Evaluating Disruption Management Strategies for Freight Logistics in Oman: A Simulation Modeling Approach

Document Type : Original Research Article

Authors

1 Assistant Prof., Faculty of Transport and Logistics, Muscat University, Muscat, Oman.

2 Ph.D. Department of Industrial Management, Senior Lecturer at the University of Tehran, Kish, Iran.

3 Ph.D Candidate, Department of Industrial Management, College of Management, University of Tehran, Tehran, Iran.

4 Ph.D Candidate, Faculty of Management and Economic, University of Guilan, Rasht, Iran.

10.22059/imj.2026.412049.1008296

Abstract

Objective: The logistics and transportation networks in the GCC, particularly in Oman, face unique problems due to the region's geographical complexity, the value of transported goods, and the significance of timely deliveries. Operating in a highly competitive environment, businesses in this industry are compelled to reduce waste, save unnecessary expenditures, and maintain consistent delivery standards while dealing with disruptions that may severely disrupt operations.
Methodology: Our research aims to apply scenario planning-based simulation modelling to examine the effects of disruptions on freight logistics and transportation performance in Oman, with two goals in mind: first, to assess the financial and operational consequences of disruptions, and second, to devise and evaluate proactive and reactive measures aimed at maintaining good service levels to avoid supply shortages. Disruptions in freight logistics and transportation have profound consequences, prompting a deliberate shift to create resilient and flexible networks.
Results: Our findings highlight the effectiveness of activating backup transportation routes in reducing expanded disruptions, while laterally enabling transshipment appears as a viable approach for smaller-scale, short-term disruptions, although with a marginal cost increase.
Conclusion: By implementing these tactics, Oman's logistics and transportation industries can successfully mitigate disruptions in freight logistics and maintain the smooth flow of commodities throughout the region. Additionally, policy-level support for digital transformation and infrastructure development is essential for enabling long-term logistics competitiveness.

Keywords

Main Subjects


 Abbasi, M., & Nilsson, F. (2016). Developing environmentally sustainable logistics: Exploring themes and challenges from a logistics service providers’ perspective. Transportation Research Part D: Transport and Environment46, 273-283. https://doi.org/10.1016/j.trd.2016.04.004
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. Logistics5(4), 84. https://doi.org/10.3390/logistics5040084
Agarwal, M. , G. R. , & T. S. (2018). Political instability and supply chain performance: Evidence from the apparel industry. Production and Operations Management, 27(8), 1637–1656.
Agostinelli, S., Cumo, F., Nezhad, M. M., Orsini, G., & Piras, G. (2022). Renewable energy system controlled by open-source tools and digital twin model: zero energy port area in Italy. Energies15(5), 1817. https://doi.org/10.3390/en15051817
Al Hosni, S., Tabrizi, S. S., Babazadeh, R., & Kamran, M. A. (2026, May). Evaluating the Risk of Storing and Transporting the Hydrogen Energy in Oman Using Multi-Criteria Decision Making. In 2026 IEEE 6th International Conference in Power Engineering Applications (ICPEA) (pp. 40-48). IEEE. https://doi.org/10.1109/ICPEA69349.2026.11533721
Al Mazroui, T. S. S., Al Alawi, M. M. S., Al Wahaibi, K. S. H., Al Amri, B. B. S., & Thottoli, M. M. (2023). Maturity of digital transformation in the shipping industry: a case study among enterprises in Gulf Cooperation Council (GCC) countries. Kapal: Jurnal Ilmu Pengetahuan dan Teknologi Kelautan20(1), 115-123. https://doi.org/10.14710/kapal.v20i1.51246
Al-Hanahi, B., Ahmad, I., Habibi, D., & Masoum, M. A. (2021). Charging infrastructure for commercial electric vehicles: Challenges and future works. Ieee Access9, 121476-121492. https://doi.org/10.1109/ACCESS.2021.3108817
