Evaluation Of B2B E-Commerce Enterprises' Competitiveness Based On BP Neural Network

With the development of the Internet era,China's e-commerce companies have achieved rapid development with this gusty exit.At the same time,competition among e-commerce companies is also increasing,especially B2B e-commerce companies.After experiencing the era of information display and online trading,now the companies are embracing the era of big data and cloud computing.Number of companies that have been eliminated by the times are not counted,and companies standing at the forefront of the industry are also scared,because in such an era of technological innovation and rapid business model iterations,missing the chance means being replaced as soon as possible.In this background,improving the competitiveness of enterprises has become a top priority.How to evaluate and improve the competitiveness of B2B e-commerce enterprises and promote the orderly and healthy development of B2B e-commerce industry is the main research purpose of this article.This article systematically summarizes the relevant theories of enterprise competitiveness,the current development status of B2B e-commerce industry and related theories of B2B e-commerce companies and their competitiveness.It summarizes that resources,performance,growth and technological innovation are the four major factors affecting the competitiveness of B2B e-commerce companies.Based on the principle of systematicness,scientificity,and effectiveness principle,a five-level index consisting of the scale of a company,effectiveness,financial capabilities,growth capabilities,technological capabilities with 16 secondary indicators constitutes a set of B2B e-commerce enterprise competitiveness evaluation index system.After a comprehensive comparison of the evaluation methods,this paper finally uses the BP neural network evaluation model to evaluate the competitiveness of B2B e-commerce companies.This paper analyzes the algorithm flow and neural network structure of BP neural network,determines the number of nodes at each layer,activation function and training function.Taking 23 listed B2B e-commerce companies in our country as samples,this paper utilizes total assets,total number of employees,total sales,operating net profit ratio,return on total assets,return on net assets,total operating revenue growth year-on-year,current ratio,quick ratio,debt ratio,fixed asset turnover,asset growth rate,total asset net margin,brand value,R&D staff,R&D investment as a percentage of total sales,etc.to evaluate the competitiveness of B2B e-commerce companies.The BP neural network evaluation model was constructed with the aid of the neural network toolbox of Matlab.The neural network was trained and tested with 23 corporate sample data.Finally,the competitive value of B2B e-commerce enterprise was obtained with the trained network and the evaluation results were analyzed.The company pointed out the advantages and disadvantages and provided suggestions for improvement.In this paper,BP neural network is used for the first time to study and evaluate the competitiveness of B2B e-commerce enterprises.After analysis and verification,it can be seen that the use of BP neural network evaluation methods to analyze and evaluate the competitiveness of B2B e-commerce companies is reasonable and scientific.This method also has certain applicability in evaluating the competitiveness of other industries.It is only necessary to use the neural network model already trained in this study to modify the relevant data of the input layer.According to the specific conditions of the industry,the output value of the enterprise's competitiveness in the industry can be obtained.The company can be classified according to the relevant results and compared with each other.The competitiveness between enterprises,to identify the main factors affecting the competitiveness of enterprises in order to enhance their own competitiveness.