Search Results (657)

In today’s volatile supply chain environment, organizations require flexible and collaborative procurement strategies. Swap contracts, originally developed as financial instruments, have recently been adopted to address inventory imbalances—such as the 2021 COVID-19 vaccine swap between South Korea and Israel. Despite its increasing adoption in the real world, theoretical studies on swap-based procurement remain limited. This study proposes an integrated model that combines buyer-to-buyer swap agreements with long-term wholesale contracts under demand uncertainty. The model quantifies the expected swap quantity between parties and embeds it into the profit function to derive optimal order quantities. Numerical experiments are conducted to compare the performance of the proposed strategy with that of a baseline wholesale contract. Sensitivity analyses are performed on key parameters, including demand asymmetry and swap prices. The numerical analysis indicates that the swap-integrated procurement strategy consistently outperforms procurement based on long-term wholesale contracts. Moreover, the results reveal that under the swap-integrated strategy, the optimal order quantity must be adjusted—either increased or decreased—depending on the demand scale of the counterpart and the specified swap price, deviating from the optimal quantity under traditional long-term contracts. These findings highlight the potential of swap-integrated procurement strategies as practical coordination mechanisms across both private and public sectors, offering strategic value in contexts such as vaccine distribution, fresh produce, and other critical products. Full article

Marine biomass, particularly from waste streams, by-products, underutilized, invasive, or potential cultivable marine species, offers a sustainable source of high-value biopolymers such as collagen and chitin. These macromolecules have gained significant attention due to their biocompatibility, biodegradability, functional versatility, and broad applicability across health, food, wellness, and environmental fields. This review highlights recent advances in the uses of marine-derived collagen and chitin/chitosan. In alignment with the United Nations Sustainable Development Goals (SDGs), we analyze how these applications contribute to sustainability, particularly in SDGs related to responsible consumption and production, good health and well-being, and life below water. Furthermore, we contextualize the advancement of product development using marine collagen and chitin/chitosan within the European Union’s Blue bioeconomy strategies, highlighting trends in scientific research and technological innovation through bibliometric and patent data. Finally, the review addresses challenges facing the development of robust value chains for these marine biopolymers, including collaboration, regulatory hurdles, supply-chain constraints, policy and financial support, education and training, and the need for integrated marine resource management. The paper concludes with recommendations for fostering innovation and sustainability in the valorization of these marine resources. Full article

The logistics industry faces challenges from evolving consumer expectations, technological advances, sustainability demands, and market disruptions. Logistics collaboration is in theory perceived as one of the most promising solutions to solve these issues, but here are still a lot of challenges that needs to be better understood and addressed. While vertical collaboration among supply chain actors is well advanced, horizontal collaboration among competing service providers remains under-explored. This study developed a novel methodology based on the COM-B behaviour-change framework to better understand the main challenges, opportunities, capabilities and drivers that would motivate competing companies to exploit the potential of horizontal logistics collaboration. A survey was designed and conducted among 71 logistics service providers in Slovenia, chosen for its fragmented market and low willingness to collaborate. Statistical analysis reveals cost reduction (M = 4.21/5) and improved vehicle utilization (M = 4.29/5) as the primary motivators. On the other hand, maintaining company reputation (M = 4.64/5), fair resource sharing (M = 4.20/5), and transparency of logistics processes (M = 4.17/5) all persist as key enabling conditions. These findings underscore the pivotal role of behavioural drivers and suggest strategies that combine economic incentives with targeted trust-building measures. Future research should employ experimental designs in diverse national contexts and integrate vertical–horizontal approaches to validate causal pathways and advance theory. Full article

