ABSTRACT Grounded in dynamic capabilities theory, this study aims to understand the influence of collaboration networks on supply-chain innovation and performance in the context of emerging markets of developing economies. This study sets a boundary condition by introducing strategic agility as a moderator to these relationships and a three-way interaction of AI integration, strategic agility and collaboration network on supply-chain innovation. Data from 351 construction firms in emerging markets were analysed based on confirmatory factor analysis and structural equation modelling through AMOS 24 and SPSS 23, respectively. The findings highlight collaboration networks as essential for mitigating uncertainties and driving innovation, with strategic agility enhancing their effectiveness. AI integration further strengthens this relationship, validating agility and AI as dynamic capabilities in volatile markets. The results offer important implications for managers to invest in robust collaboration networks, foster strategic agility and integrate AI to navigate uncertainties and sustain innovation.

ABSTRACT The integration of large language models into business is complex, causing unclear roles, development challenges, and trust issues. To address this gap, this study examines how ChatGPT enhances the resilience of the pharmaceutical supply chain through paradoxical cognition, agility, and flexibility. Using a quantitative design, data were collected from Pakistani pharmaceutical firms and analyzed using Partial Least Squares Structural Equation Model (PLS-SEM), Importance-Performance Map Analysis (IPMA), and Necessary Condition Analysis (NCA). The research results show that ChatGPT's strategic advantages enhance paradox identification, supply chain agility, and resilience, but they are constrained by distrust of AI tools. Furthermore, a lack of trust in AI can influence perceptions of supply chain paradoxes and agility, underscoring psychological barriers to technology adoption. The study shows that ChatGPT’s strategic value primarily boosts resilience by improving paradox cognition and agility, and that high distrust in AI greatly reduces these effects on pharmaceutical supply chain resilience.

ABSTRACT With rapid expansion of cross-border e-commerce, export commodity variety has increased and its logistics has become both time- and cost-sensitive, making it hard for direct-mail and overseas warehousing models to simultaneously achieve fast delivery and cost efficiency. This paper proposes an origin-based warehousing model enabled by express liner shipping and formulates a demand-response mechanism that translates transportation impedance improvement into freight demand changes. Then the express liner’s sailing speed, vessel size, and service frequency are optimised to maximise the gap between e-commerce export sales and costs for transportation and inventory. A Shanghai-Fukuoka case study indicates that the optimal operation involves two 230-TEU vessels operating at a speed of 28 knots, with three sailings per week. Sensitivity analysis identifies a strategic speed range (26–29 knots) that buffers marine fuel price volatility and stabilises economic performance. The results provide quantitative evidence for transportation model innovation in other bilateral trade markets.

ABSTRACT This study empirically investigates the interplay between Green Finance (GF), digital technologies, and smart renewable energy supply chains within an AI-empowered Physical Internet (PI) framework. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) on survey data from 498 industrial managers in Egypt, we demonstrate that GF is a critical catalyst for Smart renewable energy supply chain management adoption. Big Data Analytics (BDA) significantly strengthens this relationship by enabling predictive logistics optimisation, whereas Blockchain's (BCT) moderating effect is currently limited. Furthermore, Smart renewable energy supply chain management acts as a key mediator, translating GF into substantial environmental and social performance gains, though its short-term economic impact is less pronounced. The findings offer policymakers a validated model for designing targeted GF mechanisms and provide managers with a strategic roadmap for prioritising data analytics investments to build sustainable, efficient energy logistics systems.

ABSTRACT This study aims to evaluate the Drone Adoption Initiatives (DAIs) to achieve Sustainable Development Goals (SDGs) within the Indian logistics sector. A total of 37 SDG targets are identified through keyword-based text mining and mapped to 34 DAIs; subsequently, 19 targets are shortlisted for the final SF-TODIM evaluation. The findings reveal that the development of safe landing and charging stations, creation of dedicated drone corridors, and establishment of robust regulatory frameworks are the top DAIs for achievement of SDGs. Significant SDGs achieved due to DAIs are related to sustainable transportation (SDG11.2), policy alignment (SDG17.14), and economic productivity (SDG8.2). DAIs facilitate the development of specific transport policies that address needs of diverse stakeholders, including regulators, logistics providers, urban planners, and end-users. This study offers theoretical and managerial insights by linking DAIs to SDGs and provides a practical roadmap for policymakers, urban planners, and logistics managers.

