Optimal Strategies Of Electric Vehicle Pricing And Battery Production Capacity Allocation And Recycling

Due to the increasingly prominent issues of energy shortage and environmental pollution,new energy vehicles(NEVs)with advantages of energy-saving and environmental protection are highly valued by governments and the automobile industry.NEVs have become the main direction of the transformation and development of the global automobile industry.Under the governments’ incentive policies,the production,sales and ownership of NEVs,especially electric vehicles(EVs),are increasing every year,but this has also brought about the decision problem of recycling used power batteries.How to effectively manage the closed-loop supply chain of power batteries is one of key issues to promote the sustainable development of EV industry.In view of this,based on the systematic carding and induction of relevant literature,this dissertation discusses the optimal strategies of electric vehicle pricing and battery production capacity allocation and recycling from the perspective of operations management with the game theory.Specifically,the main research work of the dissertation includes the following three aspects:In a monopolistic market,considering a closed-loop supply chain composed of an EV manufacturer,an EV retailer and a third-party battery recycler and considering that the retailer has private demand information,the dissertation considers both demand information asymmetry and recycling competition.There are three modes: no information sharing,sharing information with the manufacturer and sharing information with the third-party recycler.The dissertation investigates the manufacturer’s optimal pricing strategy,the retailer’s optimal sales and recycling strategy and the third-party recycler’s optimal recycling strategy in different modes.By comparing the optimal decision and profit of each member of the supply chain in different modes,the dissertation explores the value of information sharing and designs a compensation mechanism to encourage the retailer to share private demand information.Finally,the dissertation further analyzes the effects of key parameters on the optimal decision and profit of each member of the supply chain through numerical experiments.In a duopoly market where an EV manufacturer and a gasoline vehicle(GV)manufacturer compete,considering battery recycling and government subsidies,based on consumers’ different buying behaviors,the dissertation studies consumers’ vehicle purchase choices,the EV manufacturer’s optimal pricing and recycling strategy and the GV manufacturer’s optimal pricing strategy under two subsidy policies including the vehicle purchase subsidy and power battery recycling subsidy offered by the government.Then the dissertation compares the optimal decision and profit of each manufacturer and the cost of government subsidy.Finally,combined with numerical experiments,the dissertation analyzes the effects of different subsidies ways on manufacturers’ optimal decisions and profits,the government’s subsidy cost,environment and social welfare.In a market where two EV manufacturers compete,considering battery recycling and the cooperation between the two EV manufacturers,that is,a manufacturer(integrated EV manufacturer)allocates partial battery production capacity to its competitor(assembled EV manufacturer).The dissertation studies the optimal battery production capacity allocation and recycling strategy of the integrated EV manufacturer and the optimal ordering strategy of the assembled EV manufacturer in two situations of competition and co-opetition,respectively,and explores the condition under which the two EV manufacturers choose cooperation.In addition,the dissertation further extends the model and studies the optimal strategies of two EV manufacturers in the case of dual-channel procurement and the optimal battery pricing strategy of the integrated EV manufacturer.Finally,the dissertation analyzes the effects of key parameters on the two manufacturers’ optimal strategies,profits and social welfare through numerical experiments.