IDEAS home Printed from https://ideas.repec.org/a/spr/opmare/v15y2022i3d10.1007_s12063-022-00275-7.html
   My bibliography  Save this article

Industry 4.0-driven operations and supply chains for the circular economy: a bibliometric analysis

Author

Listed:
  • Biman Darshana Hettiarachchi

    (University of Kassel)

  • Stefan Seuring

    (University of Kassel)

  • Marcus Brandenburg

    (University of Kassel
    Flensburg University of Applied Sciences)

Abstract

The Industry 4.0 (I4.0) concept paves the way for the circular economy (CE) as advanced digital technologies enable sustainability initiatives. Hence, I4.0-driven CE-oriented supply chains (SCs) have improved sustainable performance, flexibility and interoperability. In order to smoothly embrace circular practices in digitally enabled SCs, quantitative techniques have been identified as crucial. Therefore, the intersection of I4.0, CE, supply chain management (SCM) and quantitative techniques is an emerging research arena worthy of investigation. This article presents a bibliometric analysis to identify the established and evolving research clusters in the topological analysis by identifying collaboration patterns, interrelations and the studies that significantly dominate the intersection of the analysed fields. Further, this study investigates the current research trends and presents potential directions for future research. The bibliometric analysis highlights that additive manufacturing (AM), big data analytics (BDA) and the Internet of Things (IoT) are the most researched technologies within the intersection of CE and sustainable SCM. Evaluation of intellectual, conceptual and social structures revealed that I4.0-driven sustainable operations and manufacturing are emerging research fields. This study provides research directions to guide scholars in the further investigation of these four identified fields while exploring the potential quantitative methods and techniques that can be applied in I4.0-enabled SCs in the CE context.

