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This paper comprehensively analyzes a company's supply chain design process in the pulp and paper industry. It focuses on the company's supply chain strategy, structure, operations, and performance and highlights the challenges and opportunities specific to the industry. The purpose of this case study is to show how effective supply chain design can improve a company's competitiveness and success. This paper also offers recommendations for improving supply chain design in the pulp and paper industry and other similar industries. [ABSTRACT FROM AUTHOR]

With growing environmental concern and supply chain uncertainty, now is a fitting time to re-evaluate solvent-free methodologies in forensic chemistry processes. Here, this paper reviews solvent-free approaches for fingermark visualisation, including chemical fuming and vapour phase treatments, dry-transfer treatments, application of heat, and thermal paper specific treatments. After providing historical context, three objectives have been emphasised: identify feasible scenarios for implementing solvent-free methods; showcase the effectiveness of solvent-free methods relative to their nearest solution-based equivalent; and estimate the technological readiness level of each method discussed. Having reviewed the literature, dry-transfer methods of developing latent fingermarks on paper were found to be the most promising and feasible solvent-free approaches for near-term implementation. Such methods make use of standard materials and equipment commonly found in forensic laboratories, are effective at fingermark visualisation, and mitigate most of the pressing issues pertaining to environmental concern and solvent scarcity. [ABSTRACT FROM AUTHOR]

This paper studies the recycling and remanufacturing mode and sales channel issues in the closed-loop supply chain. Specifically, this study establishes an e-commerce closed-loop supply chain consisting of a manufacturer and an e-commerce platform, and divides the recycling model into recycling by the manufacturer or recycling by the platform. Considering two common sales models in e-commerce platforms: the resale model and agency model, combined with the recycling model, four different research scenarios are formed. We use backward induction to solve the Stackelberg game problem and explore the remanufacturing and channel strategies of the manufacturer and the e-commerce platform. The research results show that for the manufacturer, under the same recycling model, when consumers' preference for remanufactured products and the sensitivity of recycling volume to recycling prices are low, he will prefer the resale model. Under the same sales model, the manufacturer always prefers the recycling model in which he is responsible for recycling. However, the choice of platform is contrary to that of the manufacturer. In the resale model, both the manufacturer and the platform will choose to recycle by themselves, which cannot achieve a win-win situation. Under the agency model, when consumers' preference for remanufactured products is high and the sensitivity coefficient of recycling volume to recycling price is low, supply chain members can achieve a win-win situation, and the scope of the win-win situation decreases as the unit production cost of new products increases. In addition, rising consumer preference for remanufactured products will lead to lower consumer surplus. [ABSTRACT FROM AUTHOR]

The paper examines local and global logistics involved in the transfer of animals to and from zoos in the twentieth century. The key contexts discussed here are, on the one hand, the relationship between the Museum für Naturkunde Berlin (Museum of Natural History) and Berlin Zoo, and on the other hand, trade in and the market of exotic animals, a market that both exceeds and constitutes the institutions of the museum and the zoo. Taking the accidental death of a giant tortoise in the zoo in 1969 as its starting point, the paper studies the movement of animals, dead and alive. It traces the acquisition history of two new Galápagos giant tortoises by following the animals' trajectory from Ecuador to West Berlin during the Cold War. At the same time, it reconstructs the itineraries of the dead animals' remains through different natural history institutions, leading into the shared history of trade and traffic between zoos and natural history museums and into the political geographies of the Cold War. To put these episodes into a broader historical context, the article looks back on the expansion of global networks in animal trade through the lens of transport infrastructures, trading networks, and the accompanying red tape, tracing this back to the period around 1900 in order to reveal genealogies, thereby historicizing current logistical practices, policies, and problems. Taking logistics as a critical analytical category for natural history and thus examining natural history as logistics allows us to gain new insights into how logistics not only enabled but also shaped and reshaped natural history's material, economic, and epistemic frameworks. [ABSTRACT FROM AUTHOR]

To address the problem of positioning customer order decoupling point (CODP) in customized logistics service supply chain and to provide logistics service integrators (LSI) with various CODP decision-making and supplier selection solutions. We consider LSI, logistics service providers (LSPs) and customers and propose multiobjective nonlinear team optimization models for multi-CODP location, including minimizing the cost to the LSI and maximizing the synthetic satisfaction of LSPs and customers. This paper adopts an improved nondominated sorting genetic algorithm (NSGA-II), in which the key modules such as the crossover operations, chromosome structure and mutation operations are reconstructed, to solve the team models and investigate the Pareto-optimal front for the two objectives. To demonstrate the validity of NSGA-II and the reliability of mathematical models, cases from a specific dataset are generated and solved. Moreover, a classic genetic algorithm (GA) is applied to solve for the two objectives separately. The optimal solutions found by GA are f 1 = 2027.491, f 2 = 0.7704 and f 1 = 2454.512, f 2 = 0.8909. The corresponding optimal solutions in the Pareto-optimal solution set are f 1 = 2053.675, f 2 = 0.7715 and f 1 = 2427.114, f 2 = 0.8843. We find that the optimal solutions provided by GA cannot dominate any solution in the Pareto-optimal solution set, indicating that the results are valid and sufficiently convergent. In summary, the results of this paper provide LSI with easy access to various supplier selection schemes with multi-CODP, which is essential to reduce the cognitive burden on decision makers and address the diverse customization needs of many challenging real-world logistics issues. [ABSTRACT FROM AUTHOR]

