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

Jiahe Song, Kang Bok Lee, Zhongyun Zhou, Lin Jia*, Casey Cegielski, Soo Il Shin

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    9 Citations (Scopus)

    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.

    Original languageEnglish
    Pages (from-to)367-391
    Number of pages25
    JournalInformation Technology and People
    Volume35
    Issue number1
    DOIs
    Publication statusPublished - 17 Jan 2022

    Keywords

    • Environmental scanning
    • Sensing capability
    • Social media
    • Supply chain management
    • Uncertainty

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