Under China’s “Rural Revitalisation” strategy, contract farming faces challenges including farmers’ limited access to advanced technologies and high operational risks for agricultural support enterprises. The collaborative involvement of scientific research institutions offers potential solutions but remains underexplored. This study employs Stackelberg game theory to model a contract farming supply chain under two agricultural assistance modes: enterprise-led (EL) and collaborative assistance with scientific research institutions (CI). We further propose two government subsidy mechanisms: subsidies to enterprises and subsidies to scientific research institutions. The models analyze optimal decisions, supply chain performance, and subsidy efficiency, validated through numerical experiments. Key findings reveal the following: (1) The CI mode enhances agricultural output and farmer revenue but may reduce enterprise profits, deterring collaboration. (2) Government subsidies incentivize enterprise–institution collaboration. Subsidizing scientific research institutions typically improves agricultural productivity and economic benefits more effectively than subsidizing enterprises. (3) Synergistic effects exist among the government subsidy coefficient, cost coefficient of technical assistance, consumer preferences for agricultural quality, and profit-sharing ratio. The latter three parameters significantly influence subsidy model selection. This research provides policy insights for enhancing agricultural assistance efficiency and sustainable contract farming development. Full article

The global food industry is facing growing pressure to enhance food safety, extend shelf life, minimize waste, and adopt environmentally sustainable packaging solution. Nanotechnology offers innovative ways to meet these demands by enabling the creation of smart and sustainable food packaging systems. Due to their unique properties, nanomaterials can significantly enhance the functional performance of packaging by boosting mechanical strength, barrier efficiency, antimicrobial activity, and responsiveness to environmental stimuli. This review provides a comprehensive overview of nanomaterials used as smart and sustainable food packaging, focusing on their role in active and intelligent packaging systems. By integrating nanomaterials like metal and metal oxide nanoparticles, carbon-based nanostructures, and nano-biopolymers, packaging can now perform real-time sensing, spoilage detection, and traceability. These systems improve food quality management and supply chain transparency while supporting global sustainability goals. The review also discusses potential risks related to nanomaterials’ migration, environmental impact, and consumer safety, as well as the current regulatory landscape and limitations in industrial scalability. Emphasis is placed on the importance of standardized safety assessments and eco-friendly design to support responsible innovation. Overall, nano-enabled smart packaging represents a promising strategy for advancing food safety and sustainability. Future developments will require collaboration across disciplines and robust regulatory frameworks to ensure the safe and practical application of nanotechnology in food systems. Full article

Collaborative business ecosystems (CBEs) are increasingly exposed to disruptive events (e.g., pandemics, supply chain breakdowns, cyberattacks) that challenge organizational adaptability and value creation. Traditional approaches to resilience and robustness often fail to capture the full range of systemic responses. This study introduces a unified mathematical framework to evaluate four crisis response modes—plasticity, resilience, transformative resilience, and antifragility—within complex adaptive networks. Grounded in complex systems and collaborative network theory, our model formalizes both internal organizational capabilities (e.g., adaptability, learning, innovation, structural flexibility) and strategic interventions (e.g., optionality, buffering, information sharing, fault-injection protocols), linking them to pre- and post-crisis performance via dynamic adjustment functions. A composite performance score is defined across four dimensions (Innovation, Contribution, Prestige, and Responsiveness to Business Opportunities), using capability–strategy interaction matrices, weighted performance change functions, and structural transformation modifiers. The sensitivity analysis and scenario simulations enable a comparative evaluation of organizational configurations, strategy impacts, and phase-transition thresholds under crisis. This indicator-based formulation provides a quantitative bridge between resilience theory and practice, facilitating evidence-based crisis management in networked business environments. Full article

