Trains and Twitter: Firm generated content, consumer relationship management and message framing

Nisar, Tahir M.; Prabhakar, Guru P

Abstract

© 2018 Elsevier Ltd In this paper, we examine the impact of Twitter content on users’ train journeys and how train providers’ message framing moderates these relationships. Framing regards the way in which messages are worded concerning a particular object. In many consumer markets such as train journeys, firms frame messages in both positive and negative lights to persuade individuals to make purchase decisions (take intended journeys). We thus go beyond the literature's current focus on consumer-generated content (CGC), and bring into contention the important role that marketer-generated content (MGC) plays in shaping the social media-based consumer relationship management (CRM) strategies. Specifically, we analyze commuter tweets about 14 train operators, along with the companies’ Twitter feeds. The findings, obtained using sentiment analysis tools, suggest that consumer sentiments only moderately impact travel performance, as measured by operator ratings, CPM (consumer performance measure; a measure based on travel incidents) and firm financial performance. On the other hand, it appears that train operators use tweets in relation to their services particularly well, while keeping customers engaged by listening to and learning from criticism, thus confirming the moderating role of their Twitter-based message framing strategies. Train operators should look to maintain their social media use practices, ensuring they are consistently applied within an overarching CRM framework, particularly in key ‘pain’ areas such as delay and cancellation.

• Journal Article Type: Article
• Acceptance Date: Apr 24, 2018
• Online Publication Date: May 5, 2018
• Publication Date: Jul 1, 2018
• Deposit Date: Apr 26, 2018
• Publicly Available Date: May 5, 2019
• Journal: Transportation Research Part A: Policy and Practice
• Print ISSN: 0965-8564
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 113
• Pages: 318-334
• DOI: https://doi.org/10.1016/j.tra.2018.04.026
• Keywords: trains, Twitter, sentiment, consumer relationship management, framing effect, source credibility performance measure, financial performance
• Public URL: https://uwe-repository.worktribe.com/output/869153
• Publisher URL: https://doi.org/10.1016/j.tra.2018.04.026
• Additional Information: Additional Information : This is the author's accepted manuscript. The final published version is available here: https://doi.org/10.1016/j.tra.2018.04.026
• Contract Date: Apr 26, 2018