Multipoint contact without forbearance? How coverage synergies shape equity analysts' forecasting performance
研究了股票分析师的多点接触如何通过覆盖组合的协同效应提升预测准确性和信息领导力，但也会因竞争对手的观察学习而降低预测差异化。
Abstract Research Summary: Scholars regularly use multipoint contact (MPC) to explain how encountering rivals in different domains shapes performance. While most explanations rely on mutual forbearance theory, I propose that competitive deterrence does not adequately explain how MPC shapes performance in knowledge intensive work and argue instead that cross‐domain synergies may play a central role. I examine how security analysts' MPC with publicly traded firms captures synergies in their coverage portfolio, which improves forecasting accuracy and information leadership. The advantages of greater MPC for a focal analyst are counterbalanced by rivals' observational learning, which reduces the focal analyst's forecasting differentiation. A natural experiment helps corroborate my argument: rival analysts' forecasting accuracy dropped for firms in which high MPC analysts perished in the terrorist attack on September 11, 2001. Managerial Summary: Competition in the knowledge economy often unfolds across multiple domains including product markets, geographic locations, and customer segments. In these settings, an actor's level of multipoint contact (MPC) in a domain captures the knowledge and other synergies available to the focal actor, which can improve performance in the domain. In the equity research setting, an analyst's MPC on a focal firm captures the likelihood that the analyst also covers that firm's suppliers, customers and important competitors. Using data on analysts' forecasting performance between 2001 and 2013, I find that greater levels of MPC on a focal firm predicts greater forecasting accuracy and information leadership but also lowers forecasting differentiation by attracting rivals who observe and benefit from the focal analyst's knowledge.