IDEAS home Printed from https://ideas.repec.org/p/ags/haaepa/337119.html
   My bibliography  Save this paper

A Methodology to Investigate Challenges for Digital Twin Technology in Smart Agriculture

Author

Listed:
  • Büyüközkan, Gülçin
  • Uztürk, Deniz

Abstract

The agriculture sector is fundamental for social, economic, and environmental development. It needs novel approaches and technology-integrated processes to preserve its critical importance and survive for the future. Agricultural digitalization is an essential component of agricultural industrialization, focusing on agricultural research, infrastructural improvements, and data services. The combination of the Internet of Things/Everything (IoT/IoE) with RFID, sensors, and high-tech meters makes up smart agriculture (SA). Controlling and monitoring have become more easily applicable thanks to these technological improvements. SA replaces conventional farming methods with effective, rapid, and sustainable ones. It has the power to control water, pesticides, security, the environment, machines, and vehicles. Digital Twin (DT) technology is the mutual use of digital technologies such as remote sensing, IoT, and simulation. With its integrated structure, DT can help farmers to create a virtual twin of their physical entities in the virtual space. Accordingly, generating strategies and planning the production can be controlled by running simulations with the field's collected data. Therefore, this paper aims to investigate challenges to DT adoption in SA. For that purpose, a multicriteria decision-making (MCDM) approach is suggested. DEMATEL technique is provided to prioritize and evaluate causal relationships for DT adoption challenges. The DEMATEL technique is integrated with the 2-Tuple Linguistic (2-TL) model to improve its ability to deal with linguistic variables and create a decision-making process closer to human cognitive processes. A real case study is provided to test the applicability of the suggested methodology, and further discussions are presented.

