Restaurant Tipping: Free-Riding, Social Acceptance, …thewayweare.wikispaces.com/file/view/tipping...

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Restaurant Tipping: Free-Riding, Social Acceptance, and Gender Differences’ WILLIAM J. BoYEs2 WILLIAM STEWART MOUNTS, JR. Department of Economics Arizona State University Mercer University Stetson School of Business and Economics CLIFFORD SOWELL Department of Economics Berea College The practice of paying gratuities for services is a worldwide custom. Tipping is found only in some professions, which suggests that it serves to increase the efficiency of specific kinds of exchanges. The literature accepts the view that monitoring of employees by cus- tomers appears to be the logical rationale for the practice of tipping. This can be seen in that gratuities are paid at the discretion of consumers after they receive the services for which they are paying. However, it does not explain why, given the voluntary aspect of tipping, rational people would not free-ride on the tipping of others. We found that both men and women free-ride in their tipping behavior. Yet, we also found that men are more influenced by social acceptance or approval in their tipping behavior than are women. The practice of paying gratuities for services is a worldwide custom that involves many professions. Some suggest that the practice originated in the Middle Ages when journeying feudal lords purchased safe passage by tossing handfuls of coins to beggars on the road (Schein, Jablonski, & Wohlfahrt, 1984). Elsewhere, others claim that tipping grew out of the custom of vails, which required visitors in Tudor, England, to pay their host’s servants for the extra work their visit created (Shamir, 1984). Even the origin of the word tip is not known. Tip may derive from (a) the Latin word stips, meaning gift; (b) the Dutch word tippen, meaning to tap, as in tapping a coin on a table or glass to attract a server’s attention; or (c) the words “To Insure Promptitude,” which were written on collection boxes in 18th-century English coffee shops (Schein et al., 1984). ‘The authors thank Linda Brennan, Corky Brown, Mona Land, and Jay Marchand for their com- ments. We remain responsible for any errors. 2Correspondence concerning this article should be addressed to William Boyes, Department of Economics, College of Business, Arizona State University, Tempe, AZ 85257. E-mail: William .Boyes(@asu.edu 261 6 Journal of Applied Social Psychology, 2004, 34, 12, pp. 2616-2628. Copyright 0 2004 by V. H. Winston & Son, Inc. All rights reserved.

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Restaurant Tipping: Free-Riding, Social Acceptance, and Gender Differences’

WILLIAM J. BoYEs2 WILLIAM STEWART MOUNTS, JR. Department of Economics Arizona State University Mercer University

Stetson School of Business and Economics

CLIFFORD SOWELL Department of Economics

Berea College

The practice of paying gratuities for services is a worldwide custom. Tipping is found only in some professions, which suggests that it serves to increase the efficiency of specific kinds of exchanges. The literature accepts the view that monitoring of employees by cus- tomers appears to be the logical rationale for the practice of tipping. This can be seen in that gratuities are paid at the discretion of consumers after they receive the services for which they are paying. However, it does not explain why, given the voluntary aspect of tipping, rational people would not free-ride on the tipping of others. We found that both men and women free-ride in their tipping behavior. Yet, we also found that men are more influenced by social acceptance or approval in their tipping behavior than are women.

The practice of paying gratuities for services is a worldwide custom that involves many professions. Some suggest that the practice originated in the Middle Ages when journeying feudal lords purchased safe passage by tossing handfuls of coins to beggars on the road (Schein, Jablonski, & Wohlfahrt, 1984). Elsewhere, others claim that tipping grew out of the custom of vails, which required visitors in Tudor, England, to pay their host’s servants for the extra work their visit created (Shamir, 1984). Even the origin of the word tip is not known. Tip may derive from (a) the Latin word stips, meaning gift; (b ) the Dutch word tippen, meaning to tap, as in tapping a coin on a table or glass to attract a server’s attention; or (c) the words “To Insure Promptitude,” which were written on collection boxes in 18th-century English coffee shops (Schein et al., 1984).

‘The authors thank Linda Brennan, Corky Brown, Mona Land, and Jay Marchand for their com- ments. We remain responsible for any errors.

