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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]

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]

The literature review shows research gaps into the food supply chain design. In that context, this paper deals with the design of a sustainable supply chain. A multi-objective mixed-integer linear programming model includes four decisions and three sustainable criteria (economic—total network costs—, environmental—carbon emissions—, and social—work conditions and societal development—). The model aims to determine the optimal location and capacity of processing and distribution facilities, to choose the suppliers from a set of potential candidates, to determine transportation modes between all the actors, and to define the quantity of product, in order to satisfy the demand of dairy products in a set of regions. The applicability of the model is tested in a realistic case in the dairy sector in the central region of Colombia. The results show the existent trade-offs between the three dimensions of sustainability. The unweighted balance results, giving more priority to the social dimension, which obtains the least deviation, affecting the environmental performance of the chain. The analysis carried out in this paper does help decision-makers that will have at hand a set of possible configurations to be chosen in order to comply with environmental and social regulations without neglecting economic performance. [ABSTRACT FROM AUTHOR]

This paper studies the green new product development (GNPD) problem of a risk-averse capital constrained supply chain (SC). The SC is managed by an SME entrepreneur, seeking financial support from a multi-sided FinTech platform (MSP) to develop a portfolio of green and non-green products. The MSP offers the SC a combination of equity financing (EF) and debt financing (DF) facilities and must decide on the interest rate of its DF facility. Using a benchmark model, we first characterize the SC's production and the MSP's financing decisions under a deregulated scenario. Focusing on an alternative case with government intervention (i.e., hybrid environmental-green entrepreneurship policy), we next develop a three-level game theoretical model and sequentially characterize the decision-making behavior of government, MSP, and SC. The model outcomes are analyzed by considering the policy approach (i.e., economic influence vs. social welfare) and the platform's risk attitude. The results reveal that, when coupled with an appropriate government intervention policy, a regulated scenario leads to a better outcome, particularly when the MSP is risk-neutral and strikes a right balance between the EF and DF. The win–win situation may not be realized when the MSP is risk-averse and the host government is merely focused on its economic influence. To successfully promote sustainable supply chain finance (SSCF) through digital platforms, policy makers are urged to leverage their legislative power and prioritize green entrepreneurship and social welfare over their financial maximization agenda. [ABSTRACT FROM AUTHOR]

Today, supply chain finance is a very important topic. Traditional supply chains rely on banks to support the related financing activities and services. With the emergence of blockchain technology, more and more companies in different industries have considered using it to support supply chain finance. In this paper, we study supply chain financing problems in supply chains selling fashionable products. Modeling under the standard newsvendor problem setting with a single manufacturer and a single retailer employing a revenue sharing contract, we develop analytical models for both the traditional and blockchain-supported supply chains. We derive the optimal contracting and quantity decisions in each supply chain with Nash bargaining between the manufacturer and retailer. We analytically show how the revenue sharing contract can coordinate both types of supply chains. We then compare the optimal systems performances between the two supply chains. We prove that the blockchain-supported supply chain incurs a lower level of operational risk than the traditional supply chain. We have shown that if the service fees by banks are sufficiently high, adopting blockchain technology is a mean-risk dominating policy which brings a higher expected profit and a lower risk for the supply chain and its members. For robustness checking, we examine other commonly seen supply chain contracts and alternative risk measures, and analytically reveal that the results remain valid. [ABSTRACT FROM AUTHOR]

Alongside many research studies that have been presented in the open innovation domain and smart manufacturing systems, there is a research gap on integrating the outbound individual capabilities with the new smart manufacturing machines to satisfy the customers' varied and uncertain requirements. In this paper, Open Supply Chain Management (OSCM) is conceptualized as a new paradigm in the evolution of SCM. Companies can benefit from integrated physical and conceptual resources to promote efficiency and flexibility throughout the supply chain's main processes, including supplying, manufacturing, distributing, and marketing. The OSCM concept is undergoing several drivers including crowdsourcing, open innovation, Industry 4.0, cloud manufacturing, Internet of Things (IoT), big data, and the digital twin that appeared in the last decades. To validate OSCM in practice, a subset of this concept is investigated to incorporate the designing process with supply chain production planning applying a digital twin network. Additionally, dealing with epistemic uncertainty, a fuzzy tactical planning model is developed, and to study the developed model in more detail, an industrial study in the clothes manufacturing industry is employed. The results illustrate that the products' designing cost consists of only 2% of the supply chain total cost. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) and Big Data Analytics (BDA) have the potential to significantly improve resilience of supply chains and to facilitate more effective management of supply chain resources. Despite such potential benefits and the increase in popularity of AI and BDA in the context of supply chains, research to date is dispersed into research streams that is largely based on the publication outlet. We curate and synthesise this dispersed knowledge by conducting a systematic literature review of AI and BDA research in supply chain resilience that have been published in the Chartered Association of Business School (CABS) ranked journals between 2011 and 2021. The search strategy resulted in 522 studies, of which 23 were identified as primary papers relevant to this research. The findings advance knowledge by (i) assessing the current state of AI and BDA in supply chain literature, (ii) identifying the phases of supply chain resilience (readiness, response, recovery, adaptability) that AI and BDA have been reported to improve, and (iii) synthesising the reported benefits of AI and BDA in the context of supply chain resilience. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the impact of blockchain application on trust levels in supply chains. Through the systematic review of the relevant literature, three dimensions of trust, i.e., the trustor–trustee perspective, forms of trust, and time orientation, are investigated. Our findings show that, first, there are three pairs of trustors and trustees involved in blockchain implementation: (a) the user and the blockchain, (b) two supply chain partners, and (c) the consumer/public and a supply chain unit. Second, the two forms of trust, namely cognition-based and institution-based trust, are likely to be enhanced by blockchain execution, while affect-based trust may not be directly impacted by the technology. Third, the presence of blockchain technology would facilitate swift trust-building between unknown supply chain partners under specific circumstances. Moreover, we also find contradicting assertions among scholars on the implications of blockchain for trust in supply chains. While some studies pointed out that blockchain will enable a trustless trusted scheme, others expected the reinforcement of interorganizational trust. To test these assertions, we develop the blockchain-entrusted supply chain models to present the three-step process of how trust is developed through the blockchain and diffused to supply chain partners and external stakeholders. [ABSTRACT FROM AUTHOR]

