A Study of Tourists' Satisfaction and Post- Experience Behavioral Intentions in Relation to Airport Restaurant Services in the Hong Kong SAR

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1 Journal of Travel & Tourism Marketing ISSN: (Print) (Online) Journal homepage: A Study of Tourists' Satisfaction and Post- Experience Behavioral Intentions in Relation to Airport Restaurant Services in the Hong Kong SAR Dr. Vincent C. S. Heung, M. Y. Wong & Hailin Qu To cite this article: Dr. Vincent C. S. Heung, M. Y. Wong & Hailin Qu (2002) A Study of Tourists' Satisfaction and Post-Experience Behavioral Intentions in Relation to Airport Restaurant Services in the Hong Kong SAR, Journal of Travel & Tourism Marketing, 12:2-3, , DOI: / J073v12n02_07 To link to this article: Published online: 13 Oct Submit your article to this journal Article views: 266 View related articles Citing articles: 15 View citing articles Full Terms & Conditions of access and use can be found at Download by: [UCL Library Services] Date: 20 March 2017, At: 23:46

2 A Study of Tourists Satisfaction and Post-Experience Behavioral Intentions in Relation to Airport Restaurant Services in the Hong Kong SAR Vincent C. S. Heung M. Y. Wong Hailin Qu ABSTRACT. The present study aims to explore the relationships among the perceptions, satisfaction and post-purchase behavioral intentions of 630 customers dining experiences at Hong Kong s airport restaurants. The results indicated that there were positive relationships between tourists perceptions and overall satisfaction, likelihood of returning and likelihood of making a recommendation. Three perception factors were identified: Employee attributes, Reliability, and Physical features. Employee attributes was found to be the most important factor contributing to tourists overall satisfaction and their return and recommendation intentions. It is suggested that restaurant managers should pay particular attention to the recruitment, selection, and training of employees so as to satisfy their customers. [Article copies available for a fee from The Haworth Document Delivery Service: HAWORTH. address: <getinfo@haworthpressinc.com> Website: < by The Haworth Press, Inc. All rights reserved.] Vincent C. S. Heung is affiliated with the School of Hotel and Tourism Management, The Hong Kong Polytechnic University. M. Y. Wong is affiliated with the School of Business, University of Hong Kong. Hailin Qu is affiliated with the School of Hotel and Restaurant Administration, Oklahoma State University. Address correspondence to: Dr. Vincent C. S. Heung, School of Hotel and Tourism Management, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong ( hmvheung@polyu.edu.hk). Journal of Travel & Tourism Marketing, Vol. 12(2/3) by The Haworth Press, Inc. All rights reserved. 111

3 112 JOURNAL OF TRAVEL & TOURISM MARKETING KEYWORDS. Service quality, customer satisfaction, behavioral intention, airport restaurant INTRODUCTION Marketing researchers, educators and managers have paid particular attention to the area of service quality. At the same time, the understanding of consumers perception of quality of products and services, impact of the perception on consumers shopping behavior and purchase decisions have become critically important to business executives. Although market researchers have made substantial progress in understanding the theoretical relationships among customers assessments of services, other relationships are not well understood. For example, longitudinal rather than cross-sectional analyses are needed to examine the relationships between customer satisfaction, perceived service quality, and behavioral outcomes. Descriptive studies or field experiments are needed to investigate how service features are linked to customer perceptions and cognitive variables (Bolton & Drew, 1994). Companies also need to examine the impact of service quality on customers responses, including post-purchase intentions and signaling behaviors that are potentially favorable or unfavorable to the company (Zeithaml, Berry & Parasuraman, 1996). Oh and Parks (1997) reviewed customer satisfaction, and service quality theories and methodologies in the hospitality industry. They concluded that understanding the sources of customer satisfaction and service quality, and knowing and predicting the consequences of customer satisfaction and service quality for customers future purchase decisions were crucial to industry managers. A number of research studies have been done to measure customers expectations and perceptions in relation to hotel and travel services. However, few have focused on airport restaurants, especially on customers post purchase behavior. Service Quality LITERATURE REVIEW Parasuraman, Zeithaml and Berry (1988) defined perceived service quality as a global judgment, or attitude, relating to the superiority of

