Human-centric technologies in sustainable supply chain management: a systematic review of the evolution from Industry 4.0 to 5.0

Alexander Samuels

doi:10.36096/ijbes.v6i4.539

Authors

Alexander Samuels North West University https://orcid.org/0009-0009-5509-4183

DOI:

https://doi.org/10.36096/ijbes.v6i4.539

Keywords:

Industry 4.0 to 5.0 Transition; Operations Management; South African Supply Chains; Technological Innovation; Sustainable Practices

Abstract

This paper examines the shift from Industry 4.0 to Industry 5.0 in relation to sustainable supply chain management (SCM), highlighting the incorporation of human-centric technologies. As industries progress, there is an increasing necessity to integrate technologies that enhance human-machine collaboration, optimise operational efficiency, and foster sustainability. This work aims to do a systematic review of the evolutionary process, emphasising the transformation of supply chain management by these technologies. A systematic review technique, adhering to the PRISMA framework, was utilised to collect and assess pertinent material published between 2010 to 2024. The review encompassed an exhaustive database search, stringent eligibility screening, and thematic analysis via Atlas-ti software to discern main themes and patterns concerning the incorporation of human-centric technology in supply chain management. The results indicate that the change to Industry 5.0 entails a substantial movement towards human-automation collaboration, with AI and machine learning as essential components. Digital transformation is redefining supply chain management by utilising big data, the Internet of Things, and blockchain technology to enhance transparency, traceability, and decision-making. Bionic supply chains, integrating human intelligence with machine efficiency, are developing as a vital foundation for operational resilience and sustainability. The study suggests that the incorporation of human-centric technology in supply chain management enhances efficiency and sustainability while fostering a more resilient supply network adept at reacting to interruptions. This paper offers essential recommendations for academics and practitioners seeking to enhance supply chain operations in the context of Industry 5.0.

Downloads

Download data is not yet available.

References

Abbasi, M. (2017). Towards socially sustainable supply chains – Themes and challenges. European Business Review, 29(3), 261-303. https://doi.org/10.1108/ebr-03-2016-0045 DOI: https://doi.org/10.1108/EBR-03-2016-0045

Al-Mamoori, A., Krishnamurthy, A., Rownaghi, A. A., & Rezaei, F. (2017). Carbon capture and utilization update. Energy Technology, 5(6), 834-849. https://doi.org/10.1002/ente.201600747 DOI: https://doi.org/10.1002/ente.201600747

Aliahmadi, A., Nozari, H., & Ghahremani-Nahr, J. (2022). AIoT-based sustainable smart supply chain framework. International Journal of Innovation in Management Economics and Social Sciences, 2(2), 28-38. https://doi.org/10.52547/ijimes.2.2.28 DOI: https://doi.org/10.52547/ijimes.2.2.28

Anastasiadis, F., Apostolidou, I., & Michailidis, A. (2021). Food traceability: A consumer-centric supply chain approach on sustainable tomato. Foods, 10(3), 543. https://doi.org/10.3390/foods10030543 DOI: https://doi.org/10.3390/foods10030543

Ashta, A., & Herrmann, H. (2021). Artificial intelligence and fintech: An overview of opportunities and risks for banking, investments, and microfinance. Strategic Change, 30(3), 211-222. https://doi.org/10.1002/jsc.2404 DOI: https://doi.org/10.1002/jsc.2404

Baig, M. I. (2023). Industry 5.0 applications for sustainability: A systematic review and future research directions. Sustainable Development, 32(1), 662-681. https://doi.org/10.1002/sd.2699 DOI: https://doi.org/10.1002/sd.2699

Beiranvand, D. N., Firouzabadi, K. J., & Dorniani, S. (2022). A new framework for evaluating sustainable green service supply chain management in oil and gas industries. Tehni?ki Glasnik, 16(1), 74-81. https://doi.org/10.31803/tg-20210730170447 DOI: https://doi.org/10.31803/tg-20210730170447

Bentalha, B., Hmioui, A., & Alla, L. (2023). Integrating intelligence and sustainability in supply chains. DOI: https://doi.org/10.4018/979-8-3693-0225-5