Tools established for managing information flow in supply chain management and logistics should match digital transformations. This issue is particularly salient for developing nations that hope to achieve sustainable development goals in a globalized era. Modern technologies are required to ensure a secure, transparent, and traceable path of information flow in global supply chains; however, it is not always straightforward for businesses in developing economies to adopt new digital technologies while sustaining productivity. One of the foundational technologies that can be used to create a basis for economic and social systems and to affect manufacturing supply chains in developing economies is blockchain. In this study, we analyze the barriers to blockchain technology adoption in manufacturing supply chains using the neutrosophic analytic hierarchy process (N-AHP). We propose an action plan framework for the validation of blockchain technology in a developing economy. The findings demonstrate that "transaction-level uncertainties" comprise the most critical barrier and have the highest weight in the final ranking followed by "usage in the underground economy", "managerial commitment", "challenges in scalability", and "privacy risks". This paper can assist industrial managers and experts in emerging economies to more clearly identify barriers to the implementation of blockchain technology and show them how to successfully employ blockchain technology in their supply chains. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to explore the enablers for the implementation of electronic traceability in agri-food supply chain in India. In several agri-food supply chains, the lack of any form of traceability or the presence of paper-based traceability impacts the trade of the concerned food product. Electronic traceability (e-traceability) will assist agri-food firms in improving their performance, minimize food fraud activities, ensure efficient recall of the products and contribute in overall agri-food supply chain management. With the help of literature review and expert opinions, enablers of e-traceability are modelled and analyzed using Fuzzy ISM and FUZZY MICMAC. The combination of both these techniques helps in identifying the essential drivers in the implementation of e-traceability in agri-food supply chains. The proposed approach found that that electronic form of traceability is better than paper-based traceability in agri-food supply chains. The significant drivers in e-traceability implementation, particularly in agri-food supply chain are appropriate technology for e-traceability, competitive advantage, coordination and transparency and management support. The identified enablers would guide the managers or decision-makers in the adoption of e-traceability in their existing supply chains in the agri-food sector. [ABSTRACT FROM AUTHOR]

Global warming, climate change, and social problems are the worst human-induced sustainability issues that economies across the globe have witnessed. Water pollution, greenhouse effect, poor working conditions, child labour and lack of coordination among channel partners have caused the considerable interruptions in the supply chain network. The purpose of the paper is to identify critical factors affecting behavioural and sustainable supply chain coordination and evaluate strategies for risk reduction in the supply chain coordination in the context of digitization. This study purposes a novel supply chain coordination framework which consists of four themes such as system, actor, objective and action on which the success or the failure of supply chain can be contingent. Our study integrates multi-criteria decision approach using Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) and Fuzzy Decision-Making Trial and Evaluation Laboratory (Fuzzy-DEMATEL) to investigate factors that affected the behavioural and sustainable supply chain coordination in the context of digitization. The Fuzzy-AHP method qualified to hierarchically rank the factors based on the relative fuzzy weightage while Fuzzy-DEMATEL established the inter-relationships among the factors and classified them into cause and effect groups. The findings of our study identified the Environmental performance and decarbonization as the most significant factor and the speed to market as the least important factor in developing behavioural and sustainable supply chain coordination in the context of digitization. Our analysis from Fuzzy AHP-DEMATEL approach reveal that the social preferences (power balance, reciprocity, fairness) is a significant causal factor which can effectively abolish the issues plaguing behavioural and sustainable supply chain coordination in the context of digitization. The results from our study aim to facilitate decision makers in cultivating a sustainable supply chain framework that can boost trust among the channel partners environmental performance, social performance and channel efficiency of the supply chain, thereby ensuring sustainability and socio welfare of all the supply chain. [ABSTRACT FROM AUTHOR]

This study proposes a mixed-integer multi-objective integrated mathematical model solving facility location and order allocation optimisation problems simultaneously in a two-echelon supply chain network. The proposed problem is motivated by a factoryless concept and by providing a dynamic decision-making solution under a multi-period time horizon. Within the model, we also determine the optimal replenishment number of production facilities by the multi-objective functions. The multi-objective functions include minimisation of the total cost, rejected and late delivery units and, maximisation of the assessment score of the selected suppliers. The studied dynamic decision model is significant for the cost-efficient management of companies' supply chain networks. The mixed-integer mathematical model is developed by the LP-metric method and it is solved by the GAMS optimisation software. Due to the NP-hard structure of the problem, for large-scale instances, we utilise the Multi-Objective Particle Swarm Optimisation (MOPSO) and Multi-Objective Vibration Damping Optimisation (MOVDO) heuristic solution approaches. Numerical results show that, for large-scale problems, the MOPSO method performs better in Pareto solutions and decreases run times. However, the MOVDO method performs better regarding the Mean Ideal Distance and the Number of Solutions Cover surface criterion. The developed solution approach by this paper is a generic model which can be applied for any two-level network for simultaneous optimisation of supplier selection, location determination of facilities and their replenishment amounts. [ABSTRACT FROM AUTHOR]

