- Email: [email protected]
Tipping behaviour: a disconfirmation of expectation perspective
ARTICLE IN PRESS
Hospitality Management 22 (2003) 461–467
Research note
Tipping behaviour: a disconfirmation of expectation perspective Alan C. Tse* Department of Marketing, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong
Abstract This study examines the effect of expectancy–disconfirmation on tipping behaviour. Findings of our study show that restaurant patrons determine how much tips to give based on the discrepancy between the actual and expected level of food and service quality, rather than the absolute level of food and service quality. That is, given a positive disconfirmation, customers would give more tips. On the other hand, under situations of negative disconfirmation, tip size would drop. Furthermore, we found that the impact of a negative expectancy–disconfirmation on tip size is larger than that of a positive expectancy– disconfirmation of the same magnitude. r 2003 Elsevier Ltd. All rights reserved. Keywords: Tipping; Expectancy–disconfirmation; Restaurant
1. Introduction ‘‘To tip’’ means ‘‘to give a gratuity to a servant or employee’’. Tipping is a widespread custom in which service patrons give sums of money above and beyond the contracted price of the service to the workers who have served them (Lynn and McCall, 2000). The practice of giving tips is particularly common in the catering business. Tips expenditure in US restaurants alone amounts to around US$16 billion a year (Lynn and McCall, 2000). The enormous amount of expenditure on tipping contradicts with the basic economic principle that people should never pay more than they need to. As such, it attracts a lot of attention from academics as well as practitioners. *Tel.: +852-2609-7829; fax: +852-2603-5473. E-mail address: [email protected] (A.C. Tse). 0278-4319/$ - see front matter r 2003 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijhm.2003.07.002
ARTICLE IN PRESS 462
A.C. Tse / Hospitality Management 22 (2003) 461–467
One theory that can be used to explain tipping behaviour is that tip size is related to service quality. The better the service, the more tips customers would give. The purported relationship between tip size and service quality is founded on Adam’s theory of equity which suggests that a distressing state of cognitive dissonance would result if what one person receives from the relationship is not proportional to the benefits he or she delivers to the relationship partner (Adams, 1965; Walster et al., 1973). Since inequitable relationships are distressing, the theory predicts that customers would give more tips when they get better service (Snyder, 1976; Lynn and Grassman, 1990). However, in reality, empirical studies have found that the relationship between service quality and the size of tips is weak (Lynn and McCall, 2000; Oliver and Swan, 1989). One possible explanation for this weak relationship is that customers do not look at the absolute level of service quality, but instead they look at the deviation from the expected service quality level when they determine the size of the tips they should pay. Hence, the objective of this paper is to investigate how expectancy–disconfirmation could affect the amount of tipping. The expectancy–disconfirmation model (Oliver, 1977, 1980) is a very important theory that can be used to analyse how deviation from expectation affects satisfaction. In fact, Johnson et al. (1996), Bitner (1990) and Gentry et al. (1991) all suggest that the dominant model for studying consumer satisfaction is the disconfirmation of expectations paradigm. According to this theory, consumer satisfaction is a function of perceived performance and perceived disconfirmation, the latter being dependent upon perceived performance and standard for comparison. Standards of comparison may include expectations, ideals, competitors, marketer promises and industry norms (Sarah, 1999). If performance is significantly worse than the comparison standard, a customer will experience negative disconfirmation. On the contrary, if perceived performance exceeds expectation, positive disconfirmation results. This model posits that satisfaction is related to the size and direction of the disconfirmation experience (Anderson, 1973; Danaher and Mattsson, 1994; de Ruyter et al., 1997; Oliver, 1980; Oliver and DeSarbo, 1988; Spreng et al., 1996; Tse and Wilton, 1988). A considerable amount of empirical evidence has confirmed the hypothesized impact of the disconfirmation of expectations on satisfaction (Yi, 1990). In this study, we manipulate the direction and level of expectancy–disconfirmation by