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The conventional logistics’ paradigm is being replaced with smarter ways of supply chain management to readily serve the customers with quick modes of delivery in affordable operational costs. The weak infrastructure in rural terrain and congested roads in urban cities act as a big impediment in the successful accomplishment of last mile delivery down the lane across the complete chain of logistics. The traditional logistics has been evolved and improved in many respects, the last mile delivery is still plagued by security and privacy risks in logistics. The use of drones for package deliveries may offer promising gains in terms of efficiency. Nonetheless, drones undergo security and privacy risks besides physical threats for being deployed in public places communicating on open channels. Thus, more efforts are needed to secure the communication of inducted drones in delivery assignments. We propose a novel PUF-enabled drone access control mechanism PDAC-SL for smart logistics. By the careful employment of symmetric crypto-primitives, the contributed protocol not only supports low end devices but stands resistant to physical drone and other known threats besides preserving anonymity and untraceability features. The RoR model-based formal security analysis and performance analysis demonstrate distinct security properties and applicability of the PDAC-SL.

Research on agrifood supply chains has grown in recent years; however, little attention has been given to the effect of the choice of distribution channel on the sustainable and resilient performance of the network. This research proposes a system dynamics model to evaluate different distribution channels for a fresh food supply chain in a developing country. Among the main results is that the use of food hubs in a channel distribution produces long-term environmental, social and resilience benefits for the entire network, while short supply chains are the most economically viable alternative.

Nowadays, organizations must comply with high-quality standards, health and safety regulations, and socially sustainable practices to succeed in a globalized world. Supply Chains (SC) enable them to satisfy their customers' needs for quality products just in time and at the best price. However, management systems (MS) need to be improved to identify, evaluate, and control ergonomic risks, which opens a research opportunity for Ergonomics Management Systems (EMS) as they apply to sustainable SCs. This study aims to design and validate an instrument to assess the EMS within a SC using a continuous improvement approach. The study used convenience sampling as experts were invited by e-mail, at congresses, and through a digital platform. A response rate of 6.2 % was obtained from the latter, and a total of 34 experts responded to the instrument. An exploratory factor analysis (EFA) and a confirmatory factor analysis (CFA) were also carried out for the constructs of PLAN, DO, CHECK, and ACT. Finally, factors and variables were reduced by 42.71 %, leaving a 46-item final version of the instrument. Most of the structural model fit indices for the sample demonstrated good values, and the reliability indices were acceptable, this confirming the overall reliability of the instrument. In conclusion, the instrument was validated for all proposed constructs, with the exception of the PLAN construct. Thus, the instrument was found to be relevant and fit for implementation in EMS.

This study investigates the impact of recent global disruptions, focusing on the Covid-19 pandemic and the ongoing Ukraine-Russia war, on Hungary's wheat-flour supply chain, with a focus on price transmission and market integration. While much research has explored food supply chain disruptions and rising prices globally, there has been limited analysis of their effects on Central and Eastern European agricultural markets, particularly Hungary. This study fills that gap by using linear and non-linear cointegration approaches to examine price relationships along the wheat supply chain. Causality tests indicate a strong bidirectional relationship between producer and consumer prices, demonstrating a tightly integrated market. Cointegration analysis reveals a long-term equilibrium between these prices, with no significant structural breaks during either the pandemic or the Ukraine war. Despite short-term price asymmetries, the study finds that producer-level price changes are ultimately transmitted to consumer prices in the long run, offering insights into Hungary's unique agricultural market dynamics.

Context: Achieving zero hunger through food security, improved nutrition, and sustainable agriculture is one of the global agendas. Thus, the quality of seeds is important for ensuring sustainable food security, making seed certification critically important. However, classical seed certification systems are predominantly paper-based with limited digitisation. These systems, even digitised, are often centralised, and they face challenges related to transparency, traceability, and integrity. Objective: This study aims to investigate the practicality of blockchain technology in revitalising transparency, traceability, and integrity in the seed certification process. Methods: This study used a Design Science Research (DSR) approach to design and test a blockchain-based smart contract to improve the seed certification process. Within the DSR framework, the study used literature review and evolutionary prototyping to establish the requirements and design the prototype. Results and conclusions: The findings demonstrate the practical application of blockchain technology in improving aspects of transparency and integrity in the seed certification process. The findings further underscore that smart contracts can be leveraged efficiently to automate and enhance the seed certification process. The findings provide evidence-based frameworks for decision-makers and practitioners to justify the prioritisation of blockchain technology in designing future sustainable agricultural systems. Future studies should investigate how blockchain-based systems for seed certification can be scaled and integrated with existing agricultural systems. Significance: This study provides both theoretical and practical contributions on application of blockchain technology in the domain of seed supply chain. Specifically, it provides a comprehensive account of the design aspects of blockchain system in the seed certification process.

The purpose of this study was to investigate the extent of price transmission along the agri-food supply chain in selected regions in Ghana. The extent of transmission was used to assess the efficiency and effectiveness of the agricultural marketing systems in the area. Efficient marketing systems are expected to reduce the issue of regional price fluctuations, encourage fair income distribution throughout the supply chain, and improve food security. The preliminary time series stationarity/unit root and seasonality tests were performed using the Augmented Dickey-Fuller test (ADF)/Kwiatkowski, Phillips, Schmidt, and Shin (KPSS) and Canova-Hansen seasonal stability tests respectively. Following the detection of statistically significant threshold effects by the Supremum Likelihood Ratio (Sup-LR) tests, the extent of price transmission was investigated using two-region threshold vector error correction models. The initial tests found that the monthly wholesale, retail, and producer price series for maize, cowpea, and yam used in the study were first difference stationary rather than seasonally integrated. The findings revealed that price signals in the agri-food markets were not fully transmitted across the supply chain. Thus, the extent of price transmission was generally low, creating unexploited arbitrage opportunities along the chain. The study identified high transfer costs (proxied by the threshold parameter) and actor-specific market power (as revealed by the Granger causality test) as the primary obstacles to effective market functioning in the area. Minimizing transfer costs through infrastructural development such as improvements in road networks linking farming communities and markets, access to price information, and regular stakeholder engagements could help improve the functioning of the agri-food markets.

This paper presents a bi-level game model for pricing in a supply chain where the manufacturer (He) is the leader, and the retailer (She) is the follower. The leader decides on the wholesale price, and the follower decides on the selling price and selects seed nodes. The main idea of the model is that the marketing strategy used for promoting the product is focused on giving free samples to potential customers. Hence, the importance of analyzing a social network becomes evident. To maximize her profit, the retailer decides based on three factors: first, the leader's decision about wholesale price; second, the social network structure, which is critical for selecting the seed nodes; and third, people's valuation of the product. Therefore, a bi-level Mixed-Integer Nonlinear Programming model is developed to consider the social binds between potential customers. To solve this model, we employ a meta-heuristic algorithm. Finally, the effect of the model's parameters on decision variables and the objective functions is discussed. Based on the analysis and discussions, the production cost has a prominent impact on the players’ decisions and profits. Furthermore, instead of spending all the marketing budget on increasing seed nodes, it is suggested that they be spent on market research and improving good publicity. Moreover, deciding whether the players want to maximize the profit or market penetration is required before diving into decision-making.

