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International Journal of Production Research Volume 53, 2015 - Issue 10
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Articles

Identification of supply chain disruptions with economic performance of firms using multi-category support vector machines

ShiJie YeSchool of Business Administration, Chongqing City Management College, Chongqing College Town, Chongqing, China
,
Zhi XiaoSchool of Economics and Business Administration, Chongqing University, Chongqing, China;Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, ChinaCorrespondence[email protected]
&
Guangfu ZhuSchool of Business Administration, Chongqing City Management College, Chongqing College Town, Chongqing, China
Pages 3086-3103 | Received 06 Feb 2012, Accepted 30 Sep 2014, Published online: 01 Dec 2014

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Alexandra Brintrup, Edward Kosasih, Philipp Schaffer, Ge Zheng, Guven Demirel & Bart L. MacCarthy. (2023) Digital supply chain surveillance using artificial intelligence: definitions, opportunities and risks. International Journal of Production Research 0:0, pages 1-22.
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Prasanta Kumar Dey, Soumyadeb Chowdhury, Amelie Abadie, Emilia Vann Yaroson & Sobhan Sarkar. (2023) Artificial intelligence-driven supply chain resilience in Vietnamese manufacturing small- and medium-sized enterprises. International Journal of Production Research 0:0, pages 1-40.
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Shivam Gupta, Sachin Modgil & Angappa Gunasekaran. (2020) Big data in lean six sigma: a review and further research directions. International Journal of Production Research 58:3, pages 947-969.
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George Baryannis, Sahar Validi, Samir Dani & Grigoris Antoniou. (2019) Supply chain risk management and artificial intelligence: state of the art and future research directions. International Journal of Production Research 57:7, pages 2179-2202.
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Saurabh Ambulkar, Jennifer V. Blackhurst & David E. Cantor. (2016) Supply chain risk mitigation competency: an individual-level knowledge-based perspective. International Journal of Production Research 54:5, pages 1398-1411.
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Articles from other publishers (16)

Mahmoud M. Bassiouni, Ripon K. Chakrabortty, Karam M. Sallam & Omar K. Hussain. (2024) Deep learning approaches to identify order status in a complex supply chain. Expert Systems with Applications 250, pages 123947.
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Adane Kassa, Daniel Kitaw, Ulrich Stache, Birhanu Beshah & Getachew Degefu. (2023) Artificial intelligence techniques for enhancing supply chain resilience: A systematic literature review, holistic framework, and future research. Computers & Industrial Engineering 186, pages 109714.
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Taufik Baidawi, Marimin, Suprihatin, Mulyorini Rahayuningsih & Wisnu Ananta Kusuma. Data mining based framework for identification and disaster risk assessment in the supply chain. Data mining based framework for identification and disaster risk assessment in the supply chain.
Nguyen Minh Tuan, Huynh Thi Khanh Chi & Nguyen Van Hop. (2022) A Hybrid Machine Learning Approach in Predicting E-Commerce Supply Chain Risks. A Hybrid Machine Learning Approach in Predicting E-Commerce Supply Chain Risks.
Kirti Nayal, Rakesh Raut, Pragati Priyadarshinee, Balkrishna Eknath Narkhede, Yigit Kazancoglu & Vaibhav Narwane. (2021) Exploring the role of artificial intelligence in managing agricultural supply chain risk to counter the impacts of the COVID-19 pandemic. The International Journal of Logistics Management 33:3, pages 744-772.
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Priyadarsini Patnaik. 2022. Handbook of Research on Supply Chain Resiliency, Efficiency, and Visibility in the Post-Pandemic Era. Handbook of Research on Supply Chain Resiliency, Efficiency, and Visibility in the Post-Pandemic Era 352 377 .
P. Anitha, Malini M. Patil & Rekha B. Venkatapur. (2021) COVID-19 Effect on Supply and Demand of Essential Commodities using Unsupervised Learning Method. Journal of The Institution of Engineers (India): Series B 102:6, pages 1311-1317.
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Mehrdokht Pournader, Hadi Ghaderi, Amir Hassanzadegan & Behnam Fahimnia. (2021) Artificial intelligence applications in supply chain management. International Journal of Production Economics 241, pages 108250.
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Erfan Babaee Tirkolaee, Saeid Sadeghi, Farzaneh Mansoori Mooseloo, Hadi Rezaei Vandchali & Samira Aeini. (2021) Application of Machine Learning in Supply Chain Management: A Comprehensive Overview of the Main Areas. Mathematical Problems in Engineering 2021, pages 1-14.
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A. V. Thomas & Biswajit Mahanty. (2018) Dynamic assessment of control system designs of information shared supply chain network experiencing supplier disruption. Operational Research 21:1, pages 425-451.
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Seyedmohsen Hosseini & Dmitry Ivanov. (2020) Bayesian networks for supply chain risk, resilience and ripple effect analysis: A literature review. Expert Systems with Applications 161, pages 113649.
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George Baryannis, Samir Dani & Grigoris Antoniou. (2019) Predicting supply chain risks using machine learning: The trade-off between performance and interpretability. Future Generation Computer Systems 101, pages 993-1004.
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YeongGwang Oh, Moise Busogi, Kasin Ransikarbum, Dongmin Shin, Daeil Kwon & Namhun Kim. (2019) Real-time quality monitoring and control system using an integrated cost effective support vector machine. Journal of Mechanical Science and Technology 33:12, pages 6009-6020.
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YeongGwang Oh, Kasin Ransikarbum, Moise Busogi, Daeil Kwon & Namhun Kim. (2019) Adaptive SVM-based real-time quality assessment for primer-sealer dispensing process of sunroof assembly line. Reliability Engineering & System Safety 184, pages 202-212.
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Bernd Hellingrath & Sandra Lechtenberg. 2019. The Art of Structuring. The Art of Structuring 283 296 .
Paulius Danenas & Gintautas Garsva. 2016. Artificial Intelligence in Financial Markets. Artificial Intelligence in Financial Markets 179 210 .

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