Alkahtani, M. (2022). Mathematical modelling of inventory and process outsourcing for optimization of supply chain management. Mathematics10(7), 1142. https://doi.org/10.3390/math10071142
AlShaer, M., Taher, Y., Haque, R., Hacid, M. S., & Dbouk, M. (2019). IBRIDIA: A hybrid solution for processing big logistics data. Future Generation Computer Systems97, 792-804. https://doi.org/10.1016/j.future.2019.02.044
Alsudani, M. Q., Jaber, M. M., Ali, M. H., Abd, S. K., Alkhayyat, A., Kareem, Z. H., & Mohhan, A. R. (2023). RETRACTED ARTICLE: Smart logistics with IoT-based enterprise management system using global manufacturing. Journal of combinatorial optimization45(2), 57. https://doi.org/10.1007/s10878-023-01033-6
Arkhipov, A., & Maslennikov, S. (2021, May). Energy Efficiency of Integrated Transport and Logistics Systems. In International Scientific Siberian Transport Forum (pp. 921-929). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-96383-5_102
Asif, M., Chhetri, P., & Padhye, R. (2019). Do political disruptions affect supply chain performance? A qualitative case study of the textile supply chain in Pakistan. Journal of International Logistics and Trade17(3), 77-88. https://doi.org/10.24006/jilt.2019.17.3.002
Asyad. (2021, November 30). Asyad Paves The Way For A Globally Competitive Logistics Sector In Oman. Asyad.
Atasever, M., & Köse, B. (2023). COMPARISON OF VIRTUAL AND TRADITIONAL PRODUCTS IN THE CONTEXT OF LOGISTICS. Uşak Üniversitesi Sosyal Bilimler Dergisi16(1), 1-14. https://izlik.org/JA79PZ99MP
Ates, A. , K. S. , & U. A. (2019). The impact of changes in regulations on automotive supply chains: Evidence from the USA and Mexico. International Journal of Physical Distribution & Logistics Management, 49(7/8), 513–530.
Attaran, M. (2020, July). Digital technology enablers and their implications for supply chain management. In Supply chain forum: an international journal (Vol. 21, No. 3, pp. 158-172). Taylor & Francis. https://doi.org/10.1080/16258312.2020.1751568
Bahadoran, M., Fadaei Ashkiki, M., Taleghani, M., & Homayounfar, M. (2022). Designing a resilient closed-loop supply chain network under operational risk and disruption conditions by the Mulvey approach. Industrial Management Journal. https://doi.org/10.22059/imj.2022.336976.1007909
Balushi, R. A., Ajmi, K. A., & Srinivas, S. (2019). Study of Factors Influencing Green Logistics Leading towards Sustainable Development in Oman. Big Data & Smart City, 31. https://www.academia.edu/download/110450489/JBDSC
Becker, T., Illigen, C., McKelvey, B., Hülsmann, M., & Windt, K. (2016). Using an agent-based neural-network computational model to improve product routing in a logistics facility. International Journal of Production Economics174, 156-167. https://doi.org/10.1016/j.ijpe.2016.01.003
Bibri, S. E., Krogstie, J., Kaboli, A., & Alahi, A. (2024). Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review. Environmental science and ecotechnology19, 100330. https://doi.org/10.1016/j.ese.2023.100330
Büyüközkan, G., & Göçer, F. (2018). Digital Supply Chain: Literature review and a proposed framework for future research. Computers in industry97, 157-177. https://doi.org/10.1016/j.compind.2018.02.010
Calabrò, G., Le Pira, M., Giuffrida, N., Fazio, M., Inturri, G., & Ignaccolo, M. (2023). A spatial agent-based model of e-commerce last-mile logistics towards a delivery-oriented development. Transportation Research Interdisciplinary Perspectives21, 100895. https://doi.org/10.1016/j.trip.2023.100895
Callinan, C., Vega, A., Clohessy, T., & Heaslip, G. (2023). Blockchain, Supply Chain and Adoption: A Bibliometric Analysis. In Blockchain in Supply Chain Digital Transformation (pp. 122-142). CRC Press. https://www.taylorfrancis.com/books/ 
Cao, J., & C. X. (2018). The impact of road transportation disruptions on supply chain management of manufacturing industries in China. Journal of Manufacturing Systems, 49, 1–12.
