A model of lodging repeat choice intentions

AnnalsofTourism

Pergamon

Research, Vol. 21, No. 4. pp. 745-755, 1994 Copyright 0 1994 FJsevier Science Ltd Printed in the USA. All rights reserved 0160-7383/94 $6.00 + .OO

0160-7383(94)E0013-H

A MODEL OF LODGING REPEAT CHOICE INTENTIONS

Mississippi

Michael D. Richard D. S. Sundaram State University, USA

Abstract: A lodging offering involves tangible elements as well as intangible services. Therefore, the guest evaluates both the outcome and the process of service delivery. The influences on repeat choice intentions of the outcome and process dimensions of service quality are investigated using a regression model. Service quality does appear important for explaining lodging choice intentions. Results suggest that no one dimension of service quality captures the complexity of repeat choice intentions; several outcome and process quality dimensions are important. In other words, guests evaluate several dimensions when making lodging choices. Managerially, the lodging firm may wish to emphasize multiple dimensions when promoting their service to attract guests. Keywords: lodging, service quality, choice.

R&urn& Un mod+le des intentions

du choix rep&( de logement. Une offre de logement comprend des ClCments tangibles et des services intangibles. Le client (value done le processus du service aussi bien que le rtsultat. On Ctudie l’influence du processus et du rCsultat sur les intentions de choix rip&C en utilisant un modele de regression. La qualite du service ne paraft pas efre importante pour expliquer les intentions du choix de logement. Les r&hats indiquent qu’il n’y a pas un aspect unique de la qualit& du service qui resume la complexite des intentions de choix; au contraire, il y a plusieurs dimensions importantes de la qualit& du processus et du resultat. La gestion devrait souligner de multiples dimensions en presentant les services pour attirer des clients. Mots-cl&: logement, qualitC de service, choix.

INTRODUCTION Service quality is a critical competitive weapon providing lodging establishments with numerous benefits in terms of increased market share and profitability (Marinko 1990). Enlightened lodging managers realize that service is more than renting rooms. The lodging offering is a complex combination of an environment and an experience that starts when the guests make the reservation and lasts at least until they pay their bills. As such, service quality includes the establishment’s entire surroundings, from the desk clerk’s courtesy to the size and decor of the room (Bitner 1992). Therefore, the guest evaluates the outcome (e.g., was the room clean?) and the process (e.g., was the maid pleasant?) of service delivery (Gronroos 1982). The lodging industry is somewhat unique in that it may involve many encounters between a given guest and service providers and Michael Richard is Assistant Professor of Marketing at Mississippi State University (Mississippi State MS 39762: USA). He earned his Ph.D. from the University of Alabama. His research interests include chorce and market share models. D. S. Sundaram is a graduate student at Mississippi State University. His research interests include choice models and sales management. 745

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facilities. In each encounter, the guest may evaluate a number of different attributes. In order to manage service quality, therefore, lodging managers should have an understanding of the attributes that are perceived as important to the lodging guest (Lewis and Nightingale 1991). While there is agreement that service quality is a strategic tool (Marinko 1990), much of the research on lodging service quality possesses shortcomings. First, while it is generally agreed that service quality is a multi-attribute construct (Oberoi and Hales 1990), empirical studies have used a single indicant of service quality (Lewis 1985). Second, service quality evaluations involve both outcome and process quality attributes of service delivery. Outcome quality includes attributes pertaining to “what was delivered” while process quality focuses on attributes related to “how the service was delivered” (Gronroos 1982). Outcome and process quality are identical to the functional and technical quality discussed by Oberoi and Hales (1990). However, the terms of process and outcome are the more widely utilized terms. Mangold and Babakus (1991) contend that the most popular measurement instrument, SERVQUAL, focuses only on the process quality attributes. Third, the studies of lodging attributes and repeat choice intentions involve some rating of the attributes thought to influence intentions (Bush and Hair 1976). As such, these studies do not attempt to build models of the relationship between the attributes and repeat choice intentions. The purpose of this study is to develop and test a model of guests’ lodging repeat choice intentions. Specifically, this study investigates the importance of service quality to lodging repeat choice intentions. Lodging Choice Intentions The attributes of lodging selection at discount and conventional motels were investigated by Bush and Hair (1976). The rank importance of 14 attributes thought to influence motel selection were reported. The ranking differed between discount and conventional motel guests. For the discount motel, the most important attributes were price, location, and appearance. For the conventional motel, the most important attributes were past experience, appearance, and location. The rank of 26 lodging attributes, in terms of the frequency of complaints and compliments, were reported by Cadotte and Turgeon (1988). The most frequent complaints were availability of parking, traffic congestion, and quality of service. Compliments that occurred most frequently were quality of service, food quality, and helpful attitude of employees. The SERVQUAL instrument was utilized by Fick and Ritchie (1991) in the lodging industry. The mean scores of the 22 expectation and performance statements of SERVQUAL were examined. Expectation statements of reliability and assurance had the highest mean scores. For the performance statements, the highest mean scores were associated with tangibles and assurance. Rivers, Toh and Alaoui (1991) compared members to nonmembers of frequent-stayer programs in terms of the attributes that influence the