4 Heung, Wong, and Qu 113 the service. They link the concept of perceived service quality to the concepts of perceptions and expectations. In other words, perceived quality is viewed as the degree and direction of discrepancy between consumers perceptions and expectations. They concluded that customers assessment of overall service quality is based on the gap between their expectations and their perceptions of performance levels. As a result, the SERVQUAL instrument that measures service quality was developed. The SERVQUAL model is a multiple-attribute scale that measures five distinct dimensions (Tangibles, Reliability, Responsiveness, Assurance and Empathy) that can be viewed as indicators of the construct of perceived service quality. Although the SERVQUAL attributes measured at overall firm s services appear to be good predictors of global quality, it is also possible that the 22 attributes at the encounter level may be good predictors of satisfaction with service encounter (Bitner & Hubbert, 1994). Bojanic & Rosen (1994) applied the SERVQUAL instrument to a chain restaurants in Columbia. The following SERVQUAL dimensions were used: tangibles, responsiveness, knowing the customer, access, reliability, and assurance. Results showed that the restaurant performed well in knowing the customer as the quality gap was the lowest, followed by reliability and assurance. They recommended that the restaurant chain could improve the aspects of reliability and assurance, by implementing total quality management programs such as changes in operations, improved internal marketing, and training. Lee and Hing (1995) assessed applicability of the SERVQUAL instrument to the restaurant sector by measuring, comparing, and contrasting the patron-perceived service quality of a French and a Chinese restaurant in Australia. Results revealed that the patrons highest expectations of service quality were assurance and reliability, and the lowest expectation was related to tangibles. As for patrons perceptions of service quality, French restaurant patrons rated assurance, reliability, and responsiveness the highest, while Chinese restaurant patrons rated tangibles, reliability, and assurance the highest. The authors maintained that service quality is measurable, and that measuring benefits restaurateurs. Stevens, Knutson and Patton (1995) proposed an instrument called DINESERV to assess customers perceptions of restaurant quality. DINESERV was adapted and refined from SERVQUAL and LODGSERV (a measuring scale for hotel service quality) and contained 40 statements (later condensed to 29 statements) on a seven-point scale. DINESERV was used to undertake periodical surveys and to determine changes in perceptions as the result

5 114 JOURNAL OF TRAVEL & TOURISM MARKETING of changes in normative expectations and of service quality delivered. Knutson, Steven & Patton (1995) surveyed a sample of 598 customers from fine dining, casual/theme and quick service restaurants using DINESERV. They concluded that the instrument was a valid and reliable index for measuring consumer expectations and perceptions of service quality in a restaurant. Cronin and Taylor (1992) criticized various elements of the traditional view of the measurement of service quality, claiming that this measurement is the same as the measurement of attitude. They argued that the performance-based approach may actually be more in line with an antecedent/consequence conceptualization: that is, judgments of service quality and satisfaction appear to follow the evaluation of a service provider s performance. They proposed the SERVPERF, a performance-based approach to the measurement of service quality: SQ = (P) Service Quality = (Performance) SERVPERF They found that SERVPERF was more efficient than SERVQUAL with fewer problems in conceptualization and measurement. Thus, they conclude that it is unnecessary to measure customer expectations in service quality research (Cronin & Taylor, 1994). Consumer Satisfaction Conceptually, satisfaction is buyer s comparison of the rewards and costs of the purchase when comparing to anticipated consequences of the product purchase. Operationally, satisfaction is similar to attitude in that it can be assessed as the sum of satisfaction with the various attributes of the product or service (Churchill & Surprenant, 1982). Yi (1990) reviewed and integrated the studies on the definition, measurement, antecedents and consequences of consumer satisfaction. He defined customer satisfaction as the consumer s response to the evaluation of the perceived discrepancy between some comparison standards, such as expectation, and the perceived performance of the product. Customer satisfaction is a summary cognitive and affective reaction to a service incident (Rust & Oliver, 1994). Walker (1995) argued that customer satisfaction is the result of a subjective comparison between expected and perceived attribute levels.

6 Edwards et al. (1994) identified four dimensions of customer s evaluation of satisfaction: general satisfaction measurement, product attribute and benefit, personal motivation measurement, and product and service image. Thus managers need to assess how each customer experiences the product or service in relation to the four dimensions in order to understand customer satisfaction. Similarly, Spreng, MacKenzie and Olshavsky (1996) tested desire as the determinant of customer satisfaction. They proposed that satisfaction arises when customers compare their desires and expectations with their perceptions and the actual performance of a product and service. The results of the study confirmed that desire congruency and information satisfaction were determinants of satisfaction. Spreng and Mackoy (1996) proposed a model that is intended to integrate satisfaction and service quality concepts. They put forward the idea that while service quality is formed by a comparison between ideals and perceptions of performance regarding quality dimensions, satisfaction is a function of the disconfirmation of predictive expectations regarding both quality dimensions and non-quality dimensions. Further, they suggested that perceived service quality is an antecedent to satisfaction. Lam and Heung (1998) studied consumers expectations and satisfaction levels in relation to university foodservice in Hong Kong. The results of the study indicated that food quality, price, hygiene and food variety were the crucial factors that strongly affect customers satisfaction levels. The findings also suggested that there is a positive correlation between customers satisfaction levels and their perceptions of the service providers performance: the higher the perceived level of performance, the higher the level of customer satisfaction. Post-Purchase Behavioral Intention Heung, Wong, and Qu 115 Past studies have presented that there is a positive relationship between customer satisfaction and repurchase intentions (Anderson & Sullivan, 1993; Bearden & Teel, 1983; Cadotte & Turgeon, 1988; Hill 1986; Hunt 1977; Oliver, 1980; Oliver & Swan, 1989). More recent studies have also indicated that service encounter satisfaction and perceived service quality are positively related to behavioral intentions (Bitner, 1990; Bolton & Drew, 1994; Cronin & Taylor, 1992). Bolton and Drew (1991) conducted a study to investigate how changes in service offerings influence customers evaluations of service quality. The study, based on a field experiment with three survey waves,

