Cost Coefficients Research Articles

Manufacturer's cooperative recycling strategies considering the negative externality of unrecycled products: Non‐cooperative, fund‐cooperative, or labour‐cooperative

AbstractThis paper proposes a new objective function for manufacturer considering the negative externality of unrecycled products (NEUP), and develops three cooperative recycling modes: non‐cooperative, fund‐cooperative and labour‐cooperative. Results indicate that compared to non‐cooperative, while fund‐cooperative can enhance the recycling rate, it hurts the system's profitability. In contrast, labour‐cooperative can achieve a win–win situation for both. Moreover, considering NEUP expands the dominant space of fund‐cooperative in recycling rate, but weakens its advantage in market demand. Notably, considering NEUP may render cooperative recycling ineffective in improving profit, which largely depends on the degree of considering NEUP and recycling cost coefficient ratio.

Implementation mode selection for blockchain technology in green product traceability

Implementing blockchain technology to improve traceability can enhance consumer trust in green supply chains. However, the associated high fixed costs can pose challenges for companies when choosing the implementation mode. In this study, we investigate the value of blockchain adoption and explore a manufacturer’s choice between third-party or self-implementation. Specifically, we consider the traceability level and the greenness degree in a supply chain comprising a manufacturer, a retailer, and a third-party platform providing blockchain services. Our findings indicate that self-implementation by the manufacturer increases the degree of greenness, and the retailer’s involvement in decisions about traceability levels improves the manufacturer’s traceability level. The highest profits for supply chain members are achieved when both parties opt for self-implementation. Additionally, self-implementation outperforms third-party platform implantation when incentivizing the manufacturer to invest more in green and blockchain technologies. Consequently, blockchain technology’s value exceeds its costs, encouraging supply chain members to select self-implementation whenever possible. However, when the fixed costs or the cost coefficient of green investment or traceability are excessively high, the manufacturer may need to outsource blockchain services to a third-party platform. Furthermore, through comprehensive system dynamics analysis, we find that blockchain’s adoption or non-adoption and imposing an investment cap on the product’s green degree have a little effect on profitability for suppliers, manufacturers, logistics providers, and third-party platforms.

Service provision decisions of competitive manufacturers: From service spillover perspective

This paper investigates competing manufacturers’ strategic choice of service provision in a two-level supply chain composed two manufacturers and one common retailer. Our results indicate that the strategy that two competing manufacturers provide services is always the dominant choice, and two competing manufacturers could have the highest profit in that case. But when only one of them provides services, the result is related to the potential market size, the unit service cost coefficient and the service spillover intensity. Finally, through the cost sharing and quantity competition extensions, we find the Pareto regions of cost sharing under the equilibrium strategy, and there will be multiple Nash equilibrium regions under the quantity competition.

Research on renewable energy investment decision-making in power supply chain based on cap-and-trade mechanism

PurposeBy comparing and contrasting the two scenarios of power producers investing in renewable energy and electricity sellers investing in renewable energy, we explore the conditions under which profit growth and carbon emission reduction can be realized, and provide a theoretical basis for decision-making on renewable energy investment by electric power companies as well as for government policy formulation.Design/methodology/approachThis paper constructs a game model of a grid supply chain consisting of a leader generator and a follower seller in the context of the C&T mechanism, considering two scenarios in which the generator and the seller invest in renewable energy. Conclusions are drawn by comparing and analyzing the equilibrium solutions in different scenarios.FindingsThe scenario where electricity sellers invest in renewable energy exhibits a higher investment volume compared to the scenario involving power generators. In scenarios where power producers invest in renewable energy, electricity sellers achieve lower profits than power generators, while scenarios with electricity seller' investments yield higher profits for them. Increasing the cost coefficient of renewable energy investment reduces investment volume, electricity prices and electricity demand, leading to decreased profits for electricity seller but increased profits for power generator. A rise in the preference coefficient for renewable energy results in increased profits for electricity seller but decreased profits for power generator.Originality/valueAddressing a literature gap in the context of low carbon, this study examines the investment scenario of electricity sellers in low carbon technologies, complementing existing research focused on power generators and consumers. The findings enrich knowledge in low carbon investment. By analyzing the investment decisions of both power producers and electricity sellers, this study explores the practical implications of renewable energy investments on the decision-making and operational dynamics of power supply chain enterprises. It sheds light on their profitability and investment strategies.

