Tire manufacturing is increasingly scrutinized for sustainability performance due to non-exhaust pollution risks (e.g., tire and road wear particles, TRWP) and end-of-life tire (ELT) burdens that propagate across air–soil–water pathways. However, these environmental concerns are often discussed descriptively and are not consistently translated into measurable supply-chain indicators for benchmarking and improvement. This study evaluates Green Supply Chain Management (GSCM) sustainability in Iran’s tire manufacturing sector using a multi-criteria decision-making framework. Fifteen GSCM sub-criteria spanning green product, design, materials, production, management, and service were finalized through literature synthesis and expert input, and criterion weights were derived using the Base Criterion Method (BCM). Ten active Iranian tire manufacturers were assessed using the OPLO–POCOD method, an opportunity-loss-based polar coordinate distance approach that captures both the magnitude and structure of performance gaps relative to an ideal profile. Using cross-sectional data representing one operational year (ending March 2024), results reveal substantial heterogeneity among firms: Kavir Tire (A1) achieved the best overall sustainability alignment (Degree of Opportunity Losses, DOL = 0.0323), while Artavil Tire (A10) exhibited the largest deviation from the ideal (DOL = 0.1632). Overall, the findings demonstrate the practical value of OPLO–POCOD for sustainability benchmarking in manufacturing supply chains and provide actionable priorities for managers and policymakers to reduce sustainability gaps in the Iranian tire industry.

The smart manufacturing revolution: how industrial robotics reshape supplier networks

Sustainable digitalization of manufacturing supply chains: An integrated framework for resilience, efficiency, and circularity

The largest highly pathogenic avian influenza (HPAI) H5N1 outbreak to date in the United States (US) began in early 2022 and is ongoing. The analysis presented here investigates the temporal association observed between reported confirmed detections of H5N1 (cases) in commercial and non-commercial flocks at different spatial and temporal scales. Cross-correlation analysis was performed at the national level and in five states (Minnesota, South Dakota, California, Ohio, and Pennsylvania) representing approximately 60% of commercial cases at daily, weekly, and monthly frequencies. The cross-correlation results provide no support for non-commercial cases serving as a leading indicator (i.e., early warning signal) for commercial cases. In 79 counties with both commercial and non-commercial cases, approximately 65% of the first cases were in commercial flocks. Across the counties, the median arrival time of commercial cases (41 days) preceded the median arrival time of non-commercial cases (199 days). While official reported cases do not completely describe HPAI outbreak dynamics, they represent an authoritative source of information available to firms in the poultry and egg products supply chain. Based on the analysis and results presented here, non-commercial cases did not serve as a leading indicator for commercial cases in the ongoing H5N1 outbreak in the United States.

In this paper, we consider a three-level dynamic closed-loop supply chain differential game model led by manufacturers and recycled by third-party recyclers in order to study the impact on the dynamic closed-loop supply chain of innovative products based on simultaneous occurrence of consumer purchase regret and replacement regret. Then, we obtain the optimal path for wholesale price, retail price and return effort by solving the differential game model. Specifically, we explore the influence of the coupling effect of consumer purchase regret and replacement regret on the supply chain through theoretical analysis and numerical simulation. The results show that consumer purchase regret leads to lower sales in the supply chain, which in turn causes a decrease in long-term profits of manufacturers and retailers, while consumer replacement regret will attract more consumers to increase sales, thereby increasing the long-term profits for manufacturers and retailers accordingly. However, consumer purchase regret does not affect the profit of recyclers. In addition, both types of consumer post-purchase regret prolong the product length of time in the market, and consumer replacement regret has a more significant effect on the length of time of product in the market. Meanwhile, lower consumer purchase regret and higher replacement regret can improve the performance of all members of the entire dynamic supply chain. However, these factors do not influence the recyclers.

Energy use is a major driver of greenhouse gas (GHG) emissions in veterinary practice, primarily through consumption of fossil fuel-generated electricity and heating, client travel, staff commute, and the extensive supply chain of healthcare products. Here we synthesize information on these key emission sources, outline the scientific and economic rationale for decarbonizing energy use and present 6 scalable strategies for reducing energy-related emissions in veterinary hospitals: procuring 100% renewable low-carbon electricity, electrifying clinical operations and infrastructure, reducing transport-related emissions, improving hospital energy efficiency, installing on-site renewable energy generation and storage, and addressing emissions from procurement and delivery. Together, these interventions provide a structured pathway for reducing emissions from veterinary practice while strengthening operational resilience, supporting long-term financial sustainability, and advancing the profession's role in protecting the health of animals, people, and the environments they share, consistent with a One Health approach.

