The psychology of sunk cost: A classroom experiment

Abstract

Economics and business students are taught that sunk costs are irrelevant to their decisions. Yet, there is ample evidence that managers fail to integrate this simple rule and fall prey to what is known as the sunk-costs bias. To mitigate cognitive biases, such as the sunk-cost bias, educators must raise students’ awareness of these common judgment errors. In this article, the author proposes a classroom activity that actively engages students and allows them to identify this bias in their own judgments. The activity builds on a series of experiments from the psychology literature. The author discusses how these experiments have been adapted for classroom use and presents evidence suggesting that the activity increased students’ awareness of the sunk-cost bias and improved their decision-making skills.

Keywords:

• Active learning
• audience response system
• clickers
• cognitive bias
• escalation of commitment
• sunk-cost bias

JEL codes:

• A2
• D01
• D91
• G31
• M21
• M41

Notes

Notes

1 Arkes (1991), Simonson and Staw (1992) and Ghosh (1997), among others, present a series of debiasing techniques to mitigate the sunk-cost effect. A more recent paper by Denison (2009) also provides additional references.

2 In any case, Part I should be administered before any class discussion on the topic of relevant costs for decision-making, such as the concepts of sunk costs and opportunity costs. This could otherwise condition students’ responses and ultimately prevent them from witnessing their own bias. I have experienced similar results with both pre- and in-class approaches.

3 A separate appendix describing further key determinants and debiasing techniques identified in the literature, along with suggestions on how these concepts can be linked to many key topics in economics and management and integrated to complement the class discussion, is available upon request. This appendix also presents several examples illustrative of the sunk-cost bias in a variety of settings.

4 Similarly, several students expressing “no difference” explicitly state that they selected “no preference” because they knew it was the correct (rational) answer, although they felt discomfort with that decision.

5 Instructors can always expect a very small percentage of students choosing the lowest cost pizza and can jokingly refer to these as the “bargain hunters” who pride themselves on buying goods at a discount.

6 Importantly, there were no differences between the sections in the pre-activity (pre-class) survey and the topic of relevant costs for decision-making, including sunk-costs bias, received equal class time. The results from Arkes and Blumer’s (1985) experiments were discussed in all groups.

7 Evidence of sunk-cost bias associated with progress decisions comes mostly from case studies of failed projects and cost overruns in major public and civil engineering projects (e.g., Ross and Staw 1986, 1993; Drummond 1996; Montealegre and Keil 2000).

8 Related settings include membership fees and two-part pricing schemes (Thaler 1980, Example 5; Dick and Lord 1998; Soman and Gourville 1998, Study 4; Jang, Mattila, and Bai 2007), and use of costly information (Gino 2008; Robalo and Sayag 2018). There is also evidence of sunk-cost bias in relation to utilization decisions from natural experiments and field studies; for example, car usage (Ho, Png, and Reza 2018), seller behavior in housing markets (Ratnadiwakara and Yerramilli 2017), and food consumption in an all-you-can-eat restaurant (Just and Wansink 2011). Finally, classic examples include the ski trip scenario used by Arkes and Blumer (1985, Experiments 1, 9 and 10), the theatre ticket example (Arkes and Blumer 1985, Experiment 2), and the basketball game and snowstorm example in Thaler (1980, Example 4).

9 The detailed measures (questions) for the Adult Decision-Making Competence index are available online at: http://www.sjdm.org/dmidi/files/AdultDMCwithoutPathIndep.pdf or at http://sds.hss.cmu.edu/risk/ADMC.htm.