Off-site construction (OSC) is an environmentally friendly building method with substantial benefits, yet it encounters challenges, particularly in supply chain efficiency. Current research on off-site construction supply chain (OSCSC) challenges faces issues such as dispersion, cross-disciplinarity, and timeliness. This is despite a number of studies in recent years focusing on the optimization of OSCSC to improve their performance and efficiency. However, the current literature still lacks a comprehensive summary of OSCSC problems, which hinders the popularization of OSC. To address this, improve OSCSC efficiency, and enhance OSC practicability, this paper conducted a thorough review of 244 published articles. Utilizing bibliometrics and scientometrics methods, it identified research trends, prominent researchers, and topics. Current OSCSC issues were further extracted and classified from the internal supply chain perspective. The findings reveal key issues hindering OSCSC efficiency, offering practitioners, policymakers, and researchers a nuanced understanding of current research issues. In addition, this paper provides future research directions and performance optimization recommendations, contributing to solving OSCSC challenges and exploring innovative solutions for continuous improvement in the OSCSC field. [ABSTRACT FROM AUTHOR]

In traditional supply chain finance, the financing of enterprise mainly relies on the credit segmentation of the core enterprise, resulting in a short trust transmission radius and poor financing ability. The development of Internet technology, while expanding financing channels, has also seen an increasing severity in issues such as information fraud and data breaches, which has further aggravated the trust crisis in supply chain finance. This paper integrates blockchain technology into the industrial internet platform and analyzes the applicability of both in empowering supply chain financial trust. Then a supply chain financial trust framework, which emphasizes information sharing, data security, and trust circulation, is proposed. Furthermore, combined with the theories of Funk-SVD and entropy value, this paper designs a global trust evaluation mechanism that facilitates the trust circulation in supply chain finance and proposes a recommendation algorithm for global trust. With the testing conducted using the Epinions dataset, it is found that the algorithm proposed in this paper has a strong data dimensionality reduction and concentration ability, especially for large sample data, it can obtain more accurate evaluation values with less space occupation, thus enhancing the trust circulation ability of supply chain finance. Finally, the paper puts forward specific policy recommendations for the implementation of the supply chain finance information mechanism, aiming to better improve the financing accessibility of enterprises in supply chain, particularly small and medium-sized enterprises. [ABSTRACT FROM AUTHOR]

The efficiency and responsiveness of supply chains are vitally dependent on inventory replenishment and transportation decisions. In this paper, we study a supply chain consisting of a single retailer ordering seasonal products within the newsvendor framework. The primary objective of the paper is to investigate the retailer's decision-making process, aimed at determining the optimal replenishment quantities and selecting the appropriate mix and size of the truck fleet. Initially, we formulate a mathematical model where the retailer exclusively manages a limited fleet of its own trucks for inbound transportation of a single seasonal product. In this context, we determine a lower breakeven point for the fixed transportation cost than what has been previously proposed in the literature. Subsequently, we examine a commonly encountered transportation scenario where the retailer has the opportunity to expand its fleet size by leasing trucks from the external market. The outcomes of the numerical example indicates that the flexibility resulting from the utilization of different types of trucks can lead to reduced overall costs. We also address the practical transportation problem of efficiently shipping various seasonal products solely with the retailer's own trucks. For this complex problem, we propose an optimal solution procedure based on Lagrangian method. We show that the joint replenishment of multiple products results in cost savings and enhances utilization of the trucks' capacities. [ABSTRACT FROM AUTHOR]

The rapid development of supply chain finance (SCF) has significantly alleviated the financing difficulties of small and medium-sized enterprises (SMEs). However, it is important to recognize that within the accounts receivable financing segment of the SCF credit market, the credit risk associated with SMEs poses a serious challenge and potential threat to the stability, health, and sustainable development of the SCF system. This paper pays special attention to the stability of the two-party evolutionary game between SMEs and financial institutions (FIs) within the context of the Chinese SCF credit market. To identify a pathway to reduce credit risks for SMEs while simultaneously enhancing system stability, this paper adopts the stochastic evolutionary game (SEG) model and combines the fixed-point method to determine the conditions that satisfy the stability of the system's index p mean square of the system. This study has made attempts in various aspects, such as the innovative construction and investigation of a nonlinear SEG model, the endeavor to study the stability of SEG systems using fixed-point methods, and the innovative construction of a more realistic two-player SEG system. The data and simulation results generated from hypothetical scenarios show that the conclusions of the article are credible and feasible. Through the study, we conclude that the higher credit ratio from FI and the higher penalty intensity from core enterprises (CEs) will accelerate the stability of the system. Based on solid data and modeling analysis, insights into the regulation of FI are provided. [ABSTRACT FROM AUTHOR]