ABSTRACT The structure of South Korea’s manufacturing supply chain—characterized by deep dependency, prolonged payment cycles, and advanced digitalization—offers a distinctive environment to reassess the role of Supply Chain Finance (SCF). This study advances the literature by shifting the interpretation of SCF from a mere external financing tool to a mechanism that reshapes internal credit dynamics within supply networks. Using panel data on Korean manufacturing micro and small enterprises (MSEs) from 2010 to 2024, we identify three novel findings. First, SCF significantly enhances firm growth by mitigating structural liquidity constraints rooted in Korea’s long-payment-cycle system. Second, we show that SCF elevates firms’ trade-credit capacity, revealing an overlooked channel through which financing instruments alter firms’ credit positions inside the supply chain. Third, digital-finance penetration amplifies this credit-transmission process by improving the verifiability and diffusion of transaction-level information. Together, these results uncover a previously undocumented mechanism—SCF-induced credit upgrading—through which MSEs strengthen their position within supply-chain credit networks. The study provides new theoretical and empirical insights into the evolution of supply-chain financing in data-driven economies.

Ensuring sustainable food production for a growing population requires robust tools like the Life Cycle Assessment (LCA), despite the fundamental complexities characterising the agri-food sector. This study evaluates the environmental impacts of beer and bread production, two important sectors, within a circular economy framework using the LCA. The analysis focuses on innovative products: bread incorporating brewery-spent grain and beer brewed from unsold bread. The study follows a cradle-to-gate approach, covering the entire upstream supply chain, including cultivation, milling, malting, and ingredient production. Cultivation emerges as the primary environmental hotspot in both systems. In bread production, the bakery and proofing phases also show high impacts, while in brewing, packaging is the dominant contributor, followed by boiling and hopping. For co-product processing, drying and transport are critical hotspots. Compared with conventional products, innovative circular products generally show lower environmental impacts, with exceptions related to organic cultivation and allocation constraints. Circular strategies notably reduce land use and marine eutrophication in most organic cases. Overall, the fully circular scenario outperforms the Conventional System in 13 impact categories, supporting the environmental potential of circular approaches in both sectors.

When to use large language models for digital manufacturing in supply chains?

The European Union's Deforestation-Free Regulation (EUDR), approved in 2023 and set to take effect in December 2026, mandates plot-level traceability and physical segregation of compliant from non-compliant products in supply chains linked to deforestation. This paper assesses the economic and environmental impacts of EUDR compliance costs on Brazil's soybean supply chain. Using a dynamic multiregional computable general equilibrium (CGE) model with integrated land-use transitions, we simulate counterfactual outcomes from 2026 to 2035 under two policy scenarios: (i) Legal Amazon–only coverage (S1-AMZN) and (ii) nationwide coverage (S2-BRA). Compliance costs are modeled as production-tax equivalents, scaled by the regional share of EU-bound soybean-equivalent exports. Results show cumulative export losses of US$ 85.1 billion (S1-AMZN) and US$ 216.3 billion (S2-BRA), with corresponding real GDP shortfalls of US$ 409.9 billion and US$ 1.167 trillion. Avoided deforestation ranges from 51,466 to 105,899 ha, though leakage effects emerge under S1-AMZN. Estimated abatement costs are US$ 133–207 per ton of CO₂e, while forgone GDP per hectare of avoided deforestation ranges from US$ 58,630 to US$ 171,652. These findings suggest that clearing the EU's soy supply chain of deforestation alone delivers limited environmental benefits at high economic cost, underscoring the need to complement trade-based measures with robust domestic land-use governance and enforcement policies. • EUDR lowers Brazil's GDP slightly and deepens regional income disparities • Soy export losses drive land and labor shifts toward corn, cotton, and other crops • Welfare gains for the poorest and richest, losses for middle incomes • Modest avoided deforestation at high economic cost • National versus Amazon-only enforcement yields similar macro but less leakage