7 116 JOURNAL OF TRAVEL & TOURISM MARKETING provides insights into how customers change their perceptions of service performance affect their overall evaluations of service quality. Results indicated that favorable disconfirmation experience has a positive effect on customer attitudes, and that current attitudes are influenced by prior attitudes. Furthermore, customer perceptions of current performance have the greatest impact on customer satisfaction and attitudes. Barsky and Labagh (1992) tested the expectancy-disconfirmation paradigm with 100 random subjects via guest comment cards that customer satisfaction was the function of disconfirmation, measured by nine expectations met, and weighted by attribute specific importance. Results showed that customer satisfaction was correlated with willingness to return. Richard, Sundaram, and Allaway (1994) investigated the importance of service quality as a predictor of actual choice behavior as well as the impact of quality on choice of the process and outcome dimensions of service quality. They used consumer data from two home-delivery pizza firms in their study: Domino s and Pizza Hut. The results revealed that consumers used multiple dimensions rather than only one dimension in choice decisions. Thus, no single dimension of service quality captures the complexity of choice while both process and outcome quality were important determinants of choice. The results of this study was later confirmed by Qu (1997) in exploring the important selection attributes for customer selection of Chinese restaurants and identifying the determinants and predicting factors of customers intentions to return. Data were drawn from a sample of 124 customers in three Chinese restaurants in the U.S. Factor analysis found the four dimensions of customer choice: food and environment, which had the largest impact on customer choice, followed by service and courtesy, price and values, location, and advertising and promotion. He concluded that restaurant managers who emphasize only one dimension were not effective in attracting customers, and further recommended that a multidimensional strategy should be adopted. Dube, Renaghan and Miller (1994) believed that a lack of strategic orientation in managing customer satisfaction had led to the failure of a restaurant. They conducted a study in a small, independently owned upscale restaurant using a series of hypothetical dinners with 127 customers. The study aimed to identify the attributes that capture the tangible and intangible aspects of the restaurant experience and the long-term effects of service quality and the relative importance of service attributes on repeat-purchase intention. The results revealed that tasty food, attentive servers, helpful servers, atmosphere, consistent food, menu variety

8 and waiting time were the important service attributes affecting re-purchase intention. They suggested that once the restaurant managers have evaluated the costs of providing customer satisfaction on repeat purchase, they should estimate the benefits of improving the service in order to provide the greatest guest satisfaction per each cost. Study Objectives Heung, Wong, and Qu 117 The present study aims to extend the knowledge of tourists post-purchase behavior in Hong Kong airport restaurants by exploring tourists perceptions, satisfaction and likelihood of returning and making recommendations. The objectives of the study are: (1) to examine tourists perceptions, overall satisfaction levels, likelihood of returning and likelihood of making recommendations in relation to airport restaurant services in Hong Kong, (2) to identify the underlying dimensions of tourists perceptions of airport restaurant services in Hong Kong, and (3) to explore the relative impact of the perception dimensions on tourists overall satisfaction levels, likelihood of returning and likelihood of making recommendations. METHODOLOGY The survey instrument was adapted from DINESERV: a measuring scale of 29 restaurant service quality attributes (Stevens, Knutson & Patton, 1995) that was modified to suit the local situation. Four attributes were added based on the experts opinion, advice from restaurant managers, and faculty at a hotel management program in Hong Kong. Subjects were asked to give scores for the perceived levels of service of 33 restaurant service quality attributes. The scale used was a 10-point rating scale, with 1 = very low level to 10 = very high level. Three specific questions were added to explore tourists overall satisfaction levels, likelihood of returning and likelihood of making recommendations. Overall satisfaction was measured on a 5-point scale, with 1 = very dissatisfied, 5 = very satisfied ; and the scale for return and recommendation intentions was on a 5-point scale with 1 = very unlikely, 5 = very likely. The survey instrument was tested twice with 60 tourists each time to improve its validity and reliability. Some of the wording was changed as a result of the pilot tests. The coefficient alphas in the first and second pilot tests were 0.97 and 0.95 respectively. According to Nunnally, coefficients greater than or equal to 0.50 are generally ac-

9 118 JOURNAL OF TRAVEL & TOURISM MARKETING ceptable and are a good indication of construct reliability (Nunnally, 1967). An Alpha value of at least 0.70 should be considered acceptable as the minimum estimate of reliability for basic research (Churchill, 1979). Hence, the measurement scales of the 33 restaurant service quality attributes achieved a satisfactory level of reliability. Using a systematic sampling method, subjects were interviewed outside four selected restaurants of different types (full-service, casual-dining, quick service and Chinese) at the Hong Kong airport immediately after they had finished their meals. The restaurants were chosen based on their location, price level, type of food, and style of services. The required sample for the selected restaurants and the sampling interval were derived from the estimated total number of customers for each selected restaurant per survey period. A scanning question, on whether the respondent was a tourist, was used to identify the target sample. A total of 770 tourists were approached. Six hundred and sixty-three tourists were interviewed and the questionnaires were completed. After eliminating the unusable questionnaires, 630 were used for the analysis. Descriptive statistics (frequency, means, and standard deviations) were applied to all the questions in order to gain an understanding of the nature of the responses. The study utilized factor analysis to identify the underlying dimensions of tourists perceptions. Further multiple regression was employed to determine the relative impact of each perception dimension on tourists overall satisfaction levels, likelihood of returning and likelihood of making recommendations. RESULTS AND DISCUSSION Demographic Profile of Respondents As shown in Table 1, nearly half (45.2%) of the respondents were female, while male respondents represented a little more than half (54.8%). More than 80% of the respondents were aged between 18 and 45. About 12 % were aged between 46 and 55, and 7.3% were aged 56 or above. Europeans represented the largest group of respondents (23.7%), followed by Japanese (19.8%) and Taiwanese (13.2%). Mainland Chinese people accounted for 12.7% of the respondents. According to the Hong Kong Tourist Association (1997), Mainland China, Taiwan and Japan are the three major markets for Hong Kong tourism. The respondents were therefore fairly representative of the typical tourists to Hong Kong. More than half of the respondents (59%) were edu-

