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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]

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]

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]

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]

In the last decade, selling to end customers via online channels has played an increasingly important role for the rapid development of e-commerce. Unlike brick-and-mortar distribution channels, the electronic channel can endow e-tailers with more bargaining power over a manufacturer, in particular with respect to setting the wholesale prices. This paper models the strategic interaction between e-tailers, who compete (imperfectly) in the online channel(s) and a monopolistic manufacturer and allows, in contrast to the previous literature, that e-tailers have price-setting power vis-à-vis the manufacturer (who can still decide on which e-tailer(s) to supply. The paper investigates the performance of the manufacturer and the e-tailers in a model that incorporates a vertical variable (the magnitude of a cross-channel spillover between online and offline distribution channels) and a horizontal variable (the degree of e-tailer competition) and allows for a dominant e-tailer structure as well as a dominant manufacturer structure). It considers a two-stage game theoretical model that captures the two key factors and solves for an equilibrium. More specifically, the paper characterizes an equilibrium in the dominant e-tailer structure when the cross-channel spillover is positive and downstream competition is not that strong (as well as in the dominant manufacturer structure). The paper also compares the firms' performances under the two different power structures (dominant e-tailer structure and dominant manufacturer structure) and investigates the magnitude of the e-tailers benefit that is related to a change in their bargaining power. In addition, the cross-channel spillover affects e-trailers' payoffs positively while peer competition has a negative effect on their profits. This paper thus closes a gap as in the literature few papers have focused on the impact of powerful e-tailers on wholesale price decisions and highlight the importance that the e-tailer should take into account both the competition parameter and the cross-channel effect when taking measures that might affect the power structure. [ABSTRACT FROM AUTHOR]

With the rapid growth of the global digital economy, supply chain finance has entered the stage of platform development in view of the history, policy environment, market status and other factors. Supply chain finance relies on multiple supply chain stakeholders to carry out financial business, which needs to solve a variety of financial risk control and pricing issues. The financing model in supply chain finance can be differentiate from the traditional credit model. The service mode and leading mode of supply chain finance need to be adjusted in accordance with the changes of the industrial operation. Further, the business mode of supply chain finance shows a diversification trend, which includes traditional supply chain financial models such as accounts receivable, advance payment, inventory financing, and supply chain credit financing models. In this paper, we investigate the similarities between supply chain finance and options, and further introduce American call options to supply chain financial products under the mode of small and medium-sized enterprises' (SMEs) accounts receivable financing. The price of supply chain financial products is derived through the trinomial tree option pricing model, which determines the corporate financing interest rates. The rationality of the proposed pricing model is validated in comparison with the medium and long-term load bank interest rates. The contribution of the paper is in providing SMEs with supply chain financial products under the accounts receivable model to resolve financing difficulties and the pricing the products through the trinomial budget pricing model. [ABSTRACT FROM AUTHOR]

Supply Chain Finance (SCF), an important way of integrating industry and finance that has emerged in recent decades, has attracted the interest of both industry and academia. A large number of conceptual studies on SCF support the theory that SCF benefits supply chains by alleviating financing problems and maintaining stability. The focal firms which are the main SCF practices provider help alleviating the financing problem of their partners by weakening part of the working capital management. However, SCF-oriented practice on the focal firm and traditional corporate finance theory which earing profit by improving working capital management are not aligned. This paper attempts to provide empirical evidence to explain this phenomenon on the SCF-oriented perspective. Secondary panel data analysis is employed. The impact of focal firms providing SCF services is used to represent SCF practices in the supply chain since focal firms dominate SCF activities. Cash Conversion Cycle (time perspective), trade credit and prepayment (volume perspective) of the focal firms are independent variables of the analysis. Three type of performances, financial, risk and operations, are dependent variables of the analysis. This study found that a focal firm providing SCF can conditionally improve their firm's financial performance, risk levels and operations management. Results from different industrial analyses suggest that tertiary industries are best suited to implementing SCF activities. Providing SCF also benefits the firm-level performance of state-owned enterprises. This is the first paper that comprehensively analyses the effects of SCF implementation with different firm characteristics from both a time perspective and a volume perspective. [ABSTRACT FROM AUTHOR]

The anti-epidemic supply chain plays an important role in the prevention and control of the COVID-19 pandemic. Prior research has focused on studying the facility location, inventory management, and route optimization of the supply chain by using certain parameters and models. Nevertheless, uncertainty, as a vital influence factor, greatly affects the supply chain. As such, the uncertainty that comes with technological innovation has a heightened influence on the supply chain. Few studies have explicitly investigated the influence of technological innovation on the anti-epidemic supply chain under the COVID-19 pandemic. Hence, the current research aims to investigate the influences of the uncertainty caused by technological innovation on the supply chain from demand and supply, shortage penalty, and budget. This paper presents a three-level model of the anti-epidemic supply chain under technological innovation and employs an interval data robust optimization to tackle the uncertainties of the model. The findings are obtained as follows. Firstly, the shortage penalty will increase the costs of the objective function but effectively improve demand satisfaction. Secondly, if the shortage penalty is sufficiently large, the minimum demand satisfaction rate can ensure a fair distribution of materials among the affected areas. Thirdly, technological innovation can reduce costs. The technological innovation related to the transportation costs of the anti-epidemic material distribution center has a greater influence on the optimal value. Meanwhile, the technological innovation related to the transportation costs of the supplier has the least influence. Fourthly, both supply and demand uncertainty can influence costs, but demand uncertainty has a greater influence. Fifthly, the multi-scenario budgeting approach can decrease the calculation complexity. These findings provide theoretical support for anti-epidemic dispatchers to adjust the conservativeness of uncertain parameters under the influence of technological innovation. [ABSTRACT FROM AUTHOR]

