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
Based on data of 248 rural households in Pucheng County and Huxian County,we established the Two-Level Logit Model to analyze the willingness of farmers to adopt new technologies,its influence factors,and probability ...Based on data of 248 rural households in Pucheng County and Huxian County,we established the Two-Level Logit Model to analyze the willingness of farmers to adopt new technologies,its influence factors,and probability of successful adoption of new technologies.Results show that the willingness has positive correlation with whether the farmer is head of household,the educational level,occupation,agricultural loan,the number of family labor,and information dissemination channel,while it has negative correlation with non-agricultural employment proportion and whether the farmer is village cadre.In the model of the probability of farmers'successfully adopting new technologies,occupation,agricultural loan,planting area,gender and educational level are positively correlated,while age and non-agricultural employment proportion are negatively correlated.Largescale flow of rural labor plays a negative role in popularization of technologies in rural areas through influencing factors,including number of family labor,non-agricultural employment proportion,educational level,gender,and whether the farmer is village cadre.Finally,on the basis of results of empirical study,we put forward countermeasures and suggestions for strengthening ability of farmers to adopt new technologies.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.
文摘Based on data of 248 rural households in Pucheng County and Huxian County,we established the Two-Level Logit Model to analyze the willingness of farmers to adopt new technologies,its influence factors,and probability of successful adoption of new technologies.Results show that the willingness has positive correlation with whether the farmer is head of household,the educational level,occupation,agricultural loan,the number of family labor,and information dissemination channel,while it has negative correlation with non-agricultural employment proportion and whether the farmer is village cadre.In the model of the probability of farmers'successfully adopting new technologies,occupation,agricultural loan,planting area,gender and educational level are positively correlated,while age and non-agricultural employment proportion are negatively correlated.Largescale flow of rural labor plays a negative role in popularization of technologies in rural areas through influencing factors,including number of family labor,non-agricultural employment proportion,educational level,gender,and whether the farmer is village cadre.Finally,on the basis of results of empirical study,we put forward countermeasures and suggestions for strengthening ability of farmers to adopt new technologies.
