| Since the second industrial revolution,the rapid increase of global greenhouse gases,the rising of land and sea surface temperature,lead to the melting of ice and snow,the rise of sea level,which shows us an unprecedented real disaster "large area".With the introduction of low-carbon policies by governments,the gradual formation of consumer awareness of environmental protection and low-carbon consumption,the manufacturing industry invests in research and development of emission reduction while producing products.In the face of the enhancement of consumers’ low-carbon preferences,enterprises also have to consider the behavior preferences of supply chain members.Fair concern has become a research hotspot of the combination of supply chain management and limited behavior theory.A large number of experiments and theories show that fair concern has an important impact on the decision-making of supply chain.In this context,in order to make the theoretical study of low-carbon supply chain decision-making more suitable for the actual operation,this paper considers the behavior preference and carbon limit trading mechanism of supply chain members in the three-level low-carbon supply chain,and explores the optimal decision-making of supply chain members under different fairness concerns by using the theoretical basis and methods such as operation research,game theory,maple solution and numerical analysis The emission reduction and pricing decisions of chain members provide theoretical basis.The main research work of this paper is as follows:Firstly,based on the Nash bargaining model,the utility function of fairness concern in the three-level low-carbon supply chain is re characterized;secondly,considering that demand is affected by emission reduction level,price and consumers’ low-carbon preference,the utility function is used to construct the demand and profit function dominated by manufacturers,and the reverse induction method is used to obtain that only manufacturers have fair preference,only distributors have fair preference Well,the mathematical expression of the optimal decision-making of supply chain enterprises is only under the four situations that retailers have fair preference and supply chain members have fair preference.Thirdly,according to the solution results,the influence of unit carbon quota,fair preference and carbon price on the emission reduction and pricing decision-making of supply chain members is quantitatively analyzed,and the emission reduction level of manufacturers under different fair preference is comparedThe main conclusions are as follows:For manufacturer’s emission reduction,under different fairness concerns,the level of manufacturer’s emission reduction is positively correlated with unit carbon quota,and negatively correlated with fairness concerns.That is,when any enterprise in the supply chain has a fair preference,it is not conducive to the manufacturer’s input cost for emission reduction research and development;From the perspective of pricing decisions of supply chain members:under different fairness concerns,the impact of unit carbon quota on pricing decisions of manufacturers,distributors and retailers is related to carbon price.Under different equity concerns,the impact of equity concerns on pricing decisions of manufacturers,distributors and retailers is different;As far as the profits of supply chain members are concerned,the larger the unit carbon quota is,the larger the profits will be for manufacturers,distributors and retailers.Only when the manufacturer has a fair preference,and the greater the degree of fair preference,the more profits the manufacturer obtains,the greater the impact on the profits of distributors and retailers;Different from only manufacturers having fair preferences,under the circumstances that only distributors have fair preferences and only retailers have fair preferences,the fair preferences of distributors and retailers are not always beneficial to themselves,which is related to carbon price and their fair preferences,and will impact the profits of other members of the supply chain. |