Large-scale disasters occur worldwide, with a continuing surge in the frequency and severity of disruptive events. Researchers have developed several optimization models to address the critical challenges of disaster relief supply chains (e.g., emergency material reserving and scheduling inefficiencies). However, most developed algorithms are proven to have low fault tolerance, which makes it difficult for disaster relief supply chain managers to obtain optimal solutions and meet the emergency distribution requirements within a limited time frame. Considering the uncertainty and ambiguity of disaster relief information and using Interval Type-2 Fuzzy Set (IT2TFS), this paper presents a collaborative optimization model based on an integrative emergency material supplier evaluation framework. The optimal emergency material suppliers are first selected using a multi-attribute group decision-making ranking method. Multi-objective fuzzy optimization is then run in three emergency phases: early -, mid-, and late-disaster relief stages. Focusing on a massive flash flood disaster event in Yunnan Province as a case study, a comprehensive numerical analysis tests and validates the developed model. The results revealed that the proposed optimization method can optimize emergency material planning while ensuring that reserve material safety inventory is always maintained at a reasonable level. The presented method suggests a fuzzy interval to prevent emergency materials' safety inventory shortage and minimize continuous life/property losses in disaster-affected areas. [ABSTRACT FROM AUTHOR]

Supply chain viability (SCV) is an emerging concept of growing importance in operations management. This paper aims to conceptualize, develop, and validate a measurement scale for SCV. SCV is first defined and operationalized as a construct, followed by content validation and item measure development. Data have been collected through three independent samplings comprising a total of 558 respondents. Both exploratory and confirmatory factor analyses are used in a step-wise manner for scale development. Reliability and validity are evaluated. A nomological model is theorized and tested to evaluate nomological validity. For the first time, our study frames SCV as a novel and distinct construct. The findings show that SCV is a hierarchical and multidimensional construct, reflected in organizational structures, organizational resources, dynamic design capabilities, and operational aspects. The findings reveal that a central characteristic of SCV is the dynamic reconfiguration of SC structures in an adaptive manner to ensure survival in the long-term perspective. This research conceptualizes and provides specific, validated dimensions and item measures for SCV. Practitioner directed guidance and suggestions are offered for improving SCV during the COVID-19 pandemic and future severe disruptions. [ABSTRACT FROM AUTHOR]

Recent pandemic outbreaks, including the COVID-19 and SARS, have revealed that supply chains (SCs) are unable to respond to such disasters. To mitigate the destructive impacts and improve the performance of SCs, Operations Research (OR) techniques have been applied to address the issues over the last two decades. The objective of this paper is to develop a network data envelopment analysis (NDEA) model to measure the resilience and sustainability of healthcare SCs in response to the COVID-19 pandemic outbreak. In the proposed NDEA model, for the first time, outputs' weak disposability, chance-constrained programming (CCP), the convexity assumption, and the semi-oriented radial approach are aggregated. Moreover, a modified directional distance function (DDF) measure is developed to measure the overall and divisional efficiency scores. Furthermore, the proposed model can deal with different types of data such as integer-valued data, negative data, stochastic data, ratio data, and undesirable outputs. Also, several useful and interesting properties of the novel efficiency measure are presented. Finally, we measure the performance of 28 healthcare SCs to demonstrate the applicability and capability of our proposed approach. [ABSTRACT FROM AUTHOR]

Organization's sustainability performance is influenced by its suppliers' sustainability performance. This relationship makes sustainable supplier development a strategic competitive option for a buyer or focal organization. When considering sustainable supplier development practices (SSDPs) adoption, organizations have to balance and consider their limited financial resources and operational constraints. It becomes necessary to both select the best SSDPs set and investment allocation among the selected SSDP set such that the organization can maximize overall sustainability performance level. In this paper, an integrated formal modeling methodology using DEMATEL, the NK model, and multi-objective linear programming model is used support this objective. The proposed methodology is evaluated in a practical sustainable supply chain field study of an equipment manufacturing company in China. Through case study, we found that the interdependency among SSDPs must be considered in SSDPs selection and investment allocation problem. Theoretical, managerial and methodology implications, conclusions, and directions for future research are also presented. [ABSTRACT FROM AUTHOR]

