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.

This research aims to analyze and synthesize findings from various empirical studies on the implementation of supply chain management (SCM) strategies and their impact on company performance in the 2014-2024 timeframe. This research uses the literature review method by collecting and analyzing relevant scientific articles from various sources, such as academic journals, conference proceedings, and research databases. The articles selected are empirical studies that directly discuss the implementation of SCM strategies and the measurement of company performance. The results of the literature review show that effective implementation of SCM strategies has a positive and significant impact on firm performance. SCM strategies that focus on increased collaboration with suppliers and customers, business process integration, efficient information sharing, and the use of information technology are proven to improve operational efficiency, reduce costs, improve product quality, speed up delivery times, and increase customer satisfaction. In addition, the research also highlights the importance of aligning SCM strategies with the company's overall business strategy to achieve optimal performance.

Integrating third-party logistics (3PL), forecast accuracy and emission management in triadic supply chains − a large language model-based approach

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.

Purpose Implementing Internet of Things (IoT) is fundamental to the digitalisation of modern supply chains. This paper aims to provide a theory-based explanation for the impact of IoT implementation on information integration, decision-making uncertainty and hence supply chain performance. Design/methodology/approach This study adopts a qualitative multiple-case study approach to investigating three fast-fashion supply chains in China through 30 semi-structured interviews. Findings The findings demonstrate that IoT is implemented in the information collection, selection and sharing processes of information integration. Implementing firm-level information collection and selection processes impacts information quality and is linked to environmental uncertainty. Whereas implementation in the supply chain level information sharing process impacts information accuracy and efficiency and is linked to industry uncertainty. Research limitations/implications This research advances the theoretical understanding of IoT’s role in supply chain management through a two perspective Information Processing Theory-based framework, capturing the mechanisms which underpin the interactions between IoT-enabled information integration and decision-making uncertainty and resultant impact on performance. Practical implications This research provides a road map for supply chain managers demonstrating how IoT implementation in information integration processes within the firm can improve operational performance. However, when this implementation progresses to supply chain level information-sharing processes, management costs improvements are ultimately realised. Originality/value This study contributes an empirical, evidence-based explanation of the impact of IoT implementation on supply chain performance. Case study evidence from firms in the early and middle stages of IoT implementation reveal that the mechanisms governing the interactions between information integration, decision-making uncertainty and their impact on performance are fundamentally different for firm and supply chain IoT implementation processes. It is only in implementing the information sharing process at the supply chain level that cost benefits are achieved.

Against the fast-growing digital economy, corporate digital transformation has shifted from an option to a must for sustainable development. Digital transformation refers to integrating digital technologies like big data, cloud computing and AI into all business links. This paper analyzes its internal and external drivers: external drivers include fierce market competition and rapid tech upgrades that push enterprises to transform for competitive edges; internal drivers are the urgent need to boost operational efficiency, cut costs and optimize resource allocation. The paper also outlines the transformation’s multi-dimensional outcomes, such as upgraded operation models, better user experience and stronger risk resistance. It proves the transformation’ s practical value with manufacturing and service industry cases: manufacturers have achieved smart production and precise supply chain management; service providers have realized personalized customization and efficient online-offline integration. Finally, the paper forecasts the future trend of deeper integration between digital tech and business scenarios, plus wider transformation coverage. Research shows that market competition, tech progress and internal efficiency demands are core drivers. Efficiency improvement, model innovation, experience optimization and resilience enhancement are core value manifestations. These two aspects form a mutually reinforcing cycle, providing solid theoretical and practical references for enterprises’ orderly digital transformation.

Artificial Intelligence (AI) is increasingly shaping agribusiness transformation in Nepal by improving productivity, sustainability, and market integration within a largely smallholder-based agricultural economy. This article examines the current status, applications, opportunities, and constraints of AI adoption in Nepal’s agribusiness sector using a comprehensive secondary desk review of academic literature, policy documents, and development reports. Key AI applications include precision farming, satellite-based crop classification, predictive analytics, and digital advisory services across crop, livestock, and supply chain management. Initiatives such as GeoKrishi, Connect Kisan AI, and the Omdena-UNWFP collaboration illustrate AI’s potential to enhance resource efficiency and climate resilience. However, adoption remains limited due to infrastructure gaps, high costs for smallholders, data scarcity and localization challenges, low digital literacy, and evolving policy and regulatory frameworks. Drawing on insights from other emerging markets, the study adapts the extended Technology Acceptance Model-Technology-Organization-Environment (TAM-TOE) framework to contextualize AI adoption in Nepal. The article concludes that inclusive and scalable AI-driven agribusiness transformation will require coordinated stakeholder engagement, targeted investments in digital infrastructure, skills development, and robust data governance mechanisms.

