Leveraging Innovative Logistics for Strengthening Supply Chain Resilience in the Face of Disruptions
DOI:
https://doi.org/10.54392/ajir2523Keywords:
Disruption, Supply Chain Resilience, Logistics Solutions, Supply Chain PerformanceAbstract
Various disturbances can affect Supply chain (SC) networks in the dynamic global environment which comprises natural disasters and geopolitical unrest and worldwide pandemics. These disturbances caused numerous organizations to endure severe delays and stockouts together with substantial financial losses which uncovered the weaknesses of typical SC models. Research explores essential steps for upgrading SC resilience while developing new strategic logistics approaches. The research examines how innovative logistical solutions help reinforce supply chains against disruption events. Fifteen managers together with senior managers alongside senior employees from Indian smart manufacturing organizations received a survey for their participation. The survey-based approach and grey relational analysis (GRA) method established complete structural relationships between the developed logistics solutions which were subjected to ranking analysis. Research involved wide literature assessments along with knowledge from operational practices which revealed the development of key logistical strategies including AI-based predictive maintenance together with Digital twins and IoT systems for flexible transportation methods. It is alongside distributed smart warehousing and workforce flexibility for skills development through blockchain security solutions alongside digital platforms for business collaborations and reverse logistics models and agile supply chain networks designed for supplier flexibility. The study classifies Digital Platforms and Cloud-Based Collaboration (LS6) and Digital Twins and IoT (LS2) through their corresponding positions in the logistics solution list. The tested innovative logistic approaches provide manufacturers with better crisis response abilities alongside operational performance improvements. Through this study researchers and practitioners gain an opportunity to initiate proactive logistics innovation strategies during disruption times by developing operational guidelines. The purpose of this study lies in its discovery of alternative logistic solutions for manufacturing organizations to deal with SC resilience challenges and their subsequent ranking by GRA methodology.
References
Abideen, A.Z., Sundram, V.P.K., Pyeman, J., Othman, A.K., Sorooshian, S. (2021). Digital twin integrated reinforced learning in supply chain and logistics. Logistics, 5(4), 84. https://doi.org/10.3390/logistics5040084
Ahmad, R.W., Hasan, H., Jayaraman, R., Salah, K., Omar, M. (2021). Blockchain applications and architectures for port operations and logistics management. Research in Transportation Business & Management, 41, 100620. https://doi.org/10.1016/j.rtbm.2021.100620
Akram, A., Bross, P. (2018). Trust, Privacy and Transparency with Blockhain Technology in Logistics. MCIS 2018 Proceedings, 17. https://aisel.aisnet.org/mcis2018/17
Aldrighetti, R., Battini, D., Karanam ov, D., Zennaro, I. (2021). Costs of resilience and disruptions in supply chain network design models: a review and future research directions. International Journal of Production Economics, 235, 108103. https://doi.org/10.1016/j.ijpe.2021.108103
Ali, S.S., Khan, S., Fatma, N., Ozel, C., Hussain, A. (2024). Utilisation of drones in achieving various applications in smart warehouse management. Benchmarking: An International Journal, 31(3), 920-954. https://doi.org/10.1108/BIJ-01-2023-0039
Ambrosini, V., Bowman, C. (2009), “What are dynamic capabilities and are they a useful construct in strategic management?” International Journal of Management Reviews, 11(1), 29-49. https://doi.org/10.1111/j.1468-2370.2008.00251.x
Ambulkar, S., Blackhurst, J., Grawe, S. (2015). Firm's resilience to supply chain disruptions: Scale development and empirical examination. Journal of operations management, 33, 111-122. https://doi.org/10.1016/j.jom.2014.11.002
Azzeh, M., Neagu, D., Cowling, P.I. (2010). Fuzzy grey relational analysis for software effort estimation. Empirical Software Engineering, 15(1), 60-90. https://doi.org/10.1007/s10664-009-9113-0
Bag, S., Gupta, S., Foropon, C. (2019). Examining the role of dynamic remanufacturing capability on supply chain resilience in circular economy. Management Decision, 57(4), 863-885. https://doi.org/10.1108/MD-07-2018-0724
Baker, P. (2007). An exploratory framework of the role of inventory and warehousing in international supply chains. The International Journal of Logistics Management, 18(1), 64-80. https://doi.org/10.1108/09574090710748171
Ballou, R.H. (1997). Business logistics: importance and some research opportunities. Gestão & Produção, 4, 117-129. https://doi.org/10.1590/S0104-530X1997000200001
Bandyopadhyay, D., Sen, J. (2011). Internet of things: Applications and challenges in technology and standardization. Wireless personal communications, 58, 49-69. https://doi.org/10.1007/s11277-011-0288-5
BCI-Business Continuity Institute. (2019). Supply chain resilience 10 year trend analysis. 2009–2018. Zurich Insurance Group.