Chen, H. Y., Das, A., & Ivanov, D. (2019). Building resilience and managing post-disruption supply chain recovery: Lessons from the information and communication technology industry. International Journal of Information Management49, 330-342. https://doi.org/10.1016/j.ijinfomgt.2019.06.002
Clausen, U., De Bock, J., & Lu, M. (2015). Logistics trends, challenges, and needs for further research and innovation. In Sustainable Logistics and Supply Chains: Innovations and Integral Approaches (pp. 1-13). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-17419-8_1
Corrado, C. R., DeLong, S. M., Holt, E. G., Hua, E. Y., & Tolk, A. (2022). Combining green metrics and digital twins for sustainability planning and governance of smart buildings and cities. Sustainability14(20), 12988. https://doi.org/10.3390/su142012988
Daskin, M. S., Snyder, L. V., & Berger, R. T. (2005). Facility location in supply chain design. In Logistics systems: Design and optimization (pp. 39-65). Boston, MA: Springer US. https://doi.org/10.1007/0-387-24977-X_2
Delgado, J. M. D., & Oyedele, L. (2021). Digital Twins for the built environment: learning from conceptual and process models in manufacturing. Advanced Engineering Informatics49, 101332. https://doi.org/10.1016/j.aei.2021.101332
Fortino, G., & Savaglio, C. (2023). Integration of digital twins & internet of things. In The digital twin (pp. 205-225). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-031-21343-4_8
Gani, A. (2017). The logistics performance effect in international trade. The Asian journal of shipping and logistics33(4), 279-288. https://doi.org/10.1016/j.ajsl.2017.12.012
Ghadami, A., Abdsharafat, M., Rostamzadeh, R., & Isavi, H. (2026). AI-powered supply chains: Mapping the future of resilience and sustainability. Industrial Management Journal. https://doi.org/10.22059/imj.2026.410606.1008286
Gheysari, M., & Tehrani, M. S. S. (2022). The Role of Multi-Agent Systems in IoT. In Multi Agent Systems: Technologies and Applications towards Human-Centered (pp. 87-114). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-19-0493-6_5
Groten, M., & Gallego-García, S. (2021). A systematic improvement model to optimize production systems within industry 4.0 environments: A simulation case study. Applied Sciences11(23), 11112. https://doi.org/10.3390/app112311112
Guan, Z., Tao, J., & Sun, M. (2022). Integrated optimization of resilient supply chain network design and operations under disruption risks. In Supply chain risk mitigation: Strategies, methods and applications (pp. 205-238). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-031-09183-4_10
Gumzej, R. (2021). Intelligent Logistics Systems. In Intelligent Logistics Systems for Smart Cities and Communities (pp. 89-100). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-81203-4_11
Gupta, A., Singh, R., & Suri, P. (2018). Analysis of Challenges Faced by Indian Logistics Service Providers. Operations and Supply Chain Management: An International Journal, 11(4), 214-225. https://doi.org/10.31387/oscm0350215
Hakanen, J. , G. M. , G. F. , & L. T. (2011). The impact of transportation flow disruptions on automotive supply chain performance. . Transportation Research Part E: Logistics and Transportation Review, 47(4), 542–556.
Hamed Al-Wahaibi, M. H. (2019). Logistics hubs in Oman and political uncertainty in the Gulf. Contemporary Review of the Middle East6(2), 109-153. https://doi.org/10.1177/2347798919832694
Han, C., & Zhang, Q. (2021). Optimization of supply chain efficiency management based on machine learning and neural network. Neural Computing and Applications33(5), 1419-1433. https://doi.org/10.1007/s00521-020-05023-1
Hao, Y., W. M., & L. X. (2017). Supply chain disruption caused by transportation issues in the automotive industry in China. International Journal of Production Research, 1318–1336.