Continuous changes in today's market have exposed supply chain (SC) management to severe challenges. Such changes in the market are divided into two general categories: (1) Time-dependent changes such as political, economic, and cultural changes occurring over time and require decision-makers to consider the dynamics of decisions; and (2) Sudden changes and events such as diseases and natural disasters disrupting SCs. This paper investigates the impact of both changes on the decisions of a green supply chain. Moreover, these challenges may affect the organizations' activities in the market and arouse a conflict in the members' goals, leading to competition among members. This paper studies a game model for a dynamic–stochastic supply channel SC with one manufacturer and one retailer, where two types of products (green and non-green) are sold. In this study, two models are dynamically considered: The first model without demand disruptions and the second model with demand disruptions. Finally, the results are compared. On the other hand, due to environmental goals and to survive manufacturers under disruption, the government supports manufacturers in producing green products. Implementing this cooperation, the manufacturer also invests more in improving the greening level of green products, thereby enhancing its demand. Regarding numerous disruptions common in the automotive industry, this case study is conducted on the automotive supply chain to evaluate the models, and the results are presented in the form of numerical examples. Finally, to extract managerial insights, sensitivity analysis is performed on the main parameters of the problem. [ABSTRACT FROM AUTHOR]

This paper examines demand information value and acquisition strategy for a supply chain composed of a supplier and a retailer under supplier encroachment, and considers the situation that both the enterprises can obtain information directly from the market. The problem is formulated with a Bayesian game model. A signaling mechanism is considered, i.e., the supplier's demand information will be signaled to the retailer through wholesale pricing. Under the signaling mechanism, this paper analyzes whether it is still worthy to the supplier and the retailer of acquiring information at a non-ignorable cost under dual information asymmetry. Moreover, this paper examines the interaction between channel substitution rate and information acquisition. Furthermore, subsidies for inducing information sharing and the signaling effects on the payoffs are also explored. The results propose strategy selections of encroachment and information acquisition based on cost thresholds. A double information inaccuracy effect is discovered, which comes from the fact that an enterprise receives the signal from another supply chain member as well as acquires information from the market. It is interesting to find that the information inaccuracy does not necessarily have a negative effect due to double information inaccuracy. The inaccuracy rate has a positive effect first and then a negative effect on the payoffs of the supply chain under certain conditions. The value of signaling of demand information is analyzed, revealing that lower substitution rate will make the signaling mechanism have a positive impact on the enterprises payoffs. Some managerial insights are presented in the end. [ABSTRACT FROM AUTHOR]

Designing a green supply chain is becoming popular in the context of sustainable development. To address this academic concern, this paper designs a multi-product, multi-echelon green supply chain network (GSCN) from economic and environmental aspects. During the modeling process, the main challenge is to access the accurate probability distributions of uncertain parameters from limited historical data. To overcome this difficulty, this paper develops a distributionally robust design framework for bi-objective GSCN, where the distribution information of uncertain parameter is partially available and characterized by ambiguity sets. For the tractability, this paper discusses robust counterpart reformulation under Wasserstein-distance-based ambiguity sets. Finally, the obtained mixed integer programming model is resolved via commercial optimization software. To validate the proposed optimization framework, we design a meat supply chain network for a Chinese realistic food enterprise. The computational results demonstrate that the proposed distributionally robust model can provide reliable solutions compared with stochastic optimization method. [ABSTRACT FROM AUTHOR]

In order to explore the international competitiveness of China's agricultural product supply chain, this paper combines machine learning algorithms to optimize the data processing process of agricultural product supply chain, and proposes a data processing method for agricultural product supply chain based on the intra‐column rules and inter‐column rules. According to the problems of my country's agricultural product supply chain, this paper establishes a new agricultural product supply chain management model based on the various modules of the supply chain link, and constructs a corresponding intelligent analysis model. Moreover, this paper combines machine learning algorithms to study the improvement path of the international competitiveness of China's agricultural product supply chain, and builds an intelligent model to improve the international competitiveness of China's agricultural products. Finally, after constructing the model, this paper obtains the path to improve the international competitiveness of China's agricultural products through the simulation operation model, which also verifies the effectiveness of the intelligent algorithm of this paper from the side. [ABSTRACT FROM AUTHOR]

In view of the rapid development and application of blockchain technology, this paper considers a secondary supply chain system consisting of a single upstream supplier and a downstream e-tailer that implements blockchain technology and a traditional e-tailer that does not implement blockchain technology. We establish the demand function of two channels based on consumers' sensitivity to the blockchain and use the Stackelberg game model to compare and analyse the e-tailers' profits from the two channels. For the basic properties, interestingly, we find that there exists a critical threshold on the cost sensitivity to effort that helps each e-tailer decide whether to implement effort. If the cost sensitivity to effort is high, the two-sided e-tailers will reduce their effort as much as possible to obtain greater profits. Conversely, if the cost sensitivity to effort is low, they will increase their effort to obtain more benefits. We also discuss the role of blockchain technology in competition between e-tailers and analyse the impact of the product brand effect brought by the traceability characteristic of blockchain on the competition between e-tailers. To check the robustness of the core results and to investigate different forms of supply chain configurations, this paper further develops the analysis of the supplier entering agency agreements with two-sided e-tailers. Under this scenario, the supplier sells their products directly to consumers through two-sided e-platforms and shares revenue with e-tailers as platform agency fees. These core ideas remain valid in the extended model. [ABSTRACT FROM AUTHOR]