The construction sector significantly contributes to global environmental degradation through intensive resource extraction, high energy consumption, and substantial waste generation. Addressing this unsustainable trajectory requires integrated approaches that simultaneously improve operational efficiency and material circularity. Lean Construction (LC) and Circular Economy (CE) offer complementary frameworks for enhancing process performance and reducing environmental impacts. However, their combined implementation remains underdeveloped and fragmented. This study conducts a systematic literature review (SLR) of 18 peer-reviewed articles published between 2010 and 2025, selected using PRISMA 2020 guidelines and sourced from Scopus and Web of Science databases. A mixed-method approach combines bibliometric mapping and qualitative content analysis to investigate how LC and CE are jointly operationalized in construction contexts. The findings reveal that LC improves cost, time, and workflow reliability, while CE enables reuse, modularity, and lifecycle extension. Integration is further supported by digital tools—such as Building Information Modelling (BIM), Design for Manufacture and Assembly (DfMA), and digital twins—which enhance traceability and flow optimization. Nonetheless, persistent barriers—including supply chain fragmentation, lack of standards, and regulatory gaps—continue to constrain widespread adoption. This review identifies six strategic enablers for LC-CE integration: crossdisciplinary competencies, collaborative governance, interoperable digital systems, standardized indicators, incentive-based regulation, and pilot demonstrator projects. By consolidating fragmented evidence, the study provides a structured research agenda and practical insights to guide the transition toward more circular, efficient, and sustainable construction practices. Full article

Cybersecurity represents a critical challenge for data-sharing platforms involving multiple stakeholders, particularly within complex and decentralized systems such as livestock supply chain networks. These systems demand novel approaches, robust security protocols, and advanced data management strategies to address key challenges such as data consistency, transparency, ownership, controlled access or exposure, and privacy-preserving analytics for value-added services. In this paper, we introduced the Framework for Livestock Empowerment and Decentralized Secure Data eXchange (FLEX), as a comprehensive solution grounded on five core design principles: (i) enhanced security and privacy, (ii) human-centric approach, (iii) decentralized and trusted infrastructure, (iv) system resilience, and (v) seamless collaboration across the supply chain. FLEX integrates interdisciplinary innovations, leveraging decentralized infrastructure-based protocols to ensure trust, traceability, and integrity. It employs secure data-sharing protocols and cryptographic techniques to enable controlled information exchange with authorized entities. Additionally, the use of data anonymization techniques ensures privacy. FLEX is designed and implemented using a microservices architecture and edge computing to support modularity and scalable deployment. These components collectively serve as a foundational pillar of the development of a digital product passport. The FLEX architecture adopts a layered design and incorporates robust security controls to mitigate threats identified using the STRIDE threat modeling framework. The evaluation results demonstrate the framework’s effectiveness in countering well-known cyberattacks while fulfilling its intended objectives. The performance evaluation of the implementation further validates its feasibility and stability, particularly as the volume of evidence associated with animal identities increases. All the infrastructure components, along with detailed deployment instructions, are publicly available as open-source libraries on GitHub, promoting transparency and community-driven development for wider public benefit. Full article

Healthcare supply chain management operates amid fluctuating patient demand, rapidly advancing biotechnologies, and unpredictable supply disruptions pose high risks and create an imperative for sustainable resource optimization. This study investigates the underlying mechanisms through which digital intelligence drives strategic decision optimization in healthcare supply chains. Drawing on the Resource-Based View and Dynamic Capabilities Theory, we develop a chain-mediated model, defined as the multistage indirect path whereby digital intelligence first bolsters innovation capability, which then activates supply chain resilience (absorptive, response, and restorative capability), to improve decision optimization. Data were collected from 360 managerial-level respondents working in healthcare supply chain organizations in China, and the proposed model was tested using structural equation modeling. The results indicate that digital intelligence enhances innovation capability, which in turn activates all three dimensions of resilience, producing a synergistic effect that promotes sustained decision optimization. However, the direct effect of digital intelligence on decision optimization was not statistically significant, suggesting that its impact is primarily mediated through organizational capabilities, particularly supply chain resilience. Practically, the findings suggest that in the process of deploying digital intelligence systems and platforms, healthcare organizations should embed technological advantages into organizational processes, emergency response mechanisms, and collaborative operations, so that digitalization moves beyond the technical system level and is truly internalized as organizational innovation capability and resilience, thereby leading to sustained improvement in decision-making performance. Full article

