Search Results (1,225)

The transition towards sustainable manufacturing necessitates complex optimization that integrates economic goals with environmental factors, such as energy consumption and greenhouse gas emissions. This research addresses the critical challenge of optimizing the Incoming Quality Control (IQC) policy for raw material batches. The primary objective is formulated as a multi-criteria control problem that jointly minimizes the weekly final product cost, carbon footprint, and energy consumption. To handle sequential decision making under uncertainty, we adopt a scalarized reinforcement learning (RL) reward that combines these objectives into a single value function and explores different trade-offs through alternative weight configurations. To effectively handle the uncertainty in incoming quality and the sequential decision making required for dynamic control, the optimization problem is modeled as a Bayesian Adaptive Markov Decision Process (BAMDP). To maintain computational tractability despite the continuous belief space inherent in the BAMDP formulation, we employ a Deep Q-Network (DQN) architecture acting as an approximate dynamic programming solver. The Bayesian framework represents model uncertainty explicitly, updates beliefs as new inspection evidence becomes available, and allows prior domain knowledge on supplier quality to be incorporated into the learning process. The BAMDP formulation is used to learn a set of adaptive inspection policies that adjust the IQC strategy over time to achieve conflicting goals: reducing inspection costs while maintaining standard quality, minimizing energy consumption, and lowering CO₂-equivalent emissions. The goal is to find robust policies that balance these trade-offs under different quality and demand conditions. This methodology aligns with the principles of Industry 5.0 by leveraging advanced artificial intelligence (AI) methods, such as reinforcement learning (RL), coupled with a stochastic simulation of the production system, based on a geometric/physical model of the component’s tolerance chains, to support decision-makers in designing and assessing sustainable IQC strategies. Comparative simulations on the case study, including a benchmark against ISO 2859-1 sampling plans, confirm that this dynamic and risk-aware optimization paradigm can reduce overall cost, energy use, and environmental impact across various quality conditions, while preserving outgoing quality. Full article

Agricultural supply chains operating under rural infrastructure constraints face persistent logistical inefficiencies that reduce producer income and weaken territorial sustainability. This paper assesses how collaborative and coordinated distribution architectures reshape economic performance, efficiency, and equity in dispersed networks of cocoa producers in El Carmen de Bolívar, Colombia. The unified optimization framework compares three regimes: decentralized non-collaborative individual shipments, collaborative consolidation based on distribution centers, and coordinated distribution with time-window synchronization. The findings show a reduction in average logistics costs from $0.688/kg in decentralized distribution to $0.323/kg with collaborative distribution centers, and even further to $0.282/kg in coordinated distribution, representing an overall reduction of approximately 59%. A sensitivity analysis across 64 accessibility configurations shows that the advantage of coordination increases as time rigidity increases. These structural improvements translate into a 13.97% increase in total producer utility, raising average utility from $278 to $317 per producer. In addition, the distributional assessment based on Lorenz curves and Gini coefficients indicates that inequality remains stable despite gains in welfare. These results demonstrate that spatial consolidation combined with temporal synchronization is a decisive lever for resilient and inclusive rural supply systems. Full article

This study examines how FUN&EAT’s “AI+Unmanned” strategy affects system resilience in sustainable operations management. This study is based on a mixed design, combining a case study with a survey study, and uses 499 valid samples and tests the effects of AI-driven decision-making capability, resource allocation flexibility, risk forecasting ability, system synergy capability, and resource optimization ability. The results show that all five factors have significant positive effects on system resilience. Resource optimization ability has the strongest effect, followed by AI-driven decision-making capability. The mediation results show that risk forecasting ability partially mediates the effects of system synergy capability and resource allocation flexibility on system resilience. However, risk forecasting ability does not mediate the effects of resource optimization ability and AI-driven decision-making capability. The findings indicate that FUN&EAT can improve operational resilience through intelligent decision-making, flexible resource allocation, risk prediction, system coordination, and resource optimization. Full article