The COVID-19 global health crisis forced border closings, strained resources and tightened funding, forcing humanitarian organisations to innovate. This paper aims to identify gaps in the literature on innovation in humanitarian supply chains, and to develop an appropriate framework for future research through a systematic literature review. We use a systematic literature review approach and synthesis the discussion of innovation in humanitarian supply chains after reviewing 43 papers. The synthesis identifies the different contexts for and outcomes of innovation in humanitarian supply chains. Our findings indicate that research on innovation in humanitarian supply chains is an underdeveloped topic. Gaps we identified in regards to the humanitarian context are: (1) a limited discussion of the contribution by the beneficiary to the supply chain; (2) a limited discussion of reconstruction innovations; (3) a lack of study on field application for complex innovations; (4) the lack of discussion of the role of individual knowledge in humanitarian supply chain innovation and finally (5) a lack of study of position innovations where humanitarian organisations use supply chains as a way to market effectively towards donors. [ABSTRACT FROM AUTHOR]

In this paper, we develop a two-level supply chain model with low carbon emissions for defective deteriorating items under learning in fuzzy environment by using the double inspection process. Carbon emissions are a major issue for the environment and human life when they come from many sources like different kinds of factories, firms, and industries. The burning of diesel and petrol during the supply of items through transportation is also responsible for carbon emissions. When any company, firm, or industry supplies their items through a supply chain by using of transportation in the regular mode, then a lot of carbon units are emitted from the burning of petrol and diesel, etc., which affects the supply chain. Carbon emissions can be controlled by using different kinds of policies issued by the government of a country, and lots of companies have implemented these policies to control carbon emissions. When a seller delivers a demanded lot size to the buyer, as per demand, and the lot size has some defective items, as per consideration, the demand rate is uncertain in nature. The buyer inspects the received whole lot and divides it into two categories of defective and no defective deteriorating items, as well as immediately selling at different price. The fuzzy concept nullifies the uncertain nature of the demand rate. This paper covers two models, assuming two conditions of quality screening under learning in fuzzy environment: (i) the buyer shows the quality screening and (ii) the quality inspection becomes the seller's responsibility. The carbon footprint from the transporting and warehousing the deteriorating items is also assumed. The aim of this study is to minimize the whole inventory cost for supply chains with respect to lot size and the number of orders per production cycle. Jointly optimizing the delivery lot size and number of orders per production cycle will minimize the whole fuzzy inventory cost for the supply chain and also reduce the carbon emissions. We take two numerical approaches with authentic data (from the literature reviews) for the justification of the proposed model 1 and model 2. Sensitivity observations, managerial insights, applications of these proposed models, and future scope are also included in this paper, which is more beneficial for firms, the industrial sector, and especially for online markets. The impact of the most effective parameters, like learning effect, fuzzy parameter, carbon emissions parameter, and inventory cost are shown in this study and had a positive effect on the total inventory cost for the supply chain. [ABSTRACT FROM AUTHOR]

The paper aims to conduct an analysis of pricing strategies in a dual channel supply chain under external uncertainty, utilizing Interval numbers theory and Game theory as the theoretical basis. The focus is on maximizing the expected profits of manufacturers and retailers. Four models are considered: centralized decision-making, manufacturer's Stackelberg, retailer's Stackelberg strategy, and vertical Nash model, with the decision variable being the product price. By solving the game model, the paper compares the optimal decisions under the four models and conducts sensitivity analysis to reflect the influence of key parameters and analyze their relationships. The ultimate goal is to optimize profits under various circumstances by adjusting market potential and price parameters to determine the best price level. The findings suggest that decision-maker's risk indicators have a greater impact on decision results when market demand is less sensitive to price, and that the size of the market has a negative correlation with the impact of decision-maker's risk indicators on decision results. [ABSTRACT FROM AUTHOR]

How do states' positions across multiple and interconnected economic networks affect their power? The Weaponized Interdependence (WI) scholarship emphasizes that states centrally located in global economic networks have access to new sources of coercion. In this paper, we look at how their positions across multiple networks interact with each other to create new opportunities and vulnerabilities. We use network analysis to map the semiconductor supply chain and show that it can be viewed as four interrelated networks: (1) design, (2) raw material, (3) manufacturing equipment, and (4) assembled chips. We then highlight how states' centrality varies across these networks and how it shapes their respective opportunities for coercion. Looking specifically at the United States, we emphasize how its centrality in the design network enables it to weaponize chokepoints in the trade network of assembled chips. In so doing the paper makes three contributions. First, it highlights how interactions among multiple economic networks provide new opportunities for states to weaponize interdependence. Second, it contributes to recent attempts using network analysis to analyze structural power on the global stage. Last, it demonstrates how network methodology can help detect potential (ab)uses of WI and how the potential for weaponization evolves over time. [ABSTRACT FROM AUTHOR]