Borchardt, M., Pereira, G. M., Milan, G. S., Scavarda, A. R., Nogueira, E. O., & Poltosi, L. C. (2022). Industry 5.0 beyond technology: An analysis through the lens of business and operations management literature. Organizacija, 55(4), 305-321. https://doi.org/10.2478/orga-2022-0020 DOI: https://doi.org/10.2478/orga-2022-0020

Chalmeta, R., & Barqueros-Muñoz, J.-E. (2021). Using big data for sustainability in supply chain management. Sustainability, 13(13), 7004. https://doi.org/10.3390/su13137004 DOI: https://doi.org/10.3390/su13137004

Chen, J. S., Tsou, H. T., & Huang, A. Y. (2009). Service delivery innovation. Journal of Service Research, 12(1), 36-55. https://doi.org/10.1177/1094670509338619 DOI: https://doi.org/10.1177/1094670509338619

Cillo, V., Gregori, G. L., Daniele, L. M., Caputo, F., & Bitbol-Saba, N. (2021). Rethinking companies’ culture through knowledge management lens during Industry 5.0 transition. Journal of Knowledge Management, 26(10), 2485-2498. https://doi.org/10.1108/jkm-09-2021-0718 DOI: https://doi.org/10.1108/JKM-09-2021-0718

Dabo, A. A. A., & Hosseinian-Far, A. (2023). An integrated methodology for enhancing reverse logistics flows and networks in Industry 5.0. Logistics, 7(4), 97. https://doi.org/10.3390/logistics7040097 DOI: https://doi.org/10.3390/logistics7040097

Dehbozorgi, M. H. (2024). Human in the loop: Revolutionizing Industry 5.0 with design thinking and systems thinking. Proceedings of the Design Society, 4, 245-254. https://doi.org/10.1017/pds.2024.27 DOI: https://doi.org/10.1017/pds.2024.27

Dey, A., LaGuardia, P., & Srinivasan, M. (2011). Building sustainability in logistics operations: A research agenda. Management Research Review, 34(11), 1237-1259. https://doi.org/10.1108/01409171111178774 DOI: https://doi.org/10.1108/01409171111178774

Dutta, P., Choi, T. M., Somani, S., & Butala, R. (2020). Blockchain technology in supply chain operations: Applications, challenges, and research opportunities. Transportation Research Part E: Logistics and Transportation Review, 142, 102067. https://doi.org/10.1016/j.tre.2020.102067 DOI: https://doi.org/10.1016/j.tre.2020.102067

Eriksson, K. M. (2024). Beyond lean production practices and Industry 4.0 technologies toward the human-centric Industry 5.0. Technological Sustainability. https://doi.org/10.1108/techs-11-2023-0049 DOI: https://doi.org/10.1108/TECHS-11-2023-0049

Esper, T. L., Castillo, V. E., Ren, K., Sodero, A. C., Wan, X., Croxton, K. L., Knemeyer, A. M., DeNunzio, S., Zinn, W., & Goldsby, T. J. (2020). Everything old is new again: The age of consumer-centric supply chain management. Journal of Business Logistics, 41(4), 286-293. https://doi.org/10.1111/jbl.12267 DOI: https://doi.org/10.1111/jbl.12267

Farooq, M. (2024). Artificial intelligence in supply chain management: A comprehensive review and framework for resilience and sustainability. https://doi.org/10.21203/rs.3.rs-3878218/v1 DOI: https://doi.org/10.21203/rs.3.rs-3878218/v1

Feng, Z., Zhao, L., Huangfu, Z., Liu, Z., Dong, Z., Xin, Y., Han, J., Guo, Z., & Wu, Y. (2022). Bionic design of a winding roller and experiments for cleaning long foreign matter from raw cotton. Applied Sciences, 12(19), 10003. https://doi.org/10.3390/app121910003 DOI: https://doi.org/10.3390/app121910003

Fortuna, F., & Paesano, A. (2022). 5.0 as a new stakeholder responsibility. Symphonya: Emerging Issues in Management, (2), 144-155. https://doi.org/10.4468/2022.2.13fortuna.paesano DOI: https://doi.org/10.4468/2022.2.13fortuna.paesano

Frazzon, E. M., Rodriguez, C. M. T., Pereira, M. M., Pires, M. C., & Uhlmann, I. R. (2019). Towards supply chain management 4.0. Brazilian Journal of Operations & Production Management, 16(2), 180-191. https://doi.org/10.14488/bjopm.2019.v16.n2.a2 DOI: https://doi.org/10.14488/BJOPM.2019.v16.n2.a2

