The effects of background music on tipping behavior in a restaurant: A field study

Abstract

Previous research showed that focused listening to music has powerful effects on social behavior. In contrast, the impact of background music appears to depend on moderating factors. The present field study examined the effects of background music on tipping behavior in a restaurant and the possible moderating influence of age of paying guest. Participants were exposed to uplifting, melancholic, or baseline music in the background. Overall, tipping behavior did not differ across quasi-experimental conditions. However, music exposure did interact with age of paying guest. Whereas younger guests’ tipping behavior was not affected by background music, older guests were more generous when exposed to uplifting and melancholic music compared to baseline music. Theoretical and practical implications are discussed.

Keywords

background music music prosocial behavior social influence tipping

Researchers have been interested in the extent to which music influences social behavior. As proposed by the media effects model (Potter & Riddle, 2007), exposure to music should act as a prime that then evokes congruent cognition and behavior. In fact, focused listening to music does affect the listener (foreground music). In one study (Guéguen, Jacobs, & Lamy, 2010), single women between 18 and 20 years were exposed to romantic or neutral music. When asked for their telephone number by a male confederate those exposed to romantic music were more compliant. Other studies addressed the impact of music exposure on helping behavior. For example, participants listened to relaxing, stimulating, aversive music, or no music (Fried & Berkowitz, 1979). Afterwards, their level of cooperation was assessed. Participants that were listening to relaxing music showed the highest cooperativeness, especially compared to participants that were exposed to aversive or no music. More recent research examined the effects of listening to songs with prosocial lyrics (Greitemeyer, 2009a, 2009b). Results suggest that prosocial music exposure increases the accessibility of prosocial thoughts, promotes empathic feelings, and increases helping. Moreover, listening to prosocial music decreases aggression and aggression-related variables (Greitemeyer, 2011). In contrast, listening to violent music has been shown to increase aggression-related cognition, affect (Anderson, Carnagey, & Eubanks, 2003), and behavior (Brummert Lennings & Warburton, 2011). Research has also shown that music exposure can decrease prejudice and discrimination (Bodner & Bergman, 2017; Greitemeyer & Schwab, 2014). Overall, foreground music has been shown to have powerful effects on human behavior (Rentfrow, 2012; Rentfrow & Gosling 2003).

The effects of background music

Music exposure can also have an impact when the music is played in the background. One field study (North, Hargreaves, & McKendrick, 1999) showed that the background music of a supermarket had an impact on purchase decisions. When exposed to German music, people were more likely to buy German wine, whereas French wine was preferred when exposed to French music. Further research (Areni & Kim, 1993) revealed that classical (compared to Top 40) music led to consumers in a wine store purchasing more expensive wine. Milliman (1986) found that patrons in a restaurant ate more slowly when slow music was playing and they spent more money on alcoholic beverages. In another study (North, Tarrant, & Hargreaves, 2004), individuals were exposed to uplifting or annoying music during their fitness workout. When leaving the gym, they were asked if they were willing to hand out flyers for a community of disabled athletes. Individuals who were exposed to uplifting music showed more willingness to help than those who were exposed to annoying music. Most relevant to the present research, background music has been shown to influence tipping behavior (Jacob, Guéguen, & Boulbry, 2010). When prosocial music was in the background guests tipped more compared to neutral or baseline music. Other research has also found that prosocial music in the background increases prosocial outcomes (Ruth, 2017) and decreases aggressive feelings (Böhm, Ruth, & Schramm, 2016).

Yet, some research does not reveal that background music affects people’s everyday life behavior and related cognition and affect. For example, Smith and Curnow (1966) found that loudness of music does not affect sales in supermarkets and customers’ reported satisfaction. An early review (Behne, 1999) showed that about one third of all studies do not reveal significant effects and another third present inconsistent findings. Moreover, more recent studies were more likely to yield non-significant results. Behne argued that because music exposure is increasingly omnipresent in people’s lives, people are getting used to background music and hence less susceptible (habituation effect). Overall, he concluded that background music has no effects. Kämpfe, Sedlmair, and Renkewitz (2011) provided a more recent meta-analytic summary. In a global analysis, they also found a null effect. However, they pointed to potential moderating variables and argued that the effects of background music vary in that they sometimes are beneficial, but at other times there are no effects or even detrimental effects occur (see also Garlin & Owen, 2006). Hence, they argued that the conclusion should not be that background music has no effect, but rather that there is no uniform effect of background music.

