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LOGISTICS CONFERENCE - 2026JOURNAL“A Thriving Nation, A Beautiful Life”‘Clean Logistics 2030: Advancing end-to-end Logistics Excellence inSri Lanka through Digital Advancement, Green Transformation and Transparent Supply Chain Governance’
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Naval & Maritime Academy Logistics Conference - 2026VEDITORIAL BOARDChief EditorCdr (S) WAS Bandula, USP, psc, MSc (D&SS), MSc in Mil Studies, BNavalSt (Logistics Mgt) Hons, SMACEditorial CommitteeLCdr (E) SABJ SenadeeraLCdr (S) CS SerasingheLCdr (IT) KAUK HettiarachchiLCdr KAB SarudinDesign and Setting LCdr (S) CS SerasingheLCdr (IT) KAUK HettiarachchiLIT SM JuryIT HMSPW HerathPublications Naval & Maritime Academy,SLN Dockyard,Trincomalee,Sri Lanka. ISSN No. 2550 - 3197All rights reserved
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Naval & Maritime Academy Logistics Conference - 2026VIILOGISTICS CONFERENCE - 2026 JOURNALThe Logistics Conference 2026 Journal is published as an integral part of the Logistics Conference, scheduled for 23rd May 2026 at the Naval & Maritime Academy (NMA), Trincomalee. The Conference is jointly organized by the Sri Lanka Navy Logistics Branch, the Faculty of the Naval & Maritime Academy, and the graduating Officers of the Long Logistics Management Course (LLMC) No. 10. Course Participants of LLMC have played a significant role in organizing this prestigious event, applying the Professional knowledge, Strategic Insight, and Practical exposure gained throughout the year-long course.This journal represents a comprehensive collection of Scholarly Papers, Professional Studies, and Strategic perspectives presented at the conference by distinguished contributors from the Sri Lanka Navy, Academia, Industry, and other External Organizations. Aligned with the national vision of “A Thriving Nation, A Beautiful Life,” as the conference theme, “Clean Logistics 2030: Advancing end-to-end Logistics Excellence in Sri Lanka through Digital Advancement, Green Transformation, and Transparent Supply Chain Governance,” emphasizes the critical role of modern logistics in shaping a resilient, sustainable, and technologically advanced nation.The articles featured in this publication explore emerging trends, innovative practices, and strategic opportunities within the logistics domain, with particular focus on digital integration, environmentally responsible operations, supply chain transparency, and national logistics competitiveness. Collectively, these contributions highlight Sri Lanka’s strategic potential to evolve into a dynamic regional logistics hub by leveraging its geographic advantage, maritime connectivity, and growing logistics capabilities in the Indo-Pacific region.Copyright of all articles published in this journal rests with the Naval & Maritime Academy. No article published in this journal may be reproduced, in whole or in part, without the prior written approval of the Commandant, Naval & Maritime Academy.The views and opinions expressed in the articles published in this journal are those of the respective authors and do not necessarily reflect the official policy or position of the Sri Lanka Navy.All Rights Reserved
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Naval & Maritime Academy Logistics Conference - 2026IXIt is both inspiring and deeply encouraging to witness the growing professional commitment of naval personnel in strengthening their academic and analytical writing capabilities under this year’s conference theme.As for the Navy, the ability to maintain extended maritime operations, often under difficult and unpredictable conditions, is essential for success. The essence of this year’s conference lies in the pursuit of economic resilience through progressive and intelligent logistics management. Such initiatives are relevant to the Navy’s operational efficiency and the national development.I also wish to extend my sincere appreciation and best wishes to the pioneers and current organisers and participants of the Logistics Conference 2026, for their unwavering dedication, professionalism, and tireless efforts in upholding the highest standards and ensuring the resounding success of the event. Their commitment has laid a strong foundation for advancing logistics discourse within the naval and national context. I am confident that this academic endeavour will significantly broaden the perspectives of all logisticians and positive applications through deepening the understanding on contemporary and emerging logistics challenges.MESSAGE FROM THE COMMANDER OF THE NAVYBAKSP BANAGODA, RSP, USP, ndc, psc, MMaritimePol, MBA in HRM, PG Dip in HRM, BMS, Dip in Mgt, AFNI, JP (Whole Island)Vice AdmiralCommander of the Navy
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Naval & Maritime Academy Logistics Conference - 2026XII am indeed delighted to share my thoughts, when the Naval & Maritime Academy (NMA), launching its Logistics Conference 2006, with a fitting theme, “A thriving nation, a beautiful life’- ‘Clean logistics 2030: Advancing end-to-end logistics excellence in Sri Lanka through digital advancement, green transformation and transparent supply chain governance”. It is a significant step taken by the NMA not only for raising the awareness on logistics related research among the naval community but also to apply research for upliftment of the socio-economic wellbeing of our nation. A strategic vision is the starting point of sustained success. Amidst multiple crises, economic resurgence of Sri Lanka has become an increasingly challenging endavour. With a thriving nation and beautiful life in aim, “clean logistics 2030” could be seen as a clear way of adapting to a broad overarching approach, offering the needed logistical assistance. In such a context, the needed support by comprehensive research to take datadriven decisions is felt more than any other times. We need to realize the required a conference of this nature fulfills such voids in focusing on deeper and broader issues shedding much light through rigorous analysis and right interpretations.It is heartening to anticipate the conference to serve as a platform for professionals to discuss the intricate interplay of the digital advancement, green transformation, and supply chain governance, which form the backbone of end-to-end logistics excellence. With the involvement with key resource personnel representing diverse social segments, in sharing knowledge through presentations, discussions as well as networking, an insightful as well as impactful intervention will take place. May I take this opportunity to thank the NMA for their committed collaboration in vibrantly showcasing the Logistics Conference 2026. Let me wholeheartedly wish this prestigious event a phenomenal success. MESSAGE FROM THE KEYNOTE SPEAKERAJANTHA S. DHARMASIRISenior Professor in ManagementPostgraduate Institute of ManagementUniversity of Sri Jayewardenepura
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Naval & Maritime Academy Logistics Conference - 2026XIIIIt is my distinct honour and privilege to extend this felicitation message as the Director General Logistics of the Sri Lanka Navy, on the occasion of the Logistics Journal being published for the 08th Edition of the “Logistics Conference - 2026”, organized by the Course Participants of the 10th Long Logistics Management Course (LLMC).The LLMC at the Naval & Maritime Academy (NMA) was initiated on 30th January 2014 to fulfill a long-standing need for higher professional training among logistics branch officers. The primary objective of this transformative initiative is to cultivate deep professional expertise in Logistics Management, empowering our logistics officers to perform their duties with precision, agility, and strategic foresight. With the rigorous and comprehensive training imparted at NMA, I am confident that these officers are well equipped to confront dynamic and complex challenges with unwavering competence, and that the knowledge they have acquired will enable them to forge innovative solutions proactively.I strongly believe that this Logistics Conference stands as an indispensable platform for policymakers, scholars, and practitioners across both the military and corporate sectors, illuminating the very best in logistics thought and practice. This year’s conference theme “Clean Logistics 2030: Advancing end-to-end Logistics Excellence in Sri Lanka through Digital Advancement, Green Transformation and Transparent Supply Chain Governance” under the national vision of “A Thriving Nation, A Beautiful Life,” is not merely timely it is imperative. As Sri Lanka boldly charts its path towards sustainable national development, the imperatives of digital transformation, environmental stewardship, and governance integrity must be woven into the very fabric of our logistics architecture. I am deeply convinced that this conference will generate landmark contributions to theoretical, empirical, and practical discourse in the field of logistics, setting a definitive course for the nation’s logistics future.I wish to convey my profound appreciation to the Commander of the Navy for his visionary guidance, steadfast inspiration, and unwavering encouragement in making the “Logistics Conference - 2026” a resounding success. My sincere congratulations also go to the Commandant of the Naval & Maritime Academy, the Senior Course Coordinator LLMC, the Directing Staff, the Editorial Board, and the course participants for their exemplary dedication and tireless efforts in organizing this prestigious and intellectually enriching event.MESSAGE FROM THE DIRECTOR GENERAL LOGISTICS
Naval & Maritime Academy Logistics Conference - 2026XIVFinally, I extend my warmest wishes to all participants, distinguished speakers, and invited delegates. I am confident that the “Logistics Conference - 2026” will serve as an exceptional and transformative forum for knowledge dissemination, professional growth, and the collective advancement of logistics excellence in Sri Lanka.ABRA DE SILVA, RSP*, USP, ndc, psc, MDS, MSc (DS) Mgt, Dip in IR, SSAC, CDORear Admiral Director General Logistics
