Application of social media data in supply chain management: a systematic review

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Abstract

Purpose: Recently, big data has received considerable industrial and academic attention. Social media(SM) are becoming reliable big data sources that include various information such as customer’s opinions, product reviews and trends. However, the supply chain management (SCM) field has been lagging behind other industries in adopting SM. Hence, this paper aims to explore the value of SM and its application in SCM with recommendation for future work.
Methodology: This paper reviews the existing literature systematically to highlight major research works and trends by using bibliometric analysis.
Findings: Our review results show that the research on SM and SCM has attracted significant attention over the decade. SM data has been used together with different analytical tools (e.g. text mining, sentiment analysis) to manage different supply chain activities (e.g. demand forecasting, production). However, the potential of SM has not been thoroughly investigated due to the inherent nature of SM data. Therefore, this study field is in its infancy. We suggest some directions can be considered for future research, e.g. sentiment indicators for SC related posts. Originality: This paper is the first attempt to systematically analyse the interaction of SM data and SCM and to highlight the new approaches of adopting SM data for improving SCM.
Original languageEnglish
Title of host publicationProceedings of the Hamburg International Conference of Logistics
Place of PublicationBerlin-Kreuzberg
Pages499-523
Number of pages25
Volume31
DOIs
Publication statusPublished - 1 Dec 2021
EventHamburg International Conference of Logistics (HICL) 2021: New Opportunities in Logistics and Supply Chain Management - Online, hosted by the Hamburg University of Technology (TUHH), Germany
Duration: 22 Sep 202124 Sep 2021
https://hicl.org/

Conference

ConferenceHamburg International Conference of Logistics (HICL) 2021: New Opportunities in Logistics and Supply Chain Management
Country/TerritoryGermany
Period22/09/2124/09/21
Internet address

Keywords

  • big data
  • supply chain management
  • analytical review
  • social media

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