He, L., Xue, M., & Gu, B. (2020). Internet-of-things enabled supply chain planning and coordination with big data services: Certain theoretic implications. Journal of Management Science and Engineering5(1), 1-22. https://doi.org/10.1016/j.jmse.2020.03.002
Helo, P., & Shamsuzzoha, A. H. M. (2020). Real-time supply chain—A blockchain architecture for project deliveries. Robotics and Computer-Integrated Manufacturing63, 101909. https://doi.org/10.1016/j.rcim.2019.101909
Hou, H., Chaudhry, S., Chen, Y., & Hu, M. (2017). Physical distribution, logistics, supply chain management, and the material flow theory: a historical perspective. Information Technology and Management18(2), 107-117. https://doi.org/10.1007/s10799-015-0229-1
Huang, Y. (2017). Impact of regulatory changes on automo tive supply chain management.. International Journal of Production Economics, ,191, 136–146.
İmre, Ş., Celebi, D., & Koca, F. (2021). Understanding barriers and enablers of electric vehicles in urban freight transport: Addressing stakeholder needs in Turkey. Sustainable Cities and Society68, 102794. https://doi.org/10.1016/j.scs.2021.102794
Ivanov, D. (2021). Digital supply chain management and technology to enhance resilience by building and using end-to-end visibility during the COVID-19 pandemic. IEEE Transactions on Engineering Management71, 10485-10495. https://ieeexplore.ieee.org/abstract/document/9495948/
Jagtap, S., Bader, F., Garcia-Garcia, G., Trollman, H., Fadiji, T., & Salonitis, K. (2020). Food logistics 4.0: Opportunities and challenges. Logistics5(1), 2. https://doi.org/10.3390/logistics5010002
Kanike, U. K. (2023). Factors disrupting supply chain management in manufacturing industries. Journal of Supply Chain Management Science4(1-2), 1-24. https://doi.org/10.18757/jscms.2023.6986
Kern, J. (2021). The digital transformation of logistics: A review about technologies and their implementation status. The digital transformation of logistics: Demystifying impacts of the fourth industrial revolution, 361-403. https://doi.org/10.1002/9781119646495.ch25
Khanfar, A. A., Iranmanesh, M., Ghobakhloo, M., Senali, M. G., & Fathi, M. (2021). Applications of blockchain technology in sustainable manufacturing and supply chain management: A systematic review. Sustainability13(14), 7870. https://doi.org/10.3390/su13147870
Khedkar, P. , & B. A. (2019). Investigating the impact of transportation disruptions on supply chain management of the automotive industry. International Journal of Logistics Systems and Management, 32(2), 215-230.
Kuehn, W. (2018). Digital twins for decision making in complex production and logistic enterprises. https://doi.org/10.2495/DNE-V13-N3-260-271
Li, D., Cao, Q., Zuo, M., & Xu, F. (2020). Optimization of green fresh food logistics with heterogeneous fleet vehicle route problem by improved genetic algorithm. Sustainability12(5), 1946. https://doi.org/10.3390/su12051946
Li, L., & Zhang, X. (2020). Integrated optimization of railway freight operation planning and pricing based on carbon emission reduction policies. Journal of Cleaner Production263, 121316. https://doi.org/10.1016/j.jclepro.2020.121316
Liu, Z., & Warner, M. E. (2019). Multilevel governance: Framing the integration of top-down and bottom-up policymaking. International Journal of Public Administration42(7), 572-582. https://doi.org/10.1080/01900692.2018.1491597
Magnanti, T. L., & Wong, R. T. (1984). Network design and transportation planning: Models and algorithms. Transportation science18(1), 1-55. https://doi.org/10.1287/trsc.18.1.1
Mehrotra, V., K. S., & M. S. (2019). The effect of political instability on supply chain performance: Evidence from the Latin American automotive industry. International Journal of Production Economics, 207, 118–135.
