Modeling the Relationship Between EDI Implementation and Firm Performance Improvement With Neural Networks

This paper examines a number of electronic data interchange (EDI) usage and implementation factors and their role in improving a firm's efficiency, productivity and competitiveness. Unlike other studies in the literature that use exclusively linear models, we apply nonlinear neural networks to model the relationship between performance improvement and a set of predictor variables of EDI usage and supply chain coordination activities. A variable selection method is employed to identify key factors to predict a firm's operational excellence due to EDI implementation. In addition, a bootstrap resampling scheme is used to evaluate the robustness of the results.