Abstract—This study analyzed Global Entrepreneurship Monitor (GEM) data from the resource-based perspective and applied the artificial intelligence self-organizing map (SOM) approach to fill the research gap. In this study, 45 countries that participated in GEM from 2005 to 2006 were selected for analysis. Our research found that each of the factors studied in this analysis were influential in entrepreneurial opportunity recognition. Furthermore, the factors result in four specific patterns of entrepreneurs. We examined the stability on the SOM plane of the four patterns of entrepreneurial opportunity recognition. The study reveals interesting patterns of entrepreneurial opportunity recognition in the context of global entrepreneurial activities.

Index Terms—entrepreneurship, entrepreneurial opportunity, global entrepreneurship monitor (GEM), neural network, self-organizing map (SOM). 

Cite:Li-Min Chuang and Shu-Tsung Chao , "Evolution of National Entrepreneurial Opportunity Recognition: A Neural Network Analysis ," Journal of Advanced  Management Science, Vol. 1, No. 1, pp. 66-70, March 2013. doi: 10.12720/joams.1.1.66-70