The ongoing transition from a supply chain (SC) to net-zero emission (NZE) in SC performance must align with Sustainable Development Goal 13 to address climate change using life cycle assessment (LCA). Effective management of LCA significantly impacts an organization's competitiveness. With a lack of technology oversight and its connections with other enabling parameters that increase competitiveness, practices in the manufacturing industry remain limited. This study identifies and evaluates key enablers for LCA adoption in the manufacturing industry to achieve NZE in SC. Based on 123 responses, an exploratory factor analysis (EFA) was employed, followed by the Best-Worst Method (BWM). Further, a Fuzzy-Decision-Making Trial and Evaluation Laboratory (Fuzzy-DEMATEL) was used. The results revealed ‘organizational integration’, ‘data availability and quality, and ‘policy and regulation’ as significant group enablers that support NZSC to compete in the market. It provides insights for industry practitioners and policymakers on optimizing sustainable SC practices. The essential practical recommendations for resource optimization and carbon footprint reduction are also suggested.

In a Sustainable Supply Chain (SSC) context, information management offers a unique perspective on the digital economy and information management. Artificial intelligence (AI) is developing into a more robust digital field to facilitate quick information access and intelligent decisions in expanding commercial contexts. These days, Supply Chains (SC) would crumble without robust information systems. Applying AI and information management is crucial in determining the direction of sustainable supply chain management (SSCM). A systematic literature review (SLR) of the use of AI in SSCM is conducted in this research. The authors can identify crucial factors of the present literature using bibliometric and network analysis. AI is essential to the SSC to address sustainability challenges and manage the large volumes of data produced by numerous industrial processes. In the corpus of research that is already accessible, there is currently no comprehensive and bibliometric analysis of the potential for AI techniques for information management in SSC. Scientific publications were analysed from an objective point of view. Based on our results, we have drafted a proposal for an AI supply chain framework. Researchers, policymakers, and SCM practitioners may all benefit from the approach. This study is the first to analyse AI applications for information management in SSCM. In consideration of this, organizations are now exploring AI capabilities to improve operational efficiency and innovate their processes. This will assist industry people in understanding how AI methods support SC processes in their optimization to attain sustainability in SC practices.

Blockchain technology can enhance sustainable food security because of its distinct characteristics such as traceability, decentralized and unchangeable databases, and smart contract protocols. Nevertheless, blockchain technology in agricultural applications is still in the early stages of development. Therefore, this study aims to ascertain the efficiency and cognitive framework of blockchain technology for attaining long-term food security. This study used a review-based approach to ascertain the intellectual framework. A literature search was conducted using the ''Scopus'' database to locate research articles published between 2017 and 2023. A “systematic literature review” was performed using the PRISMA framework on the 52 eligible publications. The study results indicated that traceability, real-time information availability, and immutably distributed databases were the most influential factors. The results showed that blockchain technology has benefits beyond facilitating reliable data dissemination and establishing intimate bonds between manufacturers and clients. Furthermore, blockchain technology may pave the way for less food waste, improved supply chains and agricultural working environments, and more environmentally responsible eating practices. This study is the first of its kind to assess the intellectual structure of food security and augment the cognition of the in-depth examination of the benefits of blockchain technology that might ultimately provide a way to achieve zero-hunger goals.

Global market competitiveness and standards are pushing the manufacturing supply chain to adopt sustainable approaches to enhance quality, reduce waste, improve environmental practices, and optimize product costs. Blockchain technology has emerged as a promising tool for improving supply chain transparency and manufacturing sustainability. However, various challenges to the mainstream use of blockchain must be identified and addressed. In this regard, the study aims to identify and comprehend the challenges of adopting blockchain technology in the manufacturing sector to improve sustainable standards. To bridge this gap, the study used a three-step procedure. First, through a comprehensive literature review, 19 potential challenges were identified. Then, with the experts' discussion, a total of 18 challenges were finalized. In the second phase, data was collected from 15 professionals with industrial backgrounds. Lastly, the collected data was analyzed using Combined Compromise Solution methodologies and the Fuzzy-Decision-Making Trial and Evaluation Laboratory (fuzzy DEMATEL). This hybrid methodology prioritizes the challenges in blockchain adoption and categorizes them into causal groups. This improves the decision-making process by evaluating how the mutual impact of challenges in blockchain adoption affects achieving sustainability in the manufacturing supply chain. The outcomes of the presented work are validated through a sensitivity analysis of the outranked dimensions of blockchain adoption challenges. Results show that 'High Initial Investment Cost' and 'Lack of Digital Skills’ are the top challenges in its adoption. The findings of this work provide a roadmap to make the manufacturing supply chain sustainable and accomplish sustainability.

Climate change and other environmental consequences of socio-economic activities require a more sustainable and circular growth. At the same time, the limitation of the earth resource demands industries to improve resource efficiency and increase the rate of recycling of materials. There are several sustainable and circular alternatives that the industries may adopt. However, the question is that among these alternatives, which one should be selected for implementation for the highest sustainable and circular benefits. This study introduces a novel tool for assessing the sustainability and circularity of biomass-based energy supply chains, integrating multi-criteria decision-making methods with life cycle thinking approach. It evaluates five alternatives using a sustainability and circularity indicators, offering new insights into the deloyment of circular business models at companies in biomass-based energy supply chain. The tool is also applied to a specific rice straw supply chain in Italy, to assess the sustainability and circularity of five alternatives and outrank them. The results indicated that not all the alternatives are better in terms of supporting sustainable development and circular economy, compared to the baseline business model. In this supply chain, the extended lifetime for digestate from the aerobic digestion plant is the most ‘sustainable and circular’ alternative, while the capture of carbon dioxide from the same plant and its use for microalgae cultivation is the least ‘sustainable and circular’ alternative. A sensitivity analysis was conducted on different weighting sets during the assessment. It indicated that the priority of the decision makers can slightly change the outrank of the alternatives and the magnitude of the outranks.

Amidst escalating global supply system risks and interruptions, the imperative for fortified supply networks is evident. Organizations striving for competitiveness and resilience must adeptly recognize, comprehend, and address disruptions. This study presents a three-phase digital supply chain twin framework, leveraging discrete event simulation and neural networks to anticipate floods—a typical natural catastrophe and disruptive event—and predict recovery indicators. This aids supply chain (SC) managers in making informed decisions. In the first phase, machine learning algorithms, including logistic regression and Long Short-Term Memory (LSTM), were trained on Kerala India's precipitation data to predict floods. LSTM outperforms logistic regression, achieving flood prediction with 73 % recall, 75 % accuracy, and 84 % Area Under Curve-Receiver Operating Characteristics score. In the second phase, simulations replicate value chain breakdowns. A process flow logic-driven discrete event simulation within a real-world SC network emulates operational disruptions. FlexSim is employed to model service-level failures, influencing SC model performance based on the distribution center service level. The third phase employs simulated case scenario data to train a multilayer neural perceptron network (MLPNN) for predicting production network recovery post-disruptions. The MLPNN monitors the mean squared error (MSE) and disruptive inputs throughout training and validation, revealing consistent MSE reduction over recovery periods. The number of epochs needed to achieve a minimum MSE is used as a recovery indicator to predict service restoration time. Consequently, this study introduces a conceptual digital twin framework for catastrophic operations chain breakdowns and recovery prediction. The framework's output assists SC planners in shaping robust strategies by foreseeing disruptions and facilitating recovery.

