This study analyzes how the equity-return dependency network of publicly traded shipping firms changed between the pre-COVID and post-COVID periods. Using weekly returns for 30 listed shipping firms, we combine distance correlation, Planar Maximally Filtered Graph filtering, Leiden community detection, betweenness centrality, and the participation coefficient to examine nonlinear dependence, community structure, and cross-cluster bridging roles. The results show that the post-COVID network is better characterized by reconfiguration than by uniform strengthening of dependencies. The number of communities and modularity remain broadly stable across the two periods, while community composition, cluster cohesion, and bridging roles change. The post-COVID representative partition has a modestly higher silhouette score but lower run-to-run clustering stability. Tanker-related firms remain cohesive, although their cross-cluster bridging role becomes more concentrated in the post-COVID network. The findings provide a network-based account of structural change in the listed shipping-equity sample and identify firms relevant for cross-cluster transmission and risk monitoring.
Over the past two decades, maritime logistics research has expanded rapidly alongside globalisation, port system transformation, and the increasing integration of shipping into global supply chains. The discipline has evolved into a broad and heterogeneous research field spanning shipping, ports, supply chains, digitalisation, sustainability, and resilience. While this expansion has enriched the literature, it has also led to conceptual fragmentation and overlapping research agendas. Thus, the objective of this paper is to provide a systematic and reproducible mapping of the intellectual structure of maritime logistics research using a semantic-network approach based on text embeddings and community detection algorithms. Drawing on a comprehensive corpus of peer-reviewed publications, we identify eight major thematic domains, further decomposed into eleven clusters and fifteen sub-clusters, capturing both established and emerging research streams. Unlike traditional bibliometric reviews relying on keywords or citations, the proposed approach captures semantic proximity between concepts, allowing for a more nuanced representation of interdisciplinary linkages within maritime logistics. The findings clarify how research on shipping operations, port systems, maritime supply chains, digital technologies, environmental regulation, and resilience has co-evolved, while also highlighting underexplored intersections and future research opportunities. By offering a transparent taxonomy and research roadmap, the paper contributes to a clearer conceptual understanding of maritime logistics and provides practical guidance for scholars, doctoral researchers, and policy-oriented maritime institutions.
Shipyards constitute strategic maritime infrastructure in archipelagic settings because marine transport supports territorial cohesion, connectivity, and regional integration. However, shipyard growth in island peripheries is constrained not by a single market or technological factor, but by the interaction of fragmented demand, limited technical capacity, and weak governance arrangements. This paper examines how governance shapes shipyard and maintenance, repair, and overhaul (MRO) development in Maluku Province, Indonesia. Using a qualitative case study approach, the study draws on semi-structured interviews with public authorities, private shipyard operators, shipyard service users, and quasi-public maritime stakeholders, supported by NVivo-facilitated thematic analysis and triangulation with policy and contextual documents. The findings show that shipyard and MRO development is hampered by fragmented demand, limited docking infrastructure, weak central-regional policy coordination, informal public-private collaboration, and high investment risk stemming from regulatory uncertainty and policy fragmentation. These conditions reinforce one another and discourage long-term investment and capacity growth. The analysis demonstrates that shipyard development in peripheral archipelagic regions is a governance-mediated problem in which dispersed demand, weak coordination, informal collaboration, and investment uncertainty interact. The study argues that multi-level policy coordination, institutionalized collaboration, demand aggregation, and investment-risk mitigation are essential for improving shipyard and MRO performance in archipelagic regions.
Purpose This study aims to provide a comprehensive evaluation of last-mile delivery (LMD) service quality in Vietnam by integrating the SERVQUAL framework with the Fuzzy-Kano model and Importance–Performance Analysis (IPA), thereby identifying the service attributes that most significantly influence customer satisfaction and clarifying strategic priorities for service enhancement. Methodology Building on SERVQUAL, fifteen LMD service attributes were formulated and expert-validated, after which data collected from 184 customers underwent Fuzzy-Kano analysis (α = 0.5) to capture uncertainty in evaluations, followed by IPA using median thresholds to determine strategic priorities. Finding: Findings reveal that increasing the speed of complaint resolution and addressing lost or damaged goods more promptly are top priorities for improvement, whereas intact packaging, timely delivery, and accurate order fulfillment constitute essential attributes that must be reliably maintained. These results highlight the asymmetric contribution of service attributes to customer satisfaction and point to the operational areas that warrant focused managerial attention. Originality This study is one of the first to combine SERVQUAL, Fuzzy-Kano, and IPA into a unified framework for assessing LMD service quality in Vietnam, offering a more objective and comprehensive approach than traditional single-method evaluations.
