IDEAS home Printed from https://ideas.repec.org/b/zbw/hiclpr/27.html
   My bibliography  Save this book

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
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/209196/1/hicl-vol-27.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.15480/882.2460?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Diedrich, Katharina & Klingebiel, Katja, 2019. "Smart risk analytics design for proactive early warning," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Artificial Intelligence and Digital Transformation in Supply Chain Management: Innovative Approaches for Supply Chains. Proceedings of the Hamburg Int, volume 27, pages 559-585, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    2. Laurent Lim, Lâm & Alpan, Gülgün & Penz, Bernard, 2014. "Reconciling sales and operations management with distant suppliers in the automotive industry: A simulation approach," International Journal of Production Economics, Elsevier, vol. 151(C), pages 20-36.
    3. Neungho Han & Juneho Um, 2024. "Risk management strategy for supply chain sustainability and resilience capability," Risk Management, Palgrave Macmillan, vol. 26(2), pages 1-26, May.
    4. Soumyatanu Mukherjee & Sidhartha S. Padhi, 2022. "Sourcing decision under interconnected risks: an application of mean–variance preferences approach," Annals of Operations Research, Springer, vol. 313(2), pages 1243-1268, June.
    5. Damianos P. Sakas & Ioannis Dimitrios G. Kamperos & Panagiotis Reklitis, 2021. "Estimating Risk Perception Effects on Courier Companies’ Online Customer Behavior during a Crisis, Using Crowdsourced Data," Sustainability, MDPI, vol. 13(22), pages 1-26, November.
    6. K. Katsaliaki & P. Galetsi & S. Kumar, 2022. "Supply chain disruptions and resilience: a major review and future research agenda," Annals of Operations Research, Springer, vol. 319(1), pages 965-1002, December.
    7. Jajja, Muhammad Shakeel Sadiq & Chatha, Kamran Ali & Farooq, Sami, 2018. "Impact of supply chain risk on agility performance: Mediating role of supply chain integration," International Journal of Production Economics, Elsevier, vol. 205(C), pages 118-138.
    8. Sanjoy Kumar Paul & Ruhul Sarker & Daryl Essam & Paul Tae-Woo Lee, 2019. "A mathematical modelling approach for managing sudden disturbances in a three-tier manufacturing supply chain," Annals of Operations Research, Springer, vol. 280(1), pages 299-335, September.
    9. Pasura Aungkulanon & Walailak Atthirawong & Pongchanun Luangpaiboon & Wirachchaya Chanpuypetch, 2024. "Navigating Supply Chain Resilience: A Hybrid Approach to Agri-Food Supplier Selection," Mathematics, MDPI, vol. 12(10), pages 1-41, May.
    10. Seyyed Mohammad Seyyed Alizadeh Ganji & Mohammad Hayati, 2016. "Identifying and Assessing the Risks in the Supply Chain," Modern Applied Science, Canadian Center of Science and Education, vol. 10(6), pages 1-74, June.
    11. Qazi, Abroon & Dickson, Alex & Quigley, John & Gaudenzi, Barbara, 2018. "Supply chain risk network management: A Bayesian belief network and expected utility based approach for managing supply chain risks," International Journal of Production Economics, Elsevier, vol. 196(C), pages 24-42.
    12. Rika Ampuh Hadiguna, 2012. "Decision support framework for risk assessment of sustainable supply chain," International Journal of Logistics Economics and Globalisation, Inderscience Enterprises Ltd, vol. 4(1/2), pages 35-54.
    13. Silvia Carpitella & Ilyas Mzougui & Joaquín Izquierdo, 2022. "Multi-criteria risk classification to enhance complex supply networks performance," OPSEARCH, Springer;Operational Research Society of India, vol. 59(3), pages 769-785, September.
    14. Jamshed Raza & Yuxin Liu & Jianwei Zhang & Nan Zhu & Zohaib Hassan & Habib Gul & Sikander Hussain, 2021. "Sustainable Supply Management Practices and Sustainability Performance: The Dynamic Capability Perspective," SAGE Open, , vol. 11(1), pages 21582440211, March.
    15. Yingjie Fan & Frank Schwartz & Stefan Voß & David L. Woodruff, 2017. "Stochastic programming for flexible global supply chain planning," Flexible Services and Manufacturing Journal, Springer, vol. 29(3), pages 601-633, December.
    16. Hatem Elleuch & Wafik Hachicha & Habib Chabchoub, 2014. "A combined approach for supply chain risk management: description and application to a real hospital pharmaceutical case study," Journal of Risk Research, Taylor & Francis Journals, vol. 17(5), pages 641-663, May.
    17. Shafiee, Mohammad & Zare-Mehrjerdi, Yahia & Govindan, Kannan & Dastgoshade, Sohaib, 2022. "A causality analysis of risks to perishable product supply chain networks during the COVID-19 outbreak era: An extended DEMATEL method under Pythagorean fuzzy environment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).
    18. Ali, Syed Mithun & Rahman, Md. Hafizur & Tumpa, Tasmia Jannat & Moghul Rifat, Abid Ali & Paul, Sanjoy Kumar, 2018. "Examining price and service competition among retailers in a supply chain under potential demand disruption," Journal of Retailing and Consumer Services, Elsevier, vol. 40(C), pages 40-47.
    19. Nishat Alam Choudhary & Shalabh Singh & Tobias Schoenherr & M. Ramkumar, 2023. "Risk assessment in supply chains: a state-of-the-art review of methodologies and their applications," Annals of Operations Research, Springer, vol. 322(2), pages 565-607, March.
    20. Margolis, Joshua T. & Sullivan, Kelly M. & Mason, Scott J. & Magagnotti, Mariah, 2018. "A multi-objective optimization model for designing resilient supply chain networks," International Journal of Production Economics, Elsevier, vol. 204(C), pages 174-185.

    Book Chapters

    The following chapters of this book are listed in IDEAS

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:hiclpr:27. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://hicl.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.