ABSTRACT This article estimates price and income elasticities of Ecuador’s import demand disaggregated by technological intensity and trading partner (United States, China, European Union) over 2000–2023, providing the first technology-disaggregated evidence for a fully dollarized emerging economy. Using ARDL, NARDL, and DOLS models within a bounds-testing framework, we identify both long-run relationships and potential asymmetries. Results reveal a clear technological hierarchy: price elasticities decline with complexity, with low-technology imports highly responsive, medium-technology goods moderately sensitive, and high-technology imports largely price-inelastic or statistically insignificant. Income elasticities consistently favor China, indicating growing dependence on Asian manufacturing supply chains. Cross-price effects show competition between China and the United States in basic goods but complementarity in intermediate and higher-technology segments. Overall, limited substitution possibilities for technologically complex imports constrain expenditure switching and weaken the effectiveness of relative-price adjustments. These findings suggest that exchange-rate or price mechanisms alone are insufficient to correct trade imbalances in dollarized and commodity-dependent economies, underscoring the need for diversification and industrial upgrading policies.

The entrepreneur is the main actor in the capitalist economic system. The current stage of the evolution of entrepreneurship has significant specificities caused by paradigmatic shifts in the economy, the expansion of the field of entrepreneurial activity, and an even greater focus on innovation. Therefore, the aim of the article is to outline the new spheres of modern entrepreneurship and the contours of updating the conception of the entrepreneur. In the course of the study, a general analysis of the evolution of entrepreneurship is performed. The main entrepreneurial revolutions and gradual changes in understanding the role of the entrepreneur are highlighted. Special attention is paid to the origins and main ideas of J. Schumpeter's conception of the innovator-entrepreneur. The transformation of entrepreneurship and the change in its understanding in the second half of the 20th century up to the beginning of the 21st century are traced. Given this, the features of the entrepreneurial approach to solving societal problems, as well as the context of modern entrepreneurship (the increasing complexity of institutional and economic conditions, growing uncertainty, etc.), are determined. Emphasis is placed on the growing government support for entrepreneurship, which indicates a desire to strengthen and utilize its potential. The main changes in the economic paradigm (transition to sustainable development; transformation of production systems, supply chains, and consumption models; general greening and resource conservation; strengthening of the human-centric economic model, etc.), accompanied by the expansion of corporate responsibility, are identified. Attention is drawn to the emergence of new spheres of entrepreneurship (sustainable development, biotechnology, nanotechnology, artificial intelligence, human augmentation, changes in socioeconomic organization, and space exploration), which made it possible to determine the features of modern fields of activity. The qualitative changes in the modern entrepreneur under the influence of globalization, which generates a global entrepreneurial process, are taken into account. A number of transformations of the entrepreneur figure associated with innovative creativity, the presence of a value dominant, a focus on transformation, a striving for progress, a focus on transforming nature, and the strengthening of social responsibility and the pro-sociality of business are outlined. Based on this, a conclusion is drawn regarding the emergence of a new conception of the creator-entrepreneur, which is expected to be developed further.

The application of prefabrication and modularization in the construction industry has grown significantly recently. The efficiency of prefabrication supply chains yields substantial advantages for construction projects. A challenge is the variability in delivery times, which negatively impacts the economy and reliability of prefabrication supply chains. Most construction prefabrication suppliers have difficulty adjusting their schedules in response to delivery time changes in a timely manner. Despite this critical challenge, limited research has addressed proactive and robust production scheduling to mitigate these uncertainties. This study investigates a method for proactive and robust production scheduling for construction prefabrication suppliers, particularly those with multiple fabrication shops, responding to changes in delivery times. This paper introduces a multi-objective, two-stage stochastic programming model that facilitates the production planning with multiple fabrication shops, considering variable delivery times. Computational results from an experimental study demonstrate that the proposed optimization model achieves a 14.6% cost reduction compared to the traditional EDD method. Computational results also show that the expected cost of the stochastic programming model achieves a cost reduction of 0.23% compared to a deterministic model. These findings suggest the model’s capability to generate robust and flexible schedules that effectively balance cost minimization with time reduction.

