Three-level Supply Chain Research Articles

Bi-objective optimization modeling of a three-level supply chain in production planning and scheduling considering price-dependent demand: a case study of a soap factory

Bi-objective optimization modeling of a three-level supply chain in production planning and scheduling considering price-dependent demand: a case study of a soap factory

Coping with drug shortages: A study of government-enterprise option cooperation stockpiling strategies for drugs in shortage considering API surrogate stockpiling subsidies.

Drug shortage is a global problem, and the development of government-enterprise cooperative stockpiles of drugs in shortage, combining physical and production capacity, has become one of the most important means of coping with drug shortages. However, existing studies have tended to overlook the fact that shortages of Active Pharmaceutical Ingredients (APIs) have become an important constraint on production capacity stockpiling and that the lack of incentives and provisions for coordination of benefits have led to a double marginal effect of joint stockpiling by government and enterprises of drugs in shortage. Accordingly, this study introduced the option contract to the drug supply system composed of government and pharmaceutical enterprises and used the subsidy of API storage in lieu as an important initiative to incentivize the reserve of APIs, to construct a model of shortage drug reserve under the government's leadership. This study aims to improve the effect of government-enterprise joint stockpiling of drugs in shortage, which is of great theoretical and practical significance. According to the classification of production license types of pharmaceutical enterprises, this study established a three-level supply chain decentralized decision-making model consisting of the government, formulation enterprises, and API enterprises, and a two-level supply chain centralized decision-making model consisting of the government and API Formulation (API-F) integrated enterprises, respectively. By solving the inverse order derivation, the government-enterprise option cooperation conditions and optimal decision-making strategy were derived. The study results showed that: (i) The addition of enterprise API stockpiling mode can help the government conventional reserves, and enterprise production capacity reserves, broaden the way of drug reserves, and improve the effect of government-enterprise option cooperation; (ii) when the probability of drug shortages is high, the government should prefer the cooperation of API-F integrated enterprises, which is conducive to reducing intermediate links and government costs and improving the supply responsiveness to shortages of medicines; (iii) Setting appropriate government subsidies for API storage can incentivize enterprises to stockpile APIs and improve drug production capacity and physical supply response capability. This study took the problem of socialized stockpiling of drugs in shortage as an entry point and explored the problems and solution strategies in the government-enterprise cooperative stockpiling of drugs in shortage, which not only made some theoretical contributions to the application of options contract in the government-enterprise cooperative stockpiling of drugs in shortage but also provided new ideas and theoretical basis for the improvement of the stockpiling work of drugs in shortage.

A location-inventory-pricing model for a three-level supply chain distribution network

This article applies competition-based pricing method to a location-inventory-pricing problem, something which had not yet been investigated as of this study. It reveals that examining the three problems of location, inventory and pricing in an integrated and simultaneous manner can be the best approach to optimize the supply chain (SC) and increase the profitability of its companies. The investigated three-level SC distribution network model includes one supplier, several distribution centers (DCs), and several customers. The model is structured in form of a mixed integer nonlinear programming to maximize the long-term average profit of the distribution network. It considers constraints of inventory capacity along with continuous review inventory policy in each open DC. For its DCs’ retail price determination, two competing pricing approaches of higher than and lower than the average price of competitors have been used. The approach has been investigated on several potential DCs and customers and its numerical results show that retail price from the DCs to the customers is dependent on the average price of the market and its fluctuations. The major finding of this research is the fact that the type of demand function can have a substantial effect on the obtained results in the location-inventory-pricing model and greatly influence the amount of the profit of each company. Its applied strategy along with innovative competition-based pricing approach and projection of customers’ demand via linear and exponential functions show how companies can increase their profit through price adjustment and demand projection.