In recent times, the literature has seen considerable growth in research at the intersection of digital innovation, data analytics, and supply chain resilience. While the number of studies on the topic has been burgeoning, due to the absence of a comprehensive literature review, it remains unclear what aspects of the subject have already been investigated and what are the avenues for impactful future research. Integrating bibliometric analysis with a systematic review approach, this paper offers the review of 262 articles at the nexus of innovative technologies, data analytics, and supply chain resiliency. The analysis uncovers the critical research clusters, the evolution of research over time, knowledge trajectories and methodological development in the area. Our thorough analysis enriches contemporary knowledge on the subject by consolidating the dispersed literature on the significance of innovative technologies, data analytics and supply chain resilience thereby recognizing major research clusters or domains and fruitful paths for future research. The review also helps improve practitioners' awareness of the recent research on the topic by recapping key findings of a large amount of literature in one place. [ABSTRACT FROM AUTHOR]

In this paper, a supply chain including a farmer, a dairy manufacturer, and consumers is considered in which a particular product is sold through two channels, i.e., formal and informal. In the former, the dairy manufacturer buys the dairy product at a wholesale price from the farmer and sells it to consumers, whereas in the latter, the farmer sells the product directly to consumers. The farmer may add a sort of chemical additive to the product in order to increase its demand in either channel. This may be discovered only if a product safety accident happens. Furthermore, the government, as a regulator, plays an integral role in preventing the production and consumption of contaminated food. We aim to investigate the behavior of players in this supply chain and decide about safety issues and the wholesale price of the product using the game theory approach. To this end, four scenarios, including centralized structure, decentralized structure, cost-sharing contract, and safety guarantee contract, are examined. The experimental results reveal that by enacting appropriate laws, the government can prevent the supply chain players from utilizing unauthorized chemical additives. Furthermore, it is shown that the safety guarantee contract can improve the safety level of the product, which is always at a higher level in the formal channel than in the informal one. It was also revealed that fining the farmer has a greater impact on product safety than fining the manufacturer. Moreover, the farmer has less tendency to use chemical additives when the costs of the product and chemical additives are high or additives pose a high risk to consumers whereas higher product prices tempt the farmer to utilize more additives. [ABSTRACT FROM AUTHOR]

This paper investigates the effects of reselling and agency contracts on the platform's incentive to share information under two scenarios, i.e., the recommendation scenario and non-recommendation scenario. Through analyzing the equilibrium solutions, we derive the following results. First, comparing the recommendation and non-recommendation scenarios, the platform prefers the recommendation scenario under the reselling contract. However, contrary to traditional wisdom, when the recommendation efficiency is relatively more efficient, the platform chooses the non-recommendation scenario in the agency contract; as the recommendation efficiency becomes less efficient, the recommendation scenario is preferred in the agency contract. Second, for the reselling contract, the platform prefers to withhold demand information in the recommendation and non-recommendation scenarios. However, the platform voluntarily shares this information under the agency contract for the two scenarios. Third, the platform's optimal strategy depends on the commission rate, the platform's recommendation efficiency, and the level of information accuracy. Intuitively, a lower commission rate induces the platform to prefer the reselling contract in the recommendation and non-recommendation scenarios. However, a higher commission rate does not always make the platform choose the agency contract. The recommendation efficiency and the level of information accuracy affect the platform's optimal strategy. Furthermore, given the platform's optimal strategy, there are Pareto optimal regions that make the manufacturer better off. That is, the platform and the manufacturer achieve a win–win situation. Finally, in an extension of the model, this paper shows the platform's optimal strategy when a hybrid contract is used, which also demonstrates the robustness of the results. [ABSTRACT FROM AUTHOR]

In this paper, a new responsive-green-cold vaccine supply chain network during the COVID-19 pandemic is developed for the first time. According to the proposed network, a new multi-objective, multi-period, multi-echelon mathematical model for the distribution-allocation-location problem is designed. Another important novelty in this paper is that it considers an Internet-of-Things application in the COVID-19 condition in the suggested model to enhance the accuracy, speed, and justice of vaccine injection with existing priorities. Waste management, environmental effects, coverage demand, and delivery time of COVID-19 vaccine simultaneously are therefore considered for the first time. The LP-metric method and meta-heuristic algorithms called Gray Wolf Optimization (GWO), and Variable Neighborhood Search (VNS) algorithms are then used to solve the developed model. The other significant contribution, based on two presented meta-heuristic algorithms, is a new heuristic method called modified GWO (MGWO), and is developed for the first time to solve the model. Therefore, a set of test problems in different sizes is provided. Hence, to evaluate the proposed algorithms, assessment metrics including (1) percentage of domination, (2) the number of Pareto solutions, (3) data envelopment analysis, and (4) diversification metrics and the performance of the convergence are considered. Moreover, the Taguchi method is used to tune the algorithm's parameters. Accordingly, to illustrate the efficiency of the model developed, a real case study in Iran is suggested. Finally, the results of this research show MGO offers higher quality and better performance than other proposed algorithms based on assessment metrics, computational time, and convergence. [ABSTRACT FROM AUTHOR]