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choice of lodging establishments. Convenience of location and overall service were rated as most important for both groups. Service quality attributes for conference lodging establishments were examined by Oberoi and Hales (1990). The original 54 attributes of service quality were hypothesized to represent four dimensions of service quality: facilities, catering/food, pricing, and activities. Factor analysis of a subject of 23 attributes resulted in a two factor solution. The two dimensions of service quality were labeled functional components (i.e., process quality attributes) and technical components (i.e., outcome quality attributes). Using multiple regression, Lewis (1985) investigated 16 predictor variables (or attributes) of lodging choice for business and pleasure travelers. The most important attributes were service quality, security, and image for the business traveler. For the latter, the most important attributes were quietness, service quality, and location. Much of the literature investigating lodging attributes and choice intentions, such as studies by Bush and Hair (1976), Cadotte and Turgeon (1988), Fick and Ritchie (1991), and Rivers, Toh and Alaoui (1991), involve some ranking or rating of the attributes thought to influence choice intentions. As such, these studies make no attempt to examine the relationship; between these attributes and some measure of choice intentions. While Lewis (1985) examined the relationship between lodging attributes and choice intentions, the problem of multicollinearity between attributes was one limitation in data analysis. Further, only a single global measure of service quality was investigated limiting the model’s diagnostic usefulness. Service quality measurement is essential to the success of any lodging establishment (Lewis and Nightingale 1991). Service quality is defined as guest assessment of the overall excellence or superiority of the service (Zeithaml 1988). Evaluations of service quality involve a comparison of guest expectations with guest perceptions of actual service performance (Parasuraman, Zeithaml and Berry 1985, 1988, 1991). SERVQUAL h as b een developed to measure the process quality dimensions of service quality (Mangold and Babakus 1991) as perceived by the consumer (Parasuraman, Zeithaml and Berry 1985, 1988, 199 1). Perceived service quality is defined as a difference score that is obtained by subtracting a consumers’ expected performance from their perceptions of actual performance along five service quality dimensions: tangibles, reliability, responsiveness, assurance, and empathy (Parasuraman, Zeithaml and Berry 1988). Utilizing difference scores as operationalizations of service quality has been criticized (Babakus and Boller 1992; Carman 1990; Cronin and Taylor 1992; Fick and Ritchie 1991). First, the use of two sets of statements (expectation and performance) may be too time-consuming to administer (Babakus and Boller 1992; Carman 1990). Second, while expectations are important in assessing service quality, the current method of asking consumers about their expectations “after” service use is biased since expectations should be measured prior to service use (Carman 1990). Third, “consumer confusion” (Babakus and Boller 1992) may result from one set of statements referring to an industry