A robust multi-objective MIP model to optimize the supply chain of steel industry taking into account the sustainability approach

The construction of a steel production plant in the countries provided that they benefit from the required raw materials, and infrastructural facilities such as roads, power plants, water, etc. are considered an economic advantage. If these prerequisites exist, the next challenge in building a steel plant is to determine the number, optimal location, and flow between the supplier and the plant and also between the plant and the consumer market. On the other hand, there is always a serious challenge for environmental issues and the impact on pastures and wildlife due to the polluting nature of this industry. In addition, considering the situation in which the amount of consumption under disruptions makes the supply chain of steel inefficient, it is necessary to design a model that is close to the real world. In this study, to obtain the optimum number and location of steel factories, material flow, and considering the sustainability approach, we design a robust three-level supply chain network for the steel industry, taking into account the sustainability approach including three objective functions. The first objective function aims to minimize logistics and production costs, the second objective function maximizes the quality score of the final selected location, and the third objective function is proposed to maximize the efficiency of product production lines. In this study, a scenario-based robust optimization model is applied to overcome the uncertainty of the proposed model. Furthermore, to incorporate the score of location into the third objective function, a decision-making method based on the sustainability approach is used. Finally, the proposed model is validated within steel industry in Iran as a case study.

Using common redundancy components for suppliers in a supply chain network design problem considering energy costs and environmental effects

Improving the reliability of factories and suppliers through appropriate allocation of redundancy components is crucial in responding to customer demand. However, if individual factories independently buy and allocate redundancy components, huge investments will be required. To optimize the reliability level and costs of the supply chain network, the present study allocates these components to suppliers based on customer demand. While allocating redundancy components to factories improves the chain's reliability, it increases energy consumption and greenhouse gas emissions. Therefore, a balance between cost, reliability, and pollution needs to be established. The study considers a three-level supply chain, including the supplier (factories), distributor, and retailer, with stochastic and normally distributed demand assumed for each retailer. To address demand fluctuations, the risk pooling effect is implemented. As the problem belongs to the class of NP-hard problems, the study develops three multi-objective meta-heuristic algorithms, namely Non-dominated Sorting Genetic Algorithm II (NSGAII), Archived Multi-Objective Simulated Annealing (AMOSA), and Multi-Objective Artificial Bee Colony (MOABC) to solve it. The performance of these algorithms is evaluated using the results of the complete enumeration method. The comparison results based on six multi-objective performance metrics show that the MOABC algorithm has better performance in finding high-quality solutions in less time, while the NSGAII algorithm provides more diverse Pareto optimal solutions.

A Fuzzy Bi-objective Mathematical Model for Perishable Medical Goods Supply Chain Network Considering Crisis Situations: An Empirical Study.

In case of crisis, the salvation of injuries depends on the timely provision of medical goods, relief supplies, and equipment. The aim of this study is to present a mathematical model for the supply chain network of perishable medical goods in crisis situation considering the uncertain environment. In this paper, a three-level supply chain including suppliers, intermediate warehouses, and final customers is developed for perishable medical items. The uncertainty of customer demand for service and the spent time in the intermediate warehouses are considered using the exponential distribution functions. Also, it is assumed that the life-cycle of perishable medical goods follow the Weibull distribution function. The model attempts to minimize the total costs of the supply chain and total presence time of perishable items in the whole chain. The LP-Metric method is employed for solving small-sized problems. Due to the NP-Hardness of the problem, the modified Multi-objective Particle Swarm Optimization (MOPSO) and Non-dominated Sorting Genetic Algorithm (NSGA-II) are utilized as 2 well-known and efficient meta-heuristic algorithms for solving large-sized problems. The findings indicate that the meta-heuristic algorithms are efficient in achieving close to the optimal solution for large-size problems in a reasonable time. Also, the results demonstrate that NSGA-II outperforms MOPSO in terms of the high quality solution. Finally, the applicability of the model to real-world problems is demonstrated using a real case study. This paper can assist the planners and decision-makers of perishable drugs supply chain networks in crisis conditions with on-time supplying and distributing the required emergency items.