Naval & Maritime Academy Logistics Conference - 2026XVIt is with great pride and a profound sense of responsibility that I extend my message for this edition of the Logistics Journal, themed “A Thriving Nation, A Beautiful Life – Clean Logistics 2030: Advancing end-to-end Logistics Excellence through Digital Advancement, Green Transformation and Transparent Supply Chain Governance.”In an era defined by rapid technological evolution and increasing environmental consciousness, the role of logistics within the Sri Lanka Navy has transcended traditional boundaries. Logistics today is not merely a support function; it is a strategic enabler that ensures operational readiness, resilience, and sustainability across all naval domains.The vision of “Clean Logistics 2030” reflects our commitment to building a modern, efficient, and accountable logistics framework. Digital advancement remains at the heart of this transformation. By embracing data-driven decision-making, integrated systems, and emerging technologies, we are enhancing visibility, improving responsiveness, and optimizing resource utilization across the entire supply chain.Equally important is our responsibility towards environmental stewardship. Green transformation in naval logistics is no longer optional; it is imperative. From sustainable procurement practices to energy-efficient transportation and waste minimization, we must align our logistics operations with national and global sustainability goals, contributing to a cleaner and healthier future.Transparency and governance form the foundation of trust and efficiency. Strengthening supply chain governance through accountability, standardization, and ethical practices ensures that our logistics systems remain robust, reliable, and resistant to inefficiencies.As we move forward, the collective expertise, innovation, and dedication of our logistics professionals will be the driving force behind achieving excellence. I encourage all officers and contributors to continue exploring innovative solutions, sharing knowledge, and fostering a culture of continuous improvement.MESSAGE FROM THE COMMANDANTNAVAL & MARITIME ACADEMY
Naval & Maritime Academy Logistics Conference - 2026XVILet this journal serve not only as a platform for academic and professional discourse but also as a catalyst for transformation within naval logistics. Together, we will build a logistics ecosystem that supports a thriving nation and ensures a beautiful life for future generations.I commend the editorial team and all contributors for their efforts in bringing out this valuable publication and wish them continued success in their endeavors.DMDC BANDARA, RSP, USP, NWC, psc Commodore Commandant Naval & Maritime Academy
Naval & Maritime Academy Logistics Conference - 2026XVIISUB THEME 01Digital Acceleration as a Catalyst for Sri Lanka`s Logistics Backbone01. Smart Logistics as a Driver of Trade Facilitation: Technologies, Mechanisms, and Policy Implications: A Literature Review.....................................................Dr. Wasana Rathnayke02. Digital end-to-end Integration In Humanitarian LogisticsLeveraging Armed Forces Capabilities for a Resilient Sri Lanka......................Lieutenant Commander (S) CS Serasinghe03. Driving The Logistics Backbone: An Ai-Enhanced Continuous Improvement Frame work for Resilient Supply Chain Operations in Sri Lanka......................Ms.PHT Perera, Ms. TD Sooriyaarachchi04. Public-Private Partnership Governance Models for National Digital Logistics Platforms in Sri Lanka.........................................................................................Lieutenant Commander (S) DS Dahanayke05. From Traditional Logistics to Digital Excellence: The Role of Clean Logistics 2030 in Reshaping Sri Lanka’s end-to-end Supply Chain for a Thriving and Sustainable Economy ...........................................................................................Lieutenant Commander (S) SNK Vithanage06. Strengthening Sri Lanka’s National Logistics Resilience through Digital Advancement and Strategic Infrastructure Support of the Sri Lanka Army....Major KMVS Kahandugoda 07. Enhancing end-to-end Logistics Excellence in the Sri Lanka Navy through Digital Transformation and Sustainable Practices..............................................Lieutenant SPYAA Piyumal08. Strengthening Disaster Response through Military Logistics: EnhancingHumanitarian Relief Operations in Sri Lanka.....................................................Major RS MunasingheCONTENT03-1415-2425-4143-5153-6263-7071-7577-86
Naval & Maritime Academy Logistics Conference - 2026XVIIISUB THEME 02Integrating Green Transformation and Sustainability into End-to-End Logistics Systems09. Sustainable end-to-end Logistics: How Sri Lanka Can Lead the Green Supply Chain Innovation in South Asia .....................................................................................Commander (S) Lakshitha Sereasinghe10. Exploring Green Logistics Practices (GLPs) towards a Sustainable Economy: With Special Reference to the Sri Lankan Logistics Sector ...............................Mrs. Kalani Madhuwanthi11. Green Logistics Practices in Sri Lanka: Pathways to Achieve Sustainable Supply Chain Management by Year 2030 .................................................................................Major WGNP Madhusanke12. The Role of Reverse Logistics in Building Sustainable end to end Logistics SystemLieutenant Commander (S) AAS Bhanuka13. The Role of Green Supply Chain Management in Achieving Sustainable Logistics Performance.........................................................................................Lieutenant Commander (S) CN Wehalla14. Green Transition as A Pillar of Rebuilding Sri Lanka’s Logistics System.........Lieutenant Commander (S) GUYR Jayewardene15. Integrating Sustainability into Public Sector Procurement: A Framework for Green Policy Adoption in Sri Lanka. .................................................................Lieutenant Commander (S) YDS Dhananjani 16. Green Transformation in Integrated Logistics Systems: A Comprehensive Approach to Achieving Environmental Sustainability, Resource Efficiency, and Long-Term Operational Excellence ...............................................................................Lieutenant Commander (S) LHKT Srinath 89-100101-111113-118119-127129-137139-148149-161163-170CONTENT
Naval & Maritime Academy Logistics Conference - 2026XIXSUB THEME 03Transparent Supply Chain Governance17. Digital transparency in defence logistics: strengthening malaysia’s supply chain integrity through blockchain and AI: from opacity to accountability: transforming malaysia’s defence supply chain. ...................................................................................Lieutenant Commander Kamrul Abdin bin Sarudin18. The Impact of third-party Logistics Providers on Export Performance and Transparent Supply Chain Governance: Evidence from Sri Lanka’s Apparel Industry.......Ms. HNATD Wijebandara19. The Role of Blockchain Technology in Ensuring Transparency and Accountability in Sri Lanka’s Supply Chains ................................................................................. Lieutenant Commander (S) EMCB Ekanayake20. Strengthening Transparent Supply Chain Governance in Sri Lanka: A Framework based on Clean Logistics 2030 .................................................................Lieutenant Commander (S) MH Viduranga21. Transparent Procurement Reform in Sri Lanka’s Public Sector: A Comparative Analysis of Current Reforms in Procurement with Global Best Practices .................Lieutenant Commander (S) KSND Kularathne22. Advancing end to end Logistics Excellence in Sri Lanka through Digital Advancement, Green Transformation, And Transparent Supply Chain Governance...................................... Lieutenant MSS Kumarathunga23. Geopolitics of Clean Logistics: Sri Lanka’s Strategic Choices in a Fragmented Global Trade Order ............................................................................................. Ms. RPYR Rajapakse24. Clean Logistics 2030: Sri Lanka’s Journey to a Thriving Nation. ................................................Lieutenant Commander (S) DMNS Dissanayake173-188189-200201-209211-219221-230231-238 239-246247-270CONTENT
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Naval & Maritime Academy Logistics Conference - 20261SUB THEME 01Digital Acceleration as a Catalyst for Sri Lanka`s Logistics Backbone
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Naval & Maritime Academy Logistics Conference - 20263SMART LOGISTICS AS A DRIVER OF TRADE FACILITATION: TECHNOLOGIES, MECHANISMS, AND POLICY IMPLICATIONS: A LITERATURE REVIEWDr.Wasana Rathnayaka Department of Economics, University of Colombo, Colombo, Sri Lanka AbstractSmart logistics - the systematic integration of digital technologies, including the Internet of Things (IoT), artificial intelligence (AI), blockchain distributed ledger systems, and port automation into supply chain operations - has emerged as a principal driver of contemporary trade facilitation. This paper provides a structured, critical review of the theoretical and empirical literature on the relationship between smart logistics and trade facilitation, organized around five technology channels: digital customs and national single-window environments; IoT-enabled cargo tracking and supply chain visibility; AI-driven logistics optimization and risk-based customs management; blockchainbased trade documentation and finance; and automated port and warehouse systems. Drawing on peer-reviewed journal articles, World Bank analyses, OECD assessments, WTO studies, and institutional case evidence spanning advanced, emerging, and leastdeveloped economies, the paper demonstrates that smart logistics modernization generates significant and measurable reductions in trade costs, border dwell times, documentation compliance burdens, and trade finance transaction costs. The analysis further reveals important distributional asymmetries: while frontier logistics economies have achieved compound trade gains through integrated smart logistics ecosystems, the least-developed countries face structural barriers that risk widening the digital logistics divide. The paper concludes with a synthesis of evidence-based policy implications for governments, regional bodies, and international development organizations.Keywords: Smart Logistics; Trade Facilitation; Logistics Performance Index; Internet of Things; Blockchain; Digital Customs; Single Window; Global Value Chains; Trade CostsIntroduction And Theoretical FrameworkInternational trade in the twenty-first century increasingly relies on information architecture alongside physical commodity flows. The expansion of global value chains (GVCs), growth of cross-border e-commerce, and adoption of just-in-time production have intensified demands on logistics systems for speed, reliability, transparency, and cost efficiency (Saslavsky & Shepherd, 2014; Arvis et al., 2016).
