Introduction

Atmospherics: “the effort to design buying environments to produce specific emotional effects in the buyer that enhance purchase probability” (Kotler, 1973, pp. 48-64). As a Computer and Software Systems major, I take a personal interest in meticulous design principles. More specifically, I am interested in how engineering a piece of software can impact a user’s behaviour with that software. I sought to understand a similar interaction with music. How can a musical environment be designed to influence consumers? How can music be used as an atmospheric variable?

My specific interest in consumers can be attributed to my time at university. One of the subjects I took was Introductory Microeconomics, which delves deep into the psychological influences of buying and selling. Naturally, this led me to question consumers' buying behaviour and how much impact a company has over its consumers. As a prime example, how could Apple, out of all companies, price their products at a premium and still convince a large population to buy them? This investigation also explores my justification and belief in an anti-consumerist culture. That is, to consciously consider the implications of buying products.

I expected to find that music played a role in the influence, but the question lay in how influential music was from a research point of view and what types of music would work best. Luckily, there were a few critical researchers in developing this field, Adrian North and David J. Hargreaves, who have worked on many papers jointly.

North and Hargreaves focused on the impact of music on consumer behaviour in commercial settings such as retail, restaurants and supermarkets. One of their most notable papers explored the concept of musical ‘fit’ in which they showed that customers preferred different wines depending on the music played on that day. Customers preferred German wine on German music days and French wine on French music days (North et al., 1997). Naturally, the two sought to discover which types of music would influence how much consumers were willing to pay. So they conducted research in a student cafeteria and found that classical and pop music influenced increased willingness to pay (North & Hargreaves, 1998). Their results were similar to that of another critical researcher Charles Areni, who found that classical music increased the purchase of more expensive wines (Areni & Kim, 1993). However, Areni argued that classical music may not work in all contexts and needed to ‘fit’ the scene, as it did for the wine store (frequently associated with luxurious living).

Rationales

To further explore the field of music and consumption, the following will be a critical review of three studies in this field:

1. “The influence of background music on the behavior of restaurant patrons” (Milliman, 1986).
2. “The effects of music on atmosphere in a bank and a bar” (North et al., 2000).
3. “The effect of musical style on restaurant customers’ spending” (North et al., 2003).

The literature referenced in each paper makes a case for its importance. More specifically, all articles argue that there is not enough research in the field and hence set the stage for the results of their studies.

All three papers provide well-established literature in support of their remarks and provide many relevant citations to give a rich overview of the field at the time. In the case of Milliman (1986) and North et al. (2000), they both make mention of Kotler’s (1973) “atmospherics”, signalling their joint agreement as to when the field of music and consumption was first established. However, North et al. (2003) do not mention this. They instead cite back to Milliman (1986) and other notable works in this field, such as Areni and Kim (1993) and North and Hargreaves (1998).

Out of the three papers, Milliman’s (1986) paper distinctively makes a note of the Mehrabian/Russel model and its importance in understanding the tendency of consumers to “approach” or “avoid”. Using this model and one of his previous studies (which is on the relationship between music tempo and the speed at which customers eat at restaurants), he explains the importance of further developing the field with this model in mind. Personally, the Mehrabian/Russel model that Milliman explains is intriguing enough on its own for research, so his justification for his paper is convincing.

As for the North et al. (2000) and North et al. (2003) papers, they are both quite similar in structure and references. They both explore the impact of music genre on consumer behaviour with the same three scenarios: classical music, pop music and no music. However, the significant difference was in the research location, either in a restaurant or a bank and bar, which they mention to be a “more representative commercial environment than an on-campus cafeteria” (North et al., 2000, p. 1506). The student cafeteria that they are referring to is from a previous study (North & Hargreaves, 1998). Since students are, on average, relatively poor, their findings on the effectiveness of music in the student cafeteria may have been affected by bias in a cohort’s purchasing values. So the motivation to conduct research in a more commercial environment like a bank/bar or restaurant is justified.

Methods

All three papers thoroughly explain the methods with well-defined sections detailing the design and procedure. However, some crucial aspects of each paper needed more explanation.

While Milliman (1986) did mention that there were exogenous factors such as “other environmental conditions, employee assignments”, he did not mention an exhaustive list of those factors. Without a complete list, it is easy to overlook any confounding variables. He also did not mention any specific music played but only noted that it was “exclusively instrumental pieces”. He provided his reasonable justification stating that he could reduce his concern for certain exogenous factors when “no consideration had to be given to female versus male vocalist, to well-known … versus lesser known … artists”. Additionally, it is unclear why Milliman obtained two data sources (one recorded by graduate students and the other from restaurant staff members). There should have been some justification stating that multiple sources could reduce biases.

North et al. (2000) was slightly more detailed in its method. Notably, a complete list of music chosen played at the bank and bar was provided in Appendix A, while Milliman (1986) provided no list. However, there was no mention of controlling the bank staff, unlike Milliman, who kept employee work days constant. So, an employee at the bank may affect a customer’s perception of the bank and contaminate results. Out of the three papers, North et al. (2000) is the only study which collected data in the form of a survey to customers. An exhaustive list of survey questions was not provided, which would have been helpful to ensure that data was not biassed. They also mentioned that “customers were approached with the questionnaire as they walked toward the exit”. If I were a customer expecting to leave a bank but then were blocked exit by a researcher, I would probably be impatient and hastily answer the questions, which may also bias data, especially when the research is about perceptions of the bank. How many customers would have done the same? However, I appreciate the authors mentioning and comparing their current method to their previous cafeteria study (North & Hargreaves, 1998) and how they justified any improvements they made from the cafeteria study.

