Blockchain and Artificial Intelligence integration in Supply Chains: A systematic review
Subject Areas : Artificial Intelligence Tools in Software and Data Engineering
Neda Roustaei
1
*
,
Hasan Dehghan Dehnavi
2
,
Mohammad Dehghan Tezerjani
3
1 - Department of Industrial Management, Yazd Branch, Islamic Azad University, Yazd, Iran
2 - دانشیار،گروه مدیریت صنعتی، واحد یزد، دانشگاه آزاد اسلامی، یزد ، ایران.
3 - Department of Industrial Management, Yazd Branch, Islamic Azad University, Yazd, Iran
Keywords: Artificial intelligence, Blockchain, Supply Chain,
Abstract :
Artificial intelligence and blockchain are among the most popular technologies. Combine the two technologies also harbors manifold potentials. For instance, blockchain can help address specific AI-related difficulties, and vice versa, AI offers opportunities to improve the blockchain’s mining process, or smart contracts. The fusion of blockchain and artifcial intelligence (AI) marks a paradigm shift in supply chain, ensuring data privacy, and facilitating secure data transmission. This study through a systematic literature review, analyze the impact of artificial intelligence and blockchain on each other and then provides a comprehensive analysis of the integration of blockchain and artificial intelligence in supply chains and demonstrates their role in enhancing security and transparency in the field of supply chain management. In particular, supply chain is one of the areas that have been shown to benefit tremendously from blockchain and AI, by enhancing information and process resilience, enabling faster and more cost-efficient delivery of products, and augmenting products’ traceability, among others. This research aims to investigate the current studies on the integration of blockchain and AI in supply chain and our analysis of 30 English-language articles published between 2018 and 2024 identifies a number of research challenges and opportunities.
[1] K. Salah, M. H. U. Rehman, N. Nizamuddin, and A. Al-Fuqaha, “Blockchain for AI: Review and Open Research Challenges,” IEEE Access, vol. 7, pp. 10127-10149, Jan. 2019, doi: 10.1109/ACCESS.2018.2890507.
[2] D. Castelvecchi, “Can we open the black box of AI?,” Nature, News Feature, vol. 538, Issue 7623, pp. 20-23, October 2016, Available: https://www.nature.com/news/can-we-open-the-black-box-of-ai-1.20731
[3] D. Dillenberger, P. Novotny, Q. Zhang, P. Jayachandran, H. Gupta, S. Hans, D. Verma, S. Chakraborty, J. Thomas, M. Walli, R. Vaculin, and K. Sarpatwar, “Blockchain analytics and artificial intelligence,” IBM Journal of Research and Development, vol. 63:2/3, pp. 1-14, February 2019, doi: 10.1147/JRD.2019.2900638
[4] K. Sarpatwar, R. Vaculin, H. Min, G. Su, T. Heath, G. Ganapavarapu, and D. Dillenberger, “Towards Enabling Trusted Artificial Intelligence via Blockchain,” in Policy-Based Autonomic Data Governance, S. Calo, E. Bertino and D. Verma (eds.), SPRINGER NATURE, pp. 137-153, April 2019, doi: 10.1007/978-3-030-17277-0_8
[5] P. Fairley, “Blockchain world - Feeding the blockchain beast if bitcoin ever does go mainstream, the electricity needed to sustain it will be enormous,” IEEE Spectrum, vol. 54, no. 10, pp. 36-59. October 2017, doi: 10.1109/MSPEC.2017.8048837
[6] H. J. Singh, and A. S. Hafid, “Prediction of Transaction Confirmation Time in Ethereum Blockchain Using Machine Learning,” in Blockchain and applications: International congress, J. Prieto, A. K. Das, S. Ferretti, A. Pinto and J. M. Corchado (eds.), Cham, Switzerland: Springer, 2020, pp. 126-133.