Naval & Maritime Academy Logistics Conference - 20264In this context, smart logistics—integrating digital, automated, and data-driven technologies across transport, warehousing, customs, and border management—has emerged as a key driver of trade transformation. The importance of logistics efficiency is well established. Limão and Venables (2001) show that poor transport infrastructure constrains trade more than equivalent tariff barriers, while Hummels (2007) estimates that each additional day of shipping is equivalent to a 0.5 per cent ad valorem tariff. Anderson and van Wincoop (2003) further estimate border-related trade costs at around 44 per cent for OECD countries, highlighting the potential gains from logistics modernization.At the policy level, the WTO Trade Facilitation Agreement (WTO, 2015), in force since 2017, reflects a global consensus on simplifying trade procedures. The World Bank (2020) estimates that full implementation could reduce trade costs by 14.3 per cent and increase global exports by up to USD 1 trillion annually, depending on logistics performance. Smart logistics provides the operational basis for these gains. Despite growing interest, key gaps remain. Research is fragmented across individual technologies such as blockchain, IoT, and AI; cross-country disparities, including a “digital logistics divide,” are underexplored; and empirical findings are rarely translated into policy guidance. This paper addresses these gaps by developing an integrated framework, synthesizing evidence, and deriving policy implications.Smart logistics refers to the use of advanced information and communication technologies across all logistics stages, from freight consolidation to final delivery. Chen, Hasan, and Cheng (2020) define it as a system where physical assets, such as vehicles, containers, and warehouses are equipped with sensing technologies that generate real-time data for optimization and compliance. Wang, Zhang, Liu, and Wang (2022) conceptualize smart logistics as a three-layer system. The physical layer includes connected assets such as GPS-enabled vehicles, RFID-tagged containers, automated guided vehicles (AGVs), and robotic warehouses. The data layer consists of cloud computing, IoT networks, and storage systems that process data into insights. The application layer applies these insights through AI-based systems, blockchain-enabled documentation, and digital customs platforms, including single-window systems. This layer most directly supports trade facilitation.The gravity model (Anderson and van Wincoop, 2003) explains trade flows as increasing with economic size and decreasing with trade costs, including transport costs, delays, and administrative barriers. Many of these costs—especially those related to time and documentation—can be reduced through improved logistics systems, highlighting the role of smart logistics.Portugal-Perez and Wilson (2012) distinguish between hard infrastructure (e.g., transport networks) and soft infrastructure (e.g., customs efficiency), showing that improvements in both enhance export performance, particularly soft infrastructure. Similarly, Arvis et al. (2016) find that logistics performance, measured by the Logistics Performance Index (LPI), is a major determinant of trade costs.
Naval & Maritime Academy Logistics Conference - 20265These findings underscore the importance of logistics systems in facilitating trade. Transaction cost theory (Coase, 1937; Williamson, 1985) explains trade frictions arising from information asymmetry, verification requirements, and institutional differences. Smart logistics technologies reduce these costs. Blockchain systems improve transparency through secure records, reducing documentation burdens (Ganne and Lehmann, 2018). IoT-enabled tracking provides real-time shipment data, reducing information asymmetry and easing trade finance constraints (Asian Development Bank, 2020). AI enhances customs risk management by enabling targeted inspections, reducing delays and compliance costs (World Customs Organization, 2018). Krugman (1991) shows that lower trade costs allow firms in peripheral regions to access larger markets, promoting spatial dispersion. Melitz (2003) demonstrates that lower trade costs enable more firms to export by reducing productivity thresholds, expanding trade along the extensive margin.These theories imply that logistics improvements, particularly through smart technologies, expand trade participation, especially for small firms and high-cost economies. Empirical evidence supports this: Saslavsky and Shepherd (2014) highlight the role of logistics in GVC participation, while Arvis et al. (2016) find stronger effects for SMEs and less diversified economies. Literature Review01. Smart Logistics Technology Channels and Trade FacilitationThe literature identifies five key technology channels through which smart logistics enhances trade facilitation. Table 1 summarizes each channel, its underlying mechanism, associated trade facilitation effects, and supporting literature. The following sub-sections examine these channels in detail.
Naval & Maritime Academy Logistics Conference - 20266Source: Author’s compilation based on Organization for Economic Co-operation and Development (OECD, 2018); Moïsé and Sorescu (2013); Fernandes et al. (2019); United Nations Conference on Trade and Development (UNCTAD, 2020, 2022); Chae (2015); Kshetri (2018); Wang et al. (2022); Asian Development Bank (ADB, 2020); Tang and Zhang (2020); McKinsey Global Institute (2017); World Economic Forum (WEF, 2016); World Customs Organization (WCO, 2018); Zhao et al. (2019); Ganne and Lehmann (2018); International Chamber of Commerce (ICC, 2018); World Trade Organization (WTO, 2021); Ojala and Çelebi (2015); Rodrigue (2020)Among smart logistics technologies, customs digitalization, particularly national single-window systems are widely recognized as one of the most effective trade facilitation reforms. A single window, defined by UNCTAD (2020), enables traders to submit standardized information through a single electronic platform shared across government agencies. This reduces duplication, enables automated compliance checks, and supports pre-arrival risk assessment, transforming customs from a source of delay into a facilitator of trade. Empirical evidence confirms these benefits. Moïsé and Sorescu (2013) show that streamlined border procedures significantly reduce trade costs, particularly in developing countries, while OECD (2018) finds that advanced digital customs systems shorten processing times. Country-level evidence highlights Singapore’s TradeNet, which reduced clearance times from several days to under ten minutes and lowered compliance costs by 30 per cent (Tan, 2000; World Bank, 2023). Similarly, Fernandes, Hillberry, and Mendoza Alcántara (2019) find that customs automation in Albania increased import values by 18 per cent, driven by reduced clearance times, with the strongest effects for intermediate goods critical to GVCs.Smart customs also increasingly rely on AI-based risk management. Unlike traditional inspection systems, AI enables targeted identification of high-risk consignments, improving efficiency. The World Customs Organization (WCO, 2018) reports that such systems reduce inspection rates from 20–30 per cent to below 5 per cent while maintaining detection effectiveness. Complementing this, the Authorized Economic Operator (AEO) program provides trusted firms with faster clearance, reducing processing times by 30–60 per cent (De Wulf and Sokol, 2005; WCO, 2018).The Internet of Things (IoT) further enhances trade facilitation by improving supply chain visibility. IoT systems, including RFID tags, GPS tracking, and environmental sensors, generate real-time, object-level data (Wang et al., 2022). Chae (2015) finds that such systems reduce shipment loss and improve coordination through predictive arrival information, easing port congestion. This allows customs to conduct pre-arrival risk assessments and expedite clearance, reducing delays and improving supply chain efficiency. IoT also contributes to trade finance by reducing information asymmetries. The Asian Development Bank (2020) estimates a global trade finance gap of USD 1.7 trillion, disproportionately affecting SMEs. Real-time data on goods in transit improves risk assessment and enables goods to serve as collateral. Combined with blockchain and smart contracts, this enhances access to finance (Ganne and Lehmann, 2018; Kshetri, 2018).
