Data mining usage in Italian SMEs: an integrated SEM-ANN approach

Data mining is the process of knowledge extraction from the data with the algorithms that identify hidden relationships and patterns, which are usually not noticeable at first glance. Data mining has become omnipresent in various domains in the recent decade, but its usage in small and medium enterprises (SMEs) is still under-represented. This paper investigates the determinants of data mining usage in SMEs using the TOE Framework (Technology-Organisation-Environment). A model has been proposed to test the impact of individual components of the TOE framework on the intensity of data mining and, in turn, test the effect of data mining implementation on business performance. The survey has been carried out on a sample of small and medium-sized Italian enterprises. Two methodologies have been used to analyze structural equation modeling (SEM) and artificial neural networks (ANN). Using a hybrid SEM-ANN methodology, hypotheses were tested. It was shown that the TOE framework could explain the intensity of knowledge discovery use in databases, utilizing the importance-performance map analysis to reveal the significance and performance of each determinant.