An exploratory study ofmarketing, physical and peoplerelated performance criteria in

hotelsRamakrishnan Ramanathan

Nottingham University Business School, Nottingham, UK

Abstract

Purpose – Using data from online guest ratings, the purpose of this paper is to explore how theperformance of hotels in terms of various criteria influences loyalty behavior of customers.

Design/methodology/approach – Ratings of 333 hotels in the UK were collected from the web sitewww.laterooms.com and statistical analysis performed.

Findings – The criterion related to marketing management (Value for money) was found to be themost important criterion influencing loyalty behavior of customers in UK hotels. Further, it was foundthat good performance of hotels in terms of physical-product management can significantly influencethe intentions of business guests to stay again, whereas leisure guests expect good performance bothin terms of physical-product management and people and process management. While guests ofindependent hotels value performance in terms of people and process management, guests of chainhotels value both physical-product management and people and process management. Finally, it wasfound that the significance of criteria related to physical-product management and people and processmanagement generally varies across star ratings.

Practical implications – Expectations of guests have been found to be quite different acrossvarious categories – star classifications, chain and independent hotels, and leisure and businessguests. This implies that a general solution may not satisfy guests belonging to all these categories.For example, business and leisure guests perceive facilities differently and hence hotel managers needto provide different kinds of services to satisfy them. Similarly, the finding that business guests attachhigher importance to criteria related to physical-property management, in deciding their intention tostay again in the UK hotels, compared to people and process management, has interesting practicalimplications. This indicates that good performance of hotels in maintaining room quality andcleanliness can significantly influence the intentions of business guests to stay again.

Originality/value – This is one of the first studies to statistically analyze online guest ratings. Itextends the applicability of the frameworks developed in the earlier literature by employing them withthe new data source (online ratings).

Keywords United Kingdom, Hotels, Customer loyalty, Web sites, Multivariate statistics, Marketing,Online guest ratings, Performance criteria

Paper type Research paper

IntroductionThe hotel sector in the UK has generally registered growth in the past few years. Asper the web site of VisitBritain (www.tourismtrade.org.uk accessed on March 2, 2011),the average occupancy level for all serviced accommodation throughout the UK was 59percent in August 2010 which was higher by 1 percentage point compared to the figurefor August 2009. This growth is set for a further boost due to the 2012 Olympics inLondon, though there seems to be a slow-down in the short run. For example, the

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Received October 2010Revised January 2011March 2011Accepted March 2011

International Journal ofContemporary HospitalityManagementVol. 24 No. 1, 2012pp. 44-61q Emerald Group Publishing Limited0959-6119DOI 10.1108/09596111211197791

United Kingdom Tourism Survey (Visit Britain, 2010) has estimated that there were 97million trips in England in the year ending September 2010, which was about 3.9percent less than the numbers recorded for the year ending September 2009 (http://www.visitengland.org, accessed on March 2, 2011). The hotel sector, as well as theentire hospitality and the tourism industry, are highly responsive to the upward anddownward changes in the economy (BOD Consulting, 1996). Hence, hotels need to bevery competitive for survival and retain customer loyalty.

Ability of an organization to attract and retain customers is vital to its success.Customer loyalty requires that there is a strong desire by the customer for a product, andthat there are several product vendors to choose the product based on his/her preferences(Dick and Basu, 1994; Otim and Grover, 2006). These two factors are very muchapplicable in the hotel sector as more and more people visit different places and needplaces to stay (Nunes and Spelman, 2008), and huge number of hotels are available.Customer loyalty in hotels is often shaped by experience by the guest before, during andafter his/her stay in a hotel. A number of factors contribute to the experience – customerservice, cleanliness, facilities, price, food, location, etc. The relationship betweenperformance of hotels in terms of these factors and customer loyalty has been a topic ofseveral research studies (e.g. Boulding et al., 1993; Callan, 1998; Chao, 2008; de Ruyteret al., 1998; Dube and Renaghan, 1999a, b; Lee and Jang, 2010).

Most of these studies have used data collected from primary surveys for theiranalysis. With the rapid growth of hotel reservations over the internet, a new andexciting set of data is available from online guest ratings of hotel guests. In this paper,we have used these online guest ratings of the UK hotels to empirically explore therelationships between hotel performance criteria and loyalty behavior of customers(interpreted in this paper as the intentions of guests to stay again). We then analyze theinfluence of star ratings, leisure and business guests, and chain and independent hotelson these relationships. Although our study uses online guest ratings in the hotelliterature and is one of the first studies to do so, the use of online ratings is not new andhas been heavily used in understanding the drivers in the e-commerce environment(e.g. Heim and Field, 2007; Heim and Sinha, 2001; Jiang and Rosenbloom, 2005).