Naval & Maritime Academy Logistics Conference - 20267Artificial intelligence (AI) plays a broader role in logistics optimization. The McKinsey Global Institute (2017) and World Economic Forum (2016) highlight its potential to reduce costs and improve efficiency. Tang and Zhang (2020) identify three key channels: demand forecasting, which improves supply chain responsiveness; customs risk analysis, which accelerates clearance; and automated document processing, which reduces errors and delays. AI also supports predictive maintenance, reducing equipment downtime and improving port efficiency (World Economic Forum, 2016; Rodrigue, 2020).Blockchain technology addresses the documentation-intensive nature of international trade. Transactions typically require 20–30 documents, creating costs and delays (International Chamber of Commerce, 2018). Blockchain replaces paper-based systems with secure, shared digital records, reducing duplication and fraud (Zhao et al., 2019). In trade finance, blockchain reduces processing times for instruments such as letters of credit from several days to less than 24 hours (Ganne and Lehmann, 2018), lowering costs and increasing accessibility, particularly for SMEs (Asian Development Bank, 2020; World Trade Organization, 2021). Blockchain also simplifies compliance with rules of origin. UNCTAD (2020) notes that firms often underutilize preferential tariffs due to high administrative costs. Digital certification systems enable automated verification, reducing compliance costs and increasing tariff utilization, particularly in systems such as the ASEAN Single Window.Finally, automation in ports and warehouses enhances physical logistics efficiency. Ports handle around 80 per cent of global trade, and automation technologies such as automated cranes and AI-based systems increase throughput by 20–35 per cent (Rodrigue, 2020). Port Community Systems further improve coordination, reducing waiting and dwell times by 25–40 per cent. In warehouses, AI-based systems reduce errors and fulfilment times (Wang et al., 2022), improving export reliability and supporting highvolume sectors such as e-commerce.2. Smart Logistics and Trade Facilitation Across Country Income GroupsAdvanced Economies such as Germany, Singapore, the Netherlands, Sweden, Japan, and Denmark lead in smart logistics, consistently scoring above 4.0 on the LPI (World Bank, 2023). Their success stems from sustained investment in digital customs, single-window systems, port community platforms, and AI/Industry 4.0 strategies. Performance results from cumulative technological integration; Germany combines IoT-enabled transport, digital freight platforms, and automated distribution for productivity gains (Wang et al., 2022), while the Netherlands uses port automation and digital customs at Rotterdam to minimize container dwell times (Rodrigue, 2020).
Naval & Maritime Academy Logistics Conference - 20268In emerging markets, smart logistics is closely tied to global value chain (GVC) participation. Logistics performance strongly influences firms’ ability to integrate into international production networks, often more than tariffs or geography (Saslavsky & Shepherd, 2014). Vietnam’s electronic customs and logistics investments reduced clearance times, boosting exports in electronics and apparel (UNCTAD, 2022). Similarly, China’s AI-enabled customs and automated ports have strengthened export competitiveness (Tang & Zhang, 2020).Least-Developed Countries face significant gaps in logistics performance, with LPI scores far below OECD averages, resulting in higher trade costs and limited GVC participation (Arvis et al., 2016). Structural constraints include poor infrastructure, weak customs capacity, fragmented logistics sectors, and limited digital connectivity (Moïsé & Sorescu, 2013; Kshetri, 2018). Nevertheless, targeted reforms show promise: Kenya’s digital customs reduced clearance times, and Rwanda’s investments improved trade facilitation despite being landlocked. These cases highlight that institutional support and strategic investment can enhance logistics performance even in resource-constrained settings.
Naval & Maritime Academy Logistics Conference - 20269Discussion And Policy Implications1. Synthesising the Evidence: Key Findings from the LiteratureThe literature consistently shows that smart logistics improvements reduce trade costs and enhance trade facilitation. Evidence from gravity model studies, LPI analyses, and program evaluations demonstrates a positive, significant relationship between logistics performance and trade outcomes. Multiple mechanisms contribute to this effect: customs digitalization shortens clearance times, IoT enhances information availability, AI improves risk management, blockchain reduces documentation inefficiencies, and port automation increases operational capacity. These channels are interconnected, indicating that integrated adoption of technologies yields the greatest benefits. Customs digitalization, especially single-window systems, emerges as the highest-impact reform. Moïsé and Sorescu (2013), OECD (2018) Trade Facilitation Indicators, and case studies from Albania, Singapore, and Vietnam show that modernized customs procedures consistently reduce trade costs. For resource-constrained countries, prioritizing customs reform within a broader smart logistics strategy is therefore essential.The evidence also highlights the importance of complementary infrastructure. Digital technologies require adequate transport networks, capable customs institutions, regulatory frameworks, and interoperable systems to function effectively. Portugal-Perez and Wilson (2012) and Arvis et al. (2016) note that without addressing physical and institutional constraints, digital reforms alone cannot achieve maximal trade facilitation benefits.2. Policy ImplicationsFirstly, Customs digitalization should be central to trade infrastructure strategies. National single-window systems, electronic document submission, automated risk management, and paperless clearance procedures consistently yield high returns by reducing trade costs and processing times (Moïsé & Sorescu, 2013; OECD, 2018). International support, including Aid for Trade initiatives, should prioritize investments in customs modernization and related institutional capacity building.Also, Smart logistics technologies are most effective when supported by adequate physical infrastructure. Digital systems cannot offset constraints such as limited port capacity, unreliable energy, or poor road connectivity. Governments should adopt integrated investment strategies combining physical infrastructure development with digital logistics systems to ensure that efficiency gains from technology are fully realized (Portugal-Perez & Wilson, 2012).
Naval & Maritime Academy Logistics Conference - 202610Digital trade technologies, especially blockchain-based systems, require clear legal and regulatory frameworks. Uncertainty over the status of electronic documents and digital contracts can hinder adoption. Governments should enact legislation recognizing electronic trade documents and ensuring enforceability of digital transactions, drawing guidance from international frameworks such as the UNCITRAL Model Law on Electronic Transferable Records.Furthermore, adoption of smart logistics is uneven, with least-developed countries (LDCs) facing infrastructure, institutional, and connectivity constraints (Arvis et al., 2016; Kshetri, 2018). Coordinated international support is essential, combining technical assistance, financial aid, and capacity building to expand participation in digital trade systems. Targeted reforms can generate meaningful improvements, as seen in Kenya and Rwanda.Finally, smart logistics benefits increase when national platforms interact across borders. Regional cooperation is essential to establish common standards, promote interoperability between digital systems, and implement mutual recognition for trusted trader programs. Such initiatives enhance cross-border efficiency and maximize the impact of smart logistics investments.ConclusionThis paper has presented a structured and critical review of the theoretical and empirical literature on smart logistics as a driver of trade facilitation. It examined five main technology channels: digital customs and single-window systems, Internet of Things based cargo tracking, artificial intelligence driven logistics optimization, blockchainbased trade documentation and finance, and automated port and warehouse systems. The analysis drew on a wide range of sources, including academic studies and reports from international organizations, covering evidence from advanced, emerging, and leastdeveloped economies.The review leads to three main conclusions. First, smart logistics improvements result in clear and measurable reductions in trade costs, supported by both theory and empirical evidence. Among the different technologies, customs digitalization and singlewindow systems emerge as the most effective and widely applicable reforms across countries at different income levels. Second, the benefits of smart logistics depend on broader institutional and infrastructural conditions. These technologies require supportive regulatory frameworks, capable public institutions, and adequate physical infrastructure to function effectively. Therefore, investments in smart logistics should be planned in an integrated manner rather than implemented as isolated technological solutions. Third, there is a significant gap between advanced economies and least-developed countries in the adoption of smart logistics. This digital divide is not only evident but also self-reinforcing, as countries with weaker logistics systems face greater barriers to improvement. Addressing this gap requires coordinated policy efforts at both national and international levels to ensure that the benefits of smart logistics are more evenly distributed.
