IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v59y2021i7p2055-2078.html
   My bibliography  Save this article

Researchers' perspectives on Industry 4.0: multi-disciplinary analysis and opportunities for operations management

Author

Listed:
  • Dmitry Ivanov
  • Christopher S. Tang
  • Alexandre Dolgui
  • Daria Battini
  • Ajay Das

Abstract

While Industry 4.0 has been trending in practice and research, operations management studies in this area remain nascent. Our intent is to understand the current state of research in Industry 4.0 in different disciplines and deduce insights and opportunities for future research in operations management. In this paper, we provide a focused analysis to examine the state-of-the-art research in Industry 4.0. To learn about researchers’ perspectives about Industry 4.0, we conducted a large-scale, cross-disciplinary and global survey on Industry 4.0 topics among researchers in industrial engineering, operations management, operations research, control and data science at the 9th IFAC MIM 2019 Conference in Berlin in August 2019. By using our survey findings and literature analysis, we build structural and conceptual frameworks to understand the current state of knowledge and to propose future research opportunities for operations management scholars.Glossary of AbbreviationsAGV: Automated guided vehicle; AI: Artificial intelligence; APS: Advanced planning system: a wide variety of software tools and techniques, with many applications in manufacturing and logistics (including the service sector); BDA: Big data analytics; CAS: Complex adaptive system: a system composed of many interacting parts that evolve and adapt over time; CIM: Computer integrated manufacturing; CPFR: Collaborative planning, forecasting and replenishment; CPS: Cyber-physical system: a seamless integration of computation and physical components; DAMCLS: Decision analysis, modelling, control and learning systems; ERP: Enterprise resource planning; FMS: Flexible manufacturing system; I4.0: Industry 4.0; IFAC: International Federation of Automatic Control: a federation is concerned with the impact of control technology on society; IME: Industrial and mechanical engineering; IoT: Internet-of-Things; IT: Information technology; M2M: Machine-to-machine; MAS: Multi-agent system: a loosely coupled network of software agents that interact to solve problems that are beyond the individual capacities or knowledge of each problem solver; OR: Operations research; RFID: Radio frequency identification: a technology that uses electromagnetic fields to automatically identify and track tags attached to objects; RMS: Reconfigurable manufacturing system: a manufacturing system that can change and evolve rapidly in order to adjust its productivity capacity and functionality; OM: Operations management; T&T: Track and trace system; VCA: VOS viewer co-occurrence analysis: a software tool for visualising bibliometric networks; VMI: Vendor-managed inventory.

Suggested Citation

  • Dmitry Ivanov & Christopher S. Tang & Alexandre Dolgui & Daria Battini & Ajay Das, 2021. "Researchers' perspectives on Industry 4.0: multi-disciplinary analysis and opportunities for operations management," International Journal of Production Research, Taylor & Francis Journals, vol. 59(7), pages 2055-2078, April.
    • Handle: RePEc:taf:tprsxx:v:59:y:2021:i:7:p:2055-2078
    DOI: 10.1080/00207543.2020.1798035
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2020.1798035
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207543.2020.1798035?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.

    Citations

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


    Cited by:

    1. Kayikci, Yasanur & Kazancoglu, Yigit & Gozacan-Chase, Nazlican & Lafci, Cisem & Batista, Luciano, 2022. "Assessing smart circular supply chain readiness and maturity level of small and medium-sized enterprises," Journal of Business Research, Elsevier, vol. 149(C), pages 375-392.
    2. Naghshineh, Bardia & Carvalho, Helena, 2022. "The implications of additive manufacturing technology adoption for supply chain resilience: A systematic search and review," International Journal of Production Economics, Elsevier, vol. 247(C).
    3. Tsan-Ming Choi & Alexandre Dolgui & Dmitry Ivanov & Erwin Pesch, 2022. "OR and analytics for digital, resilient, and sustainable manufacturing 4.0," Annals of Operations Research, Springer, vol. 310(1), pages 1-6, March.
    4. Fernando Garrigós-Simón & Silvia Sanz-Blas & Yeamduan Narangajavana & Daniela Buzova, 2021. "The Nexus between Big Data and Sustainability: An Analysis of Current Trends and Developments," Sustainability, MDPI, vol. 13(12), pages 1-24, June.
    5. Ivanov, Dmitry & Dolgui, Alexandre & Sokolov, Boris, 2022. "Cloud supply chain: Integrating Industry 4.0 and digital platforms in the “Supply Chain-as-a-Service”," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    6. Ivanov, Dmitry, 2024. "Cash flow dynamics in the supply chain during and after disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).
    7. Zhimei Lei & Li Cui & Jing Tang & Lujie Chen & Bingbing Liu, 2024. "Supply chain resilience in the context of I4.0 and I5.0 from a multilayer network ripple effect perspective," Annals of Operations Research, Springer, vol. 342(2), pages 1149-1192, November.
    8. Bhatti, Waheed Akbar & Vahlne, Jan-Erik & Glowik, Mario & Larimo, Jorma Antero, 2022. "The impact of industry 4.0 on the 2017 version of the Uppsala model," International Business Review, Elsevier, vol. 31(4).
    9. 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.
    10. Thees, Hannes & Störmann, Elina & Thiele, Franziska & Olbrich, Natalie, 2021. "Shaping digitalization among German tourism service providers: Processes and implications," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 7, pages 3-15.
    11. Zhao, Zichao & Li, Dexuan & Dai, Wensheng, 2023. "Machine-learning-enabled intelligence computing for crisis management in small and medium-sized enterprises (SMEs)," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    12. Li, Guo & Xue, Jing & Li, Na & Ivanov, Dmitry, 2022. "Blockchain-supported business model design, supply chain resilience, and firm performance," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).
    13. Zhu, Minghao & Liang, Chen & Yeung, Andy C.L. & Zhou, Honggeng, 2024. "The impact of intelligent manufacturing on labor productivity: An empirical analysis of Chinese listed manufacturing companies," International Journal of Production Economics, Elsevier, vol. 267(C).
    14. Núñez-Merino, Miguel & Maqueira-Marín, Juan Manuel & Moyano-Fuentes, José & Castaño-Moraga, Carlos Alberto, 2022. "Industry 4.0 and supply chain. A Systematic Science Mapping analysis," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    15. Hannes Thees & Elina Störmann & Franziska Thiele & Natalie Olbrich, 2021. "Shaping digitalization among German tourism service providers: Processes and implications," Post-Print hal-03373971, HAL.
    16. EDU Tudor & CONSTANTINESCU Raluca, 2022. "Internet of Things (IoT) as an Instrument to Improve Business and Marketing Strategies. A Literature Review," European Journal of Interdisciplinary Studies, Bucharest Economic Academy, issue 02, June.
    17. Dabić, Marina & Maley, Jane F. & Črešnar, Rok & Nedelko, Zlatko, 2023. "Unappreciated channel of manufacturing productivity under industry 4.0: Leadership values and capabilities," Journal of Business Research, Elsevier, vol. 162(C).
    18. Tsan‐Ming Choi & Subodha Kumar & Xiaohang Yue & Hau‐Ling Chan, 2022. "Disruptive Technologies and Operations Management in the Industry 4.0 Era and Beyond," Production and Operations Management, Production and Operations Management Society, vol. 31(1), pages 9-31, January.
    19. Xiong, Yangchun & Lam, Hugo K.S. & Karimi, Sahar, 2024. "The effect of virtual reality-enabled manufacturing practices on production efficiency," International Journal of Production Economics, Elsevier, vol. 274(C).
    20. Gosavi, Abhijit & Gosavi, Aparna A., 2024. "CONWIP control in the digitized world: The case of the cyber-physical jobshop," International Journal of Production Economics, Elsevier, vol. 270(C).
    21. Özköse, Hakan & Güney, Gül, 2023. "The effects of industry 4.0 on productivity: A scientific mapping study," Technology in Society, Elsevier, vol. 75(C).
    22. Yongming Wang & Umar Iqbal & Yingmei Gong, 2021. "The Performance of Resilient Supply Chain Sustainability in Covid-19 by Sourcing Technological Integration," Sustainability, MDPI, vol. 13(11), pages 1-17, May.
    23. Sehrish Atif & Shehzad Ahmed & Muhammad Wasim & Bassam Zeb & Zeeshan Pervez & Lorraine Quinn, 2021. "Towards a Conceptual Development of Industry 4.0, Servitisation, and Circular Economy: A Systematic Literature Review," Sustainability, MDPI, vol. 13(11), pages 1-27, June.
    24. Mitsuhiro Fukuzawa & Ryosuke Sugie & Youngwon Park & Jin Shi, 2022. "An Exploratory Case Study on the Metrics and Performance of IoT Investment in Japanese Manufacturing Firms," Sustainability, MDPI, vol. 14(5), pages 1-21, February.
    25. Sun, Mingyao & Ng, Chi To & Yang, Liu & Zhang, Tianhua, 2024. "Optimal after-sales service offering strategy: Additive manufacturing, traditional manufacturing, or hybrid?," International Journal of Production Economics, Elsevier, vol. 268(C).

    More about this item

    Statistics

    Access and download statistics

    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:taf:tprsxx:v:59:y:2021:i:7:p:2055-2078. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    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.