Digitalization linked to greener agricultural productivity in Chinese provinces

A forthcoming study of Chinese provincial data finds that agricultural digital transformation is associated with higher agricultural green total factor productivity (AGTFP), with the estimated relationship varying across regions and according to the scale of farmland operation. The researchers analyzed panel data from 2011 to 2023 and report that the positive association remained after they addressed potential endogeneity and conducted a series of robustness checks. The findings describe statistical relationships within a provincial dataset, rather than results from a field experiment or proof that digital tools directly produced the estimated productivity changes.

The study, “The impact of digital transformation on agricultural green total factor productivity: Moderating and threshold effects of farmland scale operation,” appears in Frontiers in Sustainable Food Systems. Agricultural digital transformation was measured with an entropy-method composite index, while AGTFP was calculated using the Global Malmquist-Luvenhagen index based on a super-efficiency EBM distance function. The authors analyzed the data with two-way fixed-effects models, moderating-effect models and panel threshold models. These methods were used to estimate the relationship between digital transformation and AGTFP, test whether farmland scale operation changed that relationship, and examine whether the pattern differed across levels of scale operation.

Farmland scale operation positively moderated the relationship between digital transformation and AGTFP. In the authors’ estimates, the association between digitalization and agricultural green productivity was stronger where farmland was operated on a larger scale. The moderating effect also followed a single-threshold nonlinear pattern: marginal effects increased across the observed scale range, indicating a structural turning point in the estimated enabling role of digital transformation at different levels of farmland scale operation. The result therefore points to a scale-dependent relationship rather than an association that was uniform across farming systems. The supplied research abstract does not report threshold values, model coefficients, confidence intervals or numerical effect sizes, so the magnitude of these changes cannot be determined from the available material.

The estimated effects also differed geographically and agriculturally. Agricultural digital transformation was associated with a more pronounced improvement in AGTFP in eastern regions and major grain-producing areas than in the other categories examined. These are differences across regional and agricultural groupings, not evidence that productivity declined over time elsewhere or rose within every province. Overall, the study provides observational evidence from China linking agricultural digital transformation with green productivity, while indicating that farmland scale operation conditions the relationship. Because the analysis is based on provincial panel data, the results should be interpreted as statistical associations with observed heterogeneity, rather than a universal causal effect.

Subject of Research: Effects of agricultural digitalization and farmland scale operation on green productivity across Chinese provinces

Article Title: The impact of digital transformation on agricultural green total factor productivity: moderating and threshold effects of farmland scale operation

Article References: Ma, X., Wang, G., Ni, X., & Yang, C. (2026). The impact of digital transformation on agricultural green total factor productivity: moderating and threshold effects of farmland scale operation. Frontiers in Sustainable Food Systems, 10, Article 1856909. https://doi.org/10.3389/fsufs.2026.1856909

Image Credits: AI Generated

DOI: 10.3389/fsufs.2026.1856909

Keywords: agricultural digitalization, green productivity, farmland scale operation, China, provincial panel data, threshold effects, fixed-effects models, sustainable agriculture, impact, digital, transformation, agricultural