Real-effort survey designs: Open-ended questions to overcome the challenge of measuring behavior in surveys

Abstract

Based on data triangulation, open-ended questions can be used to overcome a typical problem with data collection using surveys: Human behavior can only be captured as stated or intended, but not as real behavior. In this study on knowledge sharing in the workplace, a quantitative measure of behavioral intention was accompanied by such a qualitative, open-ended measure of behavior. The latter was used as a proxy for real instead of stated behavior. This item was coded according to the effort a participant made in answering. It is assumed that the greater the effort put into answering the open-ended question, the more likely it is that the described behavior will be performed in reality. A factorial experimental design was used to analyze the effect of rewards on employees’ knowledge-sharing behavior. As a within-subject design was used, participants had to answer three open-ended questions referring to different vignettes. A strong order effect appeared, leading to longer answers on average for the first vignette (baseline) compared to subsequent vignettes, independent of treatment. Therefore, this approach to operationalizing behavior in surveys might not be useful in within-subject designs. However, it can be used in between-subject comparisons when participants are asked to answer to a single vignette.