption, it is also lower than in a number of European coun-

tries and, according to the forecast, by alcohol consumption in Russia will reduce to , liters per person.

In order to improve the situation with life expectancy in the Russian Federation, some measures should be taken. First of all, the control over the sale of alcohol should be strengthened as there is much alcohol of low quality that is sold illegally.

Moreover, the sale and drinking of alcohol in all public places should be limited. The amount of the fi ne should be increased. Besides, the government should also strengthen social support for pregnant women by increasing social payments.

The implementation of the measures given above is bound to improve the situation in the country.

R

. Alcohol consumption (). [Online]. Available at: https://gateway.euro.who.int/ru/indicators/hfa_–-pure-alco-h o l - c o n s u m p t i o n - l i t r e s - p e r- c a p i t a - a g e - p l u s /visualizations/#id=

. Alcohol consumption (). [Online]. Available at: http://ac.gov.ru/publications//

. Alcohol consumption in the long term. [Online]. Available at: https://ourworldindata.org/alcohol-consumption

. Country comparison: life expectancy. [Online]. Available at: https://www.cia.gov/library/publications/the-world-factbook/rankorder/rank.html

. Federal State Statistics Service [Online]. Available: http://www.gks.ru/wps/wcm/connect/rosstat_main/rosstat/en/fi gures/population/

. Life expectancy and well-being. [Online]. Available at: https://www.health.gov.au/internet/publications/publishing.nsf/Con-tent/oatsih-hpf--toc~tier~life-exp-wellb~

. Life expectancy by country . [Online]. Available at:

. http://worldpopulationreview.com/countries/life-expectancy/

. Liters of alcohol consumed per capita in the United Kingdom (UK) from to (). [Online] Available at: https://www.statista.com/statistics//alcohol-consumption-in-liters-per-head-in-the-united-kingdom/

y = 0,2112t - 351,47R = 0,8637

y = 0,2671t - 462,62R = 0,9462 y = 0,1467t - 220,06

R = 0,6848

68

69

70

71

72

73

74

75

76

77

1985 1990 1995 2000 2005 2010 2015 2020

Hungary -life expectancy

y = -0,3955t + 802,47R = 0,8828

y = -0,141t + 295,31R = 0,6947

10

11

12

13

14

15

16

17

1985 1990 1995 2000 2005 2010 2015 2020

Hungary – alcohol consumption

A R

Analysis of road traffi c accidents in Russia

D P,StudentRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences


A

This paper offers research of various components which significantly affected a number of road traffic accidents throughout the federal subjects of the Russian Federation in the year. The most crucial factors were recognized through the implementation of correlation and regression analysis. The linear model was built respectively. Moreover, this work demonstrates the depend-ence of the investigated factor on the components presented.

Consequently, dynamic series were reviewed to detect the existence of seasonality and then the data were cleared of it. The most interconnected time series were related to each other to build a function.

The fi ndings of the research established a possibility of the fu-ture improvement of road conditions for Russian drivers which can be accomplished by an eff ective assessment of the elucidate d factors.

Key words: road traffi c accidents, regression-correlation anal-ysis, time series

I

The goal of the following research was to identify and analyze the various factors that can aff ect the number of road traffi c acci-dents (RTAs) in Russia.

Therefore, the following article is based upon the results of re-search of the components infl uencing road traffi c incidents. Pre-cisely, the regression-correlation analysis was introduced to pro-vide an insight into the issue and test a hypothesis formulated on an idea that a number of road traffi c accidents is highly de-pendent on road density.

First and foremost, this paper acknowledges various compo-nents infl uencing road incidents by viewing the data for the year collected over the Russian federal subjects. Throughout the research, it was crucial to constantly test the validity of the the-ory by using the coeffi cient of determination and Fisher’s ratio test. Having reviewed both linear and exponential models the de-cision was made to examine the linear model since the identify-ing criteria demonstrated better data.

Consequently, analysis of time series was developed by exam-ining monthly data for nine years — from to . During the work the data was cleared of seasonality and both additive and multiplicative models were constructed. Furthermore, monthly material was constricted to annual to examine the time lag of one year and its infl uence on the variables. Finally, by building a linear model and putting aside a time factor, the true correlation between the number of traffi c accidents and road density was recognized.

In the end, a conclusion was formulated to summarize the fi ndings of the research.

I. M, Q M C A R

A RTA

In order to reach the primary objective and collect the required data, all the necessary information was found with the help of such reliable sources as the offi cial website of State Traffi c Safety In-spectorate (STSI) and the Russian Federal State Statistics Service.

The original version of the research included such variables as alcohol consumption per capita, government funding of roads, road mileage, road density, price of driver’s training course, av-erage precipitation, average winter temperature and the number of citizen from to years old.T . Linear model: Correlation Matrix

Number of RTAs (Y)

Government funding of roads (X)

Average precipita-tion (X)

Road density (X)

Number of RTAs (Y)

Government funding of roads (rubles) (X)

.

Average precipitation (millimeters) (X)

. -.

Road density (km of road per sq. km of land area) (X)

. -. .

Number of citizens from to years old (X)

. . . .

Nevertheless, most of the components were excluded after-ward due to the multicollinearity which jeopardized the validity of the model by making the factors correlate more with each oth-er than with the dependent variable.

Thereby, the released version of the linear model was com-prised of four factors to study which eff ect they have on the num-ber of RTAs.

The following table represents a correlation matrix demon-strating which components correlate with the dependent varia-ble to the highest degree.

Subsequently, the correlation matrix was followed by the re-gression statistics with the purpose of confi rming the linear mod-

el’s credibility and fi nding the coeffi cients which illustrate the correlation ratio between the factors:T . Regression

Regression statisticsMultiple R .R-square .Standardized R-square .Standardized error .Observations

F F-test. .

Coeffi cientsY-intercept .Government funding of roads .Average precipitation .Road density -.Number of citizens from to years old .

The coeffi cient of determination equals ., which suggests that in % of cases changes in the dependent variable are caused by the factors included in the model. Moreover, the signifi cance of the R-square is close to the standardized R-square which con-fi rms the model’s accuracy. Additionally, the value of the F-test is extremely low which also indicates the reliability of the linear model.

Regression equation:

Y = X. + X

+ X–. + X

. + .By and large, the multifactorial analysis was viable and therefore it was decided to continue the research by moving to time series and delving into the connection between the number of road traffi c accidents and road density.

A

Based on the results of the conducted analysis the work was car-ried on by studying time series and the interdependence between the number of RTAs and the road density.

I. M, Q M C A R

The capital of Russia was chosen to illustrate the dynamics due to the fact that the number of RTAs in Moscow prevails in comparison with the other regions of the country.

Subsequently, monthly data for nine years (–) was collected to construct the graph of the dynamics of seasonality coeffi cients of RTAs’ number which were crucial to proceed with the task at hand:T . Moscow: Seasonality

Seasonality

January .

February .

March .

April .

May .

June .

July .

August .

September .

October .

November .

December .

T . Moscow: Correlation Matrix

Road density RTAs

Road density

RTAs -.

The correlation coeffi cient between the rows showed an out-standing value of –.. A negative value of the correlation coef-fi cient means an inverse relationship between the series. More specifi cally, it represents that the number of RTAs decreases when road density increases respectively.

In order to build a trend, cleared of the seasonal component, a moving average and centered moving average of both rows were found and both multiplicative and additive models were con-structed to demonstrate the fl uctuations of RTAs throughout the duration of nine years:

y = 46.459x + 787.68R = 0.1241

y = -5.7324x + 1072.5R = 0.0074

y = -44.852x + 1802.3R = 0.5342

y = 18.819x + 454.05R = 0.4114

y = -13.052x + 1269.5R = 0.0775

y = -32.886x + 2126R = 0.738

y = 27.247x - 558.95R = 0.6007

y = -44.981x + 3158.8R = 0.8177

y = 20.828x - 487.22R = 0.4397

y = -2.6464x + 937.91R = 0.0034

0

200

400

600

800

1000

1200

1400

1600

0 10 20 30 40 50 60 70 80

Multiplicative model

T . Moscow: Time Series

y = 56.318x + 767.74R = 0.1626

y = -88.919x + 1894.5R = 0.3747

y = 38.66x + 454.95R = 0.9067

y = -20.582x + 1356.9R = 0.2414

y = 21.468x + 386.14R = 0.4921

y = -6.2304x + 1075.7R = 0.023

y = -34.785x + 2219.2R = 0.7555

y = 25.912x - 464.11R = 0.5646

y = -45.007x + 3172.5R = 0.8099

y = 20.173x - 419.01R = 0.4575

y = 2.6744x + 592R = 0.0034

0

200

400

600

800

1000

1200

1400

1600

1800

0 10 20 30 40 50 60 70 80

Additive model

T . Multiplicative and Additive Models

Y = -433.55t + 883806R = 0.851

8000

9000

10000

11000

12000

13000

2008 2010 2012 2014 2016 2018 2020

RTAs (Y)

I. M, Q M C A R

Over the course of work with time series, it was discovered that the highest coeffi cient of determination is apparent with original observations. Consequently, two linear trends were built illus-trating factors relation on time. It can be number of RTAs was substantially decreasing from to in contrast with the road density which was following an upward trend.

Unfortunately, the high R-square presented on the graphs could have been a characteristic of a false correlation which was crucial to exclude in order to reach a right verdict. Therefore, measures were taken to scrutinize the subject by implementing a chain-base-method.

Subsequently, in spite of the initial R-square being illustrious, chain-base method unraveled the true interdependence of the variables equaling R = .. Hence, this value is extremely low to conclude that road density has any infl uence on the number of RTAs in dynamics.

However, it was necessary to implement a chain-base method with a one year lag to determine if the coeffi cient of determina-tion ascends because of a particular time interval:

Despite the eff orts, the coeffi cient of determination remained at the same level. Therefore, it is evident that a time lag does not aff ect the eventual number of RTAs.

As can be seen from the above, a hypothesis that a number of RTAs is highly dependent on the road density was disproven due to the presence of false correlation.

R

Thus wise, by summarizing the fi ndings of the research a conclu-sion was formulated concerning the number of RTAs on the ter-ritory of Russia and Moscow in particular. Most notably, the orig-inal presumption declaring that road density infl uences the road traffi c accidents turned out to be invalid in dynamics. Apart from that, government funding of roads appeared to be of minor im-portance in terms of reduction of the RTAs number. Therefore, this may be evidence of poorly thought-out allocation of funds towards construction or repair of roads.

Hence, taking everything into consideration, it is important for the government to pay thorough attention to the quality of the road pavement in order to reduce the number of accidents caused by the roads’ condition in the future.

R

. Ovsyannikova, S. N. Econometrics/Textbook for students of the nd year of economic specialties. — Moscow: Publisher “Delo” RANEPA, – pp.

. Transport Strategy of the Russian Federation. [online]. Availa-ble at: http://docs.cntd.ru/document/

. Russian Federal State Statistics Service. [online]. Available at: http://www.gks.ru/

. State Traffi c Safety Inspectorate. [online]. Available at: https://xn-adear.xn — pai/

X = 76.488t - 151726R = 0.8943

2000

2100

2200

2300

2400

2500

2600

2700

2008 2010 2012 2014 2016 2018 2020

Road density (X)

T . Chain-base method

Y = -2.199 X - 239.12R = 0.1056

-1600

-1400

-1200

-1000

-800

-600

-400

-200

0

200

400

0 50 100 150 200 250 300

T . Chain-base method with a time lag (one year)

A

An empirical study of factors aff ecting suicide ratein the Russian Federation

A S, D TStudentsRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences


A

The present article explores suicide rate depend-ence from a number of socio-economic factors. We identifi ed the most signifi cant factors on the basis of which a multiple relation model was developed. We analyzed sensitivity of the dependent valuable to small changes in the regions included in the model. The most signifi cant factor aff ecting suicide rate was proven to be drug consumption. We also constructed a dynamic model and demonstrated its predictive ability.

Key words: suicide, socio-economic factors, sensitivity, factor aff ecting suicide rate, dynamic model.

R

Suicide in the Russian Federation is an important social prob-lem. The study showed a high level of dependence of the level of suicide on alcohol and drug use. The connection is traced be-tween the number of crimes and the level of suicide; suicides are committed by criminals, victims, as well as their relatives and acquaintances. The cause of suicide is also cancer and stress associated with the divorce and death of loved ones. These fac-tors can lead to mental disorders. The level of material well-be-ing is also a factor infl uencing the number of suicides in the country.

Subsequently, the dependence of the number of people who committed suicide on several infl uencing factors was revealed.

As the main characteristics were taken:

• Number of crimes• Number of registered divorces• Average salaries for each region• Spread of mental illness• Percentage of persons with have an Internet access• Beer consumption• Number of crimes related to drug traffi cking• Incidence of cancer• Drug dependence• Number of unemployed

All data taken as factors were given in one year.Analysis of the matrix of pairwise correlation coeffi cients

shows that the effi cient indicator, that is the number of suicides, is closely related to:

• X is the number of crimes related to drug traffi cking = .• X-the spread of mental illness = .• X-sale of beer (in liters) = .• X- drug addiction = .

I. M, Q M C A

Using the coeffi cients taken from the correlation matrix, a lin-ear model was constructed. The effi cient indicator was equal to %, but we were wondering if there could be more infl uence.

Therefore, an exponential model was constructed with the same set of factors.

Regression statisticMultiple R ,R-square ,Standardized R-square ,Standard failure ,

L

Y = ,·X + ,·X,·X + ,·X + ,·X + ,·X + + ,·X,·X + ,·X + ,·X + ,

Using the methods of regression analysis, an exponential mod-el was constructed, the coeffi cients of which showed a greater in-fl uence. In the exponential model, the effi cient indicator was %. Also, the model was tested using the Criterion of Fisher, which was close to zero, which indicated the great importance of regression models.

E

Regression statisticMultiple R ,R-square ,Standardized R-square ,Standard failure ,

Y = X,·X

,·X–,·X

,·X,·X

,·X,·X

–,·X,·X

–,·,

Meanings:

• X-Number of crimes• X-Number of registered divorces• X- Average salaries for each region• X-Spread of mental illness• X-Percentage of persons with have an Internet access• X-Beer consumption

% in

crea

se o

f eac

h va

riab

le, o

ther

co

ndit

ions

bei

ng e

qual

Chan

ge o

f the

nu

mbe

r of

sui

cide

%

dec

reas

e of

eac

h va

riab

le,

othe

r co

ndit

ions

bei

ng e

qual

Chan

ge o

f the

nu

mbe

r of

sui

cide

X-

Num

ber

of c

rim

es,

%

X-

Num

ber

of c

rim

es-

,%

X-

Num

ber

of r

egis

tere

d di

vorc

es,

%

X-

Num

ber

of r

egis

tere

d di

vorc

es-

,%

X-

Aver

age

sala

ries

-,

%

X-

Aver

age

sala

ries

,

%

X-

Spre

ad o

f men

tal i

llnes

s,

%

X-

Spre

ad o

f men

tal i

llnes

s-

,%

X-

Perc

enta

ge o

f per

sons

wit

h ha

ve a

n In

tern

et a

cces

s,

%

X-

Perc

enta

ge o

f per

sons

wit

h ha

ve a

n In

tern

et a

cces

s-

,%

X-

Beer

con

sum

ptio

n,

%

X-

Beer

con

sum

ptio

n-

,%

X-

Num

ber

of c

rim

es r

elat

ed t

o dr

ug

traffi

cki

ng,

%

X-

Num

ber

of c

rim

es r

elat

ed t

o dr

ug

traffi

cki

ng-

,%

X-

Inci

denc

e of

can

cer

-,

%X

-In

cide

nce

of c

ance

r,

%

X-

Dru

g de

pend

ence

,

%X

-D

rug

depe

nden

ce-

,%

X

-Num

ber

of u

nem

ploy

ed-

,%

X

-Num

ber

of u

nem

ploy

ed,

%

I. M, Q M C A

• X-Number of crimes related to drug traffi cking• X-Incidence of cancer• X-Drug dependence• X-Number of unemployed

The model was tested for sensitivity; it means that it was checked how the response variable would change when each factor chang-es by %. The most interesting factors were the average wages and crimes related to drug traffi cking, because these have the greatest infl uence on the number of suicides. The unemployment rate seemed very interesting. With increasing such factor as un-employment, the amount of suicide decreases.

Turning to the study of dynamic rows, was set the goal — to de-termine the relationship between the number of suicide and drug addiction. Then an Additive model was built to check for season-ality and calculate seasonal components to see in which months the suicide rate rises or falls.

Seasonal componentJanuary -,February -,March ,April ,May ,June ,July ,August ,September -,October -,November -,December -,

Due to the analysis of the seasonal component, it was revealed that the number of suicides in winter is much less than at any other time of the year. This is due to public reasons. In winter, the society is less active because of the temperature and the length of the daylight hours.

Then both dynamic series were investigated and a non-linear trend was identifi ed. For the analysis of the dynamic range, the amount of suicide and use of drugs have been taken in the last years.

t X- Drug dependence Y-The number of suicide , , , , , , , , ,

During the research, the effi cient indicator was low, which in-dicates a weak dependence. Therefore, it was decided to check the connection with a lag of year. The fi gure was %, which suggests that while using drugs the probability of committing sui cide next year is high.

Additive model of the suicide quantity

-5000

-4000

-3000

-2000

-1000

0

1000

2000

-30 -20 -10 0

-5000,00

-4000,00

-3000,00

-2000,00

-1000,00

0,00

1000,00

2000,00

-20 -10 0 10

Nonlinear trend year lag

I. M, Q M C

R

To address this social problem, the following measures were rec-ommended:

• Conduct a drug test in schools.• Explain to parents through conversations about the dangers

of drugs.• There was also a theory that the government can infl uence

the level of suicide in the country by increasing the average wages in the regions.

R

. Ovsiannikova S. N. Econometrics. A study guide for students of the nd year of special economic sciences. ()

. Statistics for Russia [electronic resource], URL: https://russia.duck.consulting

. Central Statistical Database [electronic resource], URL: http://www.gks.ru/dbscripts/cbsd/DBInet.cgi

N E E I

The refl ection of tradition at the th anniversary of Romania.The way the tradition helps at forming the identity of the nation.

O A NSenior LecturerLower Danube University of GalatiBabes-Bolyai University of Cluj-Napoca

P-A NStudent Lower Danube University of Galati Babes-Bolyai University of Cluj-Napoca

A

Starting from the initial defi nition, the naturalist one, tradition is something that repeats itself and forms the habit, comfort, well-being. It also traces identity. Traditions simply exists and it refers to cer-tain undeniable values. Tradition is an emblem, a state of fact, it is self-contained and is a normative character, is “the force of a law, respected by all members of the community, by mutual agreement”. Perceived this way, tradition seen as a value presup-poses the continuity of the cultural facts in time, fa-voring the past, a past-normative, auroral, which of-fers patterns prone to imitation. By the means of this paper, we want to emphasize the pursue of tra-dition in Romania even after years from the cre-ation of the country and how tradition is perceived by young people, especially Romanian students. The main focus will be on the continuity of dance and manufacturing of national costumes and how these

I. M, Q M C T R

fundamental elements of tradition are sought and promoted in an innovative format by youth.

Key words: tradition, identity, national costumes, folk danc-es

I

The present paper aims at presenting how Romanian traditions, especially the traditional costumes and dances, have been per-petuated over time, representing a link between the history of the Romanian nation, its ancestors, and today’s generations who, in front of the phenomenon of globalization, try to revive them. For the Romanian society of the st century, tradition means continuity, a reference to the past, which is updated by belong-ing to the present, and being adapted to the new socio-cultural requirements.

R

We can assert that the notion of culture, above all, means the study of ideas, experiences, feelings and external forms that they take when they are made public, when they are accessible to senses, relying on a social structure of people and relationships, the cultural fl ow being produced through them. “Any cultural form (…)” lives its own “life”: it begins to exist, or is “born” in a certain place and moment, it is the work of someone; it lasts from generation to generation, spreading from one place to another or from one social stratum to another; during these “movements” of time, space, or society, it is sometimes kept unaltered and some-times subjected to more or less profound transformations; Final-ly, it “dies”, as it is said many times, that is, ceasing to be used and pursued by individuals and groups “ .

At fi rst glance, it would seem that concerns about the fate of traditional culture would only be of interest to beauty and old lovers. In reality, however, it is not a leaning towards tradition for

Cirese, Alberto M., Cultura egemonica e culture subalterne. Rassegna degli studi sul mondo populare tradizionale, Palumbo Editore, Cagliari, , p..

the sake of tradition or the mere passion of some collectors, but a problem that is of a stringent and acute social interest, being in the attention of a large group of specialists. The transforma-tion processes generated by the evolution of society in recent centuries have brought to the fore the relationship between tra-dition and innovation, proving its full timeliness in the condi-tions of the dramatic changes happening both on national and international level.

A rich tradition, having its roots throughout the history of the Romanian people and its ancestors from the vast Carpathian-Danubio territory, has been preserved to this day due to particu-lar historical conditions . Therefore, any society, any culture, is characterized by dynamism, being determined by all the “cultur-al heritage” or “traditions” transmitted, but also by the “change s” or “innovations” that occur in time, in space and in social struc-tures, society or the culture itself being a “multifaceted, varied, complex reality of eternal change and development” .

An important part of the tradition of the Romanian people is the wearing, at any occasion, of the traditional costume. The tra-ditional costume has been in our culture for thousands of years. The traditional costume (mentioned on the Trajan’s Column, then on the Tropaeum Traiani Monument from Adamclisi) im-presses thanks to the simple and straight outfi t, ornaments (stitches, embroideries), colors (white, black, red), composition and material (cotton, fl ax, hemp). The Romanian traditional cos-tume fi nds its roots in the clothes of our ancient ancestors, Ge-tae and Dacians, and resembles that of the peoples of the Balkan Peninsula, of course, with the specifi c decorative and color diff e-rences.

Throughout history, the structure and evolution of the Roma-nian traditional costume kept its essential characteristics unal-tered. National embroideries, traditional costumes are not just a fad of a long-lost tradition. They are, in fact, the entire cultural

Secosan, Elena, Petrescu, Paul, The folk holiday costume in Romania, Meridiane Publishing House, Bucharest, , p..

Herseni, Traian, Social reality. Attempts of regional ontology, The publishing house of the Romanian cultural institute, Bucharest, , p..

I. M, Q M C T R

heritage of the Romanian peasant. It’s about a unitary set of leg-ends, stories, fairy tales, fables, colors and meanings. Deep mean-ings, hidden symbolism. It’s about passion and fascination, orig-inality and keeping of tradition. And some reasons come down from prehistory. They say a lot about the geographical area, the history, the tradition of each group .

Romania has evolved, people have come and gone, globaliza-tion encompasses us every day, but the identity of our people re-mains anchored in the soft and delicate cloth, in the skilful fab-ric of the elders, in the stories the Romanian traditional cos-tumes have written and carried over the ages.

Starting from the artistic achievements made with raw mate-rials produced inside the peasant households, the Romanian tra-ditional costume has evolved over the centuries, proving a rich mastery of the Romanian peasant, both in the embroidery of fab-rics and embroideries, as well as in the obtaining of the vegetal colors. Researchers found colors in the Romanian peasant ar-senal. The colors were made of herbs: walnut, onion leaves, quince, bat and others.

The traditional clothing is diff erentiated according to season, festive occasions, age and sex, adapting to occupations specifi c to each area. Romania is divided into seven folkloric regions: Transylvania, Western Plains, Banat, Wallachia, Lower Danube, Moldavia and Romanians in the Balkans (Aromanians, Istoroma-nians, Daco-Romans). Thus, depending on the occasion, the tra-ditional costume can be simpler, for example, the one used dur-ing agricultural work, to the most beautifully ornamented used at the wedding. Even today, on working days or on holidays, in Romania, you see women and men dressed in cloths of pure white, wool, hemp, or cotton, the dominant note of the Romani-an traditional costume, in terms of raw material, being the use of white fabrics from animal or vegetable fi bers. Women’s and men’s shirts, women’s footwear and skirts, men’s leggings, in other words the basics of the costume, as well as vests, thick wool or

Stanculescu, Catalin, What signifi cance have the drawings on the folk Romanian costumes? | Mythologica.ro, https://mythologica.ro/ce-semnifi catie-au-desenele-de-pe-costumele-populare-romanesti/, available at March th, .

hemp clothing are all white, the impression left by this white-clothed people being one of “calm, power, physical and moral cleansing” .

The Romanian folk costume has a discreet ornamentation and, at the same time, of eff ect. This result is achieved by placing the ornaments in well-defi ned fi elds, making the lines of the cut to be highlighted, and along with them, those of the body, giving the costume a sculptural character, and on the other hand, high-lighting the decorative motifs .

The motifs, or rather, the symbols of the Romanian folk cos-tumes are of several kinds: abstract symbols (cosmic, zoomorphic, anthropomorphic ones), fl oral and vegetal symbols (plants, leaves, fl owers, fruits), geometric and abstract symbols. The cosmic sym-bols of traditional folk costumes such as the sun, the sunfl ower, the circle, the lightning, the stars, the moon speak of the connec-tion with the sacred. They are usually ancestral symbols of divin-ity. The symbol of the sun, for example, represents the warmth, the energy of life, and the circle represents the wheel of life, the cycle of seasons.

Floral or vegetal symbols like wheat ear, acorn, grape, rose, lily or cherry fl owers, trees or their branches are symbols of reinven-tion and wisdom. The traditional Romanian blouses abound in representations and coloring according to the area. In the villag-es of the plain, there are elements related to the harvest periods, while cones and fi r trees appear in the mountain villages . The zoomorphic elements such as the horns of the ram, the sparrow, the coco, the harpsichord express the tradition and the richness of a certain geographical and ethnographic area.

The diff erence in costumes is also refl ected by age categories. Thus, for children, although as clothing style it is the same, there are some diff erences. For example, for women, the diff erence lies in the decorations of the head, which diff er from unmarried and

Secosan, Elena, Petrescu, Paul, The folk holiday costume in Romania, p.. Ibidem, p. Stanculescu, Catalin, What signifi cance have the drawings on the folk Romanian

costumes? | Mythologica.ro, https://mythologica.ro/ce-semnifi catie-au-desenele-de-pe-costumele-populare-romanesti/, available at March th, .

I. M, Q M C T R

married women. Generally, the women’s costume is composed of: shirt, skirt and the clothing covering the skirt from beneath the waist that is diff erent from region to region. The covering cloth-ing has diff erent names depending on its form and the region. Therefore, it can be called „catrinţă”, „vâlnic”, „fotă”, „opreg” . These pieces of clothing are made of wool, having a simpler or more complicated design, based on their region of provenience.

Shirts have the same ornamental parts, with some chromatic diff erences. A supplement to the women’s clothing is the wide variety of head cookies that vary from one area to another, even from village to village, the value of this cookie depending on the beauty of fabrics and embroidery or other adornments for that purpose. They are composed of: marbles, “naframe”, “cepse” or crowns. Other pieces of the women’s costume are girdles and sticks, which also feature outstanding artistic achievements.

