five

Replication Package for "Strategic Use of Unfriendly Leadership and Labor Market Competition: An Experimental Analysis"

收藏
DataCite Commons2024-07-17 更新2025-04-16 收录
下载链接:
https://www.ifo.de/node/82285
下载链接
链接失效反馈
官方服务:
资源简介:
A significant portion of the workforce experiences what we term ‘unfriendly leadership,’ encompassing various forms of hostile behavior exhibited by managers. The motivations driving managers to adopt such behaviors are insufficiently understood. To explore this phenomenon, we conducted a laboratory experiment examining the relationship between managers’ use of unfriendly leadership and labor market competition. We discern two labor market states: excess labor demand, where managers compete to hire workers, and excess labor supply, where workers compete to be hired. By perceiving unfriendly leadership as a performance-contingent punishment device inflicting discomfort on workers, we hypothesize that managers are less inclined to resort to unfriendly leadership when they compete to hire workers. We find that managers tend to engage in unfriendly leadership more frequently and intensely under excess labor supply, in comparison to excess labor demand. This trend is particularly pronounced among male participants. Additionally, workers display a decreased likelihood of accepting employment offers from more unfriendly managers and exert lower levels of effort when working under such managers, indicating that unfriendly leadership is costly.

相当比例的职场从业者会遭遇我们称之为"敌意型领导(unfriendly leadership)"的行为,这类行为涵盖管理者所展现的各类敌意性举动。目前学界对管理者实施此类行为的动机仍缺乏充分认知。为探究这一现象,我们开展了一项实验室实验,以考察管理者实施敌意型领导行为与劳动力市场竞争之间的关联。我们设定了两种劳动力市场状态:一是劳动力需求过剩,此时管理者会竞争聘用求职者;二是劳动力供给过剩,此时求职者会竞争岗位。我们将敌意型领导视为一种依绩效而定的惩罚手段,会给员工带来不适感,据此提出假设:当管理者需要竞争聘用求职者时,他们更不愿采取敌意型领导行为。实验结果显示,相较于劳动力需求过剩的场景,管理者在劳动力供给过剩的环境中实施敌意型领导行为的频率更高、程度更强。这一趋势在男性参与者中尤为显著。此外,员工接受敌意程度更高的管理者所提供的聘用邀约的概率更低,且在这类管理者麾下工作时投入的努力水平也更低,这表明敌意型领导行为会产生成本。
提供机构:
LMU-ifo Economics & Business Data Center
创建时间:
2024-07-17
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作