A data-driven, comparative review of the academic literature and news media on blockchain-enabled supply chain management: Trends, gaps, and research needs

The application of blockchain technology in supply chain management has become a popular area of discussion in research and practice. This paper develops a computational, data-driven synthesis of the scholarly literature versus news media on BT-enabled supply chain management (BT-SCM) to uncover major trends, understand how academic research is aligned with business practice, and find out existing gaps. Through text mining and topic modeling of 1148 full-text research papers and 5130 news articles, major themes within each domain, their patterns of evolution over time, and the depth and breadth of their associations were identified. Mapping analyses were also conducted based on the supply chain operations reference (SCOR) model and the main SCM research streams to further explore existing knowledge gaps. The findings revealed that BT-enabled supply chain asset management, BT-enabled reverse logistics and closed-loop supply chain, and actual versus anticipated performance outcomes of BT-SCM are among important pathways for future research. The findings also highlighted where there is more need to enhance the practical relevance of BT-SCM research considering advances in business adoption. The paper provides a comprehensive, unbiased assessment of the BT-SCM knowledge landscape and a taxonomy of the research questions related to the technical and managerial aspects of BT-SCM that are particularly useful for the community of researchers in the field. It offers a practice framework that can be applied to assess the academic literature on other emerging technologies in SCM where state-of-the-practice is key ot guiding research efforts.

Blockchain technology (BT), BT-enabled supply chain management (BT-SCM), Data-driven modeling. Latent Dirichlet allocation (LDA). Literature review. News media

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This research was funded, in part, by the Social Sciences and Humanities Research Council (SSHRC) (external link, opens in new window)  (Grant Number: 430-2021-00389) and the Natural Sciences and Engineering Research Council (NSERC) (external link, opens in new window)  (Grant Number: RGPIN-2019-06150) of Canada.