[7] J. Chen, K. Duan, R. Zhang, L. Zeng, and W. Wang, “An AI Based Super Nodes Selection Algorithm in BlockChain Networks,” August 2018, doi: 10.48550/arXiv.1808.00216
[8] G. Zyskind, O. Nathan, and A. S. Pentland, “Decentralizing Privacy: Using Blockchain to Protect Personal Data,” in 2015 IEEE Security and Privacy Workshops (SPW), San Jose, CA, USA. 21. - 22. May 2015, Piscataway, NJ: IEEE, pp. 180-184, doi: 10.1109/SPW.2015.27
[9] S. Haber, and W.S. Stornetta, “How to Time-stamp A Digital Document,” In Advances in Cryptology-CRYPTO, vol. 3, pp. 99-111, 1991, Corpus ID: 14363020, doi: 10.1007/BF00196791
[10] L.P. Perera, and K. Czachorowski, “Decentralized System Intelligence in Data Driven Networks for Shipping Industrial Applications: Digital Models to Blockchain Technologies,” Proceedings of the MTS/IEEE OCEANS 19, At: Marseille , France, vol. 2019, June 2019, doi: 10.1109/OCEANSE.2019.8867045
[11] W. Diffie, and M. Hellman, M. “New directions in cryptography,” IEEE Transactions on Information Theory, vol. 22 issue 6, pp. 644-654, November 1976. doi: 10.1109/TIT.1976.1055638
[12] B. Preneel, “The First 30 Years of Cryptographic Hash Functions and the NIST SHA-3 Competition,” in Topics in cryptology: The Cryptographers' Track at the RSA Conference 2010, San Francisco, CA, USA, March 2010, Proceedings, J. Pieprzyk (ed.), Berlin: Springer, pp. 1-14.
[13] S. Nakamoto, “Bitcoin: A Peer-to-Peer Electronic Cash System,” 2009, https://bitcoin.org/bitcoin.pdf. Accessed 24 October 2019.
[14] M. Iansiti, and K. R. Lakhani, “The truth about blockchain,” Harvard Business Review, vol. 95, no. 1, pp. 118-127, January 2017, https://www.researchgate.net/publication/341913793
[15] M. J. Casey, and P. Wong, “Global Supply Chains Are About to Get Better, Thanks to Blockchain,” March 2017, https://hbr.org/2017/03/global-supply-chains-are-about-to-get-better-thanks-to-blockchain. Accessed 30 September 2019.
[16] N. Abbatemarco, L. M. de. Rossi, and G. Salviotti, “An econometric model to estimate the value of a cryptocurrency network. The Bitcoin case,” Research Papers 164, 2018.
[17] D. Tapscott, and A. Tapscott, “The Impact of the Blockchain Goes Beyond Financial Services,” May 2016, https://hbr.org/2016/05/the-impact-of-the-blockchain-goes-beyond-financial-services. Accessed 26 October 2019.
[18] J. Chen, S. Xu, K. Liu, S. Yao, X. Luo, H. Wu, “Intelligent transportation logistics optimal warehouse location method based on internet of things and blockchain technology,” Sensors, vol. 22 (4):L 1544, February 2022, doi: 10.3390/s22041544
[19] M. Hrouga, A. Sbihi, M. Chavallard, “The potentials of combining blockchain technology and internet of things for digital reverse supply chain: a case study,” Journal of Cleaner Production, vol. 337, no. 20, 130609, February 2022, doi: 10.1016/j.jclepro.2022.130609
[20] S. J. Russell, and P. Norvig, P. “Artificial intelligence: A modern approach,” (Third Edition), Pearson, 2016, https://elibrary.pearson.de/book/99.150005/9781292401171
[21] J. Bughin, M. Chui, R. Joshi, J. Manyika, and J. Seong, “Notes from the AI Frontier – Modeling the Impact of AI on the World Economy,” McKinsey Global Institute, Discussion Paper, September 2018.
[22] R. Wang, M. Luo, Y. Wen, L. Wang, K-K. Raymond Choo, D. He, “The Applications of Blockchain in Artificial Intelligence,” Security and Communication Networks, vol. 2, pp. 1-16, September 2021, doi: 10.1155/2021/6126247
[23] Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature, vol. 521, pp. 436-444, May 2015, doi: 10.1038/nature14539
[24] G. E. Hinton, S. Osindero, Y. W. The, “A fast learning algorithm for deep belief nets,” Neural Comput, vol. 18, no. 7, pp. 1527–54, July 2006, doi: 10.1162/neco.2006.18.7.1527
[25] I. H. Sarker, “Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Research Directions,” SN Computer Science, vol. 2, no. 6:420, August 2021, doi: https://doi.org/10.1007/s42979-021-00815-1.