Suggested Citation

  • Biman Darshana Hettiarachchi & Stefan Seuring & Marcus Brandenburg, 2022. "Industry 4.0-driven operations and supply chains for the circular economy: a bibliometric analysis," Operations Management Research, Springer, vol. 15(3), pages 858-878, December.
  • Handle: RePEc:spr:opmare:v:15:y:2022:i:3:d:10.1007_s12063-022-00275-7
    DOI: 10.1007/s12063-022-00275-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12063-022-00275-7
    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/s12063-022-00275-7?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. Mohamed M. Dhiaf & Osama F. Atayah & Nohade Nasrallah & Guilherme F. Frederico, 2021. "Thirteen years of Operations Management Research (OMR) journal: a bibliometric analysis and future research directions," Operations Management Research, Springer, vol. 14(3), pages 235-255, December.
    2. Wang, Gang & Gunasekaran, Angappa & Ngai, Eric W.T. & Papadopoulos, Thanos, 2016. "Big data analytics in logistics and supply chain management: Certain investigations for research and applications," International Journal of Production Economics, Elsevier, vol. 176(C), pages 98-110.
    3. Aria, Massimo & Cuccurullo, Corrado, 2017. "bibliometrix: An R-tool for comprehensive science mapping analysis," Journal of Informetrics, Elsevier, vol. 11(4), pages 959-975.
    4. Gustavo Cattelan Nobre & Elaine Tavares, 2017. "Scientific literature analysis on big data and internet of things applications on circular economy: a bibliometric study," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 463-492, April.
    5. Sara Saberi & Mahtab Kouhizadeh & Joseph Sarkis & Lejia Shen, 2019. "Blockchain technology and its relationships to sustainable supply chain management," International Journal of Production Research, Taylor & Francis Journals, vol. 57(7), pages 2117-2135, April.
    6. Guilherme F. Frederico, 2021. "Project Management for Supply Chains 4.0: A conceptual framework proposal based on PMBOK methodology," Operations Management Research, Springer, vol. 14(3), pages 434-450, December.
    7. Zheng, Ting & Ardolino, Marco & Bacchetti, Andrea & Perona, Marco, 2021. "The applications of Industry 4.0 technologies in manufacturing context: a systematic literature review," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 129469, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    8. Kirchherr, Julian & Piscicelli, Laura & Bour, Ruben & Kostense-Smit, Erica & Muller, Jennifer & Huibrechtse-Truijens, Anne & Hekkert, Marko, 2018. "Barriers to the Circular Economy: Evidence From the European Union (EU)," Ecological Economics, Elsevier, vol. 150(C), pages 264-272.
    9. Felipe Cerdas & Max Juraschek & Sebastian Thiede & Christoph Herrmann, 2017. "Life Cycle Assessment of 3D Printed Products in a Distributed Manufacturing System," Journal of Industrial Ecology, Yale University, vol. 21(S1), pages 80-93, November.
    10. Adriana Acevedo Tirado & Mariana Ruiz Morales & Odette Lobato-Calleros, 2015. "Additional Indicators to Promote Social Sustainability within Government Programs: Equity and Efficiency," Sustainability, MDPI, vol. 7(7), pages 1-17, July.
    11. Ting Zheng & Marco Ardolino & Andrea Bacchetti & Marco Perona, 2021. "The applications of Industry 4.0 technologies in manufacturing context: a systematic literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 59(6), pages 1922-1954, March.
    12. Roberto Moro Visconti & Donato Morea, 2019. "Big Data for the Sustainability of Healthcare Project Financing," Sustainability, MDPI, vol. 11(13), pages 1-17, July.
    13. Wouter Boon & Bert van Wee, 2018. "Influence of 3D printing on transport: a theory and experts judgment based conceptual model," Transport Reviews, Taylor & Francis Journals, vol. 38(5), pages 556-575, September.
    14. Hietam Elhoone & Tianyang Zhang & Mohd Anwar & Salil Desai, 2020. "Cyber-based design for additive manufacturing using artificial neural networks for Industry 4.0," International Journal of Production Research, Taylor & Francis Journals, vol. 58(9), pages 2841-2861, May.
    15. Henry Small, 1973. "Co‐citation in the scientific literature: A new measure of the relationship between two documents," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 24(4), pages 265-269, July.
    16. Kirchherr, Julian & Reike, Denise & Hekkert, Marko, 2017. "Conceptualizing the circular economy: An analysis of 114 definitions," Resources, Conservation & Recycling, Elsevier, vol. 127(C), pages 221-232.
