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Grandfathering and benchmarking are two typical free carbon permits allocation methods used in the carbon cap-and-trade mechanism. These emission regulations would generate carbon cost and hence make the firm's manufacturing and remanufacturing production decisions more complex. In this paper, we developed two models to contrastively evaluate the effectiveness of grandfathering and benchmarking methods on motivating the monopolist manufacturer to adopt low carbon remanufacturing practice in two periods. In the first period, the manufacturer produces completely new products without restrictions of carbon emission, while in the second period, the manufacturer can use collected returns derived from the first period to produce remanufactured products with carbon emission constrained by grandfathering or benchmarking regulation. We further analyzed the impact of carbon price, carbon emission saving per remanufactured product, and technology improvement on the production decisions. Our results indicate that the benchmarking method can more effectively motivate the manufacturer to adopt the low carbon remanufacturing production than the grandfathering method. We also find that the carbon price and carbon emission saving per remanufactured product would also affect the manufacturer's remanufacturing production decision. [ABSTRACT FROM AUTHOR]

Abstract: The aim of this paper is to explore the impact of subsidy policies on the development of the recycling and remanufacturing industry in China using system dynamics methodology and by simulating Chinese auto parts industry. Firstly, we introduced four subsidy policies – initial subsidy, recycling subsidy, R&D subsidy and production subsidy – and established system dynamics models to characterize the remanufacturing dynamics system considering government subsidies. Then we analyzed the impact of four subsidy policies and mixed-subsidy policies individually and comparatively based on Chinese auto engine remanufacturing on recycling and remanufacturing activities. The results showed that varied subsidies have different incentive objectives and characteristics. The initial subsidy plays an active role in improving remanufacturing activities and is suitable to be used at the initial stage of industry development. When the remanufacturing industry develops to a certain extent, the production subsidy or R&D subsidy can reasonably control the quantity of remanufacturers and maintain remanufacturing industry scale and stability. The recycling subsidy plays a significant role in overcoming the bottleneck problem of “lack of cores”. The mixed-subsidy policies have the better positive effects on remanufacturing promotion than single subsidy policies, but involve higher costs. [Copyright &y& Elsevier]

Using the Stackelberg game theory, this paper evaluates the effectiveness of four subsidy schemes on the product eco-design and recycling rate in a manufacturing–recycling system that comprises a government, a manufacturer and a recycler. The principal results are: 1) For the cost-based subsidies, a fixed-cost subsidy to recyclers always yields higher recycling rate and social welfare. For the performance-based subsidies, the effects are closely related to market demand and the fixed cost coefficients of eco-design and recycling. Governments should select subsidy schemes according to the specific goals and market conditions. 2) Four subsidy schemes are the effective forces to promote product eco-design and recycling. Higher subsidy intensity brings better supply chain profits and better environment performance, but it does not always bring better social welfare. 3) Eco-design can increase waste recycling rates effectively, and recycling rates are more sensitive to eco-design when the government subsidizes the fixed costs of recyclers. [Display omitted] • Two cost-based subsidies and two performance-based subsidies are considered. • Government subsidy is useful to promote product eco-design and recycling. • For cost-based subsidy, government can prioritize recycler fixed cost subsidy. • For performance-based subsidy, government can adjust scheme with varied conditions. [ABSTRACT FROM AUTHOR]

Remanufacturing industry can solve the issues of resource depletion and environment deterioration by reducing consumptions of raw materials and minimizing emissions of wastes. It has been strongly promoted by Chinese government in recent years. However, its current development situation has been unsatisfactory all the time. The aim of this paper is to evaluate development level of remanufacturing industry of China and point out future directions of industrial improvement. To achieve the above objective, this paper establishes an evaluation index system of remanufacturing industry and puts forward an improved grey fixed weight clustering method, which is suitable for assessing remanufacturing industry. Then taking Jiangsu Province of China as a practical case, this method is used to evaluate its remanufacturing industry and identify rank order of improvement measures for each city. Research results show that overall development level of remanufacturing industry is still low and development unbalance is remarkable. Two more important findings are as follows: The first is that rank orders of improvement measures for all cities are different from each other and decision maker should adopt differentiated industrial policies and improvement measures. The second is that the cities which belong to the 2nd and 3rd grey class should paid more attention to improvement measures for four evaluation sub-indices: Annual sale of remanufacturing industry, Total assets of remanufacturing enterprise, Total investment of under construction and Total number of research institution and university participated in remanufacturing. The major contribution of this study is to offer an effective decision-making approach for evaluation of remanufacturing industry. It helps in classifying development levels of remanufacturing industry in different cities and providing decision makers with a scientific basis for adopting appropriate industrial policies and improvement measures, which will efficiently enhance remanufacturing industry in the future. [ABSTRACT FROM AUTHOR]