10 Heung, Wong, and Qu 119 TABLE 1. Demographic Profile of Respondents Sex N = 630 % Male Female Age N = 630 % years old years old years old years old years old 65 years old or above Nationality & Country of Residence N = 630 % European Japanese Taiwanese Mainland Chinese American S. E. Asian Australian Others Education Level N = 630 % Primary Secondary Post-secondary University Others Occupation N = 630 % Professional Manager Senior white-collar worker Proprietor Junior white-collar worker Students Blue-collar worker Housewife Retired Others Personal Income (US$ Monthly) N = 630 % Below $500 $501-$1,000 $1,001-$1,500 $1,501-$2,000 $2,001-$2,500 $2,501-$3,000 $3,001-$3,500 $3,501-$4,000 $4,001-$4,500 $4,501-$5,000 $5,001-$5,500 $5,501 or above

11 120 JOURNAL OF TRAVEL & TOURISM MARKETING cated at a university, and about one-quarter (22.4%) had received a post-secondary education. Only 3.5% had only a primary education. The results indicated that 27% of the respondents were professionals, 16% were managers, and 11.9% were senior white-collar workers. Most respondents (42.2%) had a personal monthly income of between US$1,501 and US$3,500. Those who earned less than US$500 per month represented 7.7% of the total number of respondents. Tourists Perceptions of Airport Restaurant Services The mean scores of the 33 restaurant service quality attributes ranged from 7.59 to 6.38 (Table 2). The overall mean score was 7.01, and all except one of the 33 service quality attributes had a mean score of 6.5 or above. This indicates that visitors had quite positive perception about airport restaurants. There were seven attributes that were rated relatively higher than other attributes, with mean scores ranging from 7.59 to The higher-rated perceived service levels were related to Served ordered food accurately (mean score = 7.59) and Accurate guest check (mean score = 7.51). The other seven attributes that were rated relatively lower, with mean scores ranging from 7.21 to 6.38., include Willing to handle special request (mean score = 6.38), and Employees anticipate guests needs (mean score = 6.50) and Attractive surrounding areas. These results suggest that customers had higher perceptions about the Reliability of the service and lower perceptions of Staff skill and knowledge and Attractiveness of the environment. Overall Satisfaction More than 60% (65.7%) of the respondents (n = 414) were satisfied with the services provided by the airport restaurants, 7% (n = 44) were not satisfied, and 27.3% (n = 172) gave neutral responses, indicating that they were neither satisfied nor dissatisfied (Table 3). About eighteen percent (17.8%) of the respondents indicated that they were very satisfied with their dining experience. Only 1.3% were very dissatisfied with the services provided by the airport restaurants. Likelihood of Returning More than half (57%) of the respondents (n = 359) indicated their likelihood of returning to the patronized restaurants during their next

12 Heung, Wong, and Qu 121 TABLE 2. Visitors Perceived Levels of Service for Airport Restaurants N = 630 Attributes Ranking Mean S.D. Served ordered food accurately Accurate guest check Convenient opening hours Served in promised time Prompt and quick service Customers feel safe Clean dining areas Employees shift to maintain quality Well-dressed and clean staff Quickly correct mistakes Well-trained and experienced personnel Comfortable seats Readable menu Dependable in handling service problems Polite and courteous employees Comfortable dining area Clean wash rooms Clean dining equipment Give support to employees Customers feel comfortable and confident Employees who care about guests Can answer guests' questions completely Customers feel special Attractive menu Suitable décor Employees knowledgeable about menu Employees sensitive to guest needs Attractive dining area Put customers' best interests at heart Employees are sympathetic and confident Attractive surrounding areas Employees anticipate guests' needs Willing to handle special requests Overall Mean/S.D Note: Scale 1-10, 1 = Very low, 10 = Very high