putting restaurant patrons into one of the following four different scenarios of service and food quality expectations and outcomes: Scenario 1: High-class restaurant, high level of service and food quality (no expectancy–disconfirmation). Scenario 2: High-class restaurant, low level of service and food quality (negative expectancy–disconfirmation). Scenario 3: Low-class restaurant, high level of service and food quality (positive expectancy–disconfirmation). Scenario 4: Low-class restaurant, low level of service and food quality (no expectancy–disconfirmation). In each one of the above scenarios, we manipulate the expected service and food quality level using the case of either a high-class or low-class restaurant, and the
ARTICLE IN PRESS A.C. Tse / Hospitality Management 22 (2003) 461–467
463
actual service and food quality delivered could be different from what is expected. We hypothesize that restaurant patrons with negative expectancy– disconfirmation would experience dissatisfaction, and would thereby give less tips. On the contrary, those given positive expectancy–disconfirmation would experience higher levels of satisfaction, and would therefore give more tips. In sum, we hypothesize that: Hypothesis 1. Negative expectancy–disconfirmation would result in less tips given. Hypothesis 2. Positive expectancy–disconfirmation would result in more tips given. Many researchers also point out that good service usually goes unacknowledged and unnoticed because good service is to be expected (Brandt and Reffett, 1989; Johnston, 1995). On the contrary, customers are easily sensitized by bad service because it is not usually expected nor wanted. Hence, we hypothesize that: Hypothesis 3. The impact of a negative expectancy–disconfirmation on tip size is larger than that of a positive expectancy–disconfirmation of the same magnitude. Little work has been done in the past on postpurchase phenomena such as the effect of expectancy–disconfirmation on tipping behaviour. This study therefore extends the consumer satisfaction literature in the catering industry by focusing on an important but neglected area of postpurchase evaluation, that is, expectancy– disconfirmation. In the following, we would first describe the methodology, then the results of the data analysis would be presented, and finally the conclusion and discussion.
2. Methodology 2.1. Design To test the effect of positive and negative disconfirmation of expectations on tipping behaviour, the study adopted a between-subject factorial design with four treatments (2 levels of expected service and food quality 2 levels of actual service and food quality). Since disconfirmation has been operationalized in previous research mainly as the algebraic difference between expectation measures and perceived performance measures, we used the additive difference model (Tversky, 1969) as a way of operationalizing disconfirmation. This model is more general (Spreng et al., 1996) and subsumes other models such as the ideal-point model and the value-percept disparity model (Westbrook and Reilly, 1983). In this study, subjects were told that they are dining in a high/low-class restaurant, and the actual service and food quality is high/low, and the amount of tips they would give is then examined.
ARTICLE IN PRESS A.C. Tse / Hospitality Management 22 (2003) 461–467
464
2.2. Procedure A total of 120 restaurant patrons ranged in age from 16 to 54 were interviewed outside the main entrance of one of Maxim’s Chinese restaurants located in a local busy shopping mall. Maxim’s operates the largest Chinese restaurant chain in Hong Kong. The interviews were conducted on a typical Sunday when people customarily would have dim sum and meals with friends or family in Chinese restaurants. Customers normally need to wait for a table on Sunday, so they were willing to be interviewed while our interviewers approached them in the waiting lounge. All the interviewees are Hong Kong Chinese. Before a customer was interviewed, the interviewer randomly assigned the respondent into one of the four experimental conditions described above and then announced the following message: Imagine that you are dining in a high/low class Chinese restaurant. How much tips would you give if the service and food quality is high/low? Respondents then indicate how much tips they would give using a 6-point scale from ‘‘strongly disagree’’ to ‘‘strongly agree’’ that contains the following two items. A 6-point scale is used because it avoids the central tendency bias that is common in interviews involving Chinese respondents. I would give more tips. I would give more tips than what I normally would.
