文献类型: 外文期刊
作者: Wenxuan Geng;Liping Liu;Junye Zhao;Xiaoru Kang;Wenliang Wang
作者机构:
关键词: adoption intensity;digital technology adoption;economic benefits;growers;mixed methods
期刊名称: Sustainability (Switzerland)
ISSN: 2071-1050
年卷期: 2024 年 16 卷 11 期
页码:
收录情况: SCIE(2024版) ; ; SSCI(2024版)
摘要: Governments globally aim to boost productivity and enhance farmers’ livelihoods, addressing challenges like climate change, food security, and labor shortages through digital technologies. However, adoption rates in developing countries remain low due to uncertainties regarding expected returns and obstacles stemming from subjective and objective factors among farmers. This study takes China as a case study to examine the internal and external factors influencing growers’ adoption intensity of digital technology and its impact on enhancing economic benefits, aiming to provide valuable insights for the promotion of digital technology in other countries and regions. This study employs a mixed-methods approach, integrating qualitative and quantitative methodologies, utilizing data from Shandong and Liaoning provinces. The findings underscore the significant role of growers’ knowledge, technology compatibility, government support, and competitive pressure in driving the adoption of digital technology among growers, with male growers and those managing larger cultivation areas demonstrating higher adoption intensity. Digital technologies can enhance growers’ economic benefits by reducing labor and input costs, increasing yields, and improving quality, with a 30.4% increase in economic benefits for each unit increase in adoption intensity of digital technologies. Technology promoters can use these findings to enhance growers’ awareness, highlight the practical benefits, and offer agricultural socialized services to promote digital technology adoption.
分类号:
- 相关文献
作者其他论文 更多>>
-
Quality and accuracy of radiomics models in predicting KRAS status in lung cancer: a systematic review and meta-analysis
作者:Xindong Luo;Ziqiang Wang;Di Lu;Yaping Wang;Wenliang Wang;Pengcheng Dong;Yunjiu Gou;Yayuan Yang
关键词:cancer;deep learning;KRAS gene mutation;lung cancer;non-small cell lung cancer;radiomics
-
Measurement and spatial evolution of green total factor productivity in China’s wheat production based on the three-stage DEA-GML model
作者:Liping Liu;Bin Zheng;Junye Zhao;Shuai Hao
关键词:green total factor productivity;kernel density estimation;spatial pattern evolution;three-stage DEA-GML;wheat
-
Bridging the urban–rural income divide through entrepreneurship: evidence from a double machine learning approach in China
作者:Shuai Hao;Liping Liu;Guogang Wang;Xizhao Wang
关键词:China;common prosperity;double machine learning;entrepreneurial activity;urban–rural income gap
-
Spatio-temporal evolution and driving factors of China’s agro-processing industry
作者:Shuai Hao;Liping Liu;Guogang Wang
关键词:agro-processing industry;driving factors;Geodetector;Geographically and Temporally Weighted Regression;spatial evolution
-
Promoting grain production through high-standard farmland construction: Evidence in China
作者:Shuai Hao;Guogang Wang;Yantao Yang;Sicheng Zhao;Shengnan Huang;Liping Liu;Huanhuan Zhang
关键词:difference-in-differences;farmland construction;food production area;food security;high-standard farmland
-
Identification of key volatile flavor compounds in cigar filler tobacco leaves via GC-IMS
作者:Jian Wang;Yong Pan;Liping Liu;Chuang Wu;Youzhi Shi;Xiaolong Yuan
关键词:Cigar filler tobacco leaves;Partial least squares-discriminant analysis;Principal component analysis;Volatile flavor compounds, Gas chromatography–ion mobility spectrometry