解雇
叙述的
透明度(行为)
编码(社会科学)
业务
会计
人事变更率
经济
数据库
政治学
管理
计算机科学
法学
数学
语言学
统计
哲学
计算机安全
作者
Richard J. Gentry,Joseph S. Harrison,Timothy J. Quigley,Steven Boivie
摘要
Abstract Research Summary We introduce an open‐source dataset documenting the reasons for CEO departure in S&P 1500 firms from 2000 through 2018. In our dataset, we code for various forms of voluntary and involuntary departure. We compare our dataset to three published datasets in the CEO succession literature to assess both the qualitative and quantitative differences among them and to explore how these differences impact empirical findings associated with the performance‐CEO dismissal relationship. The dataset includes eight different classifications for CEO turnover, a narrative description of each departure event, and links to sources used in constructing the narrative so that future researchers can validate or adapt the coding. The resulting data are available at ( https://doi.org/10.5281/zenodo.4543893 ). Managerial Summary This article describes the development of an open‐source database of all CEO dismissals and departures in the S&P 1500 between 2000 and 2018. Prior research on CEO turnover either does not capture the cause of departure or has coded the event independently, leading to inconsistencies and a lack of transparency in coding schemes. This has made it difficult to generate knowledge on the causes and consequences of CEO dismissal. We describe how we developed the database, and we explore how our dataset compares to prior CEO dismissal research. The resulting data are available at ( https://doi.org/10.5281/zenodo.4543893 ).
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