Meixell, M. J., & Gargeya, V. B. (2005). Global supply chain design: A literature review and critique. Transportation Research Part E: Logistics and Transportation Review41(6), 531-550. https://doi.org/10.1016/j.tre.2005.06.003
Mellor, J. A. , C. C. , & O. M. (2020). Healthcare supply chain disruption risk due to transportation issues. International Journal of Physical Distribution & Logistics Management, 50(9), 826–842. https://doi.org/10.3390/ijerph15081651
Minerva, R., Lee, G. M., & Crespi, N. (2020). Digital twin in the IoT context: A survey on technical features, scenarios, and architectural models. Proceedings of the IEEE108(10), 1785-1824. https://doi.org/10.1109/JPROC.2020.2998530
Mohamed, A. E. (2024). Inventory management. In Operations Management-Recent Advances and New Perspectives. IntechOpen. https://doi.org/10.5772/intechopen.113282
Mokhnenko, A., Babenko, V., Naumov, O., Perevozova, I., & Fedorchuk, O. (2020, October). Mathematical-Logistic Model of Integrated Production Structure of Food Production. In ICTERI Workshops (pp. 446-454). https://CEUR-WS.org/vol-2732/20200446.pdf
Moosavi, J., Fathollahi-Fard, A. M., & Dulebenets, M. A. (2022). Supply chain disruption during the COVID-19 pandemic: Recognizing potential disruption management strategies. International Journal of Disaster Risk Reduction75, 102983. https://doi.org/10.1016/j.ijdrr.2022.102983
Morenza-Cinos, M., Casamayor-Pujol, V., & Pous, R. (2019). Stock visibility for retail using an RFID robot. International Journal of Physical Distribution & Logistics Management49(10), 1020-1042. https://doi.org/10.1108/IJPDLM-03-2018-0151
Mostafa, N., Hamdy, W., & Alawady, H. (2019). Impacts of internet of things on supply chains: a framework for warehousing. Social sciences8(3), 84. https://doi.org/10.3390/socsci8030084
Mozafari Mehr, M. S., & Taghavifard, M. T. (2024). Designing and Modeling Digital Transformation in the Automotive Industry: Leveraging the Fourth Industrial Revolution. Industrial Management Journal16.‎ https://doi.org/10.22059/imj.2024.373674.1008135
Muñoz-Torres, M. J., Fernández-Izquierdo, M. Á., Rivera-Lirio, J. M., Ferrero-Ferrero, I., Escrig-Olmedo, E., Gisbert-Navarro, J. V., & Marullo, M. C. (2018). An assessment tool to integrate sustainability principles into the global supply chain. Sustainability10(2), 535. https://doi.org/10.3390/su10020535
Nguyen, H., S. J., & G. Y. (2017. (2017). The impact of political instability on supply chain performance: Evidence from Sub-Saharan Africa. International Journal of Production Economics, 188, 335–348.
Niaz, M. (2022). Revolutionizing inventory planning: Harnessing digital supply data through digitization to optimize storage efficiency pre-and post-pandemic. BULLET: Jurnal Multidisiplin Ilmu1(03), 592273. https://journal.mediapublikasi.id/index.php/bullet
Peng, P., Snyder, L. V., Lim, A., & Liu, Z. (2011). Reliable logistics networks design with facility disruptions. Transportation Research Part B: Methodological45(8), 1190-1211. https://doi.org/10.1016/j.trb.2011.05.022
Perboli, G., Musso, S., & Rosano, M. (2018). Blockchain in logistics and supply chain: A lean approach for designing real-world use cases. Ieee Access6, 62018-62028. https://doi.org/10.1109/ACCESS.2018.2875782
Petratos, P. N., Ljepava, N., & Salman, A. (2020). Blockchain technology, sustainability and business: A literature review and the case of Dubai and UAE. Sustainable Development and Social Responsibility—Volume 1: Proceedings of the 2nd American University in the Emirates International Research Conference, AUEIRC’18–Dubai, UAE 2018, 87–93. https://doi.org/10.1007/978-3-030-32922-8_7
Rahman, N. S. F. A., Hamid, A. A., Lirn, T. C., Al Kalbani, K., & Sahin, B. (2022). The adoption of industry 4.0 practices by the logistics industry: A systematic review of the gulf region. Cleaner Logistics and Supply Chain5, 100085. https://doi.org/10.1016/j.clscn.2022.100085