State corporations are instrumental in dispensing the government’s functions and mandates, thus streamlining economic growth and development. With procurement being responsible for the largest portion of government’s spending, state corporations spend a significant amount of state resources. These agencies, however, continue to record a decline in performance despite being the biggest consumers of government revenue. The agencies have been blamed for inefficiency and poor integration of technological systems in their procurement processes, leading to gaps that see inefficiencies and ineffective management of public funds. While integration of electronic procurement in these corporations has been explored, key aspects of e-procurement such as electronic contract management remain under-explored. This study examined the extent to which state corporations have embraced electronic contract management and whether it has contributed to their performance. Descriptive correlation research design was adopted. The study targeted supply chain managers from 248 state corporations in Kenya. Using a sampling formula, a sample of 153 respondents was obtained and selected through a stratified random sampling technique. A questionnaire used to collect data for the study, which was analyzed using descriptive and inferential statistics. The findings revealed that electronic contract management significantly influenced performance of state corporations in Kenya. It was concluded that most of the corporations had not effectively embraced electronic contract management and this affected their performance. It is therefore recommended that the state corporations through the management ought to integrate electronic systems in managing contracts as a way of promoting effectiveness and efficiency in contract implementation. Keywords: Electronic Procurement, electronic Contract Management, Organizational Performance, state Corporations

Modern supply chain management faces unprecedented challenges in demand forecasting and inventory optimization due to increasing market volatility, consumer behavior complexity, and global disruptions. Deep learning (DL) has emerged as a transformative approach that addresses these challenges by capturing complex nonlinear patterns in demand data and optimizing inventory decisions across multiple echelons. This review examines the current state of DL methods applied to demand forecasting and inventory optimization in supply chains. Recurrent neural networks (RNNs), long short-term memory (LSTM) networks, convolutional neural networks (CNNs), and transformer-based architectures have demonstrated superior performance compared to traditional statistical methods. The integration of DL with reinforcement learning (RL) has enabled adaptive inventory policies that respond dynamically to changing market conditions. Graph neural networks (GNNs) have proven effective in capturing network dependencies across complex supply chain structures. Despite these advances, challenges remain in model interpretability, data quality requirements, computational complexity, and real-time implementation. This paper provides a comprehensive analysis of DL architectures, hybrid approaches, performance metrics, and practical applications while identifying critical research gaps and future directions for advancing intelligent supply chain management systems.

Egg production forecasting is crucial for managing the agricultural supply chain, as it impacts operational planning, market stability, and environmental sustainability. Efficient egg production ensures dietary needs are met and economic stability is maintained in the agricultural sector. Accurate forecasts aid resource allocation, market demand prediction, pricing optimization, and mitigation of supply chain disruptions.This research compares the efficacy of ARIMA (Autoregressive Integrated Moving Average) and LSTM (Long Short-Term Memory) models in predicting trends in egg production. Historical data spanning several decades were utilized, and the models’ performance was evaluated using the Root Mean Squared Error (RMSE). ARIMA, a traditional statistical model, and LSTM, a recurrent neural network, were applied to the data. The LSTM model demonstrated a significantly lower RMSE (2,299.54) compared to ARIMA (13,394.96), indicating superior performance in capturing the underlying patterns in egg production data. The LSTM model provided forecasts that were closer to the actual figures, particularly reflecting the upward trend in production from 2019 to 2021. The findings suggest that LSTM models are more effective for forecasting in agricultural contexts due to their ability to handle complex, nonlinear data. This can lead to better resource allocation, optimised supply chain management, and more stable market conditions. The study highlights the potential for integrating advanced machine learning models into agricultural forecasting to enhance decision-making processes. Future studies could explore hybrid models that incorporate external variables to further enhance forecast accuracy and reliability.

Performance evaluation of sustainable supply chain management based on deep reinforcement learning

Abstract As competition has shifted from individual firms to entire networks, supply chain management has become central to operations research. The extensive body of related work has advanced both supply chain practice and management mathematics theory. Yet, sustainable supply chain management has not received the same depth of treatment. In this editorial, we argue that sustainability cannot simply be added to existing models through small modifications. It requires developing a brand-new perspective on model-based research. We propose four key features that models for sustainable supply chains must incorporate. First, they need to handle trade-offs across different dimensions of sustainability. Second, they must look beyond single companies to examine whole supply chains. Third, they should account for the wider uncertainties involved in measuring environmental and social impacts. Fourth, they need to embrace circular economy principles. The four articles in this special issue show how new mathematical methods can address these challenges. We conclude by discussing future research directions that would help incorporate the inherent complexity and uncertainty of sustainability problems.

