The role of social media data in operations and production management

Hing Kai Chan*, Ewelina Lacka, Rachel W.Y. Yee, Ming K. Lim

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

46 Citations (Scopus)
1206 Downloads (Pure)

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.

Original languageEnglish
Pages (from-to)5027-5036
Number of pages10
JournalInternational Journal of Production Research
Volume55
Issue number17
Early online date14 Jun 2015
DOIs
Publication statusPublished - 2017

Keywords

  • cluster analysis
  • content analysis
  • operations management
  • social media

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