Foreign direct investment: A genetic algorithm approach

This paper proposes a genetic algorithm (GA) approach as an analytical tool with a carefully defined fitness function for variable selection. Discriminant analysis will be used as a parameter evaluation method for the analysis of inward foreign direct investment (FDI) in China. Results indicate that the proposed GA method is more efficient in classifying "successful or unsuccessful" inward FDI by providing higher accuracy rates while using fewer variables than previous efforts. An implication of this result is that, given a scarcity of resources and the need to promote FDI, the proposed GA may provide a more efficient way to concentrate on those fewer variables found to be important determinants of "successful" FDI inflow.