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Employer Ratings through Crowdsourcing on Social Media: An Examination of U.S. Fortune 500 Companies

Hung-Yue Suen, Kuo-En Hung and Fan-Hsun Tseng
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Hung-Yue Suen: Department of Technology Application and Human Resource Development, National Taiwan Normal University, Taipei 10610, Taiwan
Kuo-En Hung: Department of Technology Application and Human Resource Development, National Taiwan Normal University, Taipei 10610, Taiwan
Fan-Hsun Tseng: Department of Technology Application and Human Resource Development, National Taiwan Normal University, Taipei 10610, Taiwan

Sustainability, 2020, vol. 12, issue 16, 1-15

Abstract: The aims of this study are to examine the effect of crowdsourced employer ratings and employee recommendations of an employer as an employer of choice, to examine which employer ratings that represent different employee value propositions can predict the overall employer rating through crowdsourcing, to examine whether the Fortune 500 ranking can also influence overall employer ratings, and to mine which keywords are popularly used when employees post a comment about the pros and cons of their employers on a crowdsourced employer branding platform. The study collected crowdsourced employer review data from Glassdoor based on 2019 Fortune 500 companies, and the results found that crowdsourced employer ratings are positively associated with “recommend to a friend,” while culture and values predominantly influence overall employer ratings. The rank of Fortune 500 has less predictive power for overall employer ratings than for other specific employer ratings, except for business outlook. The most popular keywords of Pros on Glassdoor are work–life balance and pay and benefits, whereas the most popular keywords of Cons on Glassdoor are work–life balance and upper management.

Keywords: electronic word-of-mouth (e-WOM); employer branding; employee value proposition (EVP); Glassdoor (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
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