Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/21604
Title: The role of social media data in operations and production management
Authors: Chan, HK
Lacka, E
Yee, RWY 
Lim, MK
Keywords: Cluster analysis
Content analysis
Operations management
Social media
Issue Date: 2015
Publisher: Taylor & Francis
Source: International journal of production research, 2015 How to cite?
Journal: International journal of production research 
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.
URI: http://hdl.handle.net/10397/21604
ISSN: 0020-7543
EISSN: 1366-588X
DOI: 10.1080/00207543.2015.1053998
Appears in Collections:Journal/Magazine Article

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