Crowdsourced firm ratings and total factor productivity: An empirical examination

Abstract

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.

Department(s)

Information Technology and Cybersecurity

Document Type

Article

DOI

10.1016/j.dss.2024.114218

Keywords

Compensation, Employee reviews, Employee satisfaction, Productivity, Work-life balance

Publication Date

6-1-2024

Journal Title

Decision Support Systems

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