Literature reviewService quality and performance criteria in the hotel industryGuests use a variety of performance criteria to judge the quality of service they receiveduring their stay in a hotel. Some of the criteria are related to intangible serviceelements and some are related to tangible physical elements. Many research studiesevaluating service quality in hotels have considered these criteria in different forms.The popular SERVQUAL instrument (Parasuraman et al., 1988) is based on fiveprominent dimensions of service quality (reliability, assurance, tangibles, empathy andresponsiveness), and the instrument has been applied to hotels. Fernandez and Bedia(2004) have used SERVQUAL instrument to measure service quality of hotels in Spainand found that, in general, hotel star ratings system does not correspond to levels ofservice quality. Akbaba (2006) has used five dimensions that are broadly based ontraditional SERVQUAL principles but are slightly different: tangibles, adequacy ofservice supply, understanding and caring, assurance, and convenience. His study hasfound that the most important dimension for business tourists was “tangibles” andthat leisure tourists had the highest expectations for “convenience”.

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Su and Sun (2007) have used content analysis and SERVQUAL dimensions foranalyzing Taiwan’s criteria of hotel service quality. Using data obtained from a primaryquestionnaire survey, Briggs et al. (2007) have shown that service quality determinantsvary according to size of the hotel. They have also found that customer service ratings interms of several operational criteria (friendliness, standards, personal service, andtangibles) differed significantly across hotels of various sizes (small, medium, large)except for the criterion “value for money”. Hsieh et al. (2008) have used the SERVQUALinstrument to measure service quality of Hot Spring hotels in Taiwan and then derivedweights for service quality dimensions. Extending the SERVQUAL instrument for arural context, Albacete-Saez et al. (2007) have developed measures and scales to assessquality of service in rurally located tourism lodgings. Using multivariate statistics(confirmatory factor analysis), they have found five dimensions as useful: personnelresponse, complementary offer, tourist relations, tangible elements and empathy.

Studies linking service quality and customer loyaltyA number of studies have explored the link between perceived service quality andcustomer loyalty (e.g. Cronin et al., 2000; Dube and Renaghan, 1999a, b; Gonzalez et al.,2007; Ha and Jang, 2010; Hutchinson et al., 2009; Um et al., 2006). In their two-part study,Dube and Renaghan (1999a, b) have examined guests’ perceptions of building customerloyalty and the contribution of various hotel criteria in delivering promised benefits. Theyhave conducted a primary survey of frequent business and leisure tourists in the USA tounderstand the relative contribution of 115 functional practices to customer loyalty. Theyhave divided the practices into three broad functional areas – physical-propertymanagement, people and process management, and marketing management.

Gonzalez et al. (2007) have used factor analysis and regression on the data from aprimary survey and have found evidence for a positive relationship between perceivedservice quality and satisfaction. They also found that customer satisfaction andperceived service quality positively influenced behavioral intentions. Wilkins et al.(2007)have used survey of 63 items relating to hotel performance to understand thedeterminants of service quality in the first class and luxury hotel segments inQueensland, Australia. Using exploratory principal component factor analysis, theyhave found that the 63 items reduced to seven components. They have further found thatthe seven components could be grouped into three dimensions – service experience,physical product, and, quality of food and beverages using confirmatory factor analysis.

Some studies have attempted to identify the relative importance of variousperformance criteria of service quality in influencing customer satisfaction (Callan andBowman, 2000; Knutson, 1988; Lockyer, 2002; McCleary et al., 1993). Cleanliness isgenerally reported as the most important criterion (Weaver and McCleary, 1991).Quality of rooms with comfortable beds and good towels have also been found to beimportant (Knutson, 1988; Weaver and McCleary, 1991; Weaver and Oh, 1993). Othercriteria such as customer service (Knutson, 1988; Lockyer, 2002; Weaver and McCleary,1991; Weaver and Oh, 1993), and, safety and security (Knutson, 1988; Lockyer, 2002;Weaver and McCleary, 1991) have also been found important.

Influence of star ratingThe function offered by hotels is essentially a service function, which is only“experienced” by customers during their stay and makes the assessment of quality

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difficult (Heineke and Davis, 2007). In order to guide potential guests on the nature offacilities and service that can be expected in hotels, a star rating of hotels is generallyused. This rating usually varies between two and five. In general, the higher the starrating, the higher is the expected level of service and facilities in a hotel.

Several research studies have attempted to test the correctness of star ratings bycomparing the ratings with the facilities available in hotels and the service experiencedby hotel guests. There have been conflicting findings. For example, using dataobtained from a primary questionnaire survey and customer reviews fromTripadvisor.com, Briggs et al. (2007) have argued that star grading schemes andassociated standards are largely driven by physical facilities of the hotels, and thatthese schemes do not adequately take into account customer service orientation ofhotels. As per Orfila-Sintes and Mattsson (2009), different levels of hotel quality do notreally have an impact on the hotel operations as such, and the difference between highand low quality accommodation is in the quality of the extra services and tangibles.Fernandez and Bedia (2004) have also found that, in general, hotel star rating systemsdo not correspond to levels of service quality. Hashim et al. (2010) have recently foundthat star rating of hotels was significantly related to the levels of internet adoption inMalaysia.

