Abu-salim, T., El Barachi, M., Mohamed, A., Halstead, S., & Babreak, N. (2022). The mediator and moderator roles of perceived cost on the relationship between organizational readiness and the intention to adopt blockchain technology. Technology in Society, 71, 102108. https://doi.org/10.1016/j.techsoc.2022.102108. 20
Al Tera, A., Alzubi, A. & Iyiola, K. (2024). Supply chain digitalization and performance: A moderated mediation of supply chain visibility and supply chain survivability. Heliyon, 10(4). https://doi.org/10.1016/j.heliyon.2024.e25584
Al-Okaily, M., & Al-Okaily, A. (2025), Financial data modeling: an analysis of factors influencing big data analytics-driven financial decision quality, Journal of Modelling in Management, 20(2), 301-321. https://doi.org/10.1108/JM2-08-2023-0183
Amini Kalibar, N. & Saghafi, F. (2021). Identifying and Prioritizing Applications of Internet of Things in the Supply Chain of Distribution and Sale of Health Care Products in Iran. In ITNG 2021 18th International Conference on Information Technology-New Generations, Springer, Cham, 147-153. https://doi.org/10.1007/978-3-030-70416-2_19
Aslani Liaei, V., Abedi, S., Irajpour, A., & Ehtesham Rathi, R. (2021). Designing a Model for Evaluation of Sustainable Supply Chain Multi Capabilities Based on Artificial Intelligence. Journal of Industrial Management Perspective, 11(3), 107-129. [In Persian] https://doi.org/10.52547/jimp.11.3.107
Attaran, M. (2023). The impact of 5G on the evolution of intelligent automation and industry digitization. Journal of Ambient Intelligence and Humanized Computing, 14(5), 5977-5993. https://doi.org/10.1007 /S12652-020-02521-X
Bag, S., & Pretorius, J. H. C. (2020). Relationships between industry 4.0,sustainable manufacturing and circular economy: proposal of a research framework. International Journal of Organizational Analysis, 30(4), 864-898. https://doi.org/10.1108/IJOA-04-2020-2120
Bai, C., Dallasega, P., Orzes, G., & Sarkis, J. (2020). Industry 4.0 technologies assessment: Asustainability perspective. International journal of production economics, 229, 107776. https://doi.org/10.1016/j.ijpe.2020.107776
Beier, G., Ullrich, A., Niehoff, S., Reißig, M., & Habich, M. (2020). Industry 4.0: how I defined from a sociotechnical perspective and how much sustainability it includes e a literature review. Journal of Cleaner Production, 259. https://doi.org/10.1016/j.jclepro.2020.120856
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Büchi, G., Cugno, M., & Castagnoli, R. (2020). Smart factory performance and Industry 4.0. Technological Forecasting and Social Change, 150, 119790. https://doi.org/10.1016/j.techfore.2019.119790
Chen, Y. & Chen, G. (2022). Optimization of the Intelligent Asset Management System Basedon WSN and RFID Technology. Ed. Chih-Cheng Chen. Journal of Sensors, 11 https://doi.org/10.1155/2022/3436530.
Clarke, V. & Braun, V. (2013), Teaching thematic analysis: Overcoming challenges and developing strategies for effective learning. The Psychologist, 26(2), 120-123.
de Vass, T., Shee, H., & Miah, S. (2021). IoT in Supply Chain Management: Opportunities and Challenges for Businesses in Early Industry 4.0 Context. Operations and Supply Chain Management: An International Journal, 14(2), 148-161. http://doi.org/10.31387/oscm0450293
Esmailipour-Masouleh, E., Aboujafari, R., & Afshari-Mofrad, M. (2022). Financing Tools of Automotive Production System Based on Value Chain Analysis of Automotive Industry. Journal of Science and Technology Policy, 15(1), 1-22. [In Persian] https://doi.org/10.22034/jstp.2022.13922
Faguet, J. (2023). Decentralization and governance. Hikama, 7(4), 187-218. https://doi.org/10.31430/RPAR6402
Feng, H., Wang, X., Duan, Y., Zhang, J., and Zhang, X. (2020). Applying Blockchain Technology to Improve Agri-Food Traceability: A Review of Development Methods, Benefits and Challenges. Journal of Cleaner Production, 260, 121031. https://doi.org/10.1016/j.jclepro.2020.121031.