Recently, the renewable energy supply chain has gained momentum as a vital component for clean energy, contributing to a sustainable future for the world. The development of the renewable energy supply chain is directly linked to circular economy targets and practices. This paper presents a systematic literature review of studies that analyze the roles, functions, and application objectives of the circular economy in the renewable energy supply chain. The aim of this review is to investigate key elements of renewable energy supply chains in the circular economy, shedding light on the state of research on the progress of sustainability in renewable energy supply chains, and guiding future research. Mainly, the systematic literature review demonstrates its findings by identifying and mapping the collated literature to reviews and applied studies that support and drive the renewable energy supply chain under the circular economy. This review paper is handled with a systematically descriptive, bibliometric, and content analysis hybrid approach, framed using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis methodology on the research topic. Findings show that circular economy applications have gained momentum in the renewable energy supply chain; nonetheless, some deficiencies persist. Redesign-based applications and design for recycling concepts encompass a significant gap in the renewable energy supply chain. Moreover, the current literature lacks outcomes on the applicability of circular economy 10R targets and the interrelationship and scalability of sustainable development goals in the renewable energy supply chain. [ABSTRACT FROM AUTHOR]

The recent passage of the Offshore Electricity Infrastructure Act (2021) (Cth) opened up the potential for Australia to produce renewable energy at unprecedented scale. Six regions have been identified as potential locations for developing offshore wind projects, promising thousands of new local jobs to legacy industrial regions. This paper charts the regulatory framework for Australia's offshore wind industry and how it positions local economic benefits in the licencing of projects. It then draws on interviews with key stakeholders supported by media and policy analysis to examine the early development of offshore wind capability in one of the proposed regions, the Illawarra, in NSW. Here existing steelmaking capacity positions the region to play a key role in supply chains for local and potentially national projects, but considerable structural and geographical constraints in the labour market will need to be addressed. In light of overseas experience indicating that economic benefits often fall short of promises, greater attention by policy makers is required to ensure hosting communities can develop local skills in the industry and facilitate their relative supply chain capabilities. This paper also calls for careful evaluation of early projects to allow for adjustments to policy settings as the industry matures domestically. [ABSTRACT FROM AUTHOR]

Thedistribution of products stands out as one of the pivotal activities for logistics companies in recent years, particularly in the aftermath of the COVID-19 pandemic and other geopolitical events. Intense competition compels companies to efficiently execute their logistical processes, with cross-docking emerging as a frequently applied solution. However, the location of cross-dock terminals in urban areas remains a problem insufficiently addressed in the literature, with a dearth of studies and models tackling this issue. This paper introduces a novel and innovative model for locating cross-dock terminals based on the CI-DEA–IDOCRIW–MABAC (Composite Indicators–Data Envelopment Analysis-Integrated Determination of Objective Criteria Weights–Multi-Attributive Border Approximation Area Comparison) methods. In the process of defining input indicators, the following three sources were utilized: relevant literature, practical insights from logistics experts, and the knowledge and experience of the authors. Eight inputs and three outputs were considered (the number of users in the observed channel; the area served by the channel; the average distance a vehicle travels in one delivery; the required number of vehicles; labor availability; competition; construction, and expansion possibilities; proximity to the main infrastructure and traffic facilities; the average number of deliveries; average delivered quantity; and service level). The model underwent testing in a case study analyzing nine distribution channels (areas within the observed urban zone). The results indicated that alternative A4 (in the southwest area) ranked the highest since it was the best-ranked in accordance with the most important criteria, suggesting that the terminal is best located in the southwest zone. The accuracy of the results was confirmed by company management. By developing a completely new model and addressing the identified gap in the literature, this paper provides unequivocal scientific contributions. [ABSTRACT FROM AUTHOR]

The paper aims to provide a theoretical basis for the application of revenue-sharing contract under bounded rationality and capital constraints. We consider an uncooperative ordering model in a supplier-Stackelberg game and coordination strategy with revenue-sharing contract for a loss-averse and capital-constrained retailer. We drive the existence and uniqueness conditions of the optimal solutions under bank financing and revenue-sharing contract. We also develop a series of propositions and corollaries to determine the optimal solutions and offer some managerial insights. The key contribution of the paper is to deepen and expand the revenue-sharing contract under the risk-neutral assumption, and to provide a theoretical basis for the application of revenue-sharing contract under bounded rationality and capital constraints. We find that the revenue-sharing ratio of loss-averse and capital-constrained retailer is larger than that of neutral retailer and the expected utility of loss-averse and capital-constrained retailer is larger than that of neutral retailer under coordination strategy with revenue-sharing contract. [ABSTRACT FROM AUTHOR]

This paper aims to understand the impact of big data analytics on the retail supply chain. For doing so, we set our context to select the best big data practices amongst the available alternatives based on retail supply chain performance. We have applied TODIM (an acronym in Portuguese for Interactive Multi-criteria Decision Making) for the selection of the best big data analytics tools among the identified nine practices (data science, neural networks, enterprise resource planning, cloud computing, machine learning, data mining, RFID, Blockchain and IoT and Business intelligence) based on seven supply chain performance criteria (supplier integration, customer integration, cost, capacity utilization, flexibility, demand management, and time and value). One of the intriguing understandings from this paper is that most of the retail firms are in a dilemma between customer loyalty and cost while implementing the big data practices in their organization. This study analyses the dominance of the big data practices at the retail supply chain level. This helps the newly emerging retail firms in evaluating the best big data practice based on the importance and dominance of supply chain performance measures. [ABSTRACT FROM AUTHOR]

