Study On Several Issues Of The Evaluation Of ERP Implementation

The implementation of ERP is a complicate systematic engineering and a high cost and risk investment. While more and more enterprises have implemented ERP systems, a few of them succeed. The evaluation of ERP implementation has become a focus problem concerned by both researchers and managers. This paper does research on several issues of the evaluation of ERP implementation and propose some useful models and methods.In accordance with the motivation of ERP implementation, a model composed by four factors is proposed and verified. The result of structural equation modeling shows that top manager and performance are the two most important motivate factors for ERP implementation. Verification shows that the model is reliable and effective.System Selection is important for the success of ERP. This paper proposes an ERP system selection method based on fuzzy DEA. Fuzzy effectiveness of DMUs are calculated and compared and thus the selection of ERP system is fulfilled.The performance of ERP implementation is depend on a number of factors, and these factors often have complicate correlations with the performance of ERP implementation. As a kind of nonlinear model, BP neural network is a valid tool for multidimensional and nonlinear problems. A performance evaluation method for ERP implementation based on BP neural network is proposed. By the self-organizing and self-learning characteristics, the method overcomes the shortage of the traditional expert method and provides a new vision for the performance evaluation of ERP implementation.An ERP success model based on D&M information system success model is proposed. Structural equation model is used to modeling and verify the model. The study shows that the value of ERP system is the most important factor for ERP success.