The local government in South Africa is important in providing critical services to communities, although local government is tasked with critical service delivery functions, many faces systemic challenges when fulfilling this responsibility. Mkhondo Local Municipality is no exception, challenges such as inefficiency, inadequate resource management, and limited public participation. This study is grounded in consequential theory, which underscores the significance of outcomes in assessing actions. This theoretical framework facilitates the exploration of strategic actions to enhance service delivery in Mkhondo. The aim of this article was to propose effective strategies to enhance service delivery at Mkhondo Local Municipality. This article adopted a qualitative methodology, with purposive sampling to select ten experienced participants from the supply chain management and finance units. Data was collected through one-on-one, semi-structured interviews with 10 key municipal staff members. The interview transcripts were analysed thematically using NVivo 12 to identify and organise the emerging themes. The results highlighted several barriers, including ineffectiveness of performance monitoring, inadequate procurement transparency, and minimal community involvement. The article recommends the implementation of performance-based accountability, improved stakeholder participation, and transparency in municipal procedures. It is recommended that municipal strategies are aligned with consequential theory to significantly improve service delivery. These interventions can foster greater transparency, efficiency, and public trust, providing a model for similar municipalities across South Africa.

Informal supply chains ensure the circulation of essential goods despite significant local constraints. In rural villages in sub-Saharan Africa, community networks organize the transport of basic foodstuffs despite impassable roads, distant markets, and seasonal supply fluctuations. In urban diasporas in North America and Europe, communities structure the transnational circulation of food, clothing, and cultural products, overcoming limitations in market access and regulatory frameworks. Drawing on the concept of social capital—structural, relational, and cognitive dimensions—the analysis highlights how actors anticipate needs, adjust operations in real time, and maintain the continuity of flows under variable conditions. The illustrations from rural and urban contexts broaden understanding of logistical mechanisms beyond conventional approaches centered on efficiency and optimization. Insights gained from these illustrations suggest pathways for hybrid supply systems that reconcile formal efficiency with local adaptability. By linking anthropology and supply chain management, the article provides an original perspective on how social relationships, local knowledge, and embedded practices shape resilience and operational agility in informal supply chains.

This paper aims to explore the current status and emerging trends of corporate supply chain management within the context of intelligent supply chains by conducting a comparative analysis of the supply chain systems employed by three typical high-tech enterprises, namely Apple, Xiaomi, and Huawei. Adopting a case analysis method, the study systematically examines the theoretical foundations of intelligent supply chains while providing a detailed analysis of the distinctive features and strategic approaches that characterize the supply chain management practices of these three corporations. The findings indicate that Apple has significantly enhanced production efficiency and reduced inventory by implementing a global outsourcing strategy and building an agile and efficient supply chain network. Huawei has remarkably improved operational efficiency and market competitiveness by focusing on digital and intelligent upgrades and constructing a high-end supply chain system integrating intelligent procurement, manufacturing and logistics. Xiaomi has achieved rapid market response and cost control by adopting a hybrid and agile collaborative supply chain model based on ecological cooperation and digital empowerment. The study concluded that the evolution of intelligent supply chains presents both unprecedented opportunities and challenges for corporate supply chain management.

Introduction Bilateral engagement between Saudi Arabia and Nigeria in the halal food sector has recently gained prominence for its potential economic benefits. Despite this growth, limited research has examined how medicinal plants and fruits can be integrated into the halal food industry across both countries. An even greater gap exists regarding the role of Islamic banking and finance experts in facilitating this integration. Objective This study explores the potential involvement of Islamic banking and finance experts in supporting the integration of Nigerian medicinal plants and fruits into Saudi Arabia's halal food sector. Methods The study adopts a library-based research design using analytical content analysis. It reviews secondary data and existing literature from Saudi Arabia and Nigeria to identify prospects, challenges, and opportunities for harmonizing medicinal plant and fruit products within the halal ecosystem. Results Findings indicate that Nigeria's abundant medicinal plants and fruits present significant value for Saudi Arabia's halal sector. Successful integration requires Nigerian farmers to comply with Saudi halal standards, particularly regarding supply chain management and certification. Islamic banking and finance professionals, together with halal industry stakeholders, contribute to ensuring that plant- and fruit-based products meet Islamic dietary regulations—such as avoiding alcohol in extraction and preventing contamination with nonhalal substances. Existing studies largely focus on anti-infective and cardiovascular applications, reflecting prevalent health needs and traditional practices that rely on halal, Sharī‘ah-compliant natural resources. Implications Experts in Islamic banking and finance should actively engage producers, suppliers, distributors, and consumers to uphold halal standards across the supply chain in both countries, thereby strengthening cross-border collaboration and value creation in the halal food industry.

