Service Quality in Restaurants: a case study in a Portuguese resort

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1 Service Quality in Restaurants: a case study in a Portuguese resort Vera Patrício 1, Rogério Puga Leal 2 and Zulema Lopes Pereira 2 1 Rua Nova da Vila 2, ALVOR, Portugal 2 Department of Mechanical and Industrial Engineering, Faculty of Sciences and Technology, Universidade Nova de Lisboa, Quinta da Torre, CAPARICA, Portugal. Abstract The work presented in this paper focuses on customer assessment of restaurants. The research was developed in a Portuguese resort and more than 300 customers were asked to fill a questionnaire based on SERVQUAL, which is one of the most popular instruments to ascertain service quality. Two restaurants representing different segments were studied. Data analysis was performed to identify and compare dimensions of customer satisfaction and critical factors within each segment. As SERVQUAL is a generic model for service quality, it seemed also important to discuss its applicability to restaurant services. The results suggest that the structure associated with SERVQUAL is not fully replicated in these activities. A regression model was also developed so that the importance of the outcomes could be compared and suggestions for quality improvement could be proposed. Introduction It has been well recognised the crucial role played by service organisations in developed countries, being quality and corresponding customer satisfaction essential to increase the effectiveness, efficiency and competitiveness of these organisations (Leal and Pereira, 2003). Empirical research on quality improvement in service organisations has been growing in recent years but it still lags behind the developments observed in manufacturing. It has been generally acknowledged that more research is needed in the field, especially with regard to the application of quantitative methods that can help managers in the decision making process. Tourism industry has become not only a driver for economic progress of many countries but also a vehicle to approximate people and cultures. Various policies have been issued and several initiatives aimed at improving tourism quality have also been fostered and implemented by private and public organisations all over the world. Despite these facts, both the tourists and the public authorities consider that the level of quality has to be enhanced rapidly in all tourism activities, catering included. In Portugal the services associated to tourism assume vital importance. Therefore, it seemed quite useful to develop an exploratory study to assess and characterise the service provided within the restaurant framework. Data Collection Two restaurants of different segments were selected to perform the study. Restaurant A has 60 seated places and delivers complete meals in a formal environment. By contrast, Restaurant B is targeted to serve light meals in a very informal atmosphere and has 70 seated places. A convenience sample of 150 customers (75 female and 75 male) was used for each restaurant. All respondents were Portuguese citizens and the questionnaires were collected from December 2002 to April 2003.

2 The Servqual instrument (original version by Parasuraman et al., 1988) was employed to assess customer expectations and perceptions. This instrument is constituted by 22 items that integrate the following five dimensions of service quality (Zeithaml et al., 1990): 1. Tangibles (four items) 1. Restaurant has modern-looking equipment 2. The physical facilities are visually appealing 3. Employees are neat-appearing 4. Materials associated with the service are visually appealing 2. Reliability (five items) 5. When the restaurant promises to do something by a certain time, it does so 6. When a customer has a problem, the restaurant shows a sincere interest in solving it 7. The restaurant performs the service right the first time 8. Services are provided at the time the restaurant promises to do so 9. The records are error-free 3. Responsiveness (four items) 10. Employees inform the customers when services will be performed 11. Employees give prompt service to customers 12. Employees are always willing to help customers 13. Employees are never too busy to respond to customers requests 4. Assurance (four items) 14. The behaviour of employees instil confidence in customers 15. Customers feel safe in their transactions 16. Employees are consistently courteous 17. Employees have the knowledge to answer customers questions 5. Empathy (five items) 18. Restaurant gives customer individual attention 19. Employees give customers personal attention 20. Restaurant understands specifics needs of its customers 21. Restaurant has customer s interests at heart 22. Operating hours are convenient to all customers The questionnaire contained two sections, namely an expectations section consisting of 22 generic statements about restaurants and a matching set of company-specific statements to assess perceptions. Perceived service quality is assumed to be a comparison between expected service and perceived service, i.e.: Perceived service quality = perceived service (P) expected service(e) Therefore, 22 scores of (P-E) were obtained for each customer. An extra item about customer s global satisfaction was added to the perceptions section. Exploratory Data Analysis As Servqual is the most popular model in service quality research and applications, it seemed important to assess how well the presented Servqual structure could be replicated under the framework of Portuguese restaurants. To perform the comparison, an exploratory factor analysis was