[26] J. Karhunen, T. Raiko, K. Cho, “Unsupervised deep learning: a short review,” Advances in independent component analysis and learning machines, pp. 125–142, Jan. 2015, doi: 10.1016/B978-0-12-802806-3.00007-5
[27] Y. Xin, L. Kong, Z. Liu, Y. Chen, Y. Li, H. Zhu, M. Gao, H. Hou, C. Wang, ‘Machine learning and deep learning methods for cybersecurity,” IEEE Access, vol. 6, pp. (99): 1-1, May 2018, doi: 10.1109/ACCESS.2018.2836950
[28] H. B. McMahan, E. Moore, D. Ramage, and B. A. y Arcas, “Federated Learning of Deep Networks Using Model Averaging,” ArXiv, vol. abs/1602.05629, February 2016, doi: 10.48550/arXiv.1602.05629
[29] D. Ivanov, A. Dolgui, & B. Sokolov, “The impact of digital technology and industry 4.0 on the ripple effect and supply chain risk analytics,” International Journal of Production Research, vol. 57, no. 3, pp. 829–846, June 2018, doi: 10.1080/00207543.2018.1488086
[30] S. Saberi, M. Kouhizadeh, J. Sarkis, & L. Shen, “Blockchain technology and its relationships to sustainable supply chain management,” International Journal of Production Research, vol. 57, Issue 7, pp. 2117–2135, 2019, doi: 10.1080/00207543.2018.1533261
[31] F. Dong, P. Zhou, Z. Liu, D. Shen, Z. Xu, & J. Luo, “Towards a fast and secure design for enterpriseoriented cloud storage systems,” Concurrency and Computation: Practice and Experience, vol. 29, Issue 19, October 2017, doi: 10.1002/cpe.4177
[32] S. A. Abeyratne, & R. P. Monfared, “Blockchain ready manufacturing supply chain using distributed ledger,” International Journal of Renewable Energy Technology, vol. 5, Issue 9, pp. 1–10, September 2016, doi: https://hdl.handle.net/2134/22625
[33] S. Seuring, J. Sarkis, M. Müller, & P. Rao, “Sustainability and supply chain management—an introduction to the special issue,” Journal of Cleaner Production, vol. 16, Issue 15, pp. 1545–1551, October 2008, doi: 0.1016/j.jclepro.2008.02.002
[34] K. Samanta, Dr. R. Sandeep. V. Sahu, M. Sundari, N. Yashan, M. P. Dande, “Blockchain and AI Integration: Transforming Transparency in Supply Chain Management,” European Economic Letters (EEL), vol. 14, no. 3, pp. 1238–1247, September 2024, doi: 10.52783/eel.v14i3.1885
[35] M. Crosby, P. Pattanayak, S. Verma, & V. Kalyanaraman, “Blockchain technology: Beyond bitcoin,” Applied Innovation, no. 2, pp. 6–19, June 2016.
[36] E. L. Odekanle, B. S. Fakinle, O. A. Falowo, & O. J. Odejobi, “Challenges and benefits of combining AI with blockchain for sustainable environment,” In K. Kaushik, A. Tayal, S. Dahiya, & A. O. Salau (Eds.), Sustainable and advanced applications of blockchain in smart computational technologies, pp. 43–62, 2022, Chapman and Hall/CRC.
[37] B. Kitchenham, and S. Charters, “Guidelines for Performing Systematic Literature Reviews in Software Engineering,” EBSE Technical Report EBSE-2007-01, July 2007, Available online: https://legacyfileshare.elsevier.com/promis_misc/525444systematicreviewsguide.pdf
[38] T. Dybå, & T. Dingsøyr, “Empirical studies of agile software development: A systematic review,” Information and Software Technology, vol. 50, Issues 9–10, pp. 833–859, August 2008, doi: 10.1016/j.infsof.2008.01.006
[39] K. Krippendorff, “Content analysis: an introduction to its methodology,” Thousand Oaks: Sage Publications, Inc., 2018, doi: https://doi.org/10.4135/9781071878781
[40] N. McDonald, S. Schoenebeck, & A. Forte, “Reliability and inter-rater reliability in qualitative research: Norms and guidelines for CSCW and HCI practice,” In Proceedings of the ACM on Human–Computer Interaction, vol. 3, no. 72, pp. 1–23, doi: 10.1145/3359174
[41] K. Panetta, “The CIO’s Guide to Blockchain,” 2019, https://www.gartner.com/smarterwithgartner/the-ciosguide-toblockchain/, Accessed 26 August 2020.