Gamberini, L. (2024). Industry 5.0: A comprehensive insight into the future of work, social sustainability, sustainable development, and career. Australian Journal of Career Development, 33(1), 5-14. https://doi.org/10.1177/10384162241231118 DOI: https://doi.org/10.1177/10384162241231118

Gasser, U., & Almeida, V. A. F. (2017). A layered model for AI governance. IEEE Internet Computing, 21(6), 58-62. https://doi.org/10.1109/mic.2017.4180835 DOI: https://doi.org/10.1109/MIC.2017.4180835

Govindarajan, U. H., & Trappey, C. V. (2018). Immersive technology for human-centric cyberphysical systems in complex manufacturing processes: A comprehensive overview of the global patent profile using collective intelligence. Complexity, 2018, 1-17. https://doi.org/10.1155/2018/4283634 DOI: https://doi.org/10.1155/2018/4283634

Guo, W. (2023). Exploring the value of AI technology in optimizing and implementing supply chain data for pharmaceutical companies. Innovation in Science and Technology, 2(3), 1-6. https://doi.org/10.56397/ist.2023.05.01 DOI: https://doi.org/10.56397/IST.2023.05.01

Haddara, M., & Elragal, A. (2015). The readiness of ERP systems for the factory of the future. Procedia Computer Science, 64, 721-728. https://doi.org/10.1016/j.procs.2015.08.598 DOI: https://doi.org/10.1016/j.procs.2015.08.598

Human, S., Neumann, G., & Alt, R. (2022). Introduction to the minitrack on human-centricity in a sustainable digital economy. Proceedings of HICSS 2022. https://doi.org/10.24251/hicss.2022.572 DOI: https://doi.org/10.24251/HICSS.2022.572

Irfan, M., Elmogy, M., Majid, M. S. A., & El-Sappagh, S. (2023). The impact of AI innovation on financial sectors in the era of Industry 5.0. DOI: https://doi.org/10.4018/979-8-3693-0082-4

Islam, M. M. (2022). Innovations and service firms’ performance: A firm-level mediating and moderating effects analysis for India. International Journal of Innovation Science, 15(3), 385-405. https://doi.org/10.1108/ijis-11-2021-0204 DOI: https://doi.org/10.1108/IJIS-11-2021-0204

Kadir, B. A., Broberg, O., & Conceição, C. S. D. (2019). Current research and future perspectives on human factors and ergonomics in Industry 4.0. Computers & Industrial Engineering, 137, 106004. https://doi.org/10.1016/j.cie.2019.106004 DOI: https://doi.org/10.1016/j.cie.2019.106004

Kay?kç?, Y., Subramanian, N., Dora, M., & Bhatia, M. S. (2020). Food supply chain in the era of Industry 4.0: Blockchain technology implementation opportunities and impediments from the perspective of people, process, performance, and technology. Production Planning & Control, 33(2-3), 301-321. https://doi.org/10.1080/09537287.2020.1810757 DOI: https://doi.org/10.1080/09537287.2020.1810757

Khan, M. Z., Al-Mushayt, O. S., Alam, J., & Ahmad, J. (2010). Intelligent supply chain management. Journal of Software Engineering and Applications, 3(4), 404-408. https://doi.org/10.4236/jsea.2010.34045 DOI: https://doi.org/10.4236/jsea.2010.34045

Khan, O., Christopher, M., & Creazza, A. (2012). Aligning product design with the supply chain: A case study. Supply Chain Management: An International Journal, 17(3), 323-336. https://doi.org/10.1108/13598541211227144 DOI: https://doi.org/10.1108/13598541211227144

Khan, S. A., Mubarik, M. S., Kusi-Sarpong, S., Gupta, H. C., Zaman, S. I., & Mubarik, M. (2022). Blockchain technologies as enablers of supply chain mapping for sustainable supply chains. Business Strategy and the Environment, 31(8), 3742-3756. https://doi.org/10.1002/bse.3029 DOI: https://doi.org/10.1002/bse.3029

