Differentiation and factor analysis on EDI usage data with an artificial neuromolecular system

It is commonly said that organizations adopting electronic data interchange (to be referred to as EDI) might decrease operational costs and increase competitive advantages. Statistics has been one of the most popular approaches employed to investigate EDI usage by organizations. Previously, we developed an artificial neuromolecular system (to be referred to as the ANM system) that captures biology-like structure-function relationship, and it demonstrated an effective differentiation capability. In this paper, the ANM system is used to investigate why, when, and how an organization adopts EDI. To collect EDI usage data, a questionnaire, consisting of 31 test items, was developed and performed with 1000 EDI organizations in Taiwan, of which 221 effective replies were received. Experimental results show that the ANM system is capable of determining significant and insignificant factors (items) that affect an organization adopting EDI in a self-organizing manner.