Bjorklund, M., Forslund, H. (2018). Exploring the sustainable logistics innovation process. Industrial Management & Data Systems, 118(1), 204-217. https://doi.org/10.1108/IMDS-02-2017-0058
Boysen, N., De Koster, R., Weidinger, F. (2019). Warehousing in the e-commerce era: A survey. European Journal of Operational Research, 277(2), 396-411. https://doi.org/10.1016/j.ejor.2018.08.023
Brah, S.A., Ying Lim, H. (2006). The effects of technology and TQM on the performance of logistics companies. International Journal of Physical Distribution & Logistics Management, 36(3), 192-209. https://doi.org/10.1108/09600030610661796
Butler, C. (2018). Five steps to organisational resilience: Being adaptive and flexible during both normal operations and times of disruption. Journal of Business Continuity & Emergency Planning, 12(2), 103–112.
Cai, Y., Starly, B., Cohen, P., Lee, Y.S. (2017). Sensor data and information fusion to construct digital-twins virtual machine tools for cyber-physical manufacturing. Procedia manufacturing, 10, 1031-1042. https://doi.org/10.1016/j.promfg.2017.07.094
Carbone, V., Rouquet, A., Roussat, C. (2017). The rise of crowd logistics: A new way to co‐create logistics value. Journal of Business Logistics, 38(4), 238-252. https://doi.org/10.1111/jbl.12164
Chan, F.T., Zhang, T. (2011). The impact of Collaborative Transportation Management on supply chain performance: A simulation approach. Expert Systems with Applications, 38(3), 2319-2329. https://doi.org/10.1016/j.eswa.2010.08.020
Chaouni Benabdellah, A., Zekhnini, K., Cherrafi, A. (2021). Sustainable and resilience improvement through the design for circular digital supply chain. In Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems, 550–559. https://doi.org/10.1007/978-3-030-85910-7_58
Cheng, M.J. Simmons, J.E.L. (1994), “Traceability in manufacturing systems”, International Journal of Operations and Production Management, 14(10), 4-16. https://doi.org/10.1108/01443579410067199
Cherchata, A., Popovychenko, I., Andrusiv, U., Gryn, V., Shevchenko, N., Shkuropatskyi, O. (2022). Innovations in logistics management as a direction for improving the logistics activities of enterprises. Management Systems in Production Engineering, 30(1), 9-17. https://doi.org/10.2478/mspe-2022-0002
Cho, B., Ryoo, S.Y., Kim, K.K. (2017). Interorganizational dependence, information transparency in interorganizational information systems, and supply chain performance. European Journal of Information Systems, 26(2), 185-205. https://doi.org/10.1057/s41303-017-0038-1
Choi, T.M., Guo, S., Luo, S. (2020). When blockchain meets supply chain: A systematic literature review on the intersection of blockchain and supply chain management. International Journal of Production Research, 135, 101860. https://doi.org/10.1016/j.tre.2020.101860
Christopher, M., Peck, H. (2004). Building the Resilient Supply Chain. The International Journal of Logistics Management, 15(2), 1-13. https://doi.org/10.1108/09574090410700275
Christopher, M., Towill, D.R. (2000). Supply chain migration from lean and functional to agile and customized. Supply Chain Management: An International Journal, 5(4), 206-213. https://doi.org/10.1108/13598540010347334
Cole, R., Stevenson, M., Aitken, J. (2019), Blockchain technology: implications for operations and supply chain management. Supply Chain Management: An International Journal, 24(4), 469-483. https://doi.org/10.1108/SCM-09-2018-0309
Cooper, M. (2024). Agile Procurement in a Changing Marketplace: Examining Adaptability and Responsiveness in Supply Chain Management. Ahead-of-Print, 1-15. https://www.preprints.org/manuscript/202407.0514/v1
Cruijssen, F., Cools, M., Dullaert, W. (2007). Horizontal cooperation in logistics: Opportunities and impediments. Transportation Research Part E: Logistics and Transportation Review, 43(2), 129-142. https://doi.org/10.1016/j.tre.2005.09.007
Deloitte. (2020). The Future of Work in Supply Chain: The Future is Flexible. Deloitte Insights.