This paper examines how improvements in logistics performance in Belt and Road Initiative partner countries influence China’s bilateral trade, with a focus on measurement and export-import asymmetries. Because the World Bank’s Logistics Performance Index (LPI) is survey-based and potentially noisy, we construct a text-based, BERT-adjusted LPI (BLPI) that augments the original six dimensions using country-level institutional and policy texts. Empirical results show that better logistics performance in partner countries generates a large, positive, and statistically robust increase in China’s exports, while having no significant effect on imports. Sectoral analysis indicates that logistics improvements promote exports across major product categories, particularly in chemicals and machinery and transport equipment, whereas import effects are weak and largely absent for resource-based goods such as mineral fuels. Mechanism tests reveal that logistics performance strongly facilitates cross-border e-commerce and that China’s overseas transport infrastructure investments amplify export gains. Decomposition further shows that reliability-related components, logistics service quality, tracking and tracing, and customs efficiency, are the primary drivers of export growth. Overall, logistics improvements along the BRI primarily function as an export-enhancing channel for China, while import patterns remain largely determined by structural factors.
Background Thailand is one of the world’s leading exporters of agricultural food products, yet small and medium enterprises (SMEs) continue to face significant challenges in maintaining efficient cold chain logistics and minimizing food loss and waste. This study investigates the structural relationships between digital transformation adoption readiness, smart management systems, Supply Chain 4.0 operational capabilities (SC40C), organisational capabilities, and food loss and waste minimization among agricultural food SMEs in Thailand. Approach Survey data were collected from 452 SMEs operating in the agricultural food sector and analyzed using structural equation modelling (SEM). Confirmatory factor analysis was conducted to evaluate the reliability and validity of the measurement model. Findings The results indicate that digital transformation adoption readiness and smart management systems are positively associated with SC4OC and organisational capabilities. In turn, organisational capabilities demonstrate a strong positive influence on food loss and waste minimisation. Although the model fit indices indicate a moderate fit (CMIN/DF = 4.251, RMSEA = 0.085, GFI = 0.882, CFI = 0.878), the results provide empirical evidence that technological integration and management system innovation play important roles in improving operational capabilities and reducing food loss within SME cold chain logistics systems. Contribution This study contributes to the emerging literature on Cold Chain Logistics 4.0 in developing economies, highlighting the mechanisms through which digital transformation and smart management practices support operational improvements in resource-constrained SMEs. The findings provide practical insights for managers and policymakers seeking to strengthen cold chain efficiency and reduce food waste in agricultural supply chains.
Existing policy evaluation frameworks often fail to capture multi-dimensional policy characteristics, particularly in complex governance systems. To address this, this study develops a novel quantitative decoding framework that integrates text mining techniques with the Policy Modeling Consistency Index (PMC‑Index) model to enable objective, multi-dimensional policy assessment, thereby reducing the subjectivity inherent in traditional variable selection. Applying this framework to 25 representative national‑level green shipping governance policies in China from 2011 to 2025, this study finds that the policies exhibit an excellent overall consistency. However, the framework also identifies three structural weaknesses: insufficient cross‑departmental collaboration, lack of clear short‑/medium‑/long‑term implementation timelines, and over‑reliance on demand‑side regulatory tools. Based on these findings, this study proposes targeted optimization pathways including multi‑level collaborative governance, balanced policy instrument mixes, and integration into global carbon pricing frameworks. This framework solves the subjectivity problem of variable selection in traditional PMC-Index model and realizes the objective decoding and multi-dimensional quantitative evaluation of complex policy texts, which provides a new scientific method for quantitative evaluation of cross sectoral and multi-dimensional policies.
Chinese ports reached their fourth stage of development in 2013. Based on this context, this study analyzes the efficiency of four-stage ports using time series data on 16 major coastal ports in China from 2010 to 2019, covering the latter half of stage three into stage four. Using Data Envelope Analysis (DEA)-Window and Tobit models, the results indicate that although most ports maintained high efficiency, issues such as inefficient resource use, over-expansion, and a lack of strategic planning were identified. Particularly, based on the average efficiency scores, ports in the central region exhibited relatively lower efficiency levels compared to those on the north and south coasts. Factors such as local population size, industrial productivity, and economic level positively influenced efficiency. In addition, our results showed a negative correlation between port efficiency and loans from financial institutions, suggesting financial support may not always positively contribute to port development. Based on these findings, we propose policy recommendations for the Chinese government, port management authorities, operators, and the international port industry.