2Correspondence concerning this article should be addressed to William Boyes, Department of Economics, College of Business, Arizona State University, Tempe, AZ 85257. E-mail: William .Boyes(@asu.edu

261 6

Journal of Applied Social Psychology, 2004, 34, 12, pp. 2616-2628. Copyright 0 2004 by V. H. Winston & Son, Inc. All rights reserved.

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Tipping is not observed in all professions and usually occurs only in exchange for services. This suggests that it serves to increase the efficiency of specific kinds of exchanges. Since many service employee inputs are difficult and costly for employers (e.g., restaurants) to monitor, this function is partially delegated to customers via the use of tips. The problem with this convention is that gratuities are paid at the discretion of consumers after they have received services. Also, why would anyone tip, since others in a party or in the establishment will tip (or past patrons had tipped)? As such, a free-riding effect is inherent in the tipping environment, which may work against the monitoring role.

The interaction of monitoring with free riding is seen in a survey we con- ducted involving 360 people who were contacted at a shopping mall about their motives for tipping at restaurants. In rank order of preferences, the reasons they gave were as follows: (a) to ensure good service in the future, (b) to be fair to servers, (c) to not be embarrassed, and (d) because everyone tips. Next, we asked these same respondents why they might tip at a restaurant they would not fre- quent in the future. The four reasons noted did not change, even though custom- ers could simply walk out without leaving a tip; that is, a free ride on the behavior of others. In fact, no one said they would not tip, but several said they might tip less than if they anticipated returning to the restaurant in the future. This was followed with an inquiry into why the free-riding problem was apparently not an important issue to the survey respondents. The principal reason given was that they would be embarrassed not to tip.

In both the question of why a person tips and why a person might not free- ride, we find that the patron desires not to be embarrassed or to be known as “cheap.” This desire suggests that tipping and social approval (or wish to avoid social disapproval) are related and that social approval or acceptance may miti- gate the possibility of free-riding on the tipping of others.

The purpose of this paper is to examine the possible interaction between monitoring, free riding, and social acceptance in restaurant tipping. Data derived from a survey involving patrons and servers at 18 restaurants in Phoenix, Arizona, are used to examine hypotheses about these aspects of tipping.

Tipping, Monitoring, and the Willingness to Free-Ride

Most restaurant owners partially delegate the monitoring of servers to patrons and their tips. Servers want to be paid for the service they provide diners. Further, they prefer to be paid more for these services as opposed to less. Free-riding behavior on the part of patrons is partially the result of the absence of perfect monitoring by servers, This is a result of the fact that tipping is ex post to service and that servers are responsible for several tables. To overcome this, servers can be expected to engage in certain types of behavior and to employ tactics

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that increase familiarity with the party, especially the payer. This may include introducing oneself (Garrity & Degelman, 1990), touching patrons (Crusco & Wetzell, 1984; Hornik, 1992), and bending down to be at the same height as the patron (Lynn & Mynier, 1993).

Similarly, patrons want good service and may try to assure this outcome through the prospect of a tip. Yet, a patron has an incentive to free-ride on the behavior of others as a result of the absence of monitoring, which is partly a result of the ex post (as opposed to ex ante) nature of the tipping relationship. For example, they may free-ride on the tips of other patrons in the restaurant. This would be likely if the patron (e.g., a tourist) had a good chance of never returning to the restaurant. In another case, a patron may free-ride on others in his or her party, regardless of whether the other members of the party tip. As stated previ- ously, the ability to free-ride is more likely when individual behavior cannot be monitored perfectly. The larger the party, the more difficult it is for the server to monitor the behavior of any one individual and the harder it is for other members of the party to monitor one of their own. Also, when the server is not able to iden- tify the payer, the server is unable to give the payer extra service, as suggested in the literature.

From a broader perspective, tipping can be viewed as a social norm (Conlin et al., 2003). Holloway (1985) and Lynn and Grassman (1990) argued that tipping is a means to purchase social approval. This argument follows from the basic notion that compliance with social norms is motivated by a desire for social approval and acceptance or a fear of social disapproval (Lynn and LatanC, 1984).

