Three-tier Supply Chain Research Articles

Optimizing carbon emission reduction strategies in power batteries: Ensuring compliance with the EU battery regulation's carbon labeling initiatives

Reducing carbon emissions from power batteries is essential for the low-carbon development of electric vehicles (EVs). In response to the carbon labeling requirements of the EU battery regulation, this study developed a three-tiered supply chain model incorporating the battery material supplier, the power battery manufacturer, and the EV company. Using Stackelberg game theory, the research evaluated four carbon emission reduction strategies and analyzed the impact of consumer environmental awareness on carbon emissions. The results reveal that for batteries with lower initial carbon footprints, increased consumer environmental awareness is associated with a reduction in carbon emissions. For batteries with higher initial carbon footprints, the relationship between consumer environmental awareness and carbon emissions is more complex. Below a certain threshold, higher environmental awareness leads to carbon emission reduction; however, beyond this threshold, increased environmental awareness can elevate carbon emissions. Moreover, under low consumer environmental awareness, a strategy of comprehensive collaboration among all supply chain tiers yields the highest economic benefits, albeit with higher emissions. As environmental awareness rises, the strategy where the material supplier independently reduces emissions and the battery manufacturer and EV company collaborate on emission reductions emerges as the most effective, striking an optimal balance between economic and environmental interests.

A multinational firm’s global manufacturing location and outsourcing strategies

Due to rising labor costs in China and trade friction, many multinational firms (MNFs) consider moving manufacturing outside China to Southeast Asian Countries. Based on observations in real world, we build a three-tier supply chain model consisting of one component supplier, two contract manufacturers (CMs), an MNF, and a local original equipment manufacturer (OEM). The MNF monopolizes the market in country 1 (e.g., U.S.), but competes in country 2 (e.g., China) with the local OEM. The component supplier and one CM are located in country 2, and the other CM is located in country 3 (e.g., a country in Southeast Asia). We investigate the MNF’s global manufacturing location and procurement outsourcing strategies with considerations of tariffs and market environments. Currently, the MNF outsources its manufacturing to the CM in country 2, and decides whether to continue the cooperation with the current CM or develop a new CM in country 3. The MNF also considers whether to outsource its component procurement to the corresponding CM. Our study reveals that the MNF’s optimal strategy depends on the relative market sizes, the fixed cost of developing a new CM, as well as the manufacturing cost and tariff disadvantages in country 2. Interestingly, we find that the tariff disadvantage in country 2 does not always motivate the MNF to cooperate with the CM in country 3. Instead, an appropriate tariff may be beneficial to the MNF that manufactures in country 2. In addition, the MNF’s preferred procurement strategy is related to its manufacturing location. When cooperating with the CM in country 2, the MNF would switch from direct procurement to outsourced procurement as the market size of country 1 increases.

Stochastic differential game of joint emission reduction in the supply chain based on CSR and carbon cap-and-trade mechanism

This paper considers both carbon emission reduction and corporate social responsibility (CSR) goodwill as endogenous variables in the joint emission reduction process of the supply chain system. The joint emission reduction strategy of the three-tier supply chain system is examined from a long-term perspective utilizing stochastic differential game models. Three models, namely the cooperative game, the Nash non-cooperative game, and the Stackelberg master–slave game, are developed to analyse and compare the equilibrium strategies under each model. The results indicate that the manufacturer-led Stackelberg master–slave game can achieve the Pareto improvement in the profits of the supplier, manufacturer, retailer, and the entire supply chain system.

Retraction Note: Three-tier supply chain on temperature control for fresh agricultural products using new differential game model under two decision-making situations

Retraction Note: Three-tier supply chain on temperature control for fresh agricultural products using new differential game model under two decision-making situations

