This study develops a conceptual system optimization model of adoption of a new infrastructure technology with multiple resource sites and multiple demand sites. With the model, this paper analyzes how the distance, s...This study develops a conceptual system optimization model of adoption of a new infrastructure technology with multiple resource sites and multiple demand sites. With the model, this paper analyzes how the distance, spillover effect, demand, initial investment cost, and learning rate influence the adoption of the new infrastructure technology and presents optimization results of the model in different scenarios. The main findings of the study are： from the perspective of system optimization, （1） different distances among different resource-demand pairs will result in different adoption time of a new infrastructure; （2） technological spillover among different resource-demand pairs will accelerate the adoption of a new infrastructuxe; （3） it is hard to say that higher demand will pull faster adoption of a new infrastructure, and the optimal time of adopting of a new infrastructure is very sensitive to its technological learning rate.展开更多
the financial support of the National Social Science Foundation of China （14ZDA038）;the National Natural Science Foundation of China （71222302;71373255;71573133）;the Institute of Geographic Sciences and Natural Re...the financial support of the National Social Science Foundation of China （14ZDA038）;the National Natural Science Foundation of China （71222302;71373255;71573133）;the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences （2012RC102）展开更多
文摘This study develops a conceptual system optimization model of adoption of a new infrastructure technology with multiple resource sites and multiple demand sites. With the model, this paper analyzes how the distance, spillover effect, demand, initial investment cost, and learning rate influence the adoption of the new infrastructure technology and presents optimization results of the model in different scenarios. The main findings of the study are： from the perspective of system optimization, （1） different distances among different resource-demand pairs will result in different adoption time of a new infrastructure; （2） technological spillover among different resource-demand pairs will accelerate the adoption of a new infrastructuxe; （3） it is hard to say that higher demand will pull faster adoption of a new infrastructure, and the optimal time of adopting of a new infrastructure is very sensitive to its technological learning rate.
基金the financial support of the National Social Science Foundation of China (14ZDA038)the National Natural Science Foundation of China (71222302+2 种基金7137325571573133)the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences (2012RC102)
文摘the financial support of the National Social Science Foundation of China （14ZDA038）;the National Natural Science Foundation of China （71222302;71373255;71573133）;the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences （2012RC102）