Collaborative Green Innovation of Livestock Product Three-Level Supply Chain Traceability System: A Value Co-Creation Perspective

To enhance the health and stability of livestock product supply chains, it is imperative to augment product sustainability and satisfy food safety requirements through collaborative green innovation. Digital traceability technology amalgamates information and resources from stakeholders in the supply chain, facilitating knowledge sharing and product tracking throughout the entire process to purify the supply chain environment. Augmenting communication and trust among supply chains paves the way for green innovation, thereby yielding value-added benefits. Consequently, this paper formulates a simulation model for manufacturers, retailers, and consumers—three pivotal stakeholders in the traceability process of livestock products—from a value co-creation standpoint. It also incorporates a contract penalty mechanism to probe the collaborative green innovation process among various entities involved in the livestock product supply chain. System simulation is employed to emulate the evolution path of collaborative green innovation in the livestock product supply chain under the value co-creation perspective. Subsequently, a stepwise penalty mechanism, green incentive mechanism, and fair distribution mechanism are proposed for stakeholders to actualize collaborative green innovation and value creation. The findings reveal that: (1) the collaborative green behavior between suppliers, retailers, and consumers is influenced by factors such as value co-creation excess returns, innovative technology costs like traceability, cost sharing among stakeholders, and a certain threshold of government penalties. (2) A balanced distribution of excess returns and cost-sharing among stakeholders fosters the evolution of a green collaborative state in the supply chain, thereby achieving sustainable development with value chain enhancement and ecological optimization.

Research on technological innovation and marketing publicity decision of green intelligent home appliance supply chain considering consumer subsidy and cost-sharing contract

Under the leadership of China’s “dual-carbon” policy, how to reduce energy consumption, reduce carbon emissions, and realize intelligent, low-carbon development has become a key issue faced by the home appliance industry. Studies have shown that green intelligent home appliances can save electricity and reduce carbon emissions. In the context of China’s “dual-carbon” goal, this study examines the technological innovation and marketing publicity decisions of the green intelligent home appliance supply chain considering the consumer subsidy and cost-sharing contract. By constructing a three-level supply chain model that includes home appliance manufacturers, retailers, and consumers, we use the Stackelberg game method to study the decision-making models under four scenarios with and without consumer subsidy and cost-sharing contract and consider the impact of consumers’ green intelligent preference, consumers’ green marketing sensitivity, consumer subsidy and cost-sharing contract on the supply chain optimal decision. Through model solving and further numerical simulation, the results show that 1) the increase of consumers’ green intelligent preference and consumers’ green marketing sensitivity can produce positive spillover effects and promote the improvement of home appliance manufacturers’ technological innovation efforts and retailers’ marketing publicity efforts; 2) consumer subsidy is always beneficial for the green intelligent development of the supply chain, which can effectively increase the total revenue of the supply chain; 3) the reasonable cost-sharing ratio can stimulate the enthusiasm of supply chain enterprises to increase technological innovation and marketing publicity investments and increase the total profit of the supply chain. However, the excessive cost-sharing ratio frustrates the enthusiasm of home appliance retailers to participate in the coordination, which results in a decline in the overall benefit of the supply chain; 4) by considering both consumer subsidy and cost-sharing contract, a reasonable level of consumer subsidy and cost-sharing ratio have a better incentive effect on the supply chain members than in the other three scenarios. This study can provide a broader reference for the green intelligent development of China’s home appliance industry, which plays an important role in the implementation of China’s “dual carbon” goal.

Effects of the carbon emission quota policy on the quality and sales of manufactured and remanufactured products

Low-carbon manufacturing is an inevitable way to achieve carbon neutrality. Further, implementing a carbon emission quota policy is an essential method for boosting the low-carbon transformation of the remanufacturing industry. Our study aims to improve the quality of remanufactured goods and promote the low-carbon, high-quality growth of the remanufacturing industry. Using a three-level supply chain comprising original equipment manufacturers (OEMs), independent remanufacturers (IRs), and retailers, we construct a game model with and without a government-implemented carbon emission quota policy. Subsequently, we examine the consequences of the carbon emission quota policy on product quality, sales, and price. We also determine the optimal range of carbon quota for governments to enforce carbon emission rewards and penalties to promote the low-carbon production of remanufacturing companies. By comparing the equilibrium results, we conclude that the carbon emission quota policy incentivizes IRs to upgrade the quality of remanufactured goods and expand production. Notably, when the carbon emission limit is less than the threshold, the policy significantly reduces the gross carbon emissions of OEMs and IRs. However, when the carbon emission limit is greater than the threshold, the effect on gross carbon emissions is negative. This study enriches the theoretical research on manufacturing and remanufacturing and provides decision support for governments to formulate a carbon emission quota policy. It also offers practical guidance for manufacturers and remanufacturers in making production decisions.

