Antonia Shroder (M’20) majored in Social Science concentrating in Cognition, Brain, and Behavior as well as Economics and Society. She used her Capstone Project to research the underlying factors that impact our perception of waiting time when waiting in lines. This is the executive summary of her project.


This Capstone identified a lack of research on the relationship between peak emotions and perceived waiting time in convenient lines. Perceived waiting time is a crucial component of customer satisfaction and therefore of great interest to businesses. This Capstone proposed a novel experiment to test the relationship between peak emotions and perceived waiting time.


Maximising customer satisfaction is of inherent interest to a business, as a satisfied customer is more likely to also become a future customer. Future customers in turn, are essential for continued profits. The amount of time a customer has to wait is a crucial component of overall customer satisfaction (Davis & Vollmann, 1990). In regard to most necessity goods, a higher waiting time impacts customer satisfaction negatively and vice versa (Pruyn & Smidts, 1998).

However, research has found that perceived waiting time, and not objective waiting time, is a better predictor for customer satisfaction (Tom and Lucey, 1997). In other words, it is not how long people have to wait, but how long they think they have to wait, which has the biggest impact on their satisfaction as a customer.

There are many different elements which impact the perception of one’s waiting time. A key influencer is the environmental surrounding, such as the attractiveness of the room, or the presence of a television (Pruyn & Smidts, 1998). Another influencer is the auditory environment, where some form of auditory stimulation will shorten the perceived waiting time (Hirsh, Bilger & Deatherage 1956). Personal differences will also alter one’s perception of waiting time; for example, a higher income will often make the wait more costly (Becker, 1966).

Many elements of perceived waiting time are well understood. Yet, there is no overarching theory which explains how different occurrences during the waiting period might alter one’s perception. According to Kahneman’s peak-end rule, people encode experiences by looking at the peak emotion experienced and the end emotion experienced (Kahneman et al, 1993). For example, during an otherwise pleasant vacation, one might get robbed on the beach, and the flight on the way back is delayed. Here both the peak and the end emotion are negative, leading to the vacation being remembered negatively.

In most convenient lines, such as supermarkets and banks, the end experience remains the same, as one attains what one has been waiting for. This would indicate that the peak emotion has a significant impact on how the experience is remembered. There are many elements of the actual waiting experience which are either clearly positive or negative. A positive personal interaction has been found to increase customer satisfaction regardless of associated enhanced waiting time (Tom and Lucey, 1997). On the other hand, injustices experienced while waiting, such as someone skipping the line, decreases customer satisfaction (Larson, 1987). However, there has been no research to my knowledge affirming the link between these peak experiences and the perception of waiting time. Yet, it seems that a positive peak increases overall satisfaction, which could mean the waiting period is perceived to be less, and vice versa.


A positive peak emotion experienced while waiting in a convenient line will reduce one’s perceived waiting time, while a negative peak emotion will increase one’s perceived waiting time. In other words, the peak emotion experienced while waiting in line has an impact on the perception of waiting time and therefore customer satisfaction.

Experimental Design

To test the hypothesis, subjects will be randomly allocated into three different groups. The two treatment groups will be subjected to either positive or negative stimuli to elicit a positive or negative peak emotion. The control group will be subjected to neutral stimuli. Afterwards the participants will be asked how long they think they waited, and the relationship between the assigned stimuli and the perceived waiting time will be analysed to test the stated hypothesis.

The subjects will be exposed to auditory stimuli to elicit a peak emotion. Emotional affect of a stimuli differs widely between people (Goldstein & Naglieri, 2011). However, auditory stimuli can be introduced in a more subtle manner, which reduces discrepancies. To further overcome personal differences, auditory stimuli with a crowdsourced affect will be employed. This avoids individual researchers deciding the affect (Bradley & Lang, 2015). The survey at the end of the experiment will also ask about how participants perceived the experience, to further account for individual differences.