There has been a revolutionary shift in manufacturing with each industrial revolution, ushering in new technology and ways of production. This study examines the emerging effects of Industry 5.0 on smart logistics using both quantitative and qualitative assessments conducted between 2015 and 2021. The “quantitative (Comparative Bibliometric Analysis) and qualitative (Content Analysis)” used data from Web of Science and Scopus. The text outlines three crucial differentiations: a transition towards a focus on human needs, increased capacity to withstand challenges, and enhanced commitment to environmental preservation. The research clarifies the concept of smart logistics and promotes its integration with Industry 5.0's four-part intelligence architecture, which includes automation, devices, systems, and materials. Limitations include a lack of consideration for the influence of CO2 emissions on profitability and transportation policy, indicating potential areas for further study. Researchers are encouraged to investigate the intersection of technology, sustainability, and smart logistics, as Industry 5.0 develops as a revolution focused on creating value and prioritizing human needs.
Selection of transportation mode (air, sea, road etc.) for sourcing goods is a critical decision in supply chain management because it directly affects cost efficiency, service flexibility and reliability. Freight cost and delivery lead time are two major decision criteria that dictates the selection process. Traditional methods often fail to account for the dynamic nature of the decision criteria in constrained logistics infrastructure. To address the challenges is logistics decision making, this study proposed a data driven multi-objective optimization (MOO) framework using Mixed-Integer Linear Programming (MILP) to minimize freight cost and lead time simultaneously. The study also developed a weighted sum approach to optimize the selection process. MATLAB intlinprog solver was utilized to solve the optimization problem and find the best route and sensitivity analysis was performed to check the model robustness and response to changes in the weight of decision criteria. A case study of 504 KG yarn shipment from India to Bangladesh was employed to validate the model effectiveness. The results highlighted that the road is the best option that minimizes freight cost and lead time for most of the cases for a given freight charges and lead time in this shipment route. The adoption of this model ensured tangible benefits for the company in terms of freight cost reduction. This optimization model could be an effective tool for flexible decision support system in logistics transportation system.
The COVID-19 pandemic profoundly disrupted global aviation networks, with long-haul connectivity particularly affected. This study assesses the evolving competitive positions of sixteen major hub airports in the Asia-Pacific region by analyzing their transfer-connectivity performance before and after the pandemic. Using flight schedule data from the Innovata Worldwide Flight Schedules Database, three key indicators are employed: Quantity of Viable Connections (QVC), Hub Connectivity Performance Index (HCPI), and Hub Efficiency Index (HEI). Two reference weeks—September 2019 and September 2023—were selected to represent pre- and post-pandemic conditions. The results show that Northeast Asian hubs such as Seoul Incheon (ICN), Tokyo Narita (NRT), and Taipei Taoyuan (TPE) have retained dominant roles in trans-Pacific connectivity, with ICN ranking first in QVC and TPE leading in both HEI and HCPI. TPE also surpassed Hong Kong International Airport (HKG) in QVC, signaling a strategic shift in hub competitiveness. In contrast, airports in mainland China (PEK, PVG, CAN) and HKG experienced significant declines following the pandemic. As the global aviation sector recovers, airports with lower QVC are encouraged to reinstate suspended routes and explore new market pairings, while those with weaker HCPI or HEI performance should focus on reducing connection times and improving schedule coordination. This study provides empirical insights into the post-COVID restructuring of hub dynamics and offers strategic guidance for policymakers and airport authorities committed to restoring and enhancing connectivity in an increasingly competitive global air transport landscape.
Asian air cargo terminals are essential components of global logistics networks, yet many remain of declining quality. This work examines whether digitalization improves the efficiency of terminal operations or just further applies technology at a terminal without operational benefit. The findings are underpinned by an interdependent hybrid approach combining the Best–Worst Method (BWM) and Failure Mode and Effects Analysis (FMEA), informed by expert opinion in the Asian air cargo industry. In the BWM results process integration, information system interoperability, and workflow coordination are the most significant dimensions of performance deficiency. Operational risks related to these priorities are evaluated by FMEA. Using Risk Priority Numbers (RPNs), we find that manual documentation, fragmented information flows, and limited system connectivity have the highest probability of failure. According to the analysis, aligning digital efforts with process redesign reduces high-risk RPN scores by about 60–75%, as failure rates decrease and detection rates increase. The findings highlight that improvements in physical capacity are insufficient to achieve performance gains from digitally enabled process alignment in air cargo terminals. It provides meaningful insights for terminal operators to enhance the operating efficiency, resilience, and competitiveness of Asian air cargo terminals.