Naval & Maritime Academy Logistics Conference - 202611Despite these contributions, the review also identifies several limitations in the existing literature. First, the availability of rigorous empirical evidence remains limited. While some studies provide strong causal analysis, much of the literature relies on cross-sectional data or case-based observations. Future research should focus on more robust methodologies, such as quasi-experimental designs, to better establish causal relationships. Second, the interaction between different smart logistics technologies is not well understood. For example, the extent to which IoT-based tracking enhances the effectiveness of digital customs systems remains largely unexplored. Third, there is limited research on how smart logistics affects the informal sector, which plays a significant role in trade in many developing countries. This represents an important area for future investigation.In conclusion, the evidence reviewed in this paper suggests that smart logistics is central to modern trade facilitation. Investments in digital systems, institutional capacity, and supporting infrastructure can significantly reduce trade costs and improve market access. For governments and international organizations, promoting smart logistics should therefore be considered a key strategy for achieving trade-led economic development.REFERENCESAnderson, J. E., & van Wincoop, E. (2003). Gravity with gravitas: A solution to the border puzzle. American Economic Review, 93(1), 170–192. https://doi.org/10.1257/000282803321455214Arvis, J.-F., Ojala, L., Wiederer, C., Shepherd, B., Raj, A., Dairabayeva, K., & Kiiski, T. (2016). Connecting to compete 2016: Trade logistics in the global economy. World Bank.Asian Development Bank. (2020). Trade finance gaps, growth, and jobs survey (ADB Briefs No. 152). https://doi.org/10.22617/BRF200268-2Chae, B. (2015). Insights from hashtag #supplychain and Twitter analytics: Considering Twitter data for supply chain practice and research. International Journal of Production Economics, 165, 247–259. https://doi.org/10.1016/j.ijpe.2014.12.037Chen, L., Hasan, R., & Cheng, L. (2020). Blockchain technology and its relationship to sustainable supply chain management. Supply Chain Management: An International Journal, 25(6), 763–775. https://doi.org/10.1108/SCM-05-2019-0206Coase, R. H. (1937). The nature of the firm. Economica, 4(16), 386–405. https://doi.org/10.1111/j.1468-0335.1937.tb00002.xDe Wulf, L., & Sokol, J. B. (Eds.). (2005). Customs modernization handbook. World Bank. https://doi.org/10.1596/0-8213-5771-8
Naval & Maritime Academy Logistics Conference - 202612Fernandes, A. M., Hillberry, R., & Mendoza Alcántara, A. (2019). Trade effects of customs reform: Evidence from Albania. The World Bank Economic Review, 33(3), 511–534. https://doi.org/10.1093/wber/lhx009Ganne, E., & Lehmann, K. (2018). The digital economy, GVCs, and SMEs. World Trade Organization. https://www.wto.org/english/res_e/booksp_e/aid4tradeglobalvalue16_e.pdfHoekman, B., & Nicita, A. (2011). Trade policy, trade costs, and developing country trade. World Development, 39(12), 2069–2079. https://doi.org/10.1016/j.worlddev.2011.05.013Hummels, D. (2007). Transportation costs and international trade in the second era of globalization. Journal of Economic Perspectives, 21(3), 131–154. https://doi.org/10.1257/jep.21.3.131International Chamber of Commerce. (2018). Rethinking trade and finance 2018.Krugman, P. (1991). Increasing returns and economic geography. Journal of Political Economy, 99(3), 483–499. https://doi.org/10.1086/261763Kshetri, N. (2018). Blockchain’s roles in meeting key supply chain management objectives. International Journal of Information Management, 39, 80–89. https://doi.org/10.1016/j.ijinfomgt.2017.12.005Limão, N., & Venables, A. J. (2001). Infrastructure, geographical disadvantage, transport costs, and trade. The World Bank Economic Review, 15(3), 451–479. https://doi.org/10.1093/wber/15.3.451McKinsey Global Institute. (2017). A future that works: Automation, employment, and productivity.Melitz, M. J. (2003). The impact of trade on intra-industry reallocations and aggregate industry productivity. Econometrica, 71(6), 1695–1725. https://doi.org/10.1111/1468-0262.00467Moïsé, E., & Sorescu, S. (2013). Trade facilitation indicators: The potential impact of trade facilitation on developing countries’ trade (OECD Trade Policy Paper No. 144). OECD Publishing. https://doi.org/10.1787/5k4bwwqbvsq2-enOrganisation for Economic Co-operation and Development. (2018). Trade facilitation and the global economy. OECD Publishing. https://doi.org/10.1787/9789264277571-enOjala, L., & Çelebi, D. (2015). The World Bank’s logistics performance index (LPI) and drivers of logistics performance. In Proceedings of the OECD/ITF roundtable on logistics development strategies.
Naval & Maritime Academy Logistics Conference - 202613Fernandes, A. M., Hillberry, R., & Mendoza Alcántara, A. (2019). Trade effects of customs reform: Evidence from Albania. The World Bank Economic Review, 33(3), 511–534. https://doi.org/10.1093/wber/lhx009Ganne, E., & Lehmann, K. (2018). The digital economy, GVCs, and SMEs. World Trade Organization. https://www.wto.org/english/res_e/booksp_e/aid4tradeglobalvalue16_e.pdfHoekman, B., & Nicita, A. (2011). Trade policy, trade costs, and developing country trade. World Development, 39(12), 2069–2079. https://doi.org/10.1016/j.worlddev.2011.05.013Hummels, D. (2007). Transportation costs and international trade in the second era of globalization. Journal of Economic Perspectives, 21(3), 131–154. https://doi.org/10.1257/jep.21.3.131International Chamber of Commerce. (2018). Rethinking trade and finance 2018.Krugman, P. (1991). Increasing returns and economic geography. Journal of Political Economy, 99(3), 483–499. https://doi.org/10.1086/261763Kshetri, N. (2018). Blockchain’s roles in meeting key supply chain management objectives. International Journal of Information Management, 39, 80–89. https://doi.org/10.1016/j.ijinfomgt.2017.12.005Limão, N., & Venables, A. J. (2001). Infrastructure, geographical disadvantage, transport costs, and trade. The World Bank Economic Review, 15(3), 451–479. https://doi.org/10.1093/wber/15.3.451McKinsey Global Institute. (2017). A future that works: Automation, employment, and productivity.Melitz, M. J. (2003). The impact of trade on intra-industry reallocations and aggregate industry productivity. Econometrica, 71(6), 1695–1725. https://doi.org/10.1111/1468-0262.00467Moïsé, E., & Sorescu, S. (2013). Trade facilitation indicators: The potential impact of trade facilitation on developing countries’ trade (OECD Trade Policy Paper No. 144). OECD Publishing. https://doi.org/10.1787/5k4bwwqbvsq2-enOrganisation for Economic Co-operation and Development. (2018). Trade facilitation and the global economy. OECD Publishing. https://doi.org/10.1787/9789264277571-enOjala, L., & Çelebi, D. (2015). The World Bank’s logistics performance index (LPI) and drivers of logistics performance. In Proceedings of the OECD/ITF roundtable on logistics development strategies.
Naval & Maritime Academy Logistics Conference - 202614World Trade Organization. (2015). Agreement on trade facilitation. https://www.wto.org/english/tratop_e/tradfa_e/tradfa_e.htmWorld Trade Organization. (2021). Global value chain development report 2021: Beyond production.Zhao, G., Liu, S., Lopez, C., Lu, H., Elgueta, S., Chen, H., & Boshkoska, B. M. (2019). Blockchain technology in agri-food value chain management: A synthesis of applications, challenges and future research directions. Computers in Industry, 109, 83–99. https://doi.org/10.1016/j.compind.2019.04.002
Naval & Maritime Academy Logistics Conference - 202615DIGITAL END-TO-END INTEGRATIONIN HUMANITARIAN LOGISTICSLeveraging Armed Forces Capabilities for a Resilient Sri LankaLieutenant Commander (S) CS SerasingheLong Logistics Managment Course No.10Naval & Maritime AcademyAbstractThe report discusses how digital transparency can be used to empower the defence supply chain of Malaysia, specifically in relation to blockchain and Artificial Intelligence (AI). The defence logistics system in Malaysia is still in its developing stage, yet it still encounters the main problems, namely, the lack of transparency, corruption threat, inefficiencies, and fragmented data management. Such problems destroy accountability, make operations more expensive, and deter the general effectiveness of the systems. The report has a transparent supply chain management framework, and the major principles that are adopted include traceability, accountability, data integrity and real-time visibility. It also determines the role of blockchain technology in enhancing transparency based on the decentralised and immutable records-keeping and AI-based predictive analytics and fraud detection, as well as optimisation of logistics operations. These technologies can be integrated to provide a hybrid model that can change the conventional defence logistics into a more efficient and accountable one. Major conclusions indicate that blockchain and AI implementation can help to minimise corruption rates and threats, enhance procurement efficiency, and increase trust in the stakeholders. Nevertheless, technical constraints, regulatory loopholes, and organisational resistance are some of the challenges that should be handled. The report ends by giving policy recommendations such as the establishment of a national digital defence logistics strategy, pilot projects, regulatory reinforcement, and workforce capacity building to help Malaysia when it comes to a transparent and resilient defence supply chain.Keywords: Transparent Supply Chain Management, Defence Logistics, Malaysia Defence Industry, Blockchain Technology, Artificial Intelligence (AI)
Naval & Maritime Academy Logistics Conference - 202616Introduction1. A Nation at RiskSri Lanka is one of the most disaster-prone countries in the Asia-Pacific region. Situated within the Indian Ocean’s cyclone zone and above tectonically active fault lines, the island frequently faces tsunamis, floods, landslides, and cyclones, along with compounded socioeconomic shocks. The 2004 Indian Ocean Tsunami, which resulted in over 38,000 deaths and displaced 834,000 people, exposed a nearly nonexistent domestic logistics system capable of delivering life-saving aid quickly and at scale. (Center, 2019) Two decades later, the 2025 Cyclone Ditwah demonstrated that these lessons had not been learned: the same issues of fragmentation, lack of coordination, poor visibility, and makeshift responses reemerged, leading to devastating consequences. (Lanka, 2026)What sets countries that save lives efficiently apart from those that do not is not their proximity to hazards; it is the quality of their logistics systems. Countries with integrated digital humanitarian logistics platforms respond faster, have lower costs per beneficiary, and are more accountable to donors and affected populations alike. Sri Lanka currently lags far behind this standard.2. The Armed Forces as the Logical AnchorIn every major disaster in Sri Lanka, the Armed Forces, which include the Army, Navy, and Air Force, have been the core of the humanitarian response. Their unmatched logistics infrastructure, extensive national coverage, and disciplined command structure make them the only institution capable of establishing a national digital humanitarian logistics system. However, current operations are still primarily analogue: there is no integrated ERP platform, no standardized IoT asset tracking, and no operational drone logistics capability. Investing in the Armed Forces’ digital logistics is not just about modernizing defense; it is the most impactful way to build a resilient, accountable, and quick national humanitarian response.3. Scope and ObjectivesThis paper explores six interconnected areas: analysis of historical disasters; benchmarking digital readiness; a proposed end-to-end (E2E) integration framework; prioritizing technology impacts; a step-by-step implementation plan with investment evaluation; and targeted policy recommendations. All analysis is conducted within the context of, and aligned with, the Clean Logistics 2030 national strategy, which provides the institutional and political mandate for transformation.