3. Analysis and results In the first part of the data analysis, the two items for measuring the amount of tips to give is factor analysed into one single factor which explains 91.2% of the variation. The Cronbach’s alpha for the two items is 0.9027, indicating that the scale is highly reliable (Nunnally, 1978). The factor score is then used as the dependent variable for subsequent analyses. Since Levene’s test of homogeneity of variances shows that the variances are unequal (Leveine’s statistic=14.472, df1=2, df2=116, p ¼ 0:000), ANOVA is not used for analysing the effects of expectancy–disconfirmation on amount of tips to give. Instead, independent sample t-tests assuming unequal variances are used. The results are shown in Table 1. From Table 1, we clearly see that the effect of expectancy–disconfirmation on tip size is significant. When customers experience positive expectancy–disconfirmation, the tip size is 0:567s (factor scores are measured in number of standard deviations, s; from the mean) more than that of the control situation when there is no expectancy– disconfirmation (t ¼ 3:050; df=84.767, p ¼ 0:003). Similarly, in the case of negative expectancy–disconfirmation, the tip size is 0:847s lower than that when no expectancy–disconfirmation is experienced (t ¼ 4:783; df=80.133, p ¼ 0:000). Hence, both Hypothesis 1 and Hypothesis 2 are supported by our data.
ARTICLE IN PRESS A.C. Tse / Hospitality Management 22 (2003) 461–467
465
Table 1 Independent sample t-test results Group
Mean
df
Mean differencea
t
Sig. (2-tailed)
Positive expectancy–disconformation Control-no expectancy–disconfirmation Negative expectancy–disconfirmation
0.636 0.069 0.772
30 59 30
0.567 — 0.841
3.050 — 4.783
0.003 — 0.000
Dependent variable=tipping size factor score. The change is statistically significant at the 1% level. a The mean difference is the difference between the positive/negative disconfirmation tip size and the no expectancy disconfirmation tip size, all measured in standard deviations from the mean.
To look into the relative impact of the same amount of positive and negative disconfirmations on tip size, Table 1 shows that in absolute terms, the increase in tip size (0:567s) arising from a positive disconfirmation is lower than the decrease in tip size (0:847s) from a negative disconfirmation of the same size. Hence, Hypothesis 3 is also supported by the data.
4. Conclusion and discussion Overall, the results provide strong support for our hypotheses. Results obtained from this study support the assertion that customers would give more tips in cases of positive expectancy–disconfirmation, and negative disconfirmations would result in smaller tip size. As hypothesized, we also find that the increase in tip size brought about by a positive disconfirmation is less than the decrease in tip size brought about by a negative disconfirmation of the same magnitude. The above results have important implications for restaurant managers. Our results suggest that tip size is influenced by the amount of deviation between the actual and expected level of food and service quality, rather than the absolute level of food and service quality. Meanwhile, customers are more sensitive to negative disconfirmations than positive ones, as the drop in tip size from the former is larger than the rise in tip size from the latter of the same size. Hence, we may conclude that unsatisfactory experience may have a greater impact on tip size than satisfactory ones. The important point for restaurant managers is therefore that they should try their best to avoid negative disconfirmations. The primary limitation of our study is that the results were obtained under conditions in which subjects were asked to imagine going through the situations described in the scenario, but did not actually experience them. Future research should solicit data from real life situations when passengers in different classes of restaurants are made to experience different food and service quality outcomes. It is in practice difficult to get cooperation from restaurants to conduct the experiment, and there are a lot of extraneous factors that need to be controlled for in such field studies, but conducting a real life experiment in natural settings is still possible.
ARTICLE IN PRESS 466
A.C. Tse / Hospitality Management 22 (2003) 461–467
Future research should also look at attribution, and how different explanations of the cause of the discrepancies in food and service quality would affect the differential impact of positive and negative disconfirmations. Such explanations could be internal or external; the former being that the cause of the discrepancy can be attributed to the management, while the later refers to causes outside management’s control. Situational and personal factors may have an influence on the reaction of a patron towards expectancy–disconfirmation. These factors include variables such as a patron’s previous experience with the restaurant, the patron’s mood state, attitudes and reactions of other customers experiencing the same discrepancy and so on. Hence, a lot of variables are at work in framing the overall disconfirmation experience, and further work is required to delineate the complex interplay among these variables in affecting tip size.