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(i.e.,

expectation statements) and one set of statements referring to a particular firm (i.e., performance statements). The use of SERVQUAL as a measure of lodging establishment service quality has been criticized (Fick and Ritchie 1991). The use of the average score of the items on a given dimension limits SERVQUAL’s diagnostic usefulness (Fick and Ritchie 1991). If the average score is low, one cannot determine which specific items are responsible. Also, SERVQUAL may not be applicable to lodging establishments where guests use multiple services and encounter numerous service providers (Fick and Ritchie 1991). Guests have to cluster “good” employee encounters (e.g., a front desk employee encounter) with “poor” employee encounters (e.g., a room service employee encounter). Furthermore, Fick and Ritchie (1991) suggest that the tangibles dimension of service quality can be further divided into room, recreational, lobby, etc. However, SERVQUAL cannot capture these divisions without increasing the number of questions. An alternative scale format has been suggested (Babakus and Boller 1992; Carman 1990). Expectation and performance are combined in single items requiring the consumers themselves to link their experience of the service product with their earlier expectations. These items and can be presented with anchors “Greatly Exceeds Expectations” “Greatly Falls Short of Expectations.” Variants of this format have been tested by Oberoi and Hales (1990) in a lodging setting and by Richard and Allaway (1993) in a food-service setting. Richard and Allaway (1993) report that the format that combines both expectation and performance in single items exhibit higher reliability and validity as compared to using difference scores to create measures of service quality.

THE

STUDY

AND ITS DESIGN

An examination of the literature by the authors produced 29 service quality items hypothesized to influence lodging repeat choice intentions (Bush and Hair 1976; Cadotte and Turgeon 1988; Fick and Ritchie 1991; Lewis 1985; Oberoi and Hales 1990; Rivers, Toh and Alaoui 1991). They used content analysis to categorize the 29 items into a manageable number of dimensions. This analysis resulted in six dimensions: reception service (RECEPTION); accommodations amenities (ACCOMMODATIONS); departure service (DEPARTURE); food service (FOOD); building appeal (BUILDING); and bathroom amenities (BATHROOM). Table 1 presents the statements utilized in this study as well as their a priori groupings. Several hypotheses were developed and tested in a regression model format : H,: The dimension of RECEPTION is not significantly or positively related to repeat choice intentions. H,: The dimension of ACCOMMODATIONS is not significantly or positively related to repeat choice intentions. H,: The dimension of DEPARTURE is not significantly or positively related to repeat choice intentions.

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Table 1. Item Names, Service Quality Statements, and A Priori Groupings Item Reception: RECEPTl RECEPTP RECEPTJ RECEPT4 Accommodations: ACCOMS ACCOM6 ACCOM7 ACCOM8 ACCOM9 ACCOMlO

ACCOMl 1 ACCOM12 ACCOMl3 ACCOM14 Departure: DEPART 15 DEPART 16 DEPART1 7 DEPART18 Food: FOOD19 FOOD20 Building: BUILD2 1 BUILD22 BUILD23 BUILD24 BUILD25 BUILD26 Bathroom: BATH27 BATH28 BATH29

Service

Quality

Statements

Reception staff courtesy at check-in Check-in efficiency Lobby staff assistance at check-in Ease of check-in Room cleanliness Room furniture comfort Room housekeeping Room television quality Comfort of the mattress and pillows Quality of the climate control system Room quietness Decor of the room Spaciousness of the room Value of room for the price paid Front desk staff courtesy at check-out Check-out efficiency Lobby staff assistance at check-out Ease of check-out Food/beverage value for price paid Quality of food/beverage Convenience of location Availability of parking Feeling of security Building decor Lobby appearance Recreational facilities Bathroom Bathroom Bathroom

cleanliness amenities and towels housekeeping

H,: The dimension of FOOD is not significantly or positively related to repeat choice intentions. H,: The dimension of BUILDING is not significantly or positively related to repeat choice intentions. H,: The dimension of BATHROOM is not significantly or positively related to repeat choice intentions. A large Southeastern airport served as the data collection site to obtain respondents from as many different lodging establishments as possible. Respondents were screened to ensure that only pleasure travelers, who were returning from a pleasure trip involving a lodging stay, were used in this study. Data collection yielded 198 usable questionnaires.