Demirkan, H., Delen, D. (2013). Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud. Decision Support Systems, 55(1), 412-421. https://doi.org/10.1016/j.dss.2012.05.048
Ding, L., Wang, T., Chan, P.W. (2023). Forward and reverse logistics for circular economy in construction: A systematic literature review. Journal of Cleaner Production, 388, 135981. https://doi.org/10.1016/j.jclepro.2023.135981
Ding, Y., Jin, M., Li, S., Feng, D. (2021). Smart logistics based on the internet of things technology: an overview. International Journal of Logistics Research and Applications, 24(4), 323-345. https://doi.org/10.1080/13675567.2020.1757053
Foroughi, A. (2021). Supply chain workforce training: addressing the digital skills gap. Higher Education, Skills and Work-Based Learning, 11(3), 683-696. https://doi.org/10.1108/HESWBL-07-2020-0159
Giannakis, M., Spanaki, K., Dubey, R. (2019). A cloud-based supply chain management system: effects on supply chain responsiveness. Journal of Enterprise Information Management, 32(4), 585-607. https://doi.org/10.1108/JEIM-05-2018-0106
Gligor, D.M., Holcomb, M.C. (2012). Understanding the role of logistics capabilities in achieving supply chain agility: A systematic literature review. Supply Chain Management: An International Journal, 17(4), 438-453. https://doi.org/10.1108/13598541211246594
Hackius, N., Petersen, M. (2017). Blockchain in logistics and supply chain: trick or treat? In Digitalization in Supply Chain Management and Logistics: Smart and Digital Solutions for an Industry 4.0 Environment. Proceedings of the Hamburg International Conference of Logistics (HICL),. Berlin.
Hamidu, Z., Boachie-Mensah, F.O., Issau, K. (2023). Supply chain resilience and performance of manufacturing firms: role of supply chain disruption. Journal of manufacturing technology management, 34(3), 361-382. https://doi.org/10.1108/JMTM-08-2022-0307
Hendricks, K.B., Singhal, V.R. (2005). An Empirical Analysis of the Effect of Supply Chain Disruptions on Long-Run Stock Price Performance and Equity Risk of the Firm.” Production and Operations Management, 14(1), 35–52. https://doi.org/10.1111/j.1937-5956.2005.tb00008.x
Holling, C.A. (1973). Resilience and stability of ecological systems. Annual Review Ecological System, 4, 1-23.
Huang, M.H., Rust, R.T. (2020). Engaged to a robot? The role of AI in service, Journal of Service Research, 24 (1), 30-41. https://doi.org/10.1177/1094670520902266
Hussain, G., Nazir, M.S., Rashid, M.A., Sattar, M.A. (2023). From supply chain resilience to supply chain disruption orientation: the moderating role of supply chain complexity. Journal of Enterprise Information Management, 36(1), 70-90. https://doi.org/10.1108/JEIM-12-2020-0558
Issaoui, Y., Khiat, A., Bahnasse, A., Ouajji, H. (2019). Smart logistics: Study of the application of blockchain technology. Procedia Computer Science, 160, 266-271. https://doi.org/10.1108/JEIM-12-2020-0558
Ivan Su, S.I., Gammelgaard, B., Yang, S.L. (2011). Logistics innovation process revisited: insights from a hospital case study. International Journal of Physical Distribution & Logistics Management, 41(6), 577-600. https://doi.org/10.1108/09600031111147826
Ivanov, D. (2020). Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case. Transportation Research Part E: Logistics and Transportation Review, 136, 101922. https://doi.org/10.1016/j.tre.2020.101922
Ivanov, D., Dolgui, A. (2021). A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0. Production Planning & Control, 32(9), 775-788. https://doi.org/10.1080/09537287.2020.1768450