Customer service offered by different star rated hotels in terms of their responseto e-mail enquiries and adoption of information technology has been studied in theliterature (e.g. Matzler et al., 2005; Siguaw et al., 2000; Wei et al., 2001). All thesestudies have found that the extent of information technology and email usage andthe corresponding customer service level were higher as star ratings of hotelsincreased.

Influence of hotel management characteristics (independent hotels vs chain hotels)Hotels that are part of a chain have some advantages and disadvantages over hotelsthat operate independently. Chain hotels generally have access to valuable operatingknowledge shared by other hotels in the chain (Ingram and Baum, 1997). They can alsoenjoy economies of scale (Chandler, 1977; Ingram, 1996). However, chain hotels areconstrained strategically as they cannot make decisions on their own and areconstrained by the strategic directions of the parent company. Much research has beencarried out to compare performances of hotels that are part of a chain and independenthotels. The benefits of being in a chain have been highlighted by Ingram and Baum(1997). They have studied the modes of chain affiliations of hotels and their failurerates focusing on Manhattan hotels for the period 1898-1980, and have found thathotels that are part of a chain generally recorded higher survival rates.

In terms of the difference between the performance of independent hotels and hotelsthat belong to a chain, Briggs et al. (2007) have cited the works of Ingram (1996) andhave argued that independent hotels normally take a transactional approach to theircustomer service while hotels that are part of a chain will take a more transformationalapproach. However, using data obtained from a primary questionnaire survey, theyhave found that customer service ratings in terms of several performance criteria(friendliness, standards, personal service, and tangibles) did not differ significantlybetween independent hotels and hotels that are part of a chain. Hashim et al. (2010)have found that hotel affiliation (chain or no-chain) was significantly related to thelevels of internet adoption in Malaysian hotels.

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Influence of guest segments (leisure vs business)Both business and leisure guests use hotels. It is important that hotels deliverappropriate bundle of benefits for all guest segments. Some studies in the literaturehave attempted to explore the preferences of these two segments of guests (e.g. Gursoyand Gavcar, 2003). Past studies have indicated that business guests generallyconsidered cleanliness and location as important attributes while leisure guestsemployed security, personal interactions, and room rates as prime attributes in theirhotel selection (Clow et al., 1994; McCleary et al., 1993; Yavas and Babakus, 2005).

Dube and Renaghan (1999a, b) have summarized their detailed study on customerloyalty in American lodging industry, and have highlighted the differences in thepreferences of three types of guests – leisure, business (transient) and business(meeting and convention). Their study has found that leisure guests preferred acomfortable stay while the other two business type guests preferred a worry-free stay.They have also found that leisure tourists attributed overall service quality andcleanliness in their perception of “Value for money”, while business tourists attributedconvenient location and value-added service in their perception of “Value for money”.

Using a structural equation modeling framework applied on primary data, Kashyapand Bojanic (2000) have found that perceived price and quality of public areas weresignificant in explaining ratings and intention to revisit for both leisure and businessguests. However, the impacts of other criteria were different for the two guestsegments. They have found that quality of room was significant in explaining ratingsand intention to revisit for business guests but was not significant in explaining thebehavior of leisure guests. Similarly, quality of staff services was significant inexplaining ratings and intention to revisit for leisure guests, but was not significant inexplaining the behavior of business guests. Chu and Choi (2000) have used the theoryof Importance-Performance Analysis framework in understanding the preferences ofleisure and business tourists. They have found that preferences of both business andleisure tourists did not differ much; both the categories stressed service quality, value,room and front desk, and, security in making their hotel choices.

Yavas and Babakus (2005) have used a primary survey to investigate whether hotelchoice attributes are comparable across these two guest segments. They have foundthat both the segments seem to provide the highest importance to the availability ofgeneral amenities. But, the next ranked attributes varied across the two categories.While business guests preferred convenience, core service, room amenities andambiance in the same order, the order of preference of leisure guests were core service,convenience, ambiance, and room amenities. Akbaba (2006) has found that the mostimportant dimension for business tourists was “tangibles” and that leisure tourists hadthe highest expectations for “convenience”.