Blockchain technology has promising benefits and provides robust solutions for managing business processes. While prior studies have primarily explored its potential in supporting logistics and supply chain management, many practitioners still lack a clear understanding of how to leverage blockchain technology, hindering its adoption within the industry. Bridging this gap and addressing critical barriers requires further empirical research. This study adopts a comprehensive approach, identifying potential barriers through a literature review and validating their significance through the Index of Item-Objective Congruence (IOC). The study then delves into the interrelationships among the significant barriers, utilising Interpretive Structural Modelling (ISM) and MICMAC methods. The results highlight seven significant barriers within the logistics sector, encompassing a lack of government support, operational standards, top management support, limited public awareness, trust issues, technical challenges, and network collaboration difficulties. Notably, the lack of public awareness and inadequate governmental support form fundamental obstacles that drive various challenges. This research offers insights into the barriers that hinder the successful adoption of blockchain technology in logistics, proposing several mitigation strategies that are in line with the principles of open innovation.

This study investigates whether and how customer firms’ environmental, social and governance (ESG) performance impacts suppliers’ green innovation quality using a sample of Chinese A-share listed companies from 2009 to 2022. We find that customers’ ESG performance facilitates suppliers’ green innovation quality through green learning and corporate competition. Additional tests indicate that customers with stickier customer–supplier relationships and a more central position in the supply chain network than peers enhance suppliers’ green innovation quality. After categorizing whether customers engage in greenwashing, we determine that those adherence to green principles, genuinely promote suppliers’ green innovation quality. Finally, we find the above effect ultimately enhances suppliers’ environmental performance. This study provides valuable insights for supply chain companies into collaboratively achieving sustainable development.

The adoption of climate-smart agriculture (CSA) is a critical component in the transition to a more sustainable food system. However, the transition calls for significant changes in the food production system, in which stakeholders in the supply chain should work collaboratively. So far, most studies have focused on the perceptions of one actor, the farmer, on implementation of CSA practices. This study aims to include also other stakeholders’ perceptions on drivers and barriers to CSA implementation in the primary production for five European food supply chains. Data were collected from stakeholders using a semi-structured interview guide, including farmers, producers and manufacturers, advisory service providers, advocacy institutions, policy officers, researchers, and consultants. The top three drivers to foster the adoption of CSA practices within the five food supply chains touched on economic, institutional and policy, as well as personal and psychological factors. Similarly, the top three barriers limiting adoption of CSA practices were seen to be economic, technology-related aspects, and institutional and policy factors. According to the stakeholders, addressing these barriers requires financial support, policy changes, and capacity-building efforts to make these practices attractive especially to farmers. They also emphasized that improved coordination among stakeholders, incentives for sustainable practices and customized strategies for communicating and disseminating CSA information can help catalyse effective understanding and implementation of CSA practices.

Logistics is critical in every company's supply chain (SC), and outsourcing helps businesses concentrate on their core competencies. Third-party logistics (3 PL) or logistics service providers (LSPs) assist businesses in cutting costs while improving performance, sustainability, and revenue. Logistics evaluation and LSPs choice are complicated and critical components of value delivery. This study aims to review logistics outsourcing literature to understand the trends, prospects, factors, and strategies used in logistics companies' outsourcing choices. This work examines the literature on LSPs selection published between 2010 and 2023. This paper uses VOSviewer (version 1.6.19) to visualize the relationships. Pricing, timely shipment, service quality, reliability, agility, technology, and consumer feedback are the most commonly utilized, whereas societal and environmental factors are seldom used. The study comprises journal publications, the year, selection criteria, and assessment methodologies. Numerous scholars have discovered and employed many critical selection criteria. Many investigators have also embraced multi-criteria decision-making (MCDM) methodologies, and their fuzzy form is widely used. In conclusion, recommendations for theorists and managers, limits, and future directions for research are offered.

Logistics and transport-production processes are critical components in the management of supply chains for enterprises. Increasing demands for the accessibility and efficiency of these processes necessitate further refinement of logistics theory and practice. The primary objective of this research was to establish the interrelationship between the structure and functioning of transport operations within manufacturing enterprises. The application of cluster analysis methods revealed the unique structure of each cluster, reflecting the specificity of transport operations. The obtained results determine the stability of the logistic cluster for a specific type of transport and its impact on overall efficiency. The research also emphasizes the importance of improving the quality of transport-production processes to ensure efficiency in supply chains. Quality and logistics service analysis identified factors that can be enhanced, such as service complexity, responsiveness to unforeseen orders, professionalism of the personnel, and fulfillment of order-related commitments. The conclusions drawn contribute to the development of logistics science and theory, providing practical insights by urging manufacturing companies to implement recommendations for optimizing their transport-production processes and selecting the most effective partners in this context. Thus, the originality of the article lies in expanding theoretical concepts of logistics and defining the specifics of transport-production processes.

Background: A “food system” approach to improve diet quality by intervening within areas such as food supply chains is gaining prominence. However, evidence of such interventions’ impact, and understanding of appropriate methods to evaluate them, is lacking. Objectives: We present an impact evaluation of an intervention that aimed to increase consumption of nutritious foods by supporting food-producing firms in Kenya. In doing so, we demonstrate how multiple methods, including those from other disciplines, can be used to evaluate a complex food systems intervention. Methods: Four methods focused on food-producing firms and their management, including a survey of intervention participants (n = 83 individuals), a “laboratory-in-the-field” experiment (n = 83 individuals), baseline/endline data on firm performance (n = 71 firms), and semistructured interviews (n = 19 firms). Three methods focused on consumers in neighborhoods targeted by a supported firm: a randomized field experiment tested effects of making a supported product exhaustively available on consumers’ purchases and consumption (n = 1295 consumers); 3 discrete choice experiments (n = 1295 consumers) tested factors influencing consumers’ willingness to pay for foods with relevant characteristics. Results: Among firms, we saw suggestive evidence of increased networking and business relationships, while laboratory-in-the-field experiments indicated the intervention might foster cooperation among participants. Qualitative interviews suggested that the intervention enabled firms to increase production, improve management, increase revenues, and lower costs. Baseline/endline data confirmed a positive effect only on the launch of new products and hiring workers. In the field experiment, consumption of the supported product increased in areas where it was made available relative to a control group, but this did not increase overall consumption of the food type or dietary diversity. Conclusions: Results showed positive signs of the intervention improving firm-level outcomes but limited impact on consumers’ diet quality. The evaluation also demonstrates how diverse methods can be used to evaluate complex interventions.

