Employer ratings through crowdsourcing on social media: An examination of U.S. Fortune 500 companies

Hung Yue Suen, Kuo En Hung, Fan Hsun Tseng*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

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.

Original languageEnglish
Article number6308
JournalSustainability (Switzerland)
Volume12
Issue number16
DOIs
Publication statusPublished - 2020 Aug

Keywords

  • Electronic word-of-mouth (e-WOM)
  • Employee value proposition (EVP)
  • Employer branding
  • Glassdoor

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Renewable Energy, Sustainability and the Environment
  • Environmental Science (miscellaneous)
  • Energy Engineering and Power Technology
  • Management, Monitoring, Policy and Law

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