This study investigates the effect of integrated governance and digitalization on port logistics performance through Port Digitalization Infrastructure and system, Competent and Certified Port Workers, Integrated Shipping and Trucking, Customer-Oriented Port Services, and Port Environment, Green, and Safety. This study used 23 manifest variables, and data were collected through an online survey from 150 respondent practitioners and direct interviews with experts. Partial least squares structural equation modeling (PLS-SEM) was applied to test the model. The measurement results show that there is a positive and significant total effect of Port integration and digitalization governance through Port Digitalization Infrastructure and System, Integrated Shipping and Trucking, Competent Port Worker Requirements, and Customer-Oriented Port Services on Port Logistics Performance. The current study finds that the implementation of the port-integrated and digitalization governance, supported by infrastructure automation, digitalization system, worker competence, and IT certification, has contributed positively and significantly to encouraging port services based on customer orientation, port environmental and safety, port-integrated shipping and trucking, which indirectly increase the efficiency, effectiveness, and productivity of port logistics performance.
Environmental turbulence, which reflects the degree of complexity, volatility, and unpredictability of the external environment, impacts the performance of logistics service providers (LSPs) and has become vital for LSPs in recent years. Managers depend on logistics capabilities to hedge themselves against environmental turbulence. However, most managers are unaware of the relationship between logistics capabilities and different types of environmental turbulence. This study examines the association between logistics capabilities and environmental turbulence (market, competitive, technological, and regulatory) by adopting a hybrid Fuzzy CRITIC & Fuzzy TAOV method, a Multiple Criteria Decision Making setting. Analysis revealed that technological turbulence has the highest objective weight, followed by competitive, market, and regulatory turbulences. The most desired capabilities are flexibility and agility, followed by resilience, responsiveness, sustainability, robustness, and visibility in order to weather the storm of general environmental turbulence. More specifically, flexibility is essential for managing market turbulence. In response to competitive and regulatory volatility, managers must prioritize agility, while technological turbulence necessitates visibility. The proposed framework guides logistics managers in making strategic decisions regarding the relationship between logistics capabilities and environmental turbulence, and it qualifies as the first endeavor to examine the prominence of logistics capabilities with environmental turbulence.
Background The growing complexity of logistics and supply chain management, particularly in third-party logistics (3PL) providers, highlights the need for effective competency models tailored to evolving operational demands. Current frameworks often lack the technical depth and global applicability required for this context. Approach This study combines a bibliometric analysis and a systematic literature review of publications from 1995 to 2024 to assess existing competency frameworks in the logistics sector. Key themes such as digitalization, sustainability, performance, and strategic management were identified. The review specifically focused on the role of logistics operations managers in 3PL environments. Findings The analysis highlighted the importance of continuous learning and digital competencies such as IoT, AI, and big data analytics for logistics professionals. However, most existing competency models overlook the specific requirements and practical realities of 3PL operations managers. This gap underscores the need for more context-sensitive and field-oriented frameworks in logistics competency research. Contribution In response, this study proposes an integrative, multidimensional competency framework of 3 PL operations manager combining technical, managerial, transversal and linguistics competencies. Designed to be scalable and aligned with global logistics standards, the model provides a robust foundation for competency-based human capital strategies in 3PL and global supply chains.
This study conducts an empirical analysis of the driving factors and development trends of China-Korea bilateral trade from the perspective of logistics, using IBM SPSS Statistics 27 for data processing and modeling. Based on annual panel data from 2013 to 2022, a multidimensional dataset of 18 core economic indicators was constructed, encompassing variables such as import and export volumes, logistics scale, enterprise expenditures, labor structure, exchange rates, and investment. To reduce dimensionality and address multicollinearity, a correlation analysis was first conducted to identify 9 key variables with strong explanatory power. Principal Component Analysis was then applied, extracting five principal components that effectively captured the underlying structure of the dataset. These components were used as independent variables in a principal component regression model to predict the China-Korea bilateral trade volume. Among them, the component representing Korea’s logistics industry scale and transportation efficiency (PC1) had the most significant positive impact on trade, highlighting the critical role of logistics in enhancing trade intensity and sustaining bilateral growth. The regression model exhibited strong goodness-of-fit and low prediction errors, through structural modeling and trend-based forecasting, this study confirms the foundational role of Korea’s logistics system in supporting bilateral trade and provides quantitative insights and policy-oriented recommendations for future China-Korea economic cooperation.
