Supply Chain Decisions Research Articles

Emission Reduction Decisions in Blockchain-Enabled Low-Carbon Supply Chains under Different Power Structures

With the global climate problem becoming increasingly severe, governments have adopted policies to encourage enterprises to invest in low-carbon technologies. However, the opacity of the carbon emission reduction process leads to incomplete consumer trust in low-carbon products as well as higher supply chain transaction costs. Based on this, this paper constructs Stackelberg game models with and without blockchain under different power structures and compares the impact of these models on low-carbon emission reduction decisions. The results show that: (1) blockchain does not necessarily improve enterprise profits and can only help enterprises maintain optimal profits within a certain range when the carbon emission cost is low; (2) when consumers’ environmental awareness is high, the blockchain can incentivize manufacturers to enhance carbon emission reduction, and it has an obvious promotional effect on retailers’ profits; and (3) the profit gap between enterprises in the supply chain is larger under different power structures, and the implementation of blockchain can coordinate profit distribution and narrow the gap between enterprises. Compared with the manufacturer-dominated model, the emission reduction in products is maximized under the retailer-dominated model. Our study provides theoretical support for the government to regulate greenhouse gas emissions as well as for the optimization of enterprises’ decision-making supported by blockchain.

Enabling explainable artificial intelligence capabilities in supply chain decision support making

Explainable artificial intelligence (XAI) has been instrumental in enabling the process of making informed decisions. The emergence of various supply chain (SC) platforms in modern times has altered the nature of SC interactions, resulting in a notable degree of uncertainty. This study aims to conduct a thorough analysis of the existing literature on decision support systems (DSSs) and their incorporation of XAI functionalities within the domain of SC. Our analysis has revealed the influence of XAI on the decision-making process in the field of SC. This study utilizes the SHapley Additive exPlanations (SHAP) technique to analysis the online data using Python machine learning (ML) process. Explanatory algorithms are specifically crafted to augment the lucidity of ML models by furnishing rationales for the prognostications they produce. The present study aims to establish measurable standards for identifying the constituents of XAI and DSSs that augment decision-making in the context of SC. This study assessed prior research with regards to their ability to make predictions, utilization of online dataset, number of variables examined, development of learning capability, and validation within the context of decision-making, emphasizes the research domains that necessitate additional exploration concerning intelligent decision-making under conditions of uncertainty.

Game Models for Ordering and Channel Decisions of New and Differentiated Remanufactured Products in a Closed-Loop Supply Chain with Sales Efforts

Environmental responsibility and economic benefits have promoted the development of closed-loop supply chains (CLSCs), and shortages and channels are considered to be two important issues in a CLSC. This paper explores the ordering and channel decisions in a CLSC with new and differentiated remanufactured products; considers the price and sales-effort-dependent demands, as well as the proportion of emergency orders determined by emergency order costs and backorder losses; and establishes integrated and decentralized CLSC game models. We introduce a stochastic sales effort, which affects two types of products. The numerical results show that sales effort and the order quantity of new and remanufactured products exhibit concave and convex functions, respectively. The upper limit of sales effort has a greater impact on supply chain decisions. High sales efforts can serve as a means of coordinating dispersed supply chains. Moreover, in different cases, the decisions of an integrated channel are better than those of a decentralized channel. Finally, whether the supply chain adopts an emergency order strategy depends on the relative cost of emergency orders and out-of-stock costs. According to this research, some management insights are also provided.

Analyzing Food Loss in Banana Pepper (Capsicum annuum) Production: Causes, Impact, and Challenges, A Case Study of Large-Scale Farming in the Hot District, Chiang Mai, Thailand

