E-business system investment for fresh agricultural food industry in China.

A fresh agricultural food online exchange system is gradually becoming an emerging e-business model in China. However, how and when to make an investment in this new business model is risky due to the unique characteristics of fresh agricultural food. In this paper, from a third party decision maker's perspective, we propose an evolutionary discounted cash flow model to investigate the optimum time point for investment. Based on the assumptions of base demand, the derived e-demand occurring on the pendent e-business system can be characterized by non-stationary stochastic processes. Then our new model can further be innovatively analyzed by considering the dynamic scheme of the cash flow and its evolution. The analytical results suggest the optimal investment time point depends upon the consumers' switch rate from the physical store to e-store and on the urbanization rate. A Monte Carlo simulation is further presented to compare the effects of multiple uncertainties embedded into the system. Our uncertainty analysis reveals that when government financial support fluctuates greatly, the optimal investment time could be either in the very beginning or in the end. This optimal time strategy also holds for the random demand factor after the coefficient variation of the demand reaches a certain threshold. [ABSTRACT FROM AUTHOR]