Ivanov, D., Dolgui, A., Sokolov, B. (2022). Cloud supply chain: Integrating Industry 4.0 and digital platforms in the “Supply Chain-as-a-Service. Transportation Research Part E: Logistics and Transportation Review, 160, 102676. https://doi.org/10.1016/j.tre.2022.102676
Jain, S., Jain, N.K., Metri, B. (2018). Strategic framework towards measuring a circular supply chain management. Benchmarking: An International Journal, 25(8), 3238-3252. https://doi.org/10.1108/BIJ-11-2017-0304
Jambol, D.D., Sofoluwe, O.O., Ukato, A., Ochulor, O.J. (2024). Transforming equipment management in oil and gas with AI-Driven predictive maintenance. Computer Science & IT Research Journal, 5(5), 1090-1112. https://doi.org/10.51594/csitrj.v5i5.1117
Javanmardi, E., Liu, S. (2019). Exploring grey systems theory-based methods and applications in analyzing socio-economic systems. Sustainability, 11(15), 4192. https://doi.org/10.3390/su11154192
Kamalahmadi, M., Parast, M.M. (2016). A Review of the Literature on the Principles of Enterprise and Supply Chain Resilience: Major Findings and Directions for Future Research. International Journal of Production Economics, 171,116–133. https://doi.org/10.1016/j.ijpe.2015.10.023
Karanam, R.K., Sachani, D.K., Natakam, V.M., Yarlagadda, V.K., Kothapalli, K.R.V. (2024). Resilient Supply Chains: Strategies for Managing Disruptions in a Globalized Economy. American Journal of Trade and Policy, 11(1), 7-16. https://doi.org/10.18034/ajtp.v11i1.719
Katsaliaki, K., Galetsi, P., Kumar, S. (2022). Supply chain disruptions and resilience: A major review and future research agenda. Annals of Operations Research, 1-38. https://doi.org/10.1007/s10479-020-03912-1
Kazancoglu, Y., Lafci, C., Berberoglu, Y., Upadhyay, A., Rocha-Lona, L., Kumar, V. (2024). The effects of globalization on supply chain resilience: Outsourcing techniques as interventionism, protectionism, and regionalization strategies. Operations Management Research, 17(2), 505-522. https://doi.org/10.1007/s12063-023-00429-1
Kim, Y., Chen, Y.S., Linderman, K. (2015). Supply network disruption and resilience: A network structural perspective. Journal of operations Management, 33, 43-59. https://doi.org/10.1016/j.jom.2014.10.006
Koh, L., Dolgui, A., Sarkis, J. (2020). Blockchain in transport and logistics–paradigms and transitions. International Journal of Production Research, 58(7), 2054-2062. https://doi.org/10.1080/00207543.2020.1736428
Lamming, R.C., Caldwell, N.D., Harrison, D.A. Phillips, W. (2001). Transparency in supply relationships: concept and practice. Journal of Supply Chain Management, 37(3), 4-10. https://doi.org/10.1111/j.1745-493X.2001.tb00107.x
Liu, S., Lin, J., Hayes, K.A. (2010). An agile and diversified supply chain: reducing operational risks. Competitiveness review: An international business journal, 20(3), 222-234. https://doi.org/10.1108/10595421011047415
Liu, S.F., Yang, Y.J., Forrest, J. (2022). Grey Systems Analysis. Springer-Verlag, Berlin. https://doi.org/10.1007/978-981-97-8727-2
Lv, Z., Qiao, L., Mardani, A., Lv, H. (2022). Digital twins on the resilience of supply chain under COVID-19 pandemic. IEEE Transactions on Engineering Management. IEEE https://doi.org/ 10.1109/TEM.2022.3195903
Makarius, E.E., Srinivasan, M. (2017). Addressing skills mismatch: Utilizing talent supply chain management to enhance collaboration between companies and talent suppliers. Business horizons, 60(4), 495-505.