ABSTRACT The digital economy promotes China’s high-quality economic development, with cross-border e-commerce transforming foreign trade. By implementing advanced management models and institutional support, cross-border e-commerce pilot zones enhance trade convenience, flexibility, and standardisation, thereby fostering greater openness in China’s foreign trade. This study analyzes panel data from seven batches of pilot cities approved between 2010 and 2021, using a multi-period Difference-in-Difference model to assess their impact on regional foreign trade competitiveness. Empirical results, supported by parallel trend tests and robustness checks, confirm a significant positive effect. Although the effects of the policy vary, the establishment of pilot zones significantly enhance regional foreign trade competitiveness. This study also elucidates the policy effects through a logistics and supply-chain lens: the pilots reduce fulfilment lead times and uncertainty via bonded warehouses, smart customs clearance, trunk-feeder connectivity, and reverse logistics, while green transport and digital warehousing enhance the resilience and sustainability of foreign trade competitiveness. Furthermore, mediation effect testing demonstrates that pilot zones enhance competitiveness by optimising industrial structure and fostering economic development. Consequently, the study recommends leveraging localised development models, maximising policy synergies, and fostering industrial clustering to sustain the positive effects of these pilot zones on regional foreign trade competitiveness.

ABSTRACT During public health emergencies, vaccine supply chains (VSCs) face systemic challenges including information silos, slow risk responses, and poor traceability. Generative AI offers a new approach to rebuilding VSC security governance with its strong multi-source data processing and knowledge generation capabilities. This paper develops the 3D-DeGAI model. Using a dual knowledge-driven framework and CAS theory, 32 core risk factors are identified. With LLM-guided causal inference, a causal network with 432 directed edges is built to reveal whole-chain risk transmission, including radiation, convergence, and bridging effects, and 30 key risk paths are recognized. Simulation results verify the model's adaptability and robustness. It effectively captures implicit risk correlations, supports risk fuse design, and enhances supply chain resilience. This interdisciplinary method can assist the WHO vaccine implementation plan and inform intelligent VSC safety management.

ABSTRACT This study examines subscription strategies of competitive logistics data providers (LDPs) for AI-driven data analytics services from Cyber-Physical Internet (CPI) in the logistics data supply chain. Using a game-theoretical model, we find that when the product competition is low, the equilibrium strategy shifts from both LDPs opting for CPI services to neither doing so as the service effort cost rises. When the product competition is high, with the service effort cost elevation, it transitions from one LDP opting for CPI services to both, then back to one, and ultimately to neither doing so. Notably, the equilibrium strategy of both LDPs subscribing to CPI services does not universally benefit CPI and consumers under the high product competition, while the low service effort cost prompts one or both LDPs to do so, achieving a win-win-win outcome. These findings provide managerial insights for LDPs on collaborating with CPIs to subscribe to AI-driven data analytics services.

ABSTRACT Closed-loop supply chain network design has garnered significant interest due to its potential for enhancing sustainability, reducing waste, and improving resource efficiency. Over the past decade, several literature reviews have examined CLSC from various aspects. However, no previous study has been explicitly carried out to systematically review the ‘practical real-world case studies’ related to the CLSC network design. This study aims to fill this gap by analysing 143 published articles between 2003 and 2023. The articles are analysed in terms of (1) CLSC design modelling approaches, (2) solution methods, (3) classification by industry sector, and (4) future gaps and potential study directions. Several gaps are identified, including the underrepresentation of quality uncertainties in returned products, the lack of integration of carbon trading mechanisms, and the scarcity of consideration of returns recovery strategies in developing mathematical models. Our findings emphasise the necessity for empirical research incorporating real-world complexities and sustainability metrics.

ABSTRACT The promotion and application of remanufactured prefabricated module products (RPMP) from construction and demolition waste can substantially reduce the demand for natural resource extraction, alleviate ecological and environmental pressures, and support the transition towards a green, low-carbon economy. However, existing market mechanisms for trading these prefabricated components suffer from high transaction costs and inefficient pricing. To address the aforementioned issues, the objective of this study is to develop an innovative two-stage model to enhance resource matching efficiency and transaction benefits. The model is designed within the framework of the physical internet (PI), which provides an open, interconnected, and shared logistics network. The first stage constructs a resource matching model for the RPMP based on a double auction mechanism to determine the winning sellers (construction waste remanufacturers) and buyers (construction companies). The second stage further develops a transport model optimised within a PI framework for both parties, employing mathematical programming to dynamically minimise logistics costs by leveraging the PI’s capabilities for open resource sharing and interconnected logistics networks. Moreover, this study has been verified through numerical simulations and comparative experiments that this mechanism significantly outperforms the fixed price mechanism in terms of total social welfare, buyer and seller utility, and total transaction volume. Specifically, compared to the traditional fixed price mechanism, the proposed two-stage model enhances total social welfare by 10.6&per;. Sensitivity analyses further confirm the model’s robustness and adaptability across varying participant numbers and valuation intervals. This study fills gaps in the design of RPMP trading mechanisms and the optimisation of transport coordination within the PI paradigm, proposing a methodological framework integrating auction theory and PI-based logistics optimisation. Practically, these findings offer novel insights for buyers, sellers, and platforms in handling construction waste recycling and reusing transactions within the emerging PI ecosystem.