Supply chain network design

Goal: This study aims to minimize the total cost of a supply chain network and determine the optimal product flow under demand uncertainty. Design / Methodology / Approach: A mathematical model is presented to minimize the total supply chain cost by identifying the optimal facility locations and product flows. The applicability of the proposed model is evaluated through a real-life case study of a multinational sporting goods retailer with sensitivity analysis. Moreover, Monte Carlo simulation is used to capture the demand uncertainty and test the robustness of the model. Results: The minimized cost is achieved with optimal facility locations and product flows. The optimal result shows a 3% reduction in the total cost, making it the most robust solution under demand uncertainty. Limitations of the investigation: The proposed model is only applicable to a single-commodity supply chain network. In addition, the cost components of the network are limited to facility costs and transportation costs, disregarding the other cost components. Practical implications: This research demonstrates a methodology that can be used as a decision support system by managers to make strategic and tactical decisions in a supply chain network when demand is uncertain. Originality / Value: The MILP and simulation techniques used together to construct a three-tiered supply chain under uncertainty receive little attention in the literature. In addition to developing a novel three-echelon MILP model, this research makes use of a real-world case study to illustrate the methodology's performance in the context of demand uncertainty through simulation.

Coordination and optimization decision of assembly building supply chain under supply disruption risk

Assembly buildings, in the context of the low-carbon transformation of the construction industry, achieve superior outcomes in terms of carbon emission reduction, enhancement of building uniformity, and optimization of resource utilization as compared to traditional buildings. However, the supply chain for assembly building is marked by a significant susceptibility to risk and a need for timely fulfillment of requirements. This paper examines the risk of disruption and capacity limitations in the assembly building supply chain resulting from supply disruptions. It establishes a three-tier supply chain for assembly buildings, including primary component suppliers, backup suppliers, assembly manufacturers, and retailers. The study compares the optimal decision-making and coordination strategies of the supply chain members under centralized, decentralized, and joint agreements. The supply chain dual-source procurement decision coordination model is constructed by incorporating capacity constraints and analyzing the effects of supply disruption probability, repurchase coefficient, revenue sharing coefficient, cost, and other parameters on the expected profits of the supply chain members using arithmetic simulation. Research has indicated that when the likelihood of a disturbance occurring rises, the anticipated financial gain for the main provider decreases, while the predicted financial gain for the secondary supplier increases. The implementation of a collaborative agreement between the assembly maker and the parts backup provider would result in much greater anticipated profits compared to the decentralized decision-making approach. The impact of the revenue sharing coefficient on the predicted earnings of retailers and assembly manufacturers is more significant compared to the repurchase coefficient. The selection bias between NA and NB techniques under capacity constraints mostly arises from the assertiveness of the wholesale asking prices of inexpensive component suppliers, leading assembly manufacturers to increasingly prefer the NA option. This paper's research successfully achieves the contractual coordination of the assembly building supply chain, enhances the resilience of the assembly building supply chain, and promotes the long-term sustainable development of the assembly building supply chain.

Revenue-sharing contract in a three-tier online supply chain under EB platform financing

This work discusses a three-tier supply chain finance system (SCFS) composed of a supplier, an electronic business (EB) platform and a financially distressed retailer, where the EB platform acts as both a seller and a financier. We build a multi-tier game model under revenue-sharing contract (RSC) and analyze the operational strategies for all members. We further examine how the commission rate influences the equilibrium outcomes and identify the coordination conditions. Finally, we discuss a modified revenue-sharing contract (MRSC) and conduct a comparative analysis between RSC and MRSC.

Manufacturer invasion and online sales mode strategy considering the level of service quality.

This study investigates the decision process of own-brand intrusion by contract manufacturers and their selection of invasion sales modes under the consideration of service quality disparities between brand manufacturers and contract manufacturers. Specifically, the study constructs a three-tier supply chain system comprising a brand manufacturer, a contract manufacturer, and an e-commerce platform. The equilibrium profits under different sales mode combinations are determined by using reverse induction methodology, and the optimal sales mode combinations are analyzed and compared. The study reveals that the decision process of contract manufacturers' own-brand invasion depends on the potential market demand. Furthermore, when brand manufacturers adopt the reselling mode, the service quality level does not affect the decision process of invasion sales modes. However, when brand manufacturers adopt the agency mode, contract manufacturers with low service quality levels are more suitable for invasion through the agency mode, whereas contract manufacturers with high service quality levels are better suited for invasion through the reselling mode. Additionally, for the equilibrium sales mode combination among members of the supply chain, it is observed that with lower commission rates, both brand manufacturers and contract manufacturers choose the agency mode, while with higher commission rates, both choose the reselling mode. When commission rates are moderate, brand manufacturers prefer the agency mode, whereas contract manufacturers prefer the reselling mode.

