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Investigating cause-and-effect relationships between supply chain 4.0 technologies

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Języki publikacji
EN
Abstrakty
EN
The developments of the fourth industrial revolution have caused changes in all areas of society, including production. The changes in production caused by the fourth industrial revolution have also resulted in fundamental changes in the supply chain and have converted it to supply chain 4.0. Organisations must be receptive to supply chain 4.0 to maintain their competitive advantage. Therefore, this study aimed to investigate the relationships among supply chain 4.0 technologies so that, by learning and understanding these connections, industries can pave the way for the implementation of these technologies in their supply chains and use them in problemsolving. The literature review was used to identify the supply chain 4.0 technologies, and the Delphi technique was applied to extract them, including the Internet of Things (IoT), cyber-physical systems, cloud computing, big data, blockchain, artificial intelligence, Radio-frequency Identification (RFID), augmented reality, virtual reality, and simulation. The relationships of supply chain 4.0 technologies were examined using the DEMATEL technique and based on interpretive structural modelling (ISM), their deployment map was drawn. The type of technologies was determined using the MICMAC method. The MICMAC analysis found that the artificial intelligence technology is independent and, based on the findings through the DEMATEL technique, this technology is related to simulation, which belongs to the first level of the interpretive structural modelling technique, and IoT, cloud computing, big data, and blockchain technologies, which are at the second level. Based on the ISM method, RFID, virtual reality, augmented reality and simulation technologies are located at the first level; IoT, cyber-physical systems, cloud computing, big data and blockchain technologies are situated in the second level; and artificial intelligence technology belongs to the third level. According to the related literature, few studies have been conducted on the issues of supply chain 4.0 and the technologies that affect it.
Rocznik
Strony
22--46
Opis fizyczny
Bibliogr. 72 poz., rys., tab.
Twórcy
  • Allameh Tabataba’i University, Iran
  • University of Mazandaran, Iran
  • University of Imam Hossein, Iran
  • Allameh Tabataba’i University, Iran
Bibliografia
  • Abdel-Basset, M., Manogaran, G. & Mohamed, M. (2018). Internet of Things (IoT) and its impact on supply chain: A framework for building smart, secure and efficient systems. Future Generation Computer Systems, 86, 614-628. doi: 10.1016/j.future.2018.04.051
  • Afshari, H., Searcy, C., & Jaber, M. Y. (2020). The role of eco-innovation drivers in promoting additive manufacturing in supply chains. International Journal of Production Economics, 223, 107538. doi: 10.1016/j.ijpe.2019.107538
  • Al-Rakhami, M. S., & Al-Mashari, M. (2021). A blockchain-based trust model for the internet of things supply chain management. Sensors, 21(5), 1759.
  • Alam, T. (2020). IAIC Transactions on Sustainable Digital Innovation (ITSDI) Cloud Computing and its role in the Information Technology. Transactions on Sustainable Digital Innovation (ITSDI), 1(2), 108-115.
