Forecasted vs. Actual Generosity in Image-Concern Interventions

• 成果类型: Article; Early Access
• 署名作者: Jung, Minah H.; Saccardo, Silvia; Gneezy, Ayelet; Nelson, Leif D.
• 署名单位: New York University; Carnegie Mellon University; University of California System; University of California San Diego; University of California System; University of California Berkeley
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2023.00149
• 发表日期: 2025
• 关键词: Field experiments; Image concerns; pay what you want; prosocial behavior; forecasting

摘要

Prior research and lay intuition suggest that amplifying image concerns promotes generosity. We test the impact of image-based interventions in consumer elective pricing (CEP), where individuals choose how much to pay for products or services. Across 10 studies (nine field experiments and one laboratory study, n = 3,182), we examine the effects of these interventions on payments and elicit forecasts from independent participants (n = 1,636). Forecasters predict large positive effects, yet behavioral data reveal small and inconsistent impacts. What drives the inconsistency between predictions and actual outcomes? Studies with more than 4,000 forecasters show that neither simulating the decision-making experience nor prior experience with CEP improve prediction accuracy. However, avoiding direct comparisons between experimental conditions-which can artificially amplify perceived differences-reduces overestimation. These findings highlight challenges associated with transferring behavioral insights across contexts and show how forecast elicitation methods shape expectations of intervention effectiveness.