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Artificial Intelligence and Digital Transformation in Supply Chain Management: Innovative Approaches for Supply Chains

Editor

Listed:
  • Kersten, Wolfgang
  • Blecker, Thorsten
  • Ringle, Christian M.

Abstract

This volume contains research contributions by an international group of authors addressing innovative and technology-based approaches for logistics and supply chains. They present business models and investment options for enhanced strategic decision making as well as recent approaches for supply chain analytics and risk management. This volume, edited by Wolfgang Kersten, Thorsten Blecker and Christian Ringle, provides valuable insights into the digitalization of Supply Chain Management and Logistics with regard to: Innovation and Technology Management, Advanced Manufacturing and Industry 4.0. Supply Chain Analytics, Risk and Security Management.

Individual chapters are listed in the "Chapters" tab

Suggested Citation

  • Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), 2019. "Artificial Intelligence and Digital Transformation in Supply Chain Management: Innovative Approaches for Supply Chains," Proceedings of the Hamburg International Conference of Logistics (HICL), Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management, volume 27, number 27.
    • Handle: RePEc:zbw:hiclpr:27
    DOI: 10.15480/882.2460
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    References listed on IDEAS

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    1. Thomé, Antonio Márcio T. & Scavarda, Luiz Felipe & Pires, Sílvio R.I. & Ceryno, Paula & Klingebiel, Katja, 2014. "A multi-tier study on supply chain flexibility in the automotive industry," International Journal of Production Economics, Elsevier, vol. 158(C), pages 91-105.
    2. William Ho & Tian Zheng & Hakan Yildiz & Srinivas Talluri, 2015. "Supply chain risk management: a literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 53(16), pages 5031-5069, August.
    3. Arunachalam, Deepak & Kumar, Niraj & Kawalek, John Paul, 2018. "Understanding big data analytics capabilities in supply chain management: Unravelling the issues, challenges and implications for practice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 416-436.
    4. Tang, Ou & Nurmaya Musa, S., 2011. "Identifying risk issues and research advancements in supply chain risk management," International Journal of Production Economics, Elsevier, vol. 133(1), pages 25-34, September.
    5. Fan, Huan & Li, Gang & Sun, Hongyi & Cheng, T.C.E., 2017. "An information processing perspective on supply chain risk management: Antecedents, mechanism, and consequences," International Journal of Production Economics, Elsevier, vol. 185(C), pages 63-75.
    6. Volling, Thomas & Matzke, Andreas & Grunewald, Martin & Spengler, Thomas S., 2013. "Planning of capacities and orders in build-to-order automobile production: A review," European Journal of Operational Research, Elsevier, vol. 224(2), pages 240-260.
    7. Thun, Jörn-Henrik & Hoenig, Daniel, 2011. "An empirical analysis of supply chain risk management in the German automotive industry," International Journal of Production Economics, Elsevier, vol. 131(1), pages 242-249, May.
    8. Volling, Thomas & Spengler, Thomas S., 2011. "Modeling and simulation of order-driven planning policies in build-to-order automobile production," International Journal of Production Economics, Elsevier, vol. 131(1), pages 183-193, May.
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    Citations

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    Cited by:

    1. Büttner, Daniel & Scheidler, Anne Antonia & Rabe, Markus, 2021. "A reference model for data-driven sales planning: Development of the model's framework and functionality," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Ringle, Christian M. & Blecker, Thorsten (ed.), Adapting to the Future: How Digitalization Shapes Sustainable Logistics and Resilient Supply Chain Management. Proceedings of the Hamburg Internationa, volume 31, pages 441-476, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    2. Farheen Naz & Anil Kumar & Abhijit Majumdar & Rohit Agrawal, 2022. "Is artificial intelligence an enabler of supply chain resiliency post COVID-19? An exploratory state-of-the-art review for future research," Operations Management Research, Springer, vol. 15(1), pages 378-398, June.
    3. Singh, Shiwangi & Sharma, Meenakshi & Dhir, Sanjay, 2021. "Modeling the effects of digital transformation in Indian manufacturing industry," Technology in Society, Elsevier, vol. 67(C).

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