The Wisdom of Electronic Employee Crowds—Employee Reviews as a Data Source in Finance, Accounting, Economics, and Management Research: A Systematic Literature Review
{"title":"The Wisdom of Electronic Employee Crowds—Employee Reviews as a Data Source in Finance, Accounting, Economics, and Management Research: A Systematic Literature Review","authors":"Nils Gimpl","doi":"10.1002/isaf.70007","DOIUrl":null,"url":null,"abstract":"<p>This study explores the wealth of information inherent in online employee reviews as an emerging resource in academic research. The focus is on the fields of finance, accounting, economics, and management, with an emphasis on how employee reviews contribute to our understanding of these areas. A systematic literature review (SLR) of 70 high-quality articles highlights the insights gleaned from employee reviews. Their data points, such as employee satisfaction, employee outlook, evaluation of culture, management, and colleagues, and text comments are mainly used in (1) explaining and predicting firm performance, (2) predicting and understanding performance and satisfaction of specific job groups, and (3) CSR- and ESG-related research. This SLR is important because the three main topics mentioned in which employee reviews are mainly used are spread across the fields of finance, accounting, economics, and management. This SLR therefore provides researchers with an important and necessary overview of the research already addressed across these fields. Furthermore, the SLR provides an overview of employer rating platforms utilized for academic research and methods used to harness employee reviews for research purposes. Here, a significant finding of this SLR is the predominant use of Glassdoor as a data source and the focus on US markets. The SLR concludes by proposing five potential avenues for future research, paving the way for a deeper understanding of the interplay between employee reviews (information) and organizational dynamics.</p>","PeriodicalId":53473,"journal":{"name":"Intelligent Systems in Accounting, Finance and Management","volume":"32 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/isaf.70007","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Intelligent Systems in Accounting, Finance and Management","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/isaf.70007","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
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Abstract
This study explores the wealth of information inherent in online employee reviews as an emerging resource in academic research. The focus is on the fields of finance, accounting, economics, and management, with an emphasis on how employee reviews contribute to our understanding of these areas. A systematic literature review (SLR) of 70 high-quality articles highlights the insights gleaned from employee reviews. Their data points, such as employee satisfaction, employee outlook, evaluation of culture, management, and colleagues, and text comments are mainly used in (1) explaining and predicting firm performance, (2) predicting and understanding performance and satisfaction of specific job groups, and (3) CSR- and ESG-related research. This SLR is important because the three main topics mentioned in which employee reviews are mainly used are spread across the fields of finance, accounting, economics, and management. This SLR therefore provides researchers with an important and necessary overview of the research already addressed across these fields. Furthermore, the SLR provides an overview of employer rating platforms utilized for academic research and methods used to harness employee reviews for research purposes. Here, a significant finding of this SLR is the predominant use of Glassdoor as a data source and the focus on US markets. The SLR concludes by proposing five potential avenues for future research, paving the way for a deeper understanding of the interplay between employee reviews (information) and organizational dynamics.
期刊介绍:
Intelligent Systems in Accounting, Finance and Management is a quarterly international journal which publishes original, high quality material dealing with all aspects of intelligent systems as they relate to the fields of accounting, economics, finance, marketing and management. In addition, the journal also is concerned with related emerging technologies, including big data, business intelligence, social media and other technologies. It encourages the development of novel technologies, and the embedding of new and existing technologies into applications of real, practical value. Therefore, implementation issues are of as much concern as development issues. The journal is designed to appeal to academics in the intelligent systems, emerging technologies and business fields, as well as to advanced practitioners who wish to improve the effectiveness, efficiency, or economy of their working practices. A special feature of the journal is the use of two groups of reviewers, those who specialize in intelligent systems work, and also those who specialize in applications areas. Reviewers are asked to address issues of originality and actual or potential impact on research, teaching, or practice in the accounting, finance, or management fields. Authors working on conceptual developments or on laboratory-based explorations of data sets therefore need to address the issue of potential impact at some level in submissions to the journal.