This study examines how halal supply chain management influences supply chain performance in food and logistics settings where product integrity, food safety, and sustainability are increasingly scrutinized. The review is motivated by fragmented empirical findings and limited synthesis on how digital technologies shape the performance effects of halal practices. A systematic literature review was conducted by searching the Scopus database for English journal articles in business, management, and accounting published between 2014 and 2025. From an initial pool of 9,780 records, stepwise screening with the keywords supply chain management, halal supply chain management, supply chain performance, and halal product yielded nine studies for synthesis and bibliometric mapping with VosViewer. The findings indicate that strict physical segregation, end to end traceability, robust certification and labelling, organisational capabilities, and knowledge management enhance efficiency, flexibility, halal compliance, and market trust, leading to stronger operational and sustainable performance. The review also highlights opportunities for technologies such as blockchain, the Internet of Things, artificial intelligence, and immersive virtual environments to improve transparency and reduce contamination and data fraud risks. These insights call for cross industry empirical testing of mediating mechanisms and infrastructure readiness to support more adaptive halal supply chains.

The ripple effect: Does digital transformation spark enterprises' technological innovation in supply chains?

The effect of creditor judicial protection on trade credit in supply chains: Evidence from the establishment of bankruptcy courts in China

Supply chain structure and blockchain deployment strategies in competing supply chains

A two-stage model for logistics service provider rank and order allocation in supply chain considering digital technology empowerment

Triple-bottom-line optimization of waste-to-biodiesel supply chains in India: Multi-objective decision support via social group optimization

• Develop a new risk-based inspection framework to combat illicit trade in freeports. • Use a BN model to assess the risk levels of illicit container trade under uncertainty. • Integrate DEMATEL and ranked nodes to address challenges in expert-driven BN. • Optimize inspection rates under inspection resource and waiting time constraints. Freeports that attract illegal activities may become vulnerable without effective measures to ensure a safe and secure Maritime Container Supply Chain (MCSC) involving them. Developing a holistic risk-based inspection framework is essential to address illicit trade challenges in freeports without the need to significantly compromise operational efficiency in a globalized trading environment. However, the existing literature is limited in addressing the uncertainty in container risk levels for establishing inspection priorities and in considering the unique features of freeports. To close these gaps, this study develops a novel framework based on a hybrid two-stage decision-making approach for the optimal container inspection solution, focusing on high-risk containers within the context of Freeport-Centric Supply Chains. The first stage employs a hybrid Decision-Making Trial and Evaluation Laboratory and Bayesian Network (DEMATEL-BN) model to assess container risk levels, accounting for interdependent vulnerabilities across MCSC nodes. The findings identify the most critical risk nodes within the MCSC, including consolidation centers and loading ports. Furthermore, it measures the risk levels of containers based on both severity and likelihood metrics, which serve as key inputs for determining inspection rates in the second stage, distinguishing the approach by effectively addressing uncertainties often overlooked in existing container inspection frameworks. This approach makes new contributions to enhancing the security of freeports and various MCSCs by enabling targeted risk mitigation, optimizing inspection strategies, and balancing security with trade flow efficiency.

Digital innovation and the cost-of-equity capital: Evidence from the supply chain

The tightening of Emission Control Area (ECA) and Vessel Speed Reduction (VSR) regulations poses significant challenges for biomass exporters, particularly from emerging economies. These regulations raise transportation costs and reduce competitiveness, threatening the resilience of the biomass supply chain (BSC). This study develops an integrated optimization framework that combines machine learning (ML) (Bayesian XGBoost and Long ShortTerm Memory (LSTM) models) with discrete-event simulation (DES) to enhance supply chain (SC) efficiency under regulatory constraints. Using operational data from twenty-four Vietnamese wood pellet plants and international shipping records (2023–2024), the framework optimizes procurement, inland logistics, maritime transport, and demand planning. Simulation results show that full SC optimization reduces costs by nearly 40%, while combining SC optimization with power plant efficiency innovations achieves up to a 43.1% reduction in total costs and doubles exporter profits compared to the baseline. Beyond economic gains, the approach enables compliance with international environmental regulations without imposing prohibitive costs on exporters. This study contributes a novel methodological framework that bridges ML and simulation for sustainable SC optimization, offering practical guidance for exporters in emerging economies to remain competitive under tightening global environmental policies.

