IDEAS home Printed from https://ideas.repec.org/a/gam/jlogis/v5y2021i4p86-d696329.html
   My bibliography  Save this article

Digital Supply Chain Twins—Conceptual Clarification, Use Cases and Benefits

Author

Listed:
  • Benno Gerlach

    (Chair of Logistics, Berlin University of Technology, 10623 Berlin, Germany)

  • Simon Zarnitz

    (Chair of Logistics, Berlin University of Technology, 10623 Berlin, Germany)

  • Benjamin Nitsche

    (Chair of Logistics, Berlin University of Technology, 10623 Berlin, Germany)

  • Frank Straube

    (Chair of Logistics, Berlin University of Technology, 10623 Berlin, Germany)

Abstract

Background : Digital supply chain twins (DSCT) are gaining increased attention in academia and practice as they emerge as one of the most important trends in logistics and supply chain management (LSCM). Still, there seems to be no common understanding of the term in scientific literature. Moreover, the broad field of LSCM allows for a multitude of feasible application areas and use cases , yet there exists no conclusive list of them as to date. Methods : This study builds upon a systematic literature review of 66 DSCT articles to identify application areas of DSCT in LSCM as well as specific use cases and their respective intended benefits . Results : To start with, the study derives a unified definition of DSCTs, including possible scopes of applications. Afterwards, five application areas of DSCT in LSCM are synthesized as well as 14 individual use cases and their respective intended benefits. Conclusions : The study leads towards a conceptual clarification of DSCT that is of importance for research and practice alike. For managers it additionally provides up-to-date use cases to guide DSCT applications in practice.

Suggested Citation

  • Benno Gerlach & Simon Zarnitz & Benjamin Nitsche & Frank Straube, 2021. "Digital Supply Chain Twins—Conceptual Clarification, Use Cases and Benefits," Logistics, MDPI, vol. 5(4), pages 1-24, December.
  • Handle: RePEc:gam:jlogis:v:5:y:2021:i:4:p:86-:d:696329
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2305-6290/5/4/86/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2305-6290/5/4/86/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Haße, Hendrik & Li, Bin & Weißenberg, Norbert & Cirullies, Jan & Otto, Boris, 2019. "Digital twin for real-time data processing in logistics," 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 4-28, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    2. Konstantinos Mykoniatis & Gregory A. Harris, 2021. "A digital twin emulator of a modular production system using a data-driven hybrid modeling and simulation approach," Journal of Intelligent Manufacturing, Springer, vol. 32(7), pages 1899-1911, October.
    3. Dmitry Ivanov & Alexandre Dolgui & Ajay Das & Boris Sokolov, 2019. "Digital Supply Chain Twins: Managing the Ripple Effect, Resilience, and Disruption Risks by Data-Driven Optimization, Simulation, and Visibility," International Series in Operations Research & Management Science, in: Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov (ed.), Handbook of Ripple Effects in the Supply Chain, pages 309-332, Springer.
    4. Min, Qingfei & Lu, Yangguang & Liu, Zhiyong & Su, Chao & Wang, Bo, 2019. "Machine Learning based Digital Twin Framework for Production Optimization in Petrochemical Industry," International Journal of Information Management, Elsevier, vol. 49(C), pages 502-519.
    5. Christian F. Durach & Joakim Kembro & Andreas Wieland, 2017. "A New Paradigm for Systematic Literature Reviews in Supply Chain Management," Journal of Supply Chain Management, Institute for Supply Management, vol. 53(4), pages 67-85, October.
    6. Ícaro Romolo Sousa Agostino & Eike Broda & Enzo M. Frazzon & Michael Freitag, 2020. "Using a Digital Twin for Production Planning and Control in Industry 4.0," International Series in Operations Research & Management Science, in: Boris Sokolov & Dmitry Ivanov & Alexandre Dolgui (ed.), Scheduling in Industry 4.0 and Cloud Manufacturing, chapter 0, pages 39-60, Springer.
    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. Tsega Y. Melesse & Chiara Franciosi & Valentina Di Pasquale & Stefano Riemma, 2023. "Analyzing the Implementation of Digital Twins in the Agri-Food Supply Chain," Logistics, MDPI, vol. 7(2), pages 1-17, June.
    2. Benjamin Nitsche & Frank Straube, 2023. "Current State and Future of International Logistics Networks—The Role of Digitalization and Sustainability in a Globalized World," Logistics, MDPI, vol. 7(4), pages 1-9, November.

