Articles
| Open Access | Integrating Agility, Digital Intelligence, and Sustainable Urban Logistics: A Comprehensive Framework for Resilient Modern Supply Chains
Dr. Elena Martínez , Universidad Autónoma de Madrid, SpainAbstract
Background: Modern supply chains operate within an environment characterized by volatility, complexity, and rapid technological change. Building supply chains that are simultaneously agile, resilient, and digitally intelligent has become an imperative across industries ranging from air cargo operations to last-mile urban deliveries (Christopher, 2000; Bombelli & Fazi, 2022). The literature contains rich but fragmented contributions on discrete elements — agility taxonomies, digital enablement, sustainable modal shifts, and empirical datasets for automation — yet a unified theoretical and operational framework that ties these elements into implementable pathways is lacking (Christopher, 2000; Costantino et al., 2012; Bamakan et al., 2021).
Methods: This paper synthesizes heterogeneous sources spanning empirical case studies, methodological contributions to agile development, technological frameworks integrating blockchain-IoT-big data, and context-specific innovations such as cargo bicycles and perpetual motion electric trucks. Using a rigorous integrative literature synthesis approach — combining conceptual mapping, comparative analysis of empirical case studies, and cross-domain theoretical elaboration — the study derives a multi-layered framework aligning strategy, operations, and digital infrastructure to support sustainable, resilient, and agile supply chains (Christopher, 2000; Bamakan et al., 2021; Gonzalez-Calderon et al., 2022).
Results: The resulting framework delineates (1) strategic principles for agility and Triple-A alignment (agility, adaptability, alignment), (2) operational modules for warehousing and last-mile logistics that embed human-in-the-loop and automated capabilities, (3) a digital intelligence stack comprising sensing, secure data fabric (blockchain), analytics, and decision automation, and (4) sustainability vectors that reconcile carbon reduction with service-level objectives through modal innovations and energy-efficient vehicle technologies (de Boer, 2018; Bamakan et al., 2021; Hunt et al., 2023; Gonzalez-Calderon et al., 2022). The framework further articulates measurement constructs and key performance indicators that balance responsiveness, cost, and environmental impact (Costantino et al., 2012; Balaji et al., 2015).
Conclusions: Integrating agility and digital intelligence provides robust pathways to resilient, low-carbon supply chains. Operationalizing this integration requires deliberate investments in data interoperability, human-centered automation in warehousing, and policy-aligned adoption of sustainable transport modes. The paper concludes with prioritized research agendas and practical implementation guidelines for managers and policymakers to accelerate transition toward agile, digitally-enabled, and sustainable supply networks (Christopher et al., 2006; Bamakan et al., 2021; Chowdhury, 2025).
Keywords
Agile supply chain, digital intelligence, resilience, sustainable logistics, last-mile delivery, warehousing
References
Bombelli, A., & Fazi, S. (2022). The ground handler dock capacitated pickup and delivery problem with time windows: A collaborative framework for air cargo operations. Transportation Research Part E: Logistics and Transportation Review, 159. https://doi.org/10.1016/j.tre.2022.102603
Camacho-Muñoz, G. A., Franco, J. C. M., Nope-Rodríguez, S. E., Loaiza-Correa, H., Gil-Parga, S., & Álvarez-Martínez, D. (2023). 6D-ViCuT: Six degree-of-freedom visual cuboid tracking dataset for manual packing of cargo in warehouses. Data in Brief, 49. https://doi.org/10.1016/j.dib.2023.109385
Gonzalez-Calderon, C. A., Posada-Henao, J. J., Granada-Muñoz, C. A., Moreno-Palacio, D. P., & Arcila-Mena, G. (2022). Cargo bicycles as an alternative to make sustainable last-mile deliveries in Medellin, Colombia. Case Studies on Transport Policy, 10(2), 1172–1187. https://doi.org/10.1016/j.cstp.2022.04.006
Hasan, R., Ta, A.-, & Razali, R. (2013). Prioritizing Requirements in Agile Development : A Conceptual Framework. Procedia Technology, 11(Iceei), 733–739. https://doi.org/10.1016/j.protcy.2013.12.252
Humpert, L., Röhm, B., Anacker, H., Dumitrescu, R., & Anderl, R. (2022). Method for direct end customer integration into the agile product development. Procedia CIRP, 109, 215–220. https://doi.org/10.1016/j.procir.2022.05.239
Hunt, J. D., Nascimento, A., Tong, W., Zakeri, B., Jurasz, J., Patro, E. R., Ðurin, B., de Jesus Pacheco, D. A., de Freitas, M. A. V., Filho, W. L., & Wada, Y. (2023). Perpetual motion electric truck, transporting cargo with zero fuel costs. Journal of Energy Storage, 72. https://doi.org/10.1016/j.est.2023.108671
Balaji, M., Velmurugan, V., & Subashree, C. (2015). OriginalTADS: An assessment methodology for agile supply chains. Journal of Applied Research and Technology, 13, 504-509. https://doi.org/10.1016/j.jart.2015.10.002
Bamakan, S. M. H., Faregh, N., & ZareRavasan, A. (2021). Di-ANFIS: An integrated blockchain-IoT-big dataenabled framework for evaluating service supply chain performance. Journal of Computational Design and Engineering, 8(2), 676-690. https://doi.org/10.1093/jcde/qwab007
Ben Ruben, R., Prasanth, A. S., Ramesh, R., & Narendran, S. A. P. (2013, February). Implementation study on apply agile supply chain paradigm in the manufacturing of a conventional automobile horn in an Indian company. International Journal of Materials, Mechanics, and Manufacturing, 1(1), 97-101. https://doi.org/10.7763/IJMMM.2013.V1.21
Chowdhury, W. A. (2025). Agile, IoT, and AI: Revolutionizing Warehouse Tracking and Inventory Management in Supply Chain Operations. Journal of Procurement and Supply Chain Management, 4(1), 41–47. https://doi.org/10.58425/jpscm.v4i1.349
Berger, P. (2022, November 29). Amazon launches supply-chain software service. The Wall Street Journal. Dow Jones Institutional News. https://usf-flvc.primo.exlibrisgroup.com/permalink/01FALSC_USF/un0hgn/cdi_proquest_wirefeeds_2741162830
Brin, D. W. (2013, February 12). Companies make supply chains more agile with better visibility. MHI.org. https://www.mhi.org/media/news/12203
Christopher, M. (2000, January). The agile supply chain: Competing in volatile markets. Industrial Marketing Management, 29(1), 37-44. https://doi.org/10.1016/S0019-8501(99)00110-8
Christopher, M., Peck, H., & Towill, D. (2006). A taxonomy for selecting global supply chain strategies. The International Journal of Logistics Management, 17(2), 277-287. https://doi.org/10.1108/09574090610689998
Costantino, N., Dotoli, M., Falagario, M., Fanti, M. P., & Mangini, A. M. (2012). A model for supply management of agile manufacturing supply chains. International Journal of Production Economics, 135(1), 451-457. https://doi.org/10.1016/j.ijpe.2011.08.021
de Boer, T. (2018, September 3). Building a Triple A supply chain: Ten tactics that work [Web log]. https://www.tradecloud1.com/en/building-a-triple-a-supply-chain-ten-tactics-that-work/
Deconinck, K., Avery, E., & Jackson, L. A. (2020). Food supply chains and Covid‐19: Impacts and policy lessons. EuroChoices, 19(3), 34–39. https://doi.org/10.1111/1746-692X.12297
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