The men’s costume is simpler, consisting of a long shirt in the south and east of the country and a shorter one in the north and west. The pants in the south and east are long and narrow, and in the north and west of the country, they are shorter and wider. They are made of cloth or woven made in the house. Over the shirt, men put their own belt sewed in the house or a leather one, depending on the region and the occupation. In winter, over the clothes listed above, they are wearing nicely ornamented clothes, or leather coats.

The traditional Romanian folk costume, especially “ ia”, mean-ing the traditional costume blouse was a source of inspiration for local designers such as Adrian Oianu who created the concept of

“Urban IA” with the Celebration of the Centenary of the Great Un-ion in Romania,; a solution of the fashion designer to make the young generation of Romanians wear the most iconic piece of the traditional Romanian costume .

The concept of “La Blouse Roumaine” has passed, however, the borders of our country, reaching the attention of the great fash-

Patrut, Bogdan, The Romanian national costumes, EduSoft Magazine, https://www.edusoft.ro/portul-popular/, available at April th, .

Sandu, Geanina, Adrian Oianu — the desgner who returned ia to the urban life, http://miscareaderezistenta.ro/article-.html, available at April rd, .

ion houses around the world, such as Christian Dior, who copied a traditional coat from the Bihor region and inserted it in a col-lection of their own in autumn . Beau Monde, a fashion mag-azine with % original Romanian content, chose to take action against the phenomenon of not being given credit to traditional Bihor craftsmen, saying that at least a small part of the amount Dior sells the piece the clothing inspired by Romanian folklore should return to the original creators .

The Romanian peasant drew his dreams and stories on shirts, pants and coats. He gathered his hopes and the way he perceives the world, his religious beliefs and his vision of life, and painted, beaten, bloomed, sculpted, burned and embroidered them on all sorts of materials. Some resisted, others less. The traditional Ro-manian costume is art and history at the same time. It is the sto-ry of the Romanian peasant from origins to the present, from the village meetings, where the village dances were created, where eternity was born.

Besides traditional folk costumes, another fundamental ele-ment of the Romanian culture that resisted the passing of time and all the external factors that caused major changes in the Ro-manian society is represented by traditional dances.

The dance had a special importance in the life of the Romani-an peasant, being indispensable in religious rituals. Over time, there have been mutations in traditional dances, some keeping their ritualic function (Calusul, Cununa, Dragaica) and others transforming into “show dances”, revealing an exaggeration of the dance of the elderly. The show dance consists of adopting a much more alert speed to please the audience’s eye, which at the same time means the loss of tradition. By playing a show dance, the style, movement and the original theme of the traditional dance, which consists of the close relationship between the part-ners, their collaboration during the dance and the transmission of a good mood to the spectators, is lost. Another considerable

VIDEO How did Bihor’s coat got copied by Dior and sold with , euros. “No part of this sum goes back to the original creators”, adevarul.ro, https://adevarul.ro/locale/oradea/videocum-ajuns-cojocul-bihor-copiat-dior-vandut--eu-r o - n i c i - p a r t e - s u m a - n u - i n t o a r c e - c r e a t o r i i - o r i g i -nali-_abadffec/index.html, available at April rd, .

I. M, Q M C T R

diff erence between traditional and show dances is revealed by the techniques used. While in traditional old dances, the dancers were playing on synopsis, contretemps, in show dances there are movements and steps always made on time.

The fi rst references to the existence of traditional dances have been made since the fi fteenth century, along with the writings of the Romanian chronicler Grigore Ureche. Over time, a whole range of dances has been enhanced, such as Hora, Sarba, Calusul, Braul.

Braul is a traditional dance played by both women and men, usually in pairs, shoulder-shaven, accompanied by shouts like:

“One, twoForty-nineAnd now wipe it out onceAnd wipe it out againLet’s see if we canOn our knees, let us goWhen shouting:The bracket is being snappedLike the oats in the turret.Still on the spot, on the spot,To rise basil:The basil of women,The love of wives “ .

Calusul is among the oldest ancient customs of the Romanians, being specifi c to the southern part of the country. Calusul, in its attested forms in the last centuries, is practiced and is known as the most representative tradition, the most impressive show and one of the most impressive and valuable Romanian folk creations. It is the most important folkloric manifestation of religious cus-toms. The ritual fulfi lled by the group of dancers translates a hu-man need, symbolically providing consistent explanations of cer-tain aspects of individual and social life.

The habit of the Calus dance has an essential role in the nor-mal development of the community life. It evades and protects

Niculescu- Varone, G.T., Dictionary of Romanian dances — Folk choreography, The Printing of the “Vacaresti” Penitentiary, Bucharest, , p.–

the community against the aggression of the wicked fairies, mak-ing them a transcendent and always present threat, which claims to be demolished by proper rituals.

To ensure the protection of the whole community, the Calus dancers played throughout the village, on the music of the mu-sicians paid by them. The dances were reiterated daily during the Pentecost period, that is, as long as there was a danger that people would be assaulted by wicked fairies. Their dance was be-tween sunrise and sunset. After that, dancing became danger-ous for them, as they did not benefi t from the protective light of the solar star, from its strength to keep the fairies away. Their dances drove the fairies away, preventing them from getting closer to people. At the same time, in order to protect them from diseases, in this case the “taking away from the Calus”, the dancers gave the villagers garlic and wormwood. People kept them at their waist, some anointing windows and doors with garlic in combination with wormwood for the same prophylac-tic purpose.

Another way of defending against the wicked fairies was for the villagers to play with the dancers or to give their children to be worn and played by them. The Calus dancers defended the community and, at the same time, defended themselves by using

“weapons” with magical powers: bats, wood swords, and even the noise of the spurs and jingle bells from their boots .

Never-failing from the village life and spread almost in all re-gions of the country, Hora has been given multiple meanings over time. The fi rst mention of the Hora was made by the chron-icler Dimitrie Cantemir in his book “Descriptio Moldaviae” in .

In the popular tradition, “going out to the Hora” meant the transition of girls and boys to those who had reached the age. The name of this dance is also related to the phrase “if you en-tered the Hora, you have to play”, which means that a thing which has started has to be fi nished . Nor is the appreciation

Tiberiu Alexandru, „La horă-n sat” — Oltenia, disc Electrecord (EPD), Bucha-rest, .

Darosi, Mircea, Hora — the symbol of our national unity, Răsunetul Magazine, /ho-

I. M, Q M C T R

“prepared for the Hora” is not meaningless, confi rming once again that the Hora is not an ordinary event, but one that off ers the oc-casion of a genuine celebration in the life of the community.

Throughout a millennial history, Hora became for the Roma-nian peasant the indispensable dance of affi rmation of his life as such, just as work and food. Thus conceived, the Hora is, without exaggeration, one of the most important factors of the eugenics of the Romanian people and culture .

Beyond the ethno-folklorical values included in the rhythms specifi c to each area, Hora also receives historical signifi cance. The clay fi gurines discovered by archeologists and symbolically called “Hora de la Frumuşica” are a testimony to the millenary existence of this dance on our lands. He is not encountered in other nations, just as the great-scholar Dimitrie Cantemir men-tions in the above-mentioned work.

The one that gives profound social signifi cance and strength-ens the historical message of the Hora is the Romanian poet Va-sile Alecsandri, who wrote the famous Hora of the Union. His lyr-ics were put on music by the composer Alexandru Flechtenmach-er and it was sung and played in the big squares of the cities of Bucharest and Iasi with the occasion of the double election of the prince Alexandru Ioan Cuza. From that moment on, Hora became the symbol of the union of all Romanians.

On January , , the song and the dance merged on the rhythm of the same sensation:

“Let’s stay hand in hand,Those with the Romanian heart,Let’s turn the brotherhood HoraOn the land of Romania “.

Since then, for Romania, Hora has become a dance and a song of the revolutionary call, a symbol of the victory and union of those who are brothers and sisters of this nation and of this earth. Like in a Hora, it seems like the Carpathians give their hand and all

ra-simbolul-unitatii-noastre-nationale, available at April rd, . Fochi, Adrian, Customs and folk tales at the end of the XIX century, Minerva Pub-

lishing House, Bucharest, , p..

the waters form a wonderful girdle. Hora is today the most faith-ful expression of permanence and freedom, it is the metaphor of our national rebirth.

The traditional dance, through its variety, through tradition and sentiment, is the expression of every corner of the country, with its customs, its people and its culture. As if forgotten by most young people, traditional dances burn in the hearts of grandparents and great-grandparents “dependent” of folklore. The specifi city of the dance and interpretation depends on the folkloric area. Thus, folkloric areas of Moldavia, Wallachia, Olte-nia, Banat, Transylvania and Dobrogea are distinguished. During dancing, the boys and girls say “shouts” that diff er from one area to another. Moldova is shouting on the pace of the footsteps. In Maramures, “screaming” is played in interesting, specifi c intona-tions. In Transylvania there are real dialogues between girls and boys. And in Oltenia, Muntenia and Dobrogea, these shouts have the role of leading the dance by announcing the fi gures. The shouts contain sometimes lyrical messages, of love, sometimes satirical or humorous, but they are not missing from traditional dances.

Both costumes and traditional dances are part of the history and tradition of the Romanian nation. They underlie the build-ing of the national identity, the building up of the cultural his-tory of the nation and the settling of the Romanian roots. To-day, when our country is aligned with technological evolution, when people’s migration is so active, when students go to stud-ies in other countries, when we embrace globalization and see it as an evolution of mankind, the only thing that does not al-low us to forget who we are and where we come from is tradi-tion. In tradition and customs stand our ancestors, our lan-guage and our dreams. It is the place where we always return, when our souls are in celebration, at weddings, events or festiv-ities. The traditions and customs of our nation are, in fact, the cultural DNA of Romania, which we disseminate and honor, even more and more intensely, when we sense the threat of the dissolution of the national ego in the sea of common habits of the planet.

I. M, Q M C

R

. Cirese, Alberto M., Cultura egemonica e culture subalterne. Rassegna degli studi sul mondo populare tradizionale, Palum-bo Editore, Cagliari, .

. Fochi, Adrian, Customs and folk tales at the end of the XIX cen-tury, Minerva Publishing House, Bucharest, .

. Herseni, Traian, Social reality. Attempts of regional ontology, The publishing house of the Romanian cultural institute, Bu-charest, .

. Niculescu- Varone, G.T., Dictionary of Romanian dances — Folk choreography, The Printing of the “Vacaresti” Penitentiary, Bu-charest, .

. Secosan, Elena, Petrescu, Paul, The holiday folk costume in Ro-mania, Meridiane Publishing House, Bucharest, .

Web Resources:. Darosi, Mircea, Hora — the symbol of our national unity,

Răsunetul Magazine, /hora-simbolul-unitatii-noastre-nation-ale, available at April rd, .

. Patrut, Bogdan, The Romanian national costumes, EduSoft Magazine, https://www.edusoft.ro/portul-popular/, available at April th, .

. Sandu, Geanina, Adrian Oianu — the desgner who returned ia to the urban life, http://miscareaderezistenta.ro/article-.html, available at April rd, .

. Stanculescu, Catalin, „ What signifi cance have the drawings on the folk Romanian costumes? | Mythologica.ro”, https://myth-ologica.ro/ce-semnifi catie-au-desenele-de-pe-costumele-pop-ulare-romanesti/, available at March th, .

. Tiberiu Alexandru, „La horă-n sat” — Oltenia, disc Electrecord (EPD), Bucharest, .

. VIDEO How did Bihor’s coat got copied by Dior and sold with , euros. “No part of this sum goes back to the original creators”, ade-varul.ro, https://adevarul.ro/locale/oradea/videocum-ajuns-cojocul-bihor-copiat-dior-vandut--euro-nici-parte-suma-nu-in-toarce-creatorii-originali-_abadffec/index.html, available at April rd, .

Research on the subsidy level in the Russian Federation:correlation-regression analysis

V B, E K Students Russian Presidential Academy of National Economy and Public Administration Faculty of Economic and Social Sciences

S O Associate Professor Russian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

A

The conducted research focuses on the dependence between the level of subsidies and socio-economic factors characterizing the regions. Correlation-re-gression analyzes the most signifi cant factors which aff ect the dependent variable. An exponential mod-el shows the dependence of the level of subsidies on the chosen basket of factors.

Statistical series indicate the change of gross re-gional product (GRP). Seasonality coeffi cients are evaluated. A visible dependence is revealed between the subsidies and the fi nancial resources lacking for the average level of fi scal capacity of the regions.

Conclusions, obtained during the research, allow subsidies allocation adjustments to be made.

Key words: fi scal capacity, subsidies, correlation analysis, regression analysis

I. M, Q M C R R F

I

The economic policy of the government sets a direction for the economy of the country. The centerpiece of this policy is subsidies allocation between federal units of the state. In Russia, the basic fi scal policy postulate is the adjustment of the level of fi scal capac-ity of the regions. However, a more rational decision would be to subsidize a region which is more economically developed and ef-fective. These two objectives create contradictions which arise a question of the governmental strategy of subsidies allocation.

The aim of this research is to study the rationale and prereq-uisites for subsidizing the regions of Russian Federation using the correlation-regression method of analysis.

R

The original hypothesis was that the level of infl uence of gross regional product on the subsidies was more than that of any oth-er factor. Other components, such as technological innovation expenditures (X), annual average employment (X), capital stock investments (X), volume of industrial output (X), volume of ag-ricultural production, were also included into the research to an-alyze the dependency between them and GPD and, thus, on sub-sidies. A linear model was composed (GDP-model).Table . Regression statistics

Multiple R ,R ,Standardized R ,Standardized error ,

F F-test, ,

Coeffi cientsY-intercept -,X ,X ,X ,X ,X -,

The linear model equation takes the following form:

Y = ,X + ,X + ,X + ,X–,X–,

The determination coeffi cient is very high with acceptable value of F-test which indicates model’s reliability. However, GRP shows only a minor dependency with the dependent variable. This rules out the original hypothesis and, subsequently, all of the factors included in the GRP-model are excluded from the main model.

Final variables:

. Expenditures of federal units — an aggregated sum of all the region’s expenditures.

. Financial resources lacking for the average level of fi scal capacity — the volume of funds which are necessary for a region to be subsidized with.

. Number of municipal units — number of populated local self-governed territories.

. Budgetary expenditures index — ratio of region’s expen-ditures to the state’s expenditures. Is calculated as: (Re-gional expenditures/Regional population) / (State expen-ditures/Country’s population)

The analysis showed the most signifi cant correlation index be-tween governmental subsidies and fi nancial resources lacking for the average level of fi scal capacity (X). Accordingly, GRP per capita (X) has small correlation of , with the dependent var-iable which again rules out the original hypothesis of subsidiz-ing the regions with the most economic development utility. However, further investigation will be based on the hypothesis of the dependency between the volume of subsidies and GRP not in statics, but in dynamics.Table . Regression statistics (linear model)


The nonviability of the linear model indicated that the shift to exponential model was necessary, followed by taking the loga-

I. M, Q M C R R F

rithm of all variables. The regression analysis proved the expo-nential model to be more proximate.Table . Regression statistics (exponential model)


F F-test, ,

Coeffi cientsY-intercept -,X -,X ,X -,X ,

The exponential model equation takes the following form:

Y = ,X(–,) X, X(–,) X,

t-statistics P-Value-, ,-, ,, ,

-, ,, ,

In comparison with P-Value, t-statistics shows the signifi cance of all of the factors included in the model with t-statistics ex-ceeding the P-Value for every factor. The viability of the model was also proved via calculating the F-test and collating it with the table F-test for the level of signifi cance of = ,. Thus, the measured value of the F-test = , exceeds the table value of F-test = , and is proved to be signifi cant.Table . Dependent variable responses

% increase Y variation % decrease Y variationX+% % X–% -%X+% % X–% -%X+% % X–% -%X+% -% X–% %

The model was also approbated for how the dependent varia-ble will react if a chosen factor is varied (increased or decreased) by %. Accordingly, the increment in the fi nancial resources un-der the average level of fi scal capacity by % results in the in-crease of the level of subsidies by %. The dependent variable gives the most signifi cant response on the change of the fi nan-cial resources under the average level of fi scal capacity.

S

Without a confi rmation in statics, the hypothesis regarding the infl uence of GRP on governmental grants was researched in dy-namics. The data on subsidies, GRP and the level of fi nancial re-sources lacking for the average level of fi scal capacity from to was collected for statistical series.

Quarterly GRP records were cleared out of seasonality to con-duct research on multiplicative and additive models. The results revealed that the correlation coeffi cient (Table ) between GRP and subsidies is of negligible importance and is negative, i. e. sig-nifying inverse relationship.Table . Correlation between GRP and subsidies

Subsidies GRPSubsidies GRP -,

The greatest response in comparing yearly unchanged data was retrieved while analyzing the polynomial trend line — R = ,.

y = 0,157x + 448,57R² = 0,173

500 000

750 000

1 000 000

1 250 000

1 500 000

1 750 000

2 000 000

2 250 000

2 500 000

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

I. M, Q M C R R F

Subsequently, the research continued with the series of dy-namics cleared of the time factor.

In doing so, no dependence was uncovered even with a time lag in one or more period. This led to the conclusion that an in-crement in GRP does not impact an increase in governmental grants. Thus, the hypothesis regarding the infl uence of GRP on the dependent variable was not confi rmed neither statics nor in dynamics. The following analysis focuses on the fi nancial re-sources lacking for the average level of fi scal capacity and its de-pendence with the subsidies.

In Table correlation coeffi cient can be seen with original ob-servations from to .

Table . Correlation matrix

Subsidies Lacking fi nancial resourcesSubsidies Lacking fi nancial resources -,

Not being able to expose a trend with base data, a dependence was revealed when conducting research was cleared out of the time factor but with a minor response. However, when imple-menting a time lag in period ( year), a linear trend with a de-termination coeffi cient of , was displayed. This indicates that the change in subsidies reacts to the change in lacking fi nancial resources with one period lag, while their unipath does not infl u-ence the dependence between factors. Moreover, the correlation

coeffi cient (Table ) equal to –, implies a signifi cant inverse relationship.Table : Cleared of time correlation matrix

ΔLacking fi nancial resources ΔSubsidiesΔSubsidies ΔLacking fi nancial resources -,

The subsequent regression analysis on the dependency be-tween governmental grants, lacking fi nancial resources and time revealed a high correlational dependence.Table . Regression statistics

Multiple R , Coeffi cientsR , Y-intercept ,Standardized R , Year ,

Standard error , Resources lacking -,

After the trend was cleared of the time factor, R suff ered a mi-nor drop (,). Therefore, the dependence between the depend-ent variable (subsidies) and factor (lacking fi nancial resources) is present separately from time.

C

To sum up, during the research was conducted via correlational-regression methods it was found out that Russian government primarily focuses on the level of fi scal capacity of the region and

Δy = 0,0026Δx - 106,71R² = 0,0165

-4000

-3000

-2000

-1000

0

1000

2000

3000

4000

5000

0

5000

0

1000

00

1500

00

2000

00

2500

00

3000

00

3500

00

4000

00

ΔY = 0,0002ΔX + 58,192R² = 0,3829

-4000

-3000

-2000

-1000

0

1000

2000

3000

4000

5000

-20000000 -15000000 -10000000 -5000000 0 5000000 10000000

I. M, Q M C

not economic development utility. Without a correlational de-pendence in static model, an attempt to reveal it in dynamic model took place. Clearing the data from false correlation, the re-sponse was negligible (R–,) that contradicted the hypothesis of achieving maximum economic utility. In a similar way, re-searching the lacking resources revealed that the largest re-sponse is present with a time lag in one period (R–,).

Thus, it was proven that GRP and economic development of the region are not taken into account as a priority while imple-menting subsidies allocation policy due to the importance of un-even fi scal capacity. Additionally, qualitative factors (e. g. geopo-litical factors) which cannot be included in the model are still of signifi cance to the subsidies` allocation between the federal units of the state. Furthermore, the research above can be a ground for further study.

R

. Belousova, A. V. (). Federal subsidies assessment on the dy-namic of diff erentiation of the fi scal capacity in Russian Federa-tion. Habarovsk: fi nanci, credit, denezhnoe obrachenie.

. Matrusov, N. (). Regional planning and regional development of Russia. Moscow: Nauka.

. Ministry of Finance of Russian Federation. (). [online]. Available at: https://www.minfi n.ru/ru/

. Ovsyannikova, S. N. (). Statistics for second-year students of economic specialties.

. Open budget of the Krasnodar crai. (). [online]. Available at: http://openbudgetregion.ru/

. Federal service of governmental statistics. (). [online]. Available at: http://www.gks.ru/

. Russian Federation Budget Code from .. #-Federal law (edited ..). [online]. Available at: http://www.con-sultant.ru/document/cons_doc_LAW_/abcd-cafeafccbbfdd/

Factors infl uencing technology innovations costs

S V,R MStudentsRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

S OAssociate ProfessorRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

A

This article considers the most infl uential factors of technological innovations costs in regions of Russian Federation. The most signifi cant factors are analyzed. By the use of correlation and regression analysis a multifactorial linear model is constructed. The accu-racy of the constructed model is proved by high coef-fi cient of determination R value. The paper demon-strates analysed indicator’s growth over time. The re-lationship between the researched indicator’s and its most signifi cant factor’s series is analyzed. Recom-mendations are made on technological innovations costs management with a view to increasing the effi -ciency of its implementation into production.

Keywords: science, technologies, innovation, cost of technology, correlation and regression anal-ysis, linear model.

I. M, Q M C F

I

The aim of this research is to identify the factors that infl uence the amount of money fi rms allocate on technologies and innova-tions in diff erent regions of Russia. Correlation and regression analysis were used.

This article investigates the factors infl uencing technological innovations costs in regions of Russian Federation. Data bas-es provided by the Federal State Statistics Service. In the modern world, investment in science and technology can be a tool for long-term development and can be vital in pursuing the goal of economic growth. Thus, the government is interested in the de-velopment of digital economy. The costs vary in diff erent regions, so twelve factors were selected, that allegedly aff ect the budget allocation.

R

Based on logical assumptions twelve factors were selected for conducting the research:

• x — The amount of innovative goods and services;• x — Innovative activity of organizations (percentage of or-

ganizations which develop technological and marketing in-novations);

• x — Internal R&D expenditure;• x — Number of research scientists with a degree;• x — Number of personnel doing R&D;• x — Organizations doing R&D;• x — Population;• x — GRP;• x — Number of educational organizations;• x — Number of teachers in organizations that provide pri-

mary, basic and secondary general education;• x — Number of students with a certifi cate of basic general

education;• x — Number of students with a certifi cate of secondary

general education.

Y X X X X X X X X X X X X

Y X . X . . X . . . X . . . . X . . . . . X . . . . . . X . . . . . . . X . . . . . . . . X . . . . . . . . . X . . . . . . . . . . X . . . . . . . . . . . X . . . . . . . . . . . .

The analysis of the factors was produced in order to identify those whose infl uence on the costs is more signifi cant.

Matrix of pair correlation analysis identifi ed that the depend-ent variable (costs) has the following association with the factors:

The data presented above shows that such factors as X and X, X and X, X and X are associated stronger in comparison with the resulting factor, thus it is necessary to exclude them from the model.

Factors X and X are excluded because they have a weak asso-ciation with the resulting factor.

Linear and exponential models were constructed. The former showed higher coeffi cient of determination (R=,) than the latter (R=,), which means that the linear model describes the data in the most effi cient way.

Coeffi cientsIntercept -.x .x .x -.x .

Y=,x+,x–,x+,x–,

I. M, Q M C F

The resulting equitation describes the linear relationship be-tween the costs of innovation technologies and four selected factors. The model demonstrates the infl uence each of the four factors has on the result. Thus, a one unit change in the volume of innovative goods and services will lead to the shift of costs of ,; a one unit change in domestic expenses on research and development will have a shift in costs of , as a consequence; the increase of the population of one million people will lead to the decrease of costs of ,; and the increase of the GRP will raise the costs by ,.

Coeffi cient of determination is used to assess the effi ciency of the model:

Regression StatisticsMultiple R .R Square .Adjusted R Square .Standard Error .Observations

R square shows that in % of events the change of the re-sponse variable can be explained by the change of other variables. Other % account for variables that are not considered in this model.

df SS MS F Signifi cance FRegression . .Residual Total

To evaluate the statistical signifi cance of this model Fisher cri-terion is used. Signifi cance F which is . confi rms the representativeness of the model.

The linear model was modifi ed into the standardized scale to compare non-dimensionalized values.

The standardized scale of the linear model:

Coeffi cientsIntercept (x — x mean)/ .(x — x mean)/ .(x — x mean)/ -.(x — x mean)/ .

y = ,t+,t–,t+,t

Regression StatisticsMultiple R .R Square .Adjusted R Square .Standard Error .Observations

To determine the infl uence of one variable, namely GDP on re-sponse variable (technological innovations costs) over time, time-series analysis is made. Factors’ reliance on time analysis shows high coeffi cient of determination.

The analysis of relationship between factors over time also shows high coeffi cient of determination. To eliminate the infl uen ce of time and detect spurious correlation chain base method is used.

x = 55.012t2 - 138.17t + 448.34R² = 0.9937

x = 1072.1t - 4191R² = 0.9229

-5 000

0

5 000

10 000

15 000

20 000

25 000

0 5 10 15 20 25

GDP (t)

y = 2.6468t2 - 18.791t + 40.046R² = 0.9784

y = 39.438t - 183.17R² = 0.8649

-200

0

200

400

600

800

1000

0 5 10 15 20 25

Technological innovations costs (t)

I. M, Q M C F

Produced coeffi cient of determination shows that the correla-tion between two variables was due to time. It is assumed that technological innovations costs in the current period depend on

the level of GDP in the previous period. The coeffi cient of deter-mination has increased up to , which confi rms the hypothesis.

C

The correlation and regression analysis helped in determining the factor which causes the change of technological innovations costs to a greater extent — gross regional product.

Time-series analysis shows that technological innovations costs in the current period depend on the level of GDP in the pre-vious period.

Several measures are introduced in order to increase the tech-nological innovations availability:

• To increase access of small and medium-sized businesses to the procurement of innovative products

• To increase debt fi nancing of innovative projects.• To develop technology commercialization mechanisms and

to increase its effi ciency.• To ensure the development of innovative projects direct

funding methods.

R

. Russian Federal State Statistics Service URL: http://www.gks.ru (accessed on: ..).

. Ovsiannikova, S. () Statistics: Student Book // M: Econ-form.

. Egorova, M. () Technological innovations as the basis for changes in economic technological structure//UEkS. № (). URL: https://cyberleninka.ru/article/n/tehnologicheskie-inno-vatsii-kak-osnova-izmeneniya-tehnologicheskoy-struktury-ekonomiki (accessed on: ..).

. Ovsiannikova, S. () Econometrics: Students Book // M: Delo.