Studies that used online ratingsWe have used online ratings (i.e. numerical ratings) of hotel guests as our data in thispaper. It is the first time a statistical analysis of such hotel ratings are used to explore therelationships between performance of hotels in terms of various criteria and loyaltybehaviour of customers. However, the use of online ratings for exploring suchrelationships is not new, and several studies exist in the context of e-commerce web sites(e.g. Heim and Field, 2007; Heim and Sinha, 2001; Jiang and Rosenbloom, 2005;Ramanathan, 2010). In the context of hotels and tourism, some recent studies have used

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information from the internet (e.g. Briggs et al., 2007; Christodoulidou et al., 2010; Lawet al., 2004; Wen, 2009; Ye et al., 2010). However, they have used online customer reviews(i.e. verbal feedback) and not online customer ratings (i.e. numerical ratings). Briggs et al.(2007) have used online reviews and comments from Tripadvisor.com as a part of theirstudy to identify the role of demand customers in improving performance of hotels, andexplore gaps between service quality determinants by hotel management and customers.Ye et al. (2010) have shown that guest reviews have a significant impact on online salesof hotels, with a 10 percent increase in traveler review ratings boosting online bookingsby more than five percent. Using 60,648 consumer ratings and comments from an onlinedistribution site, Stringam and Gerdes (2010) have explored the factors that driveconsumer ratings of hotels. Though they have collected customer ratings, their focus wasmore on analyzing verbal reviews and linking to customer ratings. They have identifiedunique words from reviews to provide clues to hotel management on actionable words:those that would suggest areas where a hotel could take action and thereby improve theircustomer satisfaction. They have argued that hotel management should deployresources to improve ratings and guest comments from the online community. As asummary, based on the above literature review, we claim that ours is one of the first fewto statistically analyse online guest ratings from hotels.

Contextual setting and hypotheses developmentConceptual frameworkFigure 1 provides the conceptual framework of our analysis. We consider the intentionof guests to stay in the hotel again as an indication of the performance of a hotel inwinning a customer. This notion is consistent with similar studies in the literature(e.g. Dube and Reneghan, 1999a, b; Heim and Sinha, 2001; Otim and Grover, 2006). Weaim to identify the relationship between performance of hotels in terms of differentcriteria and loyalty behavior of customers. We conjecture that this relationship isinfluenced by star ratings, hotel management characteristics (chain or independent)and guest segments. The hypotheses developed below are also shown in the figure.

Hypotheses developmentDube and Renaghan (1999a, b) have reported 115 functional practices that can befocused by hotel managers for improving customer loyalty, and categorized them intothree broad functional areas:

(1) Physical-property management comprising aspects such as public spaces(including landscaping and general architecture), guest rooms (includingdesign, furniture, amenities) and atmosphere. Figure 1.

Conceptual framework ofthe influence of Star

ratings of hotels, hotelmanagement

characteristics and guestsegments on the

relationships betweenperformance of hotels in

terms of different criteriaand loyalty behaviour of

customers

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(2) People and process management comprising aspects such as personnel,check-in and check-out processes, and on-site hotel services.

(3) Marketing management comprising aspects such as marketing efforts directedto the customer, brand name and reputation, and value for money.

Their study did not consider food in their survey. In our study, we draw upon thesecategories to divide the hotel service criteria in to the three broad functional areas, butinclude food also in our analysis. This classification of criteria is consistent with otherstudies in the literature. For example, Wilkins et al. (2007) have also used three sets ofcriteria – service experience, physical product, and quality of food and beverages inorder to explore their relationships with performance.

Based on these classifications and the literature survey in the second section, wepropose the following hypotheses on the relationships between performance of hotelsin terms of different criteria and guests’ intention to stay again.

H1a-H1c focus on the influence of star ratings. As we discussed earlier, there is ageneral view that star grading of a hotel is driven by physical facilities in the hotel(e.g. Briggs et al., 2007). Following this, we formulate H1a below:

H1a. The significance of criteria related to physical-property management inexplaining guests’ intention to stay again will increase as star ratings ofproperties increase.

Following the observation by Matzler et al. (2005), Siguaw et al. (2000) and Wei et al.(2001) that customer service level was higher as star ratings of hotels increased, weformulate H1b below:

H1b. The significance of criteria related to people and process management inexplaining guests’ intention to stay again will increase as star ratings ofproperties increase.

A main criterion related to marketing management, namely “value for money”, hasbeen consistently recognized by previous studies (e.g. Dube and Renaghan, 1999a, b) asa very important criterion irrespective of star ratings of hotels. Hence, we formulateH1c as follows:

H1c. Criteria related to marketing management will remain significant inexplaining guests’ intention to stay again across all-star ratings ofproperties.

Our next set of hypotheses (H2a-H2c) focus on the role of hotel managementcharacteristics (i.e. chain vs independent hotels). Following Briggs et al. (2007) whohave cited the works of Ingram (1996), independent hotels normally take atransactional approach to their customer service while hotels that are part of achain will take a more transformational approach. Hotels that are part of a chainhave incentives to perform better in terms of consistent physical criteria andservice criteria so as to attract the guest to the branch of the hotel in the locationof his next visit. In contrast, independent hotels would stress more on value formoney (a criterion for marketing management) in order to attract the customeragain:

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H2a. The significance of criteria related to physical-property management inexplaining guests’ intention to stay again will be higher for propertiesbelonging to chains than for independent properties.