The paper studies product bundling in a duopoly supply chain network under the influence of different power-balance structures, bundling decisions and advertising efforts on total supply chain profit. Mathematical models comprising two manufacturers and a single retailer are developed to capture the impact of bundling policy and advertisement strategy under three power-balance structures, namely Manufacturer Stackelberg, Retailer Stackelberg and Vertical Nash. Following game theory models and numerical examples, the study found that the total profit of the supply chain is undifferentiated under the manufacturer Stackelberg and Vertical Nash case in the manufacturer bundling and retailer bundling strategies. However, total supply chain profit under manufacturer bundling strongly dominates under retailer bundling in Retailer Stackelberg and Vertical Nash, and remains valid under multiple settings of market size, price elasticity and advertising elasticity. It is also found that manufacturer bundling is significantly affected by advertising effort compared to retailer bundling. The study contributes to the literature interfacing supply chain and marketing by studying bundling policy and advertising strategy simultaneously for homogenous products, under various power-balance structures and price competition. [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]

Emerging smart technology spawns many start-up firms, which enter into the market and bring more instability and uncertainty to supply chains. This paper develops a game-theoretic model which captures the most crucial factors in market entry stage, such as market uncertainty, competition, contract design, distribution channel, and sustainability. We consider a supply chain consisting of one supplier and two retailers (an incumbent and an entrant). We assume that the incumbent first enters a market and possesses private information about market demand. The entrant encroaches upon the market after observing its big growth potentials. In this paper, we study how the supplier optimally designs the contract for the retailers under asymmetric information to make the supply chain more efficient and sustainable. Subsequently, we investigate the preference of contractual forms between a franchise contract (FC) and a two-part tariff contract (TTC), from the perspectives of the supplier, the incumbent retailer, and the whole supply chain, respectively. It turns out that the supplier prefers the TTC while the incumbent is better off under the FC when the demand variation is relatively high. In addition, we find that the TTC is beneficial to the whole supply chain in most cases. In other words, TTC can promote the coordination of the supply chain and realize the sustainable development of the supply chain. We further analyze the impact of the entrant entry on the supplier's contract design for the incumbent. The supplier tends to charge the lower wholesale price and less franchise fee for the incumbent after the entrant entry. The supplier's contract strategy is conducive to maintaining the horizontal competition and promoting the sustainability of the supply chain. We also analyze the supplier's distribution channel decision and find that she is more willing to block the entrant from entering the market in most cases because the incumbent with the private demand information makes the supply chain more efficient. Finally, we also extend our results by altering some assumption in the basic model. [ABSTRACT FROM AUTHOR]

This paper is motivated by a real pharmaceutical supply chain (PSC) of Valsartan, facing two major concerns. First, implementing effective policies for product recall management due to disruption occurring in the manufacturing process, including impurity in raw material and packaging errors. Second, determining the optimal selling price and quality of raw material affecting the quality of the final compound, Valsartan, due to the effect of these decisions on Valsartan demand. In this paper, we analytically evaluate the impacts of production disruption, defective products recall, and decentralization among the members on the performance of the multi-echelon PSC. Moreover, for the first time, we address the context of channel coordination as a risk-mitigating strategy in case of disruption occurrence by proposing an altered revenue-sharing contract. Therefore, decisions are analyzed comparing decentralized, centralized, and coordinated decision-making structures under a range of scenarios. The results reveal that the proposed coordination scheme not only shares the incurred costs by disruption occurrence among all members but also improves their profitability compared to that of the decentralized structure, which leads to implementing effective recall management. [ABSTRACT FROM AUTHOR]

This paper presents a vendor-managed inventory model for a three-layer supply chain comprised of suppliers, manufacturers, and retailers. This model considers an imperfect production system with a deterministic percentage of defective and deteriorated items, exponential demand for perishable products, and operational costs. The VMI model maximizes the benefits, assuming a Stackelberg approach to find the optimal values of replenishment lot sizes, production rates, selling prices, and product cycle length. A solution algorithm is developed to find the optimal solutions. A case study of the Dairy Industry for highly perishable products is provided to illustrate the applications, evaluate the performance, and obtain managerial insights. The results show that the percentage of defective and deteriorated items and remanufacturing rates are crucial in replenishment, production, and selling policies. The VMI agreement includes remanufacturing defective products to obtain new dairy derivates. The deteriorated products can be sold as near-expired products or inputs for compost, fertilizers, etc. Finally, some conclusions and future research lines are provided. [ABSTRACT FROM AUTHOR]

Transshipment yards are not usually considered in optimization approaches proposed for solving the log transportation problem. However, they may provide substantive advantages with respect to the usual logistics practice of direct delivering from supply forests to mills. Therefore, this paper evaluates, at the operational level, different supply chain topologies with the purpose of assessing potential costs savings associated to the use of intermediate storage facilities. The researched problem is defined by stated sets of log-suppliers, storage and transshipment yards, and facilities demanding several types of logs over a known planning horizon. The optimal transportation and inventory plan must be found. An optimization algorithm based on Column Generation + GRASP pricing metaheuristic was developed to compute minimal operation costs associated to different supply-chain topologies over a bank of instances generated from realistic information of the forestry activity in the Argentinean province of Misiones. [ABSTRACT FROM AUTHOR]