Naval & Maritime Academy Logistics Conference - 202617Historical Disaster Analysis1. Five Disasters, One Systemic FailureThe five crises examined in this paper span two decades and cover the full range of Sri Lanka’s disaster risks, including geological, meteorological, and socioeconomic issues. What is notable is not the diversity of their causes but the consistent pattern of logistics failures. Figure 1 shows the human scale and impact of each event.The 2004 Tsunami remains unmatched in morality, but every subsequent disaster has reflected the same operational failures. The 2022 Economic Crisis, although causing no direct deaths, displaced over 2.2 million people, exposing the fragility of civilian supply chains when institutional buffers fail. The 2025 Cyclone Ditwah, the worst meteorological event since 2004, showed that twenty years of disaster experience had not resulted in a significantly more capable logistics system.2. Disaster Impact and Logistics Failure Analysis
Naval & Maritime Academy Logistics Conference - 2026183. What the Evidence DemandsFour unavoidable conclusions arise from this analysis. First, logistics failures in Sri Lanka are structural rather than situational; the same issues keep appearing regardless of disaster type, scale, or location. Second, the technology gap is growing wider: global humanitarian logistics has advanced rapidly since 2004, while Sri Lanka’s preparedness has remained stagnant. Third, the Armed Forces, though essential, are often limited by outdated operations that restrict their speed and accountability. Fourth, and most importantly, the human and economic costs of inaction now far surpass the investment needed to develop a modern, integrated system.Digital Readiness Assessment1. Benchmarking Sri Lanka Against Global StandardsSri Lanka’s current humanitarian logistics technology capacity was systematically assessed across six areas and benchmarked against documented best practices from UNHCR, the World Food Programme, and the civil defense systems of Japan and Australia, three of the world’s most digitally advanced humanitarian operators. The results, shown in Figure 2, are clear: Sri Lanka scores between 1.0 and 2.5 out of 10 in all six areas, compared to global benchmarks of 7.5 to 9.0. The average readiness gap is 7.1 out of 10, a significant difference that directly causes delayed responses, wasted resources, and preventable deaths.
Naval & Maritime Academy Logistics Conference - 2026192. Technology Readiness by DomainThe Digital E2e Integration Framework1. A Platform Built Around the Armed ForcesThe proposed Digital End-to-End Humanitarian Logistics Framework is based on a key insight: no civilian agency in Sri Lanka has the scale, discipline, or logistics infrastructure to support a national digital humanitarian system. However, the Armed Forces do. The framework focuses on a National Digital Humanitarian Logistics Platform, overseen by a permanent Civil-Military Coordination Council and supported by six integrated technology pillars. The Armed Forces ERP system acts as the main data hub, serving as the nerve center where all other systems communicate, coordinate, and operate.2. Three Operational LayersThe framework operates across three distinct but `interdependent layers, each addressing a phase of the disaster management cycle:a. Layer 1 - Anticipation and Preparedness: AI-powered analytics engine continuously ingests meteorological forecasts, historical disaster data, and population vulnerability indices to generate pre-disaster alerts 48 to 72 hours in advance. These alerts automatically trigger the pre-positioning of emergency relief stocks in the five highest-risk districts, transforming response from reactive to anticipatory.b. Layer 2 - Response and Coordination: When a disaster is declared, the Armed Forces ERP system activates a unified logistics operations module that assigns tasks, coordinates civil-military resource distribution, and offers field commanders real-time IoT-enabled visibility of every relief shipment from warehouse shelf to recipient. Drone logistics units help bridge the last-mile gap in terrains where road access fails
Naval & Maritime Academy Logistics Conference - 202620c. Layer 3 — Accountability and Learning: A blockchain traceability layer records every procurement, movement, and distribution event on an immutable ledger accessible to government, donors, and civil society. A National KPI Dashboard aggregates performance data across all operations, generating after-action insights that continuously improve the AI predictive models feeding Layer 1.This architecture transforms humanitarian logistics from a series of disconnected, crisis-triggered improvisations into a cohesive, self-improving, and fully accountable national system. It is not just a technology upgrade; it’s a fundamental reimagining of how Sri Lanka responds to the disasters it knows with certainty will occur.Implementation Roadmap And Investment Analysis1. A Three-Phase TransformationAchieving fully digital end-to-end integration requires disciplined, sequenced implementation across three phases from 2026 to 2030. Each phase builds on the previous one, ensuring that foundational infrastructure is secure before adding advanced capabilities.a. Phase 1 — Foundation (2026–2027): Establishment of the National Civil-Military Coordination Council; implementation of ERP within the Armed Forces logistics command; and deployment of IoT asset tracking across military relief stocks and vehicles. This phase creates the institutional governance and digital backbone upon which everything else depends. Estimated investment: USD 12–18 million.b. Phase 2 — Integration (2027–2028): Launch of a joint civilmilitary procurement platform; a blockchain aid-tracking pilot; development of SLAF and Navy drone logistics units across the five highest-risk districts; and activation of the AI Anticipatory Humanitarian Logistics Program. This phase provides the cross-agency integration that makes the system transformational. Estimated investment: USD 10–16 million.c. Phase 3 — Optimization (2028–2030): National KPI Dashboard launch; AI model refinement using accumulated operational data; full blockchain rollout across all humanitarian supply chains; and integration with regional ASEAN and UNHCR digital logistics frameworks. This phase achieves the target of a 40% reduction in disaster response time. Estimated investment: USD 6–16 million.
Naval & Maritime Academy Logistics Conference - 202621The Investment CaseThe total five-year investment of USD 50 million, which equals about 0.3% of Sri Lanka’s annual defense budget, is projected to generate USD 115 million in total national benefits by 2030. These benefits stem from four main sources: reduced disaster-related economic losses (approximately USD 45 million), savings from more efficient resource use (USD 22 million), increased donor confidence and aid mobilization (USD 30 million), and the value of faster response times in saving lives (USD 18 million). The break-even point is expected to be reached in late 2028 during the second phase of implementation. Figure 3 illustrates this progress.These figures provide a conservative estimate. They do not include the reputational and geopolitical benefits of Sri Lanka positioning itself as a regional leader in digital humanitarian logistics, an outcome that would attract more international technical cooperation and development funding, further increasing the value of this foundational investment.Policy RecommendationsSix evidence-based policy recommendations are proposed, ordered by priority for implementation. Each is directly actionable, assigned to a lead agency, and aligned with the Clean Logistics 2030 mandate.
Naval & Maritime Academy Logistics Conference - 202622ConclusionSri Lanka is at a pivotal moment. The evidence shown in this paper is clear: an average digital readiness gap of 7.1 out of 10 across six key technology areas has consistently caused preventable deaths, wasted resources, and loss of public trust. The 2025 Cyclone Ditwah was not just a natural disaster; it was the result of twenty years of postponed investments in the institutional infrastructure needed for modern humanitarian logistics.The Digital E2E Integration Framework presented in this paper offers Sri Lanka a clear, step-by-step, and fully funded roadmap to break this cycle. An investment of USD 50 million over five years, modest compared to the scale of what is at stake, is expected to generate USD 115 million in measurable national benefits by 2030. Still, the actual return cannot be fully measured through a cost-benefit analysis. It shows in how quickly aid reaches a displaced family in Jaffna. It shows in the accountability that builds confidence in international donors to support Sri Lanka’s response. It shows in the life of a child who isn’t just a statistic because the system functions.