[42] K. Garimella, and P. Fingar, “AI+Blockchain: A brief guide for gamechangers,” Tampa, Florida, USA : Meghan-Kiffer Press, May 2018, https://search.library.ucdavis.edu/discovery/fulldisplay/alma9914022449906531/01UCD_INST:UCD
[43] Z. Zheng, H-N. Dai, J. Wu, “Blockchain Intelligence: When Blockchain Meets Artificial Intelligence,” Cryptography and Security (cs.CR), arXiv:1912.06485v3, April 2020, doi: 10.48550/arXiv.1912.06485
[44] A. S. Almasoud, M. M. Eljazzar, and F. Hussain, “Toward a Self-Learned Smart Contracts,” in 15th International Conference on e-Business Engineering: ICEBE 2018, Proceedings, Xi'an, China. 12-14. October 2018, Los Alamitos, California: IEEE Computer Society, Conference Publishing Services, pp. 269-273.
[45] H. Nguyen, and S. Bailey, “Use of Artificial Intelligence for Smart Contracts and Blockchains,” FinTechLaw Report: E-Banking, Payments and Commerce in the Mobile World, vol. 20, Issue 2, pp. 1-7, March/ April 2018,https://www.squirepattonboggs.com//media/files/insights/publications/2018/04/use-of-artificial-intelligence-for-smart-contracts-and blockchains/huu-bailey-fintech-law-report-article-2018.pdf
[46] T. N. Dinh, and M. T. Thai, “AI and Blockchain: A Disruptive Integration,” Computer, vol. 51, Issue , pp. 48-53, September 2018 ,doi: 10.1109/MC.2018.3620971
[47] H. Subramanian, “Decentralized blockchain-based electronic marketplaces,” Communications of the ACM, vol. 61, Issue 1, pp. 78-84, December 2017, doi: 10.1145/3158333
[48] A. Goel, A. Agarwal, M. Vatsa, R. Singh, and N. Ratha, “DeepRing: Protecting Deep Neural Network with Blockchain,” in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, CVPR Workshops, Long Beach, California, 16-20. June 2019, https://dblp.org/db/conf/cvpr/cvprw2019.html
[49] G. A. Montes, and B. Goertzel, “Distributed, decentralized, and democratized artificial intelligence,” Technological forecasting and social change, Elsevier, vol. 141 (C), pp. 354-358, April 2019, doi: 10.1016/j.techfore.2018.11.010
[50] A. G. Millard, J. Timmis, and A. F. T. Winfield, “Towards Exogenous Fault Detection in Swarm Robotic Systems,” in Towards autonomous robotic systems: 14th Annual Conference, TAROS 2013 Oxford, UK, , A. Natraj, S. Cameron, C. Melhuish and M. Witkowski (eds.), Oxford, Großbritannien, Cham: Springer, pp. 429-430, 28-30 August 2013, doi: 10.1007/978-3-662-43645-5_44
[51] J. D. Bjerknes, and A. F. T. Winfield, “On Fault Tolerance and Scalability of Swarm Robotic Systems,” in Distributed Autonomous Robotic Systems: The 10th International Symposium, A. Martinoli, F. Mondada, N. Correll, G. Mermoud, M. Egerstedt, M. A. Hsieh, L. E. Parker and K. Støy (eds.), Berlin, Heidelberg: Springer Berlin Heidelberg; Imprint; Springer, pp. 431-444, January 2013, doi: 10.1007/978-3-642-32723-0_31
[52] F. Higgins, A. Tomlinson, and K. M. Martin, “Survey on Security Challenges for Swarm Robotics,” Fifth International Conference on Autonomic and Autonomous Systems, Valencia, Spain, pp. 307-312, 20-25 April 2009, doi: 10.1109/ICAS.2009.62
[53] E. C. Ferrer, “The Blockchain: A New Framework for Robotic Swarm Systems,” in Proceedings of the Future Technologies Conference (FTC) 201,: vol. 2, K. Arai, R. Bhatia and S. Kapoor (eds.), Vancouver, BC, , pp. 1037-1058, Canada. 15 - 16 November 2018, https://doi.org/10.1007/978-3-030-02683-7_77