A hierarchical model for strategic and operational planning in blood transportation with drones.

Blood transportation is a critical aspect of the healthcare systems, ensuring whole blood and blood products are delivered to patients in a timely and efficient manner. However, transportation of blood and other medical supplies can be challenging, especially in urban areas with limited infrastructure and heavy traffic. Drones have become increasingly important in recent years as a means of delivering medical supplies, including blood, due to their ability to provide fast, reliable, and cost-effective transportation. This study proposes two mathematical programming models in the hierarchical structure to improve decision-making for strategic and operational planning in the blood supply chain network. The limited information available in strategic planning presents risks to the blood supply chain, making it imperative to address uncertainties. To tackle this challenge, a novel approach called Scenario-based Robust Bi-objective Optimization has been proposed. The first model employs this approach to efficiently handle demand uncertainty by simultaneously maximizing the covered demand and minimizing costs. The model is subsequently solved using the augmented ε-constraint method. The second model is a routing-scheduling operational model that aims to minimize the sum of operations time, taking into account time windows for blood collection centers and hospitals. The developed hierarchical model is implemented in a three-level supply chain of Tehran province under three crisis scenarios in different parts. The findings and analysis of this implementation suggest that it is beneficial to set up drone stations in cost-effective and central locations to avoid costly network design. Furthermore, utilizing the minimum number of feasible drones enhances operational time and results in cost savings and increased efficiency. Overall, this study highlights the potential of using drones for blood transportation in urban settings, which can have significant implications for improving the quality of healthcare delivery.

Collaboration and coordination strategies for a multi-level AI-enabled healthcare supply chain under disaster

ABSTRACT Artificial Intelligence (AI)-based applications have been rising across the healthcare supply chain. Successful AI implementation requires proper collaboration among healthcare supply chain members. However, high investment associated with AI innovation often impedes collaboration. In this context, disruption caused by the disasters like pandemics and epidemics can add more complexity. This issue has not received substantial scholarly attention. Here, we design a multi-level AI-enabled healthcare supply chain by incorporating a three-level supply chain structure with a healthcare product manufacturer, a distributor, and a procurement agency, where the manufacturer and distributor invest in AI innovation. Here, we adopt wholesale price (W) and cost-sharing (C) contracts-based mechanisms considering four scenarios WW, WC, CW, and CC, to devise the three-level AI-enabled healthcare supply chain members’ collaboration and coordination strategies with and without disruption. Adopting a Stackelberg game-theoretic approach, we determine the supply chain members’ optimal AI innovation efforts, prices, and profits for all scenarios. We demonstrate the dominance of one scenario over other for the supply chain members’ decisions and profits and propose a scenario ranking framework. We also investigate the impact of the disruption cost-sharing between the manufacturer and retailer, the disruption probabilities, and AI innovation success on the supply chain decisions

Vannamei (Litopenaeus vannamei) Frozen Shrimp Raw Material Inventory Management With Supply Chain Management Approach

Raw material inventory is one of the most expensive assets of the company, especially at national private companies in Banyuwangi is developing a frozen vannamei shrimp agro-industry with PND commercial products (Peeled and Devained). Companies often experience problems with losing sales profits if export demand tends to increase, because companies have not maximized their inventory management. So by using a three-level supply chain management approach, namely the level of finished products, the level of processing and the level of raw materials, it is important to ensure the availability of finished products at any time. Through this approach, the average amount of raw material needed for production of each PND product is PND 26/30 of 12,333.33 kg/month, 31/40 of 75,416.67 kg/month, 41/50. 28,750 kg/month, 51/60 42,250 kg/month, 61/70 21,083.33 kg/month, and 71/90 11,083.33 kg/month. so that the company's service level for PND finished products is above 100%, which is an average of 111,39%.

