Entrepreneurship Theory and Practice 2023

Test-Retest Reliability in Metric Conjoint Experiments: A New Workflow to Evaluate Confidence in Model Results

Jens Schüler¹; Brian S. Anderson^2,3; Charles Y. Murnieks⁴; Matthias Baum¹; Alexander Küsshauer⁵

¹ University of Bayreuth · ² University of Kansas · ³ Ghent University Hospital · ⁴ University of Missouri–Kansas City · ⁵ University of Bonn

Abstract

Metric conjoint studies are a popular research design in the entrepreneurship domain. For these studies, test-retest reliabilities of ρ > .70 or higher are an often-cited reliability criterion. Despite their widespread use, however, there is little rigorous analysis of whether test-retest reliability in metric conjoint studies relates to model efficacy. Informed by a systematic literature review, we conducted two Monte Carlo simulations to evaluate the effects of various determinants of test-retest reliability in conjoint experiments. We then illustrate a workflow for entrepreneurship researchers employing conjoint designs to better evaluate—and communicate—confidence in statistical models estimated from conjoint data.

DOI

10.1177/10422587231184071

Sources

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APA 7 MLA 9 Chicago (author–date) Harvard Elsevier Harvard (JFE, JBF…) The Accounting Review Academy of Management American Marketing Association INFORMS (Management Science) Copy citation Copied ✓