Impact of cap-and-trade mechanism on investment decision of new electric power system.

Under the background of cap-and-trade mechanisms, this article constructs a game model of the electricity supply chain, which is dominated by electricity generators and followed by electricity sellers, taking into account the situation of electricity generators investing in renewable energy and energy storage under the grandfathering mechanism (GM) and benchmarking mechanism (BM). By comparing the equilibrium solutions in different cases, the research finds that (1) compared with the grandfathering mechanism, the benchmarking mechanism has more investment in renewable energy and higher energy storage quality; (2) in the consumer market, compared with GM, the electricity price and the electricity demand are higher under BM; (3) an increase in the renewable energy preference coefficient or carbon price will lead to an increase in the electricity wholesale price, renewable energy investment, energy storage quality, electricity price, and electricity demand. Further, an increase in the energy storage cost coefficient or renewable energy investment cost coefficient will result in lower electricity wholesale price, renewable energy investment, energy storage quality, electricity price, and electricity demand; and (4) the profit of the generator under GM is higher than that under BM when the total carbon quota is larger, while the profit of the generator under BM is higher than that under GM when the unit carbon quota is larger.

Blockchain technology empowers the cross-border dual-channel supply chain: Introduction strategy, tax differences, optimal decisions

Fueled by the widespread adoption of blockchain technology in supply chain management and international trade, this paper develops a cross-border dual-channel supply chain consisting of a domestic manufacturer, a domestic cross-border e-commerce company, and an overseas physical store. This paper aims to explore the impacts of tax differences, market competition intensity, consumers’ sensitivity to products with blockchain attributes, blockchain technology investment costs, and production quantity deviations on the strategies for adopting blockchain technology. Through simulation analysis, this study compares blockchain investment efforts, wholesale prices, retail prices, and the profits generated by supply chain members across different scenarios. The results show that when production quantity deviations are greater than 0, the domestic manufacturer’s adoption of blockchain technology provides free-riding benefits to other supply chain members, thereby enhancing the overall profitability of the supply chain. However, the introduction of blockchain technology by the domestic manufacturer does not always yield benefits; when the production quantity deviations are less than 0 and the blockchain investment cost coefficient is too high, it decreases the willingness of the domestic manufacturer to adopt blockchain technology. Moreover, from a profit maximization perspective, regardless of the changes in production quantity deviations and whether the domestic manufacturer introduces blockchain technology, both the domestic cross-border e-commerce company and the overseas physical store should adopt blockchain technology. Finally, The five influencing factors mentioned earlier will, to some extent, affect the profits and decision-making of supply chain members, suggesting that these members should vigilantly track these variables.

Optimal operation of multi-carrier energy systems considering demand response: A hybrid scenario-based/IGDT uncertainty method

The optimal operation of multi-carrier energy systems (MCESs) has opened new horizons for energy network management and the satisfaction of consumers. In this paper, the optimization of the MCES's operation cost is considered by combining several energy hubs (EHs). To make optimal use of thermal and electrical demand response programs (TDRPs and EDRPs), the cost factors are extracted using a new sensitivity analysis (SA) method. Then, taking into account the optimized cost coefficients in EDRP and TDRP, the optimal operation of MCES is investigated in the presence of uncertain parameters. In this paper, a two-stage uncertainty method is used for solving the uncertain problem. First, the uncertainty of wind, photovoltaic (PV), and electrical and thermal loads is modeled with a scenario-based method, in the second step, the price uncertainty of generated electricity is added to the previous model using the information gap decision theory (IGDT). A hybrid scenario-based/IGDT uncertainty has been performed simultaneously at the GAMS platform. The results show the impact of each uncertainty parameter and system resilience due to the optimization done in the problem and the EDRP and TDRP programs. The results show about 135$ difference between the lowest and highest scenarios at a total operation cost.