Abstract A hybrid manufacturing/remanufacturing system (HMRS) is an effective tool to address the global challenge of resource depletion and environmental deterioration. This paper aims to make an optimal production plan for a stochastic HMRS with demand substitution. To achieve the above objective, a multi-period mixed integer programming model was first constructed. An ant colony system algorithm with random sampling method (ACS-RSM) was proposed to minimize the total expected cost of the stochastic HMRS. Finally, the proposed model and ACS-RSM algorithm were applied to an auto alternator case. The effects of the used product recovery rate and batch sizes of new and remanufactured products on the total expected cost were analyzed. The research results showed that the ACS-RSM algorithm performed well regarding computational efficiency and solution quality. There were two major findings through the practical case study. The first finding was that with increase of recovery rate of used product, total expected cost of the HMRS declined dramatically until a certain point. When the recovery rate was greater than 91%, the total expected cost kept almost constant. The second finding was that when the batch sizes of the new product and remanufactured product rose, the total expected cost had an obvious increase and the running time of the ACS-RSM algorithm decreased monotonically. The study yields an effective decision-making tool for optimizing the production plan of the stochastic HMRS with demand substitution. Highlights • A multi-period mixed integer stochastic programming model for the hybrid manufacturing/remanufacturing system (HMRS) with stochastic demand and return and with downward substitution. • Development of an ant colony system algorithm combined with the random sampling method to determine optimal production plans for the stochastic HMRS. • Business measures for manufacturing/remanufacturing enterprises to coordinate manufacturing and remanufacturing. • A real-world case to validate the model and algorithm and to provide managerial insights. [ABSTRACT FROM AUTHOR]

Remanufacturing is a critical tool for solving resource depletion and environmental deterioration by reducing raw material and embedded energy consumption. The Chinese government, like many other countries, has been keenly interested in remanufacturing during the past ten years, because of its potential material and energy usage reductions. However, the development of the remanufacturing industry has been unsatisfactory because of little knowledge of its key industry indices. Many potential customers of remanufactured products do not trust the quality of remanufactured products. The major objectives of this paper are to classify the key industrial indices of the remanufacturing industry and to suggest future directions for improvements. To achieve these objectives, this paper used a combined method of grey incidence analysis and grey clustering, which are suitable for distinguishing critical industry indices that can measure the status of development situation of the remanufacturing industry. This approach was successfully applied to a case in Jiangsu Province, China, and consequently developed useful governmental and industrial policy recommendations for remanufacturing enterprises to promote that industry. The research results identified the “total number of employees with a master's degree or above”, the “total number of engineering and technical staff” and the “number of intermediate technicians” as the most appropriate industry indices to reflect the development situation of the remanufacturing industry in China. There are two more important findings. The first is that remanufacturing talents are the most important internal impetus of the remanufacturing industry and should be paid more attention to. The second is that investment in the remanufacturing industry does not have a strong positive correlation with industry characteristics. The “annual revenue of the remanufacturing industry” and huge investment have not played an effective role in promoting this industry so far. The main contribution of this paper is to provide an effective decision-making tool for defining key industry indices that have an important effect on the remanufacturing industry. The tool provides decision-makers a scientific basis for developing and implementing appropriate industry policies and improvement measures to expand the size and scope of the remanufacturing industry in the future. [ABSTRACT FROM AUTHOR]

Main objectives of this research are to investigate the effect of different power structures and product dual differences, quality difference among used products and price difference between new ad remanufactured products, on pricing policies of a multi-echelon closed loop supply chain (MCLSC) and to propose future improvement strategies. To achieve these objectives, centralized and decentralized pricing models for the MCLSC were constructed to explore optimal member pricing and optimal profit under different power structures: centralized, Manufacturer-led Stackelberg (MS), Retailer-led Stackelberg (RS) and Collector-led Stackelberg (CS) pricing models and to analyze the impact of three key parameters, collection rate, cross-price elasticity coefficient, and quality grade ratio of used products. By comprehensive theory comparisons and a case study of auto alternators, the results of theoretic analysis indicated three insights. (1) The centralized pricing model always achieves the maximum total profit of the MCLSC, but the CS model obtained a minimum total profit. (2) For three decentralized pricing models, the optimal wholesale price and optimal retail price for new product and remanufactured product all increase with the collection rate and cross-price elasticity coefficient. For MS model and RS model, however, optimal acquisition price for used product decrease with the two parameters. (3) The optimal wholesale price and optimal retail price for new product rise up with the quality grade ratio in each decentralized pricing model. There are also three important findings from the case study. (1) When the collection rate is increased, the optimal total profit shows a U- shaped curve, with a profit trap around a certain collection rate. (2) The optimal acquisition price drops slightly with the cross-price elasticity coefficient, but the optimal wholesale price and optimal retail price increase sharply. This causes a benefit conflict between MCLSC members and consumers. It is recommended that the cross-price elasticity coefficient should be carefully controlled under a certain value to relieve the conflict. (3) When the quality grade ratio increases, optimal profits for all member and the system all increase and have a shell shape. They reach approximate maximum when remanufacturing ratio was raised to 95%. Major contributions of this paper are an effective decision tool for optimal pricing decisions of the MCLSC and insights for appropriate industrial policies and enterprise strategies to enhance the performance of the MCLSC. ● Considerations on quality difference of used products and price difference of new and remanufactured products. ● A centralized pricing model and three decentralized Stackelberg pricing models for the multi-echelon closed-loop supply chain (MCLSC). ● Identification of the impacts of three key parameters (including collection rate, quality grade ratio and cross-price elasticity coefficient) on optimal pricing and profits. ● Industrial policies and business measures for governments and all members of MCLSC. ● A real-world case to validate the model and to provide managerial insights. [ABSTRACT FROM AUTHOR]