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

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4 Author(s)
G. Peter Zhang ; Robinson Coll. of Bus., Georgia State Univ., Atlanta, GA, USA ; Craig A. Hill ; Yusen Xia ; Faming Liang

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.

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IEEE Transactions on Automation Science and Engineering  (Volume:7 ,  Issue: 1 )