Zisos I., Grigoroudis E., Matsatsinis N., Spiridakos A.

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Technical University of Crete

14th Special Conference of the Hellenic Operational Research Society- 11th Meeting of MulticriteriaDecision AnalysisAgrinio, March 2015«Agricultural Development and Rural Economy using Multicriteria Decision Analysis»

Objective and Importance of the

specific Research

The Objective of the presented research work was to explorethe determinants of tourists’ satisfaction in the different hotel categories, using real online reviews written by hotel guests, and offer prioritized suggestions for hotels’ improvements.

The Added Value of the specific, is the use of Online opinions, provided by guests voluntarily in a multitude of tourism-oriented social media platforms, as input datasets in the MUSA model.

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Influence of Tourism-Oriented Social

MediaWeb has fundamentally reshaped the way tourist information is diffusedand the way people consume and plan trips (Buhalis and Law, 2008)

The hotel industry is well aware that customer ratings have a strong effecton customers’ willingness to book a hotel. When a hotel has negativecomments, respondents gave a probability of about 2 out of 5 that they’dbook that hotel. When they see a positive review, there is a likelihood of 3.5to 4 out of 5 that they’d book that hotel. (Verma et al., 2012)

Internet consumer opinion portals enable travelers to review anyaspect of a probable vacation including accommodation, restaurants,destinations, and other tourism related products (Burton and Khammash,2010)

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Influence of Tourism-Oriented Social

Media (2)>75% of travelers use social networks to find some type of shopping-related deal

&30% of them specifically seek out travel-related deals.

Of those who used social media to research travel plans48% stuck with their original travel plans33% changed their hotel10% switched resorts10% changed agent/operator/website7% holidayed in a different country5% switched airlines

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http://www.tourismlink.eu/http://www.stikkymedia.com

Consumer Trust

92% of consumers around the world say they trust earned media, such as word-of-mouth and recommendations from friends and family, above all other forms of advertising

70% of global consumers say online consumer reviews are the second most trusted form of advertising

Only

47% of consumers around the world say they trust paid television, magazine and newspaper ads

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http://www.stikkymedia.com

Scope

Analysis of guests’ behaviour and satisfaction levels through real guests’ web hotel ratings.

Employment of Multicriteria Satisfaction Analysis in real online rating data

resulting in recommendations to decision makers from the tourism sector that will improve guests’ satisfaction levels

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DatasetDataset obtained through crawling and mining methods from the www.hotels.com concerning Chania.

Data crawling tools: import.io , dataminer

Hotels.com -> booking web platform >240.000 hotels in ~=19.000 locations.

Platform Selection Criteria1.Validity, Volume and Quality of Data

2.Compatibility with crawling tools 3. Compatibility of rating Criteria with MUSA principles.

http://import.io/

https://chrome.google.com/webstore/detail/dataminer/nndknepjnldbdbepjfgmncbggmopgden

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Hotels.com Guests Reviews Online Platform

Imp0rt.io

Dataminer

Crawled Data in Excel Format

Methodology

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Method- MUSAThe MUSA (Siskos et al., 1998 , Grigoroudis et al., 2000) method infers an additive collective value function and a set of partial satisfaction functions .

The main objective of the method is to achieve the maximum consistency between the value function and the customers’ judgements .

Combining weights and average satisfaction indices, a series of action diagrams can be developed. These diagrams indicate the strongand the weak points of customer satisfaction, and define the required improvement efforts.

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DatasetCrawling process: in February of 2014 for hotels in Chania.

Fields extracted : Reviewer nickname, Reviewer nationality, Hotel Name, Hotel Star category, Review, and reviewer scores on the criteria: Overall Reviewer Score, Cleanliness, Service, Comfort, Condition, and Neighbourhood.

Initial dataset: 268 hotels -166 of them were rated

Number of reviews: 2029.

