Investigating the Effect of Multidimensional Review Text and Anonymity on Review Helpfulness: An Empirical Investigation in the Context of Employer Review Sites

Abstract

Employer review sites have grown popular over the last few years, with 86 percent of job seekers referring to reviews in these sites before applying to job positions. Though review helpfulness is studied in various contexts, it has received limited attention in the employee review context. In an attempt to solicit unbiased reviews, these sites allow an option of keeping reviewer information anonymous. Besides, these sites provide review text in multiple dimensions. We investigate review helpfulness focusing on the anonymity of the reviewers, and the role of review text in multiple dimensions. We use a publicly available Glassdoor dataset to model review helpfulness using a Tobit regression. The results show that anonymity and review length in multiple dimensions of review text positively impact review helpfulness. Moreover, anonymity positively moderates the review length in the cons section.