Effect of Guided Delegation and Information Proximity on Multitier Responsible Sourcing

Problem definition: Guided delegation, a practice in which companies provide guidelines when delegating supplier management to tier 1 firms, is a common practice in managing complex supply chains. We study the benefits and risks of this approach in a three-tier supply chain setting consisting of a buying firm, a tier 1 contract manufacturer, and tier 2 suppliers, where responsibility risk stems from the tier 2 suppliers. We analyze the buyer’s profit and the supply chain’s responsibility risk under a guided-delegation model, in which the buyer specifies an authorized tier 2 supplier for the tier 1 manufacturer as a guideline and may audit the tier 1 firm for compliance. We compare this model with a full-delegation model, in which the buyer fully delegates tier 2 supplier selection to the tier 1 firm. Methodology/results: We formulate a Stackelberg game for the buyer’s contract design problem. We show that guided delegation does not always yield its expected results of lower supply chain risk and greater buyer profit. In instances where compliance auditing is financially more attractive to the buyer than paying a premium for tier 1’s responsible sourcing, guided delegation can result in higher profit but increased risk because compliance auditing cannot completely eliminate the risk. Additionally, when tier 1 anticipates buyer audits and demands higher wholesale prices to offset potential penalties, guided delegation may lead to decreased risk but lower profit for the buyer. Our analysis shows that delegating audit responsibilities to tier 1 often does not improve the buyer’s profit, and in situations where it does, it invariably raises the supply chain risk. Managerial implications: Our research identifies the potential downsides of guided delegation, offering insight for external stakeholders on where to focus efforts to avoid these pitfalls. It suggests that the intended benefits of guided delegation can only be realized when paired with compliance auditing. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2020.0446 .

Revealing the hidden potentials of Internet of Things (IoT) - An integrated approach using agent-based modelling and system dynamics to assess sustainable supply chain performance

The Internet of Things (IoT) brings new opportunities for creating intelligent and streamlined supply chains that have better environmental and cost performance as compared to conventional ones. In this paper, we quantify such improvements for a specific logistics chain case. To support the inventory of cost and emission data, we utilize system dynamics (SD) and agent-based modeling (AB) to define the structure of the two logistical systems, simulating and estimating differences in e.g., required storage levels, efficiency of transport, etc. In particular, we assess the difference in carbon emissions, cost, and market performance of a battery delivery chain in the delivery process between a two-tier IoT-supported supply chain (users are served by an IoT retailer directly connected to the producer) and a conventional three-tier supply chain (include an additional wholesaler to connect retailer and producer). The results demonstrate that IoT supply chains have significant advantages in minimizing average product storage and shipment fluctuations. IoT suppliers can estimate market demand to adjust production and transportation strategies for new orders. Consequently, the overall profitability of the IoT supply chain increases by more than 30%. Heating and lighting emissions in the storage process and direct emissions in transportation per functional unit (one unit of a Li-ion cell module) are reduced by 60%–70% under middle- and low-demand scenarios, and by at least 50% under high-demand scenario. However, the increasing use and higher loading rates of heavy trucks will weaken the advantages of IoT. Moreover, IoT products occupies a 10% lower market share compared to conventional ones under the same pricing strategy but achieves similar market share under the same value-added strategy.

Multi-Layer 5G Network Slicing with UAVs: An Optimization Model

In this paper, we present a network-based optimization model describing a closed-loop supply chain for the provision of 5G network slices on demand to users and devices on the ground. The three-tier supply chain network consists of a fleet of pre-existing UAVs, to which others can be added, managed by a fleet of UAV controllers, whose purpose is to perform services requested by users and devices on the ground. The aim of this paper is to provide a constrained optimization problem through which the providers’ profits are maximized, determining the global optimal distributions of request flows, the global optimal distributions of executed services and the optimal reliability level of pre-existing UAVs of the fleet. We also derive the associated Variational inequality formulation of the problem and, finally, a numerical simulation is performed to validate the effectiveness of the model.