The application of blockchain has become a trend in the development of supply chain finance. Aiming to bridge the gap in the existing literature, this paper investigates a supply chain finance system based on blockchain technology which contains a manufacturer, a retailer and a financial institution and incorporates blockchain costs into the model. Firstly, this paper establishes a supply chain finance model based on blockchain technology and it presents a comparison with the process employed under the traditional model. Secondly, this paper establishes the revenue mathematical model of supply chain finance based on blockchain technology. Thirdly, the optimal decisions of each participant under centralized and decentralized decision-making are proved and obtained, respectively, and the influencing factors of the optimal decisions are analyzed. Finally, the conclusions are verified via simulations. This study finds that, when blockchain is used, the benefits of each participant in the chain are increased. In addition, centralized decision-making, which is more optimal in the traditional model, is also enhanced under blockchain. This paper demonstrates the superiority of blockchain-enabled supply chain finance in terms of model and revenue. This provides some suggestions for companies in the supply chain with regard to solving the problem of financing difficulties. [ABSTRACT FROM AUTHOR]

• Offering a novel fuzzy robust approach for closed-loop supply chain network design. • Examining the hybrid uncertainties and flexibility of constraints in the problem. • Considering economic, responsibility, and environmental subjects in modeling. • Using the interactive fuzzy programming approach to solve the multi-objective model. • Introducing a new application for stone paper closed-loop supply chain network design. Nowadays, the production of stone paper, in addition to its widespread utilization in various fields, does not require water consumption, cutting down trees, and stone paper products are easily recyclable and recoverable. Due to the importance of developing and using stone paper and paying attention to environmental matters, Closed-Loop Supply Chain Network Design (CLSCND) is very important for stone paper products. Moreover, due to epistemic, randomness uncertainties, the uncertainties in Objective Function (OF), and the flexible constraints for CLSCND in the real world, this paper introduces a novel Mixed Robust Stochastic, Possibilistic, and Flexible Programming (MRSPFP) approach based on credibility theory. The different attitudes of the Decision-Makers (DMs) are addressed by a more flexible measurement of the optimistic and pessimistic parameters using the criterion of credibility. In the study, a comprehensive procedure is proposed for stone paper CLSCND, to minimize costs, increase responsiveness by minimizing transit time between different facilities, and regarding environmental concerns into account through minimizing carbon emissions. The model is solved utilizing an interactive fuzzy programming solution procedure and the Best-Worst Method (BWM). The results of sensitivity analysis, the effect of changing the problem parameters, and the performance of the proposed model are investigated and compared. The results show that the MRSPFP model has a better performance compared to other previous models. The MRSPFP model performs better in strategic decisions that require high investment costs due to the minimization of the absolute deviation of OF from its mean. Also, the applied results of the study show that CLSCND has a good capability and potential for sustainable development in the field of stone paper. [ABSTRACT FROM AUTHOR]

The demand for fresh food has become a frequent high demand commodity in everyday living and accounts for a larger share of the retail consumer market. As the quality of fresh foods deteriorates from harvest to consumption due to internal or external factors, it is important to label or mark fresh products or their package directly on the surface or on the top. In recent years, there has been a growing demand for labels to monitor the quality of various fresh food products. Sellers and consumers can easily determine whether a product is edible by observing visual changes in the detection label without opening the package for visual or olfactory inspection. This review summarizes the latest research findings on advances in fresh food quality deterioration and the application of suitable detection labels in the supply chain. It highlights diverse detection labels, modification of label functionality, and several latest shelf-life prediction systems. Finally, recommendations and prospects for future research in the development of fresh detection labels are provided. This paper allows relevant researchers to quickly obtain information on food quality inspection labels and their problems to be solved. [ABSTRACT FROM AUTHOR]

This paper studies the infrastructural and organisational forms that facilitate labour exploitation within maritime logistics. My entry point is the rising wave of seafarer abandonments, which I approach not as isolated incidents of mismanagement but as an intensification of the flexibilising tendencies underpinning contemporary capitalism. I trace the recent history of these dynamics, examining their effect on shipping labour. I then investigate some of the specific legal and economic mechanics of shipping, focusing on debt, insurance, and bordering. Using supply chain mapping software, I study supply systems in a way that centres labour rather than the commodities being moved. I close by claiming that abandonments are not an accident, but an inevitable endpoint of a system designed to precaritise labour while protecting shipowners' profits. Against this, I sketch out a new way of conceiving of supply chains—as supply nets, matrices of interconnected lines, prone to becoming tangled. [ABSTRACT FROM AUTHOR]

The first part of the current study highlights the importance of developing a clean hydrogen supply chain (CHSC) in Iran to enhance energy security and contribute to global efforts towards sustainable energy transition. Depending on whether the focus is on domestic consumption or export of hydrogen, the study provides valuable insights into the prioritization of CHSC development pathways via multi-criteria decision-making tools (AHP, AHOP-TOPSIS, and AHP-VIKOR). The results show that for domestic hydrogen consumption (internal scenario), the best path of the supply chain includes blue hydrogen from steam methane reforming coupled with carbon capture and storage, H 2 -carriers (ammonia and methanol), natural gas grid for transportation and distribution, and industry sector as the end user. In the external scenario, however, the best path of the CHSC consists of green hydrogen production based on solar energy, and the other parts of the path include liquid hydrogen as the storage method, ship as the distribution and transportation, and industrial sector as the end user. By identifying the most suitable methods and technologies for each stage of the supply chain, this paper offers a comprehensive analysis that can guide decision-making in CHSC development. [ABSTRACT FROM AUTHOR]