Gao, Y., Tian, F., Li, J., Fang, Z., Alrubaye, S., & Song, W., & Yan, Y. (2022). Joint Optimization of Depth and Ego-Motion for Intelligent Autonomous Vehicles. IEEE Transactions on Intelligent Transportation Systems, 1-14. https://doi.org/10.1109/TITS.2022.3159275. 32
Ghobakhloo, M. (2020). Industry 4.0, digitization, and opportunities for sustainability. Journal of Cleaner Production, 252. https://doi.org/10.1016/j.jclepro.2019.119869
Govindan, K., Rajeev, A., Padhi, S., & Pati, R. (2020). Supply chain sustainability and performance of firms: A meta-analysis of the literature. Transportation Research Part E: Logistics and Transportation Review, 137. 101923. https://doi.org/10.1016/j.tre.2020.101923
Gupta, S., Amaba, B.A., McMahon, M., & Gupta, K. (2021). The Evolution of Artificial Intelligence in the Automotive Industry. 2021 Annual Reliability and Maintainability Symposium (RAMS), 1-7. https://doi.org/10.1109/RAMS48097.2021.9605795
He, W. (2021). IoT System for Intelligent Firefighting in the Electric Power Industry. Journal of Shanghai Jiaotong University (Science), 26(5), 686-689. https://doi.org/10.1007/s12204-021-2358-5
Hovanec, M., Korba, P., Vencel, M., & Al-Rabeei, S. (2023). Simulating a Digital Factory and Improving Production Efficiency by Using Virtual Reality Technology. Applied Sciences. 13, 5118. https://doi.org/10.3390/app13085118
Ivanov, D., Dolgui, A., & Sokolov, B. (2018). The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics. International Journal of Production Research, 57(3), 829–846. https://doi.org/10.1080/00207543.2018.1488086
Kumar, S., & Mukherjee, S. (2021). Monitoring Food Quality in Supply Chain Logistics. In Research in Intelligent and Computing in Engineering, First edition, Singapore, Publications Springer. https://doi.org/10.1007/978-981-15-7527-3_73
Lefranc, G. (2023). Trends in Robotics Management and Business Automation. IEEE Technol. Eng. Manag. Soc. Body Knowl. (TEMSBOK), 265-288. https://doi.org/10.1002/9781119987635.ch16
Li, C., Zheng, P., Yin, Y., Wang, B. & Wang, L. (2023). Deep reinforcement learning in smart manufacturing: A review and prospects. CIRP Journal of Manufacturing Science and Technology, 40, 75-101. https://doi.org/10.1016/j.cirpj.2022.11.003
Li, X., Zhou, T., & Cao, S.H. (2025). Digital transformation, supply chain collaboration, and corporate innovation boundaries. International Review of Economics & Finance, 104, 10428. https://doi.org/10.1016/j.iref.2025.104628
Liu, C., Ji, H., & Wei, J. (2022). Smart supply chain risk assessment in intelligent manufacturing. Journal of computer information systems, 62(3), 609- 621.https://doi.org/10.1080/08874417.2021.1872045
Madhup, K., Gandhi, C. C., & Kaushik Ghosh. (2022). To study the challenges faced in application of artificial intelligence in automobile industry. AIP Conf. Proc, 2519 (1), 030013. https://doi.org/10.1063/5.0111115
Minaee, M., Elahi, S., Majidpour, M., & Manteghi, M. (2020). How Industry’s Characteristics Affect the Technological Catch-up by a Latecomer Firm? Case Study of an Iranian Automobile Firm. Journal of Science and Technology Policy, 13(3), 47-66. https://doi.org/10.22034/jstp.2020.12.3.1259
Mohanta, B. K., Satapathy, U., & Jena, D. (2021). Addressing Security and Computation Challenges in IoT Using Machin Learning. In Advances in DistributedComputing and Machine Learning, 74-67. https://doi.org/10.1007/978-981-15-4218-3-7
Monshizadeh, F., Sadeghi Moghadam, M. R., Mansouri, T., & Kumar, M. (2023). Developing an industry 4.0 readiness model using fuzzy cognitive mapsapproach. International Journal of Production Economics, 255, 108658. https://doi.org/10.1016/j.ijpe.2022.108658
Munir, M., Habib, S., Hussain, A., Shahbaz, M., Qamar, A., Masood, T., Sultan, M., Abbas, M. M., Imran, S, Hasan, M., Akhtar, M., Ayub, H. M. U., & Salman, C. A. (2022). Blockchain Adoption for Sustainable Supply Chain Management: Economic, Environmental, and Social Perspectives Citation. Frontiers in Energy Research, 10, 899632. https://doi.org/10.3389/fenrg.2022.899632. 27
Nahr, J. G., Nozari, H., & Sadeghi, M. E. (2021). Green supply chain based on artificial intelligence of thing (AioT). International Journal of Innovation in Management, Economics and Social Sciences, 1(2), 56-63. https://doi.org/10.52547/ijimes.