3 conducted, where the input variables were the score differences (perceptions-expectations) for each item of the questionnaire. Factor Analysis is included among the so-called interdependency techniques. In this sort of techniques there is not a distinction between dependent and independent variables, being all the variables analysed together. Factor Analysis can be used to reach several objectives. Two of the most common, that can be combined, are those connected with the identification of some underlying structure to the data and the data reduction itself. First of all, it is important to decide whether or not Factor Analysis is an appropriate technique to analyse the available data. The KMO (Kaiser-Meyer-Olkin) measure of sampling adequacy was computed and a test of sphericity was carried out for each segment. Tables 1 and 2 present these results and reveal that Factor Analysis can be fruitfully applied. Kaiser-Meyer-Olkin Measure of Sampling Adequacy.,707 Kaiser-Meyer-Olkin Measure of Sampling Adequacy.,622 Bartlett's Test of Sphericity Approx. Chi-Square df Sig. 1882, ,000 Table 1. KMO and test of sphericity for segment A Bartlett's Test of Approx. Chi-Square Sphericity df Sig. Table 2. KMO and test of sphericity for segment B 720, ,000 The Principal Components Analysis and the Kaiser criterion were used, respectively, for factor extraction and factor retention. Seven factors (principal components) were extracted for segment A, while the segment B produced eight factors. So, the first conclusion is that there is a difference between the Servqual 5-factor structure and the factors structures obtained for the two restaurants. However, it is worth referring that some other authors defend the existence of seven to eight factors in service quality (e.g. Carman, 1990). The communalities for the variables included in the study are presented in Tables 3 and 4. The total variance explained by the solution achieved for segment A is 75%, while for segment B is 64%, despite the higher number of factors extracted for this segment. PE1 PE2 PE3 PE4 PE5 PE7 PE8 PE9 PE10 PE11 PE12 PE13 PE14 PE15 PE16 PE19 PE21 Initial Extraction 1,000,777 1,000,766 1,000,762 1,000,757 1,000,749 1,000,792 1,000,648 1,000,796 1,000,622 1,000,706 1,000,682 1,000,794 1,000,760 1,000,835 1,000,687 1,000,604 1,000,672 1,000,937 1,000,943 1,000,655 1,000,729 1,000,814 Table 3. Communalities for segment A Initial Extraction PE1 1,000,734 PE2 1,000,723 PE3 1,000,649 PE4 1,000,584 PE5 1,000,695 1,000,728 PE7 1,000,555 PE8 1,000,614 PE9 1,000,631 PE10 1,000,630 PE11 1,000,555 PE12 1,000,425 PE13 1,000,671 PE14 1,000,676 PE15 PE16 PE19 PE21 1,000,745 1,000,803 1,000,419 1,000,734 1,000,610 1,000,777 1,000,585 1,000,518 Table 4. Communalities for segment b