This study explores the application of blockchain (BC) technology in enhancing terminal operations at West African seaports, with a specific focus on Tema Port in Ghana. The purpose is to address inefficiencies in cargo processing, traceability, and data integrity that often impede port performance. Using a multi-layered qualitative approach, including observation and value stream mapping, the study examines current operational challenges at Tema Port and proposes a BC adoption model tailored to ship operations, quay transfers, yard management, container freight stations, and receipt/delivery processes. The findings suggest that BC technology significantly improves transparency, operational efficiency, and data security across port processes, offering a unified ledger system accessible to all stakeholders. Based on these findings, the study recommends a phased BC implementation, beginning with targeted pilot programs to mitigate technological and infrastructural constraints common in developing regions. Implications for port managers, policymakers, and academics underscore BC’s potential to reduce operational costs, enhance real-time visibility, and improve compliance in port logistics. This study is limited by its focus on terminal operations at a single port; future research could explore BC’s impact on other areas of the maritime supply chain across multiple ports. The originality of this study lies in its contextualized BC model for West African ports, addressing specific challenges faced by developing regions and offering a foundational framework for future BC applications in logistics.
Freight transportation modeling represents the economic demand for moving goods across spatial networks. Traditional models often treat transportation mode and destination choice as separate processes. This paper introduces an innovative framework that synthesizes a joint choice structure with a novel, supply-chain-based methodology, an approach underutilized in freight modeling. The core methodological innovation is the use of national input-output accounts to identify specific consumer industries, allowing for a more behaviorally-grounded analysis of destination attractiveness for different commodity groups. Using U.S. Commodity Flow Survey (CFS) data, two multinomial logit models were developed: one for destination choice and another for joint destination-mode choice, across three goods categories. This study also provides a direct empirical comparison in the freight context, with results revealing that the integrated model improves prediction accuracy by approximately 7 % compared to destination-only models. The findings confirm the value of this synthesized approach, which provides a more comprehensive and behaviorally sound tool for freight demand estimation.
This study investigates how digital transformation influences the performance and competitiveness of container ports in Southeast Asia. A Digital Transformation Index was developed to measure the digital maturity of ten major ports across four dimensions: smart infrastructure, integration, governance, and cybersecurity. Combining shift-share analysis and a Super Efficiency DEA model, the study reveals strong correlations between digital maturity and both operational efficiency (r = 0.83) and market share dynamics (r = 0.69). Cluster analysis identifies three port groups based on digital advancement and performance outcomes, highlighting a persistent digital divide in the region. The originality of this research lies in its integrated empirical framework that links digital readiness to strategic port performance using multidimensional indicators. The findings provide practical insights for policymakers and port authorities seeking to enhance competitiveness through targeted digital investment and governance reforms, while contributing new empirical evidence to the literature on smart port development in emerging maritime economies.
The logistics industry is among the top threats to the sustainability despite its valuable contribution to trade and growth. Despite previous efforts on the impact of logistics performance (LP), its role in driving sustainability within the transport sector is less discussed. Also, while it is generally anticipated that the impact of LP may vary depending on the levels of economic development, there has been no empirical study in this regard. This study therefore attempts to bridge these gaps by comparing between less developed economies; Sub-Saharan Africa (SSA) and developed economies (OECD). Panel dataset between 2007 and 2018 for 24 SSA countries and 34 OECD economies. The Generalized Method of Moments estimators were employed and findings showed a positive effect of logistic efficiency on transport sustainability. The findings revealed no significant variation within the economies. Even though the gravity of the effect remain higher in SSA, LP was found to worsen transport sustainability in both economies. Additionally, we noted only the timeliness of logistics service out of the six (6) sub-dimensions of LP significantly increases CO2 from transport. The findings offers a compelling insight which contradicts conventional wisdom that situations in advanced economies are always highly better. Practically, the findings implies that, regardless of the level of development in the economy, supply chain or logistics activities continue to be far from de-carbonization in both economies. Governments must therefore double efforts towards decarbonizing of modern supply chains though green logistics, if the Net Zero Emission target of 2025 is to be achieved.
