Social media data contain rich information in posts or comments written by customers. If those data can be extracted and analysed properly, companies can fully utilise this rich source of information. They can then convert the data to useful information or knowledge which can help to formulate their business strategy. This can not only facilitate marketing research in view of customer behaviour, but can also aid other management disciplines. Operations management research and practice with the objective to make decisions on product and process design is a fine example. Nevertheless, this line of thought is under-researched. In this connection, this paper explores the role of social media data in operations management research. A structured approach is proposed which involves the analysis of social media comments and a statistical cluster analysis to identify the inter-relationships among important factors. A real-life example is employed to demonstrate the concept.
Bibliographical noteThis is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Production Research on 15/06/15, available online: http://www.tandfonline.com/10.1080/00207543.2015.1053998
Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.
- Social media
- Operations management
- Content analysis
- Cluster analysis
Chan, H. K., Lacka, E., Yee, R. W. Y., & Lim, M. K. (2017). The role of social media data in operations and production management. International Journal of Production Research, 55(17), 5027-5036. https://doi.org/10.1080/00207543.2015.1053998