Background: Digital transformation is viewed as a lever of supply chain resilience, yet the intermediate pathways through which digital maturity relates to resilience remain underspecified, particularly in emerging-market contexts. Drawing on the Resource-Based View and the Dynamic Capabilities Framework, this study examines whether four dynamic capabilities (visibility, flexibility, risk management, and collaboration) mediate the relationship between digital maturity and supply chain resilience. Methods: Using a cross-sectional survey of 250 Moroccan firms and partial least squares structural equation modeling (PLS-SEM), we estimate a multi-mediator model and decompose the total association using variance accounted for (VAF). Results: The findings indicate that digital maturity is positively associated with resilience both directly (β = 0.219, p < 0.01) and indirectly through the four mediators, with the four capabilities jointly accounting for 63.7% of the total association (R² = 0.523, SRMR = 0.027). Visibility (18.9%) and flexibility (15.9%) emerge as the strongest indirect channels. Conclusions: The study contributes by simultaneously testing four dynamic capabilities as mediators within a single specification, documenting evidence from an under-represented emerging-market context, and providing empirically grounded managerial recommendations and policy implications. Because the data are cross-sectional, all reported coefficients describe statistical associations. Full article

Firms increasingly face disruptions arising from technological change, supply chain instability, and uncertain policy environments, making enterprise resilience a key concern for both managers and policymakers. As firms operate within interconnected digital and supply chain systems, this study examines whether digital intelligence policy and supply chain coordination policy are jointly associated with enterprise resilience. Using a firm-year panel of Chinese A-share listed companies from 2010 to 2024, we investigate AI innovation pilot zones and supply chain innovation pilots, with a particular focus on whether their coexistence is associated with a complementarity premium. The results suggest that both AI innovation pilot zones and supply chain innovation pilots are positively associated with enterprise resilience. The interaction between the two policies is significantly positive, providing evidence consistent with an additional joint-policy association beyond their separate associations. Dynamic analysis supports the parallel trend assumption and suggests that the estimated complementarity association becomes stronger over time. Mechanism tests provide channel-consistent evidence that joint policy exposure is associated with higher values of the digital-transformation indicator, stronger supply chain coordination, and greater resource reconfiguration. Heterogeneity analysis further suggests that this association is more pronounced among non-state-owned firms, firms in supply-chain-dependent industries, firms located in cities with stronger digital infrastructure, and firms with higher risk exposure. These findings highlight the potential importance of coordinated policy design for supporting firm-level resilience. Full article

This paper develops a theoretical model to analyze the protective effect and nonlinear mechanism of preferential rules of origin (ROOs) on regional supply chains amid global value chain restructuring and rising regional supply chain security demands. Supported by numerical simulations and a triple difference-in-differences (DDD) empirical approach based on the China–ASEAN Free Trade Agreement (CAFTA), the findings reveal a nonlinear, inverted U-shaped relationship between ROO stringency and supply chain stability—exhibiting a typical Laffer curve characteristic. Moderate restrictions significantly promote intra-regional intermediate goods procurement and stabilize regional supply chain layout, while excessively stringent rules raise enterprise compliance costs and restrain integration. These findings carry important implications for regional economic resilience and sustainable development. While our empirical analysis focuses on economic resilience (measured through regional procurement stability), we discuss how well-designed ROO may also support broader sustainability goals, including contributions to SDG 8 (Decent Work and Economic Growth) and SDG 17 (Partnerships for the Goals) through more stable and inclusive regional production networks. The study highlights the need for careful calibration of ROO stringency to balance protective effects with compliance costs in pursuit of both resilient and sustainable regional trade governance. Full article

