Data Exchanging Logistics Information Platform User Growth Influence Factors And Effect Mechanism Research

With the logistics industry rapidly development in our country, the logistics cost is driving more and more attention by the government and the social. As an important way to reduce the logistics cost, logistics information technology are paid more attention by the government and enterprises. But currently, our country’s logistics information level is not high, all kinds of logistics information system and platform operated independently formed many isolated information island, so information transfer between them are not smoothly, which has seriously blocked our country’s logistics development. Data exchanging logistics information platform whose main function is data exchanging, it can use electronic data interchange (EDI) technology to solve the problem that different system and platform transfer information between each other. Currently, as the construction and operating of our country’s data exchanging logistics information platform is just beginning, its’operating system are not perfect and lack of studying on its’mechanism and law of customer growth, which prevent its’ development. So, studying the influence factors and effect mechanism of exchanging data logistics information platform’s customer growth to guide the development of it has seriously meaningful.In this paper, according to the different function position of the exchanging data platform, dividing the platform to supervision platform and service platform to study. Taking Zhejiang E-port as the example of supervision and Logink as the example of service platform.Firstly, summarizing the factors of the two kind platform and analysising their interaction relationship. Layered the factors through the interpretative structural modeling to find the key factors.Then, select the indexes of the key factors and using the grey relational analysis method to analysis the relationship changing between the indexes and factors and the platform’s customer growth, summarize the trend of the relationship of the two kinds platform’s factors with their customer growth.Finally, building the customer growth neural network modeling of the two kinds platform with the history data of the indexes of the factors and forecasting the trend of the two kinds platform’s customer with the neural network through hypothesis and summarize the mechanism of the factors influence the two kinds platform’s customers’ growth, at the same time, analysis the development countermeasures of the two kinds platform.