    17. Dalenogare, Lucas Santos & Benitez, Guilherme Brittes & Ayala, Néstor Fabián & Frank, Alejandro Germán, 2018. "The expected contribution of Industry 4.0 technologies for industrial performance," International Journal of Production Economics, Elsevier, vol. 204(C), pages 383-394.
    18. 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).
    19. Philipp Sauer & Stefan Seuring, 2017. "Sustainable supply chain management for minerals," Post-Print hal-03891233, HAL.
    20. Yigit Kazancoglu & Esra Ekinci & Sachin Kumar Mangla & Muruvvet Deniz Sezer & Yasanur Kayikci, 2021. "Performance evaluation of reverse logistics in food supply chains in a circular economy using system dynamics," Business Strategy and the Environment, Wiley Blackwell, vol. 30(1), pages 71-91, January.
    21. Hazen, Benjamin T. & Boone, Christopher A. & Ezell, Jeremy D. & Jones-Farmer, L. Allison, 2014. "Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications," International Journal of Production Economics, Elsevier, vol. 154(C), pages 72-80.
    22. Zhisong Chen & Shong-Iee Ivan Su, 2017. "Dual Competing Photovoltaic Supply Chains: A Social Welfare Maximization Perspective," IJERPH, MDPI, vol. 14(11), pages 1-22, November.
    23. Gonçalo Cardeal & Kristina Höse & Inês Ribeiro & Uwe Götze, 2020. "Sustainable Business Models–Canvas for Sustainability, Evaluation Method, and Their Application to Additive Manufacturing in Aircraft Maintenance," Sustainability, MDPI, vol. 12(21), pages 1-22, November.
    24. Gunasekaran, Angappa & Papadopoulos, Thanos & Dubey, Rameshwar & Wamba, Samuel Fosso & Childe, Stephen J. & Hazen, Benjamin & Akter, Shahriar, 2017. "Big data and predictive analytics for supply chain and organizational performance," Journal of Business Research, Elsevier, vol. 70(C), pages 308-317.
    25. Okechukwu Okorie & Konstantinos Salonitis & Fiona Charnley & Mariale Moreno & Christopher Turner & Ashutosh Tiwari, 2018. "Digitisation and the Circular Economy: A Review of Current Research and Future Trends," Energies, MDPI, vol. 11(11), pages 1-31, November.
    26. Anthony Halog & Yosef Manik, 2011. "Advancing Integrated Systems Modelling Framework for Life Cycle Sustainability Assessment," Sustainability, MDPI, vol. 3(2), pages 1-31, February.
    27. Gebler, Malte & Schoot Uiterkamp, Anton J.M. & Visser, Cindy, 2014. "A global sustainability perspective on 3D printing technologies," Energy Policy, Elsevier, vol. 74(C), pages 158-167.
    28. Fosso Wamba, Samuel & Akter, Shahriar & Edwards, Andrew & Chopin, Geoffrey & Gnanzou, Denis, 2015. "How ‘big data’ can make big impact: Findings from a systematic review and a longitudinal case study," International Journal of Production Economics, Elsevier, vol. 165(C), pages 234-246.
    29. Jabbour, Charbel Jose Chiappetta & Jabbour, Ana Beatriz Lopes de Sousa & Sarkis, Joseph & Filho, Moacir Godinho, 2019. "Unlocking the circular economy through new business models based on large-scale data: An integrative framework and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 546-552.
    30. Rajput, Shubhangini & Singh, Surya Prakash, 2019. "Connecting circular economy and industry 4.0," International Journal of Information Management, Elsevier, vol. 49(C), pages 98-113.
    31. David Roubaud & Rameshwar Dubey & Cyril Foropon & Angappa Gunasekaran & Stephen J. Childe & Zongwei Luo & Fosso Wamba Samuel, 2018. "Examining the role of big data and predictive analytics on collaborative performance in context to sustainable consumption and production behaviour," Post-Print hal-02051276, HAL.
    32. Deqing Ma & Jinsong Hu, 2020. "Research on Collaborative Management Strategies of Closed-Loop Supply Chain under the Influence of Big-Data Marketing and Reference Price Effect," Sustainability, MDPI, vol. 12(4), pages 1-23, February.
    33. Cobo, M.J. & López-Herrera, A.G. & Herrera-Viedma, E. & Herrera, F., 2011. "An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field," Journal of Informetrics, Elsevier, vol. 5(1), pages 146-166.
    34. Kamble, Sachin S. & Gunasekaran, Angappa & Gawankar, Shradha A., 2020. "Achieving sustainable performance in a data-driven agriculture supply chain: A review for research and applications," International Journal of Production Economics, Elsevier, vol. 219(C), pages 179-194.
    35. Fahimnia, Behnam & Sarkis, Joseph & Davarzani, Hoda, 2015. "Green supply chain management: A review and bibliometric analysis," International Journal of Production Economics, Elsevier, vol. 162(C), pages 101-114.
