IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v195y2023ics0040162523004791.html
   My bibliography  Save this article

Digital twins and blockchain technology in the industrial Internet of Things (IIoT) using an extended decision support system model: Industry 4.0 barriers perspective

Author

Listed:
  • Li, Yi
  • Su, Da An
  • Mardani, Abbas

Abstract

Blockchain technology (BT) can be considered a great help to the concept of digital twins (DT) as it can make sure of transparency, the immutability of data, decentralization of data storage, and peer-to-peer communication in industrial sectors. DT refers to the integrated multiphysics, multiscale, and probabilistic representation of a real-world physical component. The current study attempts to well envisage the ways blockchain can restructure and transform DTs to provide secure manufacturing, assuring compliance, traceability, quality, authenticity, and safety. However, to the adoption of DTs and BT in the industrial Internet of Things (IIoT), there are several barriers. To identify the key barriers, the present study discusses a survey approach through comprehensive literature and interviews with experts. To do so, this study introduced a novel approach using decision-making theory under the q-rung orthopair fuzzy set (q-ROFS) to analyze the identified barriers. This study developed a new methodology called q-ROF-subjective and objective weight integrated approach (SOWIA)-weighted aggregated sum product assessment (WASPAS). An empirical case study to assess the barriers to employing BT into DTs for IIoT implementation in the era of Industry 4.0 is taken. Also, comparative work and sensitivity analysis are discussed to demonstrate the advantage of the presented approach.