This paper explores the strategic implications of technological adoption within shipping logistics service supply chains, with a particular focus on blockchain technology (BCT). When integrating new technologies, supply chain stakeholders evaluate associated risks alongside complexity, profitability, and operational challenges, which influence their strategic behaviors. Anchored in the concept of technology trust, this study examines how different risk preferences affect BCT adoption decisions and freight rate strategies. A game-theoretic model is constructed using a mean-variance utility framework to analyze interactions between shipping companies and freight forwarders under three adoption scenarios: no adoption (NN), partial adoption (BN), and full adoption (BB). The results indicate that risk-seeking agents are more likely to adopt BCT early but face greater freight rate volatility in the initial stages. As the technology matures, strategic variability declines and the influence of adaptability on pricing becomes less pronounced. In contrast, risk-neutral and risk-averse participants tend to adopt more conservatively, resulting in slower but more stable pricing dynamics. These findings offer new insights into how technology trust and risk attitudes shape strategic decisions in digitally transforming supply chains. The study also provides practical implications for differentiated pricing strategies, BCT adoption incentives, and collaborative policy design among logistics stakeholders. Full article

As global climate change intensifies and the transition to clean energy accelerates, lithium-ion batteries—critical components of electric vehicles—are becoming increasingly vital in international trade networks. This study investigates the structural evolution and determinants of the electric vehicle lithium-ion battery trade network among European Union (EU) member states from 2012 to 2023, employing social network analysis and the multiple regression quadratic assignment procedure method. The findings demonstrate the transformation of the network from a centralized and loosely connected structure, with Germany as the dominant hub, to a more interconnected and decentralized system in which Poland and Hungary emerge as the leading players. Key network metrics, such as the density, clustering coefficients, and average path lengths, reveal increased regional trade connectivity and enhanced supply chain efficiency. The analysis identifies geographic and economic proximity, logistics performance, labor cost differentials, energy resource availability, and venture capital investment as significant drivers of trade flows, highlighting the interaction among spatial, economic, and infrastructural factors in shaping the network. Based on these findings, this study underscores the need for targeted policy measures to support Central and Eastern European countries, including investment in logistics infrastructure, technological innovation, and regional cooperation initiatives, to strengthen their integration into the supply chain and bolster their export capacity. Furthermore, fostering balanced inter-regional collaborations is essential in building a resilient trade network. Continued investment in transportation infrastructure and innovation is recommended to sustain the EU’s competitive advantage in the global electric vehicle lithium-ion battery supply chain. Full article

Global supply chains face unprecedented challenges from geopolitical conflicts, climate change, economic volatility, and technological disruptions, highlighting the critical role of supply chain resilience as a core strategy for firms to maintain stability and competitive advantage. Grounded in the resource-based view and dynamic capability theory, this study examines how supply chain capability—that is, entrepreneurial leadership, collaborative capability, and digital transformation—enhances resilience, which mediates its impact on performance. Using structural equation modeling on survey data from Chinese firms, we find that resilience, comprising absorptive, reactive, and recovery capability, significantly mediates the relationship between supply chain capability and performance. Environmental uncertainty moderates this relationship, particularly in highly uncertain contexts, where resilience becomes a key driver of competitive advantage. Theoretically, this study extends dynamic capability theory by disaggregating resilience and exploring its mediating role. Practically, it emphasizes strengthening entrepreneurial leadership, collaborative capability, and digital transformation to improve resilience and performance in uncertain environments. Full article