Rahmani Meybodi, F., Alem Tabriz, A., Zandiyeh, M., & Talebi, D. (2024). Designing a resilient three-level intertwined supply network under disruption and uncertainty. Industrial Management Journal. https://doi.org/10.22059/imj.2024.381366.1008177
Rasheed, A., San, O., & Kvamsdal, T. (2019). Digital twin: Values, challenges and enablers. arXiv preprint arXiv:1910.01719. https://doi.org/10.48550/arXiv.1910.01719
Reynolds, S. (2024). Delving into the adoption of blockchain technology in supply chain management. doi: https://doi.org/10.20944/preprints202406.0481.v1
Sayardoost Tabrizi, S., Abideen, A. Z., & Moeini, A. (2025). A novel machine learning and DNDEA framework for sustainable efficiency measurement in a circular two-stage supply chain. International Journal of Logistics Research and Applications, 1-22. https://doi.org/10.1080/13675567.2025.2554826
Sayardoost Tabrizi, S., Yakideh, K., Moradi, M., & Ebrahimpour, M. (2025). Clustering with machine learning and using NDEA in development planning: A case study in the petrochemical two-stage SSC. International journal of research in industrial engineering14(2), 355-384. https://doi.org/10.22105/riej.2024.455576.1443
Sayardoost Tabrizi,S , Yakideh,K , Moradi,M and Ebrahimpour,M . (2024). Assessing Sustainability of Supply Chain Performance using Machine Learning and Network Data Envelopment Analysis. Iranian journal of management sciences19(74), 109-145. doi: https://doi.org/100/jiams.2024.8805.7702
Shen, T., & Li, B. (2024). Digital twins in additive manufacturing: a state-of-the-art review. The International Journal of Advanced Manufacturing Technology131(1), 63-92. https://doi.org/10.1007/s00170-024-13092-y
Sherimon, V., Sherimon, P. C., & Ismaeel, A. (2020). JobChain: An integrated blockchain model for managing job recruitment for ministries in Sultanate of Oman. International Journal of Advanced Computer Science and Applications11(2). http://www.ijacsa.thesai.org/
Shirazi, H., Kia, R., & Ghasemi, P. (2021). A stochastic bi-objective simulation–optimization model for plasma supply chain in case of COVID-19 outbreak. Applied Soft Computing112, 107725. https://doi.org/10.1016/j.asoc.2021.107725
Sibanda, K., Hove-Sibanda, P., & Mukarumbwa, P. (2018). Greening up in logistics: Managerial perceptions of small and medium-sized enterprises on sustainability in Zimbabwe. TD: The Journal for Transdisciplinary Research in Southern Africa14(1), 1-13. https://hdl.handle.net/10520/EJC-14aa81b464
Singh, S., Kumar, R., Panchal, R., & Tiwari, M. K. (2021). Impact of COVID-19 on logistics systems and disruptions in food supply chain. International journal of production research59(7), 1993-2008. https://doi.org/10.1080/00207543.2020.1792000
Tabrizi, S. S., Yousefi, S., & Yakideh, K. (2025). Forecasting efficiency of two-stage Petrochemical sustainable supply chains using Deep Learning and DNDEA Model. Operations Research Perspectives, 100354. https://doi.org/10.1016/j.orp.2025.100354
Taj, S., Imran, A. S., Kastrati, Z., Daudpota, S. M., Memon, R. A., & Ahmed, J. (2023). IoT-based supply chain management: A systematic literature review. Internet of Things24, 100982. https://doi.org/10.1016/j.iot.2023.100982
Tan, W. C., & Sidhu, M. S. (2022). Review of RFID and IoT integration in supply chain management. Operations Research Perspectives9, 100229. https://doi.org/10.1016/j.orp.2022.100229
Tiglao, N. C. C., De Veyra, J. M., Tolentino, N. J. Y., & Tacderas, M. A. Y. (2020). The perception of service quality among paratransit users in Metro Manila using structural equations modelling (SEM) approach. Research in Transportation Economics83, 100955. https://doi.org/10.1016/j.orp.2022.100229
Times of Oman. (2021, November 30). Asyad Group paves way for globally competitive logistics sector in Oman. Times of Oman Newspaper .