Kong, Y., & Ibrahim, M. (2019). Service innovation, service delivery, and customer satisfaction and loyalty in the banking sector of Ghana. The International Journal of Bank Marketing, 37(5), 1215-1233. https://doi.org/10.1108/ijbm-06-2018-0142 DOI: https://doi.org/10.1108/IJBM-06-2018-0142

Lee, K. L. (2023). Adopting smart supply chain and smart technologies to improve operational performance in the manufacturing industry. International Journal of Engineering Business Management, 15, 1-14. https://doi.org/10.1177/18479790231200614 DOI: https://doi.org/10.1177/18479790231200614

Lezoche, M., Hernández, J. E., Ruiz, L. P., Panetto, H., & Kacprzyk, J. (2020). Agri-Food 4.0: A survey of the supply chains and technologies for the future agriculture. Computers in Industry, 117, 103187. https://doi.org/10.1016/j.compind.2020.103187 DOI: https://doi.org/10.1016/j.compind.2020.103187

Li, B., Zhang, X., Ban, Y., Xu, X., Su, W., Chen, J., Zhang, S., Li, F., Liang, Z., & Zhou, S. (2022). Construction of a smart supply chain for sand factory using the edge-computing-based deep learning algorithm. Scientific Programming, 2022, 1-15. https://doi.org/10.1155/2022/9607755 DOI: https://doi.org/10.1155/2022/9607755

Linton, J. D., Klassen, R. D., & Jayaraman, V. (2007). Sustainable supply chains: An introduction. Journal of Operations Management, 25(6), 1075-1082. https://doi.org/10.1016/j.jom.2007.01.012 DOI: https://doi.org/10.1016/j.jom.2007.01.012

Liu, P., & Yi, S. P. (2016). New algorithm for evaluating the green supply chain performance in an uncertain environment. Sustainability, 8(10), 960. https://doi.org/10.3390/su8100960 DOI: https://doi.org/10.3390/su8100960

Mabula, J. B., Ping, H., & James, M. (2023). The impact of African firms’ utilization of financial and technology resources on innovation: A simple mediation. Sage Open, 13(1), 215824402311530. https://doi.org/10.1177/21582440231153037 DOI: https://doi.org/10.1177/21582440231153037

Macchion, L., Toscani, A. C., & Vinelli, A. (2022). Sustainable business models of small and medium-sized enterprises and the relationships to be established within the supply chain to support these models. Corporate Social Responsibility and Environmental Management, 30(2), 563-573. https://doi.org/10.1002/csr.2374 DOI: https://doi.org/10.1002/csr.2374

Majstorovic, V. D., Stojadinovi?, S. M., L?li?, B., & Marjanovi?, U. (2020). ERP in Industry 4.0 context. IFIP Advances in Information and Communication Technology, 287-294. https://doi.org/10.1007/978-3-030-57993-7_33 DOI: https://doi.org/10.1007/978-3-030-57993-7_33

Mamun, S. (2024). How technology impacts supply chain performance in the motorbike manufacturing industry. https://doi.org/10.21203/rs.3.rs-3940924/v1 DOI: https://doi.org/10.21203/rs.3.rs-3940924/v1

Marshall, D., McCarthy, L., McGrath, P., & Claudy, M. (2015). Going above and beyond: How sustainability culture and entrepreneurial orientation drive social sustainability supply chain practice adoption. Supply Chain Management: An International Journal, 20(4), 434-454. https://doi.org/10.1108/scm-08-2014-0267 DOI: https://doi.org/10.1108/SCM-08-2014-0267

Meylan, F. D., Moreau, V., & Erkman, S. (2015). CO2 utilization in the perspective of industrial ecology: An overview. Journal of CO2 Utilization, 12, 101-108. https://doi.org/10.1016/j.jcou.2015.05.003 DOI: https://doi.org/10.1016/j.jcou.2015.05.003

Mhlanga, D. (2023). Responsible Industry 4.0: A framework for human-centered artificial intelligence. DOI: https://doi.org/10.4324/9781003393382

Modgil, S., Gupta, S., Stekelorum, R., & Laguir, I. (2021). AI technologies and their impact on supply chain resilience during COVID-19. International Journal of Physical Distribution & Logistics Management, 52(2), 130-149. https://doi.org/10.1108/ijpdlm-12-2020-0434 DOI: https://doi.org/10.1108/IJPDLM-12-2020-0434

