David P. Daniels
Selected Recent Research
The streak-end rule: How past experiences shape decisions about future behaviors in a large-scale natural field experiment with volunteer crisis counselors
Kang, P., Daniels, D. P., & Schweitzer, M. E. (Forthcoming). Proceedings of the National Academy of Sciences.
Decisions about future behaviors are clearly shaped by the content of past experiences, but whether the order of past experiences matters remains controversial. By analyzing the largest field experiment about prosocial behavior to date, a natural field experiment involving 14,383 volunteer crisis counselors over five years, we examine how the content and order of past experiences causally influence decisions about future behaviors – whether individuals continue volunteering or quit. Volunteers were repeatedly and randomly assigned to perform 1,976,649 prosocial behaviors that were either harder (suicide conversations) or easier (non-suicide conversations). We found that the content of past experiences mattered: Harder (versus easier) behaviors encouraged quitting. However, the order of past experiences mattered far beyond their content alone: Harder behaviors caused disproportionately more quitting if they came in long “streaks” or at the “end.” These “streak”/“end” effects reveal important practical insights for leaders and policymakers seeking to boost prosocial behavior. For instance, a simple reordering intervention – assigning behaviors so as to avoid creating hard “streaks” – would reduce volunteer quitting rates by at least 22% (more than double the impact of previous behavioral interventions), boosting prosocial behavior and likely saving lives.
The magnitude heuristic: Larger differences increase perceived causality
Daniels, D. P. & Kupor, D. (Forthcoming). Journal of Consumer Research.
With the rise of machine learning and “big data,” many large yet spurious relationships between variables are discovered, leveraged by marketing communications, and publicized in the media. Thus, consumers are increasingly exposed to many large-magnitude relationships between variables that do not signal causal effects. This exposure may carry a substantial cost. Seven studies demonstrate that the magnitudes of relationships between variables can distort consumers’ judgments about whether those relationships reflect causal effects. Specifically, consumers often use a magnitude heuristic: Consumers infer that relationships with larger perceived magnitudes are more likely to reflect causal effects, even when this is not true (and even when correlation is held constant). In many situations, relying on the magnitude heuristic will distort causality judgments, such as when large-magnitude relationships between variables are spurious, or when normatively extraneous factors (e.g., reference points) distort perceptions of magnitudes. Moreover, magnitude-distorted (mis)perceptions of causality in turn distort consumers’ purchase and consumption decisions. Since consumers often encounter spurious relationships with large magnitudes in the health domain and in other consequential domains, the magnitude heuristic is likely to lead to biases in some of consumers’ most important decisions.
Choice architects reveal a bias toward positivity and certainty
Daniels, D. P. & Zlatev, J. J. (2019). Organizational Behavior and Human Decision Processes, 151, 132-149.
Biases influence important decisions, but little is known about whether and how individuals try to exploit others’ biases in strategic interactions. Choice architects—that is, people who present choices to others—must often decide between presenting choice sets with positive or certain options (influencing others toward safer options) versus presenting choice sets with negative or risky options (influencing others toward riskier options). We show that choice architects’ influence strategies are distorted toward presenting choice sets with positive or certain options, across thirteen studies involving diverse samples (executives, law/business/medical students, adults) and contexts (public policy, business, medicine). These distortions appear to primarily reflect decision biases rather than social preferences, and they can cause choice architects to use influence strategies that backfire.