The year 2020 can be earmarked as the year of global supply chain disruption owing to the outbreak of the coronavirus (COVID-19). It is however not only because of the pandemic that supply chain risk assessment (SCRA) has become more critical today than it has ever been. With the number of supply chain risks having increased significantly over the last decade, particularly during the last 5 years, there has been a flurry of literature on supply chain risk management (SCRM), illustrating the need for further classification so as to guide researchers to the most promising avenues and opportunities. We therefore conduct a bibliometric and network analysis of SCRA publications to identify research areas and underlying themes, leading to the identification of three major research clusters for which we provide interpretation and guidance for future work. In doing so we focus in particular on the variety of parameters, analytical approaches, and characteristics of multi-criteria decision-making techniques for assessing supply chain risks. This offers an invaluable synthesis of the SCRA literature, providing recommendations for future research opportunities. As such, this paper is a formidable starting point for operations researchers delving into this domain, which is expected to increase significantly also due to the current pandemic. [ABSTRACT FROM AUTHOR]

The emerging information and communication technologies (ICT) related to Industry 4.0 play a critical role to enhance supply chain performance. Employing the smart technologies has led to so-called smart supply chains. Understanding how Industry 4.0 and related ICT affect smart supply chains and how smart supply chains evolve with the support of the advanced technologies are vital to practical and academic communities. Existing review works on smart supply chains with ICT mainly rely on the academic literature alone. This paper presents an integrated approach to explore the effects of Industry 4.0 and related ICT on smart supply chains, by combining introduction of the current national strategies in North America, the research status analysis on ICT assisted supply chains from the major North American national research councils, and a systematic literature review of the subject. Besides, we introduce a smart supply chain hierarchical framework with multi-level intelligence. Furthermore, the challenges faced by supply chains under Industry 4.0 and future research directions are discussed as well. [ABSTRACT FROM AUTHOR]

This paper investigates the implication of three channel power structures (i.e., manufacturer-led, vertical Nash and retailer-led) on supply chain management in a setting where a manufacturer determines whether to introduce a direct sales channel and a retailer has two capital status (i.e., capital-constrained status or capital-sufficient status). The capital-constrained retailer faces the decision of financing by trade credit or bank credit. We find that compared to cooperating with a capital-sufficient retailer, cooperating with a capital-constrained retailer will make the manufacturer bear a higher encroachment cost. Surprisingly, the capital-constrained retailer choosing trade credit financing may deter the manufacturer's encroachment behavior, which means that trade credit financing has a positive financing effect with manufacturer encroachment. However, bank credit financing always makes the retailer worse off after encroachment, and the positive trade credit financing effect achieves the most efficient performance under manufacturer-led structure, yet remarkably impoverished under retailer-led structure. In addition, although conventional wisdom suggests that the manufacturer will lower the wholesale price to boost retail channel's demand with encroachment, we obtain a different conclusion by demonstrating that manufacturer encroachment has a negative wholesale price effect that the manufacturer will raise the wholesale price after encroachment to ensure that direct sales channel enjoys a price advantage in a Bertrand competition market. Interestingly, we find that retailer-led is the most conducive structure to manufacturer's encroachment, and manufacturer-led is the most unfavorable structure for manufacturer's entry except when the manufacturer cooperates the capital-sufficient retailer in a high-risk market. Furthermore, with the increase of channel competition/market risk/production cost, the manufacturer has less motivation to enter the market. [ABSTRACT FROM AUTHOR]

Humanitarian operations are increasingly receiving attention due to the numerous recent disasters and crises caused by both natural and man-made events, from mass human exodus to pandemics such as COVID-19. The successful management of humanitarian supply chains requires the effective use of human resource practices, which in turn requires strong leadership in the so-called 'soft side' of management. This study aims to investigate the current status of research on the human aspects of humanitarian supply chains. Through a systematic and comprehensive literature review, encompassing an original codification and in-depth analysis of journal articles, this work provides a research agenda and a number of lessons concerning human resource management (HRM) in humanitarian operations. The main findings reveal that: (i) HRM impacts the ability of humanitarian organizations to adequately prevent, prepare for and respond to disasters; (ii) training programs for aid personnel are a vital aspect of humanitarian responsiveness; (iii) humanitarian operations require a workforce with a variety of soft and hard skills; (iv) lack of trained staff is one of the main challenges in this field; and (v) building relationships and strengthening networks can enlarge the human resource pool available. Therefore, the findings of this study and its proposed research agenda have implications for both theory and practice. In terms of theory, this work provides seven recommendations, representing opportunities for scholars to advance this body of knowledge. For humanitarian practitioners, this paper offers insightful lessons to guide them in the management of human resources in humanitarian operations. [ABSTRACT FROM AUTHOR]

In this study we argue that recognising humanitarian logistics (HL) as a complex system is a key step in developing supply chain design and management strategies that meet the needs of stakeholders. This study draws on complex adaptive systems theory to examine the characteristics and implications of complexity for HL. Through case-study research of humanitarian responses in Haiti and Pakistan, characteristics of complexity across organisational boundaries are identified. We find that the complexity of the context impacts the outcome of the humanitarian response and conclude that HL must not only react to its environment, it must also create its environment. As HL must work within significantly differing environments to create solutions, the standardised approaches used to manage supply chains are less desirable. While this paper focuses on HL, wider applicability to other complex logistics operations is also discussed, informing the design and management of contextually specific supply chains. [ABSTRACT FROM AUTHOR]

This paper proposes a design redundancy framework for countering the risks inherent in humanitarian supply chains (SCs), particularly those operating in conflict zones. This framework deals with humanitarian SC design and risk management, drawing from literature on agility and resilience. The humanitarian SC operation directed by the logistics cluster in Yemen is analyzed using system dynamics simulation and network optimization. Real data is used as input to the models to create and five alternative SC designs which can be implemented depending on the current risks to the humanitarian SC. This constitutes the new concept of design redundancy, whereby humanitarian SC managers can analyse multiple alternative SC designs for humanitarian operations. Each design is fitted to a potential risk scenario which is likely to occur during that crisis. The approach developed empowers the decision-makers to ensure the continued flow of aid to beneficiaries despite disruption providing decision-making support for humanitarian SC managers and communication with donors. [ABSTRACT FROM AUTHOR]

