Smart farming technologies (SFTs) can increase yields and reduce the environmental impacts of farming by improving the efficient use of inputs. This paper is to estimate farmers' preference and willingness to pay (WTP) for a well-defined SFT, smart drip irrigation (SDI) technology.
This study conducted a discrete choice experiment (DCE) among 1,300 maize farmers in North China to understand their WTP for various functions of SDI using mixed logit (MIXL) models.
The results show that farmers have a strong preference for SDI in general and its specific functions of smart sensing and smart control. However, farmers do not have a preference for the function of region-level agronomic planning. Farmers' preferences for different functions of SDI are heterogeneous. Their preference was significantly associated with their education, experience of being village cadres and using computers, household income and holding of land and machines. Further analysis show that farmers' WTP for functions facilitated by hardware is close to the estimated prices, whereas their WTP for functions wholly or partially facilitated by software is substantially lower than the estimated prices.
Findings from the empirical study lead to policy implications for enhancing the design of SFTs by integrating software and hardware and optimizing agricultural extension strategies for SFTs with digital techniques such as videos.
This study provides initial insights into understanding farmers' preferences and WTP for specific functions of SFTs with a DCE.