13 122 JOURNAL OF TRAVEL & TOURISM MARKETING TABLE 3. Tourists Overall Satisfaction Levels (n = 630) Attributes Frequency Percentage Cum Percentage Very Dissatisfied Dissatisfied Average Satisfied Very Satisfied Scale: 1-5, 1=Very dissatisfied, 5=Very satisfied trip to Hong Kong, and one-fifth (19.9%, n = 125) of them indicated the opposite (Table 4). The rest (23.2%, n = 146) gave neutral responses. The overall mean score of 3.60 indicated that respondents were likely to return to the same restaurants during a subsequent visit to Hong Kong. Likelihood of Making Recommendations About 70% (n = 431) of the respondents gave positive responses in terms of their likelihood of recommending the patronized restaurants to other tourists (Table 5). Almost one-fifth (19.7%, n = 124) of them gave negative responses and the remainder (11.9%, n = 75) gave neutral responses to this question. The mean score of 3.76 indicated that the respondents, in general, were likely to recommend the patronized restaurants to other tourists. Underlying Dimensions of Tourists Perceived Levels of Service The 33 restaurant service quality attributes on tourists perceived levels of service were factor-analyzed, using principal component analysis with orthogonal VARIMAX rotation, to identify underlying dimensions or factors. The appropriateness of using factor analysis was assessed. The extraction of the factors and the variables were based on the eigenvalues and the factor loadings of the variables. Only factors with an eigenvalue larger than one and attributes with loading > 0.50 were considered. From the VARIMAX rotated factor matrix, three factors, representing 66.3% of the explained variance, were extracted from the original 33 variables. Three service quality factors with the 32 variables for perceived levels were loaded most heavily (loading > 0.50) on them. The VARIMAX process produced a clear factor structure with relatively higher loadings on the appropriate factors. The variables with

14 Heung, Wong, and Qu 123 TABLE 4. Tourists Likelihood of Returning (n = 630) Attributes Frequency Percentage Cum Percentage Very Unlikely Unlikely Maybe Likely Very likely Scale: 1-5, 1=Very unlikely, 5=Very likely TABLE 5. Tourists Likelihood of Making a Recommendation (n = 630) Attributes Frequency Percentage Cum Percentage Very Unlikely Unlikely Maybe Likely Very Likely Scale: 1-5, 1=Very unlikely, 5=Very likely higher loadings signaled the correlation of the variables with the factors on which they were loaded. One of the variables from Factor 3, Readable menu, however, was loaded less than 0.5. In other words, this variable was not significant enough according to the mentioned criteria, hence it was not included in the analysis. Table 6 illustrates the results of this VARIMAX process. Reliability analysis (Cronbach Alpha) was calculated to test the reliability and internal consistency of each factor. The results show that the alpha coefficients for the three factors were acceptable ranging from 0.96 to 0.92-well above the acceptable reliability value of 0.50 (Nunnally, 1967). The three perceived service quality factors identified by VARIMAX as reliable and consistent with an Eigenvalue greater than one are as follows. Factor One with fourteen attributes explained more than half (54.9%) of the variance in the data, with an Eigenvalue of and an alpha coefficient of This factor was mostly concerned with employees knowledge and skills in the service delivery process,

15 124 JOURNAL OF TRAVEL & TOURISM MARKETING TABLE 6. Factor Analysis Results of Tourists Perceived Levels of Service Desired Levels Attributes 1 Factor Loading Communalities No of Attributes EV 2 Pct of Variance 3 Factor Mean 4 Factor 1: Employee Attributes ( = ) (1.81) Customers feel special Employees sensitive to guests' needs Employees anticipate guests' needs Employees who care about guests Put customers' best interests at heart Customers feel comfortable and confident Employees knowledgeable about menu Employees are sympathetic and confident Can answer guests' questions completely Polite and courteous employees Give support to employees Willing to handle special requests Well-trained and experienced personnel Customers feel safe Factor 2: Reliability (0.9237) (1.66) Served ordered food accurately Served in promised time Accurate guest check Convenient opening hours Employees shift to maintain quality Quickly correct mistakes Prompt and quick service Dependable in handling service problems Factor 3: Physical Features (0.9262) (1.75) Attractive dining area Attractive surrounding areas Suitable décor Well-dressed and clean staff Clean dining equipment Comfortable dining area Clean wash rooms Clean dining area Comfortable seats Attractive menu Restaurant service quality attributes 2. EV: Eigenvalue % of Cumulative Variance Explained 4. Mean Scale: 1 = very low, 10 = very high Standard Deviations are in parentheses 5. Cronbach's Alpha

16 Heung, Wong, and Qu 125 and was named as the Employee Attributes factor. The factor included attributes such as Employees sensitive to guests needs, Employees anticipate guests needs, and Employees who care about guests. Factor Two, called the Reliability factor, contained eight attributes and accounted for 6.2% of the variance, with an Eigenvalue of 1.98 and an alpha coefficient of This factor regarding reliable service included Served ordered food accurately, Served in promised time, and Accurate guest check. Factor Three, called the Physical Attributes factor with 10 attributes, accounted for 5.2% of the variance, with an Eigenvalue of 1.66 and an alpha coefficient of This factor include attributes associated with the tangible quality of the restaurant: Attractive dining area, Attractive surrounding areas, and Suitable décor. It is worth noting that the five-factor structure identified by other researchers (e.g., Parasuraman et al, 1988) was not revealed in the present study. This is not surprising to point out that the dimensionality of service quality may depend on the type of services (Babakus & Boller, 1992). Murray (1992) identified three dimensions of customer satisfaction with family restaurant services, namely: Human Interaction, Food and Atmosphere. Johns & Tyas (1996) found that catering services did not conform to the five-factor structure model, and they grouped service quality attributes into three distinct dimensions (factors): Food, Service Staff, and Efficiency. Determinant Factors (Dimensions) in Contributing to Tourists Overall Satisfaction Levels The three orthogonal factors (Employee Attributes, Reliability and Physical Features) were used in a multiple regression analysis to test whether the underlying dimensions of tourists restaurant perceptions impacted significantly on tourists overall satisfaction levels, and to investigate the relative impact of the perception dimensions. The equation for the tourists overall satisfaction level, based on the perception dimensions derived from regression analysis of the study, is expressed as the following: Y S = b o +B 1 X 1 +B 2 X 2 +B 3 X 3

