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.

Summary We argue that job crafting opportunities are not only helpful to motivate and enable the existing workforce but that they can also function as a signal to attract talent. With the help of two empirical studies (Study 1 – a conjoint experiment and Study 2 – a vignette study), we show that (a) a signaled opportunity for job crafting helps to attract job seekers; (b) job crafting signals can trigger positive as well as negative expectations of central job demands and resources that inform job acceptance intentions, and; (c) a proactive personality strengthens most of the positive expectations of job crafting signals while buffering adverse effects.