Nguyen, T., Akbari, M. & Nguyen, K. (2024). Unlocking the potential of Vietnamese supply chain with digitalization: a bibliometric analysis and systematic literature review. Operations and Supply Chain Management: An International Journal, 17(1), 123-141. http://doi.org/10.31387/oscm0560418
Nozari, H., Ghahremani-Nahr, J., Fallah, M., & Szmelter-Jarosz, A. (2022). Assessment of cyber risks in an IoT-based supply chain using a fuzzy decision-making method. International Journal of Innovation in Management, Economics and Social Sciences, 2, 52-64. https://doi.org/10.52547/ijimes
Öztürk, Ö. (2023). Analysis of industry 4.0 technologies’ adoption using interpretive structural modelling: empirical findings from manufacturing sector in Turkey Master's thesis, Middle East Technical University, 81. https://hdl.handle.net/11511/102145
Pappas, N., Caputo, A., Pellegrini, M. M., Marzi, G., & Michopoulou, E. (2021). The complexity of decision-making processes and IoT adoption in accommodation SMEs. Journal of Business Research, 131, 573-583. https://doi.org/10.1016/j.jbusres.2021.01.010
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
Rad, F. F., Oghazi, P., Palmié, M., Chirumalla, K., Pashkevich, N., Patel, P. C., & Sattari, S. (2022). Industry 4.0 and supply chain performance: A systematic literature review of the benefits, challenges, and critical success factors of 11 core technologies. Industrial Marketing Management, 105, 268-293. https://doi.org/10.1016/j.indmarman.2022.06.009
Rasool, F., Greco, M., & Grimaldi, M. (2023). Digital supply chain performance metrics: a literature review. Measuring Business Excellence, 26(1), 23-38. https://doi.org/10.1108/MBE-11-2020-0147
Shi, X., & Liu, H. (2025). How does digital supply chain transformation enhance sustainable performance of renewable energy enterprises?. International Review of Economics & Finance, 103, 104460. https://doi.org/10.1016/j.iref.2025.104460
Wang, L., Deng, T., Shen, Z. J. M., Hu, H., & Qi, Y. (2022). Digital twin-driven smart supply chain. Frontiers of Engineering Management, 9(1), 56-70. https://doi.org/10.1007/s42524-021-0186-9
Younis, H., & Wuni, I.Y. (2023). Application of industry 4.0 enablers in supply chain management: scientometric analysis and critical review. Heliyon, 9(11), e21292. https://doi.org/10.1016/j.heliyon.2023.e21292
Zhang, Z., Wen, F., Sun, Z., Guo, X., He, T., & Lee, C. (2022). Artificial Intelligence‐Enabled Sensing Technologies in the 5G/Internet of Things Era: From Virtual Reality/Augmented Reality to the Digital Twin. Advanced Intelligent Systems, 4(7). https://doi.org/10.1002 /AISY.202100228