As a significant component of supply chain management, multi-channel pricing decision has received extensive attention in recent years. Many studies have focused on single-channel pricing decision, while limited research has been done on multi-channel pricing decision with a revenue-sharing contract. This paper establishes a multi-channel optimal pricing decision model with a revenue-sharing contract (entailing a revenue apportionment and an additional reward) in the context of a cross-channel effect, consumers trust utility, and after-sales service utility, all of which play roles in increasing or reducing supply chain members' expected profits. The results indicate that, in a bid to obtain maximum profit, manufacturer and reseller will take different measures for varying levels of differences between cross-channel effects of direct seller (D-seller) and reseller (R-seller), for different levels of consumer trust utility, and for different levels of after-sales service utility. Manufacturer and reseller both try their best to decrease the impact of sales format differences on electronic channel when the differences are small, but the action is opposite when the differences are large. In addition, manufacturer should not blindly improve the additional trust of direct-sale stores relative to reseller, but instead should increase additional reward to R-seller when manufacturer decides to improve the after-sales service of products through D-seller. [ABSTRACT FROM AUTHOR]

Research on the development of sustainable supply chain models is highly active nowadays. Merging the concept of supply chain management with sustainable development goals, leads to simultaneous consideration of all economic, environmental and social factors. This paper addresses the design of a sustainable closed-loop supply chain including suppliers, manufacturers, distribution centers, customer zones, and disposal centers considering the consumption of energy. In addition, the distribution centers play the roles of warehouse and collection centers. The problem involves three choices of remanufacturing, recycling, and disposing the returned items. The objectives are including the total profit, energy consumption and the number of created job opportunities. As far as we know, these objectives are rarely considered in a sustainable closed-loop supply chain model. The proposed model also responds to the customer demand and also addresses the real-life constraints for location, allocation and inventory decisions in a closed-loop supply chain framework. Another novelty of this research is to develop a set of efficient Lagrangian relaxation reformulations and fast heuristics for solving a real-world numerical example. The results have revealed that the obtained solution is feasible and the developed solution algorithm is highly efficient for solving supply chain models. Finally, a comprehensive discussion is provided to highlight our findings and managerial insights from our results. [ABSTRACT FROM AUTHOR]

The aim of this paper is to solve a multi-period supplier selection and inventory lot-sizing problem with multiple products in a serial supply chain. Compared to previous models proposed in the literature, our research incorporates a richer cost structure involving joint replenishment costs for raw material replenishment and production, and a more realistic description of the transportation costs represented as a vector of full-truck load costs for different size trucks. This problem can be displayed graphically as a time-expanded transshipment network defined by nodes and arcs that can be reached by feasible material flows. First, we propose an integrated mixed integer linear programming model that minimizes the cost over the entire supply chain for a given planning horizon. The model determines the optimal dynamic supplier selection, inventory lot-sizing, and production schedule simultaneously. Second, a sequential approach is proposed to solve the same problem. That is, a production schedule is determined first, and then a supplier selection and replenishment strategy is obtained according to that predetermined schedule. Sensitivity analysis comparing the two approaches is performed. Results show that, even though the integrated approach achieves the minimum cost, the sequential approach may be suitable for solving large-scale instances of the problem as it requires less information sharing and generates a near-optimal solution with shorter implementation time and computational effort. [ABSTRACT FROM AUTHOR]

This paper addresses a supply chain situation, in which a company distributes commodities over a selected subset of customers while a manufacturer produces the commodities demanded by the customers. The distributor company has two objectives: the maximization of the profit gained by the distribution process and the minimization of CO 2 emissions. The latter is important due to the regulations imposed by the government. A compromise between both objectives exists, since profit maximization only will attempt to include as many customers as possible. But, longer routes will be needed, causing more CO 2 emissions. The manufacturer aims to minimize its manufacturing and shipping costs. Since a predefined hierarchy between both companies exists in the supply chain, a bi-level programming approach is employed. This problem is modelled as a bi-level programming problem with two objectives in the upper level and a single objective in the lower level. The upper level is associated with the distributor, while the lower level is associated with the manufacturer. Due to the inherent complexity to optimally solve this problem, a heuristic scheme is proposed. A nested bi-objective tabu search algorithm is designed to obtain non-dominated bi-level feasible solutions regarding the upper level. Considering simultaneously both objectives of the distributor allow us to focus on the minimization of CO 2 emissions caused by the supply chain, but bearing in mind the distributor's profit. Numerical experimentation shows that the Pareto frontiers obtained by the proposed algorithm provide good alternatives for the decision-making process and also, some managerial insights are given. [ABSTRACT FROM AUTHOR]

To achieve the most efficiency in supply chain management, the capability of distribution networks is a key point for the entire supply chain. Stocks are critical for enhancing the efficiency of satisfying the demand of retailers in the distribution network. A configuration of a distribution network is consisted of routes and nodes. Each route connects a pair of nodes and each node is denoted as a supplier, a distribution center, or a retailer. For each route, it has a carrier whose available capacity for demand transmission is multi state. Hence, a distribution network is also regarded as a multi state network and such a network is named as a multi state distribution network (MDN) in here. The propose of this paper is to evaluate the system reliability which is defined as the probability that the MDN can meet all retailers' demand under stocks. In practical, all retailers' demand should be satisfied by stocks in the distribution centers (DCs) firstly. Therefore flow assignment in MDN model is mainly clarified by the relationship between the demand of retailers, stocks on DCs, and suppliers. The concept of minimal capacity vectors (MCVs) is then proposed and an algorithm is developed to obtaining MCVs for evaluating system reliability. [ABSTRACT FROM AUTHOR]