The biofuel supply chain is a complex value chain spanning from production to consumption. Manipulating information such as geographical origin, raw material type, and quantity at the production stage can disrupt refinery production plans and cause supply–demand imbalances. Therefore, a transparent traceability system is essential. The existing centralized database architecture poses a high risk of supply chain service suspension due to even a temporary fault in the central server, and it lacks resilience. Furthermore, it is vulnerable to data forgery, making it urgent to secure information integrity. To resolve these issues, this study proposes a blockchain-based biofuel supply chain information protection system. This system utilizes Shamir’s Secret Sharing algorithm to distribute data location information across all nodes and introduces the R-snowball consensus algorithm, which combines the reputation score of nodes with the random sampling of Snowball. The system aims to secure resilience in the event of a failure, achieve reputation-based security, and provide preliminary evidence of robustness against internal and external threats under the tested conditions. Experimental results demonstrated that the proposed system achieved an average recovery time of within 0.03 s, regardless of the load volume. Furthermore, preliminary evidence under the tested conditions suggests that the security and robustness of the system were supported through the exclusion of internal malicious nodes via a reputation-based penalty logic, the defense against main chain takeover attempts in external attack scenarios involving multiple fake nodes (Sybil nodes), and the maintenance of consistent consensus times. Full article

The growing volatility and complexity of global food supply chains have intensified the need for integrated analytical frameworks capable of supporting anticipatory and data-driven decision-making. This article examines how logistics sector observatories can function as strategic intelligence infrastructures for identifying structural tensions and supporting resilience in cold-chain logistics systems. The article introduces the concept of logistics sector observatories as strategic intelligence infrastructures and examines its empirical relevance through a longitudinal analysis of the Spanish cold-chain logistics sector. Empirically, the research draws on a multi-source dataset constructed through the ALDEFE Observatory in collaboration with industry stakeholders over the core study period 2021–2025, encompassing storage capacity, consumption dynamics, energy costs, international logistics indices, and macroeconomic variables. Complementary energy benchmark data for 2019–2025 are used to contextualize electricity cost volatility. Methodologically, the study combines qualitative insights from stakeholder interviews with exploratory quantitative longitudinal analysis. The results suggest severe structural tensions driven by the interaction between rigid capacity constraints and energy cost volatility. The analysis identifies a pattern of persistently high storage occupancy despite substantial energy-price fluctuations. This finding is consistent with the structural inelasticity of cold-chain demand, which reduces operational slack and affects system resilience. Beyond operational resilience, the study highlights the potential contribution of sector observatories to the energy sustainability transition through future sector-level indicators related to energy intensity, refrigeration efficiency, and carbon performance. The study contributes a sector-level, data-driven perspective on visibility, coordination, and anticipatory governance in complex logistics environments. Full article

As plant-based diets catalyze a global shift toward sustainable consumption, Chinese plant-based food firms are experiencing rapid growth and seeking to expand their international footprint. This study investigates the mechanisms underlying the internationalization performance of these firms by integrating the Technology–Organization–Environment (TOE) framework with a configurational perspective. We operationalize nine antecedents across three dimensions: the technological dimension (technological maturity, supply chain resilience, and digital transformation), the organizational dimension (food safety certification intensity, strategic partnership intensity, and talent acquisition intensity), and the environmental dimension (market adaptability, compliance and risk management, and product line breadth). Utilizing fuzzy-set qualitative comparative analysis (fsQCA) on a sample of N = 29 publicly listed Chinese plant-based firms, this research identifies three distinct equifinal pathways to superior internationalization performance. The first is the Collaboration-Compliance configuration (Organization–Environment-driven), which is primarily characterized by the synergy between strategic partnerships and regulatory risk management. The second is the Supply Chain-Compliance-Product Diversification configuration (Technology-Environment-driven), where international success is predicated on the interplay among supply chain resilience, institutional compliance, and product variety. The third is the Full-Factor Synergy configuration (Technology-Organization-Environment jointly driven), which emphasizes a holistic coupling of technological innovation, organizational coordination, and external institutional adaptation. By uncovering these complex causal mechanisms, this study moves beyond traditional linear analysis to reveal how diverse capability configurations can lead to equivalent internationalization outcomes. The findings provide actionable strategic guidance for firms navigating the global plant-based market and offer theoretical insights for policy frameworks supporting sustainable dietary transitions. Full article