Naval & Maritime Academy Logistics Conference - 202623The vision of A Thriving Nation, A Beautiful Life is not just a slogan; it is a standard. Meeting that standard when disaster strikes require a humanitarian logistics system worthy of the 21st century. The Armed Forces have the will and the institutional capacity. The Clean Logistics 2030 framework provides the mandate. What remains is the decision to act.REFERENCESAmpliz (2024) Lanka Logistics and Technologies Ltd., Ministry of Defence – Sri Lanka. Available at: ampliz.com [Accessed 6 March 2026].Centre for Global Digital Health Innovation (2024) Digital Tools Transforming Humanitarian Aid. Johns Hopkins Bloomberg School of Public Health.Chari, F. et al. (2024) Digitalisation and efficient humanitarian logistical operations in Zimbabwe. Cogent Social Sciences, 10(1). doi:10.1080/23311886.2024.2321725.Dubey, R. et al. (2019) Big data analytics and organizational culture in the humanitarian supply chain. International Journal of Production Economics, 210, pp.120–136.Ertem, M.A. et al. (2021) The emergent role of digital technologies in humanitarian supply chains: a systematic review. Annals of Operations Research, 305, pp.3–45.Fritz, H.M. et al. (2006) Field survey of the 2004 Indian Ocean Tsunami in Sri Lanka. Earthquake Spectra, 22(S3), pp.155–172.Jayawardena, L. (2013) Critical Evaluation on ERP Applications for the Defence Sector of Sri Lanka. Academia.edu.Logistics Cluster (2018) Global Logistics Cluster Annual Report 2018. Geneva: World Food Programme.Singh, R.K. (2024) Leveraging technology in humanitarian supply chains. Journal of Humanitarian Logistics and Supply Chain Management.The Diplomat (2025) As Cyclone Ditwah recedes, Sri Lanka confronts the failures that made disaster inevitable. 3 December.Ülkü, M.A. and Engau, A. (2024) Leveraging Industry 4.0 technologies for sustainable humanitarian supply chains. Sustainability, 16(3), 1321.
Naval & Maritime Academy Logistics Conference - 202624Van Wassenhove, L.N. (2006) Humanitarian aid logistics: supply chain management in high gear. Journal of the Operational Research Society, 57(5), pp.475–489.Wiharta, S. et al. (2008) The Effectiveness of Foreign Military Assets in Natural Disaster Response. Stockholm: SIPRI.World Food Programme (2024) Tech trends transforming humanitarian aid. Diplomatic Courier.
Naval & Maritime Academy Logistics Conference - 202625DRIVING THE LOGISTICS BACKBONE: AN AI-ENHANCED CONTINUOUS IMPROVEMENT FRAMEWORK FOR RESILIENT SUPPLY CHAIN OPERATIONS IN SRI LANKAMs.TD Sooriyaarachchi1, Ms.PHT PereraGeneral Sir John Kotelawala Defence University, Sri LankaAbstractThe national logistics backbone needs to be concerned about the fundamental shift toward digital acceleration, hence targeting “clean logistics 2030”. This paper explores the transition from reactive crisis management to proactive intelligence through an Artificial Intelligence (AI) enhanced continuous improvement framework, while the traditional supply chain modely rely mainly on lagging indicators and historical data, often failing during the black swan events like the Suez Canal blockage. This study proposes a cognitive architecture that integrates predictive analytics and IoT-enabled real-time monitoring to drive the national logistics backbone. By embedding the machine learning ensemble approaches into established frameworks such as Lean and Six Sigma, the study highlights a significant leap in operational excellence. Empirical evidence shows that such digital advancement can improve forecast accuracy by upto 30%, resulting in a 25% reduction in maintenance expenses and a 35% decrease in unscheduled downtime. The framework serves as a vital catalyst for Sri Lanka’s “green transformation” by utilizing route optimization and energy consumption algorithms to minimize carbon footprints and resource waste. This paper highlights that digital acceleration is not merely a technological upgrade but a requirement for transparent supply chain governance and end-to-end excellence. By adopting a phased implementation roadmap, which moves from contained pilots to autonomous optimization in sri lankan logistics operators can achieve a compounding performance advantage. This research provides a strategic blueprint for harmonizing computational power with human discernment to build a transparent, resilient and sustainable logistics ecosystem that supports a thriving nation by 2030.Keywords: Artificial Intelligence, Continuous Improvement, Digital Acceleration, Logistics Backbone, ResilienceIntroductionAccording to statistical information, supply chain disruptions cost companies an astounding $4 trillion per annum, approximately 5 to 6% of global Gross Domestic Product (GDP) (McKinsey & Company, 2025), and these figures underscore the actual challenges businesses face day-to-day in the rapidly evolving world. Acknowledging that supply chain weaknesses have become increasingly evident in recent years.
Naval & Maritime Academy Logistics Conference - 202626From 2020 to 2022, the COVID-19 pandemic largely interrupted international activities across industries, but the 2021 Suez Canal blockage showed how a single incident can affect many continents(Port Economics, Management and Policy, 2025). Volatility has become the norm, as demonstrated by the persistent semiconductor scarcity from 2020 to 2023 and by ongoing geopolitical strains affecting crucial trade routes. In the supply chain, volatility refers to the variable swings we observe across several dimensions, such as demand patterns, supplier availability, transportation capacity, and costs incurred. This is especially difficult because these interruptions have a cascade effect on whole networks, affecting organizations well beyond the initial point of failure. The landscape is evolving from reactive crisis management to proactive, with the support of Artificial Intelligence (AI)-enabled forecasting and adaptability. Digital acceleration acts as the primary catalyst in this transformation. Organizations are discovering that waiting to respond is no longer sustainable in today’s competitive market, and we’re moving beyond viewing continuous improvement as simply making modest tweaks to established procedures. Rather, it is an example of dynamic system evolution that creates supply networks capable of learning, adapting, and changing in response to shifting circumstances. The study explores an AIintegrated framework to advance end-to-end logistics excellence in Sri Lanka through green transformation and transparent governance.There are several restrictions in the established Supply Chain approaches across the industry. The main reason is that traditional techniques rely on lagging indicators and historical trends, which can fail in unanticipated situations, and static optimization models require hands-on intervention to respond to real-time interruptions(Stammer et al., 2022) because of siloed data systems; visibility across multiple supply chains is kept in check. The limited bandwidth for human decision-making while processing complex, highvelocity data streams can contribute to delays which can affect the efficiency. Quarterly and annual review cycles are too sluggish for today’s unpredictable circumstances, which can be encouraged due to a lack of forecasting ability, which keeps businesses in a reactive mindset. Nonlinear logistics network dynamics, including feedback loops, cannot be captured by linear cause-and-effect assumptions(Ahmad et al., 2015).With the emergence of Artificial Intelligence, the industry has undergone a significant transformation(Kagalwala, 2025). Artificial Intelligence (AI) enables the transition from descriptive (“what happened”) to prescriptive (“what should we do”) analytics. Self-learning systems that improve performance without specific reprogramming such as real-time sensing and reaction functions operating at machine speed(Borah et al., 2024), pattern recognition across billions of data points that humans cannot process, ability to model complex connections and simulate thousands of scenarios simultaneously, creation of “digital twins” that enable risk-free experimentation and optimization, with the untapped potential. Only 15 to 20% of organizations have deployed advanced Artificial Intelligence (AI) in supply chain operations, despite proven Return on Investments.
Naval & Maritime Academy Logistics Conference - 202627The theoretical contribution is as follows: integrating Artificial Intelligence (AI) capabilities with established continuous improvement frameworks such as Lean, Six Sigma, and Theory of Constraints(Mitra, Chanda and Bhattacharya, 2021). Development of the “Cognitive Supply Chain” concept, including networks that sense, learn, adapt, and optimize autonomously, extension of dynamic capabilities theory to Artificial Intelligence (AI)-augmented organizational learning(Thi, Uyen and Hieu, 2026). Bridging computer science, operations research, and organizational theory for holistic frameworks on Supply Chain domains(Thi, Uyen and Hieu, 2026). The advancement of the socio-technical systems perspective, which defines human-Artificial Intelligence (AI) collaboration rather than replacement, and its contribution to emerging literature on algorithmic management and Artificial Intelligence (AI) governance in operations.This study will show a thorough development from fundamental technology to useful real-life applications, backed by empirical data and resolving implementation challenges with an integrated framework. To keep complicated ideas intelligible for decision-makers without compromising rigor, the study carefully balances accessibility for managers with technical depth by combining quantitative information with qualitative insights from sector professionals, the study provides a comprehensive perspective that blends quantifiable results with firsthand knowledge. It also offers a future-oriented perspective on emerging Artificial Intelligence (AI) developments, specifically examining how generative Artificial Intelligence (AI) and quantum technologies may affect commercial applications. The Role Of Digital Acceleration1. Automation and Predictive AnalyticsModern instant monitoring systems have transformed supply chain management by deploying Internet of Things (IoT) sensor networks that generate continuous data streams tracking inventory levels, equipment performance, environmental conditions, and location information throughout the network (MIT Center for Transportation & Logistics, 2024). These systems combine RFID and blockchain technology to ensure endto-end traceability and provenance verification, while computer vision capabilities enable automated quality inspection and warehouse monitoring without human interaction (Dehan et al., 2026). Intelligent automatic alert systems prioritize notifications based on impact severity and importance, ensuring that major issues are addressed immediately, while digital dashboards provide key stakeholders with role-based, real-time visibility across all supply chain tiers. The automation built into these systems has reduced manual data entry errors from 1-5% to near zero, significantly improving data accuracy and reliability (Borah et al., 2024). Most crucially, continuous monitoring capabilities enable firms to spot micro-deviations in operations before they turn into macro-disruptions, permitting proactive rather than reactive supply chain management.