17 126 JOURNAL OF TRAVEL & TOURISM MARKETING where, Y S : Tourists Overall Satisfaction Level; β 0 : Constant (Coefficient of Intercept); X 1 : Factor 1 (Employee attributes); X 2 : Factor 2 (Reliability); X 3 : Factor 3 (Physical features); B 1, B 3 : Regression Coefficients of Factor 1 to Factor 3. Table 7 shows the results of the regression analysis. In order to predict the Goodness-of-Fit of the regression model, the multiple correlation coefficient (R), coefficient of determination (R 2 ) and F-ratio were examined. First, the R of independent variables (three perception dimensions, or X 1 to X 3 ) on the dependent variable (tourists overall satisfaction level, or Y S ) was 0.84, which shows that the tourists had positive and very high overall satisfaction levels with the three perception dimensions. Second, the R 2 was 0.70, suggesting that more than 70% of the variation of the tourists overall satisfaction was explained by the three perception dimensions. Lastly, the F-ratio explains whether or not the results of the regression model could have occurred by chance, had a significant value of (significant at 0.000). The regression model is said to have achieved a very satisfactory level of Goodness-of-Fit in predicting the variance of the tourists overall satisfaction in relation to the three perception dimensions, as measured by the above-mentioned R, R 2 and F-ratio. In other words, at least one of the three perception dimensions was important in contributing to tourists overall satisfaction levels with airport restaurant service quality in Hong Kong. Results showed that Factor 1 (Employee Attributes, beta coefficient = 0.64, Sig. =.000) was the most important underlying dimension affecting the tourists dining satisfaction followed by Factor 2 (Reliability, beta coefficient = 0.39, Sig. =.000). The third most important factor was Factor 3 (Physical Features, beta coefficient = 0.351, Sig. =.000) that had comparatively less influence on customers satisfaction. The results compared favorably with the findings of previous studies on restaurant service quality and customer satisfaction. For instance, Cadotte and Turgeon (1988) found Quality of service was ranked as the most, Food quality was second, and Helpful attitude of employees was

18 Heung, Wong, and Qu 127 TABLE 7. Regression Results of Tourists Overall Satisfaction Levels Based on the Perception Dimensions Dependent Variable: Tourists' overall satisfaction with dining in Hong Kong airport restaurants (used as a surrogate indicator). Independent Variables: Three orthogonal factors representing the components of perceived quality of airport restaurant service: Employee's attributes, (Factor 1), Reliability (Factor 2) and Physical features (Factor 3). Prediction: Goodness-of-Fit Multiple R R Square Adjusted R Square Standard Error Analysis of Variance Regression Residual F = Degree of Freedom Sig. F =.000 Sum of Squares Mean Square Durbin-Watson 1.84 Explanation: Variables in the Equation Independent Variable Employee's attributes Factor 1 Reliability Factor 2 Physical features Factor 3 Constant Unstandardized Coefficients (B) Standardized Coefficients (Beta) Collinearity Diagnostics Tolerance Variable Inflation Factor (VIF) Employee's attributes Factor 1 Reliability Factor 2 Physical features Factor 3 Constant T-value Condition Index Sig third important factor in determining service quality while Murray (1992) reported that Human Interaction was first, Food was second and Atmosphere was ranked third in determining the service quality (Murray, 1992). Bojanic and Rosen s (1994) concluded the most significant dimension for quality service was Knowing the customer, followed by Reliability and Assurance. Determinant Factors (Dimensions) in Contributing to Tourists Likelihood of Returning The equation for the tourists likelihood of returning, based on the perception dimensions derived from regression analysis in this study, is expressed in the following equation: Y ret = β 0 +B 1 X 1 +B 2 X 2 +B 3 X 3

19 128 JOURNAL OF TRAVEL & TOURISM MARKETING where, Y ret : Likelihood of returning; β 0 : Constant (Coefficient of Intercept); X 1 : Factor 1 (Employee Attributes); X 2 : Factor 2 (Reliability); X 3 : Factor 3 (Physical Features); B1,...B3 : Regression Coefficients of Factor 1 to Factor 3 Table 8 shows the results of the regression analysis. In order to predict the Goodness-of-Fit of the regression model, the multiple correlation coefficient (R), coefficient of determination (R 2 ) and F-ratio were examined. First, the R of independent variables (three perception dimensions, or X 1 to X 3 ) on the dependent variable (tourists likelihood of returning, or Y ret ) was 0.64, which shows that the tourists had quite a high likelihood of returning based on the three perception dimensions. Second, the R 2 was 0.41, suggesting that about 41% of the variation of the tourists likelihood of returning was explained by the same dimensions. Last, the F-ratio, which explains whether or not the results of the regression model could have occurred by chance, had a significant value of (significant at 0.000). The regression model is said to have achieved a quite satisfactory level of Goodness-of-Fit in predicting the variance of the tourists likelihood of returning in relation to the three perception dimensions, as measured by the above-mentioned R, R 2 and F-ratio. Factor 1 (Employee Attributes, beta coefficient = 0.50, Sig. =.000) was found to be the most important underlying dimension affecting the tourists likelihood of returning to the same restaurant. This was followed by Factor 3 (Physical Features, beta coefficient = 0.321, Sig. =.000). The third significant factor was Factor 2 (Reliability, beta coefficient = 0.24, Sig. =.000) which had comparatively less influence on customers return intentions. Though conducted in different settings, these results do not conform with the findings of Qu s study on the determinant factors and choice intentions for Chinese restaurants, where Food and Environment was the most important dimension, followed