The present study

Given mixed findings in previous research, we felt it an important endeavor to provide another test of the impact of background music on people’s social behavior and—as suggested by Kämpfe et al. (2011)—we examined a potential moderating factor. Concretely, we carried out a quasi-experimental study where participants were exposed to uplifting, melancholic, or baseline music (neutral music) in the background. The study was carried out in a restaurant. As a dependent measure, tipping behavior was assessed. Tipping in restaurants is customary practice and is an important source of the waiters’ income. Because tips are voluntary payments of money, part of the underlying motivation is to benefit others (Lynn, 2009, 2015) and can thus be used as a measure of prosocial behavior. Based on previous research showing that both positive and negative mood increase helping behavior compared to neutral mood (Lefevor, Fowers, Ahn, Lang, & Cohen, 2017; Carlson, Charlin, & Miller, 1988; Carlson & Miller, 1987; Yue, Wang, & Groth, 2017), we predicted that both uplifting music and melancholic music would lead to higher gratuity (i.e., more tipping) than baseline music.

Please recall that Behne (1999) argued that because people are exposed to so much music in their everyday life, they are no longer susceptible to the influence of background music. We thus reasoned that background music should have a stronger impact for people less exposed to music in everyday life. Previous research has shown that there are strong age differences in musical engagement. For example, a nationally representative survey (Bonneville-Roussy, Rentfrow, Xu, & Potter, 2013) documented that older people listen to music considerably less often than young people. The analysis also revealed that young people listen to music in different contexts, whereas older people typically listen to music in private. Hence, we predicted that age of the paying guest would interact with music condition, in that older guests would be more generous when exposed to uplifting or melancholic music in the background (relative to baseline music). In contrast, younger guests should be less affected by the different kinds of background music.

Method

The present field study took place in a restaurant near Munich (Germany). The restaurant specializes in Austrian food and wines with Italian and Bavarian influences and targets guests from middle to upper class. Data collection was carried out over a period of a little more than 2 months, with the aim of running as many participants as possible. The restaurant was open six days a week (on Mondays it was closed). Opening hours were from 6 p.m. to around 10.30 p.m. On each evening, the music of one of three playlists (see below) was played.

Materials and realization

There were three quasi-experimental conditions. The first condition contained uplifting music, the second condition contained melancholic songs, and the third (control) condition contained music that was usually played in the restaurant (baseline music). All songs were relatively unknown. Six independent acquaintances of the first author (three female and three male, with an age range from 20 to 60) evaluated a variety of songs in terms of whether they were uplifting or melancholic (taken from the playing list of the restaurant). Songs on which all agreed were put into the final playlist. The titles in the control group were selected randomly from the playlist of the restaurant. In the end, each playlist contained 70 categorized titles plus around 40 instrumentals by a pianist. One of the three playlists was used for two consecutive weeks, followed by the other playlists that were also used for the same period. The order of the three playlists was randomly determined.

As dependent measure, tipping behavior was assessed. Because amount of tipping varies considerably as a function of the total bill, tipping percentage of the total bill was recorded. When patrons split the bill, each tipping percentage was recorded separately. We also assessed the approximate age of the paying guest (separated in two age groups, see below). As control variables, number of guests at the table, gender of the paying guest, the composition of the guests (i.e., a couple, a family, friends, or business people visiting the restaurant), and gender of the waiter were recorded.

Sample

There were 277 paying guests, 91 women and 186 men. The entire sample, including the people paying the bills as well as all the other guests at their table, consisted of 813 individuals, 435 women and 378 men. Hence, although there were more women visiting the restaurant overall, men were more likely settling the bill. Regarding estimated age of the paying guest, we decided to compare individuals younger and older than retirement age (which is around 65 years where the study took place). Two-hundred and thirty-nine paying guests were up to 65 years, and 38 were older than 65 years. Age of paying guest was estimated by at least two employees of the restaurant; any discrepancies were resolved by discussion.

Results

The impact of background music on tipping rate was examined in a 3 (music: uplifting vs. melancholic vs. baseline) × 2 (age of paying guest: younger vs. older) analysis of covariance (ANCOVA). (Because of the quasi-experimental design, we decided to include all control variables in the analysis.) This analysis revealed that the experimental conditions did not differ in the extent to which tipping behavior was elicited, F(2, 264) = 1.97, p = .141, η² = .02. The corresponding means and standard deviations were: uplifting music (M = 8.18, SD = 3.50), melancholic music (M = 8.72, SD = 3.91), baseline music (M = 8.20, SD = 3.12). The main effect of age of paying guest was also not significant, F(1, 264) = 1.32, p = .252, η² = .01.

In contrast, the interaction between experimental condition and age of paying guest was significant, F(2, 264) = 4.33, p = .014, η² = .03. Whereas younger guests were not affected by the different kinds of background music, F(2, 236) = 0.67, p = .515, η² = .01, there was a trend that older guests were, F(2, 35) = 3.21, p = .053, η² = .16. As predicted, tipping rate was greatest in the uplifting condition, followed by the melancholic and the baseline condition (see Table 1). Of the control variables, number of guests at the table was negatively associated with tipping rate, F(1, 264) = 5.41, p = .021, η² = .02, showing that larger parties left smaller percentages. Gender of the paying guest, the composition of the guests, and gender of the waiter were not associated with tipping rate, all ps > .333.