Marmolejo-Saucedo, J.A. (2020). Design and development of digital twins: A case study in supply chains. Mobile Networks and Applications, 25(6), 2141-2160. https://doi.org/10.1007/s11036-020-01557-9
Mendes, L., Machado, J. (2015). Employees’ skills, manufacturing flexibility and performance: a structural equation modelling applied to the automotive industry. International Journal of Production Research, 53(13), 4087-4101. https://doi.org/10.1080/00207543.2014.993772
Min, H. (2023). Smart Warehousing as a Wave of the Future. Logistics, 7(2), 30. https://doi.org/10.3390/logistics7020030
Mishra, A., Dutta, P., Jayasankar, S., Jain, P., Mathiyazhagan, K. (2023). A review of reverse logistics and closed-loop supply chains in the perspective of circular economy. Benchmarking: an international journal, 30(3), 975-1020. https://doi.org/10.1108/BIJ-11-2021-0669
Modgil, S., Singh, R.K., Hannibal, C. (2022). Artificial intelligence for supply chain resilience: learning from Covid-19. The International Journal of Logistics Management, 33(4), 1246-1268. https://doi.org/10.1108/IJLM-02-2021-0094
Morgan, T.R., Richey Jr, R.G., Ellinger, A.E. (2018). Supplier transparency: scale development and validation. The International Journal of Logistics Management, 29(3), 959-984. https://doi.org/10.1108/IJLM-01-2017-0018
Naim, M.M., Potter, A.T., Mason, R.J., Bateman, N. (2006). The role of transport flexibility in logistics provision. The International Journal of Logistics Management, 17(3), 297-311. https://doi.org/10.1108/09574090610717491
Omsri Aeddula, Martin Frank, Ryan Ruvald, Christian Johansson Askling, Johan Wall, Tobias Larsson, (2024). AI-Driven Predictive Maintenance for Autonomous Vehicles for Product-Service System Development, Procedia CIRP, 128, 84-89. https://doi.org/10.1016/j.procir.2024.06.008
Ozkan-Ozen, Y.D., Kazancoglu, Y. (2022). Analysing workforce development challenges in the Industry 4.0. International Journal of Manpower, 43(2), 310-333. https://doi.org/10.1108/IJM-03-2021-0167
Patari, N., Venkataramanan, V., Srivastava, A., Molzahn, D.K., Li N. and Annaswamy, A., (2022) Distributed Optimization in Distribution Systems: Use Cases, Limitations, and Research Needs, IEEE Transactions on Power Systems, 37(5), 3469-3481. https://doi.org/10.1109/TPWRS.2021.3132348
Polyviou, M., Croxton, K.L., Knemeyer, A.M. (2020). Resilience of medium-sized firms to supply chain disruptions: the role of internal social capital. International Journal of Operations & Production Management, 40(1), 68-91. https://doi.org/10.1108/IJOPM-09-2017-0530
Ponomarov, S.Y., Holcomb, M.C. (2009). Understanding the concept of supply chain resilience. The international journal of logistics management, 20(1), 124-143. https://doi.org/10.1108/09574090910954873
Raja Santhi, A., Muthuswamy, P. (2022). Influence of block chain technology in manufacturing supply chain and logistics. Logistics, 6(1), 15. https://doi.org/10.3390/logistics6010015
Rui, M., Jiatai, Z. (2007). Research of hierarchy synthetic evaluation based on grey relational analysis. IEEE International Conference on Grey Systems and Intelligent Services, IEEE, Nanjing. https://doi.org/10.1109/GSIS.2007.4443243
Sahara, C.R., Aamer, A.M. (2022). Real-time data integration of an internet-of-things-based smart warehouse: a case study. International Journal of Pervasive Computing and Communications, 18(5), 622-644. https://doi.org/10.1108/IJPCC-08-2020-0113
Sawik, T. (2014). Optimization of cost and service level in the presence of supply chain disruption risks: Single vs. multiple sourcing. Computers & Operations Research, 51, 11–20.20 https://doi.org/10.1016/j.cor.2014.04.006
Schniederjans, D.G., Curado, C. Khalajhedayati, M. (2020), Supply chain digitization trends: an integration of knowledge management, International Journal of Production Economics, 220, 107439. https://doi.org/10.1016/j.ijpe.2019.07.012
Scholten, K., Schilder, S. (2015). The role of collaboration in supply chain resilience. Supply Chain Management: An International Journal, 20(4), 471-484. https://doi.org/10.1108/SCM-11-2014-0386
Sheffi, Y. (2007). The Resilient Enterprise: Overcoming Vulnerability for Competitive Advantage. MIT Press. https://www.researchgate.net/publication/23573710_The_Resilient_Enterprise_Overcoming_Vulnerability_for_Competitive_Advantage