This study aimed to assess both quantitative and qualitative food loss in banana pepper production at the agricultural level. Its objectives included employing the Supply Chain Operations Reference Model (SCOR Model) for analysis, identifying root causes of losses and evaluating quantity and quality. Food loss here refers to diminished quantity and quality due to supply chain decisions and actions. Data collection and analysis included an extensive literature review, compilation of secondary data, primary data gathering via questionnaires and measurements of lost banana pepper yield during harvesting. Qualitative insights were acquired through in-depth interviews and focus group discussions. The study identified weather variability as the primary driver of food loss, with many farmers lacking access to climatic measuring tools. Additional losses, assessed visually, comprised damage from diseases, pests, stunted growth, mechanical issues and other factors, accounting for 13.68, 10.13, 6.95, 4.03 and 7.01 % of the total loss, respectively. Remarkably, only 57.93 % of the produce met quality and sale readiness criteria. The loss of banana peppers was estimated at 55.21 %, equivalent to 1,189.62 kg/rai, resulting in an economic loss of 35,688.58 Baht/rai. The study also noted significant nutrient losses, including energy, carbohydrates, fiber, protein, potassium, phosphorus, vitamin B1 and vitamin C, amounting to 321,197 kcal/rai and 57,102, 38,068, 17,844 g/rai and 3,045,427, 559,121, 487,744, 166,547 mg/rai, respectively. Farmers, while aware of food loss issues, often struggle to quantify them accurately. This study’s findings can raise farmers’ awareness and aid in designing training programs to mitigate such losses. However, addressing the inherent variability and unpredictability of on-farm food loss remains a challenge. Future research should prioritize a comprehensive analysis of banana pepper losses on farms. HIGHLIGHTS Weather variability was identified as the primary driver of food loss, exacerbated by limited access to climatic measuring tools Various factors contribute to food loss, including damage from diseases, pests, stunted growth and mechanical issues, accounting for 68 to 7.01 % of total loss Significant economic and nutrient losses, with a 21 % loss of banana peppers, resulting in an economic loss of 35,688.58 Baht/rai and substantial nutrient losses in various categories GRAPHICAL ABSTRACT

Pricing strategy research in the dual-channel pharmaceutical supply chain considering service.

In the context of developing a new era, the pharmaceutical supply chain market has gradually transformed from a seller's market to a buyer's market. The closer the consumers are, the greater the market pricing power, so the pharmaceutical market power of manufacturers and retailers has also changed. This study considers the effect of service on the pricing strategy of the pharmaceutical platform supply chain. The study aimed to coordinate optimization, and the coordination strategy of the pharmaceutical platform supply chain of complementary products is discussed mainly by researching the price and service factors. Various situations are studied by hypothesis and model solving. This study uses Stackelberg game decision-making. Manufacturers are at the forefront of platform supply chain decisions. The research found that the price was lower under centralized decision-making than under decentralized decision-making. Coordination between price and service levels needs attention in the pharmaceutical platform supply chain of complementary products, and the service level should be controlled within a certain range. Only by improving the service level can enterprises maximize profits, providing a theoretical basis for pharmaceutical supply chain pricing strategy research. Supply chain members must strive to improve service levels to improve medical supply consumers' (patients) psychological satisfaction level. Service levels do not fully mitigate channel conflict. Therefore, pharmaceutical complements have become a way to alleviate the conflicts in the pharmaceutical platform supply chain.

Pricing decisions of online and offline dual-channel supply chains considering data resource mining

Data resources, a fundamental component in the digital economy, play a vital role for businesses aiming to establish a lasting competitive edge. A company's data resources can uniquely influence the decisions surrounding products and services within the supply chain. The integrated dual-channel supply chain (DCSC) involves direct online channels utilized by manufacturing service providers alongside offline channels, such as physical retail stores, managed by sales service integrators. The DCSC is capable of performing second-stage data mining services in accordance with the sold products and customer services after the product sales are completed. Subsequently, data resource mining can be achieved through a cross-channel approach. As such, considering the exploration of cross-channel data resources, this study strives to formulate a structure for a dual-channel closed-loop supply chain. Furthermore, utilizing concepts from the Stackelberg and Nash equilibrium game theories, it delves into the analysis of pricing decisions and profit allocation. This examination encompasses distinct closed-loop supply chain configurations, viewed through the lenses of both centralized and decentralized decision-making approaches. In addition, the effects of cross-channel data mining and channel consumption preferences on supply chain decisions are analyzed, and the analysis is conducted in combination with numerical examples. As evidenced by the findings in this investigation, cross-channel data resource mining, consumer channel preference, and the data mining value conversion rate can prominently affect the formulation of pricing strategies and the distribution of profits in closed-loop supply chains. The potential value of data resources can lead to the generation of “external incentives” following the strategy of data resource mining. Furthermore, the data resource mining strategy is promising in stimulating the growth of the product and service markets. Finally, the overall profit of the supply chain is increased with the increase in the efficiency of data resource conversion. Enhancements in the efficacy of data resource conversion correspondingly lead to heightened overall profits within the supply chain.

Cross-border dual-channel supply chain decision-making under random demand and tariff conditions.

