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Top1. Introduction
With the application and popularization of the Internet and electronic payment, the e-commerce industry is developing rapidly, and at the same time more and more information is gathered, e-commerce has entered the era of information explosion. While a large amount of information provides users and enterprises with diversified choices and marketing methods, the problem of information overload inevitably arises: From the perspective of users, users are at a loss when faced with more and more choices. It is impossible to lock in the items you want to buy as soon as possible; from the perspective of the enterprise, the influx of massive information makes it impossible for the enterprise to store and use it in time, and it is difficult to extract effective information to support decision-making, causing the loss of users and capital. At the same time as these difficulties appear, e-commerce big data platforms and e-commerce recommendation systems have emerged and gradually developed, becoming the main and effective methods for the current e-commerce massive data storage and processing and precision marketing.
How to choose to cooperate with high-quality suppliers is very important for enterprises. Deciding which suppliers to cooperate with is also a major decision for enterprises. The sound development of enterprises is closely related to the products supplied by suppliers. Therefore, e-commerce enterprises A scientific and reasonable selection mechanism must be adopted to reach strategic partnerships with high-quality suppliers. In order to reduce the risk of the enterprise supplying products, it is impossible to cooperate with inferior suppliers who have poor evaluation and product quality that does not meet the standards. In addition, we must also consider the procurement risks caused by market pressure and social and political factors. We must choose from a scientific and strategic perspective to cooperate with suppliers with good reputation and strength, and jointly develop the overall efficiency of the enterprise with high-quality suppliers to promote long-term stable operation of the enterprise.
Li X analyzes the short-term and long-term effects of the breadth and depth of seller competition on the performance of platform companies, and studies the potential mechanism of customer two-way marketing strategies on the competitive structure between sellers. It adopted a longitudinal research design and collected 250 days of data on an e-commerce platform. Daily market target data, and use vector autoregressive model to analyze the dynamic evolution effect, so as to compare short-term and short-term differences. The long-term effectiveness of different customer relationship management (CRM) strategies, survey results-The breadth of competition among sellers improves the performance of the platform, and the depth of competition among sellers has a positive impact on short-term performance. However, this has a negative impact on the long-term performance of its platform (Li et al., 2016). Supplier evaluation and selection are the central issues of supply chain management (SCM). However, the data on which the corresponding selection is based in real life is usually inaccurate or vague, leading to the introduction of fuzzy methods. Tavana M proposed a hybrid ANFIS-ANN model to help managers perform supplier evaluation. After aggregating data sets through the Analytic Hierarchy Process (AHP), ANFIS determines the most influential standards for supplier performance. Then, the multi-layer perceptron (MLP) is used to predict and rank the performance of suppliers based on the most effective criteria. However, there are errors in the perception process, resulting in inaccurate results (Tavana,et al., 2016). This research by Veisi H is to determine the sustainability strategies and ethics of Iran’s agricultural and food systems. To represent the views of 57 agricultural stockholders, including former ecologists, agricultural extension and development experts, farmers, and members of the Iranian Society of Agricultural Ecological Sciences (ISSA), the Analytic Hierarchy Process (AHP) was used. Based on the general principles of utilitarianism, rights and virtue models, two levels were selected from three moral methods to develop a hierarchical network. However, the complexity of this level is too high, causing the network to be a bit biased.