The field of supply chain management has been extensively studied, while its role in disaster relief operations has received limited contributions. Recent dedicated special issues on Humanitarian Operations and Supply Chain Management (HOSCM) and a dedicated Journal focusing on humanitarian logistics and supply chain management clearly indicate the growing popularity of the HOSCM literature. The purpose of our current study is to undertake an extensive review of extant literature published in operations and supply chain management journals as well as popular interdisciplinary journals. A review of 362 papers published between 2011 and 2017 provides a thematic outline of the study. The study pivots around nine key themes, which have gained prominent attention from HOSCM scholars, and draws a roadmap from reviewing earlier review papers to performance evaluation of HOSCM related studies. Some of the key themes include humanitarian logistics, theory focused research, case studies, mathematical models, humanitarian supply chain properties and resources needed for efficient and effective management of humanitarian operations. Finally, our study offers several research directions which may take the existing debates to a next level. [ABSTRACT FROM AUTHOR]

Environmental disaster and rapid climate change cautioned government bodies and environmental protection agencies, which resulted in legislations forcing business organizations to restrict their carbon emissions to make their supply chain a disaster resilient supply chain. In supply chain, carbon emissions are seen right away from the procurement of raw materials till the distribution of finished goods through logistics. Hence, there is strong need to fix carbon emissions and to make existing supply chain an environmentally sustainable supply chain to gain environmental disaster relief. This paper primarily focuses on minimizing carbon emissions in the raw material procurement and its logistics using a cap-and-trade method. In the raw material procurement and logistics, the carbon emission is caused during the ordering, transporting and holding the procured items from various suppliers. The paper aims to model sustainability-resilience link at the supply chain design level through the procurement and logistics of raw material which is considered as the primary stage of any supply chain. A dynamic non-linear mixed integer model featuring an environmental sustainability through cap-and-trade method of carbon emission is proposed that can be used to design sustainable procurement logistics for disaster resilient supply chain management. The proposed model in the paper is referred as SPL_DRSCM (sustainable procurement and logistics for disaster resilient supply chain management) and is validated through illustrations. Important useful managerial and practical insights are obtained from set of five different deterministic data sets. Proposed model for SPL_DRSCM MINLP shows significant cost saving while optimizing procurement and its logistics under carbon emission constraint. Comparative analysis is conducted and detailed numerical results are presented. [ABSTRACT FROM AUTHOR]

Supply chain risk management embroils quite a lot of situations of managerial decision-making under uncertainties. As contemporary supply chains are intricate networks exposed to ample vulnerabilities, a resilient supply chain with inbuilt capabilities for responding to unanticipated events can assume significance. This paper proposes a decision support model for managers for knowing, measuring and improving the level of resilience in manufacturing supply chains. A novel computational methodology involving the incidence analysis and grey theory is proposed in this study. Using the methodology of advanced analysis of grey incidences, the level of resilience of supply chains can be measured. Various strategies and attributes imparting resilience, particularly relevant to the manufacturing industry are analyzed in this research. A framework considering five strategies and twenty-three attributes contributing to supply chain resilience is also constructed. And a case evaluation has been conducted to implementing the proposed methodology. Managers can ascertain their supply chain resilience capabilities by means of synthetic resilience index, as recommended in this study. From the measures of resilience for the bygone period, top management can assess and improve the resilience capabilities of their supply chain, by taking strategic level decisions. [ABSTRACT FROM AUTHOR]

One of the major objectives of modern supply chain management is dealing with the negative impact of decentralization among the involved entities and minimizing double marginalization effect within the chain, especially when the end-customers' demand is not deterministic. This paper investigates coordination issue in a three-level supply chain with one raw-material supplier, one manufacturer, and one retailer. The retailer determines the retail price, sales effort, and order quantity simultaneously before the selling season starts. Both the supplier and the manufacturer face random yield in production. A composite contract having two components—a contingent buyback with target sales rebate and penalty between the retailer and the manufacturer, and a revenue sharing contract between the manufacturer and the supplier is proposed. The proposed composite contract is shown to achieve supply chain coordination and allows arbitrary allocation of total channel profit among all the chain members. The impact of randomness in both demand and production, and the impact of non-existence of emergency resource for the final product on the performance of the entire supply chain are analyzed. A numerical example is provided to illustrate the developed model and draw some important managerial insights. [ABSTRACT FROM AUTHOR]

In practice, a vendor may offer a retailer an advance-cash-credit (ACC) payment scheme. This implies the buyer needs to pay a fraction of the purchasing cost before he receives the item (advance payment), some cash when the item is arrived (cash on delivery), and then the remaining purchasing cost after a credit period (credit payment). This paper studies the effect of payment schemes on the supply chain network design. The network consists of an outside supplier, multiple distribution centers (DCs), and multiple retailers. The DCs receive an upstream ACC payment from the supplier. This study attempts to determine the optimal location, allocation, as well as the inventory cycle time while minimizing total cost. A continuous approximation is used in the model development and the time value of money concept is considered, since different payment schemes related to time change the cash value. Numerical studies are adopted to demonstrate the solution approach and the effects of changing parameters on decisions and total cost. This study provides novel management implications for supply chain network designers' reference. The results show that the number of DCs to be opened, the joint replenishment cycle time of DC, and the total cost increase as the interest earned decreases and the interest charged increases. [ABSTRACT FROM AUTHOR]