  • Ali, I., & Aboelmaged, M. G. S. (2021). Implementation of supply chain 4.0 in the food and beverage industry: perceived drivers and barriers. International Journal of Productivity and Performance Management, 71(4), 1426-1443. doi: 10.1108/IJPPM-07-2020-0393
  • Arora, R., Arora, P. K., Kumar, H., & Pant, M. (2020). Additive manufacturing enabled supply chain in combating covid-19. Journal of Industrial Integration and Management, 5(4), 495-505. doi: 10.1142/S2424862220500244
  • Azzi, R., Chamoun, R. K., & Sokhn, M. (2019). The power of a blockchain-based supply chain. Computers and Industrial Engineering, 135(May), 582-592. doi: 10.1016/j.cie.2019.06.042
  • Baryannis, G., Dani, S., Validi, S., & Antoniou, G. (2019). Decision Support Systems and Artificial Intelligence in Supply Chain Risk Management. Springer Series in Supply Chain Management, 7, 53-71. doi: 10.1007/978-3-030-03813-7_4
  • Baryannis, G., Validi, S., Dani, S., & Antoniou, G. (2019). Supply chain risk management and artificial intelligence: state of the art and future research directions. International Journal of Production Research, 57(7), 2179-2202. doi: 10.1080/00207543.2018.1530476
  • Belhadi, A., Mani, V., Kamble, S. S., Khan, S. A. R., & Verma, S. (2021). Artificial intelligence-driven innovation for enhancing supply chain resilience and performance under the effect of supply chain dynamism: an empirical investigation. Annals of Operations Research, 0123456789. doi: 10.1007/s10479-021-03956-x
  • Belhadi, A., Kamble, S., Fosso Wamba, S., & Queiroz, M. M. (2021). Building supply-chain resilience: an artificial intelligence-based technique and decision-making framework. International Journal of Production Research, 60(14), 4487-4507. doi: 10.1080/00207543.2021.1950935
  • Bhatia, C. (2021). Augmented Reality Based Supply Chain Management System. In Sharma, N., Chakrabarti, A., Balas, V.E., Bruckstein, A.M. (Eds.). Data Management, Analytics and Innovation. Lecture Notes on Data Engineering and Communications Technologies (pp. 325–336). Springer, Singapore. doi: 10.1007/978-981-16-2934-1_21
  • Cañas, H., Mula, J., & Campuzano-Bolarín, F. (2020). A General Outline of a Sustainable Supply Chain 4.0. Sustainability, 12(19), 7978. doi: 10.3390/su12197978
  • Chen, L., Dui, H., & Zhang, C. (2020). A resilience measure for supply chain systems considering the interruption with the cyber-physical systems. Reliability Engineering and System Safety, 199(December), 106869. doi: 10.1016/j.ress.2020.106869
  • Demir, S., & Paksoy, T. (2020). Artificial Intelligence, Robotics and Autonomous Systems in SCM. In Paksoy, T., Kochan, C.G., & Ali, S.S. (Eds.), Logistics 4.0: Digital Transformation of Supply Chain Management (pp. 156–165). CRC Press. doi: 10.1201/9780429327636-18
  • Demir, S., Yilmaz, I., & Paksoy, T. (2020). Augmented Reality in Supply Chain Management. In Paksoy, T., Kochan, C.G., & Ali, S.S. (Eds.), Logistics 4.0: Digital Transformation of Supply Chain Management (pp. 136–145). CRC Press. doi: 10.1201/9780429327636-18
  • Dwijendra, N. K. A., Akhmadeev, R., Tumanov, D., Kosov, M., Shoar, S., & Banaitis, A. (2021). Modeling social impacts of high-rise residential buildings during the post-occupancy phase using DEMATEL method: A case study. Buildings, 11(11), 504. doi: 10.3390/buildings11110504
  • Francisco, K., & Swanson, D. (2018). The Supply Chain Has No Clothes: Technology Adoption of Blockchain for Supply Chain Transparency, Logistics, 2(1), 2. doi: 10.3390/logistics2010002
  • Frederico, G. F., Garza-Reyes, J. A., Anosike, A., & Kumar, V. (2019). Supply Chain 4.0: concepts, maturity and research agenda. Supply Chain Management: An International Journal, 25(2), 262-282. doi: 10.1108/SCM-09-2018-0339
  • Frederico, G. F. (2021a). From Supply Chain 4.0 to Supply Chain 5.0: Findings from a Systematic Literature Review and Research Directions. Logistics, 5(3), 49. doi: 10.3390/logistics5030049
  • Frederico, G. F. (2021b). Project Management for Supply Chains 4.0: A conceptual framework proposal based on PMBOK methodology. Operations Management Research, 14(3-4), 434-450. doi: 10.1007/s12063-021-00204-0
  • Gabus, A., & Fontela, E. (1972). World problems, an invitation to further thought within the framework of DEMATEL. Battelle Geneva Research Center, 1(8).
  • Gibson, I., Rosen, D., Stucker, B., & Khorasani, M. (2021). Additive manufacturing technologies. Springer.