H2b. The significance of criteria related to people and process management inexplaining guests’ intention to stay again will be higher for propertiesbelonging to chains than for independent properties.

H2c. Criteria related to marketing management in explaining guests’ intention tostay again will remain significant for independent properties and forproperties belonging to chains.

Our final set of hypotheses (H3a-H3b) focus on the role of guest segments (i.e. leisureguests vs business guests). Drawing on Dube and Reneghan (1999a, b), Kashyap andBojanic (2000) and others, we formulate the following two hypotheses:

H3a. Leisure guests attach higher importance to criteria related to people andprocess management in deciding their intention to stay again compared tophysical-property management.

H3b. Business guests attach higher importance to criteria related tophysical-property management in deciding their intention to stay againcompared to people and process management.

Data and empirical analysisSample and measurementData used in our analysis have been obtained from the customer ratings in www.laterooms.com/, during August-September 2008.

LateRooms is a database offering hotel deals across the UK and worldwide. About42 percent of the total number of accommodations available in LateRooms is in the UKand Ireland. Since its launch in 1999, the web site has diversified its offerings byincluding additional services such as theatre and restaurant bookings. It hasstrategically partnered with travel agents (e.g. www.thetrainline.com) for wider appeal.As per the press pack of LateRooms in its web site, the company’s total transactionvalue was £172 million (about $258 million) in 2008.

The LateRooms database comprises many options, properties from hotels toself-catering apartments, from budget hotels to five-star hotels, and booking optionsfrom ordering online to telephone booking. A mobile version of the main site is alsoavailable. The web site provides extra information to potential tourists by providingcity guides. Hotel star classifications are either based on self-classification by the hotelsthemselves, or are assessed by the Automobile Association (AA) of the UK,VisitBritain, VisitWales or VisitScotland.

One of the attractive features of LateRooms is the availability of user reviews. Userscan read from over 190,000 reviews written by guests who have booked throughLateRooms and actually stayed at the hotel. Guests utilizing the service of a hotel(booked through LateRooms) are subsequently asked by LateRooms to rate theperformance of the hotel. The rating is captured in terms of six different criteria namelycustomer service, cleanliness of hotel, quality of room, value for money, quality of food,and family friendliness of the hotel using a Likert type scale varying from Low (1) to

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High (6) with an additional option for non-availability or non-applicability (NA). Inaddition, customer is asked whether he/she would stay in the hotel again (Yes/ No) andwhether he/she would recommend the hotel to a friend (Yes/No). The ratings from all thereviewers of a hotel are then summarized such that the hotel is rated using the 1-6 Likertscale ratings for the six criteria. The answers to the two Yes/No questions is summarizedas percentages (per cent of reviewers that said they would stay in the hotel again and percent of the reviewers that said they would recommend the hotel to a friend).

Before delving into further analysis, it is appropriate to mention some limitations ofusing the data from LateRooms for the analysis in this study. First of all, LateRooms isone of the many online hotel web sites. It specializes in offering discounted hotel rooms.Though no statistics is available to directly compare the share of LateRooms, someinferences may be made with the available data. As mentioned earlier, total transactionvalue of LateRooms in 2008 was £172 million (about $258 million). Using the share ofproperties (39 percent of total accommodation booked via LateRooms is in the UK) as aproxy for the UK share of this transaction value, about £67 million (about $100 million)may be attributed to the transaction values of LateRooms via its operations in the UK.This represents about 0.3 percent of total expenditure of overnight tourists in the UK in2008 (£21.1 billion or about $32 billion as per data from the UK national statistics).This may represent a very small proportion, but the share may be higher when onlyonline transactions are taken into account for which no data are available.

Second, the internet is not the only source for bookings for hotels in the UK,although the percentage of internet hotel bookings is not readily available. However,use of ratings provided by online guests is appropriate to this study as it aims tounderstand the behavior of online guests and not the entire super-set of the UK hotelcustomers. Also, given that internet has been growing over the years in all sectors ofthe UK economy including the hotel sector (as per the UK E-commerce Survey(www.statistics.gov.uk, accessed on April 9, 2009) and Wei et al. (2001)), understandingthe behavior of online guests becomes more and more important.

Finally, as mentioned in the literature review, data from online customer ratings hasbeen accepted in the literature to derive further insights on the behavior of onlinecustomers (e.g. Heim and Field, 2007).

For our data collection, we selected only those properties (hotels or guesthouses)that received ratings from at least 30 customers. Since our focus is not on any specificcharacteristic of hotels or guesthouses, we do not distinguish between the two in theremainder of this paper, and collectively refer them simply as hotels. Total ratings of333 hotels were collected separately for ratings from leisure customers and for ratingsfrom business customers. The 333 hotels received ratings from a total of 24,544 guests,of which 16,739 are leisure guests and 7,805 are business guests. The breakdown of theproperties is:

. 150 are part of hotel chains and 183 are independent; and

. 112 are three-star hotels, 161 are four-star, 41 are five-star while the rest aretwo-star and budget hotels.

