Reconfiguring a hierarchical supply chain model under pandemic using text mining and social media analysis

Abstract

Purpose

This study is to reconfigure a hierarchical supply chain model utilizing databases and text files to understand future pathways due to COVID-19 pandemic has had a bullwhip effect, disrupting the global supply chain, and a mechanism is needed to address this disruptive event under pandemic uncertainties.

Design/methodology/approach

To address this mechanism, this study employs bibliometric analysis and text mining to reconfigure a hierarchical supply chain model under pandemic conditions and associates it with social media to conduct an intuitive visual analysis.

Findings

The current academic concerns are related to an overconcentration on risk management and a data-driven approach, generating an enormous gap between the concerns of academics and those of the public. The evidence shows that for both countries with outstanding performance and those that need improvement, the efficiency in terms of preventing the spread of the pandemic should be promoted.

Originality/value

This study contributes to (1) reconfiguring a hierarchical supply chain model under pandemic uncertainties and (2) bridging theory and practice by offering comparable interrelated attributes to guide post-COVID-19 strategies in the supply chain. The findings are that the supply management approach and big data are attributes that involve the concerns of world public and academics under pandemic uncertainties.

Citation

Wu, K.J., Bin, Y., Ren, M., Tseng, M.-L., Wang, Q. and Chiu, A.S.F. (2022), "Reconfiguring a hierarchical supply chain model under pandemic using text mining and social media analysis", Industrial Management & Data Systems, Vol. 122 No. 3, pp. 622-644. https://doi.org/10.1108/IMDS-06-2021-0358