The circular economy (CE) is increasingly recognized as a strategic approach that enables firms to address environmental challenges while enhancing competitiveness and long-term value creation. However, evidence regarding its impact on business performance remains fragmented across sectors, performance dimensions, and organizational contexts. This study presents a systematic literature review conducted in accordance with the PRISMA 2020 guidelines to examine how CE practices influence business performance. The review synthesizes evidence from 79 peer-reviewed publications published between 2015 and 2025. The findings identify five major channels through which CE practices affect business performance: (1) economic, environmental, and social performance, (2) operational and supply chain performance, (3) competitive advantage and strategic positioning, (4) financial and environmental performance, and (5) barriers and performance in SMEs. Across these dimensions, CE practices are frequently associated with improved resource efficiency, cost reduction, innovation capacity, supply chain resilience, and enhanced environmental outcomes, including waste reduction and lower emissions. The review suggests that the performance effects of CE are contingent upon contextual factors such as firm size, ownership structure, industry characteristics, regulatory environment, and digital capabilities. While large firms often benefit from greater resources and organizational capacity, SMEs face significant barriers related to finance, technology, and governance, although these can be mitigated through collaboration networks and digitalization. The study contributes to the Strategic Environmental Management literature by indicating that CE practices may function not only as environmental initiatives but also as strategic capabilities that support competitiveness, resilience, and sustainability transitions. The findings provide implications for managers seeking to integrate circularity into business strategy and for policymakers designing institutional conditions that enable circular business transformation. Full article

Industrial hemp (Cannabis sativa L.) has emerged as a sustainable source of bioactive compounds, with increasing interest in cosmeceutical applications for acne management. This systematic review synthesises evidence on cannabinoid-containing hemp extracts, particularly cannabidiol (CBD), with emphasis on anti-inflammatory and sebostatic mechanisms, alongside formulation considerations and supply-chain sustainability. Reporting followed PRISMA 2020 guidelines and encompassed preclinical and clinical evidence relevant to acne-associated outcomes. The review protocol was registered prospectively with PROSPERO (CRD420251272093). Across cell-based, ex vivo and early clinical studies, CBD modulated key inflammatory mediators, including TNF-α, IL-1β, IL-6 and IL-8; normalised sebocyte activity and attenuated Cutibacterium acnes (Propionibacterium acnes)-induced inflammatory signalling. Preliminary clinical observations indicate reductions in lesion counts and erythema, with generally favourable short-term tolerability; however, interpretation is limited by small sample sizes, predominantly non-randomised designs, heterogeneous formulations and frequent co-formulation with additional active ingredients. Evidence supporting direct antimicrobial efficacy and durable clinical benefit remains limited. Lipid-rich hemp seed-derived products were considered only in a contextual capacity for barrier-supportive and nutritional properties and were excluded from efficacy synthesis unless cannabinoid content was verified. Sustainability analyses highlight hemp’s low water requirements, carbon sequestration potential and relevance to Sustainable Development Goal 3 (SDG 3: Good Health and Well-Being) and Sustainable Development Goal 12 (SDG 12: Responsible Consumption and Production), supporting its role in environmentally responsible cosmeceutical development. Overall, CBD-containing hemp extracts show biologically plausible and clinically promising adjunctive potential for mild-to-moderate inflammatory acne, but current evidence remains preliminary. This review highlights the need for methodologically rigorous and transparent clinical studies, standardised formulations, validated outcome measures and the integration of sustainability metrics to strengthen evidence synthesis, clarify clinical relevance and guide responsible cosmeceutical development. Full article

In this paper, the different emerging metaverse technologies are identified, and a comprehensive understanding of the various technologies that can empower supply chains in various parts of the world is provided. It also presents a structure that shows how each of these classified technologies would work towards a robust and sustainable supply chain. Moreover, the study uses the fuzzy TOPSIS method to determine the most significant metaverse technology that can significantly enhance the resilience and sustainability of the supply chain networks across the world. The basic aim of this research is to arm the organizations with the latest technology in the metaverse, which enables them to develop a future-proof supply chain network capable of surviving in this ever-evolving world. Full article