How does supply chain finance impact supply chain resilience − based on three levels of supply and demand decision making

The United Nations Sustainable Development Goals (UN SDGs) were defined to improve the quality of life of the global population particularly regarding social and economic aspects, with a major focus on environmental sustainability. The incorporation of digital technologies into the agri-food sector has become a key enabler in increasing the efficiency, productivity, and sustainability of food production and processing systems. Digital technologies and innovations including artificial intelligence (AI), robotics, in-ground and remote sensors, connectivity, and internet of things (IoT) have been recognized as also being critical for the successful implementation of the UN SDGs. In particular, the utilization of sensing technologies (e.g., in-ground and remote sensors) has been shown to be of great importance to achieve these goals. The use of vibrational spectroscopy and data analytics have shown potential to contribute with the development and implementation of UN SDGs. An overview of the contribution of sensing technologies based on the utilization of vibrational spectroscopy (e.g., near- and mid-infrared spectroscopy, hyperspectral imaging) and data analytics to achieve the UN SDGs is provided. Advantages and limitations of these techniques are also discussed. The incorporation of technology will provide tools that can be used to monitor and predict the safety and quality of foods. Furthermore, digital technologies are enabling the development of novel decision-management systems along the food supply and value chain. Ultimately, the goal will be to assure the consumers the use of these technologies plays a key role in the applicability of the UN SDG. © 2025 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Clean hydrogen supply chain risks based on circular economy principles: A comparative decision-making framework with fuzzy information

Biomass has emerged as a pivotal new resource that could alleviate dependence on fossil resources and support the ecological transition by benefiting local communities. There has been an expanding literature on the subject for the past two decades. The focus of this literature is primarily on the organization and optimization of the biomass supply chain (BSC), which is the key component in providing profitable and sustainable valorized goods from biomass. The aim of this paper is to evaluate the present state of known research gaps, identify research gaps in BSC design by including economic considerations, and propose new research orientations on the subject that rely on more multidisciplinary approaches. We found three main understudied gaps. The majority of papers still only consider the strategic and tactical decision levels, excluding the operational decision level. Therefore, there are still opportunities to improve the currently accepted BSC design. The demand, as part of the supply chain, appears to be understudied. In the reviewed literature, the demand is treated as a parameter, and is perfectly met by the production, without consideration for pricing, surplus, or shortage. The other gap found is that most of the models considered in this review describe a BSC in autarky, and few take into account importations either of additional biomass or of bioproduct in their studied case, or the potential exportation of surplus. Consequently, closing these gaps in biomass supply design and optimization would facilitate the integration of BSC modeling into broader economic models.

The sustainability of supply chains for green hydrogen production is compared from a life cycle point of view: 1) offshore electrolysis with electricity from Dutch wind farms followed by pipeline transport of hydrogen to Rotterdam (Netherlands), 2) onshore electrolysis in Rotterdam with electricity from the same wind farms, 3) electrolysis with electricity from solar PV in Algeria followed by pipeline transport of hydrogen and 4) electrolysis and ammonia production with electricity from solar PV in Saudi Arabia followed by deep sea transport and ammonia cracking. The environmental sustainability is assessed with ReCiPe 2016 and Environmental Footprint 3.0. The Total Cumulative Exergy Loss (TCExL) method is used to calculate the exergetic sustainability. According to the endpoint scores, offshore electrolysis with wind energy is preferred, but the difference between the TCExL scores of both wind energy options is small. The preference order of the other supply chains is undecided. The offshore wind option is also preferred according to the midpoint indicators GWP/climate change, land use and water consumption/use. It is advised that the systems be investigated in more detail before drawing conclusions about the order of preference and that also attention be paid to the economic and social pillars of sustainability.

Digital technology diffusion is reshaping innovation across supply chain dynamics and ecosystem partners. Prior work often looks at one firm or uniform settings, missing how technology diffusion need to be orchestrated by ecosystem leader across diverse suppliers and other actors. To address this gap, this study employs an exploratory case study of the intelligent vehicle ecosystem, focusing on an original equipment manufacturer (OEM) and six supply chain partners. Although positioned in the supply chain, these actors influence the wider ecosystem thereby affecting technology diffusion beyond dyadic ties. Drawing on 35 interviews, observations, and secondary data, the research advances the technology diffusion and innovation ecosystem literatures in three ways. First, it highlights the evolving role of focal actor as ecosystem leader, demonstrating their progression from transformational to collaborative and ultimately empowering roles across different phases of digital technology diffusion. Second, it identifies three orchestration mechanisms, namely knowledge orchestration, incentive aligned orchestration, and market driven orchestration, and specifies when each should be deployed in response to partner-specific requirements. Third, it offers a novel perspective on how ecosystem leaders shift value propositions to include both core and peripheral partners. From a practical standpoint, the study offers OEMs actionable guidance to diagnose their diffusion context and select appropriate orchestration mechanism. It also provides policymakers with insights for designing targeted instruments that strengthen digital diffusion and support sustainable industrial growth. • Orchestration mechanisms depend on partner-specific requirements. • Orchestrators' role evolve across different phases of digital technology diffusion. • Technology value propositions shift to include core and peripheral partners.