. Salgiriev, R. () Technological innovations costs analysis in Russia // Terra Economicus. № –. URL: https://cyberleninka.ru/article/n/analiz-zatrat-na-tehnologicheskie-innovatsii-rossiyskih-predpriyatiy (accessed on: ..).

y = 0.0375x - 34.773R² = 0.9763

-100

0

100

200

300

400

500

600

700

800

0 5 000 10 000 15 000 20 000 25 000

y(x)

Δy = 0.0232Δx + 12.641R² = 0.1693

Δy = 0.0448Δx - 7.4795R² = 0.6515

-50

0

50

100

150

200

-1 000 -500 0 500 1 000 1 500 2 000 2 500 3 000 3 500

I

Investigating potential tourism strategies for promoting the rich cultural heritage of the Republic of Dagestan

D DSenior LecturerRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

D M M. VProfessorCentre of Humanitarian educationMoscow Polytechnic University, Moscow

D R AProfessorDagestan State University, Makhachkala

H AHead directorDagestan Training Centre, Makhachkala

Y EGlobal Head of Customer Content and Advocacy MarketingUnify, Sofi a

A

This paper initially provides a summary of the mul-tiple streams of tourism potential in Dagestan and discusses the importance of tourism in socio-eco-

nomic development. Further to this and in essence, this research triangulates three distinctive streams of information, namely, () information provided by the Ministry of Tourism and Ethnic Arts and Crafts of the Republic of Dagestan, () information sourced from online sources and academic databases and () a short pri-mary investigation with experts from the hospitality and tourism sectors. Lastly, recommendations are provided for further devel-oping the tourism sector while taking into account the primary research fi ndings and industry literature.

Key words: The Republic of Dagestan; Northern Caucasus; in-novative tourism strategies; digital tourism strategies

I

The tourism and hospitality industries are of paramount impor-tance for socio-economic developments, as well as for increasing employment (Kurskiev, ). It is argued that the creation of a single job in the tourism industry entails the creation of up to fi ve jobs in related industries (Andreyanova and Ivolga, ). In Russia, statistics show that in , the tourism industry has con-tributed with . trillion rubles (approx. billion US dollars), the equivalent of .% of all exports, thus aff ecting related in-dustries (Dagestata, ). A place of great tourism potential in southern Russia is the Republic of Dagestan. This paper will dis-cuss various intricacies of the hospitality and tourism industries in Dagestan and present various strategies for cultivating this sector. Firstly, it will provide an overview of the republic of Dag-estan and its tourism potential. Secondly, the methodology is briefl y described and recommendations are presented based on primary fi ndings. Lastly, further recommendations are provided to suit the touristic potential.

T R D

With a total surface of , sq.km and a population of just over million people, Dagestan is a mountainous region with good ac-cess to the Caspian Sea. Located in the north-eastern Caucasus

I. M, Q M C I

region, it was previously known as ‘Albania’ or ‘Caucasian Alba-nia’. This is the most multi-ethnic region of the Russian Federa-tion. Many tribes have lived here for centuries and have learnt to coexist in harmony thanks to the unwritten laws of hospitality.

Since ancient times, the tribes which inhabited present-day Dagestan were Turruk, Lulubei, Okhtong, Sarmatians, Scythians, Caspians, Kassites and other; presently, the main tribes living here are Avars, Kumyks, Darghins, Lezgins, Varnishes, Tabasarans, and Nogai. Each tribe and ethnicity has its own language, tradi-tions and cultural traits, and the Russian language is used as the lingua franca. Although each tribe has distinctive beliefs and tra-ditions, hospitality laws are rigorously respected by all, acting as a moral code in the mountains. Hospitality is present even in folklore and literature, which include the Kumyk “Bogatyr Kart-Kozhak and the beautiful Maksuman”, the Avar “Hochbar”, the Nogai “Batyr Amit, the son of Aysyla” and many more (Akhme-dova, ).

Guests are a symbol and value reference point for most tribes and almost all literature heroes are portrayed as possessing not only a cult of high heroism but also as having an increased cult of hospitality towards guests, thus crafting a hospitality-focused culture (Akhmedova, ). The Avar ‘Hochbar’ song of the th century dictates that a person could be punished for violating any law of hospitality — ‘violators of the sacred laws of the mountains and hospitality would burn in fi re’ (Magomedbekov et al., ). It could be argued that hospitality is in the blood of every Dagestani, and many claims suggest that there is always

room for an extra guest in a Dagestani household. Traditionally, urban households have been hosting ‘kunaks’ from neighbouring villages for centuries. ‘Kunaks’ are people from villages, yet it is commonly translated into brother, sister, or relative. It is also the tradition here that every guest, regardless of their nationality or faith, should always be provided with the best food and a joyful welcome. An entrenched rule in the minds of locals is that guests should be served fi rst; this acts as an important basis for the de-velopment of tourism in Dagestan, especially the ethno-gastro-nomic one.

The tourism potential of Dagestan

The Republic of Dagestan has signifi cant touristic and recrea-tional resources and is one of the few places in Russia which fea-tures a combination of many unique factors, such as varied land-scapes, good climate, mineral springs, therapeutic muds, sandy beaches, mountainous regions, cultural heritage sites, and many more, whose potential is not yet used at their full potential. Tour-ism is one of the most promising sectors for developing the econ-omy of Dagestan and the government intends to build appropri-ate infrastructure to be able to host more than a million tourists annually, which would entail an additional billion rubles and more than k new jobs. If successful, this will allegedly solve social and economic problems and also increase the welfare lev-el of the population. There are multiple types of tourism in Dag-estan, namely, ecotourism, beach tourism, medical tourism, eth-no-cultural tourism, sport and extreme-sports tourism, gastro-nomic tourism, religious tourism, mountain tourism, and cultural heritage tourism; each is provided with a brief descrip-tion below.

Ecotourism — Ecotourism in the Republic of Dagestan in the medium term can be up to thousand people per year. The rich variety of fl ora and fauna from Dagestan has no equal in Russia (Magomedbekov et al., ); from subtropical forests close to the river Samur, the desert and semi-desert in the North of the Republic, to alpine tundra and glaciers. The fl ora of Dag-estan has about species of plants, including many endem-

I. M, Q M C I

ics and relics. The rich and diverse fauna includes species of mammals, species of birds and species of fi sh, including sturgeon. Other unique natural landscapes include Sarah-Kum barchan (m height, being the most unique detached barchan), mount Pushkin-Tau (Kayakent district), the Karadahskaja Gorge (Gunibsky district), the Grand Canyon of Sulak, the Samur Huch-ninskĳ waterfall, and the Mount Bazardüzü mountain.

Beach tourism — The length of the Caspian Sea coastline is kilometres with extensive sandy beaches, warm sea and ionized air. Currently, there are beaches in the Republic ( more than in ) totalling a length of meters of natural sea beach in the cities of Makhachkala, Izberbash, Derbent, Kaspiysk and Kayakent. What is also unique in Russia is that in Dagestan the bathing sea-son lasts for days per year. In , the number of tourists vis-iting the Caspian Sea coast amounted to about thousand peo-ple. In the summer months, the occupancy of most hospitality es-tablishments is close to %, and the main visitors are from either Dagestan or from the neighbouring regions of Russia.

Medical tourism — Dagestan houses more than balneolog-ical resorts and the government intends to focus on developing more, in its aim to support the health improvement of its citizens, as well as to attract visitors interested in this kind of tourism. The SPA services contributed to the economy with a total of . million rubles in . Further regarding Dagestan’s uniqueness, there are about mineral water sources and a number of ther-apeutic mud deposits scattered throughout the country. Also, the

‘Talgi’ resort is the only resort in the world which uses a therapy based on sulfi de high-water containing hydrogen sulphide. There are claims which suggest that the water quality has the gift of treating musculoskeletal system, dermatological, gynaecological and neurological diseases.

Ethno-cultural tourism — Dagestan is a multinational republic which unites nationalities. The culture and traditions of the people of Dagestan are very diverse and were formed over the years and passed on from generation to generation. Each of these nations has its own characteristics and diff erences, which shapes their identity. Folk traditions in many areas, especially in the vil-

lages, are well preserved. Very interesting are the weddings in the villages of Khuduts, Duakar, Kischi, Chishili, Harbuk, and many more. Dagestan is also a centre for the development of unique folk art crafts. On its territory are manufactured jewellery (c. Kubachi, Dakhadayevsky district, Gocatl district, Khunzakhsky), carpets (Tabasaran district), woodwork (Groznyy, Untsukulsky district) and ceramics (Balkhar, Akushinsky region) and many other craft prod-ucts. Dagestani tourism offi cials understand the value of their eth-no-cultural tourism potential, and claim that in order to further develop their folk, arts and crafts, it is necessary to integrate them into the tourism industry by creating specialized tourist complex-es with full tourism infrastructures, such as accommodation facil-ities, catering, trade-in folk arts and crafts, and master classes. Currently, in the Republic of Dagestan, there are more than small and medium-sized enterprises producing products of folk art crafts. In total, more than , people are employed in the fi eld of folk arts and crafts, including more than individual entre-preneurs. In , individual entrepreneurs in the fi eld of folk arts and crafts received grants and as a result, in , the manufac-turing volume of national art crafts products amounted to . million rubles.

Sport and Extreme-sports tourism — Khabib Nurmagomedov’s recent UFC victory has improved Dagestan’s sports tourism branding and there are claims suggesting that Dagestan has suit-able conditions for training athletes of diff erent ages and fi tness levels. Nonetheless, when accessing Dagestan’s Wikipedia page, under the ‘notable people’ section, out of people mentioned, of them are world champions in wrestling, MMA, UFC, boxing, Muay Thai, or other sports (Wikipedia, ). This can only mean that Dagestan has appropriate training grounds for sports cham-pions. Extreme tourism is becoming popular amongst young peo-ple who are no longer interested in the traditional forms of tour-ism. Dagestan has lots to off er in this area too, having activities such as hang gliding, kitesurfi ng, paragliding, rafting, jeeping, and canyoning. Furthermore, regional, Russian and internation-al competitions in mountaineering, rock climbing, rafting, and kitesurfi ng are held in Dagestan.

I. M, Q M C I

Gastronomic tourism — The variety and unique recipes of tradi-tional Dagestani dishes are a signifi cant factor in attracting new tourist groups to the republic. Both domestic and foreign tourists are showing a keen interest in Dagestani cuisine. This segment of tourism was underdeveloped until recently and became popular among tourist groups. This year, the capital city of Makhachkala hosted the second international culinary championship; having attracted abundant media attention, this will allegedly support further development for this niche. However, there are certain is-sues related to further development, such as the poorly developed infrastructure and of the catering facilities in rural areas, the lack of trained personnel, sanitary and epidemiological issues, and an insuffi cient amount of promotional materials for the development of gastronomic projects in rural municipalities of the Republic.

Religious tourism — Religious tourism should not be neglected. The Djuma mosque, which is one of the fi ve oldest mosques of the world (–) is considered to be one of the main reference points of the spread of Islam in Russia.

Mountain tourism — In Dagestan, there are peaks, the height of which exceeds m. These are covered with non-melting snow and glaciers, and a large number of turbulent rivers. On the territory of southern Dagestan there is a unique mountain com-plex of great interest to climbers (Shalbuzdag — m, Bazard-yuzi — m and Yarydag — m above sea level), where Russian Championships in mountain sports of all categories and complexity levels take place. These peaks are distinguished by an abundance of Sun, ultraviolet radiation and the lack of winds and fogs.

Cultural heritage tourism — The cultural heritage of Dagestan also deserves a special place in the Russian Federation. Dagest-an has cultural heritage sites (historical and cultural mon-uments), of which are cultural heritage sites of federal sig-nifi cance and , units of regional signifi cance, including his-torical and architectural complexes. There are numerous monuments of history and architecture, for example, the Naryn-Kala fortress, the Ahulgo mountain (place battle Shamil), the vil-lage of Kubachi, and many museums (Museum of local lore, Art Museum, etc.). Dagestan also houses Derbent, the most ancient

city in Russia and one of the oldest in the world. Derbent and its fortress are included in the natural heritage of UNESCO.

Statistics about tourism in Dagestan

In recent years there has been a positive increase in the major in-dicators for the tourism industry, having an annual domestic and international tourist growth of more than %. Within the last four years, the tourist fl ow in Derbent, an ancient city of Dagestan, has more than tripled; in , when celebrating the th anni-versary there were around . tourists and in , more than .. More information related to the industry growth is pre-sented in appendix . The most visited tourist site of Dagestan in was the Sulak canyon, having more than . tourists. The number of foreign tourists in was . thousand people, mainly from Greece, Cyprus, Iran, U.A.E., and China.

Some estimates claim that Dagestan has a recreational capac-ity of more than . million tourists/year, and according to dag-stata, the volume of paid tourist services amounted to billion rubles. Having collective accommodation establishments to-taling beds, these include tourist base, health insti-tutions, hotels, and guesthouses.

The most popular period is from the end of April until the be-ginning of October, that is, the peak of the tourist season and the average tourist age is to . The amount of money that tourists spend in Dagestan depends on the duration of the trip and the pur-pose of their visit. The average spent per day on a tourist route is rubles (equivalent of $.) which includes transport, tour escort, tour guide, and lunch. A further rubles (approx. $) is spent on accommodation and rubles ($.) on dinner. This is signifi cantly cheaper than most places around the world and this fact should be valued through promotional campaigns.

Tourism strategies in Dagestan

Dagestani offi cials understand the need to improve the safety, ac-cessibility and comfort of Dagestan. Tourism strategies include the construction of new accommodation facilities, modernising

I. M, Q M C I

its infrastructure, as well as building more roads and recreation-al tourist special zones. There are also aims to attract suffi cient investment to build ski resorts and more recreational complexes. In , the ministry actively participated in international tour-ist forums, exhibitions and fairs, such as the Fitur (Madrid), ITB (Berlin), the Russian-Bulgarian Tourism Forum (Sofi a), and the MITT (Moscow), where they claimed to have distributed more than thousand advertising materials which included brochures, fl yers, guides, tourist cards, and DVDs in English and in Manda-rin Chinese. Furthermore, later this year, numerous forums are scheduled to take place in Dagestan, namely ‘Open Dagestan’, the

‘International Maritime Forum’, as well as a regional fi shing com-petition. The Republic has also established an independent agen-cy responsible for the development of the tourism industry, whose work includes the implementation of state policies in the fi eld of tourism, creating conditions for developing the infra-structure and attracting investments. Their future development strategy is encompassing two stages, namely, the ‘complementa-ry’ stage (planned for the period of –) and the ‘progres-sive development’ stage (planned for the period of –). The complementary stage focuses on developing the beach, eth-no-cultural and medical types of tourism, and the progressive de-velopment stage will focus on infrastructural developments.

Barriers encountered in the tourism industry of Dagestan

However much tourism potential Dagestan has, the negative pub-lic perception about the socio-economic and political situation in Dagestan acts detrimental for developing this sector. When Googling the word ‘Dagestan’, the fi rst link to appear is Wikipe-dia’s ‘Dagestan’ webpage, followed by main attractions, and thirdly, under the ‘People also ask’ section, the most common question asked is ‘Is it safe to visit Dagestan?’. The answer is:

‘Dagestan is not a safe tourist destination by any stretch of the imagination. The mountainous areas of the republic (i. e., the most interesting areas) have seen major military operations in recent years between various groups and the Russian military’

Needless to say, that this message acts against all major eff orts undertaken by Dagestani tourism offi cials. As this paper will lat-er reveal, the majority of the respondents felt that it was going to be a ‘not quite safe’ place before their visits, and felt that it was a relatively safe place after their visits. For this purpose, sets of measures aimed at creating a positive image of Dagestan should be assumed, with coverage on Russian and international media channels. Further to this, other shortcomings include low levels of customer service and a lack of modern infrastructure.

M M

Data collection

The information provided in this article was collected from both primary and secondary sources. The aforementioned secondary information was sourced from the scarce literature found in aca-demic databases, online websites and, most importantly, infor-mation provided by the Ministry of Tourism and Ethnic Arts and Crafts of the Republic of Dagestan.

The primary data was collected from world-renowned chefs, each with a vast experience in the hospitality and tourism sec-tors, through an online Survey Monkey questionnaire (), print-ed questionnaires () and semi-structured interviews (). All re-spondents were approached during the nd international culinary championship held in Dagestan. The questionnaire (appendix ) consisted of nine questions and it was printed in both English and Russian languages, because not all respondents spoke fl uent English. The questions aimed to be simple, as the respondents’ available time was limited, but relevant for sharing their exper-tise in the context of developing tourism strategies for the Re-public of Dagestan. The completion time was not measured in de-tail, but an average estimate would suggest that respondents spent circa – minutes on completing all questions.

Questions – were used to identify the nationality of the re-spondents, their job title and how many years of experience they have in the fi eld of hospitality. Questions and assessed the re-spondents’ perception about how safe it felt to visit Dagestan be-

I. M, Q M C I

fore and after their visits; both questions employed the same fi ve-point Likert scale, being not safe at all, and being very safe. Because question enquired how safe the respondents per-ceived Dagestan before their travels, a sub-question was asked here in order to understand what channels infl uenced their per-ception the most. Question aimed to identify what did the re-spondents enjoy most when visiting Dagestan and question was designed to investigate what should be improved in Dagestan for future tourists and any constructive criticisms they want to men-tion. Question asked respondents to mention as many recom-mendations as they could think related to developing the tour-ism industry in Dagestan. Ultimately, the purpose of question was to provide the respondents with the opportunity of sharing further comments related to tourism strategies or their visit ex-perience.

The aforementioned questionnaire was used as a starting point and open framework for the semi-structured interviews, and allowed a more in-depth understanding about the theme through following topical trajectories with the interviewees (Saunders et al., ). The average time spent on the interviews was – minutes for each interview. Further to this, the au-thors have also attended round table discussions with high-rank-ing government offi cials who are involved in promoting the tour-ism industry in Dagestan.

F

The respondents’ countries of origin for both the questionnaires and semi-structured interviews include France, Germany, Mauri-tius, Serbia, Romania, Slovenia, Wales, Italy and Macedonia. Hav-ing respondents from countries who have diff erent cultures and opinions towards tourism and hospitality adds value to the opin-ions they expressed. Furthermore, most respondents were WACS (World Association of Chef Communities) international culinary judges or ‘restaurant service’ judges. Besides these titles, most re-spondents have other job titles too, which include President of the National Gastronomic National Association, President of Cu-linary Guilds, culinary advisors, chef consultants, and chef direc-

tors. Although predominantly chefs, these are people who travel very often to judge culinary competitions and who understand the value and intricacies of tourism destinations. With an aver-age of . years (per respondent) of experience in the hospitali-ty and tourism trades, the sum total of their working years totals years. Hence, it is safe to assume that their expressed opin-ions are of great value for this investigation.

When asked about how safe they perceived Dagestan before visiting, with an average of . (– scale), most respondents said that they thought it was not too safe to visit. Their opinions were infl uenced by word of mouth, friend suggestions, media (in-cluding TV and the internet), and foreign government websites. However, they were all sure that they will be safe during their trip, as the event they attended was part of a government funded pro-ject. After their trip, their safety perception increased to . (– scale). This shows that there is a predominantly negative percep-tion about safety when visiting Dagestan, but also shows that people improve their safety perception after visiting.

What the respondents enjoyed most about Dagestan were (in this order): the natural landscapes, the friendliness and hos-pitality of the local people, the food, the traditions, the histori-cal sites, the culinary competition they attended, the freshness and the quality of the ingredients and the music. Similarly, in the most reoccurring order, what the respondents did not enjoy the most were the unpleasant look of the airport and of the roads, the lack of appropriate infrastructure, the squat type lavatories, the visa cost and the challenges associated with obtaining a tour-ist visa, the lack of English signage, the lack of English speaking staff , the lack of trained hospitality staff , and the shortage of in-formation bureaus, souvenir shops and handmade goods.

When asked about what recommendations they wish to pro-vide, the respondents mentioned numerous aspects, clustered as follows:

Infrastructure

• Public places should also have European style lavatories, since this has caused great discomfort; also on this note, it

I. M, Q M C I

was revealed that there should be separate outdoor sanitary facilities for men and women when outdoor events are planned

• There should be more English signage• The airport requires an upgrade. The majority of the tou-

rists are fl ying in to Makhachkala and this is their fi rst im-pression; implicitly, this needs to feel more welcoming and more aesthetically pleasing

• The overall infrastructure and roads need improving, be-cause some respondents felt unsafe when travelling on the roads

• More attention should be paid to the fi ner details related to organising events

Promotion and enhanced visibility on a national and international level

• More online visibility about tourism in Dagestan with in-formation provided in English

• More foreign journalists specialised in food, wine and folk-lore should be invited to Dagestan. Because there is so much that Dagestan has to off er, it would be a good idea to have professionals writing articles about their experience. Three respondents explained that international media should know about how beautiful the Dagestani attractions are, and how hospitable Dagestani people are with foreign visitors. Another respondent mentioned that tourism agen-cies from Russia and abroad should be invited for future events or festivals.

• Similar to the abovementioned point, tourism experts from Dagestan should be attending world tourism events and travel fairs to promote their republic

• Organise events similar to the culinary championship, be-cause everyone seemed to have enjoyed it. One respondent said that there should be a chefs’ association established and arrange annual culinary championships, including a competition based on traditional food.

Investment in education and training

• There should be more English-speaking staff members• There should be better trained staff members in touristic

places. However hospitable local people were seen, it was also mentioned that the customer service level needs to be improved in the service industries

• Taxi drivers should receive some short-course training in customer service.

• It was mentioned that although Russian is the lingua fran-ca amongst the numerous ethnicities living in Dagestan, the English language is the lingua franca for tourism. Two respondents mentioned that, in schools, children should learn English from their early years as well, in order to have a future generation who can welcome and converse with foreign tourists. Also on this note it was mentioned that people working in service industries should speak basic English too; thus, the recommendation is to have basic English courses

• Investment in staff training. Further to just learning basic English, new generations should be trained for the hospi-tality and tourism industries. While some respondents rec-ommended that there should be cookery schools, customer service training centres and hospitality universities in Dag-estan, others mentioned that Dagestan should also off er fi -nancial support for scholarships to send some of its bright-est young minds to train at the world’s top hospitality schools.

Recommendations related to gastro-tourism

• Building up a passionate Dagestani chef to become a posi-tive symbol of Dagestani foods through national and inter-national media exposure (celebrity chef)

• Design a gastro-historic tour around Dagestan, which could also include wine tastings in local vineyards

• Promote Dagestani food products through Russian and in-ternational supermarkets

I. M, Q M C I

• Design gastro tourism packages. One respondent men-tioned that on his trip to Vietnam, when he booked his ho-tel, he was also given the opportunity to have a package that included Vietnamese cookery classes. Something sim-ilar could be applied in Dagestan’s hospitality scene.

Facilitating visa recommendations

• Instead of charging for a tourist visa, the money could be taken from tourists in other forms, including from the tax-ation on the money these tourists spend. Two of the re-spondents mentioned that their visa cost was more expen-sive than their fl ight cost.

Other comments and recommendations

• It is important to consider Dagestan’s Islamic infl uence, where alcohol consumption, although not prohibited, is not common; this is important for designing the visitor profi le.

• For events there should be a better allocation of resources — some respondents felt that in organising events, some things were well catered, but some other aspects were ne-glected

• One respondent felt that there was too much wastage and that people should understand the importance of minimis-ing wastage

• One respondent felt that it was a great idea to have high ranking offi cials and the media visiting these events, as it enhanced the importance of the event.

F

Our investigation shows that Dagestan is a place of great natural and cultural heritage which can form a unique off er on the world tourist market. However, the existing unsolved problems lead to low internal demand and adverse demand on the international tourist market. It can be clearly observed that Dagestan has much to off er with regards to tourism and that it should maximise its

potential. There aren’t many places worldwide which could pride themselves with encompassing ecotourism, beach tourism, med-ical tourism, ethno-cultural tourism, sport and extreme-sports tourism, gastronomic tourism, religious tourism, mountain tour-ism, and cultural heritage tourism in one place. Promotion strat-egies should be considered to maximise the potential of each type of tourism. Although witnessing signifi cant growth YoY, there is still scope for growth. It can be seen that some measures have already been taken into account by Dagestani authorities, and they have planned numerous future strategies. As initial strategies, we recommend touchpoint mapping, value co-crea-tion, visitor profi ling and using appropriate channels to attract them, and more research. After these, a digital strategy is briefl y presented.

Touchpoint mapping — an increasingly growing and simple-to-use concept is that of touchpoint mapping. A touchpoint could be regarded as any interaction between an existing or potential customer with your business, before, during and after a purchase decision is made.

Each touchpoint is crucial in forming a positive or negative perception for customers, in this case, visitors. An experience map could also be included in this concept. Arranging these touchpoints on a map provides a holistic understanding from a visitor’s point of view (Ewerman, ). To exemplify, some neg-ative touchpoints identifi ed in this paper were the negative per-

F. . A touchpoint map example (https://mjpdelfi n.wordpress.com/tag/touchpoints/)

I. M, Q M C I

ception related to the safety of Dagestan available after a Goog-le search, the unpleasant aesthetics of the airport, or the impo-lite taxi drivers. As positive touchpoints were the beautiful landscapes, the event that the participants attended, the food, and the hospitality of the people. Each stage shown in the pho-to should be empathetically considered for improving the over-all tourist experience.

Co-creation — co-creation is defi ned as a ‘business strategy fo-cusing on customer experience and interactive relationships which allows and encourages a more active involvement from the customer to create a value rich experience’ (Business Dictionary, ). Within a tourism context, Berrada () explains that co-creation allows tourists to ‘do things rather than just undergo the experience designed by tourism producers and also engage them-selves in activities for self-development, explore multisensory environments, and connect to other people as they are directly involved in creating and choreographing’.

Visitor profi ling and using appropriate channels to attract them — needless to say how important this is. Although the data present-ed claimed that the average age is –, belonging to the mid-dle class cluster, a more detailed profi le should be made. The au-thors suggest that the three main tourist clusters should be national (Russians), international (foreign tourists) and also neighbouring Arab countries who might be interested in religious tourism, a type of tourism which is underestimated in Dagestan. Each type of tourism should have better defi ned customer seg-ments.

More research — research is the foundation of wise business decisions, and more of it should be present on the tourism de-partment’s agenda. This could either be simply questionnaires administered to visitors, similar to the one presented in this pa-per, or it could be funding PhDs or case studies; these could fo-cus on solving the negative perception issues which Dagestan is currently facing. The information could be made available online, in a similar fashion to the one made in Britain (https://www.vis-itbritain.org/-inbound-tourism-forecast). Such information could also help local entrepreneurs and tourism agencies, in or-der to prepare specifi c tourism packages.

D

Digital strategy is of paramount importance in tourism, as it has the potential to empower positive word-of-mouth and en-hance the ‘virality’ eff ect of the information online (Vaish, ). It is also crucial for eff ective communication with the millennial generations (born mid-s to early s) and Z (born s — TBD) who saturate the web population globally (Harel, ). The proposed digital strategy will address several opportunities based on the research fi ndings from this paper:

• Building a positive online reputation• Promoting a safe environment in Dagestan• Improving customer service• Providing relevant English content to serve tourists

The list of country facts (unique selling points) presented above could be used in favor of and around the proposed communication to attract visitors; these include the hospitality of the local popula-tion, the impressive number of historic monuments (), local culture and traditions, good climate, variate landscapes, broad sandy bitches and the most ancient city — Derbent, among other USPs. Portraying the active kinds of tourism should be also considered.

