The emergence of e-commerce and express delivery services has significantly transformed business operations and consumer shopping experience. However, the resulting problem of packaging waste, particularly from overpackaging, poses serious challenges to environmental sustainability and human health. Existing research has proposed many solutions from various perspectives, but very few have considered the acceptability and consumer preference for these proposals. Using the value co-creation (VCC) theory, we established a research model to explore consumer preferences for e-commerce overpackaging solutions. A survey of 632 online consumers in Guangzhou and Shenzhen was conducted, and data were analyzed using the SmartPLS software. The results show that establishing a recycling system, government policy, and consumers’ environmental awareness have a significant positive impact on consumer preference, while combined packaging has a significant negative impact. We also found that government policy plays an intermediary role in establishing a recycling system and consumer preference. Based on these findings, we recommend that enterprises establish and improve their packaging recycling systems and that e-commerce platforms provide alternative options to combined packaging. Also, the government should play a guiding and coordinating role for enterprises and consumers, and environmental awareness among consumers should actively be promoted.
Due to the increasing awareness of sustainable manufacturing, remanufacturing has been widely accepted by enterprises in many countries. In the process of Closed-Loop Supply Chain (CLSC) development, to stimulate the demand for remanufactured products, the Chinese government’s interventions such as the “Trade old for Remanufactured” program cannot be ignored. However, prior research has not answered the questions of whether governments should offer consumption subsidies and how to determine the optimal subsidy value. This paper investigates the optimal government consumption subsidy policy and its impact on the operation of Closed-Loop Supply Chain (CLSC) where an Original Equipment Manufacturer (OEM) produces new products, while a Third-Party Remanufacturer (TPR) remanufactures the used products collected from consumers. A game model with a leader (government) and two followers (OEM and TPR) is then introduced. The government determines the consumption subsidy to maximize the social welfare, while the TPR and OEM attempt to maximize their own profit functions. Game theoretic models are proposed to explore and compare the scenarios, i.e., CLSC with a consumption subsidy policy and without a consumption subsidy policy. The equilibrium characteristics with respect to the government’s consumption subsidy decisions and the price decisions for chain members are derived. Based on the theoretical and numerical analysis, the results show that: (1) governments should not always offer a consumption subsidy; (2) the consumption subsidy cannibalizes demand for new products while boosting the demand for remanufactured products; (3) the consumption subsidy should be shared between the TPR and consumers when the TPR raises the sales price of remanufactured product; (4) the members of the CLSC do not always benefit from the consumption subsidy policy.
Closed-loop supply chain (CLSC) management faces collection and remanufacturing cost disruption challenges. This study explores a CLSC system wherein original equipment manufacturers (OEMs) license the third-party remanufacturer (TPR) to bear the remanufacturing activities and investigate pricing decisions in the CLSC, while considering collection and remanufacturing cost disruptions. To obtain the optimal pricing strategy, we develop game theory models under the disruptions of both centralized and decentralized CLSCs. Based on theoretical and numerical analyses, we obtain the following results: (1) Whether or not disruption events occur, the centralized supply chain can better encourage consumers to participate in the collection of used products than a decentralized supply chain; (2) when collection disruption in a large positive region or the remanufacturing cost disruption in a large negative region occurs, OEM and TPR profits will greatly increase, and the OEM will raise the licensing fee to extract more profit from the remanufacturing activity; (3) a certain robust region exists for the retail price and wholesale price when the supply chain faces disruption increase; (4) when the supply chain faces the disruptions, it has great influence on the OEM’s licensing fee but little on the TPR’s acquisition price. The main contributions of the study include: (1) We considered the impacts of both technology licensing and collection and remanufacturing cost disruption; (2) we developed game theory models to determine the optimal manufacturing and remanufacturing quantities, and pricing strategy under the disruptions; (3) based on theoretical and numerical analyses, we presented some interesting and important insights. The results of this paper could provide useful guidelines for supply chain members on how to effectively control costs to obtain more profit by adjusting prices and selecting a better operation mode for the closed-loop supply chain.
A firm sets up his facilities including manufacturing/remanufacturing plants and distribution/collection centers, incorporating an existing closed-loop supply chain (CLSC) network. The entering firm has to compete with the existing firms in the existing network. The entering firm behaves as the leader of a Stackelberg game while the existing firms in the existing network are followers. We assume that the entering firm can anticipate the existing firms’ reaction to his potential location decision before choosing his optimal policy. We use a CLSC network equilibrium model in which the decision makers are faced with multiple objectives to capture the existing firms’ reaction. A mathematical programming model with equilibrium constraints is developed for this competitive CLSC network design problem by taking into account the market competition existing in the decentralized CLSC network. A solution method is developed by integrating Genetic algorithm with an inexact logarithmic-quadratic proximal augmented Lagrangian method. Finally, numerical examples and the related results are studied for illustration purpose.
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