This paper studies supply chain pricing and production/ordering decisions under carbon tax policy and retailer's stochastic demand. Firstly, a supply chain model with random demand obeying normal distribution is established. Based on this, a stochastic optimization problem with the goal of maximizing expected social welfare is constructed. The multi-agent consensus is used to solve the optimization problem, and the pricing and production/ordering decisions with random demand obeying normal distribution are obtained. Finally, the theoretical results are verified by numerical simulation, and the influence and effectiveness of multi-agent consensus theory on supply chain decision-making are demonstrated in the presence of random demand and sudden failure of an enterprise in the supply chain and further analyze the impact of carbon tax policy on supply chain decision-making. [ABSTRACT FROM AUTHOR]

With the development of low-carbon economy and the dominant position of retailers, through the establishment and comparison of three cooperative advertising models: model of supplier's independent advertising, model of supplier's independent advertising and model of retailer's and supplier's cooperative advertising, this paper studies the cooperative advertising decision-making of fresh agricultural products supply chain with two channels, and the demand of both channels is affected by the level of advertising investment, the proportion of advertising cost sharing and the efficiency of carbon emission reduction. The results show that when supplier and retailer adopt the two-way cooperative advertising mode, the demand and profit level of the two channels reach the optimal level. Numerical analysis shows that carbon emission reduction efficiency has an important impact on profits and market demand, which is closely related to cooperative advertising strategy. [ABSTRACT FROM AUTHOR]

Addressing the complexities of transitioning to a sustainable bioeconomy, this paper presents a novel approach for developing regional transformation pathways (RTPs) based on narratives derived from the shared socioeconomic pathways. The methodology emphasizes a comprehensive understanding of underlying perspectives and perceptions, incorporating socio‐economic, environmental, and political dimensions. The developed indicator framework captures a balanced representation of diverse interests by integrating insights from stakeholder analyses. The case study in the Rheinisches Revier region, Germany, exemplifies the approach's applicability, providing valuable insights for decision‐making processes in the context of regional transitions toward a low‐carbon economy. The results consist of five developed RTPs, offering a multitude of potential future trajectories of possible directions for regional transformations. Understanding potential pathways and related consequences is crucial for informed decision‐making concerning resource use optimization since transformations of that scale influence the composition of supply chains and resource networks. This informed approach contributes to strategic planning and helps ensure resources are utilized efficiently and sustainably. By emphasizing the crucial role of transparency and reflection of assumptions in addressing the complexities of societal transformation processes, our approach seeks to support the implementation of a sustainable and inclusive bioeconomy at the regional level. [ABSTRACT FROM AUTHOR]

Blockchain is a modern-age technology which records digital transactions in a consistent, safe, and verifiable form to solve the problems from different sectors. In the supply chain, this technology is applied to improve traceability, ownership, and trust. Moreover, it can solve the issue pertaining to counterfeits in the supply chain. However, blockchain-based supply chains have certain disadvantages, such as privacy of the information shared between the members of the supply chain. In this paper, a new mechanism has been proposed to ensure the privacy of such information by taking traceability and ownership into account. The novelty of the proposed system is its ability to achieve privacy with the inclusion of traceability and ownership. To implement privacy, we employed a combination of symmetric and asymmetric key encryption. With the proposed system, owner of the product can trace said product and the one who owns the product can transfer the ownership. The proposed system restricts the entry of counterfeit products in the supply chain. The Hyperledger Sawtooth blockchain has been used for the experimental purpose. The subsequent analysis show that the proposed system can provide privacy without disturbing factors concerning traceability and ownership. The results show that the inclusion of privacy does not impact performance significantly. [ABSTRACT FROM AUTHOR]

Nowadays, supply chain (SC) decentralised decision making is the most usual situation in SC operations planning. In this context, different companies can collaboratively plan to achieve a certain level of individual and SC performance. However in many cases, there is reluctance to collaborate because it is not known a priori which benefits will be reported. This paper aims to develop a mathematical programming-based methodology for the evaluation of different supply chain collaborative planning scenarios (MPM-SC-CP). It is assumed that different SC decision centres (DCs) make decisions based on mixed and integer linear programming models. Two main inputs feed the proposed MPM-SC-CP, a framework and associated methodology that support the integrated conceptual and analytical modeling of the SC-CP process in which several DCs make decisions according to spatio-temporal integration. Finally, an application to a real ceramic SC was conducted. [ABSTRACT FROM AUTHOR]

Dynamic pricing is a crucial revenue management technique when product status changes over time. It can become more prominent if applied in conjunction with an inventory management strategy for deteriorating items. This paper presents a framework for dynamic pricing in a continuous time horizon for a dual-channel supply chain consisting of a manufacturer and a retailer. The manufacturer produces a deteriorating product and sells through direct and indirect retail channels, and both channels compete with each other over retail prices. The freshness of the product varies with time, and thus both channels invest in preservation technology, which further leads to carbon emissions. We derive an analytical solution to the dual-channel pricing model. Furthermore, the case of single-channel pricing has been investigated to study and compare its pricing strategy with the dual-channel pricing strategy. Lastly, a numerical illustration is presented to study the impact of key parameters on optimal decisions through sensitivity analysis. We provide managerial recommendations in various scenarios like an increase in competition, the shift of consumer preference between channels and fluctuation in demand. [ABSTRACT FROM AUTHOR]