Given the cross-border e-commerce import tariff and random demands, this study establishes a pricing decision model for cross-border e-commerce dual-channel supply chain, which is composed of domestic manufacturers and overseas retailers, so as to analyze the effects of import tariff and random demand on the pricing, demand and profit of cross-border e-commerce. According to the research, import tariffs have a positive correlation with retailers' retail prices and a negative correlation with manufacturers' direct prices, wholesale prices, demand and profit from direct channels, and profit from retail channels. The export tax rebate policy will lessen the negative effects of import tariffs and maximize the best choices made by manufacturers and retailers.

An Empirical Investigation of Manufacturers’ Operations Innovations in New Product Development Enabled by E-Commerce Platforms

E-commerce platforms are playing an increasingly important role in influencing manufacturers’ supply chain and product decisions. An emerging supply chain innovation, known as the platform-based consumer-to-manufacturer (PC2M) model, has been initiated by several large e-commerce platforms based on established digital links between consumers and manufacturers. These links enable consumer inputs into manufacturers’ operations, indirectly by capturing consumer preferences from platform-accumulated big data and directly by enabling consumer interaction with manufacturers through the e-commerce platform. Although manufacturers are increasingly integrating PC2M into new product development (NPD), there is little research on operations innovations in connection with the PC2M model and its impact on manufacturers’ new product success. To fill this research gap, we investigate the PC2M model of JD.com, a leading e-commerce platform in China that launched the PC2M model in 2018. We first identify two uses of PC2M by manufacturers to facilitate product development—platform-enabled big data analytics (PBA) and platform-enabled simulated product trials (PST)—and explore how PC2M enables operations innovations in NPD. Next, drawing on the knowledge-based view, we develop research hypotheses and empirically examine whether PC2M adoption improves new product performance using a large-scale, transactional dataset from JD.com. Through a series of carefully executed analyses, our study consistently finds that use of either PBA or PST in manufacturers’ NPD processes improves new product performance. We also explore how these effects vary across product types and markets with varying new product introduction rates. The findings offer important managerial insights for improving new product success in today's data-rich environment.

Price optimization for manufacturers in a competitive retail market: imported products and online crowdfunding option

AbstractThis study explores how manufacturers in the competitive supply chain can set prices and secure funding effectively. We use game theory to look at how competition between domestic and foreign manufacturers affects pricing decisions. Our research investigates how a domestic manufacturer can improve its market share by addressing financial challenges through modern financing methods. In this scenario, a domestic manufacturer competes with a foreign one to attract a retailer’s market share and profits. The retailer decides what products to buy and how to price them based on bid prices and demand. We also consider that the domestic manufacturer will use online crowdfunding platforms to tackle its financial problem. Hence, our study sets up a supply chain where competition revolves around both operational and financial decisions. Mathematical models are developed to analyze how costs, finances, market potential, and price sensitivity impact various parts of the supply chain. The results reveal that decisions made on the crowdfunding platform significantly influence other supply chain decisions. Manufacturers and retailers need to pay attention to the financial decisions made on this platform to maximize profits. Also, domestic and foreign manufacturers should consider customer preferences for their products when setting prices. Finally, the results demonstrate that a domestic manufacturer can gain a competitive edge in the retail market by carefully considering both product pricing and financial decisions, including those made on the lending platform.

Contributing to health system resilience during pandemics via purchasing and supply strategies: an exploratory system dynamics approach

BackgroundHealth systems worldwide struggled to obtain sufficient personal protective equipment (PPE) and ventilators during the COVID-19 pandemic due to global supply chain disruptions. Our study’s aim was to create a proof-of-concept model that would simulate the effects of supply strategies under various scenarios, to ultimately help decision-makers decide on alternative supply strategies for future similar health system related crises.MethodsWe developed a system dynamics model that linked a disease transmission model structure (susceptible, exposed, infectious, recovered (SEIR)) with a model for the availability of critical supplies in hospitals; thereby connecting care demand (patients’ critical care in hospitals), with care supply (available critical equipment and supplies). To inform the model structure, we used data on critical decisions and events taking place surrounding purchase, supply, and availability of PPE and ventilators during the first phase of the COVID-19 pandemic within the English national health system. We used exploratory modelling and analysis to assess the effects of uncertainties on different supply strategies in the English health system under different scenarios. Strategies analysed were: (i) purchasing from the world market or (ii) through direct tender, (iii) stockpiling, (iv) domestic production, (v) supporting innovative supply strategies, or (vi) loaning ventilators from the private sector.ResultsWe found through our exploratory analysis that a long-lasting shortage in PPE and ventilators is likely to be apparent in various scenarios. When considering the worst-case scenario, our proof-of-concept model shows that purchasing PPE and ventilators from the world market or through direct tender have the greatest influence on reducing supply shortages, compared to producing domestically or through supporting innovative supply strategies. However, these supply strategies are affected most by delays in their shipment time or set-up.ConclusionWe demonstrated that using a system dynamics and exploratory modelling approach can be helpful in identifying the purchasing and supply chain strategies that contribute to the preparedness and responsiveness of health systems during crises. Our results suggest that to improve health systems’ resilience during pandemics or similar resource-constrained situations, purchasing and supply chain decision-makers can develop crisis frameworks that propose a plan of action and consequently accelerate and improve procurement processes and other governance processes during health-related crises; implement diverse supplier frameworks; and (re)consider stockpiling. This proof-of-concept model demonstrates the importance of including critical supply chain strategies as part of the preparedness and response activities to contribute to health system resilience.