This paper examines a two-period dynamic contracting in a supply chain under information asymmetry, where a supplier sells a product to a retailer via a trade credit contract. It is found that the retailer always prefers to conceal her actual cost information thus signal as a higher-cost type in the first period to pursue a higher information rent, which would decrease the supplier's profit and thereby the overall profit of the supply chain. To mitigate this ratchet effect, we introduce a reputation compensation mechanism in the two-period trade credit setting. This mechanism could alleviate the information asymmetry to a certain extent as there exists a threshold that incentivizes the retailer to share her true cost information in the earlier period. Moreover, the retailer might claim as a lower-cost type when the supplier offers a relatively higher reputation compensation to take full advantage of her information. Therefore, the supplier should provide trade credit with a reasonable reputation compensation in a two-period setting to enhance his expected profit. [ABSTRACT FROM AUTHOR]

This paper considers a capital-constrained online retailer (OR) selling products through an e-commerce platform (EP) who also offers financial services to retailers. During the selling season, the OR exerts an effort to promote market demand through activities like sales promotions, advertising and live-streaming selling events. To investigate the EP-based financing scheme, a game-theoretic model is developed where the EP functions as the leader determining the interest rate and platform usage fee rate, and the OR functions as the follower determining the order quantity and effort level. We explore the impacts of the OR's risk-aversion and find that when the OR is risk-averse (1) she sets a high effort level, and the EP sets a high usage fee rate; (2) a high risk-averse OR orders less products than low risk-averse OR. We design specific revenue-cost sharing contracts to coordinate the supply chain and demonstrate that the designed contracts are feasible. Moreover, we find that the OR consistently prefers EP financing compared to bank financing. [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]

Supply chain finance (SCF) is a financial service that provides convenient loan transactions for small- and medium-sized enterprises (SMEs) upstream and downstream of the supply chain. SCF can help to smooth the capital flow of many SMEs. However, it is difficult for agricultural SMEs to participate in SCF because this kind of SME usually has various risks. Objectively, evaluating the credit rating of agricultural SMEs is difficult for commercial banks. Furthermore, unlike general manufacturing enterprises, agricultural enterprises produce directly based on nature. Sustainable development based on the natural environment is very important for agricultural enterprises. In this paper, considering sustainability, we construct a criteria system to evaluate the credit ratings of agricultural SMEs for SCF. Moreover, we study a method for processing the hybrid heterogeneous evaluation information of SMEs. A co-decision method is proposed to classify the credit ratings of agricultural SMEs with the help of three-way decisions. Agricultural SMEs are evaluated by both criteria evaluation information and misclassification loss. Finally, a credit rating evaluation example is presented to demonstrate the application of our method. The results show that our proposed method can be used to fully evaluate agricultural SMEs with fine classification effects. It can also provide a reference for commercial banks to determine the credit of agricultural SMEs with a low decision risk. [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]

Green product development depends on the green innovation behavior of upstream and downstream companies in the supply chain. This paper focuses on a green supply chain consisting of a supplier and a manufacturer and considers two financing schemes wherein the manufacturer's operating capital and green innovation capital are both constrained: bank credit financing (BCF) and supplier green investment (SGI). We investigate the financing strategy of a manufacturer with different financing decision preferences and supply chain coordination contract designs. The results show that when the manufacturer's financing decision preference is low bankruptcy risk, it should choose BCF when the bank loan interest rate is lower than a threshold and SGI when the bank loan interest rate is higher than this threshold; when the manufacturer's financing decision preference is high R&D benefit, it should choose BCF when the initial capital is lower than another threshold and choose SGI when the initial capital is higher than this threshold. Then, we compare whether cost-sharing, quantity discount and revenue-sharing contracts can coordinate the supply chain, and discuss the selection strategies of supply chain members for coordination contracts. Research shows that revenue-sharing contracts fail to coordinate; however, when the cost-sharing ratio and quantity discount rate are appropriate, both cost-sharing and quantity discount contracts can achieve supply chain coordination. The lower the supplier's unit production cost, the stronger its motivation to accept a higher cost-sharing ratio and quantity discount rate. For the supplier, the key to choosing any coordination contract lies in the relative height of the cost-sharing ratio and quantity discount rate while the manufacturer should always choose a quantity discount contract when the quantity discount rate is high enough. [ABSTRACT FROM AUTHOR]

The smart supply chain innovation (SSCI) has become the key way for enterprises to enhance their competitiveness. Therefore, it is very important for the current supply chain enterprises to choose a reasonable innovation path. Through the literature review method, this paper summarizes the four main evaluation indicators of path selection for smart supply chain innovation, which are technical indicators, organizational environment indicators, operational efficiency indicators, risk prevention and control indicators. According to the characteristics of evaluation index, the improved Fuzzy Entropy-Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is proposed. This method considers the situation that the original data contains both interval value and fixed value data. Firstly, the standardized decision matrix is constructed, and then the optimal index weight is established by Fuzzy Entropy method. Secondly, this paper calculates the weighted decision matrix by using the method of sub item weighting of hierarchical indicators. Finally, the improved TOPSIS method is used to determine the relative closeness of each scheme. According to the weighted decision matrix, the innovation path index of the smart supply chain (SSC) is further calculated. We use the actual case of a company to analyze the evaluation method for three different SSCI paths. This paper provides a reference for the path selection of SSCI from the aspects of theory and practice. [ABSTRACT FROM AUTHOR]