One of the United Nations' 17 Sustainable Development Goals is to "Ensure access to affordable, sustainable, and clean energy for all." Additionally, the growing concerns about climate change and energy security have heightened the importance of exploring alternative energy sources to replace fossil fuels. The utilisation of agricultural waste for bioenergy production has acquired significant attention due to its potential to mitigate environmental impacts and provide renewable energy sources. However, the major obstacle to producing bioenergy is managing the supply chain while considering economic, environmental, and social factors in an optimal way. This paper presents a comprehensive overview of the literature on the management of agriculture waste supply chains, specifically related to the use of modelling and optimisation techniques for planning. The first section describes different stages of the supply chain and various technologies for converting biomass to bioenergy. This is followed by a synopsis of the literature reviewed based on decision levels, objective functions, modelling methodologies, and optimisation approaches. Finally, the review highlights limitations and gaps in current research and the areas with potential for further exploration. [ABSTRACT FROM AUTHOR]

In this paper, we study unimodality conditions for distributions that describe markets with stochastic demand. Such conditions naturally emerge in the analysis of game-theoretic models of market competition (Cournot games) and supply chain coordination (Stackelberg games). We express the price elasticity of expected demand in terms of the mean residual life (MRL) function of the demand distribution and characterize optimal prices or equivalently, points of unitary elasticity, as fixed points of the MRL function. This leads to economic interpretable conditions on the demand distribution under which such fixed points exist and are unique. We find that markets with increasing price elasticity of expected demand that eventually become elastic correspond to distributions with decreasing generalized mean residual life (DGMRL) and finite second moment. DGMRL distributions strictly generalize the widely used increasing generalized failure rate (IGFR) distributions. We further elaborate on the relationship of the two classes, link their limiting behavior at infinity and examine moment and closure properties of DGMRL distributions that are important in economic applications. The DGMRL unimodality condition is useful in the analysis of optimal decisions under uncertainty in settings that are not covered by the widely-used IGFR condition; thus, it can be of broader interest to the game-theory and operations research literature. [ABSTRACT FROM AUTHOR]

The present paper deals with an integrated sustainable supply chain model with the effect of learning for an imperfect production system under a cloudy fuzzy environment where the demand rate is treated as a cloudy triangular fuzzy (imprecise) number, which means that the demand rate of the items is not constant, and shortages and a warranty policy are allowed. The vendor governs the manufacturing process to serve the demand of the buyer. When the vendor supplies the demanded lot after the production of items, it is also considered that the delivery lots have some defective items that follow an S-shape learning curve. After receiving the lot, the buyer inspects the whole lot, and the buyer classifies the whole lot into two categories: one is the defective-quality items and the other is the imperfect-quality items. The buyer returns the defective-quality items to the seller after a screening process, for which a warranty cost is included. During the transportation of the items, a lot of carbon units are emitted from the transportation, damaging the quality of the environment. The seller includes carbon emission costs to achieve sustainability as per considerations. A one-time discrete investment is also included for the minimizing of the setup cost of the seller for the next cycles. We developed models for the scenario of the separate decision and for the integrated decision of the players (seller/buyer) under the model's consideration. Our aim is to jointly optimize the integrated total fuzzy cost under a cloudy fuzzy environment sustained by the seller and buyer. Numerical examples, sensitivity, analysis limitations, future scope and conclusions have been provided for the justification of the proposed model, and the impact of the input parameters on the decision variables and integrated total fuzzy cost for the supply chain are provided for the validity and robustness of this proposed model. The effect of learning in a cloudy fuzzy environment was positive for this proposed model. [ABSTRACT FROM AUTHOR]

The escalating severity of global warming has drawn worldwide attention to ecological problems. Nevertheless, with the introduction of environmental policies, biomass resources have been effectively developed as a renewable energy source. This paper investigates an advanced biomass supply chain design wherein biomass resources are initially converted into bio-oil through widely distributed fast pyrolysis facilities, and are subsequently transported to a centralised biorefinery for further refining into biofuels. This novel biomass supply chain addressed three key issues: (1) The number of fast pyrolysis facilities, (2) The allocation of resources, and (3) The routes of resources transport. In respect of these problems, a two-stage stochastic mixed integer programming model is established to minimise the total cost of the biomass supply chain considering the uncertainty collection price of fast pyrolysis facilities. A hybrid simulated annealing algorithm which incorporates the sample average approximation method is proposed to solve the stochastic model and is effectiveness for large-scale examples. Finally, a sensitivity analysis is performed using the proposed algorithm and the results show that the proposed stochastic model outperforms the deterministic model under uncertain collection price. The model allows optimising the biomass supply chain economic performances and minimise financial risk on investment by determining the fast pyrolysis facility locations, reasonable resource allocation and optimal transport routes under uncertain collection price. • The collection price uncertainty impact is considered on biomass supply chain. • A combined biomass supply chain design is suggested. • Facility location, resource allocation and vehicle routing problem are considered. • A two-stage stochastic mixed integer programming model is established. • A hybrid simulated annealing algorithm is developed. [ABSTRACT FROM AUTHOR]