Merging Explicit Declarations With Implicit Response Time to Better Predict Behavior

Abstract

Declarations and actions do not always overlap, and thus, predicting future behavior solely on the basis of self-reported measures seems to be ineffective. The authors propose a confidence index (CI): a measure based on Fazio's attitude accessibility model. CI integrates explicit and implicit perspectives and captures how long a person hesitates when stating an opinion. The more certain someone is the stronger the attitude-behavior link is likely to be. A study was conducted to uncover differences in attitudes between average- and top-performing sales agents from the automotive industry. The results for declarative data did not show any significant differences; however, the CI results yielded interesting significant differences between groups. Random decision forests analyses confirmed that merging explicit and implicit measures increases predictive power of the tool. The study provided actionable insights on how to improve sales team performance, which were then implemented and eventually validated by sales results.