Enhancing supply chain sensing capability through social media: an environmental scanning perspective
Information Technology & People
ISSN: 0959-3845
Article publication date: 2 February 2021
Issue publication date: 17 January 2022
Abstract
Purpose
The purpose of this study is to investigate the relationship between social media and sensing capability for supply chain management (SCM) from an environmental scanning perspective. The authors consider upstream supply and downstream customer markets as two aspects of social media-enabled environmental scanning (SMES). The moderating effects of three uncertainties are explored.
Design/methodology/approach
The data were collected from 178 supply chain professionals through a survey. Generalized estimating equations (GEE) were used to analyze the data.
Findings
SMES in both supply and customer markets enhance sensing capability. Interestingly, the results reveal an accelerating effect on sensing by the incremental effort of SMES-supply. However, that of SMES-customer leads to a decelerating outcome for sensing. Also, uncertainties, especially the demand- and technology-related, play a series of interacting effects according to SMES levels.
Research limitations/implications
This research contributes to the literature of operations and supply chains regarding social media strategies and dynamic capabilities. It opens the black box of environmental scanning behavior on social media and adds new knowledge on the dynamic influence of such behavior toward organizational sensing capability for SCM. In addition, further understanding on supply chain uncertainty as a moderator is also strengthened through this research.
Originality/value
This research is the first to empirically uncover the effect of social media on sensing capability for SCM through the lens of environmental scanning. The results support the employment of social networking for improving supply and demand sensing.
Keywords
Acknowledgements
Corrigendum: It has come to the attention of the publisher that the article Song, J., Lee, K.-B., Zhou, Z., Jia, L., Cegielski, C. and Shin, S.I. (2021), “Enhancing supply chain sensing capability through social media: an environmental scanning perspective”, Information Technology & People, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/ITP-11-2019-0609 published an incorrect affiliation for author Soo Il Shin, this has now been updated to ‘Information Systems and Security, Kennesaw State University, Kennesaw, Georgia, USA’. The authors sincerely apologise for this. The authors sincerely thank the senior editor, Dr. Nianxin Wang, and the anonymous reviewers for their valuable comments. Special thanks go to Dr. R. Kelly Rainer, Jr., who provided feedback and advice at the early stage of this study. The work for the corresponding author Lin Jia was partially supported by the National Natural Science Foundation of China (Grant ID: NSFC 71602009); Special Fund for Joint Development Program of Beijing Municipal Commission of Education.
Citation
Song, J., Lee, K.-B., Zhou, Z., Jia, L., Cegielski, C. and Shin, S.I. (2022), "Enhancing supply chain sensing capability through social media: an environmental scanning perspective", Information Technology & People, Vol. 35 No. 1, pp. 367-391. https://doi.org/10.1108/ITP-11-2019-0609
Publisher
:Emerald Publishing Limited
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