Mourtzis, D. (2023). The metaverse in Industry 5.0: A human-centric approach towards personalized value creation. Encyclopedia, 3(3), 1105-1120. https://doi.org/10.3390/encyclopedia3030080 DOI: https://doi.org/10.3390/encyclopedia3030080

Mubarik, M., Raja Zuraidah Raja Mohd, R., Mubarak, M. F., & Ashraf, R. (2021). Impact of blockchain technology on green supply chain practices: Evidence from an emerging economy. Management of Environmental Quality: An International Journal, 32(5), 1023-1039. https://doi.org/10.1108/meq-11-2020-0277 DOI: https://doi.org/10.1108/MEQ-11-2020-0277

Mursidah, S., & Fauzi, A. M. (2022). Sustainable sugarcane supply chain performance assessment: A review and research agenda. IOP Conference Series: Earth and Environmental Science, 1063(1), 012039. https://doi.org/10.1088/1755-1315/1063/1/012039 DOI: https://doi.org/10.1088/1755-1315/1063/1/012039

Nayal, K., Raut, R. D., Priyadarshinee, P., Narkhede, B. E., Kazanço?lu, Y., & Narwane, V. S. (2021). Exploring the role of artificial intelligence in managing agricultural supply chain risk to counter the impacts of the COVID-19 pandemic. The International Journal of Logistics Management, 33(3), 744-772. https://doi.org/10.1108/ijlm-12-2020-0493 DOI: https://doi.org/10.1108/IJLM-12-2020-0493

Nicoletti, B. (2023). Supply Network 5.0: How to improve human automation in the supply chain. DOI: https://doi.org/10.1007/978-3-031-22032-6

Nyamekye, P. (2023). Enhancing Industry 5.0 goals through laser-based additively manufactured high-performance metals. IOP Conference Series: Materials Science and Engineering, 1296(1), 012001. https://doi.org/10.1088/1757-899X/1296/1/012001 DOI: https://doi.org/10.1088/1757-899X/1296/1/012001

Ojo, O. O., Zigan, S., Orchard, J. E., & Shah, S. (2019). Advanced technology integration in food manufacturing supply chain environment: Pathway to sustainability and companies’ prosperity. https://doi.org/10.1109/temscon.2019.8813713 DOI: https://doi.org/10.1109/TEMSCON.2019.8813713

Olan, F., Arakpogun, E. O., Jayawickrama, U., Suklan, J., & Liu, S. (2024). Sustainable supply chain finance and supply networks: The role of artificial intelligence. IEEE Transactions on Engineering Management, 1-16. https://doi.org/10.1109/tem.2021.3133104 DOI: https://doi.org/10.1109/TEM.2021.3133104

Omar, I., Debe, M., Jayaraman, R., Salah, K., Omar, M., & Arshad, J. (2022). Blockchain-based supply chain traceability for COVID-19 personal protective equipment. Computers & Industrial Engineering, 167, 107995. https://doi.org/10.1016/j.cie.2022.107995 DOI: https://doi.org/10.1016/j.cie.2022.107995

P. G. Yogindra, & Vijaya, G. S. (2022). A systematic literature review of strategic partnership in sustainable supply chain - Indian aerospace industries. ECS Transactions, 107(1), 2315-2328. https://doi.org/10.1149/10701.2315ecst DOI: https://doi.org/10.1149/10701.2315ecst

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., & Brennan, S. E. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. International Journal of Surgery, 88, 105906. https://doi.org/10.1016/j.ijsu.2021.105906 DOI: https://doi.org/10.1016/j.ijsu.2021.105906

Park, A., & Li, H. (2021). The effect of blockchain technology on supply chain sustainability performances. Sustainability, 13(4), 1726. https://doi.org/10.3390/su13041726 DOI: https://doi.org/10.3390/su13041726

Paul, S. K., Ali, S. M., & Moktadir, M. A. (2020). Guest editorial. Modern Supply Chain Research and Applications, 2(3), 115-116. https://doi.org/10.1108/mscra-08-2020-024 DOI: https://doi.org/10.1108/MSCRA-08-2020-024