Brand-Owners’ Exclusive Channel Strategies in Multitier Supply Chains: Effect of Contract Unobservability

In multitier supply chains, brand-owners often form exclusive deals with downstream retailers or upstream suppliers. Therefore, the selection of exclusive channel strategies becomes a critical decision for brand owners, resulting in three typical structures: a flexible structure, an exclusive retailing-channel structure, and an exclusive purchasing-channel structure. This paper contributes to the literature by formulating these three representative channel structures in a three-tier supply chain. Both observable and unobservable contracts are considered in each structure. We build game-theoretical models and derive the equilibrium outcomes under observable and unobservable contracts. We find that the exclusive retailing channel is more beneficial for brand-owners, regardless of whether the contracts are observable or unobservable. Additionally, the exclusive retailing channel benefits the entire supply chain more than the exclusive purchasing channel when the level of channel substitutability is low (high) under contract observability (unobservability). With regard to the effect of contract unobservability, we find that it can benefit brand-owners when the level of channel substitutability is low, but it can harm them when the level of channel substitutability is high. Furthermore, we explore the effects of channel substitutability and demonstrate that brand-owners’ performance can be positively and negatively affected by the channel substitutability under contract unobservability. Our findings provide operational strategies for brand-owners to form exclusive channels in a multitier supply chain.

A multi-objective stochastic programming approach with untrusted suppliers for green supply chain design by uncertain demand, shortage, and transportation costs

In recent decades, people are paying more attention to protecting the environment and biological resources. One of the most important issues of environmental pollution is air pollution, with production and transportation contributing a significant number of emissions. Considering the various warnings about the excessive increase in the amount of carbon dioxide on the planet, it is necessary to investigate the solutions to reduce the emission of carbon dioxide. On the other hand, in the production cycle, providing more comprehensive models and finding more optimal designs will play a significant role in reducing energy consumption and increasing profitability. Models with the most uncertain parameters are more practical and closer to the real world. In this paper, we consider a multi-objective stochastic programming approach for green supply chain design under uncertainty. Demands, supplies, processing, transportation, shortage, and capacity expansion costs are all considered uncertain parameters. At the same time, environmental approaches to reduce air pollution, (specifically reducing carbon dioxide emissions), are presented. Our multi-objective model includes the minimization of the sum of the total cost, the minimization of the variance of the total cost, the minimization of the financial risk or the probability of not meeting a certain budget, and the minimization of the amount of pollution consequent of production and transportation machines. In the following case study, a three-tier supply chain with four suppliers, four production centers, and three product distribution centers with uncertain demand, suppliers, processing, transportation, cost shortages, and capacity development are examined. To solve the model, two meta-heuristic algorithms (multi-objective genetics with faulty sorting and particle swarming) have been developed. The computational results and optimal designs of the supply set were obtained after the implementation of the algorithms, and finally, by performing Sensitivity Analysis and statistical tests, showed that there are two algorithms with good performance and in most cases, the Non-dominated Sorting Genetic Algorithm (NSGA-II) is superior to the Multi-Objective Particle Swarm Optimization (MOPSO).

Financing the Three-Tier Supply Chain: Advance Payment vs. Blockchain-Enabled Financing Mode

Supply chain finance has shown remarkable results in alleviating the financial constraints of small and medium-sized enterprises. However, most studies have concentrated on the two-tier supply chain while ignoring the financing issues of the deep-tier supply chain. This study introduced the blockchain-enabled financing mode now utilized in the manufacturing industry and constructed a three-tier agricultural supply chain considering the farmer’s financial constraints. The main contributions of this article are (1) presenting the blockchain-enabled financing mode in the three-tier agricultural supply chain and (2) investigating supply chain decision-making in the three-tier supply chain when the tier-2 supplier is financially constrained, comparing advance payment and the blockchain-enabled financing mode. Relevant parameter estimations were realized using the data of the last ten years, and numerical analyses were conducted. The results show that when the farmer’s bank’s financing capability exceeds the acquirer’s, the farmer is motivated to select the blockchain-enabled financing mode. However, a win-win situation among the three-tier supply chain is only achievable when the transmission-fee rate falls within a particular range. In addition, if government agencies wish to promote blockchain technology by subsidizing blockchain-enabled financing, they might support the farmer in obtaining a bank loan at a cheaper interest rate. All members of the supply chain would benefit from this.