  • Govindan, K., Kannan, D., Ballegård, T., Straarup, T., Jørgensen, T. B., & Nielsen, T. S. (2022). Supply Chain 4.0 performance measurement: A systematic literature review, framework development, and empirical evidence. Transportation Research Part E: Logistics and Transportation Review, 164(March),102725. doi: 10.1016/j.tre.2022.102725
  • Handal, R. (2017). An implementation framework for additive manufacturing in supply chains. Journal of Operations and Supply Chain Management, 10(2), p. 18. doi: 10.12660/joscmv10n2p18-31
  • Hofmann, E. (2017). Big data and supply chain decisions: the impact of volume, variety and velocity properties on the bullwhip effect. International Journal of Production Research, 55(17), 5108-5126. doi: 10.1080/00207543.2015.1061222
  • Intalar, N., Chumnumporn, K., Jeenanunta, C., & Tunpan, A. (2021). Towards Industry 4.0: Digital transformation of traditional safety shoes manufacturer in Thailand with a development of production tracking system. Engineering Management in Production and Services, 13(4), 79-94. doi: 10.2478/emj-2021-0033
  • Javaid, M., Haleem, A., Pratap Singh, R., Khan, S., & Suman, R. (2021). Blockchain technology applications for Industry 4.0: A literature-based review, Blockchain: Research and Applications, 2(4), 100027. doi: 10.1016/j.bcra.2021.100027
  • Kamble, S. S., & Gunasekaran, A. (2020). Big data-driven supply chain performance measurement system: a review and framework for implementation. International Journal of Production Research, 58(1), 65- 86. doi: 10.1080/00207543.2019.1630770
  • Kaya, S. K., Paksoy, T., & Garza-Reyes, J. A. (2020). The Impact of the Internet of Things on Supply Chain 4.0: A Review and Bibliometric Analysis. In Paksoy, T., Kochan, C.G., & Ali, S.S. (Eds.), Logistics 4.0: Digital Transformation of Supply Chain Management (pp. 35–50). CRC Press. doi: 10.1201/9780429327636-18
  • Kozma, T. (2017). Cooperation in the supply chain network. Forum Scientiae Oeconomia, 5(3), 45-58. doi: 10.23762/FSO_vol5no3_17_3
  • Łabȩdzka, J. (2021). Industry 4.0 - Policy-based approaches to efficient implementation in SMEs. Engineering Management in Production and Services, 13(4), 72- 78. doi: 10.2478/emj-2021-0032
  • Lamba, K., & Singh, S. P. (2017). Big data in operations and supply chain management: current trends and future perspectives. Production Planning and Control, 28(11-12), 877-890. doi: 10.1080/09537287.2017.1336787
  • Lewis, J. R. (1993). Multipoint Scales: Mean and Median Differences and Observed Significance Levels. International Journal of Human-Computer Interaction, 5(4), 383-392. doi: 10.1080/10447319309526075
  • Li, S., Sun, Q., & Wu, W. (2019). Benefit Distribution Method of Coastal Port Intelligent Logistics Supply Chain under Cloud Computing. Journal of Coastal Research, 93(1), 1041-1046. doi: 10.2112/SI93-150.1
  • Liu, K. P., & Chiu, W. (2021). Supply Chain 4.0: the impact of supply chain digitalization and integration on firm performance. Asian Journal of Business Ethics, 10(2), 371-389. doi: 10.1007/s13520-021-00137-8
  • Longo, F., Nicoletti, L., Padovano, A., D’Atri, G., & Forte, M. (2019). Blockchain-enabled supply chain: An experimental study. Computers and Industrial Engineering, 136(July), 57-69. doi: 10.1016/j.cie.2019.07.026
  • Lu, Q., Chen, J., Song, H., & Zhou, X. (2021). Effects of cloud computing assimilation on supply chain financing risks of SMEs. Journal of Enterprise Information Management. doi: 10.1108/jeim-11-2020-0461
  • Luomaranta, T., & Martinsuo, M. (2020). Supply chain innovations for additive manufacturing. International Journal of Physical Distribution and Logistics Management, 50(1), 54-79. doi: 10.1108/IJPDLM-10-2018-0337
  • Maheshwari, S., Gautam, P., & Jaggi, C. K. (2021). Role of Big Data Analytics in supply chain management: current trends and future perspectives. International Journal of Production Research, 59(6), 1875-1900. doi: 10.1080/00207543.2020.1793011
  • Makris, D., Nadja, Z., Hansen, L., Khan, O., Hansen, Z. N. L., & Khan, O. (2019). Adapting to supply chain 4.0: an explorative study of multinational companies. Supply Chain Forum: An International Journal, 20(2), 116–131. https://doi.org/10.1080/16258312.2 019.1577114
  • Makris, D., Lee Hansen, Z. N., & Khan, O. (2019). Adapting to supply chain 4.0: an explorative study of multinational companies. Supply Chain Forum: An International Journal, 20(2), 116-131. doi: 10.1080/16258312.2019.1577114
  • Martins, F. de C., Simon, A. T., & Campos, R. S. de (2020). Supply Chain 4.0 challenges. Gestão & Produção. SciELO Brasil, 27.
