Whose and What Social Media Complaints Have Happier Resolutions? Evidence from Twitter

Abstract

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.

Key words and phrases:

• airline industry
• CLASS methodology
• complaint management
• customer service
• Klout score
• online complaints
• social influence
• social media
• Twitter

Acknowledgments

An early version of this study was previously circulated as “What Drives Successful Complaint Resolutions on Social Media? Evidence from the Airline Industry.” The authors thank the JMIS coeditors Rob Kauffman, Rajiv Dewan, Thomas Weber, Eric Clemons, the HICSS minitrack chairs, Jie Zhang, Yabin Jiang, and all the participants of the HICSS minitrack on “Integrating Business Operations, Information Technologies, and Consumer Behavior” in the Organizational Systems and Technology Track, for useful discussion and comments.

Supplemental File

Supplemental data for this article can be found on the publisher’s website at 10.1080/07421222.2017.1334465

Notes

1. The Big Five personality traits refer to openness, conscientiousness, extraversion, agreeableness, and neuroticism/degree of emotional stability; see [17] for details.

2. To automate the process, one needs to apply for special permission and be approved by Twitter.

3. See Greene and Hensher [18], for details on the interpretation of ordered logit coefficients.

4. The small sample size is due to both the low response rate and limiting rules imposed by Twitter.

Additional information

Notes on contributors

Priyanga Gunarathne

Priyanga Gunarathne ([email protected]) is a Ph.D. candidate in computer information systems at the Simon Business School of the University of Rochester. Before joining Simon Business School, she worked as a software engineer in financial markets. Her primary research interests are consumer and organizational behavior on social media, and the use of deep learning and natural language processing in business.

Huaxia Rui

Huaxia Rui ([email protected]) is the Xerox Assistant Professor at the Simon Business School of the University of Rochester. He received his Ph.D. from the University of Texas at Austin in 2012. His work has been published in Management Science, Information Systems Research, Journal of Management Information Systems, MIS Quarterly, Production and Operations Management, and others.

Abraham Seidmann

Abraham Seidmann ([email protected]; corresponding author) is the Xerox Professor of Computers and Information Systems and Operations Management at the Simon Business School of the University of Rochester. His research and consulting work focuses on the development of advanced analytical tools for solving real business problems in information-intensive industries, most recently in health care, web services, software development, digital supply chains, and automated manufacturing. His research also involves the economic aspects of information technology and its strategic interactions with organizations, markets, and value chain operations. He is a Distinguished Fellow of the INFORMS Information Systems Society.