Dagestan’s online presence is somewhat negatively aff ected by the information present on BBC’s website and Wikipedia, warn-ing about the lack of safety. In order to establish a better promo-tion and understanding of the current safe situation in the coun-try, and in order to take control over the information shared on-line, this paper suggests the creation of a state-owned website for tourists in English as well as in the languages spoken by the majority of the tourists. For this purpose, an important role in the online communication could be using the story of “Kunats-kaya” (a room for guests in every home) and “Kunak” (brother), to emphasize the hospitality of the local population.

Dagestan tourist website or blog

The Dagestani tourist website should be available in language s: Russian, English and Chinese, as to cover the major tourist

I. M, Q M C I

groups. It should emphasize the English content also, as it was found that most information shared is in Russian and not many websites are available for English-speaking guests; this is espe-cially crucial when it comes to information around tourism and cultural aspects.

This tourism website would also serve as an online customer service, which was currently marked as unsatisfactory in the re-search fi ndings. Such online service may bring Dagestan’s image to another level and position the country as digitally developing. The website could also provide information around the tourist preparation before and during their stay, the history and cultur-al aspects of Dagestan, the touristic attractions, and even sports achievements, something that the Dagestani population takes pride in. The website could also share more practical information such as how to order a taxi in Dagestan, common Russian words to use on your trip, quality tour operators, digital maps for buy-ing souvenirs or making your way around, information about how to obtain a tourist visa easier, or things to know before interact-ing with the locals.

Once established and after being carefully maintained, the website would gain decent visibility and could be positioned on the fi rst results page using most search engines. However, this action might take some time, as for Google to index the website appropriately and for the web administrators to write the content for the English speakers. Search engine optimization (SEO) with relevant keywords for Google and Yandex should be considered.

Chatbot integration

In –, Facebook, the largest social media platform, has declared .x YoY growth and over billion messages were sent by its over chatbots (Vaish, ). An integrated chatbot on the tourist website may serve as an online customer service assistant, where tourists could pose general questions about tourism in Dagestan. The chatbot could redirect users to the sec-tions within the website or to any other relevant and /or external sources. Chatbots are seen as growing innovation globally and may position Dagestan’s tourism in a better light.

Social media channels — Instagram channel

Instagram is considered as a social platform for visual content, thus becomes relevant to the tourist industry and for the promo-tion of tourist elements. It is important to note that % of mil-lennial travelers globally are active on Instagram and that % of the Instagram population use the platform to fi nd new travel des-tinations to explore (Bayer, ). People on Instagram should be motivated to post high quality content, but also engage with oth-er publishers. Considering the fact that by Millennials will take over % of the workforce globally (Harel, ), it makes sense to target this audience in a narrower way. Instagram should be regarded both as a platform that might stimulate the promo-tion of high-quality content from Dagestan and for targeting cer-tain target groups which are alleged to grow and soon dominate the market. The content on the Dagestan’s tourism Instagram pro-fi le should be consistent and covering topics around the local cul-ture and hospitality, historical sides, beautiful nature, and others.

Potential campaign # — share the Dagestani hospitality

A potential campaign may ask tourists who have fi rst-hand wit-nessed the hospitality of the local population to share their ex-perience on their Instagram profi les. Such content could be or-ganised and shared by the account administrators. To leverage the experience, a prize pool could be funded for those who par-ticipate –e.g. on a lottery principle, participants could be provid-ed with additional souvenirs. This campaign could be promoted both on the tourist website and at the airport via the information stand or virtual screens. To emphasize more about the local hos-pitality, specifi c tags could be used, such as “Kunak”, or “Kunat-skaya.” These should also be supported by more general hashtags, in order to stimulate the virality of the information.

Potential campaign # — photo invitation at key touristic places

A simple request for tourists to share their best photos on Insta-gram from selected hotspots. Those hotspots could be key tour-

I. M, Q M C I

istic places and be marked with special signs — tables with infor-mation and/or special photo frames. The experience could be gamifi ed, so that the more photos from such places the more points users may amass. If the users achieve a certain number of points, they could win a special gift — a traditional coin which they may receive at the airport after showing their uploaded pho-tos to the dedicated staff . This campaign could also be followed by using specifi c country-related hashtags.

More video contents

Quality video content about Dagestan is currently challenging to fi nd on the most popular video platform — YouTube. Especially, there should be educational videos about Dagestan to help poten-tial tourists plan their trip. Worth mentioning is that embedding a video on a website can increase the conversation rates by % and that % of online users are saying that videos have helped them when making purchasing decisions (Unbounce, ). Video con-tent is regarded as the most eff ective communication tool, espe-cially in the world of tourism (Vaish, ). Such videos could be produced to unveil the beauty of the Dagestani nature, the interac-tion with the local people, and also to touch-point critical aspects —the safety levels in Dagestan and things tourists need to know in order to positively change their perception towards Dagestan.

An event for travel bloggers

Another positive impact may be arranged with bloggers — e. g., a video by Max Listov (Russian blogger) was watched nearly times in which he is clearly stating that Dagestan is not a danger-ous country for external visitors (Listov, ). Such a meeting with impactful bloggers could be organized annually — an event where bloggers are invited to travel around the country for free, and in return to share their experience online on their channels.

Creating more testimonials

Advocacy marketing is crucial today (Harel, ), and it repre-sents a form of communication where the users are speaking

about certain products or services, in this case about tourism in Dagestan. Over % of all online consumers are looking for real testimonials on the web before making any buying decisions (PMC, ). Similarly, tourists scout for recommendations and testimonials from others before planning their trip. Such eff orts towards advocacy marketing could go in several directions:

• Uploading real tourist testimonials on the tourist website.• Using tourist platforms such as TripAdvisor to raise Dagest-

an’s profi le.• Working with Dagestani celebrities in sports — written and/

or video testimonials.

Contextual online advertising

The ‘Seattle Times’ study found that percent of all their re-spondents viewed advertising as valuable when the ads were rel-evant to the page content (Vaish, ). Dagestan’s tourist web-site could be possibly advertised on other travel portals to at-tract relevant users. To pilot the project, the contextual advertisement could target Russian websites, in order to better understand if such an approach is eff ective and what KPIs should be addressed.

L

There are numerous limitations to this investigation. Firstly, the primary research could have been made on a much larger scale in order to get a better understanding of the investigated issues. Secondly, the information found about Dagestan was scarce and limited. To tackle this, more research should focus on Dagestan and its tourism. A good starting point in changing the negative perceptions could be a thorough investigation of other countries which suff ered similar negative perceptions, but have recovered relatively quick (e. g. Armenia). Another shortcoming could be that the information provided by various parties might not be thorough enough.

I. M, Q M C I

C

With great tourism potential in the categories of ecotourism, beach, medical, ethno-cultural, sport and extreme-sports, gastronomic, religious, mountain, and cultural heritage tourism, Dagestan lots to off er. Its potential should be maximised to a better extent. Al-though there are numerous strategies planned for the periods of – and –, our primary fi ndings should also be taken into consideration. As main frustrations, the respondents suggested that non-squat type lavatories should be present in pub-lic places, there should be more English speaking staff and more English signage, the airport and overall infrastructure need aes-thetic improvements, and more focus should go towards improv-ing the customer service and staff training. As recommendations, the respondents suggested more online and social media visibili-ty, more investment in staff training and customer service, design of tourist packages with specifi c off ers for the various types of tourism, and a better allocation of resources to suit tourists’ needs.

Further to these, the authors suggest that more attention should be attributed towards empathising with the target mar-kets through touchpoint mapping and co-creation, market seg-mentation should be more comprehensive for every tourism type, and more research should act consultative in making future de-velopment decisions. Lastly, the digital strategy section recom-mended the creation of an offi cial tourist website or blog and so-cial media (Instagram) accounts with chatbot integration and video content to enhance the emotional branding of Dagestan, as well as contextual online advertising, and visitor testimonials.

A

The authors would like to show their sincere gratitude to a num-ber of people who made this research possible. Firstly, to Dr Makhach Vagabov for organising the nd International Culinary Championship, part of the ‘Visit Dagestan’ project. Many thanks to Vitaly Demchenko for providing relevant information needed for this paper and to Leonid Gelibterman and Nikolay Baratov for sharing their passion for gastronomy and tourism. Nonetheless,

many thanks to the inspiring chefs who contributed with their recommendations: Domenico Maggi, Carol James, Alan and Mar-ilyn Payen, Iztok and Irena Legat, Uwe and Annette Michel, George Kostic, Draghitsa Lukin, Maria Shramko, Michel Lenz, David and Oksana Israfi lov, Kumsiyat Mirzayeva, and Adriyana Alachi.

B

. Akhmedova, R. () The unwritten law of hospitality in Dagest-an as the core of artistic synthesis and spiritual unity of diff erent peoples. Makhachkala: Unpublished Thesis.

. Andreyanova, S. and Ivolga, A. ()‘The tourism potential of the North Caucasus: the formation, characteristics and devel-opment prospects’, GeoJournal of Tourism and Geosites. (), pp. –. DOI ..

. Bayer, J. () Instagram for Tourism Marketing: How to Boost Likes, Views and Visitors in [report] [online]. Available at: https://www.convinceandconvert.com/research/instagram-tourism-marketing/ (Accessed on: April ).

. Berrada, M. ()‘Co-Creation of the Tourist Experience via In-ternet: Towards Exploring a New Practice’, Journal of Interna-tional Business Research and Marketing. (), pp. –. DOI: ./jibrm.–.... URL: http://dx.doi.org/./jibrm.–....

. Business Dictionary () Co-creation. [online]. Available at: http://www.businessdictionary.com/definition/co-creation.html (Accessed on: April ).

. Dzhamaludinova, N. М. ()‘Organisational and economic as-pects of Seaside-Mountain type of tourism development in the Republic of Dagestan’, Strategy of sustainable regional develop-ment in Russia. , –.

. Gardner, J. () Why Contextual Advertising Just Makes Sense. [online]. Available at: https://www.businessinsider.com/why-contextual-advertising-just-makes-sense-– (Accessed on: April ).

. Harel, T. () How Do Customer Testimonials Infl uence Pur-chasing Decisions? [online]. Available at: https://www.spectoos.

I. M, Q M C

com/how-do-customer-testimonials-infl uence-purchasing-de-cisions/ (Accessed on: April ).

. Kurbanova, M. () Битва шефов (Battle Chefs). [online] Available at: http://dagpravda.ru/obshestvo/bitva-shefov/ (Ac-cessed on April ).

. Kurskiev, Т. G. ()‘Potential of sustainable tourism develop-ment in the Republic of North Ossetia’, ().

. Listov, M. () The Unknown Dagestan. Goor / Gunib / Khun-zakh village. Stereotypes about Caucasus. [online]. Available at: https://www.youtube.com/watch?v=hicmwegbw&t=s (Ac-cessed on: April ).

. Magomedbekov, G. U., Gadzhiev, M. D., Gadzhiev, E. E. and Vag-abov, M.M. ()‘Preconditions for the Development of Wine-Tasting Tourism in Dagestan’, Ponte Academic Journal, (). DOI: ./j.ponte....

. Matveeva, A. and Savin, I. ()‘North Caucasus: views from within’, People’s Perspectives on Peace and Security. Pp. –. Saferworld, London, United Kingdom.

. PMC () Millennials at work Reshaping the workplace. [on-line]. Available at: https://www.pwc.com/co/es/publicaciones/assets/millennials-at-work.pdf (Accessed on: April ).

. Saunders, M., Lewis P. and Thornhill, A. () Research meth-ods for business students. th edn. Harlow: Prentice Hall.

. Unbounce () The Benefi ts of Using Video on Landing Pag-es [online]. Available at: https://unbounce.com/landing-page-articles/the-benefi ts-of-using-video-on-landing-pages/ (Ac-cessed on: April ).

. Vaish, A. () Five Reasons Why Chatbots are the Future of Customer Service. [online]. Available at: https://www.entrepre-neur.com/article/ (Accessed on: April ).

. Wikipedia () Dagestan. [online]. Available at: https://en.wikipedia.org/wiki/Dagestan (Accessed on: April ).

. Yampolskaya, D. Yu. and Ivanov, S. А. ()‘National identity of the peoples of the North Caucasus: issues and prospects’, Modern science: relevant problems and way of solution. (), pp. –.

An empirical study of water pollution in the regions of the Russian Federation

K B, V S, S V StudentsRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences


A

The paper analyzes the factors aff ecting water pol-lution in the regions of the Russian Federation.

On the ground of the collected statistics, the most signifi cant independent variables that have a considerable impact on the experimental variable were selected by using the correlation analysis.

Water contamination level and spillover of pol-luted effl uents were taken as dependent variables. Two regression models were developed: exponential and linear ones. Sensitivity estimation of the inves-tigated factors was presented. Time series of the factors were constructed, seasonality was examined, the relationships between two time series were an-alyzed.

I. M, Q M C A

On the assumption of the models the actions aimed at improv-ing water quality by infl uencing these factors were off ered.

Keywords: Correlation regression analysis, Exponential mod-el, Linear model, Time series, Seasonality, Ecology, Pollution

I

The problem of water pollution in the regions of the Russian Fed-eration was considered in diff erent spheres , in particular, ac-cording to The Federal Service for Hydrometeorology and Envi-ronmental Monitoring of Russia (Roshydromet), in special-ists registered pollution episodes in the reservoir of the country .

Water pollution is one of the most signifi cant environmental problems nowadays. Therefore, revealing factors having the greatest impact on water contamination level facilitates the fi nd-ing of pollution control measures.

R

Water contamination level (cub. meter) was taken as the depen-dent variable, as for independent variables, they are the spill-over of polluted effl uents (mln. cub. m), the number of factories, the population (country borough ), average income (per month; rub.), withdrawal of water from bodies of water (mln. cub. m), purifi cation plants (mln. cub. m/day), stream runoff (cub. kilometer/year), investment in water conservation (thou-sand rub.), the length of inner accessible waterway (km), oil ex-port (thousand ton), and industrial production index (% of the previous year).

As it was found from the correlation matrix, the most conse-quential factors are the spillover of polluted effl uents, the num-ber of factories, purifi cation plants, and industrial production in-dex.

Not only in chemistry, biology and other sciences, but also in social and eco-nomic frameworks.

ROSHYDROMED () The overlook of water condition and pollution in Russian Federation in .

Y — Water contamination level (cub. meter)

Y — Water contamination level (cub. meter) Х — Spillover of polluted effl uents (mln. cub. m) ,X — Quantity of factories ,X — Population (country borough ) ,X — Average income (per month; rub.) ,X — Withdrawal of water from bodies of water (mln. cub. m)

,

X — Purifi cation plants (mln. cub. m/day) ,X — Stream runoff (cub. kilometer/year) -,X — Investment in water conservation (thousand rub.)

,

X — Length of inner accessible waterway (km) -,X — Oil export (thousand ton) ,X — Industrial production index (% of the previous year)

,

Subject to these independent variables, the linear model was developed.

Y = . + .X + .X – .X + .X

The received determination coeffi cient, equaled ., revealed that only in .% of cases the alteration of the experimental var-iable is connected with the change in independent variables. Thus, it is not the linear dependence but diff erent from it.

SUMMARY OUTPUTRegression StatisticsMultiple R ,R square ,Adjusted R square ,Standard Error ,Observations

Hence, other types of dependences were examined. It was found that the exponential model refl ects the situation in the most appropriate way. To eliminate the least infl uencing factors the following were studied: the spillover of polluted effl uents, the quantity of factories, industrial production index, average in-

I. M, Q M C A

come, withdrawal of water from bodies of water, the population, investment in water conservation, and stream runoff .

Basing on the new correlation matrix, it was decided to ex-clude only one factor, which is the industrial production index.

The exponential model was based on the left seven factors. Thus, the coeffi cients showed that the spillover of polluted effl u-ents, the number of factories, the population, and withdrawal of water from bodies of water are in the positive correlation with water contamination level, meaning that the higher are these in-dicators, the greater is the dependent variable. On the contrary, industrial production index, average income, investment in wa-ter conservation, and stream runoff are in the negative relation-ship: the increase in those factors means the result will decrease.

0.22 0.31 0.61 -0.29 0.15 -0.24 -0.161 2 3 4 5 7 8Y = 0.145X X X X X X X

The new determination coeffi cient equals ., meaning that in .% of cases the modifi cation of the dependent variable is linked with the variation of independent variables. The coeffi -cient is low due to the number of factors which are not connect-ed with the independent variables.


Sensitivity estimation of the investigated factors approved that the most momentous factors are X, X, and X.

% increase/decrease of each vatiable (other factors being equal)

Changing Y

X+% .%X+% %X+% -.%X–% -.%X–% -.%X–% .%

Low determination coeffi cient prompt further research in the fi eld of water pollution. The level of water contamination was the original dependent variable; however, during the analysis spillo-ver of polluted effl uents was found to be more appropriate for the model.

For the new experimental variable factors having more infl u-ence were selected by using the correlation matrix. They are the population, stream runoff , and withdrawal of water from bodies of water.

Y — Spillover of polluted effl uents (mln. cub. m)

Y — Spillover of polluted effl uents (mln. cub. m) X — Quantity of factories ,X — Population (country borough ) ,X — Average income (per month; rub.) ,X — Withdrawal of water from bodies of water (mln. cub. m)

,

X — Stream runoff (cub. kilometer/year) ,X — Investment in water conservation (thousand rub.)водных ресурсов (тыс. руб)

,

X — Industrial production index (% of the previous year)

-,

On this evidence, the regression model was comprised. The re-sult was considerably diff erent from the previous ones. The de-termination coeffi cient was ., meaning that in % of cases the change in the spillover of polluted effl uents is based on the permutation of the chosen independent variables. Consequently, this model is more trustworthy, refl ecting the situation in the country.

Y = –. + .X + .X + .X


I. M, Q M C A

Furthermore, F-test is higher than critical (confi dence level equals .), signifying that the model describes the reality bet-ter than average.

ANOVAdf SS MS F Signifi cance F

Regression , ,Residual ,Total

For more precise further research the standardized regression equation, making possible to compare the regression coeffi cients, was deducted.

t = .t + .t + .t

Obviously, the population (.) has the greatest infl uence on the dependent variable; the next is the withdrawal of water from bodies of water (.). Thereafter, the spillover of polluted effl u-ents can be explained by those two factors.

While examining the coeffi cient signifi cance it was revealed that X (the population) and X (withdrawal of water from bodies of water) are more reliable and signifi cant than X (stream run-off ). Thereby the two major factors were exposed for this model, which is proven by the standardized regression equation.

Hereafter the correlation between the spillover of polluted ef-fl uents, taken as an independent variable, and the number of people caught an enteric infection as the experimental variable was explored. The statistics were taken from to for the Central Federal District.

However, there is a risk of seasonal infl uence. Additive and multiplicative model were developed in order to identify and eliminate it. They showed the absence of any trend, therefore there is no seasonality.

For the estimation of the correlation between factors it was decided to add time to the model. The analysis of the correlation and regression model revealed that time is a nonfactor, which is confi rmed by the standardized determination coeffi cient that vastly diff ers from the determination coeffi cient.


Subsequently, a model without a time element was developed. Almost in % of cases, an enteric fever is caused by contaminat-ed water.

The percentage is quite low. However, other causes of enteric infection, such as hygiene breaches, low-quality products, must be taken into account.

Y = .X +

The considerable reduction of water quality in Russian Feder-ation regions was detected.

The biggest part of independent variables, taken for analysis and model construction are interrelated: the larger is population, the higher is water consumption as well as the number of facto-ries required. Consequently, the spillover of polluted effl uents and withdrawal of water from bodies of water drastically increase.

Recommended measures, contributing to the ecological situa-tion improvement:

. The upbringing of the respect among population towards water resources, which can be developed through imple-menting additional material to school geography course or establishing a new course “Ecology”. (Thus, there will be a formation of conscious generation, possessing basic knowledge about current problems and (required) ecolog-ical behaviour).

. Installation of new treatment facilities as well as renova-tion and regular control of existing ones. This measure is of extremal importance as nowadays there are a few treatment facilities all over the country, moreover, they mostly idle or do not function in a proper way. As a result, the wastewa-ter is not treated as the norms require, hence, remains dirty.

I. M, Q M C

. Reuse of treated wastewater. This facilitates the consider-able saving of water resources and money, both govern-ment and fi rm. However, this measure cannot be accom-plished without the previous one, as it is based on quality wastewater treatment.

B

. gks.ru — Federal State Statistics Service

. mnr.gov.ru — offi cial site of Ministry of Natural Resources and Environment of the Russian Federation

. Myzin A. L., Kalina A. V., Kozytsin A. A., Pykhov P. A. () State and dynamics of changes in the level of regional energy security. Regional economics. [online]. Available at: https://cy-berleninka.ru/article/n/sostoyanie-i-dinamika-izmeneniya-urovnya-regionalnoy-energeticheskoy-bezopasnosti [Accessed on: February ]

. productcenter.ru — site, providing statistics about Russian in-dustrial production

. ROSHYDROMED () The overlook of water condition and pol-lution in Russian Federation in . [online]. Available at: http://www.meteorf.ru/special/product/infomaterials// [Accessed on: February ]

. russia.duck.consulting — Russian Statistics Service

. Salyglar, S. A., Maximova, S. G., and Molodikova, I. N. (). En-vironmental Security And Migration Challenges: A Sociological Analysis Of The Situation In Russian Regions. Society and Security Insights. [online]. Available at: http://journal.asu.ru/ssi/article/view/ [Accessed on: February ]

. Shebzukhova T. A., Vartumyan A. A., Shtapova I. S., Medyan-ik N. V., Zhukovskaya N. P. () Current state and problems of development of the water management in the South of Russia. South of Russia: ecology, development. Available at: https://cy-berleninka.ru/article/v/sovremennoe-sostoyanie-i-problemy-razvitiya-vodohozyaystvennoy-sfery-v-regionah-yuga-rossii [Accessed on: February ]

Research on the incidence rate in regions of the Russian Federation

N NStudentRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences


A

This article investigates the incidence rate on a number of socio-economic factors in the regions of the Russian Federation using correlation and re-gression analysis. Linear and exponential models of the incidence rate are obtained. The infl uence of each individual factor on the outcome was found. For the most signifi cant factor, the law of distribu-tion of probability values is constructed. The anal-ysis of the received law is given. Recommendations on the response of the performance factor from the variation of factors included in the model are g iven.

Key words: incidence rate, social and economic factors, regression analysis of correlation, linear model, exponential model

I. M, Q M C R R F

I

People health directly aff ects the country’s economy. The deteri-oration of health reduces the working capacity of the population, which negatively aff ects productivity. This, in turn, restrains eco-nomic growth as well as welfare growth of the population. There-fore, the investigation of factors and trends of the incidence rate is one of the most crucial current research directions.

The incidence rate analysis is necessary for making manage-ment decisions at both the federal and regional levels. On its ba-sis, it is possible to properly plan and forecast the development of a network of health facilities.

R

Data was collected for subjects of the Russian Federation (Nenetsky Autonomous Area, Khanty-Mansisky Autonomous Area and Yamalo-Nenetsky Autonomous Area are included in the regions) and subsequently of the most signifi cant factors af-fecting the incidence rate were selected:

• X. The amount of pollutants from stationary sources of pollution (thousand tons / km);

• X. The amount of pollutants from vehicles (thousand tons / km);

• X. The number of visits to medical institutions for the year in shift;

• X. The number of enterprises, factories, factories in the re-gion;

• X. The value of the average salary in the region;• X. The size of a living wage of the pensioner;• X. The number of doctors;• X. Score sobriety *;• X. The average age of the population.

* The total score for each region was calculated by summing up the places occupied by this region for each of the six basic criteria:

• The number of deaths by main classes and individual cause s of death is alcohol poisoning;

• The number of patients who are studying at medical institu-tions with a diagnosis of alcoholism and alcoholic psychosis;

• The number of crimes committed by persons in a state of intoxication; sold alcohol products;

• The number of off enses related to the illegal production and traffi cking of ethyl alcohol and alcohol products;

• The number of hours to ban the sale of alcohol daily and the number of days the ban on the sale of alcohol.

Then a matrix of paired correlation coeffi cients was constructed, characterizing the closeness of their relationship.Table

The number of registered patients (Y)

Х X X X X X X X X

Х , ,X , , ,X -, -, -, ,X , , , , ,X , , , -, , ,X -, -, -, -, -, , ,X -, -, -, -, , , , ,X -, , -, -, -, , , , ,X -, -, -, , , -, , -, , ,

From the data provided above, it follows that such factors as the subsistence minimum for the pensioner (X) and the sobrie-ty score (X) have a very weak correlation with the resultant in-dicator. In addition, indicators of the number of enterprises, fac-tories and plants (X); the size of the average salary in the region (X) and the average age of the population (X) have a much greater connection with other factors, and create multicollinear-ity. Therefore, for a more objective assessment of the model, the above factors have been removed.

The number of registered patients (Y)

Х X X X

Х , ,X , , ,X -, -, -, ,X -, -, -, -, ,

I. M, Q M C R R F

The linear model

Coeffi cientsY-intersection ,Х ,X ,X -,X -,

• X — the amount of pollutants from stationary sources of pollution (thousand tons / km);

• X — the amount of pollutants from vehicles (thousand tons / km);

• X — the number of visits to medical institutions for the year in shift;

• X — the size of a living wage of the pensioner;

Y = .X + .X – .X – .X + .

It follows from this model that if X changes (the amount of pollutants from stationary sources of pollution) by unit, the re-sultant indicator Y (incidence rate) will change to — . units. When X changes (the amount of pollutants from motor vehicles), the incidence rate will change by . units; a change in X (the number of visits to medical institutions for the year in shift) will lead to a change in Y to ,. also when changing X (number of doctors) — by ,. units.

Based on the value of R (coeffi cient of determination), it can be argued that in .% of cases, the change in the resultant in-dicator (incidence rate) is due to the variation of the factors pre-sented in the equation.

Regression statisticsMultiple R ,R-square ,Standardized R-square

,

Normal mistake ,Observations

Then standardized coeffi cients were calculated.

Regression statisticsMultiple R ,R-square ,Adjusted R-square ,Standard error ,Observations

Coeffi cientsY-intersection ,T ,T ,T -,T -,

Y = .T + .T – .T – .T

Since standardized regression coeffi cients can be compared with each other, it can be said that the number of pollutants from vehicles has the greatest infl uence on the incidence rate, since this coeffi cient signifi cantly exceeds the values of standardized coeffi cients for other factors.

For the construction of an exponential model, it was necessary to take logarithm of each value.

Using the values in the “Coeffi cients” column, an exponential multiple regression equation is constructed:

Coeffi cientsY-intersection ,lnX ,lnX ,lnX ,lnX -,

The exponential model is:

0.035 0.843 0.064 -0.009 -0.081 2 4 6 7Y = X X X X X 20651.16

Also, in order to trace the infl uence of each individual factor on the resultant indicator, each one was increased and reduced by %. The results of the analysis are shown in the table:

I. M, Q M C R R F

% increase/decrease of each variable,other conditions being equal

Change of Y

X+% ,%X+% ,%X+% ,%X+% -,%X+% -,%X–% -,%X–% -,%X–% -,%X–% ,%X–% ,%

Based on the data, the resultant indicator is most sensitive to factor X (the amount of pollutants from vehicles).

Thus, according to the results of the investigation, it can be concluded that air pollution takes the fi rst place among the fac-tors aff ecting the incidence rate, since air is a product of contin-uous consumption of the organism.