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Hotel

Category

Number of

Hotels

Number of

Reviews

1 Stars 13 96

2 Stars 50 465

3 Stars 65 884

4 Stars 19 270

5 Stars 19 314

Dataset processing

A. % of reviews with missing data in the “Neighbourhood” criterion was about 25%. For the satisfaction of MUSA’sfundamental property of Non-Redundancy for the existing criteria we had 2 options:1. dismiss reviews with missing data 2. fill the missing values with some type of relevant data. The objective of imputation is not to get the best possible predictions for the missing values, but to replace them by plausible values in order to exploit the information in the recorded variables in the incomplete cases for inference about population parameters (Little and Rubin, 2002)

We consider here Hot deck which is used for handling missing data in which each missing value is replaced with an observed response from a “similar” unit.

B. Dataset was split according to the hotel star rating category so that data were comparable in a standardized way.

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Satisfaction Criteria

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Criteria used : Cleanliness, Service, Comfort, Condition, and Neighborhood, Cleanliness refers to hotel’s Sanitation Standards, Housekeeping Facilities and Staff quality. Service includes providing the guest with information, special equipment and supplies.Comfort describes the hotel or room amenities and it’s quite relevant to luxury offered. Condition refers to the quality of infrastructure, meaning its level of oldness and maintenance. Neighborhood shows the quality of location where the Hotel is situated.

All criteria values range from 1 to 5 (1=worst , 5=best)

Customers’ Satisfaction AnalysisGuests of 1 and 2 Stars Hotels are very satisfied with Cleanliness and Serviceand simply satisfied with the rest of criteria.

Guests of 3 Stars Hotels are very satisfied with all criteria except for Neighbourhood that is just satisfactory to them.

Guests of 4 Stars Hotels are very satisfied with Cleanliness, Condition and Neighbourhood. Service and comfort are just satisfactory to them.

5 Stars hotels’ guests are very satisfied with Cleanliness, Service and Condition, just satisfied with

Comfort and less satisfied with the Neighbourhood criterion.

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0

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1-2 Stars 3 Stars 4 Stars 5 Stars

Global 95,421 93,858 91,895 94,773

Cleanliness 92,941 90,361 90,983 93,728

Service 97,108 92,090 90,945 96,488

Comfort 85,353 94,807 83,634 83,390

Condition 85,075 92,719 92,158 87,062

Neighbourhood 86,201 83,538 92,802 76,467

Satisfaction Indices

Weights AnalysisCustomers of 1 and 2 Stars consider Service as the most important factor of satisfaction. The rest of criteria play a minimal role their satisfaction.

Customers of 3 Stars Hotels consider Comfort as the key satisfaction factor and Condition of as the second most important. The other rating criteria seem to play a minimal role to their satisfaction.

4 Stars Hotels’ customers consider Neighborhood as the most important criterion followed by Cleanliness and Condition. Service and Comfort seem to be less important for them.

5 Stars Hotels’ customers evaluate Serviceas the most important criterion, followed by Cleanliness.

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1-2Stars

3Stars

4Stars

5Stars

Cleanliness 10,610 9,322 19,636 20,000

Service 63,237 11,097 6,980 56,010

Comfort 11,410 59,490 8,470 6,523

Condition 8,407 14,645 19,072 11,890

Neighbourhood 6,337 5,446 45,842 5,578

Weights for all Hotel Categories

1-2 Stars Hotels Actions-Improvements# Reviews:561.

Service constitutes the comparative advantage of these two categories of hotels in Chania. Comfort, Condition and Neighborhood do not seem to be considered as important criteria by hotel guests and they appear at the Status Quo region of the action diagram.

Service constitutes the 1st and Comfort the 2nd priority for improvement followed by Condition and Neighborhood. Finally, Cleanliness constitutes the last priority and resources used for it should be transferred elsewhere.

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3 Stars Hotels Actions-Improvements#Reviews :884 .

Comfort is the criterion that constitutes the comparative advantage of these hotels combining high performance with high importance for customers.

Comfort is the 1st

improvement Priority, while

Neighbourhood appears in the status quo region, being less important for hotel guests and constituties the second priority for improvement.