This paper explores the optimal joint decision of product information disclosure and ordering in a blockchain-enabled luxury supply chain. Using analytical models, we investigate the optimal joint decision of information disclosure and ordering under three scenarios (i.e., wholesale contracts only, revenue-sharing (RS) contracts only, and a hybrid of these two types of contracts). Furthermore, we extend our study to examine the impacts of the number of competing retailers and the retailers' fairness concerns on supply chain members' optimal decisions. Lastly, the theoretical results are checked and illustrated by numerical examples with sensitivity analysis. The main findings are as follows: (1) As the proportion of information-sensitive consumers in the market increases, the level of product information disclosure of supply chain members increases in varying degrees, while supply chain members' order quantities and profits first decrease and then increase in varying degrees. (2) When a RS contract is acceptable for all supply chain members, all members benefit from the cooperation between the manufacturer and retailers. (3) Although all supply chain members may benefit from an increase in the number of retailers, when the number of retailers is greater than a certain threshold, retailers would be caught in a "prisoner's dilemma" of product information disclosure due to consumer information overload. Moreover, to maximize business profits, manufacturers should sometimes strictly limit and control the number of their reseller partners, rather than blindly expand their markets. (4) Retailers may benefit from their own fairness concerns if and only if the level of fairness concerns is sufficiently low, otherwise such concerns would be harmful to all supply chain members. [ABSTRACT FROM AUTHOR]

The burgeoning digital economy has expanded the information gap in supply chains. Supply chain information transparency has thus attracted increasing attention from both industry and academia. Meanwhile, as consumers pay more attention to corporate social responsibility (CSR), firms have made efforts to audit their suppliers to avoid CSR violations. This paper explores the strategic role of CSR auditing in supply chain information transparency. We examine how CSR auditing interacts with supply chain information transparency by considering a scenario where a firm strategically sells either a single product or a product line through an online retail platform. Our results show that when the product line strategy is uncertain, the firm's audit commitment strengthens the platform's incentive to voluntarily disclose information. Our results also show that when the length of the product line is unchangeable, the platform prefers to share the information even if the firm does not make audit commitments. Additionally, when the platform's information sharing decision and the firm's product line design are made simultaneously, the platform may choose to privately withhold the information if the product line extension cost is in the moderate range and the demand loss from CSR-concerned consumers is relatively minor. [ABSTRACT FROM AUTHOR]

Vaccination is a well-known method to protect the public against an epidemic outbreak, e.g., COVID-19. To this end, the government of a country or region would strive to achieve its target of vaccination coverage. Limited by the total vaccine capacity of public hospitals, the government may need to cooperate with private hospitals or clinics for more vaccination. Exploring in this paper government coordination of public and private resources for vaccination, we model a vaccine system consisting of a public hospital, a profit-maximizing private clinic, and self-interested individuals, under three scenarios: (1) without information sharing (concerning vaccine inventory and vaccine price), (2) with information sharing and subsidy, and (3) with information sharing and allocation. We find that, under scenario (1), the vaccine demand is fully satisfied by the public hospital and the private clinic cannot make any profit. Under scenario (2), the private clinic is willing to enter the vaccine market with a positive profit-maximizing vaccination coverage. Under scenario (3), the socially optimal vaccination coverage may be lower than that under scenario (1). Moreover, we conduct a sensitivity analysis to generate practical implications of the research findings for vaccination policy-making. Our results provide both theoretical and managerial insights on vaccine supply decision, government intervention, and vaccination coverage. [ABSTRACT FROM AUTHOR]

The carbon quota allocation rules of China's pilot carbon emissions trading (CET) regions are various, which mainly include benchmarking, historical carbon intensity reduction and auctioning. When the allocation rules change, it is unresolved how to achieve the optimal product prices and effectively allocate the carbon emissions reduction profits of CET-covered enterprises in the cooperative supply chain. Thus, this paper uses the Stackelberg game, Nash equilibrium and the Shapley value based on cost modification to investigate these issues. The results indicate that: (1) The increasing carbon prices can always improve the retail prices only under the auctioning rule. Meanwhile, the growing low-carbon awareness of consumer cannot be always conducive to improving the wholesale and retail prices, and the similar product prices of non-CET-covered enterprises have greater impact on the wholesale prices than that on the retail prices. (2) Only under the free carbon quota allocation rules, can the optimal wholesale and retail prices under the Stackelberg game be always higher than those under the Nash equilibrium. Meanwhile, the auctioning rule can better reduce carbon emissions than the free allocation rules. (3) Improving carbon emissions reduction contribution and emission reduction costs can be conducive to increasing the carbon emission reduction profits of the supplier and retailer, while the impact of carbon emission reduction contribution on improving the carbon emission reduction profits is not always greater than that of the carbon emission reduction costs. [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]