Impact of Green Credit Incentives on Operational Decisions of Green Supply Chain

Financial incentives have been introduced to guide financial institutions to increase green credit allocation, strengthen environmental risk management, and enhance support for green and low-carbon development. This paper investigated the government’s support for the carbon-emission supply chain by implementing green credit incentives. Two financial incentives are explored: performance-based incentives and interest subsidies. We conduct game-theoretic models to examine the characteristics and effects of two financial incentives on the supply chain. Our results reveal that: (1) both incentives are effective in scaling up supply chain performance and stimulate investment in emission reduction, while the mechanism differs according to the direct beneficiaries; (2) performance-based incentives are more sensitive to environmental damage, while the optimal subsidy ratio is more sensitive to consumer green awareness, indicating that the bank has an instinctive aversion to the risks inherent in abatement investments; (3) it is optimal for the government to intervene in green credit financing activities when environmental advantages and costs and consumer green consciousness are recognized. Our conclusions suggest the government can determine financial incentives for green credit based on the stage of green transition development and the real, demanding requirements of transition goals.

Innovation for zero-deforestation sustainable supply chain management services: a performance measurement and management approach

PurposeFood sector supply chains have significant negative environmental impacts, including the expansion of global food commodity production, which is driving tropical deforestation – a major climate and biodiversity problem. Innovative supply chain monitoring services promise to address such impacts. Legislation also designates “forest-risk commodities”, demanding supply chain due diligence of their provenance. But such data alone does not produce change. This study investigates how theory in performance measurement and management (PMM) can combine with sustainable supply chain management (SSCM) and decision theory (DT) via case study research that addresses paradoxes of simplicity and complexity.Design/methodology/approachGiven existing relevant theory but the nascent nature of the topic, theory elaboration via abductive case study research is conducted. Data collection involves interviews and participatory design workshops with supply chain actors across two supply chains (coffee and soy), exploring the potential opportunities and challenges of new deforestation monitoring services for food supply chains.FindingsTwo archetypal food supply chain structures (short food supply chains with high transparency and direct links between farmer and consumer and complex food supply chains with highly disaggregated and opaque links) provide a dichotomy akin to the known/unknown, structured/unstructured contexts in DT, enabling novel theoretical elaboration of the performance alignment matrix model in PMM, resulting in implications for practice and a future research agenda.Originality/valueThe novel conceptual synthesis of PMM, SSCM and DT highlights the importance of context specificity in developing PMM tools for SSCM and the challenge of achieving the general solutions needed to ensure that PMM, paradoxically, is both flexible to client needs and capable of replicable application to deliver economies of scale. To advance understanding of these paradoxes to develop network-level PMM systems to address deforestation impacts of food supply chains and respond to legislation, a future research agenda is presented.

Pricing Decisions in Construction and Demolition Waste Recycling Supply Chains under Carbon Tax Scenarios

Pricing decisions for construction and demolition waste recycling are severely hampered by consumer uncertainty in assessing the value of recycled building materials. This paper uses a construction and demolition waste (CDW) recycling utilization model that consists of a building materials manufacturer and a building materials remanufacturer and compares both the prices and the profits under different carbon tax scenarios, i.e., consumer risk-averse and risk-neutral scenarios. The main conclusions are as follows. (1) The optimal price of traditional products is always negatively correlated with consumer risk aversion. Unlike traditional products, the optimal price of recycled building materials is negatively related to the degree of consumer risk aversion in the case of a low carbon tax; the opposite conclusion is obtained in the case of a high carbon tax. (2) When the abatement cost coefficient is below the threshold and the carbon tax is low, the profits of the building materials manufacturer and remanufacturer show a U-shaped trend with consumer risk aversion; in the case of a high carbon tax, the profits of the two enterprises are positively correlated with consumer risk aversion. In addition, when the abatement cost coefficient is above the threshold, there is an interval in which the profits of the building materials manufacturer are positively correlated with consumer risk aversion in the case in which the carbon tax satisfies this interval. In all the other cases, there is a U-shaped trend in profits and consumer risk aversion levels for both the building materials manufacturer and the remanufacturer.

