Paper Info
Title
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.
Year
DOI
Venue
2022
10.1108/IMDS-06-2021-0358
INDUSTRIAL MANAGEMENT & DATA SYSTEMS
Keywords
DocType
Volume
Hierarchical supply chain model, Bibliometric analysis, Text mining, Social media analysis
Journal
122
Issue
ISSN
Citations 
3
0263-5577
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Kuo Jui Wu100.34
Yan Bin200.34
Maomao Ren300.34
MingLang Tseng433026.97
Qing Wang534576.64
Anthony S. F. Chiu600.34