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Research On Pricing Decision Of Garment Supply Chain Considering Low Carbon And Marketing Input

Posted on:2021-08-16Degree:MasterType:Thesis
Country:ChinaCandidate:M N ShiFull Text:PDF
GTID:2491306467475184Subject:Master of Engineering
Abstract/Summary:PDF Full Text Request
In the new era,people’s environmental protection concepts are gradually increasing,and the demand for low-carbon products in the market is also gradually increasing.In order to meet the needs of consumers,clothing companies actively invest in low-carbon technology and produce low-carbon and environmentally friendly clothing products to increase corporate profits.The entry of low-carbon and environmentally friendly products into the market has become one of the ways for clothing companies to obtain profits.In the complex competitive environment of the market,the issue of price competition among oligarchs has always been a key issue of concern to business managers and a hot issue of academic research.This paper combines relevant domestic and foreign research and key issues in the development of China’s apparel manufacturing industry,using game theory and nonlinear dynamics theory to conduct theoretical research on the long-term and dynamic price game of enterprises,and put forward applied opinions.It explains the impact of low-carbon and marketing investment of enterprises on the pricing of enterprises and price games between enterprises from many aspects,and provides some practical references for the managers of Chinese apparel enterprises.From the macro and micro level,this article systematically thinks about the development dilemma,path and methods of China’s garment manufacturing industry from large to strong,and provides basic reference value for my country to promote the upgrading of green industry.The main work of this paper is as follows:1.In the supply chain composed of manufacturers and retailers,clothing manufacturers invest in low-carbon technology,and retailers make marketing efforts in offline channels;and both clothing manufacturers and retailers have risk aversion behaviors.This section first calculates the optimal pricing of the enterprise;analyzes the influence of the enterprise’s carbon emission reduction,marketing efforts and risk tolerance level on the optimal pricing.Based on the theory of system dynamics,a dynamic game system is constructed and the Nash equilibrium point and equilibrium conditions of the system are analyzed.Using numerical simulation methods,research and analyze the impact of the company’s carbon emission reduction,marketing efforts,and risk tolerance on the stability domain of the dynamic system under equilibrium conditions;analyze the impact of the company’s price adjustment speed and behavior on the price and utility of the dynamic system;The study found the existence of chaos,analyzed the characteristics of the system in the chaotic state,and the changing trend of the enterprise’s utility when the system was in the chaotic state.Finally,parameter control method and variable feedback control method are used to effectively control the chaotic phenomenon of the system.Studies have shown that the higher the level of carbon emission reduction and marketing efforts,the higher the optimal price of the company,and the market’s stability range will increase accordingly;when the level of carbon emission reduction is maintained at a certain value,it is conducive to the maximum utility of clothing manufacturers The large price adjustment speed of the enterprise will cause the system to lose stability and fall into chaos.The chaotic market will destroy the utility of retailers.However,the utility of clothing manufacturers will be improved in this state.The parameter adaptive control method can more effectively return the system to the original stable state.2.Based on the supply chain composed of manufacturers and retailers,this section further discusses the situation of apparel manufacturers opening a live webcast channel in the supply chain.First,build a model to calculate the optimal pricing of retailers and webcast platforms,and establish a dynamic game system to study the price game between enterprises.In the dynamic system,the stability region of the dynamic system under equilibrium conditions is simulated through numerical simulation,and the influence of carbon emission reduction level on the stability region of the system is analyzed;the Lyapunov index diagram and bifurcation diagram are used to analyze the price adjustment speed of the enterprise The impact on the price and profit of the dynamic system,as well as the impact of carbon emission reduction and marketing efforts on corporate profits;the average utility diagram is used to study the changes in corporate profits when the system is in a state of chaos;through the attractor and initial value sensitivity diagrams The characteristics of the system in the chaotic state.Finally,this section adopts parameter adaptive control method to control the chaotic state of the system with significant effect.Research shows that the stability range of the system will increase as the level of carbon emission reduction increases;in the process of price game,the greater the price adjustment speed of the enterprise,it will only make the system more likely to lose stability and eventually fall into chaos.The increase in marketing efforts makes the profits of retailers increase first and then decrease;the increase in carbon emission reduction levels will gradually increase the profits of manufacturers,while the profits of retailers and webcast platforms will gradually decrease.When the system is in a state of chaos,the profits of the three will gradually increase.Decrease,parameter adaptive control method has a good control of the chaotic phenomenon of the market in this situation.This article provides a certain reference value for the pricing decisions and related decision-making issues of my country’s apparel companies when they invest in low-carbon technology and marketing.
Keywords/Search Tags:low carbon, marketing efforts, clothing supply chain, price game, chaos control
PDF Full Text Request
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