CVP-analysis as a tool for improving economic sustainability in the cost management system of health resort organizations

Costs are the basis of any type of activity and are the factor that has a direct impact on the financial results of the organization. That is why organizations are urgent issues of implementation of methodological tools that would allow to reduce costs and ensure their rational distribution between individual responsibility centers. To identify cost reduction reserves, it is necessary to provide an effective management system using modern tools. CVP-analysis is such a tool, which provides an opportunity to take into account the impact of costs on the results of the enterprise’s activities and to evaluate alternative management decisions. The paper demonstrates the possibility of using CVP-analysis to manage costs and financial results in the health resort sector on the example of enterprises of the Republic of Crimea and Sevastopol. The necessity of application of CVP-analysis as an important tool in the management of economic stability is determined and the prerequisites for minimizing entrepreneurial risk are revealed. The relationship between costs, production volume and profit in the sanatorium-resort sphere is presented and substantiated, taking into account the current economy, namely the conditions of uncertainty and risk. The study of CVP analysis aims to identify the level of sales revenue at which the enterprise will cover fixed and variable costs to strengthen economic sustainability. Despite the fact that the CVP system does not solve all the problems of effective management, it is on the basis of the data of the classical CVP-analysis that it becomes possible to assess the risk by the indicators of financial strength reserve, sensitivity to changes in the coefficient of variable costs and the amount of fixed costs in the same way as it is offered by some methods of risk analysis. CVP-analysis capabilities allow to effectively manage costs, find the optimal ratio between fixed and variable costs, price and volume of production (services), effectively forecast and plan the company’s profit. Since the main indicator of the efficiency of the enterprise is the ratio of profit and costs, the management of the enterprise can make balanced managerial decisions to ensure high performance of operating activities and achieve the desired financial performance, using the methodology of CVP-analysis. All this allows the enterprise in conditions of uncertainty and risk to increase the potential of profit formation and, accordingly, to strengthen economic stability.

Blockchain development in a supply chain with rival entry

We investigate the impact of rival entry on blockchain technology development by modelling a supply chain, in which an incumbent manufacturer (she), facing the entry of an entrant manufacturer (it), develops the blockchain platform through investments to improve the traceability and transparency of products procured from one supplier (he). Our study shows the rival entry (competition) may not necessarily promote blockchain technology adopted by the incumbent manufacturer, whether the blockchain platform is permissioned or non-permissioned. Furthermore, the entry of a new firm may trigger an ‘all-win’ situation for all parties involved not only in the permissioned scenario but, surprisingly, also in the non-permissioned one. In such a situation, the incumbent manufacturer and the supplier will be both more profitable conditionally, after the entrant manufacturer enters the market. Finally, the issue that a permissioned or non-permissioned blockchain platform should be built is discussed in this work. If the use cost coefficient and the development cost coefficient of blockchain technology are both low, or if the use cost coefficient is high while the development cost coefficient is low (not very low), the incumbent manufacturer should establish a permissioned blockchain platform, and otherwise a non-permissioned one.

Optimal supply chain performance: risk aversion to green innovation

PurposeAlthough many countries are focusing on the management of construction and demolition waste (CDW) resource utilization, the effect of risk aversion of the green innovation-led enterprise on the performance of the CDW resource utilization supply chain is unclear when considering different green innovation contexts (green innovation led by the building materials remanufacturer or by the construction waste recycler). This study aims to investigate how the level of risk aversion of the green innovation-led enterprise affects CDW resource utilization under different green innovation contexts based on contingency theory.Design/methodology/approachUsing Stackelberg game theory, this study establishes a decision model consisting of a building materials remanufacturer, construction waste recycler and CDW production unit and investigates how the level of risk aversion of the green innovation-led enterprise under different green innovation contexts influences the performance level of the supply chain.FindingsThe conclusions are as follows. (1) For the green innovation-led enterprise, the risk-averse behaviour is always detrimental to his own profits. (2) For the follower, the profits of the construction waste recycler are negatively correlated with the level of risk aversion of the green innovation-led enterprise in the case of a small green innovation investment coefficient. If the green innovation investment coefficient is high, the opposite result is obtained. (3) When the green innovation investment coefficient is low, the total supply chain profits decrease as the level of risk aversion of the green innovation-led enterprise increases. When the green innovation investment coefficient is high, total supply chain profit shows an inverted U-shaped trend with respect to the degree of risk aversion of the green innovation-led enterprise.Originality/value(1) This study is the first to construct a green innovation context led by different enterprises in the CDW resource utilization supply chain, which provides a new perspective on green management and operation. (2) This study is the first to explore the operation mechanism of the CDW resource utilization supply chain based on contingency theory, which provides new evidence from the CDW resource utilization supply chain to prove contingency theory. At the same time, this study examines the interactive effects of the green innovation cost coefficient and the degree of risk aversion of green innovation-led enterprises on the performance of supply chain members, expanding the contingency theory research on contingencies affecting enterprise performance. (3) This study will guide members of the CDW resource utilization supply chain to rationally face risks and achieve optimal supply chain performance.