Table 1.

Mean tipping rate and standard deviation (in parentheses) as a function of background music and age of paying guest.

Background music	Age of paying guest
Background music	Younger	Older
Uplifting	7.99 (3.51)	10.96 (5.12)
Melancholic	8.64 (3.80)	9.73 (5.45)
Baseline	8.39 (3.20)	7.18 (2.48)

In ancillary analyses, we examined the interplay between gender of the paying guest and gender of the waiter. An ANOVA revealed a significant interaction, F(1, 273) = 4.63, p = .032, η² = .02. Whereas male guests were more generous toward female waiters (M = 8.68, SD = 3.13) compared to male waiters (M = 7.21, SD = 2.63), t(184) = 2.31, p = .022, d = 0.51, there was a trend in the opposite direction for female guests (female waiter: M = 8.26, SD = 4.57; male waiter: M = 9.98, SD = 4.83), t(89) = 1.06, p = .290, d = 0.37.

Discussion

Given the well-known finding that positive and negative mood compared to neutral mood increase helping behavior (Carlson et al., 1988; Carlson & Miller, 1987), we reasoned that uplifting and melancholic music may lead to greater tipping rate. However, the effect of background music on gratuity was nonsignificant and the effect size was close to zero. That the overall effect of background music on social behavior is quite small has also been shown by previous meta-analytic summaries (Behne, 1999; Kämpfe et al., 2011). Hence, our study provides further support for the notion that people are hardly affected by music in the background.

However, our study also documented that the different kinds of music did affect some of the guests. In fact, whereas younger guests’ tipping behavior was not affected by the different kinds of background music, older guests were more generous when exposed to uplifting and melancholic music compared to baseline music. Because older individuals are not as exposed to music as opposed to other demographics (Bonneville-Roussy et al., 2013), this pattern of findings is in line with Behne’s (1999) habituation hypothesis. Moreover, the interactive effect appeared to be unaffected by some control variables, such as gender of the paying guest and gender of the waiter. Most importantly, although we found that number of guests at the table was negatively associated with tipping rate, which is a replication of previous research (e.g., Freeman, Walker, Borden, & Latané, 1975), size of dining party did not account for the finding that older guests more than younger guests were affected by the different kinds of background music.

Nevertheless, whether differences in habituation indeed account for the interactive effect is unclear. Older compared to younger guests in the restaurant might have simply listened more to the background music, so the music was more on the foreground and hence had more of an impact. In this regard, future research may expose people of different ages to background music and assess afterwards to what extent they were aware of the music. It should be also noted that although the interaction effect was significant, the simple effect comparing the three experimental conditions for the older guests only was only marginally significant. However, the effect size was large (η² = .16), so if the sample size was bigger, this result might have been significant.

Please also note that the customers could not be randomly assigned to the experimental conditions (i.e., at one time point, all customers were exposed to the same type of background music). That is, like previous research that has investigated the effects of background music in the field (e.g., Jacob et al., 2010; North et al., 1999; Ruth, 2017), our study is a quasi-experiment rather than an experiment. Therefore, it may well be that factors such as method of payment, weather at the time, consumption of alcohol, time spent in the restaurant, and whether the customer was a “regular” were unevenly distributed across the background music conditions and/or age of paying guest. For example, it has been shown that restaurant patrons leave larger tips on sunny days (Cunningham, 1979). If older guests were more likely to be at the restaurant when the music was uplifting or melancholic (rather than the baseline condition) and when the sun was shining, it is unclear whether their tipping behavior was influenced by the background music or the weather. Future research that attempts to replicate our findings in the lab where participants can be randomly assigned to different background conditions would be welcome.

Future research may also attempt to replicate the moderating effect of age of listener. For example, according to recent theorizing (Rentfrow, Goldberg, & Levitin, 2011), there are five different styles of music preferences: mellow, unpretentious, sophisticated, intense, and contemporary. Recent research has shown that focused listening to intense music is positively related to recreational risk-taking but negatively related to social risk-taking (Enström & Schmaltz, 2017). It would be interesting to examine whether intense music in the background has similar effects on risk-taking and whether older people would be more susceptible than younger ones.

Conclusion

As predicted from Behne’s (1999) habituation hypothesis, we found support for the idea that individuals who are less exposed to music in their everyday life are more susceptible to different kinds of background music. These observed differences across experimental conditions were not without implications for the waiters. The typical bill for two people in the restaurant where the study took place is around 100 euros so the waiter received almost 4 euros more as a tip from an older guest when uplifting music was in the background, rather than the typical baseline music. Hence, although not everyone is affected, background music can produce (beneficial) effects.

Footnotes

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

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