Researchers in the social sciences have increasingly studied how emotions influence decision-making. We argue that research on emotions arising naturally in real-world environments is critical for the generalizability of insights in this domain, and therefore to the development of this field. Given this, we argue for the increased use of the “quasi-field experiment” methodology, in which participants make decisions or complete tasks after as-if-random real-world events determine their emotional state. We begin by providing the first critical review of this emerging literature, which shows that real-world events provide emotional shocks that are at least as strong as what can ethically be induced under laboratory conditions. However, we also find that most previous quasi-field experiment studies use statistical techniques that may result in biased estimates. We propose a more statistically-robust approach, and illustrate it using an experiment on negative emotion and risk-taking, in which sports fans completed risk-elicitation tasks immediately after watching a series of NFL games. Overall, we argue that when appropriate statistical methods are used, the quasi-field experiment methodology represents a powerful approach for studying the impact of emotion on decision-making.
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Syon Bhanot, D. Chang, J. L. Cunningham, and M. Ranson.
"Emotions And Decisions In The Real World: What Can We Learn From Quasi-Field Experiments?".