IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v348y2025i3d10.1007_s10479-023-05435-x.html
   My bibliography  Save this article

Impact of industry 4.0 on supply chain in made to order industries

Author

Listed:
  • Ramakrishnan Raman

    (Symbiosis Institute of Business Management
    Symbiosis International (Deemed University)

  • Pranav Vyas

    (Symbiosis International (Deemed University)

  • Hardik Vachharajani

    (Symbiosis International (Deemed University)

Abstract

This study explores the disruption that Industry 4.0 has on the supply chain of industries and organizations operating in custom-made or made-to-order products and services. While most industries focus on reducing costs via effective processes and employing efficiency-enhancing tools in production, not many organizations focus on the supply chain and its impact on it using Cyber-Physical Systems (CPS) and the use of real-time connection and computation and tools of Industry 4.0 in order to create value across their supply chain ecosystem. To understand this, the authors have used a case study-based design of an Indian made-to-order (custom-made) industrial organization and its logistic partners who together comprise a total supply chain ecosystem. The authors have attempted to find the challenges, opportunities, and recommendations for made-to-order in integrating Industry 4.0 tools into their process.

Suggested Citation

  • Ramakrishnan Raman & Pranav Vyas & Hardik Vachharajani, 2025. "Impact of industry 4.0 on supply chain in made to order industries," Annals of Operations Research, Springer, vol. 348(3), pages 1183-1194, May.
    • Handle: RePEc:spr:annopr:v:348:y:2025:i:3:d:10.1007_s10479-023-05435-x
    DOI: 10.1007/s10479-023-05435-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-023-05435-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-023-05435-x?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Qiu, Xuan & Luo, Hao & Xu, Gangyan & Zhong, Runyang & Huang, George Q., 2015. "Physical assets and service sharing for IoT-enabled Supply Hub in Industrial Park (SHIP)," International Journal of Production Economics, Elsevier, vol. 159(C), pages 4-15.
    2. Harris, Irina & Wang, Yingli & Wang, Haiyang, 2015. "ICT in multimodal transport and technological trends: Unleashing potential for the future," International Journal of Production Economics, Elsevier, vol. 159(C), pages 88-103.
    3. Zhong, Ray Y. & Huang, George Q. & Lan, Shulin & Dai, Q.Y. & Chen, Xu & Zhang, T., 2015. "A big data approach for logistics trajectory discovery from RFID-enabled production data," International Journal of Production Economics, Elsevier, vol. 165(C), pages 260-272.
    4. Mohamed Ben-Daya & Elkafi Hassini & Zied Bahroun, 2019. "Internet of things and supply chain management: a literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 57(15-16), pages 4719-4742, August.
    5. Guoqing Zhang & Yiqin Yang & Guoqing Yang, 2023. "Smart supply chain management in Industry 4.0: the review, research agenda and strategies in North America," Annals of Operations Research, Springer, vol. 322(2), pages 1075-1117, March.
    6. Ala-Risku, Timo & Karkkainen, Mikko, 2006. "Material delivery problems in construction projects: A possible solution," International Journal of Production Economics, Elsevier, vol. 104(1), pages 19-29, November.
    7. Julian Marius Müller & Daniel Kiel & Kai-Ingo Voigt, 2018. "What Drives the Implementation of Industry 4.0? The Role of Opportunities and Challenges in the Context of Sustainability," Sustainability, MDPI, vol. 10(1), pages 1-24, January.
    8. Tan, Kim Hua & Zhan, YuanZhu & Ji, Guojun & Ye, Fei & Chang, Chingter, 2015. "Harvesting big data to enhance supply chain innovation capabilities: An analytic infrastructure based on deduction graph," International Journal of Production Economics, Elsevier, vol. 165(C), pages 223-233.
    9. Daniel Kiel & Julian M. Müller & Christian Arnold & Kai-Ingo Voigt, 2017. "Sustainable Industrial Value Creation: Benefits And Challenges Of Industry 4.0," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 21(08), pages 1-34, December.
    10. Maciel M. Queiroz & Samuel Fosso Wamba & Charbel Jose Chiappetta Jabbour & Ana Beatriz Lopes De Sousa Jabbour & Marcio Cardoso Machado, 2022. "Adoption of Industry 4.0 technologies by organizations: a maturity levels perspective," Post-Print hal-04275087, HAL.
    Full references (including those not matched with items on IDEAS)