North et al. (2003) was as detailed in its method as North et al. (2000). The listing of music used is commendable; however, it would have been nicer in an appendix like their previous paper. The data collected in North et al.’s (2003) paper are all transactional similar to the ones by Milliman (1986), namely the tracking of “total amount spent on food, total amount spent on drinks, and total overall spend” (North et al., 2003, p. 714). The mention of the “Latin square design” signifies a good understanding of experimental design processes, and the detailed description of the restaurant provides a well-rounded picture of the research location.

Overall, the three papers did an excellent job explaining the procedure and experimental design, despite the missing music playlist by Milliman (1986). However, Milliman provided a better dataset than North et al. (2000) and North et al. (2003), as Milliman’s study was over eight weeks compared to the other two papers, which were only three weeks each.

Findings

Each paper explored slightly different aspects of music as an atmospheric variable. Milliman’s study (1986) concluded that the difference in the tempo of music played at a restaurant affected the speed at which customers ate, similar to his previous findings. North et al.’s study (2000) confirmed a positive correlation between music ratings and banking hall ratings, which means that if customers perceived the music as more fun, the bank would also be more fun. North et al.’s further study (2003) focused their findings on classical music, concluding that out of the three types of music (classical, pop and no music), classical music seemed to cause the highest spending.

Milliman found it interesting “that the number of customer groups that left the restaurant before being seated remained about the same whether slow- or fast-tempo music was playing at the time” (Milliman, 1986, p. 288). He explained this interest in relation to a different study and explained how it contradicted his result – that “ill-suited” music did not affect restaurant patrons. However, he did not mention why their studies contradicted or what his definition of  “ill-suited” music was. One possible explanation could have been that customer groups may have been more focused on getting a reservation than listening to a restaurant's music. Additionally, Milliman provides an expansive area of further research, stating that factors other than music, such as “carpeting, wall decor, temperature”, can be compared with “various consumer groups–young vs. middle-aged vs. old” (Milliman, 1986, p. 289). Although it is commendable to have such an expansive area of further research, his answer lacks relevance to music psychology. It seems he wants to lead his study toward researching other atmospheric variables on consumer behaviour.

North et al.’s study (2000) explained how they processed data in much more detail than Milliman. North’s team explained their results using statistical jargon, such as with terms like “MANOVA” and “factor analysis”, which is helpful to those that understand but can be challenging to unfamiliar readers. In the discussion, they explained their “positive correlation” result with this jargon and made a convincing argument for it (North et al., 2000, p. 1510). Additionally, it was nice to see that they compared the “four factors” they generated by comparing them to their cafeteria study (North et al., 2000, p. 1510), indicating the overall consistent outcomes of their research.

Similar to the previous study, North et al. (2003) used jargon such as “MANCOVA” and “ANCOVA” to explain their research results. The writing has much the same detail as the previous research, so the conclusion they gathered was reputable. They concluded that “classical music gave rise to the greatest spending” (North et al., 2003, p. 716) and then proceeded to discuss why classical music was so effective. They highlighted three potential reasons and stated their favourite, showing their ability to explain their outcome (North et al., 2003, p. 717).

Conclusion

Overall, the three papers discussed provided detailed insight into music and its influence on consumer behaviour. Firstly, all three studies have well-defined research motives. Additionally, they all have clear and consistent research designs, which enable a comparison of their results. Secondly, they all use well-established methods of data collection and analysis, such as observation and self-report surveys, which enhance the validity of their findings. Thirdly, all three studies provide a rich overview of the field and provide many relevant citations to support their remarks, strengthening the reliability of their results.

A limitation that is apparent in all three studies is their small sample size, affecting the generalisability of results. In order to extend their findings, future studies should include a more extensive and diverse sample. Another area for improvement is the small scope of the studies. They all focus on classical and pop music and do not consider the impact of other music genres on consumer behavior. Furthermore, they do not examine the impact of different music styles within the classical and pop music genres, such as fast or slow-tempo instrumentals. Finally, all studies do not consider individual differences in musical preferences, which may affect how music affects consumer behaviour.

Future research should address these limitations by increasing sample size and diversity, expanding the scope of the studies to include a broader range of music genres, examining individual differences in musical preferences, and conducting more studies in different commercial settings. Overall, these studies have provided valuable insights. However, further research can deepen our understanding of the role of music in shaping consumer behaviour and help businesses create more effective atmospheric environments.

References

Areni, C. S., & Kim, D. (1993). The influence of background music on shopping behavior: classical versus top-forty music in a wine store. ACR North American Advances.

Kotler, P. (1973). Atmospherics as a marketing tool. Journal of retailing, 49(4), 48–64.

Milliman, R. E. (1986). The influence of background music on the behavior of restaurant patrons. Journal of consumer research, 13(2), 286-289.

North, A. C., & Hargreaves, D. J. (1998). The effect of music on atmosphere and purchase intentions in a cafeteria. Journal of applied social psychology, 28(24), 2254–2273.

North, A. C., Hargreaves, D. J., & McKendrick, J. (1997). In-store music affects product choice. Nature, 390(6656), 132–132.

North, A. C., Hargreaves, D. J., & McKendrick, J. (2000). The Effects of Music on Atmosphere in a Bank and a Bar. Journal of Applied Social Psychology, 30(7), 1504–1522.

North, A. C., Shilcock, A., & Hargreaves, D. J. (2003). The effect of musical style on restaurant customers' spending. Environment and behavior, 35(5), 712–718.