In the past, most companies in the European apparel industry focused on minimizing manufacturing costs in the design of supply chains in conjunction with long-distance shipping from production sites in the Far East and relatively long production cycles. Today, for some market segments, the speed of production cycles is more important than the cost because short throughput time allows the flexibility to adjust to rapidly changing fashion trends in these market segments. Accordingly, choosing the most beneficial supply chain strategy has become an established research topic. However, apparel markets are complex systems. Therefore, attempts to reduce the underlying complexity in order to model these markets have limited existing research to the consideration of only selected aspects of markets (e.g., considering only homogeneous buyers, a single period, a single product, or a single manufacturer in the absence of competition) rather than taking a more comprehensive view. These limitations can be overcome by applying an agent-based simulation approach—an approach that can account for a wider range of factors, including several competing manufacturers utilizing different supply chain strategies, individual consumer preferences and behavior, word-of-mouth communication, normative social influence, and first-hand experience, as well as advertising. In this paper, the capability potential of such agent-based market simulation is demonstrated by investigating two supply chain strategies (fast fashion vs. traditional fashion) with varying product and communication strategies (product attributes and advertising) in several market scenarios. [ABSTRACT FROM AUTHOR]

Sustainable Supply Chain Management (SSCM) is a topic of growing interest among researchers. Many works have investigated the negative impact of CO2 emission, but have put less emphasis on other emission types. Many works have focused on the economic and environmental dimensions of sustainability but lacked content on the social dimension. Since SSCM is concerned with all aspects of sustainability, this work undertakes the three dimensions of sustainability and models particulate pollution (PM2.5) which has been cited in the literature to have a negative impact on human health. The paper constructs a mathematical programming model that minimizes the transportation costs and the undesirable social medical costs for remedying the release of PM2.5 into the atmosphere. The paper solves a model that evaluates different transportation modes, transportation costs, carbon emissions, PM2.5, medical costs, and capturing options. Moreover, the work utilizes a Monte Carlo simulation to best present the inherent variations in the model. Largely, the work provides stakeholders with transportation mode choices and greening opportunity investments to minimize the overall transportation costs while respecting physical and operational constraints. [ABSTRACT FROM AUTHOR]

Environmental impact is one of the major causes of tax and subsidy interactions between the government and firms. The government sets the tax of the upstream impact and designs the subsidy threshold value to promote the green effort of firms. This paper presents the optimal decision of the supply chain and the effective environmental governance strategy of the government. A Stackelberg game between the government and a two-echelon supply chain is constructed, where a supplier makes core parts for a manufacturer. First, we compared the effects of subsidy on the pricing decisions of firms and identified the profitable condition of the green effort of manufacturers. Results corroborate that a negotiated space for suppliers and manufacturers exists to reduce the environmental impact from the source, especially when the tax legislation is strict. Second, we obtained the optimal upstream contract of environmental impact in supply chains, which appears a phenomenon of the Matthew effect under any type of governance strategies. This finding affirms that subsidies make supply chains inclined to choose a greener upstream decision. The condition when subsidies make sense by effective environment improvement in the supply phase was further derived. Finally, with tax and subsidy governance strategies, the multi-perspective social welfare was simulated and analyzed. Accordingly, we verified that the growth boundary of the supply-chain profit with high subsidy threshold is better than that of the social welfare or the environment performance. It implies that setting the green subsidy standard originally high is a comprehensively sustainable choice for social welfare. In addition, the simulations of three tax structures were analyzed in extensions. [ABSTRACT FROM AUTHOR]

This paper studies the price and cold-chain service decisions of a fresh agri-product supply chain with competing retailers and explores the impacts of (horizontal/vertical) integration on the decisions and profits. When the cold-chain service price is exogenous, we find that vertical integration is more effective to decrease quantity/quality loss of agri-products; the third-party logistics provider is better off with vertical integration while horizontal integration hurts both the third-party logistics provider and the supplier. We identify the conditions under which a retailer benefits from vertical or horizontal integration. Whether horizontal integration can improve the retailer's profit depends on product substitutability. The profit of a retailer can be enhanced by vertical integration between the other retailer and the supplier if product substitutability is low. The endogenization of the cold-chain service price does not change the main results qualitatively. [ABSTRACT FROM AUTHOR]

Humanitarian supply chains (HSCs) contribute significantly to achieving effective and rapid responses to natural and man-made disasters. Though humanitarian organizations have during the last decades made considerable efforts to improve the response to crises in terms of effectiveness and efficiency, HSCs are still faced with so many challenges, one of which is the incorporation of sustainability dimensions (economic, social and environmental) in the management of their supply chains. In the literature, some authors have highlighted that the planning and achievement of sustainability performance objectives in humanitarian operations is hindered by the lack of decision support systems (DSS). Therefore, this paper proposes a multi-objective Master Planning DSS for managing sustainable HSCs. This Master Planning DSS includes: (1) the definition of a set of metrics for measuring the performance of a sustainable HSC; (2) an algorithm to solve the multi-objective problem; and (3) a Master Planning mathematical model to support the tactical planning of the sustainable HSC. Using the information gathered from field research and the literature, an illustrative numerical example is presented to demonstrate the implementation and utility of the proposed DSS. The results show that the order in which the three sustainability dimensions (economic, social and environmental) are prioritized has some impact on the performance measures. Therefore, it is important to fix a tolerance that would enable to obtain an acceptable balance (trade-off) between the three sustainability objectives, in line with the prioritization choice of the decision maker. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to demonstrate conceptual and theoretical similarities between disaster relief chains (DRCs) and commercial supply chains using the customer relationship management process model (CRM) of the seminal global supply chain forum framework (GSCF) as a lens of analysis (Croxton et al. in Int J Logist Manag 12(2):13–36, 2001). A range of empirical data from a case study of the 2006 relief and recovery response to the Cyclone Larry disaster is analysed using the CRM process model of the GSCF framework as a lens of analysis. We find that there are unexpected conceptual and theoretical similarities between DRCs in the Cyclone Larry disaster response and commercial supply chains. The study demonstrates that core commercial SCM concepts such as integration and integrative process management can also be found empirically in the domain of disaster response operations and allied management of supply chains for disaster relief and recovery (DROSCM). The study also shows that research in the DROSCM domain can develop in a range of directions unfettered by a paradigm focused on differences between DRCs and commercial supply chains. This is the first study to conceptually, theoretically, and empirically demonstrate similarities between DRCs and commercial supply chains. [ABSTRACT FROM AUTHOR]