As a result of an increase in CO (carbon oxide) in the atmos-pheric air, the process of destruction of the Earth’s ozone screen is intensively developing, acid rain is falling, causing damage to all living things, fertility of lands decreases, water is poisoned, and deforestation occurs. At least –% of human diseases, accord-ing to Russian scientists, are also associated with air pollution.

Consequently, during the investigation, randomly selected data on the amount of pollutants from vehicles (in thousands of tons) in the regions of Russia in was collected. A hypothe-sis was put forward on the exponential distribution of the amount of substances.

Then the histogram was constructed. Testing the hypothesis was carried out according to the criterion of Pearson’s agreement.

Exponential histogram

The hypothesis of the exponential distribution law was con-fi rmed. The observed value (.) does not exceed the critical value (.), which gives grounds to assert that the assump-tion is correct.

Exponential distribution law= , P W Pearson criterion

, , , ,, , , , ,, , , , ,, , , , ,, , , , ,, ,

,

Distribution function

0.006

0, 0( )

1 , 0x

xF x

e x

It should be noted that by the number of registered patients with a diagnosis established for the fi rst time in their lives, the leading position is occupied by Moscow. Then there is St. Peters-burg, Moscow Region, Krasnodar Area and Rostov Region.

C

Today, the environmental damage of motor vehicles is huge and manifests itself directly in many phenomena: pollution of the soil, water, atmosphere, motor vehicles creates noise and energy pollution. All this leads to a signifi cant deterioration in health and a reduction in the life of the population.

0

0,001

0,002

0,003

0,004

0,005

4,6;113,6 113,66;222,73 222,73;331,8 331,8;549,93 549,93;986,2

I. M, Q M C

In this regard, the main ways to reduce environmental dam-age from transport will be highlighted in the following:

• Optimization of urban traffi c.• Development of alternative energy sources;• Afterburning and cleaning of organic fuel;• Creation (modifi cation) of engines using alternative fuels;• Protection against noise.

B

. The site of the Federal Service of State Statistics http://www.gks.ru/

. Ovsyannikova S. N., Econometrics / Textbook for students of the second course of economic specialties. — Moscow: Delo,

. Efi menko S. A., Morozov P. N. Historical and sociological analy-sis of publications on medical and sociological research in pub-lic health // Sociology of Medicine. —

. Cummings P., Analysis of Incidence Rates — CRC Press,

. Skvortsova V. I., Decrease in morbidity, mortality and disability due to stroke in the Russian Federation — M .: Litterra,

. Zhidkova O. Medical statistics —

The problem of deforestation in Russia

E V, V LStudentsRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences


A

In this article the problem of deforestation in Rus-sian Federation is initiated. In the research, in terms of statistic data of the logging volume / quantity of forests, the probability distribution law of the re-sulting values over all Russian regions was con-structed. The analysis of the constructed laws al-lows to formulate the problem, which solution is based on identifying the most signifi cant factors. A multifactor and non-linear model was built up. Moreover, the sensitivity of the resulting value to the variation of factors included in the model was

I. M, Q M C T R

shown. The dynamics of the development of the analyzed trait was investigated and the existence of seasonality was revealed. The constructed model detected a social problem connected with the lack of accounting the number of inhabitants in the regions during deforestation and that infl uences people’s health nega-tively. The signifi cant factors that simulate response variable was infl uenced only by economics and fi nancial indicators.

Key words: deforestation, air pollution, non-linear model, sig-nifi cant factors.

R

The logging volume and quantity of forests statistic data over Russia was collected and the probability distribution law was constructed. It appeared to be normal. It means that there is an average value around which the rest of the data is distributed within the limits of sigma. Consequently, the average value can be taken in the further stages of the research.

The objective to fi nd out factors that infl uence the amount of deforestation in Russia most of all was set. factors were select-ed for the analysis. They acquire economic, social and ecological spheres in order to reach an accurate outcome. Based on these criteria the following factors were chosen.

• Y- logging volume (million m)• X- total stock of wood (million m)• X- woodiness (%)• X- agricultural manufactories• X- the weather in January• X- the weather in July• X- population (thousands)• X- unemployed people (%)• X- labor force aged – (thousands of people)• X- reforestation work (thousands of hectares)• X- area of forest land covered by forests (thousands of hec-

tares)• X- investments in agriculture• X- producer Price Index of Agricultural Products• X- air pollution emission (thousand tons)

Then factors which correlate with the response variable less than . were leaved out. Moreover, the factors were checked for multicollinearity and those ones that duplicate each other were excluded. As a result, factors were selected.Table . The fi nal correlation matrix

У Х Х Х ХУ (logging volume) Х (woodiness) , Х (agricultural manufactories)

, -,

Х (reforestation work) , , , Х (air pollution emission) , , , ,

To determine the degree of infl uence of independent variables on dependent variables, the next step of the research was regres-sion analysis.Table . Regression analysis

Regression statisticsMultiple R ,R-squared ,Scaled R-squared ,

In terms of the table below, a conclusion that the model, that was built, is working. That can be claimed because of the high R-square. It means that in % of cases the variability of the re-sponse variable depends on the variability of factors. The wor-king model is:

y= –,(X)+,X+,Х+,(X/)-

The model was checked for sensibility. On change the factors by % response variable changes diff erently. While altering per-centage area under forest, the amount of logging varies by %. Also, on change air pollution factor, the amount of logging fl uc-tuates around %. When quantity of agricultural manufactures and reforestation work is changed by unit, the response varia-ble changes by , and ,. The reforestation work is the most signifi cant factor. At the same time, agricultural manufac-tures make the model less sensitive.

I. M, Q M C T R

While forming a regression equation low correlation between population and amount of logging was noticed. The relationship between the volume of logging, the stand of timber and popula-tion was checked. The amount of population does little for growth of deforestation.Table

У Х ХУ Х , Х , ,

Furthermore, the regression statistics and the linear model shows that with the increase in population by person the amount of logging grows by units. Consequently, the amount of deforestation is higher in region with greater population. So, the serious ecological problem appears.Table

Regression statisticsMultiple R ,R-squared ,Scaled R-squared ,Standard error Experimental observation

Then, the pollutant emission including carbon dioxide and pro-duced oxygen in every region were calculated. Finally, the amount of net oxygen was specifi ed. The standard equals kilos per capita per year. In region of Russia there is enough oxygen for healthy living. And even Far Eastern Russia varies from standard by tons of oxygen per capita for one year. The problem here is connected with logistics and transportation. In the regions with more transport opportunities, the amount of logging is higher.

After that the impact of the volume of deforestation on GDP per capita, and on the quantity of people with respiratory diseas-es was compared in dynamics. All data was collected over year, from till . GDP data was collected over quarters, so the seasonality should be excluded. GDP per capita reaches peak lev-el in the fourth quarter and is the lowest in the fi rst one.

Table . Available oxygen

Central Russia The Volga Region Southern Russia Northwestern Russia North Caucasus District The Urals Siberia Far Eastern Russia

Table

st quarter -,nd quarter -,rd quarter ,th quarter ,

Then the impact of logging was analyzed in dynamics. The num-ber of people with respiratory diseases is more infl uenced by defor-estation that the economic situation in the country. The method of chain rates was used in order to exclude nonsense correlation.

Finally, the research showed that deforestation aff ect adversely people’s health, while the economic situation slightly changes.

y = -0,0026x + 85156R² = 0,5232

-40000-20000

020000400006000080000

100000120000

-10000000 0 10000000 20000000 30000000

ΔУ1 (GDP per capita)

Δy = 0,0004Δx + 2,0646R² = 0,7501

-5

0

5

10

15

-10000000 0 10000000 20000000 30000000

ΔУ2 (People with respiratory diseases)

I. M, Q M C

C

To recap, it is worth mentioning that the problem of the defor-estation exists in the Russian Federation and it is needed to be solved. This occurrence makes harm to ecology and people’s health. In this case the preventive measures must be taken into account. It is necessary to enhance logistics and transportation in the Eastern part of the country and reduce the number of fac-tories in the west, as it will provide more oxygen there.

B

. Gareeva, N. M. Statistics in charts and tables. — Moscow: Eksmo, . p. (in Russian)

. Harry Larson. What Is Overpopulation? / The Environmentalist, . p.

. Ovsyannikova S. N. Statistics, . (in Russian)

. gks.ru — the offi cial statistics website.

Data management for business intelligence: collection, storage and processing issues

E IHead of Management and Entrepreneurship DepartmentRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

A

Business process management dependency on data is continually growing. Practical experience has shown that even massive international corporations face a number of typical pitfalls when dealing with data. These pitfalls and simple solutions are consid-ered in the article.

Key words: applied Data Science, Process Mining, business process management (BPM), business pro-cess intelligence, data management

I

Information technology development made a signif-icant contribution into the business process man-agement. There is a plenty BMP tools that allow to design the core business process with all subpro-cesses (TO-BE), to run the processes, to control it and to do the research on the current state of the designed process (AS-IS) [].

I. M, Q M C D

Process itself is a source of company’s costs, meanwhile correct processes assure required quality and company’s effi-ciency. This makes business process management extremely important to any high-level executive. Previously the business process intelligence tasks were expensive and time consuming. Nowadays there is still might be a need for external support, but many of the business intelligence tasks can be accom-plished easier and even automatically due to the data science advancement [].

This article considers a number of issues that research groups from the Faculty of Economic and Social Sciences of RANEPA faced when did the business process researches for the Moscow headquarters of the top international corporations from diff er-ent business areas.

T C

The most global challenge came from the leading international manufacturer of home appliances. The task was to analyze the effi ciency of the company’s department of logistics. There was an assumption that the initially designed process is violated by the employees and sometimes the SLAs on the delivery timing are exceeded. To per-form the analysis a SHOULD-BE process map has been requested (see Fig. ).

At a fi rst glance one can notice that the picture has been created without any com-monly used notation (BPMN., EPC etc.) [] which makes the research process a bit more complicated. It has been decided to use Process Mining approach to replicate the AS-IS process model []. This approach assumes a number of things []:

• Company should have either ERP or CRM system that supports a process

• This system should collect a log of all events happened to any case handled

• These logs should at least contain the case id, activity name, time stamp

• Data logs should be available to researchers

The company has SAP ERP system which was promising because of the face that SAP does store the event data on any handled case or order []. The problem occurred when it was discovered that the database for the SAP logs is located in head offi ce and nobody can say how to extract the requested data from there. To solve this issue the research group had to make a detailed de-scription of the requested data, which was sent to Moscow offi ce and to the headquarter afterwards. Out of weeks of the re-search it took all together six months to receive the actual data. Obviously, there is a trade-off between data security and ability to extract value from data but sometimes it makes sense to trust the local offi ces and store the data at a place where in can be used with maximum effi ciency [].

Another issue with data acquisition was an enormous part of duplicates within the event logs. A lot of “order” and “delivery” events have been duplicated multiple times with the same case id, activity name, time stamp and resource (the responsible person conducted this particular activity). Out of Mb of CSV-format-ted data provided, Mb contained duplicated event logs. Though Mb of unique data contained a log over thousand events which was enough to build an AS-IS process map (see Fig. ) but this snap shot of the database shows that over % of the company’s data storage capacities are occupied with the useless duplicates.

The key fi nds of the research itself are outside of the scope of this article, but the Figure illustrates how useful can be the Pro-cess Mining approach to the company’s business process intelli-gence. Though the SHOULD-BE and AS-IS process maps have much in common [][], there is still a number of crucial devia-tions (business process violations), bottlenecks and many other useful insights.

The was a diff erent request for the customer handle process from one of the top global luxury cars manufacturer. The idea

Order

Delivery

Goods Issue

Invoice

Return Order

CreditNote

Return Delivery

QTY

Diff

eren

ce

Pric

e D

iffer

ence

F. . SHOULD-BE process model of logistics department

I. M, Q M C D

was to analyze the data obtained each time when a customer ar-rives at a service station. Unfortunately, even top-management representatives of Moscow offi ce couldn’t obtain a permission to do the researches on these data though the data can be encoded with no eff ect to the research outcomes.

The third negative case worth to be considered is a case of an international pharmaceutical company. There was a demand to research and re-design the current process of the charity re-quests acceptance. The time limit for a single charity request consideration has been set to be up to three months but at early there still were a number of requests from waiting for the charity committee decision. The company receives around requests from a various Russian non-profi t healthcare organ-ization annually, but all the relevant data is stored in a set of Ex-cel tables. There has been a case in the past when one of the em-ployees occasionally deleted a dozen or rows from the table with-out any possibility to recover it. Apart from that there have been a number of process violation issues.

To start investigation of the issues a group of the researches requested the access to the current tables that the company uses to trace current state of every single request. In response

all the requested Excel tables have been provided to the group without any anonymization or encoding and kept the entire in-formation about multimillion charity activity of this global company. This is another extreme case of bad data governance that may cause leaking of the commercially sensitive informa-tion.

All the above-mentioned cases of commercial information misusage also increase the importance of the access restriction policy. This policy doesn’t need to be too strict which can pre-vent getting value from the data, but it has to defend the enter-prise secrets and information completeness. In addition to tradi-tional scheme of the Role-Based Access Control (RBAC) [], it seems to be natural to introduce the following roles:

• Database assembler — a person who designs a database and grants the assess rights to it

• Writer — a person or a piece of code who puts the relevant data into the database

• Viewer — a person or a piece of code who can obtain the data from a database

• Inspector — a piece of code that checks whether the data-base is complete, consistent and bears no duplicates

It is important to say that Writer should not be capable of chang-ing the database design. Viewer should not be capable of chang-ing the data. It also makes sense to introduce the diff erent levels of viewers according to the enterprise hierarchical structure and business needs. Inspector has to make sure that a data in a data-base are stored properly, nothing is lost (this should be techni-cally impossible) and no duplicated or other irrelevant data is stored.

Analyzing the pitfalls mentioned above it is possible to list a number of data collection, storage and processing guidelines:

• Company should try and collect the data on each signifi cant event within the business process

• Data should be available to people who can generate as much value as possible unless the risk of losing critical in-formation becomes too high

Confirmaionof service 1,834

Sales Order2,948

Delivery4,331

GD Goods Issue2,179

Invoice1,826

Credit Note365

Return Order365

1,0581,181

1,692

1,219

1,229

2291,221

128 5

93

2,018

73

Confirmaionof service Instant

Sales OrderInstant

DeliveryInstant

GD Goods IssueInstant

InvoiceInstant

Credit NoteInstant

Return OrderInstant

69,1 mths1,181

25,9 hrs

Instant

83,6 mins14,2 d

63,7 mths 3,5 wks

18,6 d

11,6 yrs

2,91 hrs

F. . AS-IS process model of logistics department

I. M, Q M C

• Data should be available at a place where it can generate as much value as possible unless the risk of losing critical in-formation becomes too high

• To maintain data completeness and consistency there should be four technical levels of data collectors and users: assemblers, writers, viewers and inspectors

• Data Viewers and Collectors should not be capable of delet-ing anything from the database

By introducing the simple data access rights and rules of usage there is a possibility to get more of the data that are stored on the company’s capacities. Regular database inspections may free up the signifi cant amount of enterprise storage space by getting rid of the useless data. These simple steps could both decrease the company’s costs and generate revenue in a number of aspects.

R

. W.M.P. van der Aalst. Process Mining: Data Science in Action. Springer Verlag, Berlin, .

. C. Guenther and Wil M. P. van der Aalst. Fuzzy mining: Adaptive process simplifi cation based on multi-perspective metrics in BPM, , ser. LNCS, vol. , , pp. –.

. W.M.P. van der Aalst. Business Process Management: A Compre-hensive Survey. ISRN Software Engineering, pages –, . doi:.//.

. OMG. Business Process Model and Notation (BPMN). Object Management Group, dtc/––, .

. S.J.J. Leemans, D. Fahland, and W.M.P. van der Aalst. Process and Deviation Exploration with Inductive Visual Miner. In L. Li-monad and B. Weber, editors, Business Process Management Demo Sessions (BPMD), volume of CEUR Workshop Proceedings, pages –. CEUR-WS.org, .

. Enterprise Information Management: Best Practices in Data Gov-ernance, An Oracle White Paper on Enterprise Architecture, May .

. David F. Ferraiolo, D. Richard Kuhn, Ramaswamy Chandramou-li. Role-Based Access Control, second edition,

Project risk management: a case of developing an innovative manufacturing enterprise

A L, M S L DStudentsRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

A

The article describes the most probable risks of an emerging innovative company. The general carac-teristics of a fi rm which is continually conducting blue-sky research and implementing new technolo-gy while manufacturing rather traditional goods (metal-composite cylinders for various modes of transport) are provided. Its major potential risks are identifi ed. The measures aimed at preventing immi-nent negative ramifi cations are set forward.

Key Words: innovation, metal-composite cylin-ders, risk identifi cation, strategic risks, operational risks, fi nancial risks, hazards, competitive advantag-es, PESTLE-analysis, Spider diagram, Data Envelop-ment (Saati) Analysis

I

Nowadays high-pressure gas cylinders are in de-mand in Russia. There are several cylinder manu-facturers in Moscow and its suburbs, Izhevsk, Kot-

I. M, Q M C P

las and Orsk which have a high capacity for innovation and are permanently devising new goods with striking market potential [; ; ; ]. Often do they deliver them to other companies, which specialize in fabricting various means of transport. They operate in rocket-and-space, aviation and the automotive in-dustry. It is a particular case of the business-to-business (BB) sector.

Furthermore, these cylinders allow for the business-to-con-sumer (BC) sector, as the owners of land sections in the coun-tryside will need dependable heating and cooking units. These cylinders can make the technical appliances function for the pur-pose intended.

As for the business-to-government (BG) sales, the authorities are concerned with introducing new gasifi cation programs in the constituent territories of the Russian Federation. The cylinders could also become an integral part of this undertaking [].

All these segments are far-reaching for these goods but it is practically impossible to gauge in which sphere they will primar-ily be present in a few decades [].

K

Currently, a project on developing an innovative enterprise man-ufacturing metal-composite high-pressure gas cylinders is being carried out. Its presumable location is Chelyabinsk, which was chosen because of its proximity to the key suppliers and accept-able rent payment for the facilities. The goods are expected to be produced for wholesale trade with other enterprises, which, in turn, fabricate diverse modes of transport: aircraft, spaceships and conventional cars.

For fi nding out their characteristics and detecting their inno-vative elements, these metal-composite cylinders were compared with ubiquitous metal cylinders (Table ).

It could be inferred from the table above that metal-compos-ite cylinders have some conspicuous advantages in comparison with other types, such as non-shattering destruction, anti-corro-sion properties, high working pressure and low weight [;].

T . Comparison of diff erent kinds of cylinders

Feature Metal cylinders Metal-composite cylinders

various shapes + +non-shattering destruction — +anti-corrosion properties — +fl ameproof — +explosion safety — +temperature range (°C) - – + - – +weight (kg) ,working pressure (MPa)

Furthermore, this company is the only Russian metal-compos-ite cylinder manufacturer the machinery and equipment of which are transported from abroad, as other plants which buy some technological items overseas focus on fabricating metal cylinders for diff erent industries [].

It goes without saying that these products may be considered to be innovative, primarily for our domestic market. Nevertheless, this large-scale project implies numerous hazards [].

R

In theory, project risks may fall into four key categories:

• strategic risks which have an impact on the company value on the whole;

• operational risks which infl uence certain fi nancial fi gures (total revenue, profi t);

• diff erent kinds of fi nancial risks;• hazards which are unlikely to take place but if they do, they

will invariably incur devastating losses.

PESTLE-analysis was carried out for identifying major strategic risks of the enterprise which may emerge in the external envi-ronment (Table ).

A crucial political risk of this company is severance of relations with its foreign suppliers which may result in an urgent search for local alternatives []. This will defi nitely incur extra transac-tional costs and be time-consuming. Moreover, there is no guar-

I. M, Q M C P

antee that the fi rm will discover a Russian equipment manufac-turer which produces the machinery with comparable technical characteristics. Henceforth, decreasing company value is inevitabl e.T . PESTLE-analysis of the cylinder manufacturer

Political Economic Legalescalation of international tension

intensifi cation of competition

fi scal regulation

a shift from BB to BC and BG

exchange control

macroeconomic phenomena

customs regulationnew standards of productiona diffi culty in obtaining a patent

Social Technological Environmentalnon-adaptive employees of certain fi rms to new technology because of insuffi cient education

slow implementation of innovation

environmental regulation

competitive intelligence accidental explosion of a cylinder

The impending social negative factor is the inability of the workforce of certain Russian companies to properly use the cyl-inders while adjusting them to means of transport by reason of lacking education and experience. Apparently, this point is di-rectly linked to the hazards which may be disastrous for the or-ganization [].

As for the economic risks, fi rst of all, the competitors’ perfor-mance represents a real threat. At present, there are several pow-erful cylinder manufacturers in other towns []. For instance, over the last six months, high-pressure light aluminum cylinders were created by another fi rm. They must be of choice for the rocket-and-space industry. The Roscosmos is believed to acquire them for equipping new air vehicles.

The competitors are likely to come up with the breakthroughs that will help them surpass this company in some regards []. Presumably, the market will be overwhelmed with better alterna-tives to these goods in the near future.

Moreover, some strong market players may unexpectedly de-cide to reduce the prices of the cylinders. This pricing policy will aff ect this enterprise in a negative way, as it is labeled as up-mar-

ket. Comparatively high prices of these cylinders are explained by their outstanding technical characteristics (Table ).T . The Data Envelopment Analysis (Saati)

Features Weight of the factors

Metal cylinders

Metal-composite cylinders

Diff erence Results

Weight of the cylinders

,% , % ,%

Temperature range ,% % %Working pressure ,% % ,%Non-shattering destruction

,% % ,%

Overall ,% + % + ,% + ,% + % = ,%

According to the Data Envelopment Analysis developed by Saati, the prices of these goods should surpass the prices of other prod-ucts of the same industry by at least fi ve times []. Therefore, the pricing strategy of the company ought to remain unchanged [].

Furthermore, some experts surmise that the demand for these gas cylinders may soar in retail and in the business-to-govern-ment (BG) sector. In both cases, these cylinders would meet their needs. In contrast, the demand for these cylinders in the wholesale trade, particularly in the aviation industry, may shrink. Such drastic changes in the market patterns should be foreseen in advance [].

Another economic factor is not specifi c for the industry but it can lead to substantial damage. It embraces negative macroeco-nomic phenomena provoked by an unfavourable economic situ-ation in the country. For example, high infl ation rates will inev-itably make prices of products grow at a lower pace than those of raw materials. Probable economic recession implies cyclical un-employment. As a result, the disposable income of the popula-tion and its purchasing power may plummet.

The core strategic technological risk of the innovative enter-prise is slow implementation of innovation in production in vir-tue of ineffi cient research and development (R&D) programs []. Besides, it cannot be ruled out that some organizations will un-dertake the competitive intelligence, hoping to fi nd out and adopt the company’s unique approach.

I. M, Q M C P

Most legal factors are related to passing new laws. For example, if tax rates skyrocket, the company’s net profi t, as well as its prof-itability index, will decline. Imposing high tariff s on the foreign equipment and signifi cant changes of currency regulation will pre-vent the company from acquiring effi cacious machinery overseas []. New standards of production may also pose a challenge for the enterprise, which will have to redirect manufacturing. In addition, the company may have diffi culty in obtaining a patent. This will make it shift the deadlines and even worsen its solvency.

Strategic environmental factors can be divided into two groups []. The fi rst one is connected with the above-mentioned legal factors and implies natural conservation law-making. The second one covers accidental explosion of a cylinder (e. g. due to careless exploitation), which may cause irreparable havoc to certain nat-ural areas.

As for potential strategic risks of this cylinder manufacturer which may happen in the internal environment, the most prob-able one is a departure of a key employee. This may take place in any company regardless of the industry [].

Operational risks of the company may occur in the internal environment at three stages. At the pre-production stage, the core risk is opting for untrustworthy suppliers, which may aggra-vate the company’s performance. At the production stage, the fol-lowing risks may take place: employment of unskilled workforce lacking involvement in R&D; critical staff turnover due to a weak corporate culture; programming and technical breakdowns, such as suspension of production, an increase in rejected items and batch losses. At the post-production stage, its potential challeng-es are caused by its sales policy which may imply choosing an in-appropriate distribution channel or organizing an ineff ective ad-vertising campaign [].

Potential fi nancial risks of this cylinder manufacturer are com-prised of credit risks and market risks []. As for its credit risks, there is no guarantee that the receivables will be paid by the con-tractual partners on a full scale on time. This may either be caused by untrustworthiness of these partners or some unfore-seen circumstances. Market risks which may aff ect this company consider foreign currency exposure, as it acquires its reliable and

durable machinery and equipment in Northern Europe. As for li-quidity troubles, it is unlikely to face them because its quick and current liquidity ratios are acceptable.

All in all, it is practically impossible to mitigate some of these risks because they do not depend on the company policy, where-as some potential pitfalls can be dealt with.

D

For illustrating the strategic position of the organization on the market and choosing the most appropriate methods of tackling its potential problems, the Spider diagram was used (Picture ).

According to this diagram, our company has some detectable strategic competitive advantages on the market, such as a sophis-ticated product with unique application properties; a new pro-duction technology, as well as impressive capacity for innovation, which enable the fi rm to manufacture high-end cylinders; the policy aimed at satisfying the clients’ needs. Its production facil-ities correspond to the average level in the industry [].

However, this organization has some major weaknesses which must be dealt with for preventing it from grievous ramifi cations.

Product

Mission and vision

Corporate culture

Company management

TechnologyFacilities

Global strategy

Innovation Information disclosure

HR

Customer orientaion

Our company Market average

P . The Spider diagram

I. M, Q M C P

First of all, the mission and the vision of the company are cur-rently unclear and vague. It should determine its core objectives for which it will strive. This must help the company evade any communicative failure.

Besides, it is crucial to provide more eff ective company man-agement using diff erent motivation techniques and establish a strong corporate culture. Otherwise, a decline in company man-ageability may turn out to be outrageous [].

Maintaining and expanding international economic activity is also vital to the cylinder manufacturer, as this will result in gain-ing recognition on the global scale and maximizing profi ts.

Last but not least, information disclosure is one of the most important factors to the customers. Many of them will be reluc-tant to purchase the company’s products, being unaware of its fi -nancial condition. Thus the cylinder manufacturer must reveal its pivotal data for increasing its market share.

As for the risks which appear in the external environment and hazards, no production unit can impact them directly. These fac-tors ought to be taken into consideration while making strategic decisions regarding the company policy. Operational risks can partly be transferred to insurance companies []. Some other methods which frequently prove eff ective are:

• hiring a turn-around manager;• creating fi nancial reserves for bridging the cash gap;• looking for other kinds of suppliers;• switching to extra distribution channels;• devising various scenarios of the marketing campaign’s

outcomes;• taking extra precautions for avoiding spoilt production;• providing the labour with additional training programs in

order to enhance the workers’ skills.

C

Any innovative enterprise, in whichever industry it operates, is an extremely hazardous initiative. It incurs plenty of obstacles which may seem unsurmountable at fi rst sight.