If tipping is an attempt to purchase social approval, from whom is a customer purchasing social approval? If it is the server, then a lack of familiarity between patron and server should enhance the possibility of free riding. Conversely, familiarity and expected future interaction should increase the value of the server’s social approval. Thus, customers who frequently dine at a restaurant or who dine out in general should tip more. However, if social approval is being purchased from other diners, then customers in groups should tip more than patrons who are alone, until the size of the group is sufficient to encourage free riding. This is supported by Snyder (1976) and Freeman, Walker, Borden, and LatanC (1975) who found an inverse relationship between tip size and party size.3 Social approval also suggests that tips should be larger for couples or groups whose members are not well acquainted versus couples who are married or groups whose members know each other very well. In other words, if an impres- sion is important-a date or a business meeting-then the tip should be larger than if an impression is not important.

3The free-riding problem may be why, in some restaurants, a tip is automatically affixed to the bills of large parties.

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Data

An extensive survey of tipping behavior was conducted in November/ December 1995 in metropolitan Phoenix, A r i ~ o n a . ~ Spring 1995 was used to pre-test the survey instrument and the willingness of restaurant managers and customers to participate. Following full payment, customers departing 18 differ- ent restaurants were asked a series of questions relating to their tipping b e h a ~ i o r . ~ Over 90% of those who were asked completed the surveys. Each survey was completed during the hours of 6 p.m. and 10 p.m. on either Friday or Saturday. The responses from every third completed survey were verified by an inquiry of the server.

There were 20 surveys collected at each restaurant. Each questionnaire was reexamined and deleted from the sample if it was incomplete or contained infor- mation that was obviously in error. Next, the remaining questionnaires were classified into one of four restaurant categories where the categories are based on the average bill. There were 40 surveys in each of the four categories for a total of 160 observations.

The data are divided into three categories.6 The first category measures the personal characteristics of the respondent. Income, gender, age, occupation, use of a credit card, occupation, and so forth are included in this group. The second category measures the tipping priors that consumers bring to a dining experience. These include expected tipping percentage; frequency of dining in general and in the current establishment; attitudes toward tipping and service; and other per- sonal priors concerning tipping behavior, including the number of people in a party. The final category characterizes the dining services just received. This group includes the actual tip given, an appraisal of the actual food and service, the number of people in the party, and whether the party’s mood was good and if they consumed alcohol.

Method

The nature of the data and its internal structure affect the methodology employed to measure empirically the relationships of interest described previ- ously. The data are viewed as a set of four balanced (40 observations in each) cross-sections. Within this setup, ordinary least squares (OLS) estimation of the data pooled would not be appropriate. Such an approach would require the restrictive assumption that the tipping behavior in each restaurant is identical.

4The efforts of 30 business students at Arizona State University who carried out the surveys are

SThe survey instrument appears in the Appendix A. The customer was contacted when he or she

6A dictionary of variables i s presented in Appendix B.

appreciated. Any remaining errors are claimed by the authors.

left the table or exited the restaurant, depending on the desires of the restaurant manager.

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Accordingly, an error-components methodology is deemed more appropriate for the problem.7 Under an error-components model, the error term is assumed to be comprised of three independent parts: (a) an error across a given cross-section, (b) an error between cross-sections for a given observation, and (c) an error asso- ciated with a unique observation. Such a structure can be estimated using either a fixed-effects (FE) or a random-effects (RE) format. Either could be used, and each has advantages and disadvantages. In the present case, a fixed-effects model would be useful if it is to be applied only to restaurants in the sample or in Phoenix, Arizona. However, our view is that the four restaurant types are a ran- dom sample from a much larger population and, therefore, a random-effects approach would be appropriate. We resolve this issue by using an empirical test of fixed versus random effects.

Results

Initial results from a random effects setup are presented in Table 1. The dependent variable is the tip left by the paying patron, in percentage terms. The overall fit of the model, seen in the adjusted R2, is rather good, given the cross- sectional nature of the data.8 Coefficients estimated with an error-components model are interpreted as percentage-point changes in the tip percentage, holding other factors represented by other explanatory variables constant. This is synony- mous with a least squares multiple regression interpretation.

In tests not reported here, it was determined that there were significant differ- ences in tipping behavior across the four classes of restaurants9 This argues for the error-components format discussed earlier. Furthermore, the Hausman test statistic shown in Tables 1 and 2 indicates that a random-effects model is more appropriate than is a fixed-effects model.10

As presented, explanatory variables have been classified into three areas: per- sonal attributes, tonight's attributes, and variables suggestive of free riding and social acceptance. As shown, gender (men tip less than women) and a patron's level of income are significant determinants of the percentage tip, holding other factors controlled for in the model constant." That is to say, men tip less than do women, independent of the effects of income, group size, service quality, and so forth.