The rise in the cost of essentials affects every nation around the world, but it has become a major concern for developing nations. It is getting increasingly difficult to keep up with rising prices for everyday items in these countries, where the majority of the population is from the middle class or lower middle class. Inflation, pandemics, wars, and other important variables all contribute to price increases. There may be another significant factor at play, which is supply-chain corruption. The supply chain's unreliable, chaotic, and opaque nature is to blame for this corruption. We are concentrating on the agri-food supply chain in our study. Because many of the current agri-food supply chains are intricate and challenging to monitor, dishonest parties can exploit the situation. Therefore, we suggested a thorough blockchain-based agri-food supply chain to identify the source of price increases. The private Ethereum blockchain was used in the suggested system. Since the private Ethereum blockchain is more efficient, safe, and fast, it was chosen. Smart contracts were created to describe the system and its underlying rules and laws. Furthermore, in order to showcase the usefulness of our smart contracts, we exhibited a sample decentralized application to support our hypothesis. We also gave the system a complete security and vulnerability assessment to make sure it is operating properly and is protected from threats and attacks. Due to the use of blockchain, the system is immutable, transparent, and simple to track and monitor. The proposed system has demonstrated greater transparency, traceability, reliability, speed, security, and cost-efficiency compared to conventional systems. It effectively traces the origin of corruption in the supply chain, providing a more straightforward means to tackle concerns related to price hikes.

The utilization of blockchain technology in the fishing industry has been extensively studied and implemented to address issues such as illegal fishing and carbon emissions control. However, integrating blockchain with the vast amounts of data in the fishing supply chain poses significant challenges. Challenges include managing extensive data such as photos or videos for product traceability throughout their lifecycle, compounded by the growing complexity of cross-border trade and market expansion. Additionally, blockchain's storage capacity limitations present hurdles in fully accommodating and comprehensively storing detailed supply data from a complex and expanding supply chain.While solutions like the Interplanetary File System (IPFS) have been explored for large data storage on the blockchain, this paper proposes a directly integrated blockchain solution tailored for the challenges of fishing with big data. We introduce a novel big data design that preserves blockchain's anonymity and immutability features, addressing storage limitations while maintaining the architecture's purpose. Furthermore, our proposal integrates product supply chain traceability with carbon footprint tracking, enabling comprehensive assessment based on quality, sustainability, and carbon footprint criteria.Despite the proposed solution needing to be tested in real-life situations, we conducted rigorous testing through simulation, white-box evaluation, and complexity analysis. The results demonstrate the potential of our solution to address challenges faced in fisheries supply chains, providing valuable insights for future practical implementation and validation efforts.

The major sustainability concern is food waste, which might be minimized by more effective redistribution of surplus food, supply chain waste management, and sustainable food management. Due to technological and infrastructure issues that require technology application at a wide scale with minimal environmental impact, food waste and food loss occur at all levels of the supply chain. Strategies for food redistribution, recovery, and reuse provide the economy with extra by-products and financial advantages. Because of the complicated relationships between distributors and suppliers, contractual obligations, inaccurate food demand forecasts, and food standards, changing consumption and production patterns at the industry and market levels is difficult. Based on this the objective of the review was to discuss the strategies for reducing food waste and achieving sustainable development goals and the role of different actors in reducing food wastage and in implementing SDGs. Several Sustainable Development Goals (SDGs), including those related to finishing world hunger (SDG 2), ensuring sustainable agriculture (SDG 2), promoting sustainable economic growth (SDG 8), and combating climate change (SDG 13), among others, have been found to depend on reducing the amount of food that is wasted and have destroyed.

The article aims to propose a comprehensive approach to sustainable practices and risk resilience in a circular economy within the supply chain of a manufacturing company, addressing current challenges in sustainability, risk, and resilience. The interconnectedness of these aspects with the circular economy in the supply chain context is emphasized. The study employs fuzzy DEMATEL and fuzzy AHP tools in its design to address sustainable practices, risk resilience, and the circular economy in the manufacturing company’s supply chain. Fuzzy logic facilitates the management of imprecision and uncertainty, allowing for a flexible and precise evaluation. Fuzzy AHP focuses on ambiguous and subjective criteria, while fuzzy DEMATEL aids in understanding causal relationships among criteria, considering their fuzzy nature and interdependencies. Findings indicate that Supplier 1, Manufacturer 2, and Distributor 1 are the optimal choices, while efficiency (CSC1), security (RR3), and other criteria are identified as the most influential factors. The uniqueness of the study lies in its specific application and adaptation to the paint manufacturing supply chain sector, with a focus on sustainability, resilience, and the circular economy. The distinctive contribution involves customizing established methodologies to address sector-specific challenges, providing a practical tool for strategic decision-making. By applying an integrated approach based on fuzzy DEMATEL and fuzzy AHP techniques to the Peruvian paint company, the study offers a valuable perspective on the criteria for significant improvements in management, promoting sustainability, and the circular economy at the local level.

In the realm of healthcare, medicine and the pharmaceutical supply chain exert notable influence. Recognized as a strategic commodity, any disruption in its supply chain can precipitate significant crises. The dispersed nature of pharmacies and the critical need for prompt medication delivery to patients underscore the paramount importance of designing an optimal pharmaceutical supply chain. This necessity is particularly pronounced when addressing the needs of diabetic and epilepsy patients, who, being more susceptible and in urgent need of medication, intensify the significance of a robust supply chain. Given the critical role of medicine and the pharmaceutical supply chain in healthcare, the repercussions of supply chain disruptions are far-reaching. A well-designed pharmaceutic supply chain is indispensable, especially in ensuring timely access to medications for vulnerable patient groups. To address this imperative, this study proposes a multi-stage scenario-based mathematical model aimed at enhancing the responsiveness of demand regions amidst uncertain budgets and feasible scenarios for meeting the insulin and phenobarbital requirements of patients. By incorporating uncertainties in both demand and procurement costs, the practicability of applying this model in real-world contexts has been strengthened. A case study focusing on Kerman City in Iran is conducted to evaluate the efficacy of the proposed model.

This paper addresses knowledge gaps related to implementation of corporate zero deforestation commitments (ZDCs). Drawing on an analytical framework of organizational change, we scrutinize changes and processes internal to a company in adjusting to zero deforestation supply chains. The empirical data consists of 48 online questionnaires and 49 online interviews with actors involved in forest-risk commodity supply chains, both internal actors in companies and external actors (e.g., non-governmental organizations). Concerning organizational changes, the findings show that diverse drivers have triggered companies to adopt ZDCs, but most are external drivers. Organizational change following ZDCs has taken place within companies but only to a limited extent. Our study concludes that while corporate ZDCs can be seen as having advanced private governance in the fight against deforestation, more is needed still for effective implementation. Public governance and regulations could play an increasing role in stimulating adoption and implementation of private governance initiatives, like corporate ZDCs.

Modular construction (MC) plays a pivotal role in fostering sustainable development. However, the promotion of MC in many jurisdictions has been encumbered by its prevailing undeveloped supply chain. This study aims to systematically explore the drivers, opportunities, constraints, concerns, strategies, and measures with regard to enhancing the MC supply chain, using the empirical case of modular integrated construction in Hong Kong and the supply chain in the Greater Bay Area of China. The research was conducted through the combination of a literature review, a questionnaire survey with 244 effective responses, and 46 expert interviews. A systematic framework with foremost drivers, opportunities, constraints, concerns, strategies, and measures is proposed for guiding MC supply chain enhancement from technical, political and regulatory, socio-economic, and geographical perspectives. The findings contribute to better understanding the complexity and dynamics of the MC supply chain and guide stakeholders to work collaboratively for supply chain enhancement.

