THESIS
2022
1 online resource (vii, 46 pages) : illustrations
Abstract
This paper studies whether employee reviews on the social media platform, Glassdoor, are
useful for predicting accounting fraud committed by their employers. I find that the rating of
the employer overall and the average value of subsector ratings have predictive ability for
accounting fraud incremental to F-score and other market participants. Similar inferences
apply to the rating of employers’ culture values and the textual assessment of employers’
social and governance quality. In addition, I find that employee reviews are most useful for
predicting fraud one year before fraud revelation. Within the fraud sample, I show that above
ratings decrease and the textual assessment of social and governance quality deteriorates in
the two years before fraud revelation. The declines are more...[
Read more ]
This paper studies whether employee reviews on the social media platform, Glassdoor, are
useful for predicting accounting fraud committed by their employers. I find that the rating of
the employer overall and the average value of subsector ratings have predictive ability for
accounting fraud incremental to F-score and other market participants. Similar inferences
apply to the rating of employers’ culture values and the textual assessment of employers’
social and governance quality. In addition, I find that employee reviews are most useful for
predicting fraud one year before fraud revelation. Within the fraud sample, I show that above
ratings decrease and the textual assessment of social and governance quality deteriorates in
the two years before fraud revelation. The declines are more pronounced when fraud firms’
business operations are less complex, internal controls are poorer, reviewing employees are
not managers and reviewing employees have already left the firm. The study documents an
important channel through which fraud-related information is revealed to the public and the
findings have implications for investors and regulators.
Post a Comment