This paper aims to develop a recovery planning approach in a three-tier manufacturing supply chain, which has a single supplier, manufacturer, and retailer under an imperfect production environment, in which we consider three types of sudden disturbances: demand fluctuation, and disruptions to production and raw material supply, which are not known in advance. Firstly, a mathematical model is developed for generating an ideal plan under imperfect production for a finite planning horizon while maximizing total profit, and then we re-formulate the model to generate the recovery plan after happening of each sudden disturbance. Considering the high commercial cost and computational intensity and complexity of this problem, we propose an efficient heuristic, to obtain a recovery plan, for each disturbance type, for a finite future period, after the occurrence of a disturbance. The heuristic solutions are compared with a standard solution technique for a considerable number of random test instances, which demonstrates the trustworthy performance of the developed heuristics. We also develop another heuristic for managing the combined effects of multiple sudden disturbances in a period. Finally, a simulation approach is proposed to investigate the effects of different types of disturbance events generated randomly. We present several numerical examples and random experiments to explicate the benefits of our developed approaches. Results reveal that in the event of sudden disturbances, the proposed mathematical and heuristic approaches are capable of generating recovery plans accurately and consistently. [ABSTRACT FROM AUTHOR]

Supply chain performance evaluation problems are evaluated using data envelopment analysis. This paper proposes a fuzzy network epsilon-based data envelopment analysis for supply chain performance evaluation. In the common data envelopment analysis models which are used for evaluation of decision-maker units efficiency, there are several inputs and outputs. One of the bugs of such models is that the intermediate products and linking activities are overlooked. Considering these intermediate activities and products, the current study evaluates the performance of decision-maker units in an automotive supply chain. There are ten decision-maker units in the supply chain in which there are three suppliers, two manufacturers, two distributors, and four customers. Moreover, the overall efficiency of input-oriented (input-based) model and input-oriented divisional efficiency are calculated. In order to improve the efficiencies, the projections onto the frontiers are obtained by using the outputs of the solved model and Lingo software. In order to show the applicability of the proposed model, it is applied on automotive industry, as a case study, to evaluate supply chain performance. Then, the overall efficiencies of DMUs and each sections (divisions) of DMUs were calculated separately. Therefore, every organization can apply this evaluation method for improving the performance of alternative factors. [ABSTRACT FROM AUTHOR]

This paper studies a two-tier duopoly competing supply chain system consisting of two manufacturers and two exclusive retailers. Both manufacturers produce differentiated products and both retailers provide extended warranties for the products they sell. Two types of channel-structure strategy options are considered: a decentralized structure with a wholesale price contract and a coordinated structure with a sophisticated contract. We first derive the equilibrium outcomes under three possible chain-to-chain competition scenarios. Subsequently, we reveal how manufacturers control their retail channels to gain more supply chain system profit under an interactive environment with supply chain competition and retailers' extended warranties. We find that pure coordinated channel competition and pure decentralized channel competition may both reach equilibrium. Furthermore, the interaction forces of supply chain competition and extended warranty service significantly impact the characteristics of the equilibria. Finally, we analyze the competing supply chain's coordination contract design by using the example of a two-part tariff contract, and determine the feasible contract parameter range that results in a win-win solution for supply chain members. [ABSTRACT FROM AUTHOR]

A supplier of products and services aims to minimize the capacity investment cost and the operational cost incurred by unwanted byproducts, e.g. carbon dioxide emission. In this paper, we consider a sustainable supply chain network design problem, where the capacity and the product flow along each link are design variables. We formulate it as a multi-criteria optimization problem. A bio-inspired algorithm is developed to tackle this problem. We illustrate how to design a sustainable supply chain network in three steps. First, we develop a generalized model inspired by the foraging behaviour of slime mould Physarum polycephalum to handle the network optimization with multiple sinks. Second, we propose a strategy to update the link cost iteratively, thus making the Physarum model to converge to a user equilibrium. Third, we perform an equivalent operation to transform a system optimum problem into a corresponding user equilibrium problem so that it is solvable in the Physarum model. The efficiency of the proposed algorithm is illustrated with numerical examples. [ABSTRACT FROM AUTHOR]

Supply chain (SC) design problems are often characterized with uncertainty related to the decision-making parameters. The stochastic goal programming (SGP) was one of the aggregating procedures proposed to solve the SC problems. However, the SGP does not integrate explicitly the Manager's preferences. The aim of this paper is to utilize the chance constrained programming and the satisfaction function concept to formulate strategic and tactical decisions within the SC while demand, supply and total cost are random variables. [ABSTRACT FROM AUTHOR]