Snyder, L.V., Atan, Z., Peng, P., Rong, Y., Schmitt, A.J., Sinsoysal, B. (2021). OR/MS models for supply chain disruptions: A review. IIE Transactions, 50(2), 89-109. https://doi.org/10.1080/0740817X.2015.1067735
Song, M., Ma, X., Zhao, X., Zhang, L. (2022). How to enhance supply chain resilience: a logistics approach. The International Journal of Logistics Management, 33(4), 1408-1436. https://doi.org/10.1108/IJLM-04-2021-0211
Song, Q., Shepperd, M. (2011). Predicting software project effort: A grey relational analysis based method. Expert Systems with Applications, 38(6), 7302-7316. https://doi.org/10.1016/j.eswa.2010.12.005
Stock, G.N., Greis, N.P., Kasarda, J.D. (2000). Enterprise logistics and supply chain structure: the role of fit. Journal of operations management, 18(5), 531-547. https://doi.org/10.1016/S0272-6963(00)00035-8
Sugimura, Y., Murakami, S. (2021). Designing a resilient international reverse logistics network for material cycles: a Japanese case study. Resources, Conservation and Recycling, 170, 105603. https://doi.org/10.1016/j.resconrec.2021.105603
Sunny, J., Undralla, N., Pillai, V.M. (2020). Supply chain transparency through block chain-based traceability: An overview with demonstration. Computers & Industrial Engineering, 150, 106895. https://doi.org/10.1016/j.cie.2020.106895
Tang, C.S. (2006). Perspectives in supply chain risk management. International Journal of Production Economics, 103(2), 451-488. https://doi.org/10.1016/j.ijpe.2005.12.006
Ünlü, R., Söylemez, İ. (2024). AI-Driven Predictive Maintenance. In Engineering Applications of AI and Swarm Intelligence. Springer Nature, Singapore. https://doi.org/10.32628/CSEIT241061118
Verdonck, L., Caris, A.N., Ramaekers, K., Janssens, G.K. (2013). Collaborative logistics from the perspective of road transportation companies. Transport Reviews, 33(6), 700-719. https://doi.org/10.1080/01441647.2013.853706
Verma, P. (2024). AI-Driven Predictive Analytics for Supply Chain Risk Management. MZ Journal of Artificial Intelligence, 1(2), 1-12.
Wagner, S.M., Bode, C. (2008). An empirical examination of supply chain performance along several dimensions of risk. Journal of Business Logistics, 29(1), 307–325. https://doi.org/10.1002/j.2158-1592.2008.tb00081.x
Wang, Y., Wang, X., Liu, A. (2020). Digital twin-driven supply chain planning. Procedia Cirp, 93, 198-203. https://doi.org/10.1016/j.procir.2020.04.154
Wei, G.W. (2011). Gray relational analysis method for intuitionistic fuzzy multiple attribute decision making. Expert systems with Applications, 38(9), 11671-11677.https://doi.org/10.1016/j.eswa.2011.03.048
Wilson, M., Paschen, J., Pitt, L. (2022). The circular economy meets artificial intelligence (AI): Understanding the opportunities of AI for reverse logistics. Management of Environmental Quality: An International Journal, 33(1), 9-25. https://doi.org/10.1108/MEQ-10-2020-0222
Xu, P., Lee, J., Barth, J.R., Richey, R.G. (2021). Block chain as supply chain technology: considering transparency and security. International Journal of Physical Distribution & Logistics Management, 51(3), 305-324. https://doi.org/10.1108/IJPDLM-08-2019-0234
Yu, W., Jacobs, M.A., Chavez, R., Yang, J. (2019). Dynamism, disruption orientation, and resilience in the supply chain and the impacts on financial performance: A dynamic capabilities perspective. International Journal of Production Economics, 218, 352-362. https://doi.org/10.1016/j.ijpe.2019.07.013
Zadeh, L.A. (1973). Outline of a new approach to the analysis of complex systems and decision processes. IEEE Transactions on systems, Man, and Cybernetics, IEEE. (1), 28-44. https://doi.org/10.1109/TSMC.1973.5408575
Zaidi, S.A.H., Khan, S.A., Chaabane, A. (2024). Unlocking the potential of digital twins in supply chains: A systematic review. Supply Chain Analytics,7, 100075. https://doi.org/10.1016/j.sca.2024.100075
Zimon, D., Madzik, P., Sroufe, R. (2020). Management systems and improving supply chain processes: Perspectives of focal companies and logistics service providers. International Journal of Retail & Distribution Management, 48(9), 939-961. https://doi.org/10.1108/IJRDM-04-2019-0107
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