Enhancing supply chain sensing capability through social media: an environmental scanning perspective

Department

Information Systems and Security

Document Type

Article

Publication Date

1-17-2022

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.

Journal Title

Information Technology and People

Journal ISSN

09593845

Volume

35

Issue

1

First Page

367

Last Page

391

Digital Object Identifier (DOI)

10.1108/ITP-11-2019-0609

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