References Adams, J.S., 1965. Inequality in social exchange. In: Berkowitz, L. (Ed.), Advances in Experimental Social Psychology, Vol. 2. Academic Press, New York. Anderson, R.E., 1973. Consumer dissatisfaction: the effect of disconfirmed expectancy on perceived product performance. Journal of Consumer Research 10 (1), 38–44. Bitner, M.J., 1990. Evaluating service encounters: the effects of physical surroundings and employee responses. Journal of Marketing 54 (2), 69–82. Brandt, D.R., Reffett, K.L., 1989. Focussing on customer problems to improve service quality. The Journal of Services Marketing 3 (4), 5–14. Danaher, P.J., Mattsson, J., 1994. Customer satisfaction during the service delivery process. European Journal of Marketing 28 (5), 5–16. de Ruyter, K., Bloemer, J.M., Peeters, P., 1997. Merging service quality and service satisfaction: an empirical test of an integrative framework. Journal of Economic Psychology 18 (4), 387–406. Gentry, J.W., Mowen, J.C., Tasaki, L., 1991. Salesperson evaluation: a systematic structure for reducing judgmental biases. Journal of Personal Selling and Sales Management 11 (2), 27–38. Johnston, R., 1995. The zone of tolerance: exploring the relationships between service transactions and satisfaction with the overall service. International Journal of Service Industry Management 6 (2), 46–61. Johnson, M.D., Nader, G., Fomell, C., 1996. Expectations, perceived performance, and customer satisfaction for a complex service: the case of bank loans. Journal of Economic Psychology 17 (2), 163–182. Lynn, M., Grassman, A., 1990. Restaurant tipping: an examination of three rational explanations. Journal of Economic Psychology 11 (2), 169–181. Lynn, M., McCall, M., 2000. Gratitude and gratuity: a meta-analysis of research on the service-tipping relationship. Journal of Socio-Economics 29 (2), 203–214. Nunnally, J.C., 1978. Psychometric Theory, 2nd Edition. McGraw-Hill, New York. Oliver, R.L., 1977. Effect of expectation and disconfirmation on postexposure product evaluations: an alternative interpretation. Journal of Applied Psychology 62 (4), 480–486. Oliver, R.L., 1980. A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Consumer Research 17 (4), 460–469. Oliver, R.L., DeSarbo, W.S., 1988. Response determinants in satisfaction judgments. Journal of Consumer Research 14 (4), 495–508. Oliver, R.L., Swan, J.E., 1989. Consumer perceptions of interpersonal equity and satisfaction in transactions: a field survey approach. Journal of Marketing 53 (2), 21–35.
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Sarah, M., 1999. Less pain, some gain: the effects of priming fairness in price negotiations. Psychology & Marketing 16 (7), 545–562. Snyder, M.L., 1976. The inverse relationship between restaurant party size and tip percentage: diffusion or equity? Personality and Social Psychology Bulletin 2, 308. Spreng, R.A., MacKenzie, S.B., Olshavsky, R.W., 1996. A reexamination of the determinants of consumer satisfaction. Journal of Marketing 60 (3), 15–32. Tse, D.K., Wilton, P.C., 1988. Models of consumer satisfaction formation: an extension. Journal of Marketing Research 25 (2), 204–212. Tversky, A., 1969. Intransitivity of preferences. Psychological Review 76 (2), 31–48. Walster, E., Berscheid, E., Walster, W.G., 1973. New directions in equity research. Journal of Personality and Social Psychology 25 (3), 151–176. Westbrook, R.A., Reilly, M.D., 1983. Value-percept disparity: an alternative to the disconfirmation of expectations theory of consumer satisfaction. Advances in Consumer Research 10, 256–261. Yi, Y., 1990. A critical review of consumer satisfaction. In: Zeithaml, V.A. (Ed.), Review of Marketing. American Marketing Association, Chicago, pp. 68–123.