Analyze the Stochastic Solid Fuzzy Transportation Problem with Mixed Constraints through Weibull Distribution

This paper proposed a general formulation of the stochastic solid transportation problem (SSTP) with mixed constraints such as supply, demand and conveyance capacity taken as uncertain under stochastic environment, following the Weibull distribution (WD). The aim of this study is to minimize the transportation cost includes probabilistic constraints have inequalities of stochastic solid transportation problem (SSTP). SSTP with probabilistic constraints is represented as a chance constrained programming problem. Obtain alpha cut representation from cost coefficient of the fuzzy objective function. We have developed four models for stochastic solid transportation problem. The suggested models are demonstrated by taken as numerical example. A sensitivity analysis is performed to understand parameter’s sensitivity in the proposed model. Introduction: In system of transportation, goods are moved from various sources to destinations using different vehicles and organizational systems, involving both technology and human efforts. Efficient resource allocation in transportation system is crucial for industries and imprecision from factors like fluctuating demand, unreliable supply chains and unpredictable traffic. To address these complexities, advanced mathematical models are needed to manage stochasticity, fuzziness and mixed constraints. The study explores the stochastic solid fuzzy transportation problem with mixed constraint by utilizing the Weibull distribution to model uncertainties inherent in transportation systems. This research addresses the complexity introduced by stochastic variables and fuzzy parameters, particularly in situations where demand, supply and cost of transportation are not deterministic. Objectives: The aim of this study is to minimize the cost of transportation includes probabilistic constraints have inequalities of stochastic solid transportation problem (SSTP). Methods: Obtain alpha cut representation form the cost coefficient of the fuzzy objective function and four models are developed for stochastic solid transportation problem. These models are demonstrating by using a numerical example and a sensitivity analysis is conducted to understand the sensitivity of the parameters in the propose model. Results: Obtained optimal solutions for developed four models of SFSTPMC and sensitivity analysis shows that cost of transportation and flow of unit are sensitive to change in probabilities of demand. Improve transportation system by understanding sensitivity patterns that help decision maker choose appropriate supply availability probabilities. Conclusions: This study presented an approach for solving the SFSTPMC using the Weibull distribution for probabilistic constraints and fuzzy objective functions for transportation cost. Developed and optimized four models, focusing on stochastic parameters. Sensitivity analysis demonstrated the impact of these parameters on transportation cost and unit flow. The results validate the model’s effectiveness in practical resource allocation and decision making under uncertainty.

Application of energy combined thermal comfort in intelligent building management in complex environments

The efficient operation of heating ventilation and air conditioning systems relies on advanced control strategies. However, current control methods are often limited by issues such as uncertain system parameter information and spatial coupling constraints related to the supply rate of the air supply fan. To this end, an energy joint thermal comfort management method for complex environments in multiple regions is proposed. The long-term total cost minimization of the system is established, and then the Lyapunov optimization technology is used to design the distributed control algorithm. Simulation validation shows that the proposed method reduces the energy cost by an average of 11.24% compared to other methods with a thermal discomfort cost coefficient of 0. The average temperature deviation in the area is improved by 0.15 °C and 0.68 °C, respectively. The method saves more than 10% of the total energy cost under different thermal perturbations with an average total temperature deviation of 0.04 °C. The results indicate that the proposed energy joint thermal comfort management method can flexibly balance energy costs and user thermal comfort without knowing any prior information of system parameters, which can also greatly protect user privacy information. This method has application value in the control of heating ventilation and air conditioning systems in complex environments such as commercial buildings.

Entropic analysis: understanding economic sector relationships with Leontief's input-output tables

The article delves into the evolution of the "entropy" concept and its corresponding theoretical interpretations. Employing Shannon's entropy formula and leveraging the methodology of entropy calculation through Leontief's input-output tables, the study conducts entropy calculations for the economic systems of Australia, the Republic of South Africa, the United States, Luxembourg, Russia, South Korea, Japan, India, and China. These calculations are based on the tables published by the Organization for Economic Cooperation and Development. The primary finding of the study can be summarized as follows: Economic entropy, determined through the coefficients of total costs in Leontief's input-output tables, serves as a gauge of the interconnectedness among various branches within the economic system. Furthermore, financial and economic crises, as well as natural disasters, contribute to an escalation in the interconnectedness of economic branches, signifying a rise in entropy.