Environmental responsibility has become an important part of doing business. Government regulations and customers' increased awareness of environmental issues are pushing supply chain entities to reduce the negative influence of their operations on the environment. In today's world, companies must assume joint responsibility with their suppliers for the environmental impact of their actions. In this paper, we study coordination between a buyer and a vendor under the existence of two emission regulation policies: cap-and-trade and tax. We investigate the impact of decentralized and centralized replenishment decisions on total carbon emissions. The buyer in this system faces a deterministic and constant demand rate for a single product in the infinite horizon. The vendor produces at a finite rate and makes deliveries to the buyer on a lot-for-lot basis. Both the buyer and the vendor aim to minimize their average annual costs resulting from replenishment set-ups and inventory holding. We provide decentralized and centralized models for the buyer and the vendor to determine their ordering/production lot sizes under each policy. We compare the solutions due to independent and joint decision-making both analytically and numerically. Finally, we arrive at coordination mechanisms for this system to increase its profitability. However, we show that even though such coordination mechanisms help the buyer and the vendor decrease their costs without violating emission regulations, the cost minimizing solution may result in increased carbon emission under certain circumstances. [ABSTRACT FROM AUTHOR]

This paper studies the impact of service outsourcing under three supply chain power structures: manufacturer-Stackelberg, vertical-Nash and retailer-Stackelberg supply chains. We first investigate price and service decisions by comparing the integrated channel and the decentralized channel with service outsourcing. It is found that a lower retail price or a higher service level could occur in the decentralized channel with service outsourcing compared to those in the integrated channel, but they never occur simultaneously. Next, we examine the manufacturer's channel strategies, and demonstrate that service outsourcing can always help the manufacturer earn more profit from the decentralized channel than from the integrated channel in the manufacturer-Stackelberg and retailer-Stackelberg markets, as long as the retailer's service investment is sufficiently efficient. However, in the vertical-Nash supply chain, this occurs only when the manufacturer is inefficient and the retailer is efficient enough in service provision. Finally, comparisons of channel efficiency and numerical analysis are provided. [ABSTRACT FROM AUTHOR]

This paper deals with the supply chain network design and planning for a multi-commodity and multi-layer network over a planning horizon with multiple periods in which demands of customer zones are considered to be price dependent. These prices determine the demands using plausible price-demand relationships of customer zones. The net income of the supply chain is maximized, while satisfying budget constraints for investment in network design. In addition, a new approach is considered for capacity planning to make the problem more realistic. In this regard, when production plants are opened and expanded, capacity options are taken into account for manufacturing operations. Furthermore, several aspects relevant to real world applications are captured in the problem. Different interconnected time periods in the planning horizon are considered for strategic and tactical decisions in the problem and then, a mixed-integer linear programming (MILP) model is developed. The performance and applications of the model are investigated by several test problems with reasonable sizes. The numerical results illustrate that obtained solutions after solving the MILP model by using CPLEX solver are acceptable. Moreover, using an alternative pricing approach, a tight upper bound is provided for the problem. In addition, a deep sensitivity analysis is conducted to show the validity and performance of the proposed model. [ABSTRACT FROM AUTHOR]

In this article, we intend to model and optimize the bullwhip effect (BWE) and net stock amplification (NSA) in a three-stage supply chain consisting of a retailer, a wholesaler, and a manufacturer under both centralized and decentralized scenarios. In this regard, firstly, the causes of BWE and NSA are mathematically formulated using response surface methodology (RSM) as a multi-objective optimization model that aims to minimize the BWE and NSA on both chains. The simultaneous analysis of the BWE and NSA is considered as the main novelty of this paper. To tackle the addressed problem, we propose a novel multi-objective hybrid evolutionary approach called MOHES; MOHES is a hybrid of two known multi-objective algorithms i.e. multi-objective electro magnetism mechanism algorithm (MOEMA) and population-based multi-objective simulated annealing (PBMOSA). We applied a co-evolutionary strategy for this purpose with eligibility of both algorithms. Proposed MOHES is compared with three common and popular algorithms (i.e. NRGA, NSGAII, and MOPSO). Since the utilized algorithms are very sensitive to parameter values, RSM with the multi-objective decision making (MODM) approach is employed to tune the parameters. Finally, the hybrid algorithm and the singular approaches are compared together in terms of some performance measures. The results indicate that the hybrid approach achieves better solutions when compared with the others, and also the results show that in a decentralized chain, the order batching factor and the demand signal processing in wholesaler are the most important factors on BWE. Conversely, in a centralized chain, factors such as rationing, shortage gaming, and lead time are the most effective at reducing the BWE. [ABSTRACT FROM AUTHOR]

This paper considers the pricing decisions of substitutable products which are produced by duopolistic manufacturers respectively and then sold by one common retailer to the consumers. Both the manufacturing cost and the customer demand for each product are characterized as fuzzy variables. Six expected value models are developed to explore the effects of the duopolistic manufacturers' three pricing strategies (i.e. Bertrand competition, Stackelberg competition, cooperation) and vertical competition between the manufacturers and the retailer on the optimal pricing decisions and channel profit-split of a two echelon supply chain, and the corresponding analytical solutions are derived. Finally, a numerical example is given to illustrate the effectiveness of the proposed models, and to gain additional managerial insights. [ABSTRACT FROM AUTHOR]

In this paper, we develop a supply chain network game theory model with product differentiation, possible outsourcing of production and distribution, and quality and price competition. The original firms compete with one another in terms of in-house quality levels and product flows, whereas the contractors, aiming at maximizing their own profits, engage in competition for the outsourced production and distribution in terms of prices that they charge and their quality levels. The solution of the model provides each original firm with its optimal in-house quality level as well as its optimal in-house and outsourced production and shipment quantities that minimize the total cost and the weighted cost of disrepute, associated with lower quality levels and the impact on a firm's reputation. The governing equilibrium conditions of the model are formulated as a variational inequality problem. An algorithm, which provides a discrete-time adjustment process and tracks the evolution of the product flows, quality levels, and prices over time, is proposed and convergence results given. Numerical examples are provided to illustrate how such a supply chain network game theory model can be applied in practice. The model is relevant to products ranging from pharmaceuticals to fast fashion to high technology products. [ABSTRACT FROM AUTHOR]