JOURNAL ARTICLE

Brand Crisis and Customer Relationship Management on Social Media: Evidence from a Natural Experiment from the Airline Industry.

  • Published In: Information Systems Research (INFORMS), 2023, v. 34, n. 2. P. 442 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Al Balawi, Ramah; Hu, Yuheng; Qiu, Liangfei 3 of 3

Abstract

This article examines how a brand crisis affects a brand's customer relationship management (CRM) efforts on social media, focusing on United Airlines' 2017 crisis involving the forcible removal of a passenger. Using a natural experiment and difference-in-differences estimation on over 1.5 million Twitter interactions, the study analyzes three dimensions of social CRM efforts: informativeness (providing explanations), timeliness (response speed), and attentiveness (degree of interaction). Findings reveal that following the crisis, United Airlines increased informativeness but decreased both timeliness and attentiveness in its social media responses. Mediation analysis indicates that these adjusted efforts had minimal success in mitigating the negative impact of the crisis on customer satisfaction, suggesting a conservative social CRM approach may not be effective in such situations. The study offers insights for brands and social media managers on managing customer relationships publicly during crises, while highlighting the need for further research across industries, platforms, and crisis types.

Additional Information

  • Source:Information Systems Research (INFORMS). 2023/06, Vol. 34, Issue 2, p442
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2023
  • ISSN:1047-7047
  • DOI:10.1287/isre.2022.1159
  • Accession Number:164615180
  • Copyright Statement:Copyright of Information Systems Research (INFORMS) is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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