Liyue Yan

Strategy Science Doi: https://doi.org/10.1287/stsc.2023.0116

We examine “reputational herding,” where decision makers follow the herd to maintain or improve their reputation, rather than to make optimal decisions for the firm. We propose this as an additional mechanism for firms’ mimetic behaviors. We model the mechanism and demonstrate that decision makers are less likely to herd when they have a high reputation, as it strengthens their confidence in private signals and buffers them against reputational penalties in the event of a bad outcome. Conversely, herding is more likely when experts have highly correlated information (high “signal correlation”). The model’s prediction on the effect of reputation differs from previous research; the model’s secondary predictions on the effect of signal correlation distinguish reputational herding from informational herding. We test the theory in the context of sell-side stock analysts and employ a difference-in-differences design to compare award-winning analysts and runners-up with similar ability to assess the impact of a reputation shock on herding behavior. The overall results are consistent with the reputational herding mechanism. We discuss several managerial implications of the model and provide recommendations regarding how to mitigate the moral hazard problem of reputational herding. Supplemental Material: The online appendix is available at https://doi.org/10.1287/stsc.2023.0116 .

Strategic Management Journal 42(11) p. 1963-1992 Doi: https://doi.org/10.1002/smj.3290

We revisit Zuckerman's (1999) “The Categorical Imperative: Securities Analysts and the Illegitimacy Discount,” which theorizes that when organizations are recognized as legitimate players in a category, they perform better. A replication exercise fails to reproduce two of three sets of results. Assisted by data shared by the original author, we find evidence that the inconsistency is due to a coding error in the original and differences between analyst data sets. We illustrate the use of epistemic maps and evaluate the theory's predictive power across a broad set of plausible empirical assumptions and also for a subsequent time period. The results are not robust. We conclude that these data provide little evidence to support strategic recommendations. Challenges and remedies for replication are discussed