The sustainability of the sugarcane agro-industry supply chain plays a crucial role in providing economic benefits, minimizing social and environmental impacts, and optimizing resource utilization. This research aims to analyze the sustainability performance of the sugarcane agro-industry supply chain using multi-criteria assessment and formulate strategies for sustainability improvement. The study proposes a multi-criteria assessment model with twenty-eight indicators and four dimensions of sustainability: economic, social, environmental, and resources, which were developed based on previous research. The fuzzy inference system (FIS) and multi-dimensional scaling (MDS) methods were utilized to analyze the multi-criteria indicators of sustainability performance in each dimension and overall supply chain. The Adaptive Neuro Fuzzy Inference System (ANFIS) model was used to aggregate multi-dimension sustainability to achieve overall sustainability performance. A fuzzy cognitive map (FCM) framework was developed to formulate strategies for improving the sustainability performance of the supply chain. The research was verified at two sugar mill locations in Java Island, Indonesia. The FIS and MDS models successfully analyzed the sustainability performance of the two sugar agro-industries, showing an average value of “quite sustainable”. The overall sustainability performance using the ANFIS model for mill A and B were 57.2 and 61.9, respectively. Series of FGDs combined with the FCM model successfully formulated five clusters of strategies as initiatives in improving the sustainability performance, namely raw material provision, harvesting and post-harvest activities, production process optimization, IT-based technology implementation, and institutional aspects. This present work seeks to contributes to the development of multi-criteria of sustainability performance for the food industry's supply chain. It also proposes a comprehensive framework for analyzing and improving sustainable supply chain performance under uncertainty using a combination of conventional and fuzzy assessment modeling approach. A practical initiative strategy in sustainability improvement is revealed for the sugarcane agroindustry's supply chain.

Securing visibility and dependable information from stakeholders poses a significant challenge for companies engaged in supply chain management. Timely and accurate information exchange is crucial for assessing factors such as carbon emissions and consumer demand. This paper explores the impact of digital and carbon reduction technologies on supply chain decisions, incorporating fuzzy logic and blockchain technology for enhanced decision-making. We specifically focus on a single buyer ordering from a vendor, where faulty items are promptly returned upon inspection. The lead time for the initial delivery includes both production and non-productive time, while successive deliveries only entail transportation time. The research employs intuitionistic triangular fuzzy numbers to represent all carbon factors and integrates blockchain technology to improve demand forecasting. The purpose is to determine the optimal strategies to minimize the carbon and joint total cost of the system. A solution methodology has been proposed for determining optimal strategies, illustrated through a numerical example. The optimal decisions are compared, both with and without blockchain, to validate the proposed model. The findings suggest that blockchain has a substantial impact on both optimal decision-making and the results of carbon reduction efforts. Sensitivity analysis reveals that a blockchain-based supply chain is both time- and cost-efficient, reduces costs and errors in data information, and efficiently shortens lead time in the network.

This article proposes a supply chain-based green hydrogen microgrid modelling for a number of remote Australian communities. Green hydrogen can be used as an emissions-free fuel source for electricity generation in places where large-scale renewable energy production is impossible due to land availability, population, or government regulations. This research focuses on the Torres Strait Island communities in northern Australia, where the transition from diesel to renewable electricity generation is difficult due to very limited land availability on most islands. Due to geographical constraints, low population and smaller electrical load, the green hydrogen needs to be sourced from somewhere else. This research presents a green hydrogen supply chain model that leverages the land availability of one island to produce hydrogen to supply other island communities. In addition, this research presents a model of producing and transporting green hydrogen while supplying cheaper electricity to the communities at focus. The study has used a transitional scenario planning approach and the HOMER simulation platform to find the least-cost solution. Based on the results, a levelised cost of energy range of AU$0.42 and AU$0.44 was found. With the help of a green hydrogen supply chain, CO2 emissions at the selected sites could be cut by 90 %. This study can be used as a guide for small clustered communities that could not support or justify large-scale renewable generation facilities but need more opportunities to install renewable generation.

Inventory management challenges are optimizing inventory levels, minimizing stockouts, and streamlining the supply chain process for the vendor and the customer. The study tries to improve these challenges by proposing a new Viable Supply Chain (VSC) incorporating Vendor-Managed-Inventory (VMI) with a Consignment Stock (SC) policy for managing inventory between SC components. These strategies access the inventory level of the customer in the vendor, and if the items are sold, the customer pays the vendor for the inventory that was sold. The Robust Stochastic Optimization (RSO) with Conditional Value at Risk (CVaR) as risk criteria is utilized to solve the model. The objective function of this model combines the expected value, maximum, and CVaR of cost. To promote viability against disruption, sustainability requirements such as CO2 emissions and energy consumption are considered. An agile approach that includes a learning factor is suggested. In addition, a resiliency strategy by addressing order disruption requirements is proposed. The case study of this research is a small healthcare industry that prepares drug products. It is one of the largest industries with high sales and added value. The results show that the inclusion of VMI and CS in the main problem-solving approach resulted in a 14.8 % cost reduction compared to the scenario where VMI and CS were not considered. Finally, sensitivity analysis is performed on CVaR confidence, conservatism coefficient, learning rate, agility rate and scale of the main problem.

Sustainable packaging is a crucial focus in the context of circular economy efforts. This study evaluates the circularity of two secondary packaging systems used in Spanish fresh food produces: Reusable Plastic Crates and Single-use Cardboard Boxes. A Mass Flow Analysis was performed to assess the material flows in the production and use phases of both systems and two circular indicators were applied: the Material Circularity Indicator and Product Circular Indicator. While most previous studies for single-use packaging use these indicators at the product level, this study applies a system approach since the Reusable Plastic Crates can be reused 100 times. The functional unit was defined as the distribution of 1000 tonnes of fresh products, resulting in the distribution of 6,666,700 packages with 15 kg of products. The Material Circularity Indicator and Product Circular Indicator results show that Reusable Plastic Crates are more circular than Single-use Cardboard Boxes. The Product Circular Indicator provides a more comprehensive assessment of circularity by considering multiple life cycle stages, efficiency, and unrecoverable waste, resulting in a difference in circularity evaluations. The indicators used have limitations as they do not consider the resource stock. Further research is needed to explore this aspect.