This paper investigates a green supply chain (GSC) consisting of one manufacturer and one retailer who possesses private demand forecast information. To promote green consumption, the government may provide subsidies to consumers. Within a dynamic game where the manufacturer serves as the leader and the retailer acts as the follower, three cases are examined: centralized decision, decentralized decision with and without demand forecast information sharing between the retailer and the manufacturer. We mainly examine the value of information sharing on the decisions of a GSC in the context of government subsidies for consumers. We find that: (i) demand forecast information sharing benefits the manufacturer but damages the retailer; (ii) if the predicted value is higher than the determinate part of the demand, the manufacturer is willing to choose a higher green degree of products in the case with information sharing compared with that without information sharing; otherwise, the manufacturer is willing to choose a lower green degree of products; (iii) a two-part tariff contract is appropriate to coordinate the GSC and it is effective in increasing the green degree of products; (iv) information sharing benefits the GSC if the green production efficiency is high enough; (v) the ex-ante social welfare always increases with information accuracy. Finally, numerical analyses are conducted to verify the above findings. [ABSTRACT FROM AUTHOR]

This paper considers a supply chain with one supplier and two retailers. The supplier has limited normal capacity. When the orders of two retailers exceed the capacity, the supplier can satisfy the retailers with the limited normal capacity, or he can start an emergent production to increase his capacity in a short time with a high unit production cost. When the cost of quickly expanding capacity is lower than the market price, it is profitable for the whole system to start the emergent production. But the supplier has no incentives to do additional production if his cost is higher than the wholesale price. To resolve this issue, we propose a supply commitment contract that the supplier will fully fill a retailer's order if the retailer pays a premium to the supplier. We consider a practical setting that each retailer has private information on her average demand. Two contracting scenarios of the supplier are compared: contracting with the two retailers simultaneously (the simultaneous scenario) and sequentially (the sequential scenario). It is shown that the retailers will adopt the threshold strategy based on their private demand information to pay the premium. By numerically studies, we further illustrate the supplier's optimal contract choices and the consequent system performance. First, the suppliers always prefer the retailers to move simultaneous although the supplier's profit is only slightly higher than that of the sequential scenario; second, the supplier sets a lower wholesale price and a higher commitment fee in the sequential scenario than those of simultaneous scenario; finally, the sequential scenario is a better choice from the perspectives of both the whole supply chain system and the retailers. Our research recommends the sequential moving in the supply commitment contract that it benefits the whole supply chain system with only slightly less efficient for the supplier. [ABSTRACT FROM AUTHOR]

Traditional research shows that a retailer suffers a loss due to information sharing with a manufacturer in a supply chain. However, when the manufacturer produces both new and remanufactured products, the retailer's trade-offs change. This paper investigates whether the retailer can share demand information with the manufacturer if they can add remanufactured products to the product line. We reveal that the retailer can benefit from information sharing when the manufacturer may remanufacture. On the one hand, if the retailer shares information, the manufacturer utilizes information to strategically adjust wholesale prices, resulting in a reduction in the retailer's profit. On the other hand, if the retailer does not share the information, the manufacturer abandons remanufacturing, leading to a lower profit for the retailer. Therefore, when the former loss is less than the latter, the retailer is willing to share information with the manufacturer. Furthermore, we find that remanufacturing and information sharing can achieve a triple-win situation for the retailer, the manufacturer and the environment. [ABSTRACT FROM AUTHOR]

Information asymmetry leads to short-term competitive antagonism between downstream manufacturers and upstream suppliers. This paper applies a master-slave game to reproduce the interest conflict between a manufacturer and a supplier, and proposes a cooperative decision-making model based on information sharing, considering the interest consistency of upstream supply chain members. Additionally, the overall profit coordination mechanism is constructed to ensure the continuation of the cooperative decision-making relationship. In addition, to ensure that the supplier participating in cooperative decision-making has the supply capacity desired by the manufacturer, a rational evaluation system combined with game theory is employed to determine the most suitable participating supplier. A numerical example is given to demonstrate the systematization and effectiveness of the proposed method. Finally, through sensitivity analysis and comparative analysis, managerial insights and recommendations are obtained. [ABSTRACT FROM AUTHOR]

This paper proposes a novel advanced buyback (ABB) contract to coordinate a supply chain that consists of one supplier and one retailer. The contract stipulates when a buyback contract is executed and the amount of buyback. We model the interaction of supply chain participants as a Stackelberg game and incorporate the participants' reservation profits into the game to examine the effectiveness of the ABB contract with complete information. We demonstrate that the ABB contract can conveniently coordinate the supply chain, flexibly allocate profit, and facilitate avoidance of the aggressive overordering behavior of the retailer. This model is extended to the situation of information asymmetry, where the retailer holds private information about the cost of sales in discrete or continuous states. The optimal strategies of the supply chain and the participants are derived. Information asymmetry can damage the supplier but be beneficial to the retailer. The condition under which the supply chain achieves coordination is clarified. A numerical simulation is performed to verify and extend the results of the theoretical analysis. We show that the ABB contract always outperforms the ordinary wholesale price and buyback contracts with complete information. Supply chain coordination is more likely to be achieved if the demand variability is lower when weighing whether to share private information. Our findings can explain why retailers always have an incentive to inflate their cost of sales. [ABSTRACT FROM AUTHOR]