Optimal carbon quota allocation for a capital-constrained e-commerce supply chain under the carbon rights buyback policy

This paper examines the optimal choices of carbon quota allocation methods for members of a capital-constrained e-commerce supply chain that obtains financing through carbon rights buyback. Considering two carbon quota allocation methods, namely the grandfathering system and the benchmarking system, this paper constructs and solves a game model with two cycles in which an e-commerce platform dominates a manufacturer that produces ordinary products and low-carbon products in the two cycles, respectively, examines the impacts of the carbon emissions reduction coefficient, carbon emissions benchmark coefficient, carbon price, and carbon saving on e-commerce supply chain decisions, derives the optimal carbon quota allocation method for each supply chain member under different carbon savings, and finally conducts numerical studies to verify the analytical findings. The study shows that: (1) The grandfathering system is more suitable for manufacturers with low carbon savings, and the benchmarking system is more suitable for manufacturers with high carbon savings. (2) The supply chain system and members prefer different quota allocation methods under different conditions. The e-commerce platform prefers the benchmarking system when the carbon emissions benchmark coefficient is high; otherwise, it chooses the grandfathering system. The manufacturer and the e-commerce supply chain prefer the benchmarking system when the carbon saving is high; otherwise, they prefer the grandfathering system. (3) The grandfathering carbon quota allocation method can more effectively facilitate capital financing for capital-constrained manufacturers.

Carbon intensity of mass timber materials: impacts of sourcing and transportation

Mass timber construction is widely considered a promising alternative construction method to reduce buildings’ total life-cycle carbon emissions because wood is a carbon sink. Cross-laminated timber (CLT) panels, manufactured by gluing lumber layers with grains at right angles, are potential low-carbon alternatives to carbon-intensive concrete and steel construction. However, most environmental impact assessment studies do not consider variation in transportation impacts within the CLT supply chain when calculating life-cycle impacts. This study investigates the embodied primary energy and the global warming potential (GWP) of CLT supply chain decisions regarding the type of timber species used, the U.S. region it is sourced from, and the location of the CLT mill. Longer transport distances in the supply chain for timber and CLT panels can contribute as much as 923 MJ/m2 (20%) of the embodied primary energy of a CLT building, and the use of a higher-density timber species increases this contribution to 1246 MJ/m2 (24%), with most of that energy derived from fossil energy sources. For perspective, the GWP of a building whose CLT panels and timber have been transported by truck over 6,000 km (252–270 kgCO2/m2) is greater than the GWP of an equivalent reinforced concrete (RC) building (245 kgCO2/m2). Thus, factors like the location of CLT processing facilities and the type of timber species can significantly impact the overall life-cycle assessment and, if chosen appropriately, can mitigate the environmental impacts of CLT construction.

Research on Supply Chain Coordination Decision Making under the Influence of Lead Time Based on System Dynamics

Supply chain coordination has been a research hot spot in supply chain management. This paper constructs a secondary supply chain system. Taking the abatement of the bullwhip effect and the double marginal effect as the coordination objective, a simulation study of supply chain decision coordination was conducted using system dynamics. First, by controlling the lead time, it was found that in the decentralized decision-making model, the profit of the supplier and the whole supply chain increases with the shortening of the lead time, and vice versa for the retailer. In the centralized decision-making model with the addition of information sharing and contract, it was found that the retailer’s profit is consistent with the trend of the supplier and the supply chain as a whole, and the supplier’s profit is lower than that of decentralized decision making in the pre-cooperation period. In addition, it is also found that adjusting the contract parameters can effectively improve the situation. Finally, the above models were analyzed for supply chain coordination decisions based on two scenarios: “cooperative stability” or “balance of effects”.