The ratings of business guests and leisure guests are independent of each other as aguest can identify himself/herself as a business guest or leisure guest but not bothwhile recording his/her ratings. For this reason, we consider the effective number of

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hotels in our analysis as 666 comprising 333 hotels based on ratings from leisureguests and an equal number for ratings from business guests.

Table I provides overall summary of the data. Most of the correlations are below orjust around 0.7. Ratings for “Customer service”, “Cleanliness”, “Quality of room” and“Value for money” ranged from 2 to 6, while the ratings for the other two criteriaranged from 1 to 6. Hotels received the highest possible rating of 6 in terms of all theperformance criteria, and also the highest possible rating of 100 percent in terms of“Stay again” and “Recommend to friends.” The standard deviation of ratings in termsof “Quality of food” and “Family friendliness” were higher than that of the other fourcriteria.

Empirical analysisFor validating the hypotheses, we adopt the theoretical framework of Dube andRenaghan (1999a, b) and categorize the six criteria collected by Laterooms into thethree functional areas as follows:

(1) Physical-property management comprising “Cleanliness”, “Room quality” and“Family friendliness.”

(2) People and process management comprising “Customer service.”

(3) Marketing management comprising “Value for money.”

We use multiple ordinary least squares regression analysis for testing H1-H3 becauseof the need to assess the marginal predictive contribution of theoretical variables.Regression analysis is a popular methodology used for assessing marginal predictivecontributions (e.g. Heim and Sinha, 2001). We carried out the usual tests and verifiedthat the assumptions of regression are valid for the data. We tested for normalityassumption of the error terms, checked for the presence of outliers in the data andchecked for multi-collinearity and heteroskedasticity. All these assumptions aresatisfied.

Results of the multiple regression analysis are presented in Table II considering allthe 666 hotels. We have used loyalty behavior of customers (i.e. guest ratings in termsof staying again) as the dependent variable and guest ratings in terms of otherperformance criteria as independent variables. The regression is significant as shown

A B C D E F G H

Customer service (A) 1.0Cleanliness (B) 0.642 1.0Quality of room (C) 0.596 0.710 1.0Value for money (D) 0.581 0.582 0.671 1.0Quality of food (E) 0.662 0.549 0.538 0.535 1.0Family friendliness (F) 0.515 0.433 0.443 0.468 0.493 1.0Loyalty behavior of customers (G) 0.618 0.643 0.689 0.679 0.556 0.461 1.0Recommend to friends (H) 0.678 0.693 0.726 0.699 0.610 0.490 0.893 1.0Minimum 2 2 2 2 1 1 5 21Maximum 6 6 6 6 6 6 100 100Mean 4.78 5.01 4.66 4.56 4.44 4.19 83.18 81.68Std deviation 0.680 0.657 0.766 0.674 0.866 0.838 14.500 15.475

Table I.Correlations and

summary statistics

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53

by the high value of F- statistic ( ¼ 165), which, as the triple asterisk next to it shows, ishighly significant at 1 percent level. The value of R 2 is also high (0.619) signifying thatthe independent variables are able to explain 61.9 percent of variability in thedependent variable. The coefficient for the criterion “Customer service” has a value of2.668 and this criterion is significant at 1 percent level (shown by the triple asterisk,which as the footnote to the table explains is interpreted as p , 0:01). Other entries ofthis table can be interpreted in a similar way. Thus, we find that all the six criteria aresignificant in explaining loyalty behavior of customers.

Table III provides the results for hotels with various star ratings, chain andindependent hotels, and leisure and business guests. Note that the sum of all the threecategories of star ratings do not add to 666 as there were some two-star and budgethotels that are not considered in these regressions. The results of this table shows thatour H1a is not supported as “Cleanliness” and “Room quality” are significant forthree-star hotels and four-star hotels, but not for five-star hotels. “Family friendliness”is significant only for four-star hotels. Thus we conclude that the significance ofcriteria related to physical-property management in explaining guests’ intention tostay again does not increase as star ratings of hotels increase. H1b is partiallysupported as customer service is not significant for three-star hotels but is significantfor four- and five-star hotels. Since “Value for money” is significant for all the threelevels of star ratings, we have support for H1c.

Looking at the columns of Table III for chain and independent hotels, we find thatH2a is not supported as “Cleanliness” and “Room quality” are significant and “Familyfriendliness” is not significant for both chain and independent hotels. We henceconclude that the significance of criteria related to physical-property management inexplaining guests’ intention to stay again does not vary for hotels belonging to chainsand for independent hotels. We find that “Customer service” is not significant for chainhotels but is significant for independent properties. This result does not support H2b,but supports the exact opposite; guests of independent hotels value performance interms of people and process management. Since “Value for money” is significant forboth chain and independent hotels, H2c is supported.

