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Open AccessArticle

Text Mining for Supply Chain Risk Management in the Apparel Industry

1
International Graduate School for Dynamics in Logistics (IGS), University of Bremen, Hochschulring 20, 28359 Bremen, Germany
2
Faculty of Production Engineering, University of Bremen, Badgasteiner Str., 28359 Bremen, Germany
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BIBA—Bremer Institut für Produktion und Logistik GmbH, University of Bremen, Hochschulring 20, 28359 Bremen, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Yosoon Choi
Appl. Sci. 2021, 11(5), 2323; https://doi.org/10.3390/app11052323
Received: 12 January 2021 / Revised: 20 February 2021 / Accepted: 2 March 2021 / Published: 5 March 2021
(This article belongs to the Section Computing and Artificial Intelligence)
Text mining tools are now widely used for the efficient management of information and resources in business, academic and research organizations. This paper provides a comprehensive overview of research articles on the application of text mining techniques in the field of Supply Chain Risk Management and the apparel industry. Research articles published between 2000 and 2020, were obtained from various journals through two online databases, i.e., SCOPUS and IEEE Xplore. Through a systematic approach following PRISMA guidelines, 370 research papers were screened, filtered and finally classified into three main areas: Supply Chain Risk Management and outsourcing in the apparel industry, application of text mining in Supply Chain Risk Management and application of text mining in the apparel industry. In this study, we have identified a comprehensive list of various available data sources for text mining, methodologies and risks associated with outsourcing in the apparel industry. We classify the gaps in expanding the application of text mining in the apparel industry’s Supply Chain Risk Management. Extracting useful information from online newspapers through text mining could vividly enhance the ability to monitor supply chain risks and provide the ability to link data to provide decision makers with the right information at the right time. View Full-Text
Keywords: supply chain risk management; big data and big data analytics; text mining; apparel industry; data mining techniques; future technologies supply chain risk management; big data and big data analytics; text mining; apparel industry; data mining techniques; future technologies
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MDPI and ACS Style

Shah, S.M.; Lütjen, M.; Freitag, M. Text Mining for Supply Chain Risk Management in the Apparel Industry. Appl. Sci. 2021, 11, 2323. https://doi.org/10.3390/app11052323

AMA Style

Shah SM, Lütjen M, Freitag M. Text Mining for Supply Chain Risk Management in the Apparel Industry. Applied Sciences. 2021; 11(5):2323. https://doi.org/10.3390/app11052323

Chicago/Turabian Style

Shah, Sayed M.; Lütjen, Michael; Freitag, Michael. 2021. "Text Mining for Supply Chain Risk Management in the Apparel Industry" Appl. Sci. 11, no. 5: 2323. https://doi.org/10.3390/app11052323

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