[54] Y. Nishida, K. Kaneko, S. Sharma, K. Sakurai, “Suppressing Chain Size of Blockchain-Based Information Sharing for Swarm Robotic Systems,” Sixth International Symposium on Computing and Networking Workshops, pp. 524-528, November 2018, doi: 10.1109/CANDARW.2018.00102
[55] F. Corea, “Applied Artificial Intelligence: Where AI Can Be Used In Business,” Springer, January 2019, doi: 10.1007/978-3-319-77252-3
[56] E. Markopoulos, I. S. Kirane, D. Balaj, and H. Vanharanta, “Artificial Intelligence and Blockchain Technology Adaptation for Human Resources Democratic Ergonomization on Team Management,” in Human Systems Engineering and Design II, pp. 445-455, January 2020, doi: 10.1007/978-3-030-27928-8_68
[57] V. Keršič, P. Štukelj, A. Kamišalić, S. Karakatić, M. Turkanović, “A Blockchain and AI based Platform for Global Employability,” in Blockchain and applications, pp. 161-168, January 2020, doi: 10.1007/978-3-030-23813-1_20
[58] M. Arora, A. B. Chopra, V. S. Dixit, “An Approach to Secure Collaborative Recommender System Using Artificial Intelligence, Deep Learning, and Blockchain,” in Intelligent communication, control and devices, Springer Singapore, January 2020, pp. 483-495, doi: https://doi.org/10.1007/978-981-13-8618-3_51
[59] A. Ladia, “Privacy Centric Collaborative Machine Learning Model Training via Blockchain,” Blockchain and applications, January 2020, pp. 62-70, doi: 10.1007/978-3-030-23813-1_8
[60] Z. Li, H. Guo, W. M. Wang, Y. Guan, A. V. Barenji, G. Q. Huang, K. S. McFall, X. Chen, “A Blockchain and AutoML Approach for Open and Automated Customer Service,” IEEE Transactions on Industrial Informatics, vol. 15, Issue 6, pp. 3642-3651, June 2019, doi: 10.1109/TII.2019.2900987
[61] V. Charles, A. Emrouznejad, T. A. Gherman, “A critical analysis of the integration of blockchain and artificial intelligence for supply chain,” Annals of Operations Research, vol. 327, no. 5, pp. 7–47, January 2023, doi: 10.1007/s10479-023-05169-w
[62] N. Tsolakis, R. Schumacher, M. Dora, M. Kumar, “Artificial intelligence and blockchain implementation in supply chains: a pathway to sustainability and data monetisation?,” Annals of Operations Research, vol. 327, pp. 157–210, 2023, doi: 10.1007/s10479-022-04785-2
[63] Z. K. Idrissi, M. Lachgar, H. Hrimech, “Blockchain, IoT and AI in logistics and transportation: A systematic review,” Transport Economics and Management, vol. 2, Issue 8, pp. 275-285, September 2024, doi: 10.1016/j.team.2024.09.002
[64] N. Roˇzman, R. Vrabic, M. Corn, T. Poˇzrl, J. Diaci, “Distributed Logistics Platform Based on Blockchain and IoT,” Procedia CIRP, vol. 81, pp. 826-831, January 2019, doi: https://doi.org/10.1016/j.procir.2019.03.207
[65] S. Wong, J.K.-W. Yeung, Y.-Y. Lau, T. Kawasaki, “A case study of how maersk adopts cloud-based blockchain integrated with machine learning for sustainable practices,” Sustainability, vol. 15, no. 9, April 2023, doi: https://doi.org/10.3390/su15097305
[66] C.A. Bai, J. Sarkis, W. Xue, “Improving Operational Efficiency and Effectiveness through Blockchain Technology,” Production Planning & Control, vol. 35, no. 9, pp. 1-9, March 2024, doi: 10.1080/09537287.2024.2329182