Looking at the significance of criteria in the last two columns of Table III, we find thattwo of the three criteria related to physical-property management (“Cleanliness” and“Room quality”) are significant and also “Customer service” is significant for leisure

All hotels

Intercept 28.018 * *

Customer service 2.668 * * *

Family friendliness 0.912 *

Value for money 6.225 * * *

Cleanliness 3.286 * * *

Room quality 5.326 * * *

Quality of food 1.163 *

R 2 0.619Adjusted R 2 0.613F statistic 165 * * *

Notes: *p , 0:10, * *p , 0:05, * * *p , 0:01; dependent variable: loyalty behavior of customers

Table II.Multiple regressionanalysis of all hotels

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ily

frie

nd

lin

ess

0.15

1.35

*2

1.46

0.73

0.71

0.95

1.09

Criterion

relatedto

peopleandprocessmanagement

Cu

stom

erse

rvic

e0.

344.

43*

*5.

42*

1.44

3.31

**

3.76

**

1.26

Criterion

relatedto

Marketingmanagement

Val

ue

for

mon

ey6.

01*

*5.

53*

*4.

77*

*6.

81*

*5.

37*

*5.

75*

*6.

75*

*

Criterion

relatedto

food

andbeverages

Qu

alit

yof

food

1.72

0.69

3.90

**

1.72

*1.

87*

1.12

1.54

*

R2

0.59

0.64

0.58

0.59

0.63

0.57

0.64

Ad

just

edR

20.

580.

630.

550.

580.

620.

560.

64F

stat

isti

c52

.1*

*91

.44

**

17.5

6*

*70

.96

**

101.

95*

*73

.28

**

95.5

4*

*

Notes:

* p,

0:05

;*

* p,

0:01

;d

epen

den

tv

aria

ble

:lo

yal

tyb

ehav

ior

ofcu

stom

ers

Table III.Results of regressionanalysis for various

categories

Performancecriteria in hotels

55

guests. This result does not show overwhelming preference for people and processmanagement. Hence, H3a is not supported. But, H3b is supported because two of thethree criteria related to physical-property management (“Cleanliness” and “Roomquality”) are significant but “Customer service” is not significant in the case of businessguests. Further, the criterion “Quality of food” is significant only in some of the columnsof Table III – five-star hotels, hotels that are part of chains, independent hotels and forbusiness guests.

Discussion and managerial implicationsTable IV provides a summary of acceptance or rejection of our hypotheses. Thus H1a,H2a, H2b and H3a have not been supported while hypotheses 1c, 2c and 3b have beensupported. H1b is partially supported.

We believe that these results provide useful information for managers of hotels inthe UK in particular and for worldwide hotels in general. The most important result ofour analysis is the universal significance of the criterion related to marketingmanagement, “Value for money”, evidenced by the support of H1c and H2c. Asmentioned earlier, this is a complex criterion that is related to the price and discountson the room rate, and other value added features of hotels such as overall servicequality, convenient location, uncommon services, cleanliness, etc. (Dube andRenaghan, 1999a). As per Tables III and IV, this criterion is significant in all theregressions. This finding calls for efficient operational practices that minimize the costof operation, which will be ultimately passed on to guests who will perceive gettinggood service for the best possible price. The importance of this criterion has beenstressed in several studies on hotel performance (Briggs et al., 2007; Chen andSchwartz, 2008; Dube and Renaghan, 1999a, b; Gallarza and Saura, 2006).

As mentioned in the literature survey, Dube and Renaghan (1999a, b) have found“Value for money” as an important criterion in explaining customer loyalty in the USA,with 80 percent of their respondents identifying this as a major criterion for their choiceof a preferred hotel. Chen and Schwartz (2008) have stressed the importance of valuewhen guests book a room on the internet and showed that the patterns of changes inroom rates observed by guests while searching for a deal affects their propensity tobook. Using a structural equation modeling study, Gallarza and Saura (2006) haveconfirmed the existence of a quality-value-satisfaction-loyalty chain in explaining thebehavior of tourist customers in Spain.

Star rating

Chain orindependenthotels

Leisureguests

Businessguests

Criteria related to physical-propertymanagement

H1a notsupported

H2a notsupported

H3a notsupported

H3b supported

Criterion related to people andprocess management

H1b partiallysupported

H2b notsupported

Criterion related to marketingmanagement

H1c supported H2c supported

Table IV.A summary of acceptanceor rejection of thehypotheses

IJCHM24,1

56

Table II shows that all the criteria are significant in explaining guests’ intention to stayagain in the UK hotels when all the hotels are considered in the analysis. This resultpoints to the need for generally performing well in terms of all the hotel service criteriain order to influence the repeat stay intentions of guests. This result is consistent withthe finding of Dube and Renaghan (1999a, b) that has found quality standards ofhotel-stay services, guest room design, amenities, personnel, brand name, and value formoney as the five top functional areas of customer loyalty. These functional areas werementioned by 80 percent to 85 percent of guests for choosing their preferred hotel.

