众包企业评级与全要素生产率:实证研究

IF 6.7 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Decision Support Systems Pub Date : 2024-04-04 DOI:10.1016/j.dss.2024.114218
Zongxi Liu , Donglai Bao , Xiao Xiao , Huimin Zhao
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引用次数: 0

摘要

目前,人力资源管理研究人员广泛利用员工在众包平台上分享的评论、反馈、意见和经验来分析企业的绩效、管理效率和文化。通过分析员工在众包平台上发布的企业评价,不仅可以及时反馈和洞察企业的运营情况,还能启发管理者做出更好的决策,从而提高组织绩效。基于经济学和心理学理论,我们利用面板向量自回归对 Glassdoor 上的企业评级进行了全面的逐项分析,探讨了众包企业评级与全要素生产率(TFP)之间的互动关系,并研究了这种关系在不同行业之间是否存在差异。我们发现企业的总体评分与全要素生产率之间存在循环互动关系。此外,我们还探讨了员工对薪酬和工作生活平衡的看法。我们的结果表明,薪酬评级会对全要素生产率产生负面影响,而工作与生活平衡评级则仅受滞后自我的影响。最后,我们观察到,Glassdoor 公司评级与全要素生产率之间的相互作用在不同行业有所不同。我们的研究表明,不同行业的决策者应根据其员工的具体需求制定激励战略,在薪酬和工作与生活平衡举措之间分配不同的资源。
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Crowdsourced firm ratings and total factor productivity: An empirical examination

Employees' reviews, feedback, opinions, and experiences shared on crowdsourcing platforms are now widely used by human resource management researchers to analyze a firm's performance, management effectiveness, and culture. The analysis of firm ratings posted by employees on crowdsourcing platforms can not only provide timely feedback and insights into a firm's operations but also inspire managers to make better decisions to improve organizational performance. Based on economic and psychological theories, we conduct a comprehensive and item-by-item analysis of firm ratings on Glassdoor using panel vector autoregression to explore the interactive relationship between crowdsourced firm ratings and Total Factor Productivity (TFP), examining whether this relationship differs across industries. We find a circular interaction between firms' overall ratings and TFP. Additionally, we explore employees' perspectives on compensation and work-life balance. Our results indicate that compensation ratings negatively impact TFP, whereas work-life balance ratings are solely influenced by the lagged self. Finally, we observe that the interaction between Glassdoor firm ratings and TFP varies across industries. Our study suggests that decision makers of different industries should tailor motivation strategies to suit the specific needs of their workforce, allocating resources differently between compensation and work-life balance initiatives.

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来源期刊
Decision Support Systems
Decision Support Systems 工程技术-计算机:人工智能
CiteScore
14.70
自引率
6.70%
发文量
119
审稿时长
13 months
期刊介绍: The common thread of articles published in Decision Support Systems is their relevance to theoretical and technical issues in the support of enhanced decision making. The areas addressed may include foundations, functionality, interfaces, implementation, impacts, and evaluation of decision support systems (DSSs).
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