Service, Condition and Cleanliness are also criteria of relatively low importance.

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4 Stars Hotels Actions-Improvements#Reviews:270.

Neighbourhood is the criterion that constitutes the comparative advantage combining high performance with high importance, constituting the first priority for improvement.

Comfort and Service appear in the status quo region, being less important for hotel guests. Condition and Cleanliness,despite presenting high performance, according to hotel guests they are of low importance and their Resources could be transferred elsewhere.

Cleanliness is the second priority for improvements followed byService and Comfort. Condition is the last priority.

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5 Stars Hotels Actions-Improvements#Reviews: 314 guest reviews. Service is the criterion that constitutes the comparative advantage and it constitutes the hoteliers first priority for improvement.

Comfort and Neighborhood do not seem to be considered as important criteria by hotel guests.

Neighbourhood constitutes the second priority for improvement followed by Comfort. Cleanliness and Condition appear at the Transfer Resources region achieving high performance but being of low importance.

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Priorities for Improvement

Criteria/Hotel

Categories 1-2 Stars 3 Stars 4 Stars 5 Stars

Cleanliness

4rth

priority 3rd priority 2nd priority 4rth priority

Service

1st

priority 3rd priority 3rd priority 1st priority

Comfort

2nd

priority 1st priority 3rdpriority 3rd priority

Condition

3rd

priority 3rd priority 4rth priority 4rth priority

Neighbourhood

3rd

priority

2nd

priority 1st priority 2nd priority

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Summarized ResultsEvery Star hotel category in Chania, has different parameters that play the most crucial role to guests’ satisfaction. For 1 , 2 and 5 Star Hotels Service appears to be the catalyst to guests’ satisfactionFor 3 Star hotels Comfort is the most important criterionFor 4 Star hotels guests consider Neighbourhood as the most important criterion. Cleanliness seems to be important for guests of 4 and 5 Stars Hotels. Condition doesn’t seem to be very important for any hotel Star category.First priority for 1,2,5 Stars hotels is Service. Last priority for almost all of the hotel categories is the Conditioncriterion. Neighbourhood is among the first priorities for improvement for 3,4 and 5 stars hotels.Cleanliness appears as one of the first priorities only for 4 star hotels.

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RemarksThe aforementioned results are realistic and close to the real hotels characteristics.

Hotel guests mostly care about the Service delivered to them

Neighborhood being less satisfactory for guests is explained by the fact that most hotels in Chania, are situated far away from the center of the city and the old harbor which constitute the attractions for visitors.

Condition of hotels being the last priority for all the categories is logical bearing in mind that most of them have been built in the last decade and they are in great condition.

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ConclusionMUSA worked efficiently with this type of data and produced satisfactory resultsFuture research concentrates on the integration of textand emotional analysis of guests’ reviews to the already existing data, which will lead to more personalized results both for hotels facilities and for guests’ preferences. Research will extend its geographical borders in order to study other destinations characteristics through guests’ reviews and ratings and compare different regions’ results. More booking WebPages can be processed not only from the hotel sector but from other touristic sectors, too.The encapsulation of more variables will highlight many interesting aspects of guests’ preferences and destination characteristics

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Thank YOU

Ioannis Zisos, PhD Candidate, Technical University of Crete izisos@isc.tuc.gr . School of Production Engineering and Management, Technical University of Crete, 73100 Chania,GreeceDr. Evangelos Grigoroudis, Associate Professor , Technical University of Crete, vangelis@ergasya.tuc.gr, School of Production Engineering and Management , Technical University of Crete,73100 Chania , GreeceDr. Nikolaos Matsatsinis , Professor,Technical University of Crete, nikos@ergasya.tuc.gr, School of Production Engineering and Management, Technical University of Crete,73100,Chania, GreeceDr. Athanasios Spyridakos, Professor, Piraeus University of Applied Sciences, tspyr@teipir.gr, School of Business and Economics, Piraeus University of Applied Sciences, 12244, Egaleo, Greece

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