  • Chiu, M.-Ch., & Lin, Y.-H. (2016). Simulation based method considering design for additive manufacturing and supply chain: An empirical study of lamp industry, Industrial Management & Data Systems, 116, 322-348. doi: 10.1108/imds-07-2015-0266
  • Modgil, S., Singh, R. K., & Claire, H. (2021). LJMU Research Online. The International Journal of Logistics Management.
  • Mostafa, N., Hamdy, W., & Alawady, H. (2019). Impacts of Internet of Things on Supply Chains: A Framework for Warehousing. Social Sciences, 8(3), 84. doi: 10.3390/socsci8030084
  • Nara, E. O. B., da Costa, M. B., Baierle, I. C., Schaefer, J. L., Benitez, G. B., do Santos, L. M. A. L., & Benitez, L. B. (2021). Expected impact of industry 4.0 technologies on sustainable development: A study in the context of Brazil’s plastic industry. Sustainable Production and Consumption, 25(August), 102-122. doi: 10.1016/j.spc.2020.07.018
  • Perussi, J. B., Gressler, F., & Seleme, R. (2019). Supply chain 4.0: Autonomous vehicles and equipment to meet demand. International Journal of Supply Chain Management, 8(4), 33-41.
  • Princes, E. (2020). Facing disruptive challenges in supply chain 4.0. International Journal of Supply Chain Management, 9(August), 52-57.
  • Raman, S., Patwa, N., Niranjan, I., Ranjan, U., Moorthy, K., & Mehta, A. (2018). Impact of big data on supply chain management. International Journal of Logistics Research and Applications, 21(6), 579-596. doi: 10.1080/13675567.2018.1459523
  • Ramirez-Peña, M., Mayuet, P. F., Vazquez-Martinez, J. M., & Batista, M. (2020). Sustainability in the aerospace, naval, and automotive supply chain 4.0: Descriptive review. Materials, 13(24), 1-23. doi: 10.3390/ma13245625
  • Rejeb, A., Simske, S., Rejeb, K., Treiblmaier, H., & Zailani, S. (2020). Internet of Things research in supply chain management and logistics: A bibliometric analysis, Internet of Things (Netherlands), 12. doi: 10.1016/j.iot.2020.100318
  • Rejeb, A., & Rejeb, K. (2020). Blockchain and supply chain sustainability. Logforum, 16(3), 363-372.
  • Rueda-Rueda, J. S., & Portocarrero, J. M. T. (2021). Framework-based security measures for Internet of Thing: A literature review. Open Computer Science, 11(1), 346-354. doi: 10.1515/comp-2020-0220
  • Sartori, J. T. D., Frederico, G. F., & de Fátima Nunes Silva, H. (2021). Organizational knowledge management in the context of supply chain 4.0: A systematic literature review and conceptual model proposal. Knowledge and Process Management, 29(2), 147-161. doi: 10.1002/kpm.1682
  • Scavarda, A., Scavarda, L. F., Daú, G., Scavarda, A., Scavarda, L. F., & Portugal, V. J. T. (2019). The healthcare sustainable supply chain 4.0: The circular economy transition conceptual framework with the corporate social responsibility mirror. Sustainability, 11(12), 3259.