Suggested Citation

  • Li, Yi & Su, Da An & Mardani, Abbas, 2023. "Digital twins and blockchain technology in the industrial Internet of Things (IIoT) using an extended decision support system model: Industry 4.0 barriers perspective," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    • Handle: RePEc:eee:tefoso:v:195:y:2023:i:c:s0040162523004791
    DOI: 10.1016/j.techfore.2023.122794
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162523004791
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2023.122794?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. Leng, Jiewu & Ruan, Guolei & Jiang, Pingyu & Xu, Kailin & Liu, Qiang & Zhou, Xueliang & Liu, Chao, 2020. "Blockchain-empowered sustainable manufacturing and product lifecycle management in industry 4.0: A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    2. Marietheres Dietz & Günther Pernul, 2020. "Digital Twin: Empowering Enterprises Towards a System-of-Systems Approach," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 62(2), pages 179-184, April.
    3. Mousavi, M. & Gitinavard, H. & Mousavi, S.M., 2017. "A soft computing based-modified ELECTRE model for renewable energy policy selection with unknown information," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 774-787.
    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. Sung, Kiseo & Park, Kyu-Tae & Lee, Hakyeon, 2024. "Landscaping the digital twin technology: Patent-based networks and technology reference model," Technological Forecasting and Social Change, Elsevier, vol. 206(C).
    2. Wang, Weizhong & Chen, Yu & Wang, Yi & Deveci, Muhammet & Cheng, Shuping & Brito-Parada, Pablo R., 2024. "A decision support framework for humanitarian supply chain management – Analysing enablers of AI-HI integration using a complex spherical fuzzy DEMATEL-MARCOS method," Technological Forecasting and Social Change, Elsevier, vol. 206(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. Naseri, F. & Gil, S. & Barbu, C. & Cetkin, E. & Yarimca, G. & Jensen, A.C. & Larsen, P.G. & Gomes, C., 2023. "Digital twin of electric vehicle battery systems: Comprehensive review of the use cases, requirements, and platforms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 179(C).
    2. Johannes Sedlmeir & Reilly Smethurst & Alexander Rieger & Gilbert Fridgen, 2021. "Digital Identities and Verifiable Credentials," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(5), pages 603-613, October.
    3. Ezbakhe, Fatine & Pérez-Foguet, Agustí, 2021. "Decision analysis for sustainable development: The case of renewable energy planning under uncertainty," European Journal of Operational Research, Elsevier, vol. 291(2), pages 601-613.
    4. Noori, Amir & Bonakdari, Hossein & Salimi, Amir Hossein & Gharabaghi, Bahram, 2021. "A group Multi-Criteria Decision-Making method for water supply choice optimization," Socio-Economic Planning Sciences, Elsevier, vol. 77(C).
    5. Ibrahim Yitmen & Amjad Almusaed & Sepehr Alizadehsalehi, 2023. "Investigating the Causal Relationships among Enablers of the Construction 5.0 Paradigm: Integration of Operator 5.0 and Society 5.0 with Human-Centricity, Sustainability, and Resilience," Sustainability, MDPI, vol. 15(11), pages 1-25, June.
    6. Li, Tao & Li, Ang & Guo, Xiaopeng, 2020. "The sustainable development-oriented development and utilization of renewable energy industry——A comprehensive analysis of MCDM methods," Energy, Elsevier, vol. 212(C).
    7. Rivero-Iglesias, Jose M. & Puente, Javier & Fernandez, Isabel & León, Omar, 2023. "Integrated model for the assessment of power generation alternatives through analytic hierarchy process and a fuzzy inference system. Case study of Spain," Renewable Energy, Elsevier, vol. 211(C), pages 563-581.
    8. Ahmad A. A. Khanfar & Mohammad Iranmanesh & Morteza Ghobakhloo & Madugoda Gunaratnege Senali & Masood Fathi, 2021. "Applications of Blockchain Technology in Sustainable Manufacturing and Supply Chain Management: A Systematic Review," Sustainability, MDPI, vol. 13(14), pages 1-20, July.
    9. Hassan Hashemi & Seyed Meysam Mousavi & Edmundas Kazimieras Zavadskas & Alireza Chalekaee & Zenonas Turskis, 2018. "A New Group Decision Model Based on Grey-Intuitionistic Fuzzy-ELECTRE and VIKOR for Contractor Assessment Problem," Sustainability, MDPI, vol. 10(5), pages 1-19, May.
    10. Arunodaya Raj Mishra & Pratibha Rani & Raghunathan Krishankumar & Edmundas Kazimieras Zavadskas & Fausto Cavallaro & Kattur S. Ravichandran, 2021. "A Hesitant Fuzzy Combined Compromise Solution Framework-Based on Discrimination Measure for Ranking Sustainable Third-Party Reverse Logistic Providers," Sustainability, MDPI, vol. 13(4), pages 1-24, February.
    11. Abdul Karim Feroz & Hangjung Zo & Ananth Chiravuri, 2021. "Digital Transformation and Environmental Sustainability: A Review and Research Agenda," Sustainability, MDPI, vol. 13(3), pages 1-20, February.
    12. Guillermo Fuertes & Jorge Zamorano & Miguel Alfaro & Manuel Vargas & Jorge Sabattin & Claudia Duran & Rodrigo Ternero & Ricardo Rivera, 2022. "Opportunities of the Technological Trends Linked to Industry 4.0 for Achieve Sustainable Manufacturing Objectives," Sustainability, MDPI, vol. 14(18), pages 1-36, September.
    13. Zerfaß, Ansgar & Stieglitz, Stefan & Clausen, Sünje & Ziegele, Daniel & Berger, Karen, 2023. "Communications Trend Radar 2023. State revival, scarcity management, unimagination, augmented workflows & parallel worlds," Communication Insights 17, Academic Society for Management & Communication – An initiative of the Günter Thiele Foundation, Leipzig.
    14. Mihai Andronie & George Lăzăroiu & Mariana Iatagan & Iulian Hurloiu & Irina Dijmărescu, 2021. "Sustainable Cyber-Physical Production Systems in Big Data-Driven Smart Urban Economy: A Systematic Literature Review," Sustainability, MDPI, vol. 13(2), pages 1-15, January.
    15. Renato Camodeca & Alex Almici, 2021. "Digital Transformation and Convergence toward the 2030 Agenda’s Sustainability Development Goals: Evidence from Italian Listed Firms," Sustainability, MDPI, vol. 13(21), pages 1-18, October.
    16. Isazadeh, Amin & Ziviani, Davide & Claridge, David E., 2023. "Global trends, performance metrics, and energy reduction measures in datacom facilities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 174(C).
    17. Issam A. R. Moghrabi & Sameer Ahmad Bhat & Piotr Szczuko & Rawan A. AlKhaled & Muneer Ahmad Dar, 2023. "Digital Transformation and Its Influence on Sustainable Manufacturing and Business Practices," Sustainability, MDPI, vol. 15(4), pages 1-35, February.
    18. Ali, Fahad & Khurram, Muhammad Usman & Sensoy, Ahmet & Vo, Xuan Vinh, 2024. "Green cryptocurrencies and portfolio diversification in the era of greener paths," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    19. Eirini Stavropoulou & Konstantinos Spinthiropoulos & Konstantina Ragazou & Christos Papademetriou & Ioannis Passas, 2023. "Green Balanced Scorecard: A Tool of Sustainable Information Systems for an Energy Efficient Business," Energies, MDPI, vol. 16(18), pages 1-18, September.
    20. Thomas Kitsantas, 2022. "Exploring Blockchain Technology and Enterprise Resource Planning System: Business and Technical Aspects, Current Problems, and Future Perspectives," Sustainability, MDPI, vol. 14(13), pages 1-17, 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:eee:tefoso:v:195:y:2023:i:c:s0040162523004791. 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: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    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.