4 Table 5 presents the rotated component matrix for segment A. According to Hair et al. (1995), only factor loadings above 0,500 can be considered significant for the sample size considered in the study. Although a meaningful structure appears to emerge it must be noticed that some variables are not easy to allocate to a single factor (e.g. variables 21 and 9). PE14 PE15 PE7 PE16 PE5 PE10 PE4 PE8 PE9 PE1 PE2 PE3 PE19 PE13 PE12 PE11 PE21 Component ,819,048,334,071,005,040 -,027,747,276 -,074,219,202,321,065,739,016,002,067,137,066,337,718,188,281,079,102,006 -,030,677,055 -,057,008 -,101,165 -,320,675,235,116,193 -,264,308 -,150,601 -,118 -,281,173,287 -,292,233,120,846 -,187,031,125,120 -,132,272,711,273,107 -,214,060,206,439,708,137,155 -,029,229 -,069,143 -,523,110,106,227,503,013 -,019,125,831,056,215 -,052 -,137,129 -,101,765,164,088 -,122,324,306 -,055,698 -,023 -,153,375 -,116,103,045,095,954,012 -,050,058,226,041,069,937,016,018,083 -,005 -,279,067 -,043,804,110,132,191,278 -,098,047,657,469,127,074,000,410,075,655 -,205 -,178,169,162 -,032 -,075,036,780,037 -,052,023 -,001,047 -,016,030,805,103 -,544 -,039,186,200,052,585 Table 5. Rotated Component Matrix for segment A Table 6 presents the rotated component matrix for segment B. The allocation of some variables to factors is not immediate too (e.g. variables 5 and 12). PE10 PE8 PE4 PE14 PE12 PE5 PE9 PE11 PE7 PE1 PE2 PE16 PE15 PE13 PE21 PE19 PE3 Component ,763,038,063,061,112,159,008 -,042,755 -,062 -,015,146,066 -,117 -,019,007,628,007,194,102 -,119 -,345 -,034 -,082,607,417 -,159 -,179,123,130 -,191,088,433,346,088 -,139,048,218,108,171,385,379 -,216,357,306 -,262,186,179,198,695,026,037,188 -,322,252 -,033 -,053,681 -,187,257,178,084 -,118 -,103 -,028,571,363 -,105 -,160,215,042,110,160,501,232,459 -,039,107,012,017,018 -,094,818,151,060 -,136,072,075,145,181,721 -,351,080,096,034 -,092,112,092 -,116,682 -,010 -,039 -,020,127 -,007,016,039,619,100,048,026 -,145,126 -,020,000,344,815,035 -,042 -,042,069,183,121 -,174,787,128,142,078,112 -,005 -,142 -,052,043,735,304 -,035 -,176,143,209,230,205,570 -,051,261 -,035 -,002 -,036,026 -,089,030,849 -,013 -,041,089,172 -,015,277,216,669 -,012,010,067,075,040,064,143 -,069,858 -,009,313,372,246,126,238 -,157 -,506 Table 6. Rotated Component Matrix

5 Table 7 presents a comparison of the variables allocated to each factor in each segment. Segment A Segment B Factor 1 PE5,, PE7, PE10, PE14, PE15, PE16 PE4,PE5, PE8, PE10, PE12, PE14 Factor 2 PE4, PE8,, PE7, PE9, PE11 Factor 3 PE1, PE2, PE3 PE1, PE2 Factor 4, PE19, Factor 5 PE11, PE12, PE13 PE15, PE16 Factor 6, PE9 PE13, PE21 Factor 7, PE21, PE19 Factor 8, PE3 Table 7. Comparison of structures for segments A and B The structure obtained for segment B cannot be considered meaningful, since the allocation of variables does not seem to follow a logical pattern. Furthermore, as mentioned before, the explained variance is below 65%, despite the extraction of 8 factors. Therefore, further investigation on sampling and data acquisition must be considered for this segment and the environment for questionnaires administration may need to be improved. On the contrary, the results for segment A are globally meaningful. Factors 4 and 7 include the variables that belong to the Empathy dimension of Servqual. However, it seems that customers tend to consider separately the individual attention, which resembles logical due to the type of service considered. Factor 5 generically includes those variables that Servqual assumes to represent the Responsiveness dimension. The only variable excluded is PE10 that is considered by restaurant customers as a variable more related to reliability. In fact, this variable is considered together with variables 5, 6 and 7 in Factor 1. This result can be considered logical, as PE10 represents to a large extent a reliability characteristic. Factor 1 also includes variables 14 and 15, which reflect confidence and safety, i.e., issues strongly related to reliability. Factor 3 includes the variables associated to Tangibles in Servqual, with the exception of variable 4. Factor 2 includes variables 8 and 22. It is not a surprise that they are grouped together, since both variables are related to time characteristics. This factor also includes, with a slightly lower factor loading, variable 8. However, it is hard to find a logical explanation for that. Finally, Factor 6 includes variables 17 and 9. Variable 9 could be included either in Factor 6 or 2, although it makes more sense its inclusion in Factor 6. In fact, variables 9 and 17 are both related to the technical skills of the employees. Summarising, the proposed structure for service quality in restaurants is displayed in Table 8.