Managing degraded-quality materials in a supply chain with a single-vendor and multi- buyers is prevalent and critical in modern industry. This research addresses the single-vendor multi-buyer problem by incorporating multiple raw materials and quality degradation to maximize joint total profit (JTP). The proposed model utilizes the Whale Optimization Algorithm (WOA) for optimization, with empirical data derived from an agri-food industry case study in Indonesia. Experimental findings demonstrate the superior effectiveness of WOA compared to Chim optimization algorithm (ChOA), Genetic algorithm (GA), (GWO), Particle Swarm Optimization (PSO), and heuristic algorithm in solving the single-vendor multi-buyer problem. Sensitivity analysis reveals noteworthy insights: increased demand boosts total profit and production cycle efficiency, while elevated shipping costs for finished products negatively impact JTP by reducing production efficiency. Moreover, escalating quality degradation rates decrease JTP and production cycle time. This study significantly contributes to optimizing single-vendor and multi-buyer operations by addressing multiple raw materials and quality degradation, offering valuable insights into sensitivity analysis for critical factors in the agri-food industry.

Understanding the economic efficiency of pond-based fish culture in tropical developing countries is essential for defining development programs. This study was designed to describe the aquaculture of tambatinga in various farm sizes that is being performed in a region close to the equator in Brazil called the midnorth. The major focus was on the economic performance and the relationship between different farm sizes and downstream value chains. We also describe the attractiveness of investments in small farms. A purposive sample of commercial tambatinga farms was taken. Sixteen farms were selected which encompassed a representative sample of progressively increasing production areas, ranging from 0.1 ha to 220 ha. Complete enterprise budgets were developed for each farm based on standard budgeting techniques, and indicators of financial feasibility were computed. The farming of tambatinga in the midnorth is performed in semi-intensive levee or watershed pond systems in farms of various levels of complexity and different production strategies. All farms perform a monophase cycle, stock small fingerlings (3 to 6 g) and feed fish with a commercial diet. Yield, net income, economic profit, net present value, internal rate of return and benefit/cost ratio were found to decrease as farm size increased. Payback period and break-even point increased as farm size increased. Small aquaculture farms (≤ 1.5 ha) had a vertical business structure and presented a more effective economic performance. They are also attractive as family investments. This model of enterprise can boost rural economies and reduce poverty in developing countries. Large farms (≥ 17 ha) were not economically feasible because they do not operate in the market and sell their production at lower prices. Increasing farm size should go hand in hand with improvements in technology to be feasible.

The utilization of soybean as a key oil crop to enhance sustainable agriculture has garnered significant attention from researchers. Its lower water requirements compared to rice, along with its reduced environmental impact, including greenhouse gas emissions, improved water quality, enhanced biodiversity, and efficient resource utilization, make it an attractive option. Unfortunately, Iran, like many other developing countries, heavily relies on soybean imports (over 90%) to meet the demand for oil and protein in human and livestock food rations. The decline in soybean production, coupled with diminishing cultivation areas, yield rates, and increasing import needs, underscores the urgent need to address the challenges faced in Iran. The decline in soybean production in the country can be attributed to various factors, including environmental stresses (both biotic and abiotic), limited variation in soybean cultivars, inadequate mechanization for cultivation, and economic policies. Hence, this review provides a comprehensive overview of the current status of soybean production in Iran and highlights its potential to enhance sustainable agriculture. Additionally, it examines the challenges and constraints associated with soybean cultivation, such as environmental changes and unbalanced marketing, and explores potential solutions and management strategies to bridge the gap between small-scale and large-scale production. Given the increasing global demand for plant-based protein and the significance of the feed industry, studying the limitations faced by countries with slower soybean production growth can shed light on the issues and present opportunities to capitalize on novel soybean advancements in the future. By addressing these challenges and unlocking the potential of soybean cultivation, Iran can contribute to sustainable agricultural practices and attain a more resilient food system.

This study developed a novel framework that combined data envelopment analysis and multi–regional input–output database to investigate the economic and environmental productivity change in the global supply chains associated with 18 manufacturing sectors in 43 countries from 2000 to 2014. Two models are developed; manufacturer model is used to evaluate performance of direct production activity of a sector in countries and supplier model is used to evaluate performance of indirect production activity of upstream suppliers of the sector. The proposed framework enables us to separately analyze the performance of supply chains into direct production activity and indirect production activity of suppliers. The empirical results show that the environmental productivity of direct production activity of 18 manufacturing sectors was improved by 12.9 percent, while the environmental productivity of the upstream suppliers was improved by only 4.7 percent during 2000–2014 on average. Different patterns of economic and environmental productivity growth were observed between the direct production activity and upstream suppliers in all sectors. The finding suggests that the performance of an entire supply chain should be separately analyzed to consider industry-specific policies. The proposed framework is used to identify countries that succeed/fail to improve economic and environmental performance. Based on the results, this study discusses policies regarding production and supply chain management toward CO2 mitigation.

Prepared foods bring great convenience to people’s lives, but they also entail safety risks in all aspects, from production to sales. The cooperation of the supply chain and the supervision of the government are key to promoting the safety management of prepared foods. This paper considers the government’s regulation, focuses on the interaction relationship between the producer and the retailer of prepared foods, and builds an evolutionary game model to analyze the influence of collaborative decision-making between prepared food producers and retailers in preventing and controlling food safety risks under the government’s regulatory strategy. The research finds that: (1) Under certain conditions, there are three stable equilibrium strategies within the prepared foods supply chain: bilateral low-safety inputs, unilateral high-safety inputs, and bilateral high-safety inputs. (2) Government regulators can influence the safety input behaviors of prepared food supply chain enterprises by adjusting investigation probabilities and punishment severity. (3) The safety input behaviors of these enterprises are influenced by various factors, including costs, revenues, brand image, reputation, and the consequences associated with contractual violations. This paper represents the first systematic analysis of prepared food safety from a supply chain perspective. It fills a gap in the existing literature in this area, offering guidance and suggestions for prepared food supply chain enterprises, as well as references and recommendations for government regulators.

Teff is a gluten-free cereal crop widely cultivated in Ethiopia and is a critical ingredient in making injera, a unique flatbread. However, there is a significant issue with adulteration of teff, impacting its safety and quality. This study evaluated economically-driven adulteration effects on teff grains' nutritional and microbial quality. A preliminary survey revealed that it is a common practice to adulterate teff grains with inexpensive and inedible materials throughout the supply chain in the study area. One hundred and thirty teff grain samples were collected from producers, collectors, whole-sellers, and retailers in the cities of Tulu bolo and Jimma to determine the types and extents of adulterants present and their effect on the nutritional and microbial quality of the grains. They were mixed separately to create composite samples representing different supply chain actors. Standard protocols were used to evaluate nutritional and microbial quality. The results showed significant differences among the supply chain actors regarding identified adulterants, nutritional content, and microbial quality. The study identified chaff, soil + sand, and dukkaa (a combination of nonedible substances separated from teff grains in milling houses and warehouses) as the significant adulterants, with mean ranges of 1.17–8.07%, 1.29–7.23%, and 8.93–37.13% respectively. The study also evaluated the proximate composition and microbial load of the teff samples collected from different supply chain actors. The ranges of values for moisture, protein, fat, ash, fiber, carbohydrate, and energy were 8.33–10.53%, 6.49–9.42%, 2.29–3.86%, 2.33–6.39%, 2.42–3.95%, 70.9–73.76%, and 333.52–361.9 kcal, respectively. The microbial load showed ranges of 6.92–7.98, 3.17–3.22, 1.78–2.04, 6.73–7.89, and 6.88–7.93 log CFU/g for Total Plate Count, Escherichia coli, Salmonella, mold, and yeast, respectively. The results showed an increase in teff adulteration from producers to Jimma retailers, indicating multiple-stage adulteration throughout the supply chain, posing a threat to product safety and quality. The study recommends good coordination among the bodies responsible for food safety, producers, and consumers to mitigate this issue effectively.