Hospitality Management 22 (2003) 461–467
Research note
Tipping behaviour: a disconfirmation of expectation perspective Alan C. Tse* Department of Marketing, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong
Abstract This study examines the effect of expectancy–disconfirmation on tipping behaviour. Findings of our study show that restaurant patrons determine how much tips to give based on the discrepancy between the actual and expected level of food and service quality, rather than the absolute level of food and service quality. That is, given a positive disconfirmation, customers would give more tips. On the other hand, under situations of negative disconfirmation, tip size would drop. Furthermore, we found that the impact of a negative expectancy–disconfirmation on tip size is larger than that of a positive expectancy– disconfirmation of the same magnitude. r 2003 Elsevier Ltd. All rights reserved. Keywords: Tipping; Expectancy–disconfirmation; Restaurant
1. Introduction ‘‘To tip’’ means ‘‘to give a gratuity to a servant or employee’’. Tipping is a widespread custom in which service patrons give sums of money above and beyond the contracted price of the service to the workers who have served them (Lynn and McCall, 2000). The practice of giving tips is particularly common in the catering business. Tips expenditure in US restaurants alone amounts to around US$16 billion a year (Lynn and McCall, 2000). The enormous amount of expenditure on tipping contradicts with the basic economic principle that people should never pay more than they need to. As such, it attracts a lot of attention from academics as well as practitioners. *Tel.: +852-2609-7829; fax: +852-2603-5473. E-mail address: [email protected] (A.C. Tse). 0278-4319/$ - see front matter r 2003 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijhm.2003.07.002
ARTICLE IN PRESS 462
A.C. Tse / Hospitality Management 22 (2003) 461–467
One theory that can be used to explain tipping behaviour is that tip size is related to service quality. The better the service, the more tips customers would give. The purported relationship between tip size and service quality is founded on Adam’s theory of equity which suggests that a distressing state of cognitive dissonance would result if what one person receives from the relationship is not proportional to the benefits he or she delivers to the relationship partner (Adams, 1965; Walster et al., 1973). Since inequitable relationships are distressing, the theory predicts that customers would give more tips when they get better service (Snyder, 1976; Lynn and Grassman, 1990). However, in reality, empirical studies have found that the relationship between service quality and the size of tips is weak (Lynn and McCall, 2000; Oliver and Swan, 1989). One possible explanation for this weak relationship is that customers do not look at the absolute level of service quality, but instead they look at the deviation from the expected service quality level when they determine the size of the tips they should pay. Hence, the objective of this paper is to investigate how expectancy–disconfirmation could affect the amount of tipping. The expectancy–disconfirmation model (Oliver, 1977, 1980) is a very important theory that can be used to analyse how deviation from expectation affects satisfaction. In fact, Johnson et al. (1996), Bitner (1990) and Gentry et al. (1991) all suggest that the dominant model for studying consumer satisfaction is the disconfirmation of expectations paradigm. According to this theory, consumer satisfaction is a function of perceived performance and perceived disconfirmation, the latter being dependent upon perceived performance and standard for comparison. Standards of comparison may include expectations, ideals, competitors, marketer promises and industry norms (Sarah, 1999). If performance is significantly worse than the comparison standard, a customer will experience negative disconfirmation. On the contrary, if perceived performance exceeds expectation, positive disconfirmation results. This model posits that satisfaction is related to the size and direction of the disconfirmation experience (Anderson, 1973; Danaher and Mattsson, 1994; de Ruyter et al., 1997; Oliver, 1980; Oliver and DeSarbo, 1988; Spreng et al., 1996; Tse and Wilton, 1988). A considerable amount of empirical evidence has confirmed the hypothesized impact of the disconfirmation of expectations on satisfaction (Yi, 1990). In this study, we manipulate the direction and level of expectancy–disconfirmation by putting restaurant patrons into one of the following four different scenarios of service and food quality expectations and outcomes: Scenario 1: High-class restaurant, high level of service and food quality (no expectancy–disconfirmation). Scenario 2: High-class restaurant, low level of service and food quality (negative expectancy–disconfirmation). Scenario 3: Low-class restaurant, high level of service and food quality (positive expectancy–disconfirmation). Scenario 4: Low-class restaurant, low level of service and food quality (no expectancy–disconfirmation). In each one of the above scenarios, we manipulate the expected service and food quality level using the case of either a high-class or low-class restaurant, and the