Nowadays the market of metal-composite cylinders is at the initial stage of development in Russia []. It is highly likely that new manufacturers of these goods will become successful owing to their remarkable products, eff ective management and timely estimation of all the risks. Nonetheless, the companies must be able to adapt to market tendencies and even shift to other mar-ket segments in no time, if it is required by the emerging patterns.

R

. Choonjoo Lee, Yong-bae Ji Data Envelopment Analysis in Sta-ta// The Stata Journal. — . — № URL: https://www.cgdev.org/sites/default/fi les/archive/doc/stata/MO/DEA/dea_in_stata.pdf

. Knyaginin V. N. Novaya tekhnologicheskaya revolyutsiya: vy-zovy i vozmozhnosti dlya Rossii. Ekspertno-analiticheskiy doklad. M.: Tsentr strategicheskikh razrabotok, . — s.

. Lazonick W. Innovative enterprise or sweatshop economics? In search of foundations of economic analysis// SSRN. — . — №

. http://kemz.ru — the offi cial website of Kotlas Electromechan-ical Plant

. http://safi t.info — the offi cial website of Safi t Company

. http://www.realstorm.ru — the offi cial website of Real-Storm Research and Production Company

. https://www.digitronicgas.ru/ — the offi cial website of Dig-itronic Autogas Company

. https://www.mirgaza.ru/vse-o-gbo/opisanie-tipovykh-komple-ktuiushchikh-gbo/metanovye-ballony/ — the website describ-ing diff erent kinds of high-presssure clinders

. https://pestleanalysis.com/what-is-pestle-analysis/ — the web-site describing the technique of PESTLE-analysis

. https://tehindustria.ru/gazovye-ballony/metallokompozitnye-ballony/ — the website describing metal-composite cylinders

. https://www.the-organic-mind.com/spider-diagrams.html — the website describing the Spider diagram

A

A new approach for manufacturer to improve traditional price negotiation at the retailer`s market monopoly

P S, A ZStudentsRussian Presidential Academy of National Economy and Public Administration Faculty of Economic and Social Sciences

E IHead of Management and Entrepreneurship DepartmentRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

A

The aim of this paper is to provide an insight into the approaches for manufacturers to sell-out price negotiation with the retailer within the new market conditions on the Russian consumer electronics market.

Key words: collaboration, distribution channels, manufacturer-retailer relationships, sell-out pricing

I

Retail sector refl ects changes in the global economy, which stem from the alterations in fi scal, monetary and trade policies. For retailers, this change will

mean slower consumer spending growth, higher consumer pric-es, and disrupted global supply chains . Therefore, negotiations on the pricing strategies between manufacturers and retailers to-day are becoming more and more relevant, since manufacturer and retailer want to sustain current level of sales.

This article focuses on the Russian consumer electronics mar-ket, which recently faced a gradual merge of tree the most infl u-ential market players. In April M. Video Group closed a pur-chase deal with Eldorado Company, and later in September the company bought German retailer Mediamarkt. By , a market share of the joint company will have been increased up to %. In such market conditions, there is a high pressure on manufac-turers from the joint retailer’s side, including the price setting process. Therefore, suggested in this article strategies will focus both on costs and pressure reduction.

The aim of this paper is to provide an insight into the ap-proaches for manufacturers to sell-out price negotiation with the retailer within the new market conditions. Further strategy is di-vided into two separate parts, called “Standoff Strategy” and

“Collaborative Strategy”. A content of these strategies is funda-mentally diff erent. The fi rst one implicates a complete drift from price negotiation into creating own distribution channels, which may allow a manufacturer to increase its infl uence at the market. While the second one is based on the establishing reciprocally profi table relationships between a manufacturer and the retailer and concentrates on creation of shared business processes be-tween the parties.

S :

Within this strategy, the aim is to increase a manufacturer’s in-fl uence on the price of goods by creating alternative distribution channels, or in other words, to achieve a price autonomy from

Ira Kalish, Vicky Eng. Global Powers of Retailing . Available at: https://www.deloitte.com/global/en/pages/consumer-business/articles/global-powers-of-re-tailing.html (Accessed May ).

I. M, Q M C A

the retailer-monopolist. In order to elaborate innovative solu-tion, it is highly important to count on the current trends, one of which is shopping personalization. Nowadays consumers are becoming more and more exacting: not only do they want to re-ceive information instantly and buy on the spot, but to get a unique and personalized buying proposition. That is why voice assistance is a new and innovative decision. However, program-ming own voice assistant is somewhat expensive, therefore it is suggested to use an already excising innovative Russian voice assistant Alisa by Yandex. With Voice Assistance consumers get a personalized proposition by answering key Alisa’s questions about their needs. Moreover, recently Yandex has launched a loudspeaker Alisa — an important step in creating a Smart House System. Thereby integrating with Yandex Alisa now, manufac-turer will create a possibility for a consumer to turn his or her own house into a shop in a long term. In addition, now there is a sharp growth of applications-aggregators (like Airbnb, Avia-sales, Booking.com, AliExpress etc), which are easy and conven-ient in usage, but have nothing to do with brand awareness and brand commitment.

Pizzeria Papa John’s has already followed the trend of person-alization and successfully integrated its ordering service into Yandex Alisa, even though it is presented in the Application-ag-gregator “Delivery Club”. The reason for is that via Alisa consum-er has practically no choice, but to order with Papa John’s, be-cause it was the fi rst to collaborate with the voice assistant, and by saying “Alisa, I want to order pizza”, he will automatically re-ceive a proposition by Papa John’s. But if one opens an aggrega-tor like Delivery, he would see numerous off ers by diff erent res-taurants, and there is a little chance he would choose particular-ly Papa John’s, unless he is their regular consumer and is very loyal to the brand.

In a nutshell, using Yandex Alisa as a new distribution Chan-nel within the Standoff Strategy is a highly innovative way to at-tract new customers, whereby a manufacturer is free from the need of price negotiation with the retailer. Furthermore, this so-lution would create a great competitive advantage for the com-pany today as well as in the long term.

C : -

While Stadoff strategy is somewhat radical and innovative idea, there is an alternative collaboration strategy, which is based on the ROPO model (Research online/purchase offl ine). Insights of Consumer Barometer by Google show that % of users in Rus-sia google about the product before making buying decision. At the same time % buy the product offl ine and only % buy on-line. Hence, it is necessary to maintain relationships with the al-ready existing retailer-monopolist.

Collaboration strategy is also based on the realities of Indus-try ., which could be implemented only with the existence of end-to-end digitalization of all the tangible assets and their in-tegration into the digital ecosystem along with all the partners who participate in value-added chain . In our case these are dis-tributors and retailers.

Basically, collaboration strategy includes main points of con-tiguity with between the manufacturer and retailer. These are hu-man capital, pricing and supply chain. Each part provides clear information about main business processes which can be im-

New Retail (). Available at: https://new-retail.ru/business/eff ektivnye_kom-munikatsii_kak_digital_reklama_vliyaet_na_offl ayn_pokupki/. (Accessed May ).

Eli Tidhar, Jeremy Siegman, Dan Paikowsky. Toward the next horizon of Indus-try ., . Available at: https://www.deloitte.com/insights/us/en/focus/in-dustry-–/building-capabilities-through-collaborations-startups.html (Ac-cessed May ).

I. M, Q M C A

proved by manufacturer and retailer both. The fi rst approach is called KAM model and capabilities changing . It concentrates on retailer-producer relations, as well as on building eff ective vari-ation of interpersonal relations between retailer’s and manufac-turer’s employees.

The main problem for today is that Key-account managers rely more on personal relationships with individual buyers and aren’t well versed in big data and advanced analytics. So if company de-cides to change KAM model and capabilities, it will bring growth above the category, as well as sales expenses reduction.

The fi rst step is to shift from customer segmentation to cus-tomer-portfolio management. Company should determine the distinct role that each retailer plays in the manufacturer’s port-folio of customers. Examples of roles might be growth driver, profi t driver, scale builder, core customer, or future bet.

Second step is to tailor key-account teams into customers’ business drivers:

• strategic objectives;• analytical capabilities;• retail operations;• collaboration style;• procurement processes and posture.

In order to support this changes company has to overhaul capa-bilities, commit to collaboration and upgrade negotiation skills.

And the last but the most important part is to supercharge in-sights at areas:

• category performance;• assortment;• pricing/promotions;• operations;• innovation;• shopper /consumer behavior.

Kari Alldredge, Brandon Brown, and Max Magni. Playing catch-up: How to part-ner with the retailer of the future, . Available at: https://www.mckinsey.com/industries/consumer-packaged-goods/our-insights/playing-catch-up-how-to-partner-with-the-retailer-of-the-future# (Accessed May ).

Companies that commit to this journey will be well on their way toward sales excellence and sustained competitive advan-tage.

The second approach is called Catalyst workshops . The aim of this approach is to create a platform for the innovations’ devel-opment. In our case, retailer provides all the data about the cus-tomers and customer behavior. Meanwhile, producer shares its experience on logistics and eff ective warehousing. A fresh set of eyes with an outside perspective can be a catalyst for new ideas. That is why such sessions called catalyst workshops.

The following fi ve measures are critical for eff ective workshop:

• Set up mutually benefi cial incentives;• Invite the right participants;• Develop a fact base in advance;• Create an idea matrix with specifi c improvement levers;• Follow up and implement.

In fact, each catalyst workshop is unique, hence a content of such even will depend on the specifi c companies’ goals and objectives.

C :

The main problems that low OSA leads to are postponed sales, lost sales, drop in customer satisfaction and the possibility of the customer switching to another retailer and/or brand.

Despite the fact that this issue is much more acute in food re-tail, in electronic retail these eff ects may also be seen. Thus, the following two solutions are widely applied (with the latter being the “next step” of the fi rst one):

• OSA-cooperation• VMI

In order to use the OSA-cooperation model the following steps need to be taken:

Marc Gilbert, Andreas Gocke, Peter Rosenfeld, and Robert Tevelson. Suppliers as Partners: A Catalyst for Savings, . Available at: https://www.bcg.com/publi-cations//sourcing-procurement-supply-chain-management-suppliers-as-partners.aspx (Accessed May ).

I. M, Q M C A

• Order fulfi llment rates should be analyzed, defi ciencies should be worked out

• Data (both on the retailer’s and supplier’s side) should be made compatible

• The measurements needed should be made and relevant data should be exchanged continuously and on a regular ba-sis

• Supply schedules should be jointly devised and optimized• Further improvements should be searched for and made

In order to proceed to the next stage of collaboration the follow-ing requirements must be met, and the following steps need to be made:

• The objectives for Inventory turns, Inventory levels, Fill-rates, Transaction costs are agreed upon

• The supplier is obliged to manage the inventories of the re-tailer at the level negotiated (and at the predetermined lev-el of the logistics infrastructure)

• Real-time sharing of data (sales and transfers, inventory position information such as on-hand, on-order and in-transit) at the SKU level, point-of-sale and promotions data.

C : P -’

Pricing is a very individual aspect of manufacturer-retailer’s re-lationships. Monopoly on the market makes it diffi cult to specu-late the retailer’s discount. However, several concepts were dis-covered, whereby the manufacturer could partially gain control over sell-out pricing of retailer.

. Margin maintenance concept

Margin maintenance is defi ned as the retailer’s perception of the manufacturer’s promise (ability) to maintain the retailer’s gross margin, in dollars, on its sales of the manufacturer’s merchandise.

The suggestion is as follows: under the terms of this off er, if the dollar goal is not met, manufacturer agrees to compensate

retailer with cash allowances to cover the diff erence.Outcomes: margin maintenance benefi ts retailer by reducing

the fi nancial risk associated with partnering with the manufac-turer. Therefore, margin maintenance should be perceived by the buyer to have a positive eff ect on relationship value and may al-low the manufacturer to receive control over sell-out pricing.

. Special treatment concept

Relationships are elitist, in that they imply special status (Gutek, ). We defi ne special treatment as exceptional service off ered by manufacturer that the retail buyer perceives as symbolic of preferred status in the manufacturer’s portfolio of accounts.

The suggestion is that retailer count on the manufacturer to off er the service not only before all the competitors, but also be-fore the “sister” stores in the corporate portfolios, with whom the retailer do not directly compete (food stores etc).

Outcomes: special treatment by the manufacturer is supposed to have a positive eff ect on the retailer’ buyer’s relationship valu e and thereby positively infl uences relationship maintenance in-tention (RMI). Furthermore, it can serve as an argument for the manufacturer in sell-out price setting.

. Minimum purchase quantity сoncept

A minimum purchase quantity is a minimum rubble amount worth of goods that the distributor or retailer must purchase in order to carry the manufacturer’s products. The manufacturer may have a minimum purchase quantity of ₽,. This means that distributors and retailers must purchase at least ₽, worth of goods to carry their products in their inventory. Mini-

Janet Wagnera, Sabine Benoit. Creating value in retail buyer–vendor relation-ships: A service-centered model, Volume , January . Available at: https://www.sciencedirect.com/science/article/pii/S. (Accessed May ).

Connor Gillivan. Supplier Relationships — How Do They Impact Retail? . Available at: http://connorgillivan.com/supplier-relationships-aff ect-retail/. (Ac-cessed May ).

I. M, Q M C A

mum purchase quantities are common for large brands that have a strong foothold in the consumer market.

Outcomes: MPQs help the manufacturer to stay profi table, maintain a healthy cash fl ow and reduce the inventory.

. Key value indicators

Key value items (KVIs) are usually top sellers, traffi c generators, or highly-searched stock keeping units whose prices consumers tend to remember. Key-value categories can account for up to % of an average retailer’s revenue but only half of its profi t.

Outcomes: Defi ned KVI’s can boost manufacturer’s earnings and improve return on sale rate.

C

There are several ways for the manufacturer to enhance its rela-tionships with retailer on a market monopoly. The most eff ective strategy is the one with a comprehensive approach, including pricing and non-pricing methods at the same time. Creating new distribution channels may occur simultaneously too, but it is im-portant to take into account the risk of undermining relations with the current retailer. However, it may be more favourable de-cision in the long term.

R

. Ira Kalish, Vicky Eng, Global Powers of Retailing . [электронный ресурс] []. URL: https://www.deloitte.com/global/en/pages/consumer-business/articles/global-powers-of-retailing.html

. New Retail [электронный ресурс] []. URL: https://new-re-tail.ru/business/eff ektivnye_kommunikatsii_kak_digital_rekla-ma_vliyaet_na_offl ayn_pokupki/

Gadi Benmark, Sebastian Klapdor, Mathias Kullmann, and Ramji Sundararajan. How retailers can drive profi table growth through dynamic pricing, . Avail-able at: https://www.mckinsey.com/industries/retail/our-insights/how-retailers-can-drive-profi table-growth-through-dynamic-pricing. (Accessed May ).

. Eli Tidhar, Jeremy Siegman, Dan Paikowsky, Toward the next horizon of Industry . [электронный ресурс] []. URL: htt-ps://www.deloitte.com/insights/us/en/focus/industry-–/building-capabilities-through-collaborations-startups.html

. Kari Alldredge, Brandon Brown, and Max Magni, Playing catch-up: How to partner with the retailer of the future [электронный ресурс] []. URL: https://www.mckinsey.com/industries/consumer-packaged-goods/our-insights/playing-catch-up-how-to-partner-with-the-retailer-of-the-future#

. Marc Gilbert, Andreas Gocke, Peter Rosenfeld, and Robert Tev-elson, Suppliers as Partners: A Catalyst for Savings [электронный ресурс] []. URL: https://www.bcg.com/pub-lications//sourcing-procurement-supply-chain-manage-ment-suppliers-as-partners.aspx

. Janet Wagnera, Sabine Benoit. Creating value in retail buyer–vendor relationships: A service-centered model [электронный ресурс] []. URL: https://www.sciencedirect.com/science/ar-ticle/pii/S

. Connor Gillivan. Supplier Relationships — How Do They Impact Retail? [электронный ресурс] []. URL: http://connorgilli-van.com/supplier-relationships-aff ect-retail/

. Gadi Benmark, Sebastian Klapdor, Mathias Kullmann, and Ram-ji Sundararajan, How retailers can drive profi table growth through dynamic pricing [электронный ресурс] []. URL: https://www.mckinsey.com/industries/retail/our-insights/how-retailers-can-drive-profitable-growth-through-dynamic-pricing

H — H

Herfendahl — Hirshman index calculation problem for diff erent markets

A P, A S, I D StudentsRussian Presidential Academy of National Economy and Public Administration Faculty of Economic and Social Sciences

A L Senior Lecturer Russian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

A

Herfendahl-Hirshman index is a common way to ac-cess the level of monopolization in the USA starting from . It shows how legal it is to make any mergers or absorption’s by companies. Nowadays it is widely used in many countries to estimate the market state and solve many judicial proceedings. This index helps small companies to develop with-out any concerns that “big players” would easily consume them or just make bankrupt. Even now many mistakes are made by calculating it — and they are not even numeral. This article presents the com-mon practices that are used in countries to calculate HH index, an analysis of problems that could lead to

miscalculation of the index and some advices to avoid these mis-takes. During the work, diff erent practices were found and ana-lyzed, examples data was made and then developed into the check-list which presents cumulative information which would help to avoid possible miscalculations.

Key words: Herfendahl-Hirshman index, HH index, marketing, mergers, absorptions

I

Herfendahl-Hirshman — the indicator which is used for the as-sessment of the industry monopolization. It was named after Or-ris Herfendahl and Alberth Hirshmann, who introduced its prior form.

To calculate HH index it necessary to wield the information about market shares of the companies, which are presented on the market. After this, the formula would be the following:

HHI = S + S

+ … + Sn

S — part of market equity of companyn — number of companies on marketAfter the calculation, it should be compared to the following

table:T . HH index market type

HH index Market type - free competition- monopolistic competition- oligopolyMore than monopoly

Nowadays the HH index popularity raised to the worldwide levels. It is used not only in the marketing sphere but many o thers, including ethnic levels, population density, etc. Neverthe-less, the disputes across the index are growing and growing — there are many problems which could occur during the calcula-tion and which can lead to poor results.

To prevent such possibilities, the research was conducted. The main aim of it was to create a check-list and some advices, which

I. M, Q M C H — H

could help during the calculation of the index. The main steps of the investigation and the check-list with advices are presented below.

I HH

In order to defi ne main problems, virtual situations were con-structed.

Example — Interception

The fi rst one is related to the interception. There are fi ve drug manufacturers on the market (A, B, C, D and E). Each of them has the same market share. Consequently, the Herfendahl-Hirsh-man — Hirschman index will be equal to two thousand, and the type of market will be oligopoly.T . Example calculations

Market equity Market equity ^ Company A % Company B % Company C % Company D % Company E % Herfendahl — Hirshman index

Market type Oligopoly

This is a common example of HH index calculation. But even on this stage minor mistakes can be conducted. For example, it

is not necessary to include companies with less than % of mar-ket equity — they would not change the index at all. It is better to eliminate them from the index and divide left percent to the higher companies.

Example — Diff erentiation

The second one is diff eren-tiation. Let us consider the same example, but with dif-ferent conditions.

The same manufacturers, but however three out of fi ve factories belong to the same investor and are locat-ed in diff erent places. Then the Herfendahl-Hirshman index will be equal to , and this is already a monop-oly.

Such a correspondence leads us to the second new rule — you should check the owners of the companies. By check-ing it, you can fi nd that the owner is the same — and in the end, it would come to the completely diff erent type of calculations.T . Example calculations

Market equity Market equity ^ Company A B C % Company D % Company E % Herfendahl — Hirshman index Market type Monopoly

Example — Market split

The third example is market split. What if company A recently ap-peared on the market after research and released a new medicine

Drugs market

Company А Company B Company C Company D Company E

P . Example Interception

Drugs market

Group of companies

Company A

Company B

Company C

Company D Company E

P . Example Diff erentiation

I. M, Q M C H — H

that has no analogues. Will it com-pete with others? It is unlikely, as they are forbidden to produce med-icine without possessing a patent.

Therefore, it is more reasonable to divide them into two markets.

On this basis, in the fi rst market, the Herfendahl-Hirshman index will be equal to , (Pure mo-nopoly), and in the second, , (Oligopoly).

This strategy is related to the market tool of positioning — Blue Ocean. You place yourself on the market which is completely diff erent from the market on which you are now. This gives a diff erent calcula-tion — and mostly is unconsidered.

T . Example calculations

Market equity Market equity ^ Company A % Herfendahl — Hirshman index Market type Total monopoly

Market equity Market equity ^ Company B % Company C % Company D % Company E % Herfendahl — Hirshman index Market type Oligopoly

Example and — POS and Franchise market

The fourth and fi fth examples are applied to the same companies, but with completely diff erent conditions.

There are two main toy sellers on the market — A and B. Sell-er A has points of sale, and Seller B has . Each of the stores

has an equal market share. On this basis, the Herfen-dahl-Hirshman index will be equal to , which corresponds to a mono-poly.

However, what if all the shops of seller B are franchise sold? Then the market will look very dif-ferent.


Market equity Market equity ^ Company A % Company B % Herfendahl — Hirshman index Market type Monopoly


Market equity Market equity ^ Company A % Company B % Company B % Company B % Company B % Company B % Company B % Company B % Company B % Company B % Company B % Company B % Company B % Company B % Company B % Company B % Herfendahl — Hirshman index Market type Oligopoly, close to monopolistic competition

Drugs market

New drug market

Company A

Generic market

Company B

Company C

Company D

Company E

P . Example Market split

Toy market

Company A

(5 points of sail)

Company B

(15 points of sail)

P . Example – POS and Franchise market

I. M, Q M C H — H

The market has changed and has even become close to monop-olistic competition. What a paradox. But it usually happens in our daily life — just check how the small coff ee shops are made by their own and big franchise Starbucks carefully consumes them. But the process of competition comes from the diff erent owners, what brings to another type of calculation.

C

So, it can be clearly seen that the calculation of the Herfendahl-Hirshman index is not as simple as it seems at fi rst glance. That is why the following check list and advices were conducted.T . Checklist

Question Tick boxDo all companies apply market you prescribe them?Does any of the companies wield the product hard to copy?Do all the points of sale apply to the same company?Does any of the companies is included in conglomerate?

If any of the boxes is ticked, you should improve the calcula-tion you make.

Advices

. Always check not only product sales, but the revenue too — sometimes it can be a good point to reshape market into diff erent one.

. Don’t include companies which wield less than % of eq-uity. This would not help improving the index. It is better to take them off and give the left percent to the higher companies.

. Check the monopolization law of the countries. According to it, the level of monopolization can be considered diff er-ently, what can lead to change in calculation.

R

As the result of our research a check-list and some advices for better calculation were found. They would help to improve HH

index calculation, but it does not make it fi nal. Even now the HH index has some problems which still need further research. This problem still remain vital, because of it high rate of spread among all spheres and levels — including political one. That is why it is important to continue investigation towards this sphere.

R

. Kotler, Philip. . Marketing — An introduction. Englewood Cliff s, NJ: Prentice-Hall.

. Leonow, Alexander. . Marketing basics. Moscow: Econ-In-form.

P

Process mining as an advanced tool for process analysis:logistics department case study

A C, G B, Z AStudents of Russian Presidential Academy of National Economy and Public Administration Faculty of Economic and Social Sciences

E IHead of Management and Entrepreneurship Department of Russian Presidential Academy of National Economy and Public Administration Faculty of Economic and Social Sciences

A

Supply chain and logistics are the core of modern producing companies. Any deviations and bottle-necks that take place in this area may cause signif-icant repercussions for the whole business. Further-more, within the modern hectic lifestyle, the con-ventional methods of analysis and compliance checking are becoming less and less productive and frequently lead to subjective conclusions. This arti-cle is devoted to the application of process mining techniques, which are built around completely dif-ferent algorithms and allow to obtain quick and ac-curate results on the basis of the data logs extract-ed from the already existing information systems.

Key words: process mining, process analysis, business process management, BPM, logistics pro-cesses

I

Despite the fact that the fi rst mentions of Process Mining start-ed arising as far back as in , it continues being a new and rapidly growing research area of Business Process Management (BPM) even today. The concept behind this toolkit refers to the possibility to discover, analyse and improve existing processes using the data logs extracted from the information of a company or any other type of institutions [].

Being a bridge between data mining and conventional meth-ods of BPM, Process Mining is signifi cantly more process-centric than the majority of previously employed techniques. The key diff erence is that it uses sequentially recorded events, which, in its turn, opens up a wide range of innovative algorithms for vis-ualisation, compliance check, etc.

The aim of this article is to present a real case study involving the analysis of the logistics department of an international man-ufacturer of domestic appliances. The abovementioned scope of activity seems to be fundamental for any producing company since it is directly related to its capability of high-quality stock management and salesmanship. Therefore, the results obtained during the project implementation are of particular value both for future research and practice.

G

The problem

In this article we will provide a thorough description of a project, the objective of which was to analyse the event logs from the ERP-system of the Company’s logistics department and identify deviations that worsen its effi ciency.

The comparison of AS-IS and TO-BE models

One of the fi rst steps of the conducted business process analysis was to compare real visualized process with its ideal version. The

I. M, Q M C P

project team was provided with a TO-BE model of the process, which demonstrates how work of the logistics department is expected to be done. As can be seen from picture , it is mainly linear, i. e. there are no forks, the only fork that can occur takes place in case of a return. However, this op-eration is somewhat rare (% of all cases).

Based on the data from the ERP-system, AS-IS model has been created in order to describe how the process is really organ-ized. The map of the real process with all actions and paths is depicted in Picture .

Initially, it might seem that models dif-fer signifi cantly. Nevertheless, these dif-ferences are caused by the fact that a suf-fi cient number of infrequent connections are shown in AS-IS model, some of them happen once or twice in all cases.

Therefore, it was decided to fi lter the least frequent paths, which resulted in the model (Picture ).

Models in pictures and look similar, which means that the majority of orders comply with the preconceived process. Nevertheless, some devia-tions still occur. For in-stance, action Credit Note takes place after Goods Is-sue in AS-IS model, while two more actions Return Order and Return Delivery happen in TO-BE model. However, this deviation can be easily explained. SAP application lacks sep-arate actions for return process, namely Return Delivery and GD Goods Issue. Instead they are marked as regular delivery and write off , which in turn, distorts the visualization of the process. Furthermore, an action called Confi rmation of Service is present in the logs, but it is not present in TO-BE model but this diff er-ence is not a deviation, this action simply occurs automatically, and that is why it is not taken into consideration in TO-BE mode l.

Discovered loops of actions Delivery and Sales Order are worth mentioning, however, these and other deviations are harder to explain. Consequently, they will be examined in detail in the re-maining of the article.

I-

Method and deviations

During the analysis the well-known Pareto or / principle was used, and it was decided to divide the data set into groups.

Order

Delivery

Goods Issue

Invoice

Return Order

CreditNote

Return Delivery

QTY

Diff

eren

ce

Pric

e D

iffer

ence

P . TO-BE model

Confirmaionof service 909

Sales Order2,465

Delivery2.000

GD Goods Issue937

Invoice902

Credit Note50

Return Order43

968

286

61

1,495

11

1

1

1

11025

292

638277

277

63139

3

46

862

10

1

1

2

1630

908

1,007

P . AS-IS model (all aspects)

968

28

61

25

638

631

39 3862

630

908

1,007


Sales Order2,465

Delivery2.000

GD Goods Issue937

Invoice902

Credit Note50

Return Order43

P . AS-IS model (the most frequent paths)

I. M, Q M C P

The fi rst group contained % of the cases and % of so-called variants, which are basically clusters that unite the cases following the same paths. It covered the most mainstream cases, and this is well illustrated by its visualisation in picture , which is almost identical to the TO-BE model.

