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A machine learning based approach for predicting blockchain adoption in supply chain

Author

Listed:
  • Sachin Kamble
  • Angappa Gunasekaran
  • Vikas Kumar
  • Amine Belhadi
  • Cyril Foropon

    (Groupe Sup de Co Montpellier (GSCM) - Montpellier Business School)

Abstract

No abstract is available for this item.

Suggested Citation

  • Sachin Kamble & Angappa Gunasekaran & Vikas Kumar & Amine Belhadi & Cyril Foropon, 2021. "A machine learning based approach for predicting blockchain adoption in supply chain," Post-Print hal-03539287, HAL.
    • Handle: RePEc:hal:journl:hal-03539287
    as

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    Citations

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    Cited by:

    1. Pardis Roozkhosh & Alireza Pooya & Renu Agarwal, 2023. "Blockchain acceptance rate prediction in the resilient supply chain with hybrid system dynamics and machine learning approach," Operations Management Research, Springer, vol. 16(2), pages 705-725, June.
    2. Rakshit, Sandip & Islam, Nazrul & Mondal, Sandeep & Paul, Tripti, 2022. "Influence of blockchain technology in SME internationalization: Evidence from high-tech SMEs in India," Technovation, Elsevier, vol. 115(C).
    3. Jana, Rabin K. & Ghosh, Indranil & Wallin, Martin W., 2022. "Taming energy and electronic waste generation in bitcoin mining: Insights from Facebook prophet and deep neural network," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    4. Shahbaz Khan & Abid Haleem & Zafar Husain & Daniel Samson & R. D. Pathak, 2023. "Barriers to blockchain technology adoption in supply chains: the case of India," Operations Management Research, Springer, vol. 16(2), pages 668-683, June.
    5. Dehghani, Milad & William Kennedy, Ryan & Mashatan, Atefeh & Rese, Alexandra & Karavidas, Dionysios, 2022. "High interest, low adoption. A mixed-method investigation into the factors influencing organisational adoption of blockchain technology," Journal of Business Research, Elsevier, vol. 149(C), pages 393-411.
    6. Gupta, Somya & Ghardallou, Wafa & Pandey, Dharen Kumar & Sahu, Ganesh P., 2022. "Artificial intelligence adoption in the insurance industry: Evidence using the technology–organization–environment framework," Research in International Business and Finance, Elsevier, vol. 63(C).
    7. Ulpan Tokkozhina & Ana Lucia Martins & Joao C. Ferreira, 2023. "Uncovering dimensions of the impact of blockchain technology in supply chain management," Operations Management Research, Springer, vol. 16(1), pages 99-125, March.
    8. Kraus, Sascha & Kumar, Satish & Lim, Weng Marc & Kaur, Jaspreet & Sharma, Anuj & Schiavone, Francesco, 2023. "From moon landing to metaverse: Tracing the evolution of Technological Forecasting and Social Change," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    9. Sharma, Prateek & Shukla, Dhirendra Mani & Raj, Alok, 2023. "Blockchain adoption and firm performance: The contingent roles of intangible capital and environmental dynamism," International Journal of Production Economics, Elsevier, vol. 256(C).
    10. Dwivedi, Yogesh K. & Balakrishnan, Janarthanan & Das, Ronnie & Dutot, Vincent, 2023. "Resistance to innovation: A dynamic capability model based enquiry into retailers’ resistance to blockchain adaptation," Journal of Business Research, Elsevier, vol. 157(C).
    11. Lili Geng & Huixian Hui & Xiaomeng Liang & Shaocong Yan & Yongji Xue, 2023. "Factors Affecting Intention Toward ICT Adoption in Rural Entrepreneurship: Understanding the Differences Between Business Types of Organizations and Previous Experience of Entrepreneurs," SAGE Open, , vol. 13(3), pages 21582440231, September.
    12. Sahebi, Iman Ghasemian & Mosayebi, Alireza & Masoomi, Behzad & Marandi, Fatemeh, 2022. "Modeling the enablers for blockchain technology adoption in renewable energy supply chain," Technology in Society, Elsevier, vol. 68(C).
    13. Zhang, Xi & Cheng, Yihang & Chen, Aoshuang & Lytras, Miltiadis & de Pablos, Patricia Ordóñez & Zhang, Renyu, 2022. "How rumors diffuse in the infodemic: Evidence from the healthy online social change in China," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    14. Ihab K. A. Hamdan & Wulamu Aziguli & Dezheng Zhang & Eli Sumarliah, 2023. "Machine learning in supply chain: prediction of real-time e-order arrivals using ANFIS," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 549-568, March.
    15. Ieva Meidute-Kavaliauskiene & Amir Karbassi Yazdi & Amir Mehdiabadi, 2022. "Integration of Blockchain Technology and Prioritization of Deployment Barriers in the Blood Supply Chain," Logistics, MDPI, vol. 6(1), pages 1-16, March.
    16. Zhang, Mingming & Zhou, Simei & Wang, Qunwei & Liu, Liyun & Zhou, Dequn, 2023. "Will the carbon neutrality target impact China's energy security? A dynamic Bayesian network model," Energy Economics, Elsevier, vol. 125(C).

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