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How can firms encourage consumers to adopt smartphone apps? The authors show that several inexpensive choice architecture techniques can make users more likely to enable important app features and complete app onboarding. In six preregistered experiments (n = 5,968) and a field experiment (n = 594,997), choice architecture interventions manipulating choice sequence, color, and wording of app adoption decisions dramatically increased app adoption. Across experiments, integrating multiple feature decisions into a single choice increased adoption. This integration effect emerges because it decreases decision noise and reduces the prominence of individual features, consistent with support theory. Changing colors to match habitual patterns commonly found in current digital interfaces appears to increase adoption by accelerating consumers’ decisions. Finally, wording options as if enabling the app is the default response (even without changing the actual default) also increases adoption. These “defaultless defaults” may be particularly relevant in heavily regulated consumer domains, such as finance or health care. The effects generalized across different types of apps and were robust across subsamples varying in demographics, attitudes toward the apps, and political affiliation. These results suggest simple tools that marketing managers and app developers can use to increase app adoption.

Researchers and practitioners in marketing, economics, and public policy often use preference elicitation tasks to forecast real-world behaviors. These tasks typically ask a series of similarly structured questions. The authors posit that every time a respondent answers an additional elicitation question, two things happen: (1) they provide information about some parameter(s) of interest, such as their time preference or the partworth for a product attribute, and (2) the respondent increasingly “adapts” to the task—that is, using task-specific decision processes specialized for this task that may or may not apply to other tasks. Importantly, adaptation comes at the cost of potential mismatch between the task-specific decision process and real-world processes that generate the target behaviors, such that asking more questions can reduce external validity. The authors used mouse and eye tracking to trace decision processes in time preference measurement and conjoint choice tasks. Respondents increasingly relied on task-specific decision processes as more questions were asked, leading to reduced external validity for both related tasks and real-world behaviors. Importantly, the external validity of measured preferences peaked after as few as seven questions in both types of tasks. When measuring preferences, less can be more.

Loss aversion can occur in riskless and risky choices. We present novel evidence on both in a non-student sample (660 randomly selected customers of a car manufacturer). We measure loss aversion in riskless choice in endowment effect experiments within and between subjects and find similar levels of average loss aversion in both. The subjects of the within study also participate in a simple lottery choice task which arguably measures loss aversion in risky choices. We find substantial heterogeneity in both measures of loss aversion. Loss aversion in riskless choice and loss aversion in risky choice are strongly positively correlated, but on average riskless loss aversion is higher than risky loss aversion. We find that in both choice tasks, loss aversion increases in age, income, and wealth, and decreases in education. Our results provide novel supportive input to the debate about the reality of loss aversion.