The role of social media data in operations and production management

H. K. Chan; E. Lacka; R. W. Y. Yee; Ming K. Lim

doi:10.1080/00207543.2015.1053998

The role of social media data in operations and production management

H. K. Chan, E. Lacka, R. W. Y. Yee, Ming K. Lim

Research output: Contribution to journal › Article › peer-review

46 Citations (Scopus)

67 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 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.

Original language	English
Pages (from-to)	5027-5036
Number of pages	10
Journal	International Journal of Production Research
Volume	55
Issue number	17
Early online date	15 Jun 2015
DOIs	https://doi.org/10.1080/00207543.2015.1053998
Publication status	Published - 2017
Externally published	Yes

Bibliographical note

This 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.

Keywords

Social media
Operations management
Content analysis
Cluster analysis

Access to Document

10.1080/00207543.2015.1053998

Post-PrintAccepted author manuscript, 935 KBLicence: CC BY

Cite this

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title = "The role of social media data in operations and production management",

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 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.",

keywords = "Social media, Operations management, Content analysis, Cluster analysis",

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year = "2017",

doi = "10.1080/00207543.2015.1053998",

language = "English",

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TY - JOUR

T1 - The role of social media data in operations and production management

AU - Chan, H. K.

AU - Lacka, E.

AU - Yee, R. W. Y.

AU - Lim, Ming K.

N1 - This 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.

PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

KW - Social media

KW - Operations management

KW - Content analysis

KW - Cluster analysis

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DO - 10.1080/00207543.2015.1053998

M3 - Article

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EP - 5036

JO - International Journal of Production Research

JF - International Journal of Production Research

IS - 17

ER -

The role of social media data in operations and production management

Abstract

Bibliographical note

Keywords

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Cite this