  • Scavarelli, A., Arya, A., & Teather, R. J. (2021). Virtual reality and augmented reality in social learning spaces: a literature review. Virtual Reality, 25(1), 257-277. doi: 10.1007/s10055-020-00444-8
  • Schniederjans, D. G., Ozpolat, K., & Chen, Y. (2016). Humanitarian supply chain use of cloud computing. Supply Chain Management, 21(5), 569-588. doi: 10.1108/SCM-01-2016-0024
  • Sestino, A., & De Mauro, A. (2021). Leveraging Artificial Intelligence in Business: Implications, Applications and Methods. Technology Analysis and Strategic Management, 34(1), 1-14. doi: 10.1080/09537325.2021.1883583
  • Sharma, A., Kaur, J., & Singh, I. (2020). Internet of things (IoT) in pharmaceutical manufacturing, warehousing, and supply chain management. SN Computer Science, 1(4), 1-10. doi: 10.1007/s42979-020-00248-2
  • Singh, A., Mishra, N., Ali, S. I., Shukla, N., & Shankar, R. (2015). Cloud computing technology: Reducing carbon footprint in beef supply chain. International Journal of Production Economics, 164, 462-471. doi: 10.1016/j.ijpe.2014.09.019
  • Sobb, T., Turnbull, B., & Moustafa, N. (2020). Supply chain 4.0: A survey of cyber security challenges, solutions and future directions, Electronics, 9(11), 1-31. doi: 10.3390/electronics9111864
  • Suherman, A. G., & Simatupang, T. M. (2017). The network business model of cloud computing for end-toend supply chain visibility. International Journal of Value Chain Management, 8(1), p. 22. doi: 10.1504/ ijvcm.2017.10003557
  • Szum, K. (2021). IoT-based smart cities: A bibliometric analysis and literature review. Engineering Management in Production and Services, 13(2), 115-136. doi: 10.2478/emj-2021-0017
  • Terra, J. D. R., Berssaneti, F. T., & Quintanilha, J. A. (2021). Challenges and barriers to connecting World Class Manufacturing and continuous improvement processes to Industry 4.0 paradigms. Engineering Management in Production and Services, 13(4), 115-130. doi: 10.2478/emj-2021-0035
  • Thiebes, S., Lins, S., & Sunyaev, A. (2021). Trustworthy artificial intelligence, Electronic Markets, 31(2), 447-464. doi: 10.1007/s12525-020-00441-4
  • Venkatesan, M., Mohan, H., Ryan, J. R., Schürch, C. M., Nolan, G. P., Frakes, D. H., & Coskun, A. F. (2021). Virtual and augmented reality for biomedical applications. Cell Reports Medicine, 2(7), 1-13. doi: 10.1016/j.xcrm.2021.100348
  • Wang, L., & Zhang, Y. (2020). Linear approximation fuzzy model for fault detection in cyber-physical system for supply chain management. Enterprise Information Systems, 15(7), 1-18. doi: 10.1080/17517575.2020.1791361
  • Wang, Y., Chen, C. H., & Zghari-Sales, A. (2021). Designing a blockchain enabled supply chain. International Journal of Production Research, 59(5), 1450-1475. doi: 10.1080/00207543.2020.1824086
  • Warfield, J. N. (1973). Intent structures. IEEE Transactions on Systems, Man, and Cybernetics, 2, 133-140.
  • Wu, H.-H., & Chang, S.-Y. (2015). A case study of using DEMATEL method to identify critical factors in green supply chain management. Applied Mathematics and Computation, 256, 394-403.
  • Zekhnini, K., Cherrafi, A., Bouhaddou, I., Benghabrit, Y., & Belhadi, A. (2022). Supply Chain 4.0 risk management: an interpretive structural modelling approach. International Journal of Logistics Systems and Management, 41(1-2), 171-204
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
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Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e13f7d11-4f3a-41cb-82cf-89d8ce70a663
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