    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. Truant, Elisa & Giordino, Daniele & Borlatto, Edoardo & Bhatia, Meena, 2024. "Drivers and barriers of smart technologies for circular economy: Leveraging smart circular economy implementation to nurture companies' performance," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    2. Özköse, Hakan & Güney, Gül, 2023. "The effects of industry 4.0 on productivity: A scientific mapping study," Technology in Society, Elsevier, vol. 75(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. Acciarini, Chiara & Cappa, Francesco & Boccardelli, Paolo & Oriani, Raffaele, 2023. "How can organizations leverage big data to innovate their business models? A systematic literature review," Technovation, Elsevier, vol. 123(C).
    2. 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.
    3. Centobelli, Piera & Cerchione, Roberto & Esposito, Emilio & Oropallo, Eugenio, 2021. "Surfing blockchain wave, or drowning? Shaping the future of distributed ledgers and decentralized technologies," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    4. Mohammadreza Akbari & John L. Hopkins, 2022. "Digital technologies as enablers of supply chain sustainability in an emerging economy," Operations Management Research, Springer, vol. 15(3), pages 689-710, December.
    5. Usama Awan & Robert Sroufe & Muhammad Shahbaz, 2021. "Industry 4.0 and the circular economy: A literature review and recommendations for future research," Business Strategy and the Environment, Wiley Blackwell, vol. 30(4), pages 2038-2060, May.
    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. 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, June.
    8. Pournader, Mehrdokht & Ghaderi, Hadi & Hassanzadegan, Amir & Fahimnia, Behnam, 2021. "Artificial intelligence applications in supply chain management," International Journal of Production Economics, Elsevier, vol. 241(C).
    9. Kristoffersen, Eivind & Mikalef, Patrick & Blomsma, Fenna & Li, Jingyue, 2021. "The effects of business analytics capability on circular economy implementation, resource orchestration capability, and firm performance," International Journal of Production Economics, Elsevier, vol. 239(C).
    10. Deepa Mishra & Angappa Gunasekaran & Thanos Papadopoulos & Stephen J. Childe, 2018. "Big Data and supply chain management: a review and bibliometric analysis," Annals of Operations Research, Springer, vol. 270(1), pages 313-336, November.
    11. Benzidia, Smail & Makaoui, Naouel & Bentahar, Omar, 2021. "The impact of big data analytics and artificial intelligence on green supply chain process integration and hospital environmental performance," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    12. Magdalena Rusch & Josef‐Peter Schöggl & Rupert J. Baumgartner, 2023. "Application of digital technologies for sustainable product management in a circular economy: A review," Business Strategy and the Environment, Wiley Blackwell, vol. 32(3), pages 1159-1174, March.
    13. 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).
    14. Sundarakani, Balan & Ajaykumar, Aneesh & Gunasekaran, Angappa, 2021. "Big data driven supply chain design and applications for blockchain: An action research using case study approach," Omega, Elsevier, vol. 102(C).
    15. 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.
    16. Sandip Solanki & Seema Singh & Meeta Joshi, 2023. "A Bibliometric Analysis of the International Journal of Energy Economics and Policy: 2013-2022," International Journal of Energy Economics and Policy, Econjournals, vol. 13(5), pages 260-270, September.
    17. S. Vijayakumar Bharathi, 2017. "Prioritizing and Ranking the Big Data Information Security Risk Spectrum," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 18(3), pages 183-201, September.
    18. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Papadopoulos, Thanos & Luo, Zongwei & Wamba, Samuel Fosso & Roubaud, David, 2019. "Can big data and predictive analytics improve social and environmental sustainability?," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 534-545.
    19. Arijit Bhattacharya & Shefali Srivastava & Abhijit Majumdar, 2024. "Circular supply chains in manufacturing—Quo vadis? Accomplishments, challenges and future opportunities," Business Strategy and the Environment, Wiley Blackwell, vol. 33(5), pages 4397-4423, July.
    20. Büşra Ayan & Elif Güner & Semen Son-Turan, 2022. "Blockchain Technology and Sustainability in Supply Chains and a Closer Look at Different Industries: A Mixed Method Approach," Logistics, MDPI, vol. 6(4), pages 1-39, December.

    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:opmare:v:15:y:2022:i:3:d:10.1007_s12063-022-00275-7. 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.