• Hydrogen supply chain framework developed for Central America. • Costa Rica and Nicaragua identified as strategic production sites. • Alkaline electrolysis chosen for cost-effective hydrogen production. • Liquefied hydrogen and ammonia selected as efficient energy carriers. • Electricity cost is the main factor in hydrogen production economics. This study presents a comprehensive framework for establishing a hydrogen supply chain network in Central America, encompassing Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, and Panama, in alignment with global decarbonization efforts. Utilizing Mixed Integer Linear Programming, the research assesses the techno-economic feasibility of hydrogen integration, focusing on its role in freight transportation and regional electricity supply. The findings highlight alkaline electrolysis as the preferred production method, with liquefied hydrogen and ammonia identified as optimal carriers. Costa Rica and Nicaragua emerge as key production hubs, supplying hydrogen to neighboring countries via sea transport. The estimated levelized cost of hydrogen is 10.84 USD/kg, largely driven by electricity prices, with projections indicating a reduction to 5.16 USD/kg by 2050. A comparative analysis suggests that under specific conditions, hydrogen could achieve cost parity with diesel by 2050. While acknowledging data limitations and socio-economic uncertainties, this study provides critical insights into hydrogen’s potential role in Central America’s energy transition, serving as a foundation for future research and policy development.

Spatial evolution and influencing factors of new retail supply chain networks: Freshippo case study

Research on supply chain optimization under different government subsidy strategies in the remanufacturing-insurance combination system

It is of great significance to unveil the supply chain dynamics of the primary microplastic pollutants as well as to identify the emission responsibilities of different regions and sectors. In this study, a clustering-aided multiregional input–output microplastic emission (CMME) model is developed through integrating the multiregional input–output model and hierarchical clustering into a general framework. The CMME model can trace primary microplastic emissions under production-based accounting (PBA), consumption-based accounting (CBA), and income-based accounting (IBA). It can also reveal the emission patterns across regions and sectors, providing a practical basis for differentiating responsibilities and formulating policy implications. The results reveal that the microplastic emissions in the eastern coastal provinces of China are dominant; however, their contributions vary along with different perspectives (PBA: Guangdong > Shandong > Zhejiang; CBA: Guangdong > Zhejiang > Jiangsu; IBA: Shandong > Guangdong > Jiangsu). The results show that, under all perspectives, transportation and textile industries are the main contributors of microplastic emissions. Provinces with abundant energy resources (e.g., Inner Mongolia and Xinjiang) have a large number of energy extraction and processing industries, which form an important microplastic emission cluster under IBA. The findings are helpful in clarifying the emission responsibilities of different regions and industries, providing a scientific basis for the Chinese government to formulate policies for reducing and controlling microplastics emissions.

The purpose of this study is to examine the impact of green innovation products on an organization’s social performance through mediation of green supply chain management. Using stakeholder resource-based view theory as a theoretical framework, the research model was developed with quantitative data from 170 managers in various industries in Israel that operate in international markets. The analyses of this study were done by structural equation modeling method via AMOS28 software. The findings show that both green innovation products and green supply chain management directly affect an organization’s social performance. Moreover, green supply chain management partially mediates the relationship between green innovation products and an organization’s social performance. That is, social performance in this study is driven by technological improvements in developing green innovative products, such as pre-designing products that minimize waste in production, more efficient utilization of raw materials, less hazardous materials, and reduction of risks to the public, as well as by selecting green suppliers throughout the supply chain and logistics. The main contribution of this study is an integrative model that combines two different disciplines – marketing and supply chains – into one integrative model that examines their joint impact on the organization’s social performance. The findings provide five main insights. First, managers who want to promote social performance in their organizations should adopt green innovation products to fulfill their customers’ needs. Second, combining green supply chain management with green innovation products can create new organizational processes that may respond to stakeholders’ requirements and environmental changes, improving the organization’s social performance. Third, these findings help stakeholders such as policymakers and regulators to encourage the integration of green innovative products based on green technology, along with the development and regulatory prioritization of green suppliers, leading to a green supply chain. Fourth, the introduction of green operational indicators and data transparency enables customers and the organization to purchase greener products, services, and raw materials. Finally, researchers can extend the study findings to identify similarities across industries, make cross-country comparisons, and examine the long-term impacts of green innovation products and green supply chains on social performance. • Green innovation and supply chain enhance organizational social performance. • Green supply chain partially mediates green innovation and social performance. • Green supply chain and innovation advance processes that respond to stakeholders.