Cultivation And Optimal Control Design For Supervision Of E-commerce Platform Market

At present,online shopping has become a trend among young people,and the economy of ecommerce platforms has already penetrated into all aspects of social life.Research on how to govern platforms through regulatory and control measures,and how to evolve the platform to its expected state,has attracted the attention of many well-known scholars both domestically and internationally.This article studies platform evolution from the perspective of automatic control and discusses optimal control design.Based on the evolution of the e-commerce platform market,research and design the optimal control for maximizing platform revenue.Using evolutionary game theory to characterize the relationship between platform pricing control strategies and platform status,in order to solve the decision-making problem of maximizing platform revenue.Propose a dynamic control strategy for platform pricing: when the platform pricing control value is greater than zero,it represents changing the platform status by adopting a penalty control strategy against the seller;When the platform’s pricing control quantity is negative,it represents a change in platform control by adopting a subsidy strategy for sellers.By analyzing the role of platform pricing control strategies at different stages,taking into account control effectiveness and control costs,a constrained allowable control set is proposed as the optimal control scheme.Then,the optimal analytical solution of the optimal control system model is calculated using Pontryagin Maximum Principle.Using Python 3.9 software for numerical simulation,draw a conclusion on how to efficiently cultivate the high-quality e-commerce platform market under optimal pricing control.Finally,based on the conclusion of cultivating the e-commerce platform market under optimal pricing control,by dividing sellers into honest sellers and fraudulent sellers,we propose control measures for cultivating the e-commerce platform market and further study how to govern the platform.Using Python 3.9 software for numerical simulation,obtain the conditions for achieving the maximum expected revenue of the platform,and verify the correctness of the scheme.The specific work is as follows.(1)Research on the Evolutionary Game of E-commerce Platform Market CultivationBased on evolutionary game theory and optimal control theory,this paper abstracts the e-commerce platform market into an idealized model for research.Firstly,make reasonable assumptions,construct a payment matrix,and calculate the benefits of each participant.In order to achieve the maximum expected revenue of the platform,the optimal pricing control strategy for the e-commerce platform is proposed when the market revenue is optimal.Then,from the perspective of automatic control theory,the evolution analysis of the e-commerce platform market was conducted,providing theoretical analysis for the later research on how dynamic pricing affects the platform state,the stable equilibrium point of platform state,and the consideration of platform investment while ensuring the growth rate of the platform.Secondly,make reasonable assumptions on the evolution game of e-commerce platform market cultivation,and use replicon to dynamically depict the evolution of platform status.The two-dimensional evolutionary game model of seller group and buyer group is established,and the dynamic equation of replicon is obtained according to the evolutionary game assumptions.Finally,solve the evolutionary stability strategy of the two-dimensional evolutionary game model,and combine it with the actual situation to analyze the stability of the results of the e-commerce platform market cultivation evolutionary game model,and provide an allowable control assumption to achieve profit maximization.(2)Design and Simulation Research on the Optimal Pricing Strategy for Cultivating the Ecommerce Platform Market under Platform Pricing ControlThis article proposes the optimal pricing strategy and establishes an optimal control system model based on the study of the evolutionary game of e-commerce platform market cultivation.Firstly,an objective function is introduced to seek the optimal control quantity to minimize the objective function under conditions such as initial conditions,initial state,dynamic constraints,and allowable control.Then,by introducing the Hamiltonian function,the optimal control system model is solved.In order to facilitate theoretical analysis and decouple the dynamic system reasonably,a complex and multidimensional problem is simplified to calculate the analytical solution of the optimal control.Using Python 3.9 software,conduct numerical simulations on the main indicators characterizing the evolution of the e-commerce platform market.Research shows that within the allowable control range of platform pricing,as the weight increases,the influence time of the upper and lower control limits on the state equation becomes shorter,the time for the number of sellers entering the platform to reach the optimal value becomes shorter,and the number of sellers entering the platform reaches the optimal value becomes larger,resulting in better control effects.From the perspective of cost reduction,smaller platform pricing controls are more cost-effective and yield higher output.From the perspective of platform governance,implementing subsidy control on sellers during the platform cultivation period can quickly expand the platform;During the platform boom,punishing and controlling illegal sellers can reduce the sellers’ moral hazard behavior,thus reducing buyers’ adverse selection and promoting the platform boom.(3)Design of Supervision and Control for E-commerce Platform Market Based on Rewards and PunishmentsTo further study platform regulatory issues,reduce seller fraud,and create a high-quality platform.We subdivide the seller group into honest sellers and fraudulent sellers,and propose a reward and punishment strategy for market supervision and control of e-commerce platforms.By simulating the market evolution control model of e-commerce platforms under initial and optimized parameters,we calculate the conditions for the platform to achieve maximum revenue.Research has shown that in order for a platform to achieve maximum revenue,the quality of products sold by sellers in the platform market needs to be targeted.At the same time,regulatory measures should be taken to regulate fraudulent behavior and cultivate high-quality sellers.The platform adopts a reward and punishment mechanism to govern the platform,and increases the punishment for violations,which can attract more high-quality buyers and sellers to enter the platform and expand platform revenue.By analyzing the simulation results,the evolutionary game results are consistent with the expected research objectives,and the reward and punishment strategies for e-commerce platform market regulation and control are reasonable and efficient.