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LODGING REPEAT CHOICE INTENTIONS

The representativeness of the sample was investigated by comparing the demographic profile of the sample with the most recent available population distribution within the study area. Population data on age, household income, and employment were used to compare the population to the sample. Both the parametric (t = 0.1744, df = 9, p > 0.9000)and the nonparametric (tR = 0.0880, df = 9, p > 0.9000) paired t-tests support the hypothesis of not significant differences between the two groups. Respondents were asked to complete a two-page questionnaire. One section contained items designed to gather the name of the lodging establishment utilized on the present trip, repeat choice intentions and an overall service quality rating of the named establishment, and a set of service quality statements concerning the same establishment. The items in this section were scrambled. The second section consisted of a standard demographic profile of respondents. Ratings on each of the service quality statements in Table 1 were assessed using lo-point response scales anchored by “Greatly Falls Short of Expectations” (0) and “Greatly Exceeds Expectations” (9). Results of Richard and Allaway (1993) suggest the psychometric superiority of this type of format over the traditional difference score approach. Lodging repeat choice intention was measured using a lopoint scale anchored by “Definitely Would Not Return” (0) and “Delinitely Would Return” (9). RESULTS

OF THE

STUDY

Since the items are purported to measure six dimensions of service quality, the reliability and factor structure of the items require assessment. All 29 items were subjected to a factor analysis and a varimax rotation. For the factor analysis, the data of all 198 respondents were utilized. The criterion utilized to extract factors was the latent root ( i.e., eigenvalue) criterion. Six eigenvalues exceeded 1 .OOOO.As such, a six dimension solution suggested by the content analysis was confirmed by the factor analysis and latent root criterion. While there was an a priori determination of how the items should load, the results of the factor analysis was utilized to confirm (or to fail to confirm) the said determination. This approach of applying factor analysis to a priori groups of items has been extensively utilized to examine the dimensionality of constructs (Carman 1990). The factor structure, while not in accord with a priori expectations for the grouping of items, was encouraging. Specifically, only items ACCOMlO and BUILD22 did not load with their a priori groups. As a result, these two items were deleted from further analysis for lack of convergent validity. This deletion of items necessitated the recomputation of alpha values and the reexamination of the factor structure of the reduced item pool. The factor loadings for the 27 items and alpha values are summarized in Table 2. The resulting six factor solution explains approximately 90 % of the variance. The factor loadings in Table 2 reveal a clean structure and one in accord with a priori expectations. The alpha values associated with each dimension are consistent with those reported in other service quality

RICHARD

AND SUNDARAM

Table 2. Reliability

and DimensionaIity (n = 198)

Dimension/Item

Coefficient Alpha

Reception: RECEPTl RECEPTZ RECEPT3 RECEPT4 Accommodations: ACCOM5 ACCOM6 ACCOM7 ACCOM8 ACCOM9 ACCOMlO” ACCOMl 1 ACCOM12 ACCOM13 ACCOM14 Departure: DEPART1 5 DEPART16 DEPART1 7 DEPART18 Food: FOOD19 FOOD20 Building: BUILD2 1 BUILD22” BUILD23 BUILD24 BUILD25 BUILD26 Bathroom: BATH27 BATH28 BATH29 “ACCOMlO and BUILD22 lack of convergent validity.

751

Results

Factor Loading on Dimension to Which Item Belongs

0.8569

0.7711 0.7557 0.7071 0.6041 0.8699 0.6038 0.5731 0.6709 0.5826 0.6706 0.6120 0.6025 0.5617 0.6414 0.8343 0.7540 0.7227 0.6682 0.5864 0.8628 0.6864 0.7230 0.7448 0.5092 0.5491 0.5090 0.5255 0.5274 0.8708 0.6098 0.7404 0.7615 were omitted from analysis due to

Zeithaml and Berry 1988, 199 1). These findstudies (Parasuraman, ings support the internal consistency of the scale items for each dimension. Regression analysis was employed to investigate whether a group of explanatory variables, which constitute six dimensions of service quality, exert a significant influence on repeat choice intentions. These explanatory variables were the six linear combinations (i.e., dimensions) of the 27 items derived from factor analysis. Since the linear combinations are the result of the factor analysis