With the increasingly fierce market competition and the rapid development of advanced logistics technology, service quality guarantee and demand updating become effective ways to promote procurement decisions in logistics supply chain. However, information asymmetry and obedience behavior have made it more complicated. In this paper, we considered the above factors, and studied the capacity procurement issue in a logistics service supply chain consisting of a logistics service integrator (LSI) and a functional logistics service provider (FLSP) in two periods. First, we find the optimal purchase quantities increase with the FLSP's obedience factor, in specific conditions, the LSI's guaranteed service quality and FLSP's obedience behavior can reach the upper limit (or lower limit). Second, the information symmetry creates a win–win situation iff the penalty cost to the FLSP is moderate and the demand is incompletely revealed. Third, demand updating relaxes the condition for the LSI's service quality guarantee reaching to the upper limit. For FLSP, when the penalty cost is moderate, the demand updating makes FLSP less obedient in case that the demand is completely revealed and more obedient when the demand is incompletely revealed. [ABSTRACT FROM AUTHOR]

The widespread outbreak of a new Coronavirus (COVID-19) strain has reminded the world of the destructive effects of pandemic and epidemic diseases. Pandemic outbreaks such as COVID-19 are considered a type of risk to supply chains (SCs) affecting SC performance. Healthcare SC performance can be assessed using advanced Management Science (MS) and Operations Research (OR) approaches to improve the efficiency of existing healthcare systems when confronted by pandemic outbreaks such as COVID-19 and Influenza. This paper intends to develop a novel network range directional measure (RDM) approach for evaluating the sustainability and resilience of healthcare SCs in response to the COVID-19 pandemic outbreak. First, we propose a non-radial network RDM method in the presence of negative data. Then, the model is extended to deal with the different types of data such as ratio, integer, undesirable, and zero in efficiency measurement of sustainable and resilient healthcare SCs. To mitigate conditions of uncertainty in performance evaluation results, we use chance-constrained programming (CCP) for the developed model. The proposed approach suggests how to improve the efficiency of healthcare SCs. We present a case study, along with managerial implications, demonstrating the applicability and usefulness of the proposed model. The results show how well our proposed model can assess the sustainability and resilience of healthcare supply chains in the presence of dissimilar types of data and how, under different conditions, the efficiency of decision-making units (DMUs) changes. [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]

Distributed Ledger Technology (DLT) is highly applicable in various fields, especially the supply chain in many sectors. Against limited empirical evidence, this paper analyzes the relations between the Kensho Distributed Ledger Technology Index and stock indices of 12 sectors, including communication services, consumer discretionary, consumer staples, energy, health care, financials, industrials, information technology, materials, utilities, and real estate, and ESG by employing the quantile coherency and dynamic connectedness techniques. Our results reveal that the quantile coherency between the DLT stock index and the sectoral stock indices in almost all cases is significant and positive. The positive co-movement tends to be stronger in the longer terms and as we move from the lower to the higher quantiles, implying that they are more strongly connected in the long term and during the bearish market condition. Moreover, the dynamic connectedness indicates that the DLT stocks and the sectoral stocks are highly connected, with the former being a net transmitter of spillover shocks. The spillovers are also time-varying, and the results significantly corroborate those of the quantiles coherency methods. Among other relevant implications, DLT can be an important factor in the development and enhancement of these sectors. [ABSTRACT FROM AUTHOR]

Supply chains (SCs) are susceptible to risks because of their dynamic and complex nature. Big data analytics (BDA) through blockchain technology (BCT) can significantly contribute to managing SC risks. However, to date, the combined effect of BDA-BCT for SC risks has not been investigated extensively in the literature. This paper aims to identify the risk factors of the BDA-BCT initiative for Indian manufacturing organisations. Through the literature and experts' judgments, sixteen risk factors were identified. Data was collected from machine tool, automobile component, and electrical manufacturing organisations. Further interrelations between risk factors were evaluated using the grey DEMATEL approach. The results show that 'supply chain visibility risks', 'infrastructure and development costs', 'demand forecasting and sensing risks', 'data privacy and security risks', 'policy and legality related risks', and 'supply chain resilience' were identified as common factors in the adoption of BDA-BCT practices by the three organisations. The cause-effect relationship between risk factors can assist managers, suppliers, service providers, and policymakers in the significant adoption of BDA-BCT in the context of manufacturing organisations. The study provides a novel way to utilise BDA-BCT in minimising supply chain risks. Limitations of the study are that it was conducted only for Indian organizations. In the future, the findings of the study can be validated through empirical analysis. [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]

In today's business, environment natural and manmade disasters like recent event (Covid 19) have increased the attention of practitioners and researchers to Supply chain vulnerability. Purpose of this paper is to investigate and prioritize the factors that are responsible for supply chain vulnerability. Extant literature review and interviews with the experts helped to extract 26 supply chain vulnerability factors. Further, the relative criticality of vulnerability factors is assessed by analytical hierarchy process (AHP). Critical part supplier; location of supplier; long supply chain lead times; Fixing process owners and mis-aligned incentives in supply chain are identified as the most critical factors among twenty-six vulnerability factors. Research concludes that not only long and complex supply chain but supply chain practices adopted by firms also increase supply chain vulnerability. Relative assessment of vulnerability factors enables professionals to take appropriate mitigation strategies to make the supply chains more robust. This research adds in building a model for vulnerability factors that are internal to supply chain & controllable. [ABSTRACT FROM AUTHOR]