    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. Amelio, Andrea & Giardino-Karlinger, Liliane & Valletti, Tommaso, 2020. "Exclusionary pricing in two-sided markets," International Journal of Industrial Organization, Elsevier, vol. 73(C).
    2. Aditi S. Saha & Rakesh D. Raut & Vinay Surendra Yadav & Abhijit Majumdar, 2022. "Blockchain Changing the Outlook of the Sustainable Food Supply Chain to Achieve Net Zero?," Sustainability, MDPI, vol. 14(24), pages 1-21, December.
    3. Yu Gong & Xiaojiang Xu & Changping Zhao & Tobias Schoenherr, 2024. "Multi-Tier Supply Chain Learning Networks: A Simulation Study Based on the Experience-Weighted Attraction (EWA) Model," Sustainability, MDPI, vol. 16(10), pages 1-25, May.
    4. Ayman AboElHassan & Soumaya Yacout, 2023. "A digital shadow framework using distributed system concepts," Journal of Intelligent Manufacturing, Springer, vol. 34(8), pages 3579-3598, December.
    5. Pirrone, Lorenzo & Meyer, Dennis, 2021. "Development of a Procurement-4.0-PMS using the Balanced Scorecard," 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 691-721, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    6. Robert Suurmond & Finn Wynstra & Jan Dul, 2020. "Unraveling the Dimensions of Supplier Involvement and their Effects on NPD Performance: A Meta‐Analysis," Journal of Supply Chain Management, Institute for Supply Management, vol. 56(3), pages 26-46, July.
    7. Hendrik Haße & Hendrik Valk & Frederik Möller & Boris Otto, 2022. "Design Principles for Shared Digital Twins in Distributed Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(6), pages 751-772, December.
    8. Thomas Johnsen & Marie-Anne Le Dain & Nadine Kiratli & Holger Schiele, 2022. "Editorial: Purchasing and innovation: Past, present and future of the field of research," Post-Print hal-03761525, HAL.
    9. Nassim Mrabti & Nadia Hamani & Laurent Delahoche, 2022. "A Comprehensive Literature Review on Sustainable Horizontal Collaboration," Sustainability, MDPI, vol. 14(18), pages 1-38, September.
    10. Chi Ma & Hongquan Gui & Jialan Liu, 2023. "Self learning-empowered thermal error control method of precision machine tools based on digital twin," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 695-717, February.
    11. Mukesh Kumar & Rakesh D. Raut & Mahak Sharma & Vikas Kumar Choubey & Sanjoy Kumar Paul, 2022. "Enablers for resilience and pandemic preparedness in food supply chain," Operations Management Research, Springer, vol. 15(3), pages 1198-1223, December.
    12. Tessmann, R. & Elbert, R., 2022. "Multi sided platforms in competitive B2B networks with varying governmental influence – a taxonomy of Port and Cargo Community System business models," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 132320, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    13. Michael Sony & Jiju Antony & Guilherme L. Tortorella, 2023. "Critical Success Factors for Successful Implementation of Healthcare 4.0: A Literature Review and Future Research Agenda," IJERPH, MDPI, vol. 20(5), pages 1-22, March.
    14. Beatriz Acero & Maria Jesus Saenz & Davide Luzzini, 2022. "Introducing synchromodality: One missing link between transportation and supply chain management," Journal of Supply Chain Management, Institute for Supply Management, vol. 58(1), pages 51-64, January.
    15. Chen, Xi & Wong, Tse Chiu, 2021. "Application of social media data in supply chain management : A systematic review," 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 499-523, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    16. Muhammad Umar Farooq & Amjad Hussain & Tariq Masood & Muhammad Salman Habib, 2021. "Supply Chain Operations Management in Pandemics: A State-of-the-Art Review Inspired by COVID-19," Sustainability, MDPI, vol. 13(5), pages 1-33, February.
    17. Diéssica Oliveira-Dias & José Moyano-Fuentes & Juan Manuel Maqueira-Marín, 2022. "Understanding the relationships between information technology and lean and agile supply chain strategies: a systematic literature review," Annals of Operations Research, Springer, vol. 312(2), pages 973-1005, May.
    18. Konstantinos Siassiakos & Stamatia Ilioudi & Tsaktsira Effrosyni & Vasiliki Mitsiou & Dimitris Nanouris, 2020. "Utilization of Blockchain Technology in Greek Public Administration," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 10(4), pages 1-12.
    19. Shraddha Mishra & Surya Prakash Singh, 2022. "A stochastic disaster-resilient and sustainable reverse logistics model in big data environment," Annals of Operations Research, Springer, vol. 319(1), pages 853-884, December.
    20. Alena Khaslavskaya & Violeta Roso, 2020. "Dry ports: research outcomes, trends, and future implications," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 22(2), pages 265-292, June.

    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:gam:jlogis:v:5:y:2021:i:4:p:86-:d:696329. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.