Pipe spool supply in Korean shipbuilding industry consists of a complex supply chain comprising manufacturing and painting vendors. Major Korean shipyards with the most competitive edge have applied various policies and techniques to control the pipe spool supply chain and prevent production delays related to supply delays in pipe spools. Although research has been done on implementing the policies and techniques, there has been a gap on the theoretical consideration of pipe spool supply chain characteristics using a simulation model. Therefore, this study proposes an analytical method based on queueing model to analyze the characteristics of the pipe spool supply chain and also proposes a simulation model based on discrete event simulation (DES) to verify it. In addition, a numerical experiment using DES for the M/G/1 queuing model is conducted to examine the effect of time variability in the spool supply chain. From the more reliable experimental results, control parameters and management insights to manage the supply chain optimality are proposed and the effectiveness of policies that have been implemented by major shipyards is verified.

The goal of this review study is to look into the most important sustainable practices that fresh food startups can use to improve their resilience and environmental responsibility. It also aims to identify the difficulties and impediments these companies face when putting these sustainable strategies into effect. Fresh food startups can integrate several sustainable techniques and innovations into their operations, as identified by the study. These include using IoT technology to enhance supply chain management and implementing packaging with a modified environment to keep goods fresher for longer. The review also emphasizes the difficulties these firms have had putting these strategies into practice. The review's findings have important real-world ramifications for fresh food entrepreneurs. Through the development and improvement of their sustainability initiatives, they can make their business operations more robust and ecologically conscious. This review adds to the corpus of current knowledge by methodically analyzing the most recent advancements in fresh food supply chains, particularly with regard to startups. It illuminates the particular difficulties they encounter in promoting sustainability, making it an important and novel contribution to the area.

Background: Investigating the causes and impact of essential medicines and supplies shortages in the supply chain of the MOH in Saudi Arabia could be the initial step in setting innovative strategies for mitigating this issue. This study aimed to identify the key factors contributing to essential medicines and supplies shortages in the supply chain of the MOH in Saudi Arabia and assess their impact on healthcare delivery. Methods: A structured questionnaire was designed to collect relevant data on the causes and impact of essential medicines and supplies shortages. A representative sample of healthcare professionals, from various healthcare MOH facilities in Saudi Arabia. The Statistical Package for the Social Sciences (SPSS) software version 26 was used for the data analysis. Results: A total of 379 respondents participated in the study, 73.7% were males, 51.2% were aged 36–45 years, 23.5% were supply chain professionals, and 32.9% reported an experience of >15 years. 90.0% of the participants reported that they personally have experienced shortages of essential medicines and supplies in the MOH supply chain in KSA. Inadequate planning, forecasting, and procurement were identified as the most significant contributing factors for shortages by about half (48.5%). At least two-thirds of the participants agreed with all strategies adopted for mitigating the issue of shortages. Conclusions: The impact of shortages on patients and healthcare professionals was found to be substantial. The study also identified several key strategies to reduce shortages that received strong support from the participants.

A distributed and decentralised ledger system shared by a variety of users in a peer-to-peer network is defined as a blockchain. Through its decentralised approach, it makes pharmaceutical products more accessible and secure for vendors, while they can maintain and access their inventories themselves. Between a company and its suppliers, a supply chain is used to produce and distribute a specific product or service, whose efficiency is increased with its integration in the supply chain. For efficient and transparent tracking of products, blockchain will be the right choice. In view of blockchain being incorporated into the supply chain system, it solves many logistical issues that supply chains face, such as appropriate data access, ensuring data quality, and many more. This can increase the traceability of the material supply chain and improve the maintenance of the list when there are several products to be supplied. Therefore, the concept of supply chain was developed in two platforms namely, Hyperledger Fabric and Hyperledger Sawtooth. Finally, Hyperledger Sawtooth was found to be well suited for creating decentralised apps or platforms with respect to resource utilization It enables developers to separate their application domain from the core system so that business rules for apps can exist without requiring knowledge of the primary platform's underlying architecture. The proposed system shows that Hyperledger Sawtooth framework consumes lower CPU than Fabric which helps in increasing the number of transactions.

Transportation plays a key role in combating human trafficking. This paper discusses data from the 2021 National Outreach Survey for Transportation (NOST), from the first ever United States Department of Transportation Combating Human Trafficking in Transportation Award winning project. Survey data collected from transportation personnel, victim service providers, and trafficking survivors reinforces the documented perceptions, limitations, and challenges in understanding and combating forced labor discussed among frontline workers. Among 173 respondents working in various state DOT construction units, only 26 % feel slightly or very confident (19 % and 7 %, respectively) about identifying labor trafficking in their work environment. Participating transportation workers confirm specific training topics that may help to identify forced labor proximate to the work environment or within the community, transportation-related venues, and events. Respondents from multiple transport modes also provide valuable suggestions on how personnel and industry leaders can help combat human trafficking in supply chains. For the primarily U.S.-based transportation respondents, the most suggested strategy for encouraging companies to use products free from forced labor in their supply chains was high penalties (1,229 respondents), followed by loss of tax benefits (850 respondents) (total n = 1,766).

This review article explores and locates the current state-of-the-art related to application areas from freight transportation, supply chain and logistics that focuses on arrival time, demand forecasting, industrial processes optimization, traffic flow and location prediction, the vehicle routing problem and anomaly detection on transportation data. This review categorizes the related works according to machine learning methodologies so as to present the methods’ evolution through time, their combinations and their connection with the various applications in the specified fields. Thus, a reader would effortlessly get insights about the current state-of-the-art related to machine learning in freight transportation and related application areas.

Background: The global supply chains of essential medicines faced frequent disruptions over the past five years, particularly during the COVID-19 pandemic. Different causes of prescription drug supply interruptions have been identified in Saudi Arabia. However, studies have yet to explore the views of pharmaceutical supply chain personnel regarding the causes of these interruptions. Therefore, this study aimed to survey individuals working in the pharmaceutical supply chains about their views on the observed interruptions in the supply of some essential drugs. Methods: This was a questionnaire-based cross-sectional study. The 10-item questionnaire was created based on the findings of previously published research that investigated the root causes of essential drug shortages and the impact of COVID-19 pandemic on the supply chains of essential drugs in Saudi Arabia. Purposive sampling was used to identify individuals with at least one year of experience in the area of the pharmaceutical supply chain, and the data collection occurred between April 19th, 2022 and October 23rd, 2022. In addition, descriptive statistics (e.g., frequencies and percentages) were conducted to present the views of the respondents. Results: Seventy-nine pharmaceutical supply chain specialists accepted the invitation and completed the questionnaire. About two-thirds (69.62%) of the respondents reported that centralized pharmaceutical procurement negatively affected the supply chain of essential drugs. Procurement of unregistered medications by the Saudi Food and Drug Authority (SFDA), as well as generic drugs with a history of recalls, and failure to supply requested quantities were the three most commonly reported reasons behind the observed interruptions in the supply of some essential drugs according to those respondents with a negative view of the centralized procurement. Furthermore, failure of pharmaceutical companies to inform SFDA of potential drug shortages, manufacturing issues, poor demand forecasting, unpredictable increase in demand, and low prices of essential drugs were also believed to be behind the observed interruptions in the supply of some essential medicines. Conclusion: The majority of surveyed pharmaceutical supply chain professionals held negative views about the role of centralized pharmaceutical procurement in exacerbating the issues with essential medicines supply chain. Future research should examine different strategies to improve purchasing and procurement practices in Saudi Arabia.

