The More You Ask, the Less You Get: When Additional Questions Hurt External Validity

Antonia Krefeld-Schwalb, Daniel Wall, Eric J. Johnson, Olivier Toubia, Daniel M. Bartels, Ye Li

Research output: Contribution to journalArticleAcademicpeer-review

9 Citations (Scopus)
439 Downloads (Pure)

Abstract

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.

Original languageEnglish
Article numberhttps://journals.sagepub.com/doi/pdf/10.1177/00222437211073581
Pages (from-to)963-982
Number of pages20
JournalJournal of Marketing Research
Volume59
Issue number5
DOIs
Publication statusPublished - Oct 2022

Bibliographical note

Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: AKS gratefully acknowledges funding from the Swiss National Science Foundation (P400PS_186660). EJJ gratefully acknowledges funding from the Alfred P. Sloan Foundation (G-2018-11114) and from the National Science Foundation (UV-GA11247-155597).

Publisher Copyright:
© American Marketing Association 2022.

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