Study on sustainable development of pharmaceutical health industry under ecological coordination.

Particularly in the post-pandemic period, where public health emergencies offer a greater risk of supply disruptions, the operational hazards of pharmaceutical supply chains are uncertain. One of the main concerns for businesses is how to handle the risk of supply disruption and take the necessary precautions to lower the chance of loss. Pharmaceutical raw material suppliers, pharmaceutical manufacturers and medical institutions constitute a complete three-tiered supply chain. On the basis of this, in Materials and methods part, a share contract based on buyback proceeds is created as a result, and a combination contract based on centralized decision-making and decentralized decision-making is employed to maximize the order volume of pharmaceutical supply chain participants. An out-of-stock cost pharmaceutical supply chain model is created, and a related solution is provided and measurable examples. In Results and discussion part, to confirm the accuracy of the model and algorithm, numerical examples are employed. Buyback prices and order volumes were subjected to sensitivity analysis, and discussion is had over how various parameters affect a model's performance. Due to supply disruptions, the study's findings show that there is "double sourcing" between upstream pharmaceutical raw materials and downstream major suppliers, necessitating the establishment of a supply chain with numerous standby suppliers. At the same time, modifying the contract parameters can improve the supply motivation of backup suppliers and guarantee the profitability of downstream medical institutions.

Manufacturing and procurement outsourcing strategies of competing original equipment manufacturers

To cope with market competition and focus on core competence, many Original Equipment Manufacturers (OEMs) choose to outsource their product manufacturing and/or component procurement functions to Contract Manufactures (CMs). In this paper, we aim to investigate the strategic interplay between manufacturing outsourcing and procurement outsourcing in a three-tier supply chain consisting of one component supplier, one common CM, and two competing OEMs. Each OEM has four outsourcing strategies: no outsourcing, “manufacturing-only” outsourcing, “procurement-only” outsourcing, and “manufacturing + procurement” outsourcing. We build a two-stage game model, where two OEMs simultaneously choose their outsourcing strategies in the first stage; in the second stage, the CM and two OEMs make wholesale prices and quantity decisions based on the outsourcing structure formed in the first stage. We find that OEMs’ equilibrium outsourcing strategies depend on the discount rate of component price and the fixed investment cost of manufacturing. Our analysis also reveals the strategic relationship between manufacturing outsourcing and procurement outsourcing: OEMs would not outsource procurement until the product manufacturing is outsourced. Moreover, there may exist Prisoners’ Dilemma, where both OEMs earn higher profits when they choose “manufacturing + procurement” outsourcing, but neither OEM is willing to outsource procurement. Interestingly, we show that OEMs’ and CM’s profits may decrease with the discount rate and market potential, but increase in the fixed investment cost.

Impact of Traceability Technology Adoption in Food Supply Chain Networks

Improving traceability in food supply chains has been a big part of ongoing effort to reduce contamination risks and food waste. Recent technology advancement such as blockchain technology has propelled innovative retailers to promote food traceability system adoption in their supply chains. We develop a three-tier supply chain model with multiple upstream (tier 2) suppliers to investigate how traceability technology adoption affects incentives of supply chain members and whether and how its anticipated benefits can be realized. We find that full traceability brings direct revenue benefit to every supply chain member by saving uncontaminated food from disposal (pure traceability effect) but also leaves each tier of the supply chain vulnerable to its immediate downstream buyer’s exploitation through strategically lowering the purchasing price (strategic pricing effect). The interplay of the two effects may result in some of the supply chain members (even the retailer) being worse off with traceability adoption and the system being exposed to higher contamination risk; the latter is because of the weakened upstream supplier’s incentive to exert contamination risk-reduction effort. Moreover, we find that the supply chain network structure also influences the benefit distribution of traceability adoption: The retailer always benefits from traceability adoption in network structures where the tier 1 supplier’s strategic pricing power is eliminated or weakened; all supply chain members benefit from traceability adoption in a network with a large number of tier 2 suppliers. Finally, we show that alternative risk-mitigation schemes such as tier 2 coordination can diminish the value of traceability adoption, and partial traceability enabled by tier 1 product inspection can be more beneficial to the retailer than full traceability. This paper was accepted by Victor Martínez-de-Albéniz, operations management. Supplemental Material: The online appendices are available at https://doi.org/10.1287/mnsc.2022.4440 .