ABSTRACT Motivated by the imperative of industrial decarbonization, this study investigates how different regulatory frameworks—Carbon Cap, Carbon Tax, and Cap‐and‐Trade—impact a manufacturer's carbon abatement investment and supply chain coordination. Distinct from prior literature assuming frictionless markets, we explicitly model the “bid‐ask spread” in permit trading and introduce endogenous contract negotiation to resolve vertical investment inefficiencies. Our analysis yields five critical findings. First, under cap‐and‐trade policies with asymmetric trading prices and moderate quotas, the manufacturer optimally exhausts its allocated permits without engaging in trading, effectively treating the policy as a rigid cap. Second, we identify a unique optimal abatement level that maximizes manufacturer profit; notably, the retailer derives no incremental benefit from increases in the manufacturer's permit allocation. Third, contrary to standard intuition, we demonstrate that in markets with environmentally conscious consumers, increasing regulatory stringency can inadvertently suppress the manufacturer's emission reduction efforts. Fourth, comparing instruments reveals that cap‐and‐trade policies induce higher abatement levels than carbon taxes when both tax rates and assigned quotas are at their respective extremes (either very low or very high). Finally, regarding coordination, we show that perfect supply chain coordination is achievable under specific regulatory conditions if the manufacturer commits to an emission reduction level prior to negotiating order quantities and wholesale prices. These findings highlight the critical role of market frictions and bargaining power in designing effective carbon policies and operational strategies.

ABSTRACT Reaching global net‐zero targets has become an urgent priority as businesses and nations face increasing pressure to reduce greenhouse gas emissions. Achieving carbon neutrality in manufacturing supply chains requires comprehensive systemic changes across business processes. It demands forward‐looking strategies that guide companies toward long‐term sustainability and net‐zero objectives. While earlier research has identified several drivers and barriers, there remains a lack of clear, actionable roadmaps that companies can follow. This paper fills this research gap by determining 11 interdependent strategies and grouping them into six levels of hierarchy and discovering that they play the roles of driving and dependent. Results showed that important strategies consist of policy development and incentives, carbon accounting, collaborative learning, renewable energy adoption, low‐emission transportation, digitalization, and circular practices. Using expert insights and a multi‐round Delphi technique, the study identifies key strategies, which are then organized through total interpretive structural modeling (TISM) and cross‐impact matrix‐multiplication applied to classification (MICMAC) analysis. Results identify a pathway roadmap where strategies connect, allowing businesses to focus on initiatives including circular practices, digitalization, and waste reduction. Policy and incentives serve as essential tools, with companies responsible for turning concepts into key performance indicators. Our research offers a blueprint for global organizations to better align efforts, lower emissions, and work toward net‐zero. It outlines the relationship among the strategies and priorities needed by global companies and governments to develop effective cross‐border collaboration and coordinate sustainability efforts, thus supporting climate change commitments.

ABSTRACT This study examines how, after adopting digital twins, manufacturing supply chains shape members' decision reconfiguration to strengthen pollution governance and build sustainable development capability. Survey data were collected from manufacturing supply chains in China, and partial least squares structural equation modeling was used to test a decision transformation framework. The results show that digital twins promote shared situational clarity about pollution and perceived controllability of predictive interventions among supply chain members. These conditions consistently and differentially strengthen Decision Synchronization and anticipation, both directly and indirectly through a Proactive Pollution Intervention Orientation, with perceived controllability exerting a stronger influence on anticipatory decision‐making than on synchronization ( β = 0.318 vs. 0.241). All hypothesized relationships were statistically supported. This is driving governance decisions to shift from fragmented responses toward more centralized patterns and thereby substantially enhancing sustainable pollution governance resilience. This study provides evidence on how digital twins reshape decision‐behavior pathways that advance sustainable pollution governance resilience and offers practical implications for related research.

This article examines the impact of UN Security Council sanctions on the right to health and attempts to look beyond conventional analyses that focus mainly on the objectives and political legitimacy of sanctions by shifting attention from these concerns toward the actual mechanisms of their impact on fundamental rights. The main issue of this research is the gap between the legal design of sanctions and their practical consequences for access to essential health services and goods. While many sanctions regimes formally exclude humanitarian goods, including medicine, in practice, financial and banking restrictions, coupled with excessive caution by economic actors, cause serious disruptions in the supply chain of medical products and healthcare services. Using a legal-descriptive analysis method and relying on UN documents and case studies, this research shows that the violation of the right to health in the context of sanctions is not merely a random outcome, but a structural, predictable, and legally attributable consequence of the design and operation of sanctions regimes. In particular, the phenomenon of the indirect effects of sanctions, through the transfer of risk to private actors and their reduced willingness to engage with target countries, plays a decisive role in limiting access to health services. The findings of the article show that these effects, although indirect, are attributable to the structure of sanctions from an international law perspective and highlight the need to rethink their design and implementation. Consequently, the article argues that in order to ensure the compatibility of sanctions with human rights obligations, especially in the area of the right to health, it is inevitable to pay attention to their structural and foreseeable consequences.