6 Name of the factor Surrogate Variable Factor 1 Reliability Factor 2 Time Convenience Factor 3 Tangibles PE1 Factor 4 Customization Factor 5 Responsiveness PE13 Factor 6 Technical Skills Factor 7 Empathy Table 8. Structure for service quality in restaurants Definition of Priorities It seems quite useful to define strategic priorities based on the importance of the several factors implicit in the customer s answers. To achieve this objective, a multiple regression model is developed. The global satisfaction of customers (extra item added to questionnaire) is the dependent variable and the factors are the independent variables. Each factor is represented by a surrogate representative variable (Table 8), which is the variable with the highest factor loading for that particular factor (Hair et al., 1995). The standardised regression coefficients might constitute a good approach to the weight given by customers to the several factors. The backward procedure is applied, leading to the exclusion of variable PE1 in the first model and of variable PE13 in the second model. No other variable was excluded. Table 9 shows the evolution of R-Square. The final value is close to 50%, which is considered to be very interesting for this type of study. Table 10 shows the regression coefficients for the final model. Model Adjusted R R Square R Square,715,511,487,710,503,483,704,495,478 Table 9. Evolution of R Square Model 3 (Constant) Unstandardized Coefficients Standardized Coefficients B Std. Error Beta t Sig. 5,760,079 73,039,000,299,041,445 7,255,000,102,017,369 6,112,000,118,042,173 2,836,005,102,044,143 2,341,021,052,021,149 2,496,014 Table 10. Regression Coefficients A relative weight for each factor (Table 11) can be calculated from the standardised coefficients.

7 Factor Relative Weight (%) Reliability 34,8 Time Convenience 28,9 Customization 13,5 Technical Skills 11,1 Empathy 11,7 Table 11. Relative weight of the factors The highest importance attributed to Reliability is consistent with the findings of several other authors, including Parasuraman et al. (1991). However, the dimension Time Convenience, which reflects the operating hours of the restaurant as well as its ability to provide the service on time, also reveals a very high weight. Taking into account the type of service, this fact is not surprising and leads to the conclusion that an enlargement of the operating hours might have a very positive impact on customer satisfaction. Curiously, the variable representing the Tangibles factor was not significant in the regression analysis. Although further research is needed, one can not exclude the possibility of Tangibles being a sort of basic characteristics under Kano s perspective. Conclusions The Servqual model constitutes a milestone in service quality research. However, as it is a general model, it is interesting to study its application under several service environments. The study presented in this article is simply exploratory and uses a convenience sample. Therefore, it is recognised that further research is needed to confirm the current results. Despite the limitations of the study, it seems clear that the Servqual structure is not fully replicated in the restaurants environment. In fact, the Factor Analysis with the Kaiser criterion produced a final structure with seven factors, instead of the five Servqual dimensions. However, the achieved structure is consistent with several others that are available in the literature and suggest a higher number of service quality dimensions. It is quite peculiar to notice the merge in one single factor of those items that Servqual includes in the dimensions Reliability and Assurance. Therefore, one can conclude that restaurant s customers do not perceive as different those issues. On the other hand, individual attention given to customers emerged as a single factor. This reflects the modern trend to service customization and should constitute a clear strategic option for the tourism industry. Another important trend is the necessity to increase service availability. Effectively, time convenience proved to be a significant factor and it is clear that customers give great importance to it. The non-significance of tangibles is somehow surprising. Although further research is needed, it appears that tangibles are a sort of basic characteristics, i.e., only its lack of adequacy is noticed. As a general conclusion it can be said that professional education of the employees, both in technical and relational issues, as well as the enlargement of operating hours, must constitute strategic options for the restaurant industry.

8 References Carman, James M.(1990) - Consumer Perceptions of Service Quality: An Assessment of the SERVQUAL Dimensions, Journal of Retailing; Vol. 66, No. 1; Spring 1990, pp Hair, Joseph, Anderson, Rolph, Tatham, Ronald, Black, William (1995)- Multivariate Data Analysis with Readings, 4ª ed., New Jersey, Prentice-Hall Inc. Leal, Rogério P., Pereira, Zulema L. (2003) Service Recovery at a financial institution, International Journal of Quality and Reliability Management, Vol.20, No.6, pp Parasuraman, A., Berry, Leonard L, Zeithaml, Valarie A., (1991) - Understanding Customer Expectations of Service, Sloan Management Review, Spring 1991, pp Parasuraman, A., Zeithaml, Valarie A., Berry, Leonard L. (1988) - SERVQUAL: A Multiple-Item Scale for Measuring Consumer Perceptions of Service Quality, Journal of Retailing, Vol. 64, No. 1; Spring, pp Zeithaml, Valarie A., Parasuraman, A., BERRY, Leonard L.(1990) - Delivering Quality Service: Balancing Customer Perceptions and Expectations; The Free Press, A Division of Macmillan, Inc.