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

Jens Schüler, Brian S. Anderson, Charles Y. Murnieks, Matthias Baum and Alexander Küsshauer

Entrepreneurship Theory and Practice, 2024, vol. 48, issue 2, 742-757

Abstract: Metric conjoint studies are a popular research design in the entrepreneurship domain. For these studies, test-retest reliabilities of Ï â€‰> .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.

Keywords: entrepreneurship experiments; metric conjoint analysis; test-retest reliability; Monte Carlo simulation; testing entrepreneurship theory (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:sae:entthe:v:48:y:2024:i:2:p:742-757

DOI: 10.1177/10422587231184071

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