Toufighi, S. P., Saberifard, N., & Vang, J. (2026). Relief logistics network design for facility location and flow allocation under environmental considerations. Industrial Management Journal. https://doi.org/10.22059/imj.2026.409518.1008281
Trivedi, A., Sohal, A., Joshi, S., & Sharma, M. (2021). A two-stage optimization model for tactical planning in fresh fruit supply chains: A case study of Kullu, India.  https://www.sid.ir/paper/668335/en
Vostriakova, V., Kononova, O., Kravchenko, S., Ruzhytskyi, A., & Sereda, N. (2021). Optimization of agri-food supply chain in a sustainable way using simulation modeling. International Journal of Computer Science & Network Security21(3), 245-256. https://doi.org/10.22937/IJCSNS.2021.21.3.33
Wang, K. (2016, November). Logistics 4.0 solution-new challenges and opportunities. In 6th international workshop of advanced manufacturing and automation (pp. 68-74). Atlantis Press. https://doi.org/10.2991/iwama-16.2016.13
Wang, X., Kumar, V., Kumari, A., & Kuzmin, E. (2022). Impact of digital technology on supply chain efficiency in manufacturing industry. In Digital transformation in industry: Digital twins and new business models (pp. 347-371). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-94617-3_25
Wei, F., Alias, C., & Noche, B. (2019). Applications of digital technologies in sustainable logistics and supply chain management. In Innovative logistics services and sustainable lifestyles: Interdependencies, transformation strategies and decision making (pp. 235-263). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-98467-4_11
Winkelhaus, S., & Grosse, E. H. (2020). Logistics 4.0: a systematic review towards a new logistics system. International journal of production research58(1), 18-43. https://doi.org/10.1080/00207543.2019.1612964
Wu, J., & Wang, P. (2021). Post-disruption performance recovery to enhance resilience of interconnected network systems. Sustainable and Resilient Infrastructure6(1-2), 107-123. https://doi.org/10.1080/23789689.2019.1710073
Wu, L., Yue, X., Jin, A., & Yen, D. C. (2016). Smart supply chain management: a review and implications for future research. The international journal of logistics management27(2), 395-417. https://doi.org/10.1108/IJLM-02-2014-0035
Wu, M. Y., Ke, C. K., & Lai, S. C. (2022). Optimizing the routing of urban logistics by context-based social network and multi-criteria decision analysis. Symmetry14(9), 1811. https://doi.org/10.3390/sym14091811
Wu, W., Cheung, C., Lo, S. Y., Zhong, R. Y., & Huang, G. Q. (2020). An iot-enabled real-time logistics system for a third party company: A case study. Procedia Manufacturing49, 16-23. https://doi.org/10.1016/j.promfg.2020.06.005
Xu, Z., Elomri, A., Kerbache, L., & El Omri, A. (2020). Impacts of COVID-19 on global supply chains: Facts and perspectives. IEEE engineering management review48(3), 153-166. https://ieeexplore.ieee.org/abstract/document/9174793/
Zhao, P., Liu, J., Jing, X., Tang, M., Sheng, S., Zhou, H., & Liu, X. (2020). The modeling and using strategy for the digital twin in process planning. IEEE Access8, 41229-41245. https://doi.org/10.1109/ACCESS.2020.2974241
Zielske, M., & Held, T. (2021). Application of agile methods in traditional logistics companies and logistics startups: Results from a German Delphi Study. Journal of Systems and Software177, 110950. https://doi.org/10.1016/j.jss.2021.110950