ARTICLE IN PRESS A.C. Tse / Hospitality Management 22 (2003) 461–467
463
actual service and food quality delivered could be different from what is expected. We hypothesize that restaurant patrons with negative expectancy– disconfirmation would experience dissatisfaction, and would thereby give less tips. On the contrary, those given positive expectancy–disconfirmation would experience higher levels of satisfaction, and would therefore give more tips. In sum, we hypothesize that: Hypothesis 1. Negative expectancy–disconfirmation would result in less tips given. Hypothesis 2. Positive expectancy–disconfirmation would result in more tips given. Many researchers also point out that good service usually goes unacknowledged and unnoticed because good service is to be expected (Brandt and Reffett, 1989; Johnston, 1995). On the contrary, customers are easily sensitized by bad service because it is not usually expected nor wanted. Hence, we hypothesize that: Hypothesis 3. The impact of a negative expectancy–disconfirmation on tip size is larger than that of a positive expectancy–disconfirmation of the same magnitude. Little work has been done in the past on postpurchase phenomena such as the effect of expectancy–disconfirmation on tipping behaviour. This study therefore extends the consumer satisfaction literature in the catering industry by focusing on an important but neglected area of postpurchase evaluation, that is, expectancy– disconfirmation. In the following, we would first describe the methodology, then the results of the data analysis would be presented, and finally the conclusion and discussion.
2. Methodology 2.1. Design To test the effect of positive and negative disconfirmation of expectations on tipping behaviour, the study adopted a between-subject factorial design with four treatments (2 levels of expected service and food quality 2 levels of actual service and food quality). Since disconfirmation has been operationalized in previous research mainly as the algebraic difference between expectation measures and perceived performance measures, we used the additive difference model (Tversky, 1969) as a way of operationalizing disconfirmation. This model is more general (Spreng et al., 1996) and subsumes other models such as the ideal-point model and the value-percept disparity model (Westbrook and Reilly, 1983). In this study, subjects were told that they are dining in a high/low-class restaurant, and the actual service and food quality is high/low, and the amount of tips they would give is then examined.
ARTICLE IN PRESS A.C. Tse / Hospitality Management 22 (2003) 461–467
464
2.2. Procedure A total of 120 restaurant patrons ranged in age from 16 to 54 were interviewed outside the main entrance of one of Maxim’s Chinese restaurants located in a local busy shopping mall. Maxim’s operates the largest Chinese restaurant chain in Hong Kong. The interviews were conducted on a typical Sunday when people customarily would have dim sum and meals with friends or family in Chinese restaurants. Customers normally need to wait for a table on Sunday, so they were willing to be interviewed while our interviewers approached them in the waiting lounge. All the interviewees are Hong Kong Chinese. Before a customer was interviewed, the interviewer randomly assigned the respondent into one of the four experimental conditions described above and then announced the following message: Imagine that you are dining in a high/low class Chinese restaurant. How much tips would you give if the service and food quality is high/low? Respondents then indicate how much tips they would give using a 6-point scale from ‘‘strongly disagree’’ to ‘‘strongly agree’’ that contains the following two items. A 6-point scale is used because it avoids the central tendency bias that is common in interviews involving Chinese respondents. I would give more tips. I would give more tips than what I normally would.
