Browsing by Author "Silverman, Jackie"
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Item Doing good for (maybe) nothing: How reward uncertainty shapes observer responses to prosocial behavior(Organizational Behavior and Human Decision Processes, 2022-01-06) Silver, Ike; Silverman, JackieWhen firms or individuals stand to benefit from doing good, observers often question their motivations and discount their good deeds. We propose that this attribution process is sensitive not only to the presence of extrinsic incentives, but also to their prior likelihoods. Across eleven studies, observers treat uncertain rewards (vs. equally valuable certain rewards) as weaker signals of extrinsic motivation. Consequently, observers judge actors who do good when facing uncertain incentives as more purely motivated, benevolent, and likable, and they prefer products from brands that incur profit uncertainty when launching CSR initiatives. Even actors who are handsomely rewarded for doing good are judged favorably if rewards were uncertain at the outset. These effects may stem from more general processes of counterfactual attribution: Actors who do good knowing they might not be rewarded for it may seem more like they would have been willing to act without any incentive at all.Item Harder Than You Think: Misconceptions about Logging Food with Photos versus Text(Journal of the Association for Consumer Research, 2022-07-26) Silverman, Jackie; Barasch, Alixandra; Diehl, Kristin; Zauberman, GalConsumers lose more weight when they log their food consumption more consistently, yet they face challenges in doing so. We investigate how the modality of food logging—whether people record what they eat by taking photos versus writing text—affects their anticipated and actual logging experience and behavior. We find that consumers are more likely to adopt and anticipate better experiences with photo-based food logging tools over text-based tools. However, in a weeklong field study, these expectations reveal themselves to be inaccurate; once participants start logging, they find taking photos (vs. writing text) to be more difficult, log less of what they eat, and are less likely to continue using the logging tool. These findings contribute to existing research on how people track goal progress, as well as persistence with and dis-adoption of products. Moreover, our findings provide insights into what might increase the use of products that encourage healthy eating.Item Hot streak! Inferences and predictions about goal adherence(Organizational Behavior and Human Decision Processes, 2023-10-03) Silverman, Jackie; Barasch, Alixandra P.; Small, Deborah A.When do people make optimistic forecasts about goal adherence? Nine preregistered studies find that a recent streak of goal-consistent behavior increases the predicted likelihood that the individual will persist, compared to various other patterns holding the rate of goal adherence constant. This effect is due to perceiving a higher level of commitment following a streak. Accordingly, the effect is larger when the behavior requires commitment to stick with it, compared to when the same behavior is enjoyable in its own right. Furthermore, the effect is weaker in the presence of another diagnostic cue of commitment: when the individual has a high historic rate of goal adherence. People also behave strategically in ways consistent with these inferences (e.g., are less likely to adopt costly goal support tools following a streak, choose partners with recent streaks for joint goal pursuit). Together, these results demonstrate the significance of streaky behavior for forecasting goal adherence.Item On or Off Track: How (Broken) Streaks Affect Consumer Decisions(Journal of Consumer Research, 2022-06-30) Silverman, Jackie; Barasch, AlixandraNew technologies increasingly enable consumers to track their behaviors over time, making them more aware of their “streaks”—behaviors performed consecutively three or more times—than ever before. Our research explores how these logged streaks affect consumers’ decisions to engage in the same behavior subsequently. In seven studies, we find that intact streaks highlighted via behavioral logs increase consumers’ subsequent engagement in that behavior, relative to when broken streaks are highlighted. Importantly, this effect is independent of actual past behavior and depends solely on how that behavior is represented within the log. This is because consumers consider maintaining a logged streak to be a meaningful goal in and of itself. In line with this theory, the effect of intact (vs. broken) logged streaks is amplified when consumers attribute a break in the streak to themselves rather than to external factors, and attenuated when consumers can “repair” a broken streak. Our research provides actionable insights for companies seeking to benefit from highlighting consumers’ streaks in various consequential domains (e.g., fitness, learning) without incurring a cost (e.g., reduced engagement or abandonment) when those streaks are broken.Item The Prediction Order Effect: People Are More Likely to Choose Improbable Outcomes in Later Predictions(Management Science, 2024-03-01) Silverman, Jackie; Barnea, UriPeople often need to predict the outcomes of future events. We investigate the influence of order on such forecasts. Six preregistered studies (n = 7,955) show that people are more likely to forecast improbable outcomes (e.g., that an “underdog” will win a game) for predictions they make later versus earlier within a sequence of multiple predictions. This effect generalizes across several contexts and persists when participants are able to revise their predictions as well as when they are incentivized to make correct predictions. We propose that this effect is driven by people’s assumption that improbable outcomes are bound to occur at some point within small sets of independent events (i.e., “belief in the law of small numbers”). Accordingly, we find that the effect is attenuated when the statistical independence of events is made salient to forecasters both through the nature of the predictions themselves (i.e., when the events are from distinct domains) and through directly informing them about statistical independence. These findings have notable practical implications, as policy makers and businesses have the ability to control the order in which people evaluate and predict future events.