Dynamic incentive mechanisms in mega project-risk management considering the participation of the insurance company

PurposeThe construction of megaprojects often involves substantial risks. While insurance plays an important role as a traditional risk transfer means, owners and insurance companies may still suffer huge losses during the risk management process. Therefore, considering the strong motivation of insurance companies to participate in the on-site risk management of megaprojects, this study aims to propose a collaborative incentive mechanism involving insurance companies, to optimize the risk management effect and reduce the risk of accidents in megaprojects.Design/methodology/approachBased on principal-agent theory, the research develops the static and dynamic incentive models for risk management in megaprojects, involving both the owner and insurance company. The study examines the primary factors influencing incentive efficiency. The results are numerically simulated with a validation case. Finally, the impact of parameter changes on the stakeholders' benefits is analyzed.FindingsThe results indicate that the dynamic incentive model is available to the achievement of a flexible mechanism to ensure the benefits of contractors while protecting the benefits of the owner and insurance company. Adjusting the incentive coefficients for owners and insurance companies within a specified range promotes the growth of benefits for all parties involved. The management cost and economic benefit allocation coefficients have a positive effect on the adjustment range of the incentive coefficient, which helps implement a more flexible dynamic incentive mechanism to motivate contractors to carry out risk management to reduce risk losses.Originality/valueThis study makes up for the absence of important stakeholders in risk management. Different from traditional megaproject risk management, this model uses insurance companies as bridges to break the island effect of risk management among multiple megaprojects. This study contributes to the body of knowledge by designing appropriate dynamic incentive mechanisms in megaproject risk management through insurance company participation, and provides practical implications to both owner and insurance company on incentive contract making, thus achieving better risk governance of megaprojects.

Decisions and Coordination of E-Commerce Supply Chain Considering Product Quality and Marketing Efforts under Different Power Structures

With the rapid development of internet technology, consumers have increasingly higher requirements for product quality. High-quality products can win consumers’ trust. Enhancing both product quality and sales in e-commerce platform transactions has long been a focal point of research. To address this issue, this paper constructs Stackelberg game models under different power structures and compares their impacts on pricing decisions and profits within e-commerce supply chains. Numerical simulations are used to explore the optimal combination strategy for the interaction of product quality and marketing efforts in the e-commerce supply chain. The results show that: (1) Under a centralized decision-making model, product quality and marketing efforts reach their optimal values, maximizing benefits for the supply chain system. (2) Under different power structures, the relationship between the profits of the supplier and the e-commerce platform self-operator is closely linked to the cost coefficients of product quality and marketing efforts. (3) Through the mechanism of “cost-sharing + compensation contract”, the supplier can reduce wholesale price, and the e-commerce platform self-operator can subsidize a portion of the sales to the supplier, thereby maximizing the profits of both parties and achieving a win–win situation. The research in this paper aids suppliers in improving product quality and e-commerce platform self-operators in enhancing their marketing efforts, providing theoretical support for optimizing supply-chain decision making on e-commerce platforms.

Forward–reverse blockchain traceability: promoting electric vehicles with battery recycling in the presence of subsidy

AbstractElectric vehicles (EVs) and their battery recycling have recently garnered heightened attention from both firms and consumers, primarily driven by concerns related to environmental sustainability. However, consumers often grapple with uncertainties regarding the green valuation of EVs. Integrating blockchain traceability technology presents a promising solution to mitigate these ambiguities by providing traceable, immutable, and precise information. Within this context, this research, grounded in a game-theoretical framework, delves into the strategies involving blockchain traceability in the pre-purchase and post-purchase stages of EVs. Specifically, the paper analytically studies the influence of three distinct strategies, namely, non-blockchain traceability, forward blockchain traceability, and Forward–reverse blockchain traceability, on the willingness of EV manufacturers to adopt blockchain technology. In addition, the study incorporates two prevalent government subsidies to scrutinize and contrast their implications on optimal outcomes. The findings of this study uncover the nuanced relationship between adopting blockchain traceability and its impact on EV sales. Notably, the research shows that the positive impact on consumers’ surplus from blockchain adoption depends on the cost coefficient of green low-carbon levels not exceeding a particular threshold. Moreover, regarding the use of government subsidies to enhance overall social welfare, it is shown that the forward blockchain traceability strategy should align with consumer-oriented subsidies and the Forward–reverse blockchain traceability strategy with EV maker-oriented subsidies.