Naval & Maritime Academy Logistics Conference - 202628Our predictive analytics architecture uses sophisticated forecasting and risk assessment capabilities to drive proactive supply chain management. To predict future trends and patterns, the system uses time-series forecasting techniques such as ARIMA, exponential smoothing, and neural network models (Thi et al., 2026). We’ve developed robust risk assessment algorithms that consistently evaluate supplier financial status, geopolitical exposure, and operational soundness, enabling us to detect weaknesses before they cause problems. The architecture includes powerful predictive maintenance models that analyse vibration, thermal, and acoustic monitoring data to forecast equipment failures 7-14 days in advance, resulting in significant reductions in unplanned downtime (Mao, 2025). Our demand sensing capabilities go beyond traditional historical sales research by incorporating real-time signals from sources such as weather patterns, social media mood, and financial indicators, yielding more sophisticated insights into market dynamics. To protect supply chain integrity, we have included anomaly detection algorithms that detect unexpected patterns that may indicate fraud, quality concerns, or process irregularities, enabling prompt intervention (Masum et al., 2026).The system’s scenario planning engines run Monte random simulations across thousands of possible disruption scenarios, allowing us to plan for various situations and build resilience (McKinsey & Company, 2025). Finally, our early warning systems provide important 48-72-hour notice of anticipated stockouts, delays, or capacity restrictions, allowing operations teams enough time to formulate contingency plans and maintain service levels.Modern supply chains require evolved risk-reduction strategies that help firms transition from reactive firefighting to proactive risk management, leveraging predictive signals and advanced analytics. Core to this technique is multi-tier supplier risk mapping, which reveals hidden dependencies and concentration concerns that would otherwise go undetected until a crisis occurs. This extensive insight enables dynamic safety stock optimization, balancing the competing pressures of inventory costs with the potential impact of stockouts (Ahmad et al., 2015). When danger thresholds are exceeded, automated contingency plan activation enables a timely response without the delays inherent in manual decision-making procedures. Organizations that apply these strategies frequently see a 30-50% reduction in unexpected supply chain interruptions, while also improving business continuity and achieving 40-60% faster recovery times when disruptions do occur. Organizations that apply these strategies frequently see a 30-50% reduction in unexpected supply chain interruptions, while also improving business continuity and achieving 40-60% faster recovery times when disruptions do occur (McKinsey & Company, 2025). Aside from operational advantages, predictive risk assessments enable more calculated approaches to insurance and financial hedging, allowing businesses to maximize risk transfer methods based on evidence rather than historical assumptions or industry benchmarks.
Naval & Maritime Academy Logistics Conference - 2026292. Machine Learning ApplicationsThe emergence of demand forecasting is among the most significant advancements in supply chain analytics. While older statistical methods typically achieve forecast accuracy rates of 60-75%, current machine learning algorithms have improved this to 75-90% (Kagalwala, 2025). This improvement results from using ensemble approaches that integrate multiple high-level algorithms, such as XG Boost, Random Forests, and Long Short Term Memory (LSTM) neural networks, to achieve higher predictive performance (Mao, 2025). These cutting-edge systems use thorough feature engineering to account for hundreds of demand variables, including promotional activity and holiday patterns, as well as weather conditions, rival actions, and macroeconomic data. The granularity of forecasting has also changed, from aggregate monthly estimates to extremely granular SKU-location-day forecasts that enable more precise inventory management. Specialized approaches have been developed for specific forecasting challenges, such as new product introductions that leverage comparable product performance data and market signals, and intermittent demand patterns for slow-moving items that use improved versions of Croston’s method augmented with machine learning. Consensus forecasting enriches these systems by combining statistical forecasts with crucial sales inputs and market intelligence from human professionals. The verified commercial impact of these modifications is significant, with 15-30% improvements in accuracy resulting in 10-20% reductions in inventory and 5-15% increases in revenue due to enhanced product availability (Kagalwala, 2025).Dynamic decision optimization is the operational heartbeat of contemporary supply chain management, allowing companies to make optimal decisions in real time as conditions change. Real-time inventory allocation algorithms continuously determine the optimal stock positioning across the entire distribution network, whereas dynamic pricing engines adjust prices based on complex calculations that include demand elasticity, rival positioning, and current inventory levels (Ahmad et al., 2015). Multi-echelon inventory optimization has changed how businesses determine optimal stock levels by assessing each node in the supply chain and balancing service levels with carrying costs. Production scheduling methods strike a fine balance between capacity constraints, changeover costs, and competing customer requirements to maximize production while minimizing costs (Masum et al., 2026). Transportation route optimization has advanced substantially, responding in real time to traffic conditions, weather disruptions, fuel price fluctuations, and delivery time windows to secure efficient, timely deliveries. To discover effective sourcing strategies, suppliers today use algorithms that assess multiple factors simultaneously, such as cost, quality indicators, lead times, and other risk considerations. Make-or-buy decisions have evolved beyond simple cost comparisons to include total cost of ownership assessments and strategic factors that influence the long-term competitive posture (Mao, 2025). Perhaps most interesting is the introduction of reinforcement learning agents that continuously improve their decision-making through trial-and-error learning in sophisticated simulated settings, allowing them to learn from experience without incurring real-world consequences.
Naval & Maritime Academy Logistics Conference - 202630Prescriptive analytics is the cutting edge of supply chain intelligence, going beyond simple prediction to actively recommend optimal courses of action (Thi et al., 2026). This paradigm shift moves companies beyond the question of “what will happen” and toward the more important question of “what should we do.” These cutting-edge systems use sophisticated approaches, such as stochastic programming and resilient optimization, to optimize under uncertainty, accounting for unreliability and risk in decision-making (Mao, 2025). What-if analysis tools allow managers to test and appraise potential decisions in a risk-free environment before committing themselves to their implementation in the real world. Technology generates automated action suggestions that include confidence ratings and comprehensive risk assessments, providing decision-makers with both direction and transparency (Dehan et al., 2026). Closed-loop systems have emerged that can perform prescribed activities automatically within precisely defined boundaries, enabling quick response to routine events while maintaining reasonable oversight. The incorporation of explainable Artificial Intelligence (AI) capabilities fulfils the important need for openness by providing clear explanations for why specific recommendations are made, thereby increasing confidence and enabling better human decision-making. The architecture adheres to a person-in-the-loop design philosophy, which leaves critical, high-stakes decisions to humans while automating standard choices, achieving an optimal mix of efficiency and supervision by leveraging the capabilities of both artificial and human intelligence (Mitra et al., 2021).3. Data Integration and ManagementModern supply chain analytics is based on integrating data from several sources to produce a complete operating picture. Enterprise systems act as the core layer, with ERP systems recording transactional data, WMS systems tracking warehouse operations, TMS systems handling transportation logistics, and MES systems monitoring factory execution. Beyond internal systems, firms use external data streams such as supplier portals, customer point-of-sale data, weather services, economic databases, news feeds, and social media insights. Unstructured data sources, such as emails, contracts, quality reports, and service records, require natural language processing to generate actionable intelligence(Simchi-levi et al., no date). Real-time streaming data from Internet of Things sensors, GPS trackers, and connected assets delivers dynamic insight into operations as they occur. Organizations employ data lakes and warehouses as centralised repositories with controlled access to manage this diverse data landscape, and middleware and APIs facilitate seamless data transfer across multiple systems (Mao, 2025). By ensuring uniform definitions of partners, goods, and locations across all systems, master data management establishes a single basis for analytics and decision-making.