Priyanga Gunarathne’s research while affiliated with University of Pittsburgh and other places

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.

Companies increasingly are providing customer service through social media, helping customers on a real-time basis. Although some traditional call centers might prioritize customers based on their expected business values, the grounds for differential customer service on social media are unclear, since there has been little theoretical or empirical investigation of this new phenomenon. Building on the literature of social psychology and complaint management, we hypothesize two main drivers of differential treatment: the social media influence effect, which refers to the impact of the customer's relative standing on social media, and the bystander effect, which refers to the impact of the presence of other social media users. To test these effects, we analyzed more than three million tweets to seven major U.S. airlines on Twitter from September 2014 to May 2015. The evidence is clear that airlines respond to less than half of the tweets directed at them by complaining customers-in contrast with traditional call centers, which are expected to address all callers. Interestingly, we find that the airlines are more likely to respond to complaints from customers with more followers, and customers with more followers are more likely to receive faster responses, thus confirming the existence of a concealed (or at least unpublicized) social media influence effect. We also find that airlines are less likely to respond to complaints with multiple parties mentioned, confirming the existence of the bystander effect. To the best of our knowledge, this is the first paper in the literature to study the existence and drivers of differential treatment when customer service is delivered on social media, and we expect our findings will have important implications for companies, customers, and regulators.

Many brands try to manage customer complaints on social media, helping their customers on a real-time basis. Inspired by this popular practice, in this study, we aim to understand whose and what complaints on social media are likely to have happier resolutions. We analyzed the complaint resolution experience of customers of a major U.S. airline, by exploiting a unique data set combining both customer–brand interactions on Twitter and how customers felt at the end of these interactions. We find that complaining customers who are more influential in online social networks are more likely to be satisfied. Customers who have previously complained to the brand on social media, and customers who complain about process-related rather than outcome-related issues are less likely to feel better in the end. To the best of our knowledge, this study is the first to identify the key factors that shape customer feelings toward their brand–customer interactions on social media. Our results provide practical guidance for successfully resolving customers’ complaints through the use of social media—an area that expects exponential growth in the coming decade.

Many companies are now providing customer service through social media, helping and engaging their customers on a real-time basis. To study this increasingly popular practice, we examine how major airlines respond to customer comments on Twitter by exploiting a large data set containing all Twitter exchanges between customers and four major airlines from June 2013 to August 2014. We find that these airlines pay significantly more attention to Twitter users with more followers, suggesting that companies literarily discriminate customers based on their social influence. Moreover, our findings suggest that companies in the digital age are increasingly more sensitive to the need to answer both customer complaints and customer compliments.