We present a novel variational inequality model (VIM) to capture the complex real decision-making process in multi-tiered supply chain networks (MSCN) without strictly limiting the features of related functions. The VIM is formulated with the equilibrium conditions on links as the optimization goal and the flow conservation condition as the main constraints. We transform the VIM into a series of equivalent Non-Linear Programming Models (NLPMs) to solve. To address this challenge, we propose a novel population-based heuristic algorithm called the Multiscale Model Learning Algorithm (MMLA). The MMLA is inspired by the learning behavior of individuals in a group and can converge to an optimal equilibrium state of the MSCN. The MMLA has two key operations: zooming in on the search field and learning search in a learning stage. The excellent performers, called medalists, are imitated by other learners. With the increase in learning stages, the learning efficiency is improved, and the searching energy is concentrated in a more promising area. We employ sixteen benchmark optimization problems and two supply chain networks to demonstrate the effectiveness of the MMLA and the rationality of the equilibrium models. The results obtained by MMLA for the NLPM show that the MMLA can solve the equilibrium model effectively, and multiple optimal equilibrium states may exist for an MSCN. The flexibility of the NLPM makes it possible to consider more complicated decision-making mechanisms in the model.

This study triangulates three interrelated and interdependent goals. First, we provide a framework to establish the supply chain (SC) theory within the linchpins of the nine waves of sustainability theory. Second, we provide a real-world example of how blockchain operates to support the premise that hacking a blockchain requires very large capacities of computing power. We also demonstrate a method of detecting the possibility of hacking individual nodes that supply information to the blockchain. Third, we utilize the blockchain and gather thousands of data points and prove statistically that the tokenization of the oil and gas industry will increase market liquidity, market volume, profitability, and sustainability while reducing transaction time. The robotic blockchain is investigated as a mechanism for improving the efficiency of natural gas SC resource use through fuzzy modular function hashing and salting algorithms and entropy density.

The implementation of occupational health and safety management in the supply chain by core enterprises is a significant step towards improving the working conditions of their suppliers. To guide core enterprises to adopt active and effective management modes, it is crucial to identify the characteristics of different management modes and classify them accordingly. This paper employs the grounded theory method to conduct an in-depth analysis of occupational health and safety management modes within the supply chain of core enterprises. This research mainly adopts semi-structured interview method. A total of 16 person-times are interviewed, and 210,000 words of in-depth interview scripts are obtained. After three coding process of the grounded theory，the evolution model of occupational health and safety management modes in supply chain by core enterprises was established. The research results indicate that core enterprises currently employ three modes of occupational health and safety management for their suppliers: defensive mode, passive mode, and strategic mode. Different modes have distinct characteristics in four dimensions of cognition, motivation, strategy and result. This research may provide strategic guidelines for core enterprises to evolve from the defensive mode to the strategic mode.

Integration of lean-green practices has benefited companies in many ways, particularly the large ones. Small and Medium Enterprises (SMEs), as key players within supply chains, should also be encouraged to apply the lean and green practices to support the large enterprises in the supply chain. However, it remains all time challenging for SMEs that operate with limited resources, and often emphasize on short-term goals with rapid turnaround. The impact of green-lean practices on sustainability performance has been investigated earlier, however further study is needed to understand the phenomena in context of SME supply chain. This study examined the moderating effects of top management commitment and leadership (TMCL) and organizational culture transformation (OCTr) on the relationship between Lean Practice (LP) and Green Practice (GP). Further, it investigated the moderating effect of both policy initiative (PI) and collaborative synergy (CS) on the relationship between GP and sustainability performance. The survey-based study analyzed the data from 345 Indonesian manufacturing SMEs using structural equation modeling (SEM) with Smart-PLS. The findings suggest that GP mediates LP to improve sustainability performance of SMEs. TMCL facilitates significantly the adoption of integrated lean and green practices. Meanwhile, OCTr, PI, and CS did not have a significant moderating effect. It means that OCTr does not significantly moderate lean practices for the adoption of green practice. Similarly, results demonstrate that neither PI nor CS moderate the correlation between green practice and sustainability performance of supply chain in manufacturing SMEs. The findings help SME owners or managers to build a comprehensive model of a lean-green system to direct SMEs to achieve sustainable development.

As being environmentally responsible is a potential source of competitive advantage, incorporating genuine environmental practices across the supply chain may help firms capitalize on the growing demand for corporate accountability and consumer awareness. Therefore, it is important to understand to what extent firms are using greenwashing to mislead their stakeholders in the supply chain. The purpose of this paper is to review the existing literature regarding greenwashing in supply chain management (SCM) to shed light on the main thematic groups addressed in the literature, understand its challenges and develop a framework that highlights the key drivers that companies need to tackle to prevent greenwashing in supply chains. For this purpose, we have conducted a systematic literature review, following a three-stage method. It was possible to identify possible solutions to prevent greenwashing across four main dimensions of SCM: consumers/customers; relationships between focal firms and suppliers; certification programs and reporting assessment; and corporate leadership. We provide a framework to help firms develop their sustainable strategy and prevent greenwashing along the supply chain. This paper synthesizes the challenges that firms face when implementing a sustainable supply chain, suggests solutions to prevent greenwashing and provides future research avenues.

Soursop (SSF) is a popular fruit in the southern region of Vietnam. It is a fruit that contains many essential nutrients and antioxidant components, which are good for human health. However, the process of transportation and storage at the stages before reaching the consumer has been greatly affected by natural conditions. In this study, we looked at the impact of each stage in the supply chain on physicochemical and biological quality. 11 indicators were evaluated throughout (Bonded rating, mass loss rate, moisture content, hardness, vitamin C content, total polyphenol content (TPC), total flavonoid content, DPPH• and ABTS+ scavenging activity). The supply process is distributed in 2 popular distributors, markets and supermarkets with supply chain times of 105 h and 197 h respectively. The results have shown that the supply process by supermarket distributors is capable of maintaining better product quality and less variation in physicochemical/bioactive composition. The increase in DPPH• and ABTS+ scavenging activity is proportional to the increase in TPC. Vitamin C is significantly depleted in both supply chains. The research results are a premise for the development of soursop protection solutions at each stage through knowledge of the variations of biologically active substances and physicochemical properties of SSF in the supply chain corresponding to the ripening of SSF. A database that assists suppliers in making the right decisions to prevent quality, and economic losses.