Trains and Twitter: firm-generated content, customer relationship management and message framing
Trains and Twitter: firm-generated content, customer relationship management and message framing
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.
318-334
Nisar, Tahir M.
6b1513b5-23d1-4151-8dd2-9f6eaa6ea3a6
Prabhakar, G.
51b623ea-f92c-45f6-8f60-95ec4ff6e892
July 2018
Nisar, Tahir M.
6b1513b5-23d1-4151-8dd2-9f6eaa6ea3a6
Prabhakar, G.
51b623ea-f92c-45f6-8f60-95ec4ff6e892
Nisar, Tahir M. and Prabhakar, G.
(2018)
Trains and Twitter: firm-generated content, customer relationship management and message framing.
Transportation Research Part A: Policy and Practice, 113, .
(doi:10.1016/j.tra.2018.04.026).
Abstract
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.
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Accepted/In Press date: 24 April 2018
e-pub ahead of print date: 5 May 2018
Published date: July 2018
Identifiers
Local EPrints ID: 419981
URI: http://eprints.soton.ac.uk/id/eprint/419981
ISSN: 0965-8564
PURE UUID: 93aed066-1f13-4995-a3dd-2d9f445cb1fd
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Date deposited: 25 Apr 2018 16:30
Last modified: 16 Mar 2024 06:31
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Author:
G. Prabhakar
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