The role of social relations in supply chain decision‐making: Evidence from China

AbstractThis study examines the extent to which firms in emerging markets build supply chains around social relationships. Most existing studies contend that companies decide who to buy (sell) products from (to) based on cost–benefit trade considerations of product quality, price, and other factors. We argue that companies make supply chain decisions around social relations to reduce possible risks. We empirically test this conjecture by using data from Chinese municipal party secretaries who served in different places from 2006 to 2017, and the primary customers of listed companies. The results show that after an official move from one jurisdiction to work in another, the firms in the latter jurisdiction will see an increase in customers from where the official previously served. Further investigation reveals that companies that are economically strong, face fierce competition, are state‐owned, and are located in areas with low degrees of marketization are more likely to attract customers from the area where the official last served after the new municipal party secretary takes office. Making supply chain decisions based on the social relationships of the secretaries of the municipal party committees does not improve companies' profitability, but doing so will increase the turnover rate of accounts receivable and accounts received in advance.

Pricing and low-carbon decisions in an uncertain supply chain with cap-and-trade regulation

This paper studies the pricing and low-carbon decision problems in a supply chain containing a manufacturer and a downstream retailer. The manufacturer produces a single product under the cap-and-trade scheme. We formulate the price and carbon-concerned demand function. To maximize their revenue, the manufacturer and the retailer determine their selling prices and carbon emission reduction rates separately. Due to the fast product updates speed, some parameters do not have enough historical data. For example, the sales cost of the retailer, the demand of consumers, and the total carbon emissions of manufacturers are far from frequency stability. This fact makes the distribution function obtained in practice usually deviate from the frequency. They are all uncertain variables whose distributions are estimated from the empirical data of experts or managers. In this paper, we give three decentralized game models to explore the equilibrium behaviors in the corresponding decision environment under an uncertain environment. Corresponding analytical solutions are offered under different game scenarios. Finally, numerical experiments are performed to illustrate the effectiveness of the established models and yield some remarkable insights.

Pricing and coordination in a dual-channel supply chain considering internet celebrity’s sales effort and personal influence

The main purpose of this paper is to study the coordination, price and sales effort decisions of a dual channel supply chain under live streaming commerce mode. In nowadays’ e-commerce age, more and more people have interest in live streaming especially after the outbreak of COVID-19, but the research on live streaming supply chain is lacking. To fill this gap, a supply chain composed of a manufacturer and an internet celebrity is established, in which the demand is affected by the internet celebrity’s sales effort and personal influence. Considering different power structures of the supply chain, price and sales effort decisions are studied in four models: Nash, manufacturer dominant (MD), internet celebrity dominant (KD) and cooperative game models. Subsequently, the feasible region of bargaining game is discussed in terms to share the extra profits and coordinate the supply chain. The manufacturer and the internet celebrity can be coordinated through bargaining problem in the cooperation model, and the extra profits sharing ratio is depend on each other’s bargaining power. Numerical analysis is further provided to test the propositions and show the impacts of market share rate, internet celebrity’s commission rate and personal influence on supply chain’s performance.

Can “dual credit” replace “subsidies” successfully? -based on analysis of vehicle supply chain decisions under the digital transformation of technology

Transportation is the second largest source of carbon emissions today, with more than 80% of the carbon emitted from automobile operations. Hence, reducing the fuel consumption per unit mileage while vigorously developing new energy vehicles has become an inevitable choice for carbon emission reduction. So, this paper applies the differential game approach to investigate the production trade-offs of fuel and new energy vehicles, fuel consumption reduction, and digital technology investment strategies in an automotive supply chain under a dynamic framework. In addition, it further analyzes whether the dual credit policy (DCP) can promote the healthy development of China's auto market after the withdrawal of the purchase subsidy policy for new energy vehicles (PSP). The results show that the implementation of DCP will reduce the sales of fuel vehicles with fuel consumption higher than the critical value (HFCV) but will not promote the willingness of manufacturers to invest in fuel consumption reduction of HFCV; the abolition of the PSP will not reduce the demand for fuel vehicles, nor will it affect the investment in fuel consumption reduction of fuel vehicles, but it will reduce the consumer demand for new energy vehicles. However, assuming that the government appropriately adjusts the intrinsic mechanism of the DCP, such as increasing the requirement for the proportion of new energy vehicles in the sales of cars by manufacturers and the value of the points per unit of new energy vehicles, it will be possible to promote the growth of new energy vehicles while discouraging the production of fuel-intensive vehicles. In addition, If the government abolishes PSP, the maximum rate of change in the profits of the manufacturer, retailer, and the entire supply chain in the parameter change intervals analyzed in our numerical example is only 1.6%, 0.04%, and 0.13%, respectively, which can be said to have minimal impact. The findings provide a theoretical basis for the government's choice of carbon regulation policy for the automotive supply chain.