The role of social media data in operations and production management. Issue 17 (2nd September 2017)

• Record Type: Journal Article
• Authors: Chan, Hing Kai; Lacka, Ewelina; Yee, Rachel W.Y.; Lim, Ming K.
• Is Part Of: International journal of production research. Volume 55:Issue 17(2017)
• Page Start: 5027
• Page End: 5036
• Publication Date: 2017-09-02
• Subjects: social media -- operations management -- content analysis -- cluster analysis; Factory management -- Periodicals; 658.57
• DOI: 10.1080/00207543.2015.1053998
• Languages: English
• ISSNs: 0020-7543

Abstract

Abstract : 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 cannot only facilitate marketing research in view of customer behaviour, but can also aid other management disciplines. Operations management (OM) 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 OM research. A structured approach is proposed, which involves the analysis of social media comments and a statistical cluster analysis to identify the interrelationships amongst important factors. A real-life example is employed to demonstrate the concept.