Optimal strategies for innovation and market allocation in joint production

Capacity sharing is an important way for relevant enterprises to save production materials. This paper constructs a capacity sharing decision-making model that considers market competition intensity, and introduces the independent market size of participating entities into the model design. This paper explores the impact mechanism of factors such as market competition intensity, independent market size of participating entities, and innovation cost coefficient on system decision-making. Research has found that the increase in independent market size has a consistent impact on the innovation and pricing decisions of enterprises sharing production capacity. Although the increase in independent market size enhances the sharing ability of production line innovation costs, it may not necessarily alleviate the problem of excessive competition among participating entities in overlapping markets. It is also necessary to specifically consider the impact of market competition intensity. The specific research conclusions provide decision-making basis for enterprises to participate in the process of capacity sharing, and also provide theoretical basis for relevant government departments to intervene in the process of capacity sharing.

Contract adoption of motivating green technological innovation in a supply chain

AbstractGreen technological innovation has been widely recognized around the world; however, consumer environmental awareness may result in uncertain market demand growth and lead to manufacturers’ risk‐averse attitude towards green technological innovation. This paper focuses on the contract adoption problem of a risk‐averse manufacturer who is responsible for green technological innovation, through a resell contract (RC) or agency contract (AC) with a retail platform. Stackelberg models are built, and the conditional value at risk method is used to measure the manufacturer's risk‐averse behavior. The differences between two contracts are compared. We find that when the commission rate is less than some threshold, the green technological level under AC is greater than that under RC regardless of the fixed cost coefficient, otherwise the green technological level under RC is higher. Further, there is the dual excellent region for AC and RC where the manufacturer can not only obtain a higher level of green technology but also achieve better utility. Finally, consumer surplus and social welfare under two contracts are performed through numerical experiments.

The cost bearing mechanism for advertising in a capital-constrained supply chain

With rising market competition, increasing numbers of firms are launching adverting to attract customers and promote product sales. The increase in operating costs caused by advertising places greater pressure on small retail businesses that are prone to capital shortages, leading them to seek financing from upstream firms. However, in the financing process, upstream and downstream firms may not be able to acquire all of one another's real information, which inevitably has a significant impact on their operating strategies. In this paper, by constructing a Stackelberg game, we study the effects of information asymmetry on the retailer's initial capital and the manufacturer's financing rate on their advertising strategies. We find that in a capital-constrained supply chain with symmetric information, when the advertising cost coefficient is low, manufacturer advertising is the superior strategy and increases the profits of the retailer and the manufacturer, consumer surplus and social welfare; when it is moderate, retailer advertising is the superior policy; but when it is high, retailer advertising is more beneficial for the manufacturer's profit, consumer surplus and social welfare but is more unfavorable for the retailer's profit. In addition, information asymmetry on the manufacturer's financing rate affects the advertising strategies of the manufacturer and the retailer, but information asymmetry on the retailer's initial capital fails. Additionally, we further extend the model to the Nash game scenario and cooperative advertising scenario and draw some different conclusions. The findings provide new theoretical implications for the formulation of firm advertising strategies.

Recycling Mode Choice in a Textile and Apparel Closed-Loop Supply Chain considering Blockchain

The development of the textile and apparel (T&A) industry has led to an increasing focus on recycling used products. Remanufactured product quality raises consumer concerns, and blockchain can effectively solve this problem. We establish a closed-loop supply chain (CLSC) in which a manufacturer, a retailer, or a third-party recycler collects used T&A products to examine the most efficient recycling mode with and without blockchain and the impact of blockchain on CLSC decisions. The results show that (1) if the manufacturer’s recycling cost coefficient is relatively low, used T&A products are collected directly by the manufacturer. Otherwise, the responsibility for recycling used T&A products falls to the retailer or the third-party recycler. It is noteworthy that the manufacturer’s choice of recycling mode remains unchanged whether a blockchain is implemented or not. (2) The implementation of blockchain by the manufacturer and the retailer can increase profits and consumers also benefit when the cost of validating blockchain units remains below a certain threshold. (3) When the recycling cost coefficient exceeds a certain threshold, the implementation of blockchain increases prices and recycling rates. These findings offer CLSC members’ management insights into how to select the optimal recycling mode and the consequences of implementing blockchain.