    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. Ray Qing Cao & Dara G. Schniederjans & Vicky Ching Gu, 2021. "Stakeholder sentiment in service supply chains: big data meets agenda-setting theory," Service Business, Springer;Pan-Pacific Business Association, vol. 15(1), pages 151-175, March.
    2. Tao, Zhibin & Chao, Jiaxiao, 2024. "Unlocking new opportunities in the industry 4.0 era, exploring the critical impact of digital technology on sustainable performance and the mediating role of GSCM practices," Innovation and Green Development, Elsevier, vol. 3(3).
    3. Mariani, Marcello & Borghi, Matteo, 2019. "Industry 4.0: A bibliometric review of its managerial intellectual structure and potential evolution in the service industries," Technological Forecasting and Social Change, Elsevier, vol. 149(C).
    4. Eryarsoy, Enes & Kilic, Huseyin Selcuk & Zaim, Selim & Doszhanova, Marzhan, 2022. "Assessing IoT challenges in supply chain: A comparative study before and during- COVID-19 using interval valued neutrosophic analytical hierarchy process," Journal of Business Research, Elsevier, vol. 147(C), pages 108-123.
    5. Guoqing Zhang & Yiqin Yang & Guoqing Yang, 2023. "Smart supply chain management in Industry 4.0: the review, research agenda and strategies in North America," Annals of Operations Research, Springer, vol. 322(2), pages 1075-1117, March.
    6. Rimalini Gadekar & Bijan Sarkar & Ashish Gadekar, 2022. "Key performance indicator based dynamic decision-making framework for sustainable Industry 4.0 implementation risks evaluation: reference to the Indian manufacturing industries," Annals of Operations Research, Springer, vol. 318(1), pages 189-249, November.
    7. Li, Ying & Dai, Jing & Cui, Li, 2020. "The impact of digital technologies on economic and environmental performance in the context of industry 4.0: A moderated mediation model," International Journal of Production Economics, Elsevier, vol. 229(C).
    8. Bai, Chunguang & Dallasega, Patrick & Orzes, Guido & Sarkis, Joseph, 2020. "Industry 4.0 technologies assessment: A sustainability perspective," International Journal of Production Economics, Elsevier, vol. 229(C).
    9. Pérez-Mesa, Juan Carlos & García Barranco, Mª Carmen & Ciagnocavo, Cynthia & Hernández Rubio, Jesús, 2023. "Seeking new strategic options for promotion of intermodal transport in perishables: the use of Short Sea Shipping," MPRA Paper 119464, University Library of Munich, Germany, revised 2023.
    10. Roßmann, Bernhard & Canzaniello, Angelo & von der Gracht, Heiko & Hartmann, Evi, 2018. "The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 135-149.
    11. Abirami Raja Santhi & Padmakumar Muthuswamy, 2022. "Pandemic, War, Natural Calamities, and Sustainability: Industry 4.0 Technologies to Overcome Traditional and Contemporary Supply Chain Challenges," Logistics, MDPI, vol. 6(4), pages 1-32, November.
    12. Kozjek, Dominik & Vrabič, Rok & Eržen, Gregor & Butala, Peter, 2018. "Identifying the business and social networks in the domain of production by merging the data from heterogeneous internet sources," International Journal of Production Economics, Elsevier, vol. 200(C), pages 181-191.
    13. Wang, Hui & Gong, Qiguo & Wang, Shouyang, 2017. "Information processing structures and decision making delays in MRP and JIT," International Journal of Production Economics, Elsevier, vol. 188(C), pages 41-49.
    14. Purva Grover & Arpan Kumar Kar, 2017. "Big Data Analytics: A Review on Theoretical Contributions and Tools Used in Literature," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 18(3), pages 203-229, September.
    15. Montecchi, Matteo & Plangger, Kirk & West, Douglas C., 2021. "Supply chain transparency: A bibliometric review and research agenda," International Journal of Production Economics, Elsevier, vol. 238(C).
    16. Wenping Liu & Bangyi Li & Guoqing Zhang & Zhe Wang & Yongbo Cheng, 2025. "Quality disclosure pattern options for competing refurbishers: blockchain vs online platform," Annals of Operations Research, Springer, vol. 344(2), pages 1027-1056, January.
    17. Julian Marius Müller & Daniel Kiel & Kai-Ingo Voigt, 2018. "What Drives the Implementation of Industry 4.0? The Role of Opportunities and Challenges in the Context of Sustainability," Sustainability, MDPI, vol. 10(1), pages 1-24, January.
    18. Raut, Rakesh D. & Mangla, Sachin Kumar & Narwane, Vaibhav S. & Dora, Manoj & Liu, Mengqi, 2021. "Big Data Analytics as a mediator in Lean, Agile, Resilient, and Green (LARG) practices effects on sustainable supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    19. Sanjeev Yadav & Sunil Luthra & Dixit Garg, 2022. "Internet of things (IoT) based coordination system in Agri-food supply chain: development of an efficient framework using DEMATEL-ISM," Operations Management Research, Springer, vol. 15(1), pages 1-27, June.
    20. Dong-Hui Jin & Hyun-Jung Kim, 2018. "Integrated Understanding of Big Data, Big Data Analysis, and Business Intelligence: A Case Study of Logistics," Sustainability, MDPI, vol. 10(10), pages 1-15, October.

    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:spr:annopr:v:348:y:2025:i:3:d:10.1007_s10479-023-05435-x. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.