Participants will be told that the study is researching attention and cognitive flexibility. The partial disclosure of the true purpose prevents participant’s from focusing on their waiting time. Participants will be asked to wait in three different locations, such as three different hallways. The most important element is that the three locations are audibly shielded from each other. In these locations, the participants wait to be let into the room and participate in the study. However, unbeknownst to them, the true experiment takes place while they are waiting to be let into the room. Participants waiting will be asked to stand and not interact with each other to avoid confounding each other’s experience, while simulating the experience of standing in a convenient line. During this waiting time, participants are exposed to the assigned auditory stimuli eliciting their peak experience. The auditory stimuli will be administered at different times for different people, to test for whether the timing of the peak has a differentiating impact.

Once in the room, participants will be asked to complete the ‘Stroop Test’, which is a simple Psychology test requiring participants to repeatedly call out the colour a colour is written in on a screen (MacLeod, 1991). This test is a mere distraction and was chosen for its minimal cognitive load imposition, as well as its short duration. After completing, the subjects will be asked to fill out a survey evaluating their lab experience. This survey entails, among other elements, a question about how long they think they waited, which is a crucial question for the subsequent analysis. Again, this survey is disguised as a laboratory evaluation to avert unwanted focus from the objective waiting time. Subjects will be briefed on the true purpose of the experiment after submitting the survey.

The external validity of this study would be enhanced if this study were to take place in a field experiment, such as an actual convenient line. However, in real-life convenient lines there are many uncontrollable factors which could change the peak experience away from the assigned group. Hence, given the sensitivity of peak experiences, a lab experiment should be employed first as a proof of concept, as this setting allows one to more easily control external stimuli. This experiment has been designed with the intent of approximating an actual convenient line .


If the stated hypothesis holds true, a positive peak experience could reduce someone’s perception of waiting time, which in turn improves the customer’s satisfaction.

In a supermarket this could mean that if faced with an unexpected influx of customers, free samples could be given out. Assuming that free samples are a positive peak, this could reduce the customer’s perceived waiting time without negotiating natural caps such as number of staff present. Similar interventions could be executed in any convenient line.

There are countless everyday scenarios where waiting is required. These findings, if found to be true, could lessen suffering in small ways, whether in hospitals, soup kitchens, or at sporting events. The potential for applications are numerous


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Bradley , M., & Lang, P. (2015). The Center for the Study of Emotion and Attention. Retrieved December 12, 2019, from

Davis, M., & Vollmann, T. (1990). A framework for relating waiting time and customer satisfaction in a service operation. Journal of Services Marketing, 4(1), 61-69. doi:10.1108/EUM0000000002506

Goldstein, Sam, & Naglieri Jack A., eds. (2011). Encyclopedia of Child Behavior and Development. Boston, MA: Springer US. (December 12, 2019).

Hirsh, I. J., R. C. Bilger, and B. H. Deatherage. (1956). ‘The Effect of Auditory and Visual Background on Apparent Duration’. The American Journal of Psychology 69(4): 561–74.

Kahneman, D., Fredrickson, B., Schreiber, C., & Redelmeier, D. (1993). When more pain is preferred to less: Adding a better end. Psychological Science, 4(6), 401-405. (December 12, 2019).

Larson, Richard C. (1987). ‘Perspectives On Queues: Social Justice and the Psychology’. Operations Research; Linthicum 35(6): 895.

MacLeod, C.M. (1991). Half a century of research on the Stroop effect: An integrative review. Psychological Bulletin, 109, 163-203.

Pruyn, Ad, & Smidts, Ale. (1998). ‘Effects of Waiting on the Satisfaction with the Service: Beyond Objective Time Measures’. International Journal of Research in Marketing 15(4): 321–34.

Tom, Gail, & Lucey, Scott. (1997). ‘A Field Study Investigating the Effect of Waiting Time on Customer Satisfaction’. Journal of Psychology; Provincetown, Mass., etc. 131(6): 655–660.

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