The second group contained the other % of the cases, which, in their turn, were divided between the % of the variants. As can be derived from the picture, it mainly consisted of the devi-ant cases, which will be discussed further.

Throughout the analysis diff erent deviations from TO-BE model were identifi ed, yet many of them were rejected after the discussions with the company representatives. The reason for that is because they are normal, but not actually taken into ac-count by TO-BE model. The rest of the deviations can be seen in the table.

Changes in order

This deviation is an alteration of activities: Sales Order and De-livery, which is caused by the non-availability of certain goods at

stock. The main reason for such deviations is the diffi culty in communication with the warehouse that doesn’t allow logisti-cians to monitor the stock in real time.

Delivery repetition

It is a sort of a loop, which makes one and the same activity to be triggered several times. Due to the fact that Delivery covers many possible actions in real life, it is actually possible to explain its appearance once or twice during a case. In fact, however, there are cases with , and even Delivery stamps, which defi nitely need to be examined.


Sales Order707(148)

Delivery381(147)

GD Goods Issue937

Invoice142(140)

Credit Note50(46)

Return Order43(38)

39

286(6)

186

519(118)

1(1)1(1)

1

1(1)

1

11025(23)

80(73)

638277

56(56)

83(83)39(31)

10(10)

46

102

3(3)

1(1)

1

2(2)

182(81)

148

170(106)

789(767)

7(7)

22(22)

548(548)

548(548)

760 7(7)

548(548)

767

837(738)


Sales Order1.765(767)

Delivery1.626(767)

GD Goods Issue767(767)

Invoice760(760)

Credit Note7(7)

P . Case division in two groups

T . The most frequent deviations in the logistics process and frequencies of their occurrence

Deviation Absolute frequency

Share in deviant cases

Share in all cases

. Changes in order ,% ,%

. Delivery repetition ,% ,%

. The lacks of Confi rmation of service, invoice, return order

,% ,%

. Multiple repetitions of Confi rmation of service и GD Goods Issue

,% ,%

. Repetition of the return process

,% ,%

P . Example of a change in an order

I. M, Q M C P

The lack of Confi rmation of Service, Invoice and Return Order

About % of the cases that were analysed lacked some of the ac-tivities that seem to be necessary for any possible order. Such de-viations might be caused by the ERP-system error or by the irreg-ularities in the work of the logisticians.

Multiple repetitions of Confi rmation of service and GD Goods Issue

A curious characteristic of this deviation is that it lasts for a few minutes or even seconds. That’s why, in all likelihood, its cause can be found in the ERP-system program code and doesn’t real-ly correlate with the real process. Nevertheless, it does use cer-tain system capacity and can overload it.

Repetition of the return process

It is one of the rarest deviations described yet it causes signifi -cant time delays and deviations from the TO-BE model standards.

Trying to assess the eff ect of such deviations, the idea of ana-lyzing the time diff erence between mainstream and deviant cas-es occurred, the outcome of which you can see in picture. In short, deviant cases last more than twice as much as mainstream ones and have , times more events. There are some cases, the aston-ishing durations of which are , and even days.

P . Example of delivery repetition

P . Example of a lack of Confi rmation of Service, Invoice and Return Order

P . Example of Multiple repetitions of Confi rmation of service and GD Goods Issue P . Example of repetition of the return order

I. M, Q M C P

T . Time comparison between standard and deviant cases

Deviant StandardMedian duration (days) d , dAverage duration (days) d , dNumber of events , ,

Such fi gures fl atly contradict the company’s standards. There-fore, in order to maximize the effi ciency of the logistics depart-ment and bolster the company’s reputation, it is necessary to elim-inate the possibility of occurrence for such process deviations.

As a fi nal step of the research, the work of the logisticians them-selves was analyzed. The result of it can be seen in the picture. The percentage of deviations seems to be pretty similar but the work itself is distributed unequally. For instance, logisticians and to-gether do almost % of the total work. According to the informa-tion provided by the company representatives, each employee has their own accounts, so it is defi nitely not the cause. For this rea-son, it was believed that this fact required further investigation.

R

Summing up, it should be mentioned that although on the whole the processes in the department are well-organised, sometimes

deviations occur and have a negative impact on its work. There-fore, we recommend to:

• to streamline the communication process between depart-ments, including the unifi cation and aggregation of exist-ing ERP-systems;

• to review the existing TO-BE model and add information to it;

• to look for incorrect terms and/or loops in the program code of the ERP-system;

• to change the user interface in order to prevent an order’s development, if obligatory actions are not performed;

• to identify the reasons for the unequal work distribution among logisticians.

C

In this paper the logistics department’s business processes were examined using Process Mining techniques. As expected, this method turned out to be useful because it allowed to identify a number of overlooked deviations. Furthermore, one of the unique characteristics of this approach are its generality and capability of being reproduced in the future. Therefore, once implemented by a company, this toolkit may also be used in other departments.

A

The article itself is a part of the results obtained during the uni-versity project at the Faculty of economic and social sciences (FESS), the Russian Academy of National Economy and Public Administration (RANEPA).

All the analyses and process visualizations mentioned in the presentation were done with the help of Disco by Fluxicon BV.

R

. Van der Aalst W. M. () Process mining: discovery, conform-ance and enhancement of business processes. Springer.

0% 5% 10% 15% 20% 25% 30% 35% 40%

Logist 2

Logist 1

Logist 6

Logist 5

Logist 3

Logist 4

Workload share Share of deviant cases

P . Work distribution among employees and share of deviant cases in their work

I. M, Q M C

. IEEE () Task force on process mining. Process mining man-ifesto. Business process management workshops, Berlin, Heidel-berg: Springer, pp. –.

. Rozinat A., van der Aalst W. M. () Conformance testing: Measuring the fi t and appropriateness of event logs and process models. Business Process Management Workshops, Berlin, Hei-delberg: Springer, pp. –.

Comparative study of certain factors determining qualityassurance in higher education between Hungary and Russia

B HPhD candidateSzent István University, Faculty of Economics and Social SciencesInstitute of Social Studies and Lecturer Training

K DVisiting LecturerRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

T MMaster lecturerBudapest Business School — University of Applied SciencesFaculty of International Management and Business Institute of Commerce and Marketing

M KHead of Planning and Organization of Educational ProcessRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

A MUniversity Associate LecturerSzent István University, Faculty of Economics and Social SciencesInstitute of Social Studies and Lecturer Training

I. M, Q M C C

A

After the establishment of its economic union, Europe was indis-pensable to the actual establishment of its social union. The main driving force behind the European Higher Education Area was the promotion of mobility among the acceding Member States through the comparability and acceptance of the diplomas awarded. To achieve this, the training courses in the higher edu-cation institutions of the Member States will be regularly moni-tored and evaluated on the basis of the Quality Standards and Guidelines for the European Higher Education Area (ESG). In our study, we compare the domestic and Russian accreditation pro-cedures.

Key words: European Higher Education Area, ESG, quality as-surance

I

The compliance to the expectations of today’s fast-paced glo-balized world poses greater and greater challenges for nations. Establishing the European Union meant not only economic inte-gration but a political union as well where all citizens of the member states of the European Union are entitled to equal rights. These rights include the free movement of labour also.

The great bottleneck in the practical realization of this prin-ciple was the inharmonious higher education system whose har-monisation processes started in the s and the Bologna Dec-laration signed at the end of the millennium can be regarded as its pinnacle.

Sorbonne University celebrated its years of existence in and in the framework of this celebration four leading Euro-pean states issued a joint declaration which became known as the Sorbonne Declaration. In this statement it was stipulated that Europe can only pick up the pace the competitors dictate if it be-comes the Europe of knowledge and it harmonises the work be-ing done in the institutions of higher education and not just dealing with the issues of politics and economics. This harmoni-sation would open the option of mobility not only for students

but for tutor/researcher employees as well, thus promoting the free movement of labour and integration in the member states. At the end of the declaration the signatories called upon the oth-er member states to join the initiative and they forecasted the necessity of institutionalising the harmonisation of the Europe-an higher education. (Csekei, L (a))

A year later, during the conference organized in Bologna member states already had joined the invitation and supported the realisation of the initiative by signing the declaration. Fol-lowing this event the ministers of education got together about every two years to fi ne tune the contents of the Bologna Decla-ration, to institutionalise the realisation of goals assigned by and to be able to establish the EFT, the European Higher Ed-ucation Area. (Csekei, L (b))

One of the aims of the establishment of the EFT was to form a European cooperation based on comparable criteria and meth-ods to be able to synchronise the quality assurance of the Euro-pean Higher Education (Bologna Declaration, ). The en-hanced role of the quality assurance of higher education was fur-ther strengthened by the commitment towards quality manifested during the second meeting by the ministers in Berlin in . The ministers agreed that a quality assurance system was the key to mutual trust, acceptance of the issued degrees as well as to the encouragement of mobility.

It was during this conference that the E, the European Asso-ciation for Quality Assurance in Higher Education (ENQA), the European University Association (EUA), the European Associa-tion of Institutions in Higher Education (EURASHE) and the Eu-ropean Students’ Union (ESU) were asked to prepare for the next meeting a standardised qualifi cation credit system accepted by all member states of the European Union. Fulfi lling the request and meeting the deadline specifi ed a document was drawn up, the Standards and Guidelines for Quality Assurance in the Euro-pean Higher Education Area, hereinafter referred to as ESG. Thus due to the Bologna process the ESG was prepared by and by establishing the registry of quality assurance agencies the insti-tutionalisation of cooperation has started in the specialization of quality assurance (Csekei, L. (c)).

I. M, Q M C C

M

The examined issues are analysed and discussed empirically in this material partly by processing related professional literature sources, partly by observation carried out as participants of the educational and operational processes in the Hungarian and Rus-sian institutions of higher education, furthermore by analysing the experiences obtained by following the accreditation process-es of Hungarian and Russian institutions of higher education, as well as examining documents related to the topic. During the re-search qualitative analysis also took place by applying the inter-view method.

R

As a result of the processes induced by the Bologna Declaration after six years in Bergen () the framework of Standards and Guidelines of Quality Assurance in the European Higher Educa-tion Area was approved, which ensured the standardized accred-itation of EFT institutions of higher education in the following decade. In during the last meeting of the ministers in Yere-van the substantially renewed ESG, based on the experiences col-lected in the last ten years, was approved. (Kováts, G. — Temesi, J., )

The communiqué issued by the ministers of education pre-sented the results of the meeting in Yerevan and they were ex-pressed in the following policies:

• Enhancing the quality and relevance of learning and teach-ing

• Fostering the employability of graduates throughout their working lives

• Making our systems more inclusive (social sensitising)• Implementing agreed structural reforms

(Yerevan Communiqué, )

In the introduction of the Hungarian version the changes of the new framework were summarized by Tibor Szántó. Without giv-ing a very detailed explanation here, we can highlight that he

mentioned the following changes: it became clearer and more standardized and easily interpreted by consistently separating the document standards and guidelines and the main concepts. The main structure of the standards and guidelines did not change (Part ), but regarding the content and wording some changes have been made. Furthermore, a few new ones were add-ed (e. g. . Student-oriented learning, teaching and evaluation). When assessing the changes, we can state that as a result the standards and guidelines became more defi ned and transparent and these facilitate the achievement of the goals for the next pe-riod of the EFT. (ESG, )

According to the expectations of the ESG the revision and re-organization of the Russian accreditation system has started. As the newest element of the reform series of the education system in the Russian Federation which has been in progress for years, the reorganization of the work of the Ministry of Education and Science started in May . Within this process the primary ed-ucation and secondary education were separated as the fi rst step. Two new and separate ministries were established: the Ministry of Education is responsible for primary and secondary education and the Ministry of Science and Higher Education oversees the activities in higher education in the Russian Federation. Next, in July the Federal Service for Supervision in Education and Science (Rosobrnadzor) was separated from the ministries and it operates as an organizational unit directly reporting to the gov-ernment.

T H B P

Following the change of regime the number of students entering into higher education as well as the number of tutors began to in-crease at the same time. Due to this change education became somewhat operational which called for establishing new educa-tional methods (e. g. distance learning). With the purpose of avoid-ing the deterioration of the quality of education due to the sud-den changes of external circumstances, the Act LXXX of on Higher Education established the National Accreditation Commit-

I. M, Q M C C

tee (a bit later the Hungarian Accredita-tion Committee, abbreviated as MAB (Figure ). According to Article para-graph () the task of the Committee is ‘the continuous monitoring of higher education, the standard of scientifi c ac-tivity and certifi cation’ to ensure the ex-ternal quality assurance of the institu-tions. According to Article paragraph

() of Act CCIV of ‘MAB is an independent national body of professionals which was set up for the external evaluation of the training, scientifi c research, artistic activities and the operation of inner quality assurance system of the institutions of higher edu-cation and it participates as a body of experts in the procedures concerning the institutions of higher education according to the regulations of the pertaining law’. Furthermore, its tasks and au-thority as well as its structure are described in Article and .

The Government Decree / (II.) pertaining to the is-sues of quality assurance and development declares that MAB is a non-profi t professional body which carries out the quality as-surance of trainings in institutions of higher education and ac-credits those according to ESG.

In its twenty-fi ve years of existence MAB has carried out the accreditation of the whole set of institutions in the Hungarian higher education according to the regulations in a systematic way and in more ‘rounds’. In the profession these are called ac-creditation cycles. Three of these had already closed and accord-ing to the accreditations started due to the changes of ESG in the fourth cycle has started.

The accreditations in the fi rst cycle were conducted between and and the institutions were mostly accredited for eight years but some of them were accredited for shorter periods. The second cycle of accreditation was carried out between and (from it was carried out according to the ESG), then in the autumn of the third accreditation of institutions started.

The institutions must pay attention to the validity of the ac-creditation and apply for extensions when needed and for the

carrying out of the regular (earlier eight years, from fi ve years) quality assurance procedure MAB establishes a profession-al visiting committee which consists of educational and research professionals and representatives of students. The committee ex-amines the self-evaluating reports and pertaining documents and then has an onsite visit (– days depending on the size of the institution). Following the visit, the evaluation report is prepared which is presented to and is discussed by an ad hoc board and then by a Plenum/Body ( members of the MAB). After the ap-proval of the report a resolution is made.

In Hungary the operational permits of institutions in higher education are inspected by the Ministry of Education (OH) and if compliance to the rules is decided then a new permit is issued and this process repeats every fi ve years. Part of the process in-cludes that for OH it is obligatory to request the expert opinion of MAB about the institution which opinion is formulated by and based on regulated procedures according to the European quali-ty assurance standards in higher education (ESG). If during the investigation process an institution in higher education does not receive satisfactory qualifi cation, the renewal of the operational permit is not issued and the institution cannot continue its op-eration (Act CCIV of ).

During the accreditation process the visiting committee exam-ines if the contents of the Act pertaining to Higher Education are adhered to in the given institution of higher education and whether the requirements of ESG are fulfi lled paying special at-tention to the extent of student satisfaction. Among the basic principles of accreditation there are independence, objectivity and professional impeccability. The process itself must be verifi -able, the results must be public and last but not least the stand-ards must be in accordance with international practice.

Since MAB was established — besides institution accredita-tion — it has carried out program accreditation procedures simul-taneously by the requests of controlling bodies, which includes the detailed and professional quality assurance examination of the training programmes of a certain scientifi c fi eld (parallel ac-creditation) extended to the whole country and carried out si-multaneously. When drawing up the new accreditation procedure

F . The logo of the Hungarian Accreditation Committee

I. M, Q M C C

MAB was determined to have the institutional and programme accreditation requirements to be fulfi lled within the framework of one procedure. (www.mab.hu)

T R F

There are two parallel systems in the accreditation of institutes in higher education in the Russian Federation. Besides the state accreditation a professional public accreditation is also available. The two systems diff er in several ways. While the state accredi-tation is geared for investigating whether the institution com-plies with the Russian educational standards, the professional ac-creditation aims at defi ning those accomplishments which high-light the outstanding result achieved in the educational and scientifi c fi eld. This accreditation is based on the Russian stand-ard as well as on the principles of the ESG. The accreditation committee consists of foreign professionals who represent not only the scientifi c community but the profession and the stu-dents’ interests as well.

The state accreditation of educational institutions was fi rst stipulated in a federal act on education issued in (.. № –). Since then the system of accreditation has been re-vised on many occasions but its importance was preserved. The system of accreditation constitutes an integral part of the con-cept included in the Russian Federal Program of Education and Development for the time period of – since ’develop-ment of the quality assurance system of the secondary and high-er education via the assessment of the independent accreditation and the quality of programs in education means the assurance of the execution of accreditation mechanism in vocational and pub-lic education’ (Federal Educational Development Program, –).

The Federal Service for Supervision in Education and Science (РОСОБРНАДЗОР — Figure ) which was established in is responsible for education and sciences and similarly for the exe-cution of accreditation tasks. The regulation of its operation was renewed on th July in by issuing the latest regulations of

the Federal Service for Supervision in Education and Science.

The aim of the state accredita-tion of educational activities is to strengthen the compliance to the federal state educational norms in the educational activities of the ed-ucational programs and education-al organizations. The state accredi-tation of educational activities is executed according to the main ed-ucational programs specifi ed in the federal state educational norms. The aim of the accreditation process is to defi ne whether the content and quality of the training program complies with the standards of state accreditation programs and the federal state education. During the accreditation process of the training programs accreditation expert inspections are not held (this be-longs in the jurisdiction of the body which establishes education-al standards — ФГОС — the Russian state system of standards). Accreditations are carried out for entire institutions and individ-ual faculties or specializations cannot be examined and accred-ited on their own.

We would like to present the accreditation process in the Rus-sian Federation by showing the results of our quantitative re-search. The interview was made with Margarita Kozlova at her in-stitution who is an employee of the RANEPA Faculty of Econom-ics and Social Sciences after fi nishing the latest accreditation process in .

The institution applies for the process of accreditation by fi ll-ing in an application form. The application has to be turned in the previous year thus providing enough time for preparation. The Federal Service for Supervision in Education and Science consid-ers the application in a few weeks and the offi cial accreditation process starts from the receipt of the information notice. The preparation is in progress simultaneously at the institution by checking the compliance with the requirement list issued by the Federal Service, and at the Federal Service where the public data of the institution is examined approximately in one month. The

F . The emblem of the Federal Service for Supervision in Education and Science

I. M, Q M C C

Service continues the examination with onsite inspection and for this event a visiting committee is formed. During the process the committee examines if the institution and its subunits fulfi l the requirements of the state which are stipulated in the Law on Ed-ucation. The visiting committee forms an opinion based on the online and onsite inspections and other opinions which are sent to the Federal Service for Supervision in Education and Science. Then they make a decision about the accreditation process wheth-er it was successful or it had a negative outcome.

If the process of accreditation has a positive outcome, the in-spected institution receives a six-year permit/accreditation reso-lution.

If the process of accreditation has a negative outcome, the Ser-vice chooses from the options below:

• Carries out an ’unplanned’ inspection again, and forms an opinion again

• Might terminate the operation of the institution• Or it withdraws the accreditation of the institution (in this

case the institution can continue its operation as a non-ac-credited institution but the degrees issued during this pe-riod of time cannot be accepted as qualifi cation of higher education).

If the accreditation process has a positive outcome, the inspect-ed institution receives a certifi cation for six years which is the basis of the issuance of state recognized degrees. Training cours-es which are started and continued without a successful state ac-creditation do not result in providing qualifi cations of higher ed-ucation since the institution which fails the accreditation process cannot be considered as an institution of higher education.

C,

As a conclusion of our research we can state that the accredita-tion processes in institutions of higher education in Russia and in Hungary have several similarities:

• The operation of institutions of higher education must be licensed

• ESG serves as the foundation of conducting the processes• In both countries an independent institution system con-

ducts the accreditation processes• The accreditation processes include onsite inspections be-

sides the document examination• Under the umbrella of one accreditation process the inspec-

tion of viewpoints of institutional operation and profes-sional aspects are examined simultaneously

• The members of the onsite visiting committee are recog-nized professionals in the fi elds whose profi les fi t the spe-cialization of the inspected institute and they are aware of the quality assurance policies of higher education

• The institutions themselves must initiate the accreditation process

• The costs of the accreditation process are borne by the in-stitutions

While carrying out our research we considered the diff erences as well:

• The Russian accreditation process is static in its character, it examines issues at the given moment, the institutions do not have to conduct a preliminary self-assessment and turn that in to the organization of accreditation

• In the Hungarian accreditation process the procedure is based on the self-assessment of the inspected institution pertaining to the past fi ve years of operation and on the in-formation found on public platforms which is amended by information gathered by onsite visits

• Diff erent validity period of the accreditation (in Hungary it is fi ve years, in Russia it is years)

• The level of commitment to the fulfi lment of ESG criteria is diff erent, in Hungary is it stronger

• In the Russian Federation institutions need the successful accreditation for keeping their permits for operation but as opposed to Hungary the minimum requirement is the ad-herence to the Russian accreditation norms and not adhe-rence to the ESG.

I. M, Q M C C

• Regarding the results of accreditation processes carried out by MAB the institutions receive not only a resolution but a professional opinion also, as well as suggestions for the continuous development and facilitation of the principles of the ESG. As opposed to this the Federal Service for Su-pervision in Education and Science issues only a resolution but does not provide recommendations for further develop-ment for the institutions.

As a result of our research we have shed light on the fact that be-tween the accreditation procedures of the two countries there are several diff erences, out of which the most signifi cant is manifest-ed in the need to conform to the criteria of the ESG. Despite the fact that Russia is a major player in the European Higher Educa-tion Area and applying the ESG is equally mandatory for all mem-ber states, the application of the practice of conforming to the ESG requirements in Russia is not as well-developed as it is in Hungary.

In order to facilitate the educational/researcher and student mobility the Russian Federation recognized the need for devel-oping its mandatory state accreditation system which is clearly manifested in the changes instigated in where the fulfi l-ment of the expectations of ESG now has greater importance.

R

. Kováts Gergely- Temesi József (): A magyar felsőoktatás egy évtizede –. NFKK Kötetek, . Budapest Corvinus Egyetem Nemzetközi Felsőoktatási Kutatások Központja, Buda-pest.

. Csekei László (a): A bolognai folyamat előzményei https://tka.hu/nemzetkozi//a-bolognai-folyamat-elozmenyeiCsekei László (b): A Bolognai Nyilatkozat és az európai felsőa felelős az akkreditációk lebonyolításoktatás https://tka.hu nemzetkozi//a-bolognai-nyilatkozat-es-az-europai-fel-sooktatas

. Csekei László (c): A Bolognai Nyilatkozattól az Európai Felsőoktatási Térségig (-ig): a bolognai folyamat

https://tka.hu/nemzetkozi//bolognai-folyamat-es-az-eu-ropai-felsooktatasi-terseg--ig#Pr%C%Aga

. Russian Federal Program of Education and Development (–)

. Bologna Declaration http://www.nefmi.gov.hu/felsooktatas/tu-dastar/bolognai-nyilatkozat

. Quality Standards and Guidelines for the European Higher Ed-ucation Area (ESG ) https://enqa.eu/indirme/esg/ESG%in%Hungarian_by%OFI-HAC.pdf

. Yerevan Communique, https://tka.hu/hir//jerevani-kommunike

. Federal Act on Education (.. № –)

. /. (II. .) Korm. Rendelet a felsőoktatási minőségértékelés és -fejlesztés egyes kérdéseiről

. . évi LXXX. törvény a felsőoktatásról

. évi CCIV. törvény a nemzeti felsőoktatásról

. Oktatási Törvény, Федеральный закон «Об образовании в Российской Федерации» от .. № –

. MAB website www.mab.hu

Q R — L ESG

Quality and Responsibility — Lessons learnt from the ESG based institute accreditation for higher educational institutions

A MUniversity Associate Lecturer Szent István University, Faculty of Economics and Social Sciences Institute of Social Studies and Lecturer Training

B HPhD candidateSzent István University, Faculty of Economics and Social SciencesInstitute of Social Studies and Lecturer Training

T MMaster lecturerBudapest Business School — University of Applied Sciences Faculty of International Management and Business Institute of Commerce and Marketing

K DVisiting LecturerRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

A

The creation of the European Higher Education Area (EHEA), as a result of the Bologna process that

started in , can be related to the Ministerial Conference Bu-dapest-Vienna in , that is the offi cial the launch time of the EHEA. This does not mean, of course, that all the objectives of the Bologna Process in each of the acceding countries were fully met by .

But it can be taken as a fact that the higher educational insti-tutions of the member countries have put a great force in the past one and a half decade into developing quality assurance systems, that are aligned with the Standards and Guidelines for Quality Assurance in the European Higher Education Area (ESG).

In May , at the ministerial meeting in Armenia, Yerevan, the ESG criteria system was revised and adopted based on a decade of experience of application, published as an ESG document.

The study highlights the novelty of the new ESG requirements for higher education institutions and the diffi culties they face in implementing accreditation procedures (both institutions and accreditation bodies).

Key words: higher education, quality, quality assurance, ac-creditation

I

ESG sets standards and guidelines for the quality assurance of higher education in the internal and external fi eld. ESG does not mean specifi c quality standards, nor does it specify how quality assurance processes are applied; instead, it serves as a guideline in all areas that are essential for quality service and learning en-vironment in higher education.

The ESG covers all higher education activities, regardless of the mode and location of the studies. So the ESG can be applied to all types of higher education, including transnational and cross-bor-der services. The ESG can be interpreted in a broad context, which creates the basis for transparency in higher education and strengthens mutual trust in the European Higher Education Area.

ESG is basically about quality assurance in learning and teach-ing in higher education. It covers the learning environment and relevant links to research and innovation.

I. M, Q M C Q R — L ESG

Standards set the quality assurance practice for higher educa-tion adopted in the European Higher Education Area; therefore, standards should be taken into account and respected by all stakeholders in all types of higher education.

In Hungary, according to the accreditation practice in the countries of the European Higher Education Area, the Hungari-an Accreditation Committee (HAC) examines compliance with ESG standards in the framework of the institution accreditation procedure.

The institutional accreditation process focuses on a meaning-ful self-assessment by the higher education institutions, which is an eff ective tool for the institution’s internal quality improve-ment and at the same time provides the basis for the quality as-surance and quality assessment activities of the HAC.

The purpose of self-assessment is to analyze the quality of ed-ucation, research, creative work, social success, the self-critical analysis of the functioning of the institution, to show its values, to reveal its problems, to gather the systematic information needed to plan the next steps of institution building.

M

Examining the topic in an empirical approach, basically discuss-ing the related literature and legal sources and discussing it in the present material. This is complemented by the processing of their experience gained through the monitoring of accreditation procedures for higher education institutions and the analysis of related documents.