Exploring the action mechanisms and enhancement pathways of the resilience of agricultural product green supply chains is conducive to strengthening the system’s risk resistance capacity and providing decision support for achieving the “dual carbon” goals. Based on theories such as dynamic capability theory and complex adaptive systems, this paper constructs a resilience framework covering the three stages of “steady-state maintenance–dynamic adjustment–continuous evolution” from both single and multiple perspectives. Combined with 768 units of multi-agent questionnaire data, it adopts Structural Equation Modeling (SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA) to analyze the influencing factors of resilience and reveal the nonlinear mechanisms of resilience formation. Secondly, by integrating configurational analysis with machine learning, it innovatively constructs a resilience level prediction model based on fsQCA-XGBoost. The research findings are as follows: (1) fsQCA identifies a total of four high-resilience pathways, verifying the core proposition of “multiple conjunctural causality” in complex adaptive system theory; (2) compared with single algorithms such as Random Forest, Decision Tree, AdaBoost, ExtraTrees, and XGBoost, the fsQCA-XGBoost prediction method proposed in this paper achieves an optimization of 66% and over 150% in recall rate and positive sample identification, respectively. It reduces false negative risk omission by 50% and improves the ability to capture high-risk samples by three times, which verifies the feasibility and applicability of the fsQCA-XGBoost prediction method in the field of resilience prediction for agricultural product green supply chains. This research provides a risk prevention and control paradigm with both theoretical explanatory power and practical operability for agricultural product green supply chains, and promotes collaborative realization of the “carbon reduction–supply stability–efficiency improvement” goals, transforming them from policy vision to operational reality. Full article

The swift expansion of China’s automotive manufacturing industry has spurred a constant rise in the demand for automotive parts production and distribution, making the optimization of distribution routes in complex environments a crucial research topic. Efficiently optimizing these routes not only boosts production efficiency and cuts costs for automotive manufacturers but also enhances supply chain management and advances sustainable development. This study focuses on the optimization of automotive parts distribution routes under a multi-manufacturer collaboration framework. An optimization model is proposed to minimize the total operational costs within a joint distribution system, incorporating an improved Ant Colony Optimization (ACO) algorithm to formulate an effective solution approach. The model considers complex factors such as dynamic demand, time-window constraints, and periodic distribution. A PIVNS algorithm integrating a virtual distribution center with an enhanced variable neighborhood search is designed to efficiently address the problem. The efficacy of the proposed model and algorithm is substantiated through extensive experiments grounded in real-world case studies. The results confirm the high computational efficiency of the proposed approach in solving large-scale problems, which significantly reduces distribution costs while improving overall supply chain performance. Specifically, the PIVNS algorithm achieves an average travel distance of 2020.85 km, an average runtime of 112.25 s, a total transportation cost of CNY 12,497.99, and a loading rate of 86.775%. These findings collectively highlight the advantages of the proposed method in enhancing efficiency, reducing costs, and optimizing resource utilization. Overall, this study provides valuable insights for logistics optimization in automotive manufacturing and offers a significant reference for future research and practical applications in the field. Full article

Through the energy conversion of building skins, building-integrated photovoltaic (BIPV) technology, the core carrier of the smart city energy system, encourages the conversion of buildings into energy-generating units. However, the decommissioning of the module faces the challenge of physical dismantling and financial environmental damage because of the close coupling with the building itself. As the first tranche of BIPV projects will enter the end of their life cycle, it is urgent to establish a multi-dimensional collaborative recycling mechanism that meets the characteristics of building pv systems. Based on the theory of reverse logistics network, the research focuses on optimizing the reverse logistics network during the decommissioning stage of BIPV modules, and proposes a dual-objective optimization model that considers both cost and carbon emissions for BIPV. Meanwhile, the multi-level recycling network which covers “building points-regional transfer stations-specialized distribution centers” is designed in the research, the Pareto solution set is solved by the improved NSGA-II algorithm, a “1 + 1” du-al-core construction model of distribution center and transfer station is developed, so as to minimize the total cost and life cycle carbon footprint of the logistics network. At the same time, the research also reveals the driving effect of government reward and punishment policies on the collaborative behavior of enterprise recycling, and provides methodological support for the construction of a closed-loop supply chain of “PV-building-environment” symbiosis. The study concludes that in the process of constructing smart city energy system, the systematic control of resource circulation and environmental risks through the optimization of reverse logistics network can provide technical support for the sustainable development of smart city. Full article