This study examines how entrepreneurial ecosystem constraints shape MSME resilience in the Jakarta–Bogor–Depok Indonesia corridor using a qualitative multiple-case design. Drawing on 20 MSME case reports across food and beverage, retail, services, and small-scale manufacturing, the study addresses two questions: (1) which ecosystem domains are the most binding constraints, and (2) how MSMEs convert ecosystem resources into resilience outcomes. The analysis shows that market pressure is the most universal constraint (20/20 cases), followed by digital-managerial support infrastructure gaps (18/20), supply chain volatility (13/20), and finance, human capital, and institutional constraints (each 12/20 cases). Cross-case evidence identifies four recurrent mechanisms: market pressure is managed through digital channel orchestration and customer engagement; capital constraints are managed through internal cash discipline and partnership-based financing; input volatility is managed through supplier diversification, local sourcing, and inventory control; and skill gaps are managed through internal training and process standardization. Building on these mechanisms, the study develops a threefold resilience typology: Adaptive Leaders, Operational Survivors, and Vulnerable Traditionalists. The main theoretical contribution is to show that MSME resilience is configurational and depends on inter-domain alignment rather than on isolated ecosystem components or entrepreneur-level grit alone. The practical contribution is a typology-based policy logic that prioritizes integrated intervention bundles, which are finance, digital capability, operations, supply chain, and managerial upgrading, over fragmented support programs. Full article

Following the 2022 disruption of Russian pipeline gas, European countries shifted toward liquefied natural gas (LNG) at markedly different speeds; yet, the drivers of this variation remain poorly understood. This study asks what explains these differences. Using a balanced panel of eight major European gas importers over 2015–2024 (80 observations), the study models the share of LNG in total gas imports as the dependent variable, reversing the conventional approach that treats LNG as an explanatory variable for gas prices. The interaction between the post-2022 structural break and storage fill levels is negative and statistically significant (β = −0.006, p = 0.019 clustered; p = 0.002 Driscoll-Kraay), suggesting that countries with lower storage reserves tended to increase their LNG dependence more strongly. This result is robust across seven of eight specifications and survives time-trend controls and leave-one-country-out analysis. Marginal effects reveal that the storage–LNG relationship was absent before the shock and emerged only after the disruption. Renewable energy penetration emerges as a significant positive predictor. Full article

Supply chain disruptions have become a major source of macro-financial stress, yet their implications for green finance remain underexplored. This paper investigates the state-dependent connectedness between supply-side bottlenecks and the green finance market, represented by clean energy equities, green bonds, and carbon prices. Using daily data on regional Supply Bottleneck Indices (SBIs) for China, the United States, and the euro area, we first construct a global Supply Bottleneck Index (GSBI) by principal component analysis and then estimate pairwise quantile-on-quantile connectedness (QQC) between supply bottleneck indicators and each green finance submarket. The results show that connectedness is strongly nonlinear, asymmetric, and time-varying. For the global indicator, connectedness intensifies at both joint and cross-tail quantile combinations, while mid-quantile states exhibit weak coupling. Regional results reveal clear heterogeneity: China and the United States display the strongest connectedness with clean energy equities in extreme upper-tail states, whereas the euro-area indicator is most tightly linked with the carbon market. Across many extreme states, supply bottleneck indicators show positive net connectedness with green finance markets, but green finance markets, especially carbon prices, can dominate the bilateral connectedness relation under calmer or intermediate regimes. Robustness checks based on average and quantile-rank GSBI constructions, a post-2023 subsample, and alternative QQC tuning choices support the tail-dominance pattern. These findings suggest that supply bottlenecks are not uniformly related to all green assets; rather, they are associated with state-dependent changes in the internal connectedness architecture of the green finance system. The paper contributes to the literature on financial connectedness and sustainable finance by showing how a real-economy disturbance is associated with changes in the connectedness and resilience of green financial markets. Full article