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How Does the Adoption of Digital and Intelligent Technologies Affect Farmers’ Farmland Rental-In Behavior? Evidence from Grain-Growing Farmers in China

Year: 2026

Type: article

Abstract: Farmland rental is an important means of optimizing agricultural land allocation and promoting appropriately scaled farming. Against the backdrop of accelerating digital and intelligent transformation in agricultural, how digital and intelligent technology (DIT) adoption relates to farmers’ farmland rental-in behavior require clear theoretical explanation and empirical validation. Using 2024 survey data from 385 grain-growing farmers in Jiangsu Province, China, this study examines the relationship between DIT adoption and farmland rental-in behavior using Probit, endogenous switching regression, IV-Probit, and conditional mixed-process models. The results show that DIT adoption is significantly and positively associated with both farmland rental-in decisions and rented-in scale. These findings remain robust across alternative samples and estimation specifications. Heterogeneity analyses indicate that this positive association is more pronounced for production-oriented than information-oriented DIT applications, for farms with larger baseline operational scales than smallholders, and for households with lower aging ratios. Mechanism analyses suggest that DIT adoption corresponds to farmland rental-in primarily through labor substitution effects and transaction cost reductions in rural land markets. This study extends farmland rental research to the context of agricultural digitalization, offering empirical insights for advancing digital agriculture, improving farmland rental markets, and fostering appropriately scaled farming operations.

Source: Agriculture

DOI: 10.3390/agriculture16202298

Authors: Guoying Han, Gang Wu, Jianhua Wang, Qiang Gao

Institutions: Jiangsu Open University, Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Sciences, Jiangnan University, Nanjing Forestry University

Language: English

Topic: Agricultural Innovations and Practices

Subfield: General Agricultural and Biological Sciences

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDGs: Zero hunger, Industry, innovation and infrastructure, Decent work and economic growth

Open Access status: gold

Estimated APC paid: $3,137