Purpose This study aims to examine the integrated impact of artificial intelligence (AI)-powered supply chain risk management (AISCRM), autonomous resilience (AR), organizational sensemaking (OS) and supply chain resilience (SCR) on enhancing US manufacturing supply chain resilience during digital transformation, thereby addressing a critical gap in the current literature. Design/methodology/approach Utilizing a quantitative approach, the research collected data from 741 respondents across 27 US states, representing 100 manufacturers in automotive, aerospace, electronics and industrial manufacturing sectors. The study used systematic random sampling via SurveyMonkey, distributing questionnaires to 1,900 employees. Structural equation modeling was used to test hypotheses linking AISCRM, AR, OS and SCR, grounded in the dynamic capability view (DCV). Findings The results confirm that AISCRM has a positive influence on AR (H1); AR enhances OS (H2) and SCR (H3); OS has a positive effect on SCR (H4); and OS mediates the relationship between AR and SCR (H5). These findings highlight the synergistic role of AI-driven autonomy and human sensemaking in fostering resilience, with significant implications for diverse manufacturing contexts. Practical implications Manufacturers can leverage AISCRM and AR to enhance autonomous recovery, while OS can guide strategic adaptations to reduce the $50bn annual loss from supply chain disruptions. This provides actionable strategies for large, digitally intensive manufacturers to enhance their competitiveness. Originality/value To the best of the authors’ knowledge, this research is among the first to empirically integrate AISCRM, AR, OS and SCR, addressing a gap identified in recent studies, providing a holistic framework for resilience in the digital era, and contributing to both theory and practice in manufacturing supply chain management.

Despite the increased research interest in the field of food loss and waste (FLW), understanding the true extent of food losses, both overall and by product type, remains a challenge at each stage from production to consumption. Emphasizing the importance of FLW reduction, current Russian and international studies focus mainly on identifying ways to prevent them, without paying due attention to assessing the total volume of lost products in the food supply chain. The dairy industry of the Russian Federation is a strategic sector that ensures food security, but the level of self-sufficiency in milk is still below the planned indicators of the Food Security Doctrine. This creates the potential for further increase in dairy resources, including by reducing losses. The data already available in literature on estimates of milk losses at different stages of the food supply chain cannot be aggregated due to the incomparability of the studied range of dairy products, different methodological approaches to assessment, differences in the methods of identifying sources of losses and low degree of reliability of the initial information. This paper presents the results of quantification of milk and dairy product losses at the stages from agricultural production up to retail, excluding the latter, based on the methodology developed by the authors. This approach made it possible to identify the real scale of milk losses in Russia: physical volume in the equivalent of raw materials, the economic cost of losses, as well as in relative values to the total volume of resources at each stage of the milk supply chain. Verification of the obtained results indicates their comparability with FAO estimates for the world and other scientific studies for individual countries. In addition, for the first time for Russia, this paper presents a quantitative assessment of the possible effects of preventing milk and dairy product losses from the point of view of improving food security, and demonstrates how reducing losses can contribute to solving various economic, social and environmental issues.

Against the backdrop of domestic and international dual circulation and rural revitalization, artificial intelligence (AI) serves as the core impetus driving the digital transformation of the agricultural product supply chain. Existing research mostly focuses on the application ofAI in a single link of the agricultural supply chain, lacking studies from the perspective of e-commerce platforms on how to solve the problem of dispersed supply chain entities and achieve full-chain collaboration. This paper takes the Pinduoduo's Agricultural Land Cloud Group Buying Project as the research object and uses the case study method to analyze the empowerment practice of AI in the entire process of agricultural supply chain production, circulation, and sales, and explores the impact of macro and micro factors on the empowerment effect of AI. The research finds that the project has achieved the compression of supply chain links, reduction of losses, and increase in sales through AI, but it faces bottlenecks such as the low digital literacy of elderly farmers and the tilt of platform R&D resources towards the sales end. Based on this, this paper designs optimization paths from three dimensions: e-commerce platforms, government departments, and research institutions, providing theoretical and practical references for e-commerce platforms to empower the digital transformation of the agricultural supply chain.