20 Heung, Wong, and Qu 129 TABLE 8. Regression Results of Tourists Likelihood of Returning Based on the Perception Dimensions Dependent Variable: Tourists' likelihood of returning to Hong Kong airport restaurants (used as a surrogate indicator). Independent Variables: Three orthogonal factors representing the components of perceived quality of airport restaurant service: Employee's attributes, (Factor 1), Reliability (Factor 2) and Physical features (Factor 3). Prediction: Goodness-of-Fit Multiple R R Square Adjusted R Square Standard Error Analysis of Variance Regression Residual F = Degree of Freedom Sig. F =.000 Sum of Squares Mean Square Durbin-Watson 1.72 Explanation: Variables in the Equation Independent Variable Employee's attributes Factor 1 Reliability Factor 2 Physical features Factor 3 Constant Unstandardized Coefficients (B) Standardized Coefficients (Beta) Collinearity Diagnostics Tolerance Variable Inflation Factor (VIF) Employee's attributes Factor 1 Reliability Factor 2 Physical features Factor 3 Constant T-value Condition Index Sig by Service and Courtesy, Price and Value, and Location, Advertising and Promotion (Qu, 1997). This may mean that airport restaurants could have different sets of factors affecting customers likelihood of returning. Determinant Factors (Dimensions) Contributing to Tourists Likelihood of Making Recommendations The equation for the tourists likelihood of making recommendations, based on the perception dimensions derived from regression analysis in this study, is expressed in the following equation: Y rec = β 0 +B 1 X 1 +B 2 X 2 +B 3 X 3

21 130 JOURNAL OF TRAVEL & TOURISM MARKETING where, Y rec : Likelihood of making recommendations; β 0 : Constant (Coefficient of Intercept); X 1 : Factor 1 (Employee attributes); X 2 : Factor 2 (Reliability); X 3 : Factor 3 (Physical features); B 1,... B 3 : Regression Coefficients of Factor 1 to Factor 3. Table 9 shows the results of the regression analysis. In order to predict the Goodness-of-Fit of the regression model, the multiple correlation coefficient (R), coefficient of determination (R 2 ) and F-ratio were examined. First, the R of independent variables (three perception dimensions, or X 1 to X 3 ) on the dependent variable (tourists likelihood of making recommendations, or Y) was 0.75, which shows that the tourists had a high likelihood of making recommendations based on the three perception dimensions. Second, the R 2 was 0.57, suggesting that about 57% of the variation of the tourists likelihood of making recommendations is explained by these dimensions. Lastly, the F-ratio, which explains whether or not the results of the regression model could have occurred by chance, had a significant value of (sig. = 0.000). The regression model is said to have achieved a satisfactory level of Goodness-of-Fit in predicting the variance of the tourists likelihood of making recommendations in relation to the three perception dimensions, as measured by the above-mentioned R, R 2 and F-ratio. Results showed that Factor 1 (Employee attributes, beta coefficient = 0.582, Sig. =.000) was the most important underlying dimension affecting the tourists likelihood of recommending the restaurant to others. Factor 3 (Physical Features, beta coefficient = 0.369, Sig. =.000) came in second. The next most important factor was Factor 2 (Reliability, beta coefficient = 0.297, Sig. =.000), which had comparatively less influence on tourists likelihood of recommending the restaurant. The results confirmed the findings of the study by Getty and Thompson (1994), in which the service quality factors had a significant impact on customers intent to make recommendations.

22 Heung, Wong, and Qu 131 TABLE 9. Regression Results of Tourists Likelihood of Making a Recommendation Based on the Perception Dimensions Dependent Variable: Tourists' likelihood of recommending the airport restaurants (used as a surrogate indicator). Independent Variables: Three orthogonal factors representing the components of perceived quality of airport restaurant service: Employee's attributes, (Factor 1), Reliability (Factor 2) and Physical features (Factor 3). Prediction: Goodness-of-Fit Multiple R R Square Adjusted R Square Standard Error Analysis of Variance Regression Residual F = Degree of Freedom Sig. F =.000 Sum of Squares Mean Square Durbin-Watson 1.73 Explanation: Variables in the Equation Independent Variable Employee's attributes Factor 1 Reliability Factor 2 Physical features Factor 3 Constant Unstandardized Coefficients (B) Standardized Coefficients (Beta) Collinearity Diagnostics Tolerance Variable Inflation Factor (VIF) Employee's attributes Factor 1 Reliability Factor 2 Physical features Factor 3 Constant T-value Condition Index Sig It should be pointed out that about 4% of the respondents (n = 23) indicated that they were unlikely to returning to the same restaurant even though they had high service perceptions and satisfaction. This phenomenon can be explained as follows. As some tourists may have no future plans to return to Hong Kong, or may wish to try other restaurants, they would probably give a negative response to the likelihood of returning question. This might contribute to the relatively poorer predictive power of the perception dimensions on the likelihood of returning compared with the overall satisfaction and the likelihood of making recommendations. CONCLUSIONS AND IMPLICATIONS The results of the study confirmed previous research studies (Hunt 1977; Churchill 1979; Oliver 1980; Hill 1986; Cadotte & Turgeon, 1988;