Suggested Citation

  • Büyüközkan, Gülçin & Uztürk, Deniz, 2022. "A Methodology to Investigate Challenges for Digital Twin Technology in Smart Agriculture," Agri-Tech Economics Papers 337119, Harper Adams University, Land, Farm & Agribusiness Management Department.
    • Handle: RePEc:ags:haaepa:337119
    DOI: 10.22004/ag.econ.337119
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/337119/files/A%20methodology%20to%20investigate%20challenges%20for%20digital%20twin%20technology%20in%20smart%20agriculture.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.337119?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
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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).
    3. Verdouw, Cor & Tekinerdogan, Bedir & Beulens, Adrie & Wolfert, Sjaak, 2021. "Digital twins in smart farming," Agricultural Systems, Elsevier, vol. 189(C).
    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. Büyüközkan, Gülçin & Uztürk, Deniz, 2022. "A Methodology to Investigate Challenges for Digital Twin Technology in Smart Agriculture," Land, Farm & Agribusiness Management Department 337119, Harper Adams University, Land, Farm & Agribusiness Management Department.
    2. Asif, Muhammad & Searcy, Cory & Castka, Pavel, 2023. "ESG and Industry 5.0: The role of technologies in enhancing ESG disclosure," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    3. Lai, Kee-hung & Feng, Yunting & Zhu, Qinghua, 2023. "Digital transformation for green supply chain innovation in manufacturing operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    4. 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.
    5. Zhao, Nanyang & Hong, Jiangtao & Lau, Kwok Hung, 2023. "Impact of supply chain digitalization on supply chain resilience and performance: A multi-mediation model," International Journal of Production Economics, Elsevier, vol. 259(C).
    6. Iftikhar, Ilaria Giannoccaro & Anas, 2023. "Mitigating ripple effect in supply networks: the effect of trust and topology on resilience," OSF Preprints 2spt3, Center for Open Science.
    7. Piccarozzi, Michela & Silvestri, Luca & Silvestri, Cecilia & Ruggieri, Alessandro, 2024. "Roadmap to Industry 5.0: Enabling technologies, challenges, and opportunities towards a holistic definition in management studies," Technological Forecasting and Social Change, Elsevier, vol. 205(C).
    8. Davies, Jennifer & Sharifi, Hossein & Lyons, Andrew & Forster, Rick & Elsayed, Omar Khaled Shokry Mohamed, 2024. "Non-fungible tokens: The missing ingredient for sustainable supply chains in the metaverse age?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 182(C).
    9. Niu, Baozhuang & Ruan, Yiyuan & Yu, Xinhu, 2024. "Purchasing new for remanufacturing: Sourcing co-opetition, tax-planning and data validation," International Journal of Production Economics, Elsevier, vol. 273(C).
    10. Ghannouchi, Imen, 2023. "Examining the dynamic nexus between industry 4.0 technologies and sustainable economy: New insights from empirical evidence using GMM estimator across 20 OECD nations," Technology in Society, Elsevier, vol. 75(C).
    11. Patrick Brandtner & Farzaneh Darbanian & Taha Falatouri & Chibuzor Udokwu, 2021. "Impact of COVID-19 on the Customer End of Retail Supply Chains: A Big Data Analysis of Consumer Satisfaction," Sustainability, MDPI, vol. 13(3), pages 1-18, January.
    12. Duan, Yunlong & Mu, Chang & Yang, Meng & Deng, Zhiqing & Chin, Tachia & Zhou, Li & Fang, Qifeng, 2021. "Study on early warnings of strategic risk during the process of firms’ sustainable innovation based on an optimized genetic BP neural networks model: Evidence from Chinese manufacturing firms," International Journal of Production Economics, Elsevier, vol. 242(C).
    13. Essam Kaoud & Mohammad A. M. Abdel-Aal & Tatsuhiko Sakaguchi & Naoki Uchiyama, 2020. "Design and Optimization of the Dual-Channel Closed Loop Supply Chain with E-Commerce," Sustainability, MDPI, vol. 12(23), pages 1-21, December.
    14. Bai, Chunguang & Sarkis, Joseph, 2022. "A critical review of formal analytical modeling for blockchain technology in production, operations, and supply chains: Harnessing progress for future potential," International Journal of Production Economics, Elsevier, vol. 250(C).
    15. Yi Zheng & Li Liu & Victor Shi & Wenxing Huang & Jianxiu Liao, 2022. "A Resilience Analysis of a Medical Mask Supply Chain during the COVID-19 Pandemic: A Simulation Modeling Approach," IJERPH, MDPI, vol. 19(13), pages 1-21, June.
    16. Shuyao Li & Wenfu Wu & Yujia Wang & Na Zhang & Fanhui Sun & Feng Jiang & Xiaoshuai Wei, 2023. "Production Data Management of Smart Farming Based on Shili Theory," Agriculture, MDPI, vol. 13(4), pages 1-26, March.
    17. Uztürk, Deniz & Büyüközkan, Gülçin, 2022. "Smart Agriculture Technology Evaluation: A Linguistic-based MCDM Methodology," Agri-Tech Economics Papers 337128, Harper Adams University, Land, Farm & Agribusiness Management Department.
    18. Uztürk, Deniz & Büyüközkan, Gülçin, 2022. "Smart Agriculture Technology Evaluation: A Linguistic-based MCDM Methodology," Land, Farm & Agribusiness Management Department 337128, Harper Adams University, Land, Farm & Agribusiness Management Department.
    19. Xuehao Bi & Bo Wen & Wei Zou, 2022. "The Role of Internet Development in China’s Grain Production: Specific Path and Dialectical Perspective," Agriculture, MDPI, vol. 12(3), pages 1-14, March.
    20. Arranz, Carlos F.A. & Arroyabe, Marta F. & Arranz, Nieves & de Arroyabe, Juan Carlos Fernandez, 2023. "Digitalisation dynamics in SMEs: An approach from systems dynamics and artificial intelligence," Technological Forecasting and Social Change, Elsevier, vol. 196(C).

    More about this item

    Keywords

    Research and Development/Tech Change/Emerging Technologies;

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ags:haaepa:337119. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/dlhauuk.html .

    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.