7A discussion of this methodology can be found in Davidson and MacKinnon (1993) *Tests for heteroscedasticity were insignificant. In addition, judging by correlation coeffrcients,

multicollinearity appears not to be a problem. A correlation matrix is available from the authors. 9This is the result of an F test: estimated F(3, 144) = 9 . 5 3 , ~ = .OOOO.

loThe Hausman xz test statistic for a fixed-effects versus random-effects model is reported in

"Other personal attributes that were insignificant include age (and age2), occupation, and Table I .

whether diners were related.

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Table 1

Results of the Random-Effects Model

Sum of squared residuals = 1,152.80 Variance of residuals = 8.01 SE of regression = 2.83 Hausman test of HO: RE vs. FE: x2(3) = 12.07, p = .007 df = 146

R2 = .64 Adjusted R2 = .61

Constant Personal attributes

GENDER 1NC2 INC3 INC4 TIPAT

MOOD DRINK SERN BILLN

PHX FREQO PARTY

Tonight’s attributes

Free riding and social acceptance

Estimated Variable coefficient SE t

0.65 2.93 0.22

-0.67 2.32 2.82 3.24 0.06

1.54 1.64 1.88 0.08

-0.65 0.1 1 0.04

0.45 1.47 1.45 1.56 0.07

0.69 0.5 1 0.43 0.03

0.48 0.1 1 0.23

- 1.47* 1.58* 1.95* 2.08* 0.76

2.23* 3.21* 4.36* 2.88*

- 1.36* 1.05 0.18

Note. HO = null hypothesis, RE = random effects, FE = fixed effects. See Appendix B for variable definitions. *lo% level of confidence.

The patron’s anticipated tip (TIPAT) was included to control for the tipping priors brought to a restaurant. Its role is insignificant, however. It should be noted that, in results not reported here, the relationship between the anticipated tip and anticipated dining variables like quality and service were largely insignificant. Anticipated tips may simply be a learned percentage.

As might be expected, the attributes of the night’s dining experience (MOOD, DRINK, SERN, and BILLN), proxies for the monitoring role, were strong deter- minants of the tip percentage, holding other factors such as gender, income, party

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Table 2

Results of the Random-Effects Model With the Interaction of GENDER and PARTY (GENPA R T)

Sum of squared residuals = 1,12 1.3 1 Variance of residuals = 7.84 SE of regression = 2.80 Hausman test of HO: RE vs. FE: ~ ~ ( 4 ) = 12 .50 ,~ = .014 df= 145

R2 = .65 Adjusted R2 = .62

Estimated Variable coefficient SE t

Constant Personal attributes

GENDER INc2 INC3 INC4 TIPAT

Tonight's attributes MOOD DRINK SERN BILLN

Free riding and social acceptance PHX FREQO PARTY GENPART

1.99

-3.29 2.80 3.23 3.59 0.04

1.30 1.70 1.93 0.08

-0.61 0.12

-0.48 0.90

2.96

1.33 1.47 1.44 1.55 0.07

0.69 0.51 0.43 0.03

0.47 0.11 0.33 0.43

0.67

-2.47" 1.91* 2.24* 2.32* 0.59

1.89* 3.36* 4.51* 2.66*

-1.29* 1.12

-1.44* 2.09*

Nofe. HO = null hypothesis, RE = random effects, FE = fixed effects. See Appendix B for variable definitions. * 10% level of confidence.

size, and residency constant. The overall value of the night's service (SERN) had the largest estimated coefficient.12 We suspect that these variables capture many of the hedonic attributes of dining (e.g., the gender and attrativeness of the

12Service is being treated as a continuous variable.

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server). Interestingly, as the night’s bill (BILLN) increased, percentage tipped increased, holding other factors constant (e.g., group size). This may be sugges- tive of the overall quality of the restaurant and the meal. The role of income was positive in tip determination.13 Holding other factors constant, increases in income increased the percentage tipped.