3. Analysis and results In the first part of the data analysis, the two items for measuring the amount of tips to give is factor analysed into one single factor which explains 91.2% of the variation. The Cronbach’s alpha for the two items is 0.9027, indicating that the scale is highly reliable (Nunnally, 1978). The factor score is then used as the dependent variable for subsequent analyses. Since Levene’s test of homogeneity of variances shows that the variances are unequal (Leveine’s statistic=14.472, df1=2, df2=116, p ¼ 0:000), ANOVA is not used for analysing the effects of expectancy–disconfirmation on amount of tips to give. Instead, independent sample t-tests assuming unequal variances are used. The results are shown in Table 1. From Table 1, we clearly see that the effect of expectancy–disconfirmation on tip size is significant. When customers experience positive expectancy–disconfirmation, the tip size is 0:567s (factor scores are measured in number of standard deviations, s; from the mean) more than that of the control situation when there is no expectancy– disconfirmation (t ¼ 3:050; df=84.767, p ¼ 0:003). Similarly, in the case of negative expectancy–disconfirmation, the tip size is 0:847s lower than that when no expectancy–disconfirmation is experienced (t ¼ 4:783; df=80.133, p ¼ 0:000). Hence, both Hypothesis 1 and Hypothesis 2 are supported by our data.
ARTICLE IN PRESS A.C. Tse / Hospitality Management 22 (2003) 461–467
465
Table 1 Independent sample t-test results Group
Mean
df
Mean differencea
t
Sig. (2-tailed)
Positive expectancy–disconformation Control-no expectancy–disconfirmation Negative expectancy–disconfirmation
0.636 0.069 0.772
30 59 30
0.567 — 0.841
3.050 — 4.783
0.003 — 0.000
Dependent variable=tipping size factor score. The change is statistically significant at the 1% level. a The mean difference is the difference between the positive/negative disconfirmation tip size and the no expectancy disconfirmation tip size, all measured in standard deviations from the mean.
To look into the relative impact of the same amount of positive and negative disconfirmations on tip size, Table 1 shows that in absolute terms, the increase in tip size (0:567s) arising from a positive disconfirmation is lower than the decrease in tip size (0:847s) from a negative disconfirmation of the same size. Hence, Hypothesis 3 is also supported by the data.
4. Conclusion and discussion Overall, the results provide strong support for our hypotheses. Results obtained from this study support the assertion that customers would give more tips in cases of positive expectancy–disconfirmation, and negative disconfirmations would result in smaller tip size. As hypothesized, we also find that the increase in tip size brought about by a positive disconfirmation is less than the decrease in tip size brought about by a negative disconfirmation of the same magnitude. The above results have important implications for restaurant managers. Our results suggest that tip size is influenced by the amount of deviation between the actual and expected level of food and service quality, rather than the absolute level of food and service quality. Meanwhile, customers are more sensitive to negative disconfirmations than positive ones, as the drop in tip size from the former is larger than the rise in tip size from the latter of the same size. Hence, we may conclude that unsatisfactory experience may have a greater impact on tip size than satisfactory ones. The important point for restaurant managers is therefore that they should try their best to avoid negative disconfirmations. The primary limitation of our study is that the results were obtained under conditions in which subjects were asked to imagine going through the situations described in the scenario, but did not actually experience them. Future research should solicit data from real life situations when passengers in different classes of restaurants are made to experience different food and service quality outcomes. It is in practice difficult to get cooperation from restaurants to conduct the experiment, and there are a lot of extraneous factors that need to be controlled for in such field studies, but conducting a real life experiment in natural settings is still possible.
ARTICLE IN PRESS 466
A.C. Tse / Hospitality Management 22 (2003) 461–467
Future research should also look at attribution, and how different explanations of the cause of the discrepancies in food and service quality would affect the differential impact of positive and negative disconfirmations. Such explanations could be internal or external; the former being that the cause of the discrepancy can be attributed to the management, while the later refers to causes outside management’s control. Situational and personal factors may have an influence on the reaction of a patron towards expectancy–disconfirmation. These factors include variables such as a patron’s previous experience with the restaurant, the patron’s mood state, attitudes and reactions of other customers experiencing the same discrepancy and so on. Hence, a lot of variables are at work in framing the overall disconfirmation experience, and further work is required to delineate the complex interplay among these variables in affecting tip size.
