The Effects of a Short-Term Corporate Social Impact Activity on Employee Turnover: Field Experimental Evidence

亲社会行为 企业社会责任 组织公正 人事变更率 公共关系 激励 情感(语言学) 业务 相关性(法律) 入职培训 员工敬业度 员工激励 心理学 社会心理学 政治学 经济 组织承诺 管理 微观经济学 法学 沟通
作者
Florencio F. Portocarrero,Vanessa Burbano
出处
期刊:Management Science [Institute for Operations Research and the Management Sciences]
被引量:12
标识
DOI:10.1287/mnsc.2022.01517
摘要

Short-term corporate social impact activities, wherein employees participate in firm-sponsored prosocial initiatives, are becoming increasingly common. However, it remains unclear whether short-term social impact activities affect employee behavior in a manner of relevance to the firm. Theoretically, arguments could be made in favor of or against the likelihood that such short-term activities would increase firm-benefitting employee behavior. We utilized data from a randomized field experiment implemented at a large Latin American bank to examine whether a short-term social impact activity can be beneficial for firms, focusing on one important outcome: turnover. Newly hired employees were randomly assigned to a short-term social impact activity as part of the new employee onboarding process or not. Notably, we find causal evidence that a day-long, short-term engagement reduced employee turnover almost a year later. We explore potential mechanisms behind this effect and find that employees’ perceptions of organizational justice help to explain the effects of the intervention on turnover. We also explore heterogeneous treatment effects and find more substantial effects for male, rather than female, employees. This paper advances the literature on the implications of corporate social responsibility (CSR) practices by shedding light on the causal mechanisms through which a theoretically underexplored and practically relevant type of CSR activity can benefit organizations and their employees. This paper was accepted by Lamar Pierce, organizations. Funding: The authors acknowledge funding from NSF through the Learning the Earth with Artificial intelligence and Physics (LEAP) Science and Technology Center (STC) (Award #2019625). Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2022.01517 .
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