The only significant variable measuring free riding and social acceptance is whether or not the patron is a resident of metropolitan Phoenix. This variable is a proxy for whether a patron will return to the particular restaurant. As shown, a nonresident tip was 0.65 percentage points less than that of a resident, holding all other things constant.’4

The monthly frequency of dining out (FREQO) and the number of people in tonight’s party were marginally insignificant. Two opposing effects can be seen playing a role in PARTY. The first is that the larger the party, the more likely the patron will tip less. This effect implies that it is easier for a member of a party to escape monitoring by other members of the party or the server; that is, to be able to free-ride more easily. Yet, the larger the party, the greater the penalty in terms of social acceptance on an individual who does free-ride. In this latter case, the percentage tipped would rise as party size increases.l5

The results in Table 1 do not strongly support the presence of free riding, social acceptance, or approval in the determination of percentage tipped. As a result, the basic model was extended to see if there was a gender difference that needed to be isolated so that the model could be estimated better. This was prompted by the notion that men are punished more for failing (in general) than are women (Aronson, Wilson, & Akert, 1994). This may suggest that there is a gender difference in compliance with social norms. Given that free riding in tips goes against the norm of tipping, there may be a gender difference in willingness to engage in this type of tipping behavior.

The results of this extension are presented in Table 2. Again, a random effects setup was employed.16 The results in Table 2 are an improvement over those shown in Table 1.

The only difference between Table 2 and Table 1 is that a variable was added, seen in an interaction between gender and the size of the party (GENPART).” Given that PARTY is our proxy for the interaction of free riding and social

I3The omitted group is those individuals with incomes below $20,000. I4This variable is highly correlated with the patron being a tourist or business traveler. I5lt should be noted that the data were collected on Friday and Saturday nights. Also, a dummy

variable indicating whether or not a dinner was business-related was not significant. These consider- ations lead us to believe that groups were largely social in composition and in purpose.

I6The F statistic for differences in tipping behavior between restaurants was F(3, 144) = 9.46, p =

.OOOO. The Hausman x2 test statistic continues to reject the use of a fixed-effects model (Table 2). ‘7The interaction of gender with other variables, particularly frequency of dining and Phoenix

residence, were not significant.

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acceptance, ceteris paribus, GENPART represents the gender-specific aspect of these two opposing factors. As shown, the estimated coefficient on gender increased measurably, holding the influences of the other explanatory variables constant.18 Furthermore, PARTY was negative and significant, indicating that both men and women showed a net willingness to free-ride. However, the sig- nificant positive coefficient on GENPART suggests that the willingness of men to free-ride in tipping was more than offset by their desire for social acceptance. This reduces the overall tipping differential seen in the large coefficient on GENDER.

Given that the remaining variable coefficients and their individual signifi- cance remained unchanged, this extension strongly supports the presence of a gender differential in tipping behavior that goes beyond just the simple treatment of gender differences. It must be noted that the estimated coefficient on GENPART does not allow us to differentiate between the hypothesis that men are trying to avoid social sanction by other party members or the hypothesis that men are buying social acceptance.19 In either case, however, it seems to us that social approval is being sought by men, given that other factors (e.g., party size, size of the bill, level of income, etc.) are being held constant.

Tipping is a worldwide custom honored by most people. It stems, in part, from the fact that some inputs, particularly those in the service industry, are difficult and costly for managers to monitor. Consumers are placed in the monitoring role through the act of tipping. In such an arrangement, however, there is a possibility of a free-rider problem within multiperson dining parties and across a restaurant that serves to reduce the efficiency of this form of monitoring. The findings of this paper support the presence of free riding on the part of men and women. Furthermore, we found this behavior on the part of men to be offset by the presence of social acceptance sought in a tipping environ- ment.

References

Aronson, E., Wilson, T. D., 19 Akert, R. M. (1994). Socialpsychology: The heart

Conlin, M., Lynn, M., & O'Donoghue, T. (2003). The norm of restaurant tipping. and mind. New York, NY: Harper Collins.

Journal of Economic Behavior and Organization, 52,291-321.

'8A reader suggested that the groups associated with male tippers may have greater range in size and that this may explain male tipping. However, the impact of group size is being held constant when GROUP is included in the estimation. Therefore, the role of gender shown in the coefficient is independent of the range of group sizes. This is the same as assuming that the range of groups between men and women is the same.

'9We would like to thank an anonymous reader for pointing this out.

