Farmers' willingness to pay for smart farming technologies: Evidence from a smart drip irrigation technology in North China
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 conduct...
| Autores principales: | , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Emerald Publishing Limited
2024
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/135276 |
| _version_ | 1855528922046791680 |
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| author | Tao, Hui Xiong, Hang You, Liangzhi Li, Fan |
| author_browse | Li, Fan Tao, Hui Xiong, Hang You, Liangzhi |
| author_facet | Tao, Hui Xiong, Hang You, Liangzhi Li, Fan |
| author_sort | Tao, Hui |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | 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. |
| format | Journal Article |
| id | CGSpace135276 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Emerald Publishing Limited |
| publisherStr | Emerald Publishing Limited |
| record_format | dspace |
| spelling | CGSpace1352762025-12-08T10:29:22Z Farmers' willingness to pay for smart farming technologies: Evidence from a smart drip irrigation technology in North China Tao, Hui Xiong, Hang You, Liangzhi Li, Fan agricultural technology crop yield farmers irrigation 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. 2024-03-22 2023-12-12T16:43:13Z 2023-12-12T16:43:13Z Journal Article https://hdl.handle.net/10568/135276 en Limited Access Emerald Publishing Limited Tao, Hui; Xiong, Hang; You, Liangzhi; and Li, Fan. 2024. Farmers' willingness to pay for smart farming technologies: Evidence from a smart drip irrigation technology in North China. China Agricultural Economic Review 16(1): 114-134. https://doi.org/10.1108/CAER-03-2023-0050 |
| spellingShingle | agricultural technology crop yield farmers irrigation Tao, Hui Xiong, Hang You, Liangzhi Li, Fan Farmers' willingness to pay for smart farming technologies: Evidence from a smart drip irrigation technology in North China |
| title | Farmers' willingness to pay for smart farming technologies: Evidence from a smart drip irrigation technology in North China |
| title_full | Farmers' willingness to pay for smart farming technologies: Evidence from a smart drip irrigation technology in North China |
| title_fullStr | Farmers' willingness to pay for smart farming technologies: Evidence from a smart drip irrigation technology in North China |
| title_full_unstemmed | Farmers' willingness to pay for smart farming technologies: Evidence from a smart drip irrigation technology in North China |
| title_short | Farmers' willingness to pay for smart farming technologies: Evidence from a smart drip irrigation technology in North China |
| title_sort | farmers willingness to pay for smart farming technologies evidence from a smart drip irrigation technology in north china |
| topic | agricultural technology crop yield farmers irrigation |
| url | https://hdl.handle.net/10568/135276 |
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