References Adams, J.S., 1965. Inequality in social exchange. In: Berkowitz, L. (Ed.), Advances in Experimental Social Psychology, Vol. 2. Academic Press, New York. Anderson, R.E., 1973. Consumer dissatisfaction: the effect of disconfirmed expectancy on perceived product performance. Journal of Consumer Research 10 (1), 38–44. Bitner, M.J., 1990. Evaluating service encounters: the effects of physical surroundings and employee responses. Journal of Marketing 54 (2), 69–82. Brandt, D.R., Reffett, K.L., 1989. Focussing on customer problems to improve service quality. The Journal of Services Marketing 3 (4), 5–14. Danaher, P.J., Mattsson, J., 1994. Customer satisfaction during the service delivery process. European Journal of Marketing 28 (5), 5–16. de Ruyter, K., Bloemer, J.M., Peeters, P., 1997. Merging service quality and service satisfaction: an empirical test of an integrative framework. Journal of Economic Psychology 18 (4), 387–406. Gentry, J.W., Mowen, J.C., Tasaki, L., 1991. Salesperson evaluation: a systematic structure for reducing judgmental biases. Journal of Personal Selling and Sales Management 11 (2), 27–38. Johnston, R., 1995. The zone of tolerance: exploring the relationships between service transactions and satisfaction with the overall service. International Journal of Service Industry Management 6 (2), 46–61. Johnson, M.D., Nader, G., Fomell, C., 1996. Expectations, perceived performance, and customer satisfaction for a complex service: the case of bank loans. Journal of Economic Psychology 17 (2), 163–182. Lynn, M., Grassman, A., 1990. Restaurant tipping: an examination of three rational explanations. Journal of Economic Psychology 11 (2), 169–181. Lynn, M., McCall, M., 2000. Gratitude and gratuity: a meta-analysis of research on the service-tipping relationship. Journal of Socio-Economics 29 (2), 203–214. Nunnally, J.C., 1978. Psychometric Theory, 2nd Edition. McGraw-Hill, New York. Oliver, R.L., 1977. Effect of expectation and disconfirmation on postexposure product evaluations: an alternative interpretation. Journal of Applied Psychology 62 (4), 480–486. Oliver, R.L., 1980. A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Consumer Research 17 (4), 460–469. Oliver, R.L., DeSarbo, W.S., 1988. Response determinants in satisfaction judgments. Journal of Consumer Research 14 (4), 495–508. Oliver, R.L., Swan, J.E., 1989. Consumer perceptions of interpersonal equity and satisfaction in transactions: a field survey approach. Journal of Marketing 53 (2), 21–35.
ARTICLE IN PRESS A.C. Tse / Hospitality Management 22 (2003) 461–467
467
Sarah, M., 1999. Less pain, some gain: the effects of priming fairness in price negotiations. Psychology & Marketing 16 (7), 545–562. Snyder, M.L., 1976. The inverse relationship between restaurant party size and tip percentage: diffusion or equity? Personality and Social Psychology Bulletin 2, 308. Spreng, R.A., MacKenzie, S.B., Olshavsky, R.W., 1996. A reexamination of the determinants of consumer satisfaction. Journal of Marketing 60 (3), 15–32. Tse, D.K., Wilton, P.C., 1988. Models of consumer satisfaction formation: an extension. Journal of Marketing Research 25 (2), 204–212. Tversky, A., 1969. Intransitivity of preferences. Psychological Review 76 (2), 31–48. Walster, E., Berscheid, E., Walster, W.G., 1973. New directions in equity research. Journal of Personality and Social Psychology 25 (3), 151–176. Westbrook, R.A., Reilly, M.D., 1983. Value-percept disparity: an alternative to the disconfirmation of expectations theory of consumer satisfaction. Advances in Consumer Research 10, 256–261. Yi, Y., 1990. A critical review of consumer satisfaction. In: Zeithaml, V.A. (Ed.), Review of Marketing. American Marketing Association, Chicago, pp. 68–123.