It was possible to collect and analyze data and information in the case of institutions out of higher education institutions operating in Hungary (the sample provides % representativity). The results and fi ndings of this study are based on the analysis of the fi nal documents of the accreditation process based on the

“new type”, ie ESG requirements, carried out in the years – by HAC.

The higher education institutions included in the study — in terms of their training portfolio — operate in the fi elds of agricul-ture, economics and technical and social sciences, but there are

also institutions that carry out church and religious training in the sample. In terms of their size, the examined institutions have a student population of between and , based on the number of students.

R

The ESG standard is divided into three parts:

• internal quality assurance (ie standards and guidelines for higher education institutions),

• external quality assurance,• quality assurance agencies.

These three parts are organically intertwined and together form the European quality assurance framework. The external quality assurance described in Part takes into account the internal quality standards set out in Part to ensure that the quality as-surance activities of the higher education institution are direct-ly relevant to the quality assurance performed by external organ-izations. Similarly, part returns to Part .

The three parts therefore work in complementarity, in higher education institutions as well as quality assurance agencies, and also assume that other stakeholders can contribute to the frame-work. Consequently, the three parts should be read and applied as a single whole.

During the research our conclusions have been formulated only on the fi rst part of ESG : Standards and Guidelines for Institutional Internal Quality Assurance.

In the following sections, we list the factors that have emerged as areas, weaknesses to be developed during the accreditation process, both by the institutions and by the participants in the accreditation process.

ESG . and . Policy for quality assurance and Cyclical external quality assurance

• There is no uniform, mature defi nition of quality in higher education.


• Higher education institutions are mainly characterized by ISO -standard quality management systems, but there is still a lack of consistency between ISO and ESG (knowledge and training of the latter is still incomplete).

• The PDCA is known, but the application of the Check and Act phases is still incomplete.

• Process approach and systemic operation are incomplete.• Quality Assurance and Quality Management — „splendid

isolation”• Leadership commitment is not pronounced.• Quality Department• its location is “unworthy” and its reputation low• senior management support is low• cooperation with other departments would be desirable• One-person quality responsibility is dominant.• Quality Policy and Goals are not well communicated (inter-

nally and externally).• Lack of consistency among quality goals, strategic goals

and development plan.• Existing quality goals are not measurable.• Insulated faculty systems and operation although ESG

expect institutional quality assurance.• Refl ection on the development proposals of the previous

accreditation procedure is lacking.• Wordy quality documentation and policies.• Higher educational and ESG references of external accred-

itation specialists are incomplete.

ESG . and . Design and approval of programmes and On-going monitoring and periodic review of programmes

• The teacher-student ratio is uneven and the deviation is high (. to students / teacher).

• The framework for a healthy and sustainable training port-folio based on regular feedback from stakeholders is miss-ing.

• Responsibilities of program heads for quality management and development is not clearly defi ned.

• Missing harmony of portfolio and human resources.• Program accreditation and licensing are not always harmo-

nized.• To be developed:

— stakeholder relations for developing practical education (businesses, alumni, graduate career tracking system)

— publicity of educational content and subject require-ments (on-line accessibility)

— correct accountability system in line with the orienta-tion of the educational program

• The practice of using fl exible learning and assessment so-lutions is moderate.

• Moderate awareness of the principles, expectations and measurement of competence-based training.

ESG . Student-centred learning, teaching and assessment

• The means of student motivation is incomplete (mentor-ing).

• The eff ectiveness and representation of student evaluation of teaching is very low (on-line?), practically useless for de-velopment purposes.

• The feedback of student evaluation of teaching is incom-plete — resulting in low level of motivation.

• There is hardly any institutional-level knowledge platform, the institutional linking of talent management practices is missing.

• The development of service and infrastructure development based on student needs, should be improved.

• Under-regulated student complaint management (not on whole institution level), no “client satisfaction” measure-ment of it.

• Analysis and feedback of exam results are incomplete, the unifi ed metrics of the subject fulfi llment are unfi nished.

• Institutional regulatory background (and training) of pro-fessional credit allocation is incomplete.

• Exam equity (suffi cient and evenly distributed exam time, other instructor, written-oral exchange).


• Teachers’ pedagogical skills and language skills can be im-proved.

• Shortcomings of credit recognition (unregulated, untrained, inconsistent, uneven).

• Additions to institutional regulations are sometimes redun-dant, non-specifi c.

• The system of preferential study arrangements is not uni-form.

• Institutional sharing of best practices for dealing with drop-outs is incomplete.

ESG . Student admission, progression, recognition and certifi cation

• The reason for the high level of not issued diplomas due to the lack of language exam is unknown, therefore the suc-cess rate of actions taken to terminate them is accidental — missing system.

• Application management systems and methods and their payment obligations are outdated and not student-friendly. The intention to revise and develop them is minimal.

• Mobility windows are scarce, credit recognition processes are complicated.

• Missing mobility focused motivation system.• Accurate, up-to-date communication system or database re-

garding the relevant rules for foreign students is missing.• The number of foreign language courses is limited, and the

encouragement of local student involvement is lacking.

ESG . Teaching staff

• No traces of conscious HR focusing on providing suffi cient amount and academic level of teaching staff to insure im-proved proportion of professors and highly qualifi ed lead instructors.

• Missing conscious HR system for effi cient support of the tracking of stages of degree process.

• Missing HR support for planning, supporting and motivat-

ing sabbaticals and international exchange initiatives.• The requirements of recruitment and promotion of teach-

ing staff are neither public nor clearly and transparently regulated.

• There is no conscious, comprehensive education policy and system for teaching staff .

• The organization of specifi c career models (researcher, teacher, practical teacher) into workshops is not fi nalized.

• The faculty practices and systems of performance evalua-tion are diff erent and there is no unifi ed institutional framework.

• MTMT documentation of academic activity and citation of trainers is not up to date.

• Incentives to encourage and support academic staff partic-ipation at trainings and conferences are inadequate.

• Institutional employee satisfaction measurement and eval-uation systems are underdeveloped.

• Educational-methodological, pedagogical and research skills of educators need to be improved.

ESG . Learning resources and student support

• Not enough language and language exam preparation and catch-up courses.

• Library shortcomings: number of copies, fl exible opening ours.

• IT shortcomings: wifi , outdated hardware background, not enough free software.

• Students` dining options are not always provided.• Sometimes the student demand for more and more practi-

cal courses is not met.• Multi-campus institutions have unequal infrastructural ser-

vice levels.• The system of institutional rules for judging social scholar-

ships does not always ensure equal opportunities for stu-dents.

• There is no uniform perception of public activities.• Student demand for career services, mental health and psy-


chic counselling services is increasing, but diffi cult to serve.• Uneven quality of sports facilities.• Accessibility is lacking at many points.• Study administration processes can be made more up-to-

date, faster, and better (mostly IT-based).

ESG . Information management

• Uniform querying capabilities for information in diff erent databases are limited in some cases, their development is needed.

• The management information systems required for mana-gerial decisions are at diff erent levels of development and their development is desirable.

• Gaps in the integration of databases and access.• Institutions do a lot of measurements, but their use in de-

cision-making and closing of the PDCA cycle is in many cases not or not at the right levels.

• The dilemma of paper-based and electronic-based measure-ment effi ciency.

ESG . Public information

• It would be desirable to coordinate the content of the web-sites, and to strengthen the single image in case of multi-faculty institutions (Corporate Handbook).

• There is a clear need for modern, up-to-date, informative, easy-to-use, up-to-date websites.

• The need for maximum compliance with data protection re-quirements for public information (GDPR).

• Easy, quick access to up-to-date, public, multilingual infor-mation related to institutional operation is required.

• Training programs and subject requirements are not always publicly available throughout the whole institution.

• Expected to promote mutual accessibility of partners ‘and stakeholders’ websites (in particular: dual training).

• There are diff erences in publication of analysis of diff erent student surveys and evaluations (publicity, feedback!).

• Public information on learning and success rates and the location of graduates should be expanded.

C

In conclusion, the following development proposals were formu-lated and drawn up on the basis of the studies carried out for higher education institutions.

• In addition (instead of?) the very powerful, traditional fac-ulty approach, overall quality policy, quality strategy, qual-ity approach. Institutional leadership should strongly be committed to quality representation and communication.

• The principal focus of ESG is to ensure that accredit-ed institutions issue diplomas of accredited educational programs. Contradictory, if not accredited courses are held in the portfolio.

• Internalize the perception that the institution is responsi-ble for quality (the institution initiates, consciously devel-ops the PDCA cycle).

• The specifi c quality assurance system needs to be selected and developed according to the size and capabilities of the institution — by adapting the ESG principles.

• A uniform quality assurance system is needed at institu-tional level.

• High positioning of quality assurance within the institution (directly reporting to the rector) and corporate manage-ment.

• Continuous, institutionalized training of managers and quality professionals is required.

• Adopting external best-practices, recognizing and celebrat-ing internal best-practices.

• Exploiting the potential of digitalization, digital literacy, Big Data and IT.

Experience gained during these accreditation processes, the de-tected observations and weaknesses can serve as guidelines for those institutions, that are operating in the EHEA and are will-ing to comply with the accreditation requirements of ESG .

I. M, Q M C

R

. Standards and Guidelines for Quality Assurance in the Europe-an Higher Education Area (ESG). (). https://enqa.eu/wp-content/uploads///ESG_.pdf

. Self-assessment guide (). Hungarian Higher Education Ac-creditation Committee. Budapest. http://www.mab.hu/web/doc/akkreditacio/OnertUtmut_Intakkr.pdf

. http://www.mab.hu/web/index.php?option=com_content&view=article&id=&Itemid=&lang=hu

. http://www.mab.hu/web/index.php?option=com_content&view=article&id=&Itemid=&lang=hu

. CCIV. Act on National Higher Education https://net.jogtar.hu/jogszabaly?docid=A.TV

Managing Educational Projects:Cloud Solutions for Workfl ow Automation

O MAssociate ProfessorRussian Presidential Academy of National Economy and Public AdministrationFaculty of Economic and Social Sciences

A OAssociate ProfessorRussian Presidential Academy of National Economy and Public Administration Faculty of Economic and Social Sciences

A

The present paper describes a workfl ow automation framework designed for managing educational pro-jects at FESS, RANEPA. The framework consists of the following integral parts: artifacts, processes and documentation.

Keywords: PMBoK, project workfl ow automa-tion, educational projects, project team manage-ment, artifacts, processes, documentation.

I

Educational programs, both bachelor and master, usually encompass diff erent sort of projects, be it real-life or instructional ones. Such training models as individual or group design projects are conducive

I. M, Q M C M E P

to developing hard and soft skills and acquiring hands-on expe-rience in the fi eld of interest. They facilitate self-directed learn-ing, learning-by-doing and learning-by-interaction, promote knowledge spillovers and result in synergetic eff ects for all par-ties involved in the process. Implementing project approach to education helps build up links between academia and business, international relationships and knowledge transfer between countries. Such an approach to education can be used in diff er-ent fi elds, though it requires basic project management skills from both students and teaching staff . Organizing workfl ow in educational projects appears to be a labor-consuming matter. That is the reason why workfl ow automation becomes an issue of utmost importance nowadays.

According to PMBOK standard, a project is a temporary en-deavour undertaken to create a unique result []. Two main pro-ject properties stem from this defi nition:

• Temporary character: each project has a predefi ned begin-ning and ending linked to one of the following conditions:

— the aim of the project has been achieved; — there is no possibility that the aim be achieved; — there is no need to continue the project.

• Uniqueness: a project is aimed at an idiosyncratic objec-tive and its results diff er from the analogues. Sometimes to accomplish a singular goal one needs to bring together people who do not usually come across each other, who ac-complish diff erent functions and have diff erent competen-cies.

For the purpose of the present paper, we defi ne an educational project as one whose main objective is to prepare a piece of aca-demic writing (paper, article, report, executive summary etc.) usually subject to further defense in viva voce. Thus, such a pro-ject is always time-bound since its completion period is stipulat-ed by the curriculum, and has unique results. Here, uniqueness means that each work is to be done independently, has an objec-tive, is idiosyncratic and no plagiarism is allowed. A standardized structure of the work does not contradict uniqueness of the re-sult in this sense.

In terms of scope, educational projects may be narrow-focused, intended to master skills on a single subject (e. g. a teamwork on fi nancial analysis) or comprehensive, encompassing interdiscipli-nary studies (e. g. a group design graduation paper or a business plan containing market research, business-process engineering and fi nancial modelling). Since preparing a project is a way of self-directed learning, it helps students train practical application of theoretical concepts covered in the subject. Moreover, an impor-tant tutorial goal pursued by project approach to education is building up teamwork skills. Each member of a project team has his or her own roles and responsibilities and contribute to the fi -nal project result. Some project goals can be achieved indepen-dently; nevertheless, overall performance depends on collective work and interaction between team members. It is especially the case for comprehensive projects where team members accomplish diff erent functions and one member’s outputs become inputs for the others. Henceforth, an eff ective work breakdown and person-al contribution tracking are of utmost importance, as well as en-abling cooperation, coordination and communication.

P : FESS, RANEPA

The Faculty of Economic and Social Sciences (FESS) specializes in management education and possesses many years of experience and track record in implementing project approach to education. One of the main competitive advantages is working in small teams, which fosters group interaction, empowerment and taking respon-sibility. Currently the following projects are in execution.

The need for workfl ow automation is largely due to the in-creasing number of students and projects executed. Changing la-bour market requirements force the faculty to implement new types of projects (especially business-academia collaboration and international projects) and to broaden their scope. Therefore, a number of problems arise, for instance:

• Low transparency and bad traceability. Project execution was similar to a black box: a supervisor and administration

I. M, Q M C M E P

could only see working progress at milestones, therefore, quality enhancement was limited and/or deadlines missed.

• Free-rider problem. Personal contribution was hardly track-able in teamwork projects

• Loss of time on register creation/errors in the register. A lot of administrative staff working time was lost on creat-ing project registers for graduation papers. Sometimes reg-isters contained outdated information.

• Teaching staff overload. In absence of systemic approach to project management academic load was distributed une-venly during the year and between teachers. The former re-lates to low deadline controllability and lack of possibility

to impose personal deadlines to make load more balanced. The latter occurred because no limit on number of works under supervision was established.

Thus, the main workfl ow automation objectives can be stated as follows:

. Enhancing intragroup communications. Making work progress trackable. Fighting free-rider issue. Improving effi ciency of control procedures. Enabling collective mentorship and supervision. Optimizing teaching staff working time

In order to achieve goals stated above we developed a frame-work based on cloud business solution. The proposed workfl ow automation framework consists of three building blocks — Arti-facts, Processes and Documents, containing the following items:T . Framework structure

Artifacts Processes DocumentsDatabase Forms• Registration form• Reporting formFolder• Team member

folder• Group folder

• Initiating• Planning• Executing• Controlling

• interim• fi nal

• Closing

Team Reports:• Initiation report (establishing scope,

schedule and responsibilities)• Gantt chart• Interim planning report• Change management report• Interim results consolidationProject materials• Intermediate• FinalPersonal contribution memorandum

Artifacts are elements of the framework created by the ad-ministrator and have public or limited access. The main artifacts are presented below:

Database

A Database contains information on the students and is created by means of fi lling in registration forms. For purposes of the pre-sent work we used cloud tools, namely Google Spreadsheets with forms attached, to create a database. A database architecture fol-

T . Educational projects executed at the Faculty

Y Subject Type Focus Supervisorst year B

Entrepreneurship and business planning

Individual narrow course instructor

Entrepreneurship and business planning

Teamwork comprehensive course instructor

nd year B

Corporate planning Teamwork narrow course instructorStatistics and Econometrics

Teamwork narrow course instructor

End-of-the-year paper Individual narrow (subject to choose)

supervisor to choose

rd year B

Financial analysis Teamwork narrow course instructorProject management and investment project valuation

Teamwork comprehensive course instructor

Collaboration projects Teamwork narrow/ comprehensive

collective supervi-sion (instructor and business mentor)

th year B



Graduation project individual/ teamwork

narrow/ comprehensive

supervisor to choose

st — nd year M



Master thesis * Individual narrow supervisor to chooseMaster project Teamwork comprehensive supervisor to choose

(collective supervi-sion possible)

*The choice between individual master thesis and teamwork master project is up to the student

I. M, Q M C M E P

lows main relational database principles and consists of the fol-lowing tables and fi elds:

. Students:• Name• Email• Personal folder link. Project teams (created from Team registration form):• Team ID• Project manager (linked to Students table)• Team members (linked to Students table)• Team folder link• Percentage completion (by sections — to be fi lled by project

supervisor).. Reports (created from Reporting form)• Timestamp• Team (linked to Teams table)• Report type• Report number• Attendees• Agenda• Resolution• Links to appendices

Database access is provided to teaching staff involved in project execution and administrative staff if needed. For convenience sake we also created two reports — Gantt chart and Project team log, whose interface is presented in Table .

Forms

The framework comprises two form types: Team Registration form and и Reporting form. Data from forms is registered in re-spective tables of the Database.

Team registration form is active until the deadline for the in-itiation stage. After all groups are put together, the form is disa-bled and no further changes are allowed. The registration form is fi lled in once at a time of a single project and has the following structure:

• Project supervisor (if applied — dropdown)• Project manager (dropdown)• Team members (dropdown)• Project name (combobox/text)• Team members emails.

Dropdown questions are automatically pulled from the data-base.

Reporting form is enabled during all project execution period for approved project teams, is to be fi lled in regularly and has the following structure:

• Team ID (dropdown)• Report type (combobox)• Report number (number)• Attendees (dropdown or text)• Agenda (text)• Resolution (text)• Appendix (link or upload)

T . Project team log

Project Team ID Team Folder https://drive.google.com/drive/u//folders/Project NameProject Supervisor Anna OlkovaProject Manager Ivan Ivanov https://drive.google.

com/drive/folders/[email protected]

Team Members Petr Petrov https://drive.google.com/drive/folders/

[email protected]

Sidor Sidorov https://drive.google.com/drive/folders/

[email protected]

Reports.. :: https://drive.

google.com/open?id=

Initiation report

.. :: https://drive.google.com/open?id=

Interim planning report

.. :: https://drive.google.com/open?id=

Change management report

I. M, Q M C M E P

Folders

Folders are created for each team and student and are structured in a hierarchy : a team folder contains team member folders. Folders serve for collective work on the project, tracking and su-pervising working progress and responsibilities. All project team members have access to view a team folder and all its content (in-cluding personal member folders). Project manager has also rights to modify content (without changing permissions). Project supervisor also possesses editing rights. No students not making part of a project team are allowed to view folder content.

Processes are defi ned in compliance with PMBoK th edition requirements. Detailed process descriptions are provided below.

Initiating

The fi rst project management stage requires that course instruc-tor or administrative staff provide to students the following doc-uments:

• A list of project scope statements,• Aggregated Gantt chart,• Registration form.

Scope Statement

Teaching staff is able either to provide a single case with multi-ple ways of solving or multiple cases to choose or to empower students to fi nd a case of interest on their own.

Gantt Chart

It is essential to establish deadlines for blocks of processes, track work in progress and assure in-time project completion. Gantt chart visual representation is provided on fi gure .

The given above Gantt chart does not set out any work break-down structure. In general, a one-for-all schedule stipulates deadlines only for aggregated groups of activities. Further work

Assigning multiple root folders for a student folder is also possible. F

. G

antt

Cha

rt

I. M, Q M C M E P

breakdown as well as preparing a detailed Gantt chart are left up to team members. Moreover, a detailed project management plan is to be developed by a member responsible for the work area.

Registration form

It is an artefact that serves the data collection purpose on pro-ject initiation stage.

Planning

After project teams have been created and project scope state-ment approved by the teaching staff , each team is supposed to prepare a work breakdown structure, defi ne work sequence and schedule, as well as to assign roles and responsibilities. An out-put of this stage is Initiation report defi ning scope, WBS, sched-ule and responsibilities with an appendix containing detailed Gantt chart. Such a report is compiled automatically from the Re-porting form. While planning, MBO approach is applicable — a team is required to decompose objectives (possibly in a form of an objective tree) and design processes to achieve goals defi ned. ALAP principle is viable as well — project ending date is usually fi xed and schedule is set up on backward pass.

The team member responsible for an area of work of the ag-gregated Gantt chart is required to provide a detailed WBS and schedule of the area the day the activity begins. Such a plan is called an Interim plan and is to be uploaded as a report in the re-spective form.

Executing

Project manager functions comprise the following tasks (besides executing a number of activities stipulated by project scope): co-ordinating teamwork processes, tracking deadline fulfi llment, setting team members’ goals and objectives, organizing team meetings and discussing intermediate results. Project team assis-tant, when applicable, is responsible of uploading and keeping project materials, managing project folders, creating reports and meeting minutes, compiling and formatting fi nal documentation.

During project execution stage it is appropriate to have regu-lar project team meetings (optimal meeting frequency is consid-ered to be weekly or fortnightly). Each meeting is to be reported on, keeping record of achieved results, deviations from scope/schedule, tracking possible issues. Interim results should be up-loaded with similar frequency to personal or team folders.

Reports should also keep track of missed deadlines and deci-sions made to handle project issues, including but not limited to organizational measures such as cancelling team membership or introducing new members, reassigning roles and responsibilities. Any changes are subject to documenting as change management reports. If deadlines are missed, a report should contain informa-tion about the missed deadline and the new one. Project team manager is allowed to expel students who are unable to fulfi l their functions from the team. In this case project supervisor should be informed at short notice.

Monitoring and controlling

Project manager, project supervisor and administrative staff are charged with control functions. The framework envisages both intermediate functional and fi nal control. Monitoring shall be ex-ecuted on a regular basis with frequency corresponding to that of project team meetings. It encompasses tracking current state of the work in progress, keeping record of percentage of completion and making critical remarks in form of online comments. All is-sues identifi ed by project supervisor are subject to revision. Final control measures include a dry run procedure held approximate-ly weeks before project presentation. During dry run presenta-tion teaching staff and team members discuss in praesentia re-sults obtained by the group. Students get recommendations re-garding project content, formatting and presentation.

For tracking purposes, a Database contains Percentage of Completion section located in Teams table. When working time is due for an aggregated group of processes, project supervisor can mark activity as done, subject to revision or missing and add a comment on result quality. If a team fails to deliver work on time, it is possible to organize automatic direct mailing to teams

I. M, Q M C M E P

failing to comply with deadlines. Data provided by project super-visors help calculate overall percentage of completion and visu-alize by means of the Gantt chart.

Closing

Project closing stage requires compiling project results into a fi -nal document and presenting them in a form of defence in viva voce. Each project has to contain personal contribution memo-randum stating ex-post roles and responsibilities for each team member. A mark comprises the following criteria: project con-tent, presentation/defence, compliance with deadlines and pro-cedures. If a project has been dismissed during dry run proce-dures because of its low quality, a presentation of such project is delayed and project teams get a “fail” grade.

Documents. Project documentation is to be prepared by pro-ject team and should comprise the following records:

Team meeting minutes

Team meeting minutes has usually the following layout:

• Title (to contain number and timestamp)• Attendees• Agenda• Resolved (action plan statement and decisions made). Dur-

ing meetings team members make decisions defi ning and modifying scope, WBS, schedule and responsibilities, as well as confi rming intermediate results.

• Appendices (e. g. Gantt chart). Appendices are to be up-loaded in the respective form.

A minutes is never subject to changes. Any changes can be made only by introducing a change management report. The pre-sent framework stipulates the following minutes/report types:

• Initiation report — fi rst team meeting minutes containing work breakdown structure, schedule, roles and responsibil-ities. A Gantt chart is also to be attached.

• Interim planning report, made and uploaded by a team member responsible for the area of work.

• Change management report, uploaded if changes in WBS, schedule, roles and responsibilities are to be made. Such a report should contain both old and new information on the changing matter.

• Intermediate result confi rmation, containing description and links to all project materials.

Project materials

Unlike team minutes, project materials are working documents and subject to editing if necessary. Project materials are to be up-loaded in personal folders by members responsible for the area of work. Consolidating project materials is a project manager or assistant task.

Personal contribution memorandum (to be prepared shortly before project presentation) Contribution memo refl ects actual ex post roles and responsibilities and each member contribution to the fi nal result.

C

The described above framework represents project approach to student work administration. Preparing instructional projects diff ers from real-life project management, though, the main are-as of knowledge remain the same with minor amendments made to processes. Project management areas of knowledge have the following properties:

• Integration: requires integrating a project into the whole educational environment. For the time being the framework is applied to single project types (namely, graduation pro-jects, master projects and term papers), though further de-velopment is aimed at making a comprehensive tool for managing all educational projects in the faculty and build-ing up systematic approach. The main integration result for the moment is a more evenly spread academic load.

• Scope: basically represents work breakdown structure, or activities to complete in order to accomplish project goal. Scope area has no specifi c properties for educational pro-

I. M, Q M C M E P

jects compared to real-life ones. It is tracked through use of team folders.

• Schedule — represents deadlines for each activity, tracked by project supervisor in an effi cient and transparent man-ner. Tracking schedule fulfi lment was one of the main aims for workfl ow automation. Due to framework implementa-tion, the on-time fi nished rate has increased substantially. A project supervisor acts therefore like a project portfolio manager.

• Quality — stands for fulfi lling stakeholders’ expectations. An educational project is usually subject to a set of require-ments, in terms of both content and layout. Workfl ow auto-mation helps make control consistent, enables intermedi-ate inspection, enhancing overall project quality.

• Resources — represent project team creation and manage-ment. Team creation for instructional projects is left up to students. Though, students become aware of the free-rider issue and get to understand a complicated character of a project. That encourages building up relationships with people having diff erent professional skills as well as a dif-ferent mindset.

• Communication — comprises data collection, creation, dis-tribution and storage. Documenting workfl ow is an essen-tial issue for a real-life project. First implementation expe-rience shows that in general students lack discipline in re-porting working progress. That is the reason why workfl ow automation could be conducive.

• Stakeholders — relationships with all counterparties infl u-encing or infl uenced by a project. Implementing project ap-proach to education helps build up links between academ-ia and business, international relationships and is benefi -cial in terms of bringing qualifi ed workforce to the labour market. Students get hands-on experience on preparing a project, learn by doing and by interaction and become more competitive in the labour market.

R

. PMBОK Guide. th ed. Newton Square, Pennsylvania, USA: Pro-ject Management Institute,

Scientifi c LiteratureOrdered issue

nd International Management, Quality and Marketing Conference

–th April

Научное изданиеЗаказное издание

Выпускающий редактор Е. В. ПоповаХудожник ///////

Оригинал-макет О. З. ЭлоевВерстка Е. В. Немешаевой

Подписано в печать //.//.. Формат х/.Гарнитура «ПТ Сериф Про». Усл. печ. л. ,

Тираж /// экз. Заказ № ////

Издательский дом «Дело» РАНХиГС, Москва, пр-т Вернадского,

Коммерческий центр: тел. () ––, () ––www.ranepa.ru

[email protected]Интернет-магазинwww.delo.ranepa.ru

Отпечатано в типографии РАНХиГС, Москва, пр-т Вернадского, д.

fesn.ranepa.ru · C M H C Online reviews: are they useful for consumers? David D`Acunto . . . . . ....

Documents

Transcript of fesn.ranepa.ru · C M H C Online reviews: are they useful for consumers? David D`Acunto . . . . . ....