Blockchain-Enabled Deep-Tier Supply Chain Finance

Problem definition: For many supply chains, deep-tier suppliers, due to their small size and lack of access to capital, are most vulnerable to disruptions. We study the use of advance payment (AP) as a financing instrument in a multitier supply chain to mitigate the supply disruption risk in a traditional system (with limited visibility) and a blockchain-enabled system (with perfect visibility). The main goal of this paper is to shed light on how blockchain adoption impacts agents’ operational and financial decisions as well as profit levels in a multitier supply chain. Academic/practical relevance: Traditionally, because of the limited visibility in the deep tiers, powerful downstream manufacturers’ financing schemes offered to their immediate upstream suppliers are not effective in instilling capital into the deep tiers. Advancements in blockchain technology improve the supply chain visibility and enable the manufacturer to better devise deep-tier financing to improve supply chain resilience. Methodology: We develop a three-tier supply chain model and take a game-theoretic approach to compare how blockchain-enabled deep-tier financing schemes affect a financially constrained supply chain’s optimal risk-mitigation and financial strategies. Results: We find that although improved visibility via blockchain adoption can help the manufacturer make informed supply chain financing decisions, whether it can benefit all supply chain members depends on the financing schemes in use. Blockchain-enabled delegate financing increases risk-mitigation investments and benefits all three tiers of the supply chain only when the tier 2 supplier is severely capital-constrained with the working capital below a threshold. Because delegate financing endows the intermediary tier 1 supplier with leverage over the manufacturer, the inefficiency inhibits an all-win outcome when the tier 2 supplier is not severely capital-constrained. Blockchain-enabled cross-tier direct financing exhibits a compelling performance as it always leads to win-win-win outcomes (and is thus ubiquitously implementable) regardless of the suppliers’ working capital profile. Managerial implications: Our insights help firms assess opportunities and challenges associated with enhancing supply chain visibility via blockchain adoption.

RETRACTED ARTICLE: Three-tier supply chain on temperature control for fresh agricultural products using new differential game model under two decision-making situations

RETRACTED ARTICLE: Three-tier supply chain on temperature control for fresh agricultural products using new differential game model under two decision-making situations

Research on Corporate Social Responsibility Coordination of Three-Tier Supply Chain Based on Stochastic Differential Game.

In the Internet era, consumers prefer products with the attributes of social responsibility. Supply chain enterprises strengthen corporate social responsibility (CSR) management for their own development. To improve CSR throughout the supply chain, it requires coordination and cooperation among the members of the supply chain. In this paper, we consider a three-tier supply chain system consisting of a supplier, a manufacturer, and a retailer and use stochastic differential game to study the CSR coordination of the supply chain. The following indicators are investigated under four decision situations, such as the optimal level of CSR effort for the supply chain members, the optimal value of profit for the supply chain members and the supply chain system, and the expectation and variance of CSR goodwill. Some important results are obtained. (i) Compared with decentralized decision-making, the optimal level of CSR effort increases for the supplier and the manufacturer under local alliance decision-making without cost sharing, whereas the optimal level of CSR effort remains unchanged for the retailer. (ii) Compared with local alliance decision-making without cost sharing, the optimal level of CSR effort remains unchanged for the supplier and the manufacturer under local alliance decision-making with cost sharing. When the sum of the marginal profit for the supplier and the manufacturer is greater than half of the marginal profit for the retailer, the optimal level of CSR effort increases for the retailer. (iii) Compared with local alliance decision-making with cost sharing, the optimal level of CSR effort increases for the supply chain members under overall alliance decision-making. (iv) From decentralized decision-making to local alliance decision-making without cost sharing, to local alliance decision-making with cost sharing, and then to overall alliance decision-making, the optimal value of profit increases for the supply chain members and the supply chain system. Also, the expectation and variance of CSR goodwill increase.