In addition, some more interesting results emerge based on validating the hypotheses.Our results generally indicated that guests perceive performance of the UK hotelsdifferently across various categories – star classifications, chain and independent hotels,and leisure and business guests. This shows that the expectations of guests are quitedifferent across these categories, and a general solution may not satisfy all thesecategories. For example, business and leisure guests perceive facilities differently andhence hotel managers need to provide different kinds of services to satisfy them. Thisfinding is consistent with those of Dube and Renaghan (1999a, b) for the USA. Thisresult is also similar to that of Briggs et al. (2007) that have found for Scotland thatcustomer service ratings in terms of several performance criteria (friendliness, standards,personal service, and tangibles) differed significantly across hotels of various sizes(small, medium, large) except for the factor “value for money”.

Summary and conclusionsWe studied the significance of performance of hotels in terms of six customer servicecriteria on the intentions of guests to stay in the UK hotels again. We used the onlineratings available at www.laterooms.com as our data, and employed regression for theempirical analysis.

Results of H1-H3 provide specific insights on the significant criteria across thesecategories. The most important result is the support for Hypothesis 3b that foundbusiness guests exhibit higher importance to criteria related to physical-propertymanagement in deciding their intention to stay again in the UK hotels compared topeople and process management. This indicates that good performance of hotels inmaintaining room quality and cleanliness can significantly influence the intentions ofbusiness guests to stay again. This result agrees well with those of Kashyap andBojanic (2000), who have found quality of room was significant for business guests’intention to revisit the USA. However, this result is somewhat contrary to the findingsof Brown and Maxwell (2002) for the UK and Tsaur and Lin (2004) for Taiwan, whohave found that good performance in terms of service-specific criteria was important tohotels. However, as the result of H3a shows, leisure guests expect good performanceboth in terms of physical-property management and, people and process management.

Results of H1a and H1b indicate that the significance of criteria related tophysical-product management and people and process management generally varyacross star ratings in the UK hotels. It may be because guests’ expectation of thequality differed depending on star rating, and their ratings accounted for suchdifferences in expectations. This finding is somewhat contrary to the belief that starratings are mainly based on physical facilities (Briggs et al. (2007) for Scotland) orbased on service (Matzler et al. (2005) for Austria; Orfila-Sintes and Mattsson (2009) forthe Balearic Islands). Our finding generally agrees with that of Fernandez and Bedia

Performancecriteria in hotels

57

(2004) who did not identify significant relationships between hotel star ratings systemand the levels of service quality in the Spanish context.

From Table III, we see that physical-property management is significant inexplaining loyalty behavior for three-star and four-star hotels, but not for five-star hotels.This may be due to the differing expectations from hotels of various star ratings. A guestsatisfied with physical facilities has a positive impact on his loyalty intentions in the caseof three-star or four-star hotels. But they may consider good physical facilities as a basicnecessity for five-star hotels and hence a satisfaction in terms of physical facilities doesnot influence their intentions to visit the same five-star hotel again.

Results of H2a and H2b generally point that criteria related to people and processmanagement are valued by guests of independent hotels. This finding is somewhatcontrary to previous observations by Briggs et al. (2007) that hotels that are part of achain take a transformational approach by providing a consistently efficient service.Guests of chain hotels do not consider the criteria related to people and processmanagement as significant. Further, two of the three criteria related tophysical-product management are significant for these guests. These results indicatethat chain hotels in the UK tend to emphasize uniform levels of physical productsacross chains and are valued by guests.

Table III also shows that customer service is significant for four-star and five-starhotels and not for three-star hotels. Thus, customer service could be considered as aservice differentiator for higher star hotels.

While our study has provided important results, we wish to stress some of thelimitations of our study and scope for future research. The most important limitation ofour study is the use of secondary data in our analysis. Unlike a primary questionnairesurvey, our data is not based responses of individual customers but is based on theaggregated ratings provided by several customers (minimum 30) for a hotel. Theaggregation might have concealed some differences in individual responses. Because wehave used secondary data, the hotel service criteria chosen in this study are limited bythose collected at the web site. While all the six criteria considered in this study areimportant, some other potentially important criteria (e.g. location, use of technology, etc.)could not be considered in the analysis. Our analysis has been limited to the UK hotels butmore geographical regions could be considered and related to the cultural perspectives ofthe region. We focused on the web site of LateRooms for collecting our data, but datacould also be collected from more hotel rating sites (e.g. tripadvisor.co.uk, expedia.co.uk,etc.). However, in spite of these limitations, we hope that the present study is useful tohotel managers in understanding the drivers of guests’ intention to stay again.

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About the authorRamakrishnan Ramanathan is an Associate Professor in Operations Management at NottinghamUniversity Business School and can be contacted at: ram.ramanathan@nottingham.ac.uk

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