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Reserach On The Pricing Strategy Of A Enterprise’s Green Product Supply Chain

Posted on:2024-01-04Degree:MasterType:Thesis
Country:ChinaCandidate:J Y ZhengFull Text:PDF
GTID:2531307076490674Subject:Engineering Management
Abstract/Summary:PDF Full Text Request
With the continuous development of the world economy and the continuous expansion of the population,problems caused by excessive dependence on environmental resources appear,thus the concept of sustainable development and environmental consciousness emerge.Due to the particularity of some fast-moving consumer goods industries such as the beauty industry and the huge market demand,the process from product research and development to production and final scrap may have a huge impact on the environment.Therefore,domestic and foreign enterprises in fast-moving consumer goods industry and manufacturing industry have begun to implement green transformation,integrate sustainable concept into supply chain design,and build their own green supply chain.However,there are still some problems and challenges in the construction of enterprise green supply chain.This paper summarizes the current domestic and foreign research results of supply chain starting from the above research background and literature analysis about static pricing,dynamic pricing strategy,green supply chain pricing decision and supply chain pricing decision under advertising input,and summarizes the current research status in related fields.Then,based on the analysis of the current situation and existing problems of the green product supply chain of Enterprise A,A centralized decision-making model of the green product supply chain of Enterprise A consisting of a single manufacturer and a single retailer considering the greenness of the product and the advertising input is established through the mathematical modeling method.Finally,the optimal decision and maximum profit of Enterprise A under different pricing strategies in different models are analyzed respectively.Finally,the influence of parameter changes on model equilibrium decision and optimal profit under different pricing strategies is analyzed and compared by parameter sensitivity analysis and numerical simulation method.The main conclusions are as follows:(1)When the market green sensitivity is low,the static pricing strategy is expected to achieve greater profits for A cosmetics company,but this result does not take into account consumer behavior,so this profit may be optimistic;(2)The more sensitive the market is to green products,the profit of manufacturers and retailers will increase under static pricing and dynamic pricing,but the profit of manufacturers in the first stage may decline under dynamic pricing;(3)The increase of market green preference and advertising sensitivity can increase the optimal decision of all parties in the supply chain and increase the profit.And when the market is more sensitive to greenness and advertising level,dynamic pricing will gain greater profits;(4)Balanced decision-making under dynamic pricing is more sensitive to market changes,and A more sensitive market may prompt A beauty cosmetics company to take the initiative to reduce its product greenness and advertising level.(5)Under the dynamic pricing strategy of enterprise A,the first stage is the main profit source,and the second stage is mainly aimed at selling products to reduce inventory Finally,combining the research conclusions with the characteristics of the supply chain of beauty enterprise A,reasonable suggestions are provided for the improvement and optimization of the supply chain.The research results of this paper provide feasible suggestions for A cosmetics company to formulate reasonable pricing strategies,and provide certain references for the price decision-making of green supply chain in fast-moving consumer goods industry and manufacturing industry,and enrich the relevant research in the field of dynamic pricing and green supply chain.
Keywords/Search Tags:Green product supply chain, Dynamic price, Statical price, Advertisement expenditure
PDF Full Text Request
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