Research On The Early-warning Management Of Enterprise Reverse Logistics System

Faced with the challenge of the deteriorating natural environment, the predicament of the difficulty in gaining resources and the increasingly diverse demands of consumers, enterprises have to look for new profit sources. Thus reverse logistics has been paid more and more attention by different countries and enterprises. But the status of implementing reverse logistics in China is not ideal. One of the reasons is the inherently uncertainty of reverse logistics which causes bigger risk. Therefore this paper studies the risk early-warning management of enterprise reverse logistics based on the basic theories of reverse logistics and early-warning management.This paper firstly proposes research background and research significance, and sums up research situations on reverse logistics among domestic and foreign scholars. According to the connotation and characteristics of reverse logistics and the connotation of risk early-warning management, it proposes the connotation and characteristics of reverse logistics early-warning management, identifies the types of reverse logistics and builds the process and systematic structure of risk early warning for reverse logistics. Based on identifying reverse logistics risks, it builds the initial risk early-warning indicator system and uses the software SPSS to screen the initial indicator system to get the finial indicator system with the data obtained by the questionnaires. Compared to other risk evaluation methods, it selects BP neural network to build the risk evaluation model of reverse logistics and uses MATLAB 6.5 to build, train and check the model, which is validated by the data obtained by questionnaires. It proposes the different pre-control strategies according to the different level of risks so as to form the strategy library of risk early-warning system of reverse logistics. This paper aims to provide enterprises with a set of systematic, scientific and reasonable risk early-warning management tools to avoid the risks in reverse logistics system, reduce the loss of enterprises and promote the implementation of reverse logistics.