Search

Detecting and reporting systemic racial bias is an essential step toward the eradication of racial discrimination in our society. Doing so not only requires society members to voice and share their anecdotal experiences, but also relies on researchers to document systematic statistical evidence of racial bias. This paper documents the first large-scale evidence of business-to-customer racial bias on digital platforms on which the perpetrators are individual employees who act on behalf of a company and the victims are customers. This is in contrast to existing studies of racial bias on digital platforms that focus on peer-to-peer marketplaces in which both the perpetrators and the victims are individuals acting independently and on their own behalf. By analyzing more than 57,000 social media customer complaints to U.S. airlines and leveraging a variety of analytics techniques, including text mining and facial recognition, we present quantitative evidence that African American customers are less likely to receive a response when they complain than otherwise similar White customers. Furthermore, our deep learning–based falsification test shows that the bias is absent without the race-revealing visual cue. This study offers a practical yet powerful recommendation for companies: conceal all customer profile pictures from their employees while delivering social media customer service.

This paper studies whether social media personal branding (PB) improves a job candidate’s labor market performance in the context of executive employment and compensation. We focus on executives employed by Standard & Poor’s 500 constituent companies from 2010 to 2013 and evaluate their PB on social media by analyzing their Twitter accounts. To disentangle the effect of PB from that of personality traits, we exploit a (positive) shock to the effectiveness of PB caused by a series of technology upgrades by Twitter. Estimations from a two-sided matching model suggest that social media PB benefits executive candidates in job markets. This paper contributes to the literature by initiating the study of the emerging phenomenon of social media PB and testing its effect on job market performance.

Incentivizing reviewers to write product reviews is a widespread yet controversial practice. Whereas outright fake reviews are clearly unacceptable and should be removed from any review platform, reviews contributed by incentivized consumers with otherwise authentic product experiences fall in a gray area. This paper offers a fresh perspective for us to understand conceptually the relationship between incentivized reviews and its two counterparts (i.e., organic reviews and advertisements) on the two ends of the spectrum, and it studies whether incentivized reviews are of higher text quality. The authors argue that incentivized reviewers may shift their “writing mode” from back stage to front stage and may also “compensate” for their reduced impartiality through better text quality. Drawing on recent advancements in computational linguistics, the authors demonstrate that incentivized reviews tend to have more coherent writing and cover more details, suggesting higher review text quality. Their finding highlights the often-overlooked value of incentivized reviews, which can complement an organic review system and also alleviate the cold-start problem for new products, thereby promoting healthy competition in the e-commerce era. For review platforms, the authors suggest they explicitly group and label incentivized reviews without their numerical ratings and separate them from organic reviews. In this way, we can take the best of both worlds.