Paulus, T., Woods, M., Atkins, D. P., & Macklin, R. (2017). The discourse of QDAS: Reporting practices of ATLAS.ti and NVivo users with implications for best practices. International Journal of Social Research Methodology, 20(1), 35-47. https://doi.org/10.1080/13645579.2015.1102454 DOI: https://doi.org/10.1080/13645579.2015.1102454

Rethlefsen, M. L., Kirtley, S., Waffenschmidt, S., Ayala, A. P., Moher, D., Page, M. J., & Koffel, J. B. (2021). PRISMA-S: An extension to the PRISMA statement for reporting literature searches in systematic reviews. Systematic Reviews, 10(1), 1-19. https://doi.org/10.1186/s13643-020-01542-z DOI: https://doi.org/10.1186/s13643-020-01542-z

Reynolds, S. (2024). Exploring the role of governance mechanisms in promoting sustainability across supply chains. https://doi.org/10.21203/rs.3.rs-4286347/v1 DOI: https://doi.org/10.21203/rs.3.rs-4286347/v1

Richey, R. G. (2023). Artificial intelligence in logistics and supply chain management: A primer and roadmap for research. Journal of Business Logistics, 44(4), 532-549. https://doi.org/10.1111/jbl.12364 DOI: https://doi.org/10.1111/jbl.12364

Saberi, S., Kouhizadeh, M., Sarkis, J., & Shen, L. Y. (2018). Blockchain technology and its relationships to sustainable supply chain management. International Journal of Production Research, 57(7), 2117-2135. https://doi.org/10.1080/00207543.2018.1533261 DOI: https://doi.org/10.1080/00207543.2018.1533261

Shamseer, L., Moher, D., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., Shekelle, P., & Stewart, L. A. (2015). Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: Elaboration and explanation. BMJ, 349. https://doi.org/10.1136/bmj.g7647 DOI: https://doi.org/10.1136/bmj.g7647

Sharifpour, H., Ghaseminezhad, Y., Hashemi-Tabatabaei, M., & Amiri, M. (2022). Investigating cause-and-effect relationships between supply chain 4.0 technologies. Engineering Management in Production and Services, 14(4), 22-46. https://doi.org/10.2478/emj-2022-0029 DOI: https://doi.org/10.2478/emj-2022-0029

Singh, R., Modgil, S., & Shore, A. (2023). Building artificial intelligence-enabled resilient supply chains: A multi-method approach. Journal of Enterprise Information Management, 37(2), 414-436. https://doi.org/10.1108/jeim-09-2022-0326 DOI: https://doi.org/10.1108/JEIM-09-2022-0326

Snyder, H., Witell, L., Gustafsson, A., Fombelle, P. W., & Kristensson, P. (2016). Identifying categories of service innovation: A review and synthesis of the literature. Journal of Business Research, 69(7), 2401-2408. https://doi.org/10.1016/j.jbusres.2016.01.009 DOI: https://doi.org/10.1016/j.jbusres.2016.01.009

Soares, M. C., Ferreira, C. V., & Murari, T. B. (2021). Supply chain resilience and Industry 4.0: An evaluation of the Brazilian Northeast automotive OEM scenario post COVID-19. AI Perspectives, 3(1). https://doi.org/10.1186/s42467-021-00010-1 DOI: https://doi.org/10.1186/s42467-021-00010-1

Steffen, N., Ansari, F., & Schlund, S. (2022). Reciprocal learning in human-machine collaboration: A multi-agent system framework in Industry 5.0. In Wirtschaftsinformatik Proceedings 2022 (pp. 207-225). https://doi.org/10.30844/wagb_2022_11 DOI: https://doi.org/10.30844/WAGB_2022_11

Sun, J., Sarfraz, M., Khawaja, K. F., & Abdullah, M. I. (2022). Sustainable supply chain strategy and sustainable competitive advantage: A mediated and moderated model. Frontiers in Public Health, 10. https://doi.org/10.3389/fpubh.2022.895482 DOI: https://doi.org/10.3389/fpubh.2022.895482

Treiblmaier, H. (2019). Combining blockchain technology and the physical internet to achieve triple bottom line sustainability: A comprehensive research agenda for modern logistics and supply chain management. Logistics, 3(1), 10. https://doi.org/10.3390/logistics3010010 DOI: https://doi.org/10.3390/logistics3010010