23 132 JOURNAL OF TRAVEL & TOURISM MARKETING Yi 1990; Barsky & Labagh, 1992; Murray 1992; Rust & Oliver, 1994; Bitner & Hubbert, 1994; Spreng, MacKenize & Olshavsky 1996, Lam & Heung, 1998) that perceived service quality is positively related to customer satisfaction, likelihood of returning and likelihood of making recommendations. It is of critical importance that restaurateurs maintain the service quality standards by managing customers perceptions. For example, the managers of the airport restaurants should ensure that staff training programs are geared to provide the standards that meet customers service expectations. The findings of this study indicate that customers had low perceptions on employees skills and knowledge, such as Willing to handle special request and Employees anticipate guests needs. Employee Attributes was found to be the most important dimension in contributing to overall satisfaction, likelihood of returning and likelihood of making recommendations. Employees Attributes dimension includes attributes such as Well-trained and experienced personnel, Willing to handle special requests, Polite and courteous employee, Employees are sympathetic and confident, Employees who care about guests, Employees knowledgeable about menu, Employees sensitive to guests needs and Employees anticipate guests needs. Since employees knowledge, skills and attitudes have a significant impact on service quality and customer satisfaction, airport restaurateurs should pay particular attention to the recruitment, selection and training of their employees. As service staff is an integral part of the restaurant product and services, it is essential to standardize the quality of staff services in order to maintain consistent services. Also, it is critical that firms in the hospitality industry undertake regular analyses in those areas to understand the consumer evaluation process and to manage customer expectations (Bojanic & Rosen, 1994). Although this study focused on restaurants at Hong Kong airport, the results also have implications for other restaurants in hotels, convention centers, and theme parks that catering overseas tourists. Managers of these operations may find the results useful, in that they offer some broad guidelines for restaurant planning, staff training, marketing, and promotion. Study Limitations and Future Research The present study explores tourists general perceptions and satisfaction of four different types of airport restaurants in Hong Kong: full-service, casual dining, quick service and Chinese cuisine. There are some limitations in applying the results to a specific type of restaurants. The

24 Heung, Wong, and Qu 133 study only takes into account those tourists who patronized the selected restaurants during the survey periods, therefore, the results may not apply to tourists who had their meals outside the periods and tourists who did not dine at the selected airport restaurants. The interviewers who were fluent in English, Chinese and Japanese conducted the study. However, visitors who did not speak any of the three chosen languages in the target samples were not included in this study. Future studies could examine the restaurant service perceptions and satisfaction of customers in relation to a particular type of restaurant, with a set of restaurant service attributes specially developed for that particular type of restaurant. The results of such studies could help to establish determinant attributes of service quality and satisfaction for each type of airport restaurants. Since this study focused on Hong Kong restaurants, future research could explore restaurant quality and customer satisfaction at airports in different countries around the world. The results of such studies could provide useful information in understanding tourists dining behavior in different places and hence help marketers to formulate appropriate marketing and service strategies for international market. REFERENCES Anderdon, E.W., & Sullivian, M.(1993). The antecedents and consequences of customer satisfaction for firms. Marketing Science, 12, Babakus, E., & Boller, G.W. (1992). An empirical assessment of the SERVQUAL scale. Journal of Business Research, 24, Barsky, J.D. & Labagh, R. (1992). A strategy for customer satisfaction. The Cornell H.R.A. Quarterly, 33(5), Bearden, W. O., Teel, J. E. (1983). Selected determinants of consumer satisfaction and complaints reports. Journal of Marketing Research, 20, Bitner, M.J. (1990). Evaluating service encounters: The effects of physical surroundings and employee responses. Journal of Marketing, 54, Bitner, Mary Jo & Hubbert, Amy R. (1994). Encounter satisfaction versus overall satisfaction versus quality In Rust, R. T. & Oliver, R. L (ed.) Service quality: New directions in theory and practice, California: Sage Publications, Bojanic, D.C. & Rosen, L.D. (1994). Measuring service quality in restaurants: An application of the SERVQUAL instrument. Hospitality Research Journal, 18(1), Bolton, R.N. & Drew, J.H. (1991). A longitude analysis of the impact of service changes on customer attitudes. Journal of Marketing, 55 (January), 1-9. Bolton, R.N. & Drew, J. H. (1994). Linking customer satisfaction to service operations and outcomes. In Rust, R. T. & Oliver, R. L (ed.) Service quality: New directions in theory and practice. California: Sage Publications,