Zongxi Liu , Donglai Bao , Xiao Xiao , Huimin Zhao
{"title":"众包企业评级与全要素生产率:实证研究","authors":"Zongxi Liu , Donglai Bao , Xiao Xiao , Huimin Zhao","doi":"10.1016/j.dss.2024.114218","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"181 ","pages":"Article 114218"},"PeriodicalIF":6.7000,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Crowdsourced firm ratings and total factor productivity: An empirical examination\",\"authors\":\"Zongxi Liu , Donglai Bao , Xiao Xiao , Huimin Zhao\",\"doi\":\"10.1016/j.dss.2024.114218\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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.</p></div>\",\"PeriodicalId\":55181,\"journal\":{\"name\":\"Decision Support Systems\",\"volume\":\"181 \",\"pages\":\"Article 114218\"},\"PeriodicalIF\":6.7000,\"publicationDate\":\"2024-04-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Decision Support Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167923624000514\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Decision Support Systems","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167923624000514","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
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.
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).