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with a varimax rotation, the factors should be orthogonal. An examination of the “condition indexes and variance decomposition proportions” confirms that there are no severe problems with multicollinearity between the dimensions. In fact, the largest condition index is only 5.6488. As such, the use of these factors overcomes the multicollinearity problem encountered by Lewis (1985). The parameters of the regression model were estimated using the data of 125 respondents. Table 3 presents the parameter estimates and goodness-of-fit statistics for the regression model. The model achieved a significant overall level of goodness-of-fit as measured by the F-test. In other words, at least one of the dimensions of service quality is important for explaining repeat choice intentions. In addition, the R* indicates that approximately 81% of the variance in repeat choice intentions can be explained by the six dimensions of service quality. The true test of a model’s diagnostic usefulness is evidenced by its predictive accuracy. Prior to parameter estimation, survey participants were randomly assigned to the estimation (125 respondents) or to the holdout (73 respondents) data sets. The parameters of the regression model estimated from the estimation data set were used to predict repeat choice intentions in the holdout data set. Predicted intentions are correlated with actual intentions in the holdout data set to obtain a measure called a cross validity correlation coefficient (Green and Srinivasan 1978), which for this study is 0.7327. As such, the encouraging fit of the regression model carries over to the holdout sample of observations. The t-test (one-tailed test) produced by the regression program was

Table 3. Parameter Estimates, Goodness-Of-Fit, and Cross Validation of Regression Analysis’

Dimension

Parameter Estimates (Standard Error)

Reception Accommodations Departure Food Building Bathroom Intercept

0.0622b 0.0536b 0.0419 - 0.0339 0.0555b 0.0506b - 0.9338b

(0.0279) (0.0144) (0.0457) (0.0305) (0.0174) (0.0173) (0.2321)

Goodness-Of-Fit:

RZ Adjusted R2

0.8137 0.8093

Cross Validation: Cross Validity Correlation Coefticient

0.7327

“125 observations were used to estimate the parameters of the regression model while the remaining 73 observations were retained for cross validation. bSignificant at the 0.05 level.

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employed to assess the statistical significance of the dimensions of service quality. At the 0.05 level, the regression model has four significant dimensions. In addition, all of the significant dimensions agree with their a priori signs. It appears that attributes of RECEPTION (e.g., reception staff courtesy), ACCOMMODATIONS (e.g., room cleanliness), BUILDING (e.g., lobby appearance), and BATHROOM (e.g., bathroom amenities and towels) are important to repeat choice intentions. As such, there is support for hypotheses 1, 2, 5, and 6. This study is not without limitations. First, although Cadotte and Turgeon (1988) found availability of parking to be an important source this study did not investigate this attribute. of guest compliments, While guests were asked to evaluate the availability of parking in this study, this attribute was deleted from analysis due to lack of convergent validity. Second, price only enters the analysis as two items (i.e., value of room for price paid and food/beverage value for price paid). Intuitively, guests might also assess the value of other services (e.g., recreational facilities, convenience of location, etc.). However, the value of these other services was not explicitly examined in this study. Finally, unique segments of the population may vary in the ‘importance of specific attributes or dimensions of service quality as predictors of intentions. For example, while the FOOD dimension may not have been found to be important in predicting repeat choice intentions for the entire sample, it is entirely possible for this dimension to be important for some subset of the population. Segment-specific analysis would allow the researcher and manager to investigate the differential influence of these dimensions across segments. Such differential influences could form the basis of segmentation strategies aimed at attracting specific segments of the population. However, no analyses were performed on separate segments of the sample in this study. CONCLUSIONS Overall, the findings of this study provide support for the conceptualization of service quality in a lodging setting. Lodging service quality appears to be a multidimensional construct. In addition, there appears to be support for six dimensions (reception, accommodations, departure, food, building, and bathroom) of this construct. Four of the six dimensions were found to be significant in predicting repeat choice intentions. The reliability and validity of the multi-item scale used in this study were encouraging. As such, the use of this type of scale should facilitate further research. Lodging managers may find these results insightful when attempting to attract guests. Lodging firms are realizing that their offering is partly a tangible product and partly intangible services (Shostack 1977). Guests utilize multiple dimensions of service quality in repeat choice intentions. No one dimension of service quality captures the complexity of repeat choice intentions. As such, lodging managers may wish to emphasize multiple dimensions when promoting and providing lodging services. For example, advertisements could emphasize multiple dimensions such as room accommodations, ease of check-in, recre-

