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

Author

Listed:
  • Jens Schüler
  • Brian S. Anderson
  • Charles Y. Murnieks
  • Matthias Baum
  • Alexander Küsshauer

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.

Suggested Citation

  • Jens Schüler & Brian S. Anderson & Charles Y. Murnieks & Matthias Baum & Alexander Küsshauer, 2024. "Test-Retest Reliability in Metric Conjoint Experiments: A New Workflow to Evaluate Confidence in Model Results," Entrepreneurship Theory and Practice, , vol. 48(2), pages 742-757, March.
    • Handle: RePEc:sae:entthe:v:48:y:2024:i:2:p:742-757
    DOI: 10.1177/10422587231184071
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