The Three-Level Supply Chain Finance Collaboration under Blockchain: Income Sharing with Shapley Value Cooperative Game

With the gradual and widespread application of blockchain technology in the supply chain, its characteristics can help solve the financing problem of MSMEs. To this end, this paper constructs a cooperative game model for suppliers, manufacturers and retailers in the case of a cross-level guarantee of order-to-factoring, studies the pricing strategy of supply chain finance members based on blockchain technology by adopting the Stackelberg primary-secondary game method, and makes a reasonable allocation of total supply chain revenue with the help of the Shapley value of the cooperative game. The study found that the adoption of blockchain can be effective in increasing the benefits to supply chain members and systems. The adoption of blockchain increases the blockchain costs but decreases the financing costs for the supplier. The Shapley value of the cooperative game is used to distribute the benefits, allowing for Pareto improvements in the benefits to supply chain members. In the next step, we will focus on examining the impact of risk assessment and the degree of information disclosure on supply chain finance with blockchain technology.

Designing an integrated blockchain-enabled supply chain network under uncertainty

With the development of communication infrastructure, the design of supply chains has changed significantly. Blockchain technology, as one of the most cutting-edge technologies, can promote transparency among members of the supply chain network. To the best of our knowledge, this is the first study that tries to develop a novel bi-objective optimization model to integrate the transparency resulting from the use of blockchain for designing a three-level supply chain network. The first objective function is to minimize total cost while the second objective function seeks to maximize transparency based on the application of blockchain technology. Moreover, it is worth noting that it is the first attempt to investigate the role of a blockchain model under stochastic conditions. The bi-objectiveness and stochastic nature of the proposed model are then treated using Fuzzy Goal Programming (FGP) and Chance-Constrained programming (CCP) approaches, respectively. To tackle the problem, an improved Branch and Efficiency (B&E) algorithm is developed by incorporating transparency along with cost and service. The impacts of blockchain exclusively through transparency (Case 1) or through transparency, cost, and benefits (Case 2) in Supply Chain Design (SCD) are compared. The results demonstrated that the first case has less computational complexity and better scalability, while the second case has more transparency, less congestion, and more security. As one of the main implications, supply chain managers who are focused on cost minimization as well as transparency maximization are advised to take into account the trade-off between featuring costs and benefits of blockchain technology.

Collaborative Innovation Strategy of Supply Chain in the Context of MCU Domestic Substitution : A Differential Game Analysis

The domestic substitution of the IC (the Integrated Circuit) industry improves economic efficiency and is significant in ensuring national security, which has gradually become an essential strategy for countries worldwide. Based on the background of domestic substitution of integrated circuits, we select a typical component Micro Controller Unit) as the research object, construct a three-level supply chain game model under different scenarios in a dynamic architecture, and analyze the game problem of collaborative innovation of the MCU supply chain. We fully consider the impact of factors such as time, cost and the innovation and collaborative innovation efforts of various supply chain members on the level of domestic substitution. Moreover, we put forward a two-part pricing + cost-sharing contract to achieve supply chain coordination. We found that: (1) Collaborative innovation of the supply chain in the centralized decision-making scenario achieves the highest level, followed by the cost-sharing scenario; (2) The two-part pricing + cost-sharing contract can help achieve supply chain coordination; (3) The trend of the MCU domestic substitution level with manufacturing cost is U-shaped, which means the increase of manufacturing cost may have a positive impact on the process of domestic substitution.

Agricultural insurance and power structure in a capital-constrained supply chain

This study focuses on an agricultural supply chain with a capital-constrained manufacturer, a bank and an insurer under three power structures: insurer-led Stackelberg (IS), bank-led Stackelberg (BS) and vertical Nash (VN). By establishing a two-level Stackelberg game, we examine the application condition and role of agricultural insurance under three channel structures and reveal the preferences of the supply chain and its participants for different channel structures. This study shows that, in either model, the manufacturer purchases agricultural insurance when the bank is highly loss-averse, but the probability of the manufacturer adopting agricultural insurance in the BS model is lower than that of the VN model but higher than that of the IS model. In these three models, the manufacturer’s application of agricultural insurance increases the profits of the manufacturer, bank and insurer but reduces supply chain efficiency. In addition, from the perspective of the profit level and profit share of supply chain participants, for the manufacturer, the VN model of the two-level supply chain power structure betters than the BS and IS models of the three-level supply chain power structure, but the BS model is superior to the IS model; for the bank and the insurer, the higher their leadership positions in which power structure model, the better the power structure model. From the perspective of the overall profit and efficiency of the agricultural supply chain, the model preference of the supply chain is the same as that of the manufacturer. The findings provide new theoretical insights for the application of agricultural insurance and power relationship in the agricultural supply chain.