Purpose This study, grounded in the natural resource-based view (NRBV) theory, aims to investigate how green practices influence firms’ sustainable performance (SP), and to examine the roles of organisational green culture (OGC) and corporate green image (CGI) in this relationship. Design/methodology/approach A quantitative approach was adopted, with data collected from 364 manufacturing enterprises in China. To assess the relationships between OGC, green practices and SP, the study used partial least squares structural equation modelling (PLS-SEM) and artificial neural network (ANN) techniques, combining both linear and non-linear analyses. Findings Organisational green culture significantly promotes the adoption of green human resource management (GHRM) practices, green supply chain management (GSCM) practices and green innovation, all of which positively enhance sustainable performance. Moreover, corporate green image strengthens the impact of these green practices on sustainable performance, indicating that firms with a well-established CGI achieve superior performance outcomes. Originality/value This study contributes to the theoretical development of the NRBV theory by applying it to OGC and SP within the manufacturing sector. It emphasises the importance of GHRM practices in promoting employee engagement with environmental objectives. By combining PLS-SEM and ANN techniques, the study provides deeper insights into how cultural and reputational factors influence sustainable outcomes, offering strategic guidance for human resource practitioners and decision-makers aiming to align organisational, managerial and employee needs for optimal SP.

ABSTRACT Composite smart contracts coordinate vaccine supply chains, where multiple contracts run in parallel and inputs are uncertain. Existing verification tools typically capture concurrency while assuming crisp inputs, or handle uncertainty while omitting explicit interactions among contracts. This separation reduces detection power and weakens formal guarantees under realistic noise and interleavings. A fusion of Fuzzy Logic (FL) and Colored Petri Nets (CPN) (FL–CPN) models both aspects in one framework. The FL layer converts uncertain measurements into crisp scores; the CPN layer encodes places, transitions, colors, and guards; integration maps scores to token colors and guard enabling so that fuzzy outcomes drive execution. This enables formal verification and vulnerability analysis of composite smart contracts under uncertainty and concurrency. Contributions are: (1) a formal FL–CPN integration with algorithms and execution semantics; (2) a verification workflow covering safety, liveness, and reachability with attack path tracing; (3) case studies on counterfeit insertion and temperature log tampering with rule driven token flows and mitigations; (4) an empirical comparison against CPN, FSM, and NuSMV using 10‐fold cross‐validation and standard metrics. Across folds, the approach achieves precision 0.9828–0.9937, specificity 0.964–0.988, sensitivity 0.973–1.000, accuracy 0.9758–0.9933, and F 0.9733–0.9908. The method extends to other supply chains and multi‐party blockchain workflows that combine uncertain evidence with concurrent contract interactions.

ABSTRACT Supplier selection and transportation are critical to supply chain management, as they directly affect purchasing performance and material flow efficiency. However, balancing procurement and transportation costs while ensuring supply reliability remains insufficiently addressed in the literature. This paper explores the impact of transportation on supplier selection and order allocation by proposing a multi-criteria decision support model based on mathematical programming. The model minimises total costs, including purchasing, ordering, transportation, and inventory, while considering delivery quality, supplier capacity, and buyer demand, with inventory managed across multiple stages encompassing suppliers, transit, and buyer. It then determinesefficient suppliers and optimal order quantities assigned to each. To validate the model, it was applied to a real-world case in the French railway sector. The results demonstrate that integrating transportation planning into the supplier selection process reduces costs while enhancing supply chain reliability and overall performance. The study also highlights relevant directions for future research.

ABSTRACT The climate crisis and global commitments to achieve net-zero emissions by 2050 have intensified the focus on renewable energy. However, Australia’s renewable energy sector faces significant challenges, particularly reliance on imported materials and technologies. This study evaluates trends and policy developments, identifies challenges to Australia’s renewable energy transition and proposes strategic recommendations to enhance economic viability and environmental sustainability. A review of 45 selected studies based on the energy transition theory, sustainable supply chain management and global-local interdependencies, reveals key barriers such as reliance on fossil fuels, grid integration issues and regional disparities. These findings highlight the need for technological innovation, policy reforms and strategic investments to strengthen grid resilience and build sustainable supply chains. Australia has strong potential to lead the global renewable energy transition by expanding domestic manufacturing capacity, upgrading infrastructure and fostering coordinated action between government and industry. A comprehensive conceptual framework is presented to guide sustainable sector development. This study also identifies priorities for future research, including advanced grid technologies, local production systems, recycling practices and region-specific energy strategies to support a resilient and competitive renewable energy ecosystem.