This paper considers a dynamic platform-based, closed-loop supply chain consisting of a manufacturer and an online platform. As an online distributor of the manufacturer, the platform expands the market scale by exerting the platform power. At the same time, to solve the problem of inconsistency between the actual recycling amount and the theoretical recycling amount in the recycling process of waste electronic products, the whole-process supervision of waste products is carried out with the help of blockchain technology, which is difficult to tamper with and is traceable. With the help of differential game theory, four differential game models of manufacturer recycling and platform recycling with and without blockchain are established. The state feedback strategies are derived from Bellman’s continuous dynamic programming theory. Through analytical results and comparative analysis, the adoption conditions of blockchain and the impact of blockchain on the selection of recycling models are obtained. The results illustrated that the introduction of blockchain technology effectively improves the real recycling rate of waste electronics, building trust in consumers, which benefits corporations in certain conditions. However, it amplifies the double marginal effect of the CLSC. Nevertheless, the implementation of blockchain is still beneficial to consumers, as the adverse impact of the double marginal effect is compensated by the improvement in consumer surplus. In addition, the study shows that the implementation of the blockchain incentivizes members, who benefit on the same recycling model when the fixed cost of the blockchain and the share ratio of the residual value of waste electronics are between certain thresholds. That is, both the manufacturer and the platform are better off in a manufacturer recycling model enabled by blockchain. Moreover, in this model, the social welfare and the recycling rate of waste electronics are increased, which enable the CLSC to achieve benefits related to economy, environment, and society.
Considering the significant impact of the reference effect on consumer purchasing decisions and corporate profits, this paper mainly focuses on the influence of the reference effect of consumers in carbon emission reduction (CER) on the platform selling mode selection. To this end, this paper establishes a two-level supply chain consisting of a manufacturer who decides on CER in the production process and an online platform that conducts low-carbon publicity. Four differential game models in which the platform uses reselling mode or agency selling mode with or without consumer reference effect are established. The long-term stable cooperation relationship between the manufacturer and the platform, as well as the consumer surplus and social welfare under four models are further investigated. It is found that the reference effect on the platform selling mode is related to the low-carbon publicity effect and commission rate. When the reference effect exists, the intuition indicates that the platform will choose the reselling mode when the commission rate is relatively low. We clarify this result under the condition that the publicity effect is high. However, the manufacturer also prefers platform reselling, which is counterintuitive. When the commission rate is in the middle range, the platform chooses the agency selling mode, which is in line with the preference of the manufacturer. Surprisingly, when the platform’s publicity effect is low, the manufacturer and the platform reach stable cooperation in reselling mode when the commission rate is low or high, which is also counterintuitive. When the commission rate is in the middle range, they both prefer the agency selling mode. In addition, it is suggested that the triple benefits in economy, environment, and society are achieved as the optimal selling mode is confirmed in the presence of consumer reference effect in CER.
In order to solve the problem of false recycling, where the real recycling volume does not match the theoretical one, blockchain is widely used in practice due to its characteristics of transparency, traceability, and tamper resistance. To study its value in academics, this paper focuses on a closed-loop supply chain (CLSC) consisting of a manufacturer and an online platform. This paper discusses the implementation conditions of blockchain, the impact on enterprise decision making, and manufacturer recycling channel selection, and the triple benefits of economy, environment, and society in the CLSC with blockchain empowerment are achieved. Because of the nontransparency of the supply chain, the problem of false recycling is always present. To further solve the problem of false recycling, the recycler decides whether to implement blockchain or not. Through analysis and numerical examples, it is concluded that the greater the difference between real and theoretical recycling volumes, the greater the need for blockchain implementation. At the same time, three major effects of blockchain implementation are defined as decision incentive effect, marketing leverage effect, and incentive alignment effect, which reveal the impact of blockchain on increasing the motivation of CLSC members to make efforts, expanding the market size by improving brand goodwill, and avoiding the inconsistency between the manufacturer and the platform in the preference of the recycling channel. In addition, under blockchain empowerment, a cost range of blockchain implementation is defined, where both the manufacturer and the platform are better off, as well as the optimal recycling channel, which achieves the triple benefits of the CLSC.
Government subsidies have played an important role in the development of green agriculture. In addition, the Internet platform is becoming a new channel to realize green traceability and promote the sale of agricultural products. In this context, we consider a two-level green agricultural products supply chain (GAPSC) consisting of one supplier and one Internet platform. The supplier makes green R&D investments to produce green agricultural products along with conventional agricultural products, and the platform implements green traceability and data-driven marketing. The differential game models are established under four government subsidy scenarios: no subsidy (NS), consumer subsidy (CS), supplier subsidy (SS), and supplier subsidy with green traceability cost-sharing (TSS). Then, the optimal feedback strategies under each subsidy scenario are derived using Bellman’s continuous dynamic programming theory. The comparative static analyses of key parameters are given, and the comparisons among different subsidy scenarios are conducted. Numerical examples are employed to obtain more management insights. The results show that the CS strategy is effective only if the competition intensity between two types of products is below a certain threshold. Compared to the NS scenario, the SS strategy can always improve the supplier’s green R&D level, the greenness level, market demand for green agricultural products, and the system’s utility. The TSS strategy can build on the SS strategy to further enhance the green traceability level of the platform and the greenness level and demand for green agricultural products due to the advantage of the cost-sharing mechanism. Accordingly, a win-win situation for both parties can be realized under the TSS strategy. However, the positive effect of the cost-sharing mechanism will be weakened as the supplier subsidy increases. Moreover, compared to three other scenarios, the increase in the environmental concern of the platform has a more significant negative impact on the TSS strategy.
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