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Crusco, A. H., & Wetzel, C. G. (1984). The Midas touch: The effects of inter- personal touch on restaurant tipping. Personality and Social Psychology Bulletin, 10, 512-517.

Davidson, R., & MacKinnon, J. G. (1993). Estimation and inference in economet- rics. New York, N Y Oxford University Press.

Freeman, S., Walker, M. R., Borden, R., & Latane, B. (1975). Diffusion of responsibility and restaurant tipping: cheaper by the bunch. Personalify and Social Psychology Bulletin, 1, 584-587.

Garrity, K., & Degelman D. (1990). Effect of server introduction on restaurant tipping. Journal of Applied Social Psychology, 20, 168- 172.

Holloway, J. C. (1985). Between gratitude and gratuity: Commentary on Shamir. Annals of Tourism Research, 12,239-242.

Hornik, J. (1992). Tactile stimulation and consumer response. Journal of Con- sumer Research, 19,449-458.

Lynn, M., & Grassman, A. (1990). Restaurant tipping: An examination of three “rational explanations.” Journal of Economic Psychology, 11, 169-1 81.

Lynn, M., & Mynier, K. (1993). Effect of server posture on restaurant tipping. Journal of Applied Social Psychology, 23,678-685.

Schein, J . E., Jablonski, E. F., & Wohlfahrt, B. R. (1984). The art of tipping: Customs and controversies. Wausau, WI: Tippers International.

Shamir, B. (1984). Between gratitude and gratuity: An analysis of tipping. Annals of Tourism Research, 11, 59-78.

Snyder, M. L. (1976). The inverse relationship between restaurant party size and tip percentage: Diffusion or equity? Personality and Social Psychology Bulle- tin, 2, 308.

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Appendix A

Tipping Survey

General Information

How many people in your party? Your age Your sex: Male ~ Female Are the people in your party:

friends business associates family

Occupation Average Annual Income:

Less than $20,000 $20,000 to $30,000 $30,000 to $50,000 Greater than $50,000

In what city do you reside? Are you visiting the Phoenix metropolitan area? Yes ~ No-

If yes, on vacation __ or on business -.

Frequency

How many times a month do you eat out? How many times have you frequented this restaurant in the past month? ~

Anticipated Tips

What percentage of the bill do you typically leave as a tip? __

On a scale of 1 to 5 where 5 is very important and 1 is not important, rate the importance of the following factors in their influence on the percent of total bill you leave as a tip?

Service Quality Speed of Service Quality of Food Size of Bill Number of People in Party Time of Day Friendliness of Server

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Tonight 5 Considerations

Please rate on a scale of 1 to 5, where 5 is excellent and 1 is very poor: the quality of your food tonight the quality of service you received tonight

What was your bill (including tax) today prior to tip? How much of a tip did you leave today? How would you classify your mood today? Good bad __ Did you or anyone in your party consume any alcohol prior to or during your

meal?yes no-

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Appendix B

Dictionary of Variables

Personal attribute variables AGE = age of respondent (continuous) GENDER = gender of respondent (1 = male) OCC = occupation of respondent (0 = professional) INC 1, INC2, INC3, INC4 = income class of respondent (categorical) PHX = respondent is Phoenix resident (0 = Yes) VAC = vacationing in area (0 = Yes)

General attitude variables FREQO = number of times per month dine at this restaurant (continuous) FREQH = frequency of dining out per month (continuous) GENSERVICE = general importance of service in tipping (categorical) GENSPEED = general importance of speed of service in tipping

GENFOOD = general importance of food in tipping (categorical) GENBILL = general importance of bill in tipping (categorical) GENPARTY = general importance of party size in tipping behavior

GENFRIEND = general importance of server friendliness in tipping

GENATT = general restaurant atmosphere in tipping behavior (categorical) TIPAT = anticipated tip (continuous)

(categorical)

(categorical)

(categorical)

Tonight’s attributes, free riding, and social acceptance variables PARTY = number in tonight’s party (continuous) GENPART = PARTY and GENDER interaction QFOOD = quality of food tonight (categorical) SERN = quality of service tonight (categorical) BILLN = size of tonight’s bill (continuous) MOOD = mood tonight (1 = good) ALCOHOL = consumed alcohol tonight (1 = Yes) TIPN = percentage tip tonight (continuous) CREDIT = paid by credit card (1 = cash)