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ational facilities, etc. Conversely, since guests consider multiple dimensions in repeat choice intentions decisions, emphasis on only one dimension may not be as effective in attracting guests. The approach taken in this study should prove diagnostically useful to the lodging manager in terms of investigating the influence of several dimensions of service quality on repeat choice intentions. Service quality is a competitive weapon (Marinko 1990). Managers must realize that meeting and/or exceeding guest expectations more efficiently than competition is what ultimately drives guest choice. The challenge is to determine which specific dimensions have the greatest impact on choice. Once identified, lodging managers can then develop a marketing program that emphasizes the most important dimensions while reasonably containing the cost of these service quality dimensions to which the guest is indifferent. •i 0 REFERENCES Babakus, Emin, and Gregory W. Boller 1992 An Empirical Assessment of the SERVQUAL Scale. Journal of Business Research 24(2):253-268. Bitner, Mary Jo 1990 Evaluating Service Encounters: The Effects of Physical Surroundings and Employee Responses. Journal of Marketing 54(2):69-82. 1992 Servicescapes: The Impact of Physical Surroundings on Customers and Employees. Journal of Marketing 56(2):57-73. Bush, Ronald F., and Joseph F. Hair 1976 Consumer Patronage Determinants of Discount Versus Conventional Motels. .Ioumal of Retailing 52(2):41-50, 90-92. Cadotte, Ernest R., andNormand Turgeon 1988 Kev Factors in Guest Satisfaction. The Cornell Hotel and Restaurant Administration Quarterly 28(1):45-51. Carman, James M. 1990 Consumer Perceptions of Service Quality: An Assessment of the SERVQUAL Dimension. Journal of Retailing 66(1):33-55. Cronin, J. Joseph, and Steven A. Taylor 1992 Measuring Service Quality: A Reexamination and Extension. Journal of Marketing 56(3):55-68. Fick, Gavin R., and J. R. Brent Ritchie 1991 Measuring Service Quality in the Travel and Tourism Industry. Journal of Travel Research 30(3):2-g. Green, Paul E., and V. Srinivasan 1978 Conjoint Analysis in Consumer Research. Journal of Consumer Research 5(4):13-23. Gronroos, Christian 1982 Strategic Management and Marketing in the Service Sector. Helsingfors, Sweden: Swedish School of Economics and Business Administration. Lewis, Robert C. 1985 Predicting Hotel Choice: The Factors Underlying Perception. The Cornell Hotel and Restaurant Administration Quarterly 25(1):82-96. Lewis, Robert C., and Michael Nightingale 1991 Targeting Service to your Customer. The Cornell Hotel and Restaurant Administration Quarterly 31(3):18-27. Mangold, W. Glynn, and Emin Babakus 1991 Service Quality: The Front-Stage vs. the Back-Stage Perspective. Journal of Services Marketing 5(3):59-70. Marinko, Barbara 1990 Ringing in Service at the Touch of a Button. Hotel and Motel Management 205(2):57.

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Oberoi, Usha, and Colin Hales 1990 Assessing the Quality of the Conference Hotel Service Product: Towards an Empirically Based Model. The Service Industries Journal 10:700-721. Parasuraman, A., Valarie A. Zeithaml, and Leonard Berry 1985 A Conceptual Model of Service Quality and its Implications for Future Research. Journal of Marketing 49(4):41-50. 1988 SERVQUAL: A Multi-Item Scale for Measuring Consumer Perceptions of Service Quality. Journal of Retailing 64(1):2-40. 1991 Refinement and Reassessment of the SERVQUAL Scale. Journal of Retailing 67:420-450. Richard, Michael E., and Arthur W. Allaway 1993 An Empirical Investigation of the Psychometric Properties of Alternative Service Quality Scales. 1993 Annual Meeting of the Journal of Marketing Theory And Practice 43 l-43 7. Rivers, Mary J., Rex S. Toh, and Mehdi Alaoui 1991 Frequent-Stayer Programs: The Demographic, Behavioral, and Attitudinal Characteristics of Hotel Steady Sleepers. Journal of Travel Research 30(3):4145. Shostack, G. Lynn 1977 Breaking Free from Product Marketing. Journal of Marketing 41(2):73-80. Zeithaml, Valarie A. 1988 Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence. Journal of Marketing 52(3):2-22. Submitted 3 December 1992 Resubmitted 7 June 1993 Accepted 7 October 1993 Refereed anonymously Coordinating Editor: Pauline J. Sheldon