Digital Supply Chain Resilience: Analyzing the Literature Using a Topic Modeling Approach

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dc.contributor.author Kazeroonimonfared, Atiyeh
dc.contributor.author Vatrapu, Ravi
dc.date.accessioned 2023-12-26T18:37:04Z
dc.date.available 2023-12-26T18:37:04Z
dc.date.issued 2024-01-03
dc.identifier.isbn 978-0-9981331-7-1
dc.identifier.other b4f943be-664c-4ba7-b947-22d00d2cc7ff
dc.identifier.uri https://hdl.handle.net/10125/106548
dc.language.iso eng
dc.relation.ispartof Proceedings of the 57th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Intelligent Decision Support for Logistics and Supply Chain Management
dc.subject digitalization
dc.subject resilience
dc.subject supply chain
dc.subject topic modeling
dc.title Digital Supply Chain Resilience: Analyzing the Literature Using a Topic Modeling Approach
dc.type Conference Paper
dc.type.dcmi Text
dcterms.abstract The Covid-19 pandemic highlighted digitalization's crucial role in creating resilient supply chains. Academics believe that technologies like Big Data Analytics, the Internet of Things, Blockchain, and Cloud Computing enhance supply chain visibility and transparency. Leveraging these technologies helps firms proactively anticipate disruptions, adapt swiftly, and cultivate resilient and agile supply chains. Although the pandemic accelerated the adoption of digital technologies in supply chain management, comprehensive academic research on digital supply chain resilience is lacking. The primary objective of this study is to thoroughly explore the existing body of literature in this field and analyze it to capture the knowledge that has been neglected in the previous research. Through text mining and topic modeling, we identified the research topics and trends. Finally, we identified digital transformation, viable supply chain, Internet-of-Things, Blockchain, Machine Learning, and Artificial Intelligence as the promising research directions in the field of digital supply chain resilience.
dcterms.extent 10 pages
prism.startingpage 1380
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Intelligent Decision Support for Logistics and Supply Chain Management