2003
DOI: 10.1111/j.1559-1816.2003.tb01973.x
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Ethnic Differences in Tipping: Evidence, Explanations, and Implications

Abstract: Anecdotal evidence suggests that many waiters and waitresses deliver poor service to ethnic minorities because they believe that ethnic minorities are poor tippers. How managers should deal with this problem depends in part on whether or not ethnic minorities really do tip less than Whites and (if they do) on when and why this occurs. This paper reports on 2 studies that address these issues. The results indicate that Asians tip less than do Whites in comparisons across (but not within) restaurants and that Bl… Show more

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Cited by 63 publications
(120 citation statements)
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“…The primary emphasis of these studies has been on ethnic differences in tipping (cf. Harris, 1995;Lynn and Thomas-Haysbert, 2003;Lynn, 2004a,b;Noll and Arnold, 2004). The findings have been generally consistent that African-Americans tip less (as a percentage of total bill size) than Caucasian or other ethnic groups (i.e., Asian, Hispanic).…”
Section: Introductionmentioning
confidence: 76%
“…The primary emphasis of these studies has been on ethnic differences in tipping (cf. Harris, 1995;Lynn and Thomas-Haysbert, 2003;Lynn, 2004a,b;Noll and Arnold, 2004). The findings have been generally consistent that African-Americans tip less (as a percentage of total bill size) than Caucasian or other ethnic groups (i.e., Asian, Hispanic).…”
Section: Introductionmentioning
confidence: 76%
“…However, a grateful disposition was associated with a greater likelihood of non-restaurant tipping and this effect was sizably reduced after controlling for motivation, so the intrinsic motives associated with a grateful disposition appear to mediate the effects of that disposition on non-restaurant tipping. Previously shown demographic effects on tipping (see Lynn and Thomas-Haysbert, 2003) were replicated -i.e., more educated, wealthier, and White consumers based restaurant tips on bill size more than others and younger, more educated, wealthier, and White consumers left larger restaurant percentage tips. These demographic effects on tipping behavior were not sizably diminished after statistically controlling for motivation, so tipping motives do not appear to mediate these effects.…”
Section: Tablementioning
confidence: 83%
“…This existing research has largely focused on situational determinants of tip size (e.g., Conlin et al, 2003) with a few studies focusing on the effects of consumer demographic (e.g., Lynn and Thomas-Haysbert, 2003) and personality (e.g., Lynn, 2008) characteristics. Very little research has examined the determinants and consequences of individual differences in consumers' motivations or reasons for tipping and the two studies on this topic that do exist have features that limit their contributions.…”
Section: Introductionmentioning
confidence: 99%
“…However, this study also pointed to a high level of variability among individual respondents and noted that while most respondents increased tips at higher levels of service, this pattern of behavior was not consistent across all study participants. Although a number of studies have made a case for the impact of certain demographic characteristics on the likelihood of tipping or the amount of tip given (Brewster and Mallinson, 2009;Kerr and Domazlicky, 2009;Lynn, 2004aLynn, ,b, 2009Lynn and Thomas-Haysbert, 2003), demographics were not shown to impact on the underlying motivations for engaging in tipping behavior in the single study where motivations were examined (Lynn, 2009). …”
Section: Economic Researchmentioning
confidence: 93%
“…Hierarchical regression was selected in this case so that we could control for both ethnicity (Brewster and Mallinson, 2009;Kerr and Domazlicky, 2009;Lynn, 2004aLynn, ,b, 2006Lynn and Thomas-Haysbert, 2003) and whether the participant had ever worked in the service industry (Rogelberg et al, 1999;Conlin et al, 2003;Harris, 1995). A fourth dependent variable, the range of tip size between exceptional and poor service, was also created from the existing data.…”
Section: Stage 3: Predictive Modelmentioning
confidence: 99%