Research on optimal supply decision of manufacturers considering futures purchase under deferred payment

Taking the three-level supply chain consisting of a single supplier, a manufacturer and a strong brand as the research object, the manufacturer's optimal supply decision model is constructed, which considers the futures purchase under the deferred payment of the brand, and it is proved that the optimal solution not only exists but also is unique. Then, the influence of parameter variation on the optimal ordering strategy was analyzed by numerical example simulation and sensitivity analysis. The results show that when the period of deferred payment to the manufacturer is extended and the price discount is strengthened, the manufacturer can purchase from the futures market to lock the price and make up for its income loss through the supplier's delayed payment. Production rate should also be controlled, too high or too low production rate will affect the manufacturer's production cycle.

Location-inventory-reliability optimisation problem in a multi-objective multi-period three-level supply chain network with stochastic demand

Location-inventory-reliability optimisation problem in a multi-objective multi-period three-level supply chain network with stochastic demand

Optimizing the Interaction Between Two Closed-Loop Supply Chains Based on Inverse Logistics Using the Game Theory Method

Abstract Over the past few years, attention to environmental problems, legal necessities, and economic advantages emerging from reproduction activities has attracted attention to reverse logistics activities in the form of a closed-loop supply chain, whether in industry or scientific research. The current study aims to model competitiveness and comparison between two closed-loop three-level supply chains, each of which includes a manufacturer, a retailer, and a third party to collect the products used by the customer, taking into account the concepts of game theory and the existence of aggregates. Moreover, a separate supplier for each chain is considered. In the forward supply chain, the manufacturer produces new products using new components or re-used products that have been collected from the consumer, then sells these products mainly to the retailer, and the retailer sells them. In the reverse chain, the collector provides the used products to the manufacturer after collection. The study utilized the definitions and concepts of game theory to model this closed loop chain as a Stackelberg game to obtain the optimal value of wholesale and retail price and the optimal value of the product return coefficient for the collector. Finally, the models based on some numerical examples are solved. Given the results, the remanufacturing costs have a significant role in making more profits for all members in such chains, and competitive chains should attempt to remanufacture the products at lower costs.

To Be or Not to Be? Strategic Analysis of Carbon Tax Guiding Manufacturers to Choose Low-Carbon Technology

This paper analyzes the environmental tax’s effect on manufacturers’ choice of low-carbon technology in competitive supply chains. The existing studies only consider a single oligopoly enterprise and ignore the competition between supply chains. Few papers study the manufacturer’s technology choice under the carbon tax policy in the competitive supply chains, especially investigating the factors influencing the technology choice, including the market volume, and technology carbon emission reduction efficiency because different industry sectors have their distinctive carbon emissions reduction efficiencies and facing the different market volume. The study adopts a game theoretical approach, including the three-level supply chain consisting of the regulator, the manufacturers, and the retailers. A high carbon tax does not always help firms choose low-carbon technology. However, the monotonous effect of the carbon tax on manufacturer technology selection is no longer valid if the market volume and the carbon-reducing efficiency are considered. When the market volume is large, the regulator can set a high carbon tax to induce the manufacturers to choose low-carbon technology. We identify cases where the manufacturers are caught in a prisoner’s dilemma. When the market volume is small, and the carbon-reducing efficiency is high, the competitive manufacturers adopt the common technology. However, if the regulator increases the carbon tax, the manufacturers acquire the differential technology strategic choice, which is the Pareto optimal. We also extend the base model to the imperfect substitutable Cournot model and the Bertrand model to check the robustness and find our main results still hold in these extensions.