Truby, J. (2020). Governing artificial intelligence to benefit the UN Sustainable Development Goals. Sustainable Development, 28(4), 946-959. https://doi.org/10.1002/sd.2048 DOI: https://doi.org/10.1002/sd.2048

Truby, J., Brown, R. D., & Dahdal, A. (2020). Banking on AI: Mandating a proactive approach to AI regulation in the financial sector. Law and Financial Markets Review, 14(2), 110-120. https://doi.org/10.1080/17521440.2020.1760454 DOI: https://doi.org/10.1080/17521440.2020.1760454

Wang, S., Fang, Z., & Wu, D. (2022a). Internet of Things-enabled tourism economic data analysis and supply chain modeling. Technological and Economic Development of Economy, 30(2), 423-440. https://doi.org/10.3846/tede.2022.17120 DOI: https://doi.org/10.3846/tede.2022.17120

Wang, S., Wan, J., Zhang, D., Li, D., & Zhang, C. (2016). Towards smart factory for Industry 4.0: A self-organized multi-agent system with big data-based feedback and coordination. Computer Networks, 101, 158-168. https://doi.org/10.1016/j.comnet.2015.12.017 DOI: https://doi.org/10.1016/j.comnet.2015.12.017

Wang, T., Chen, H., Dai, R., & Zhu, D. (2022b). Intelligent logistics system design and supply chain management under edge computing and Internet of Things. Computational Intelligence and Neuroscience, 2022, 1-12. https://doi.org/10.1155/2022/1823762 DOI: https://doi.org/10.1155/2022/1823762

Yan, J., Xin, S., Liu, Q., Xu, W., Yang, L., Li, F., Chen, B., & Wang, Q. (2014). Intelligent supply chain integration and management based on Cloud of Things. International Journal of Distributed Sensor Networks, 10(3), 624839. https://doi.org/10.1155/2014/624839 DOI: https://doi.org/10.1155/2014/624839

Yang, J., Liu, T., Liu, Y., & Morgan, P. L. (2022). Review of human-machine interaction towards Industry 5.0: Human-centric smart manufacturing. Proceedings of the ASME International Design Engineering Technical Conferences (DETC). https://doi.org/10.1115/detc2022-89711 DOI: https://doi.org/10.1115/DETC2022-89711

Yao, X., Ma, N., Zhang, J., Wang, K., Yang, E., & Faccio, M. (2022). Enhancing wisdom manufacturing as industrial metaverse for Industry and Society 5.0. Journal of Intelligent Manufacturing, 35(1), 235-255. https://doi.org/10.1007/s10845-022-02027-7 DOI: https://doi.org/10.1007/s10845-022-02027-7

Yawar, S. A., & Seuring, S. (2015). Management of social issues in supply chains: A literature review exploring social issues, actions, and performance outcomes. Journal of Business Ethics, 141(3), 621-643. https://doi.org/10.1007/s10551-015-2719-9 DOI: https://doi.org/10.1007/s10551-015-2719-9

Yontar, E. (2023). Challenges, threats and advantages of using blockchain technology in the framework of sustainability of the logistics sector. Turkish Journal of Engineering, 7(3), 186-195. https://doi.org/10.31127/tuje.1094375 DOI: https://doi.org/10.31127/tuje.1094375

Yuan, Z., Eden, M. R., & Gani, R. (2015). Toward the development and deployment of large-scale carbon dioxide capture and conversion processes. Industrial & Engineering Chemistry Research, 55(12), 3383-3419. https://doi.org/10.1021/acs.iecr.5b03277 DOI: https://doi.org/10.1021/acs.iecr.5b03277

Zeiringer, J. P., & Thalmann, S. (2020). Knowledge risks in digital supply chains: A literature review. Proceedings of the Wirtschaftsinformatik Conference 2020, 370-385. https://doi.org/10.30844/wi_2020_d1-zeiringer DOI: https://doi.org/10.30844/wi_2020_d1-zeiringer

Zelbst, P. J. (2023). Linkages between technologies and supply chain performance: Benefits, power and risk reduction. Supply Chain Management: An International Journal, 29(1), 207-218. https://doi.org/10.1108/scm-03-2023-0131 DOI: https://doi.org/10.1108/SCM-03-2023-0131