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Article

A Study on the Adoption of Digital Technologies by New Agricultural Operators Under Climate Adaptation and Sustainable Development Goals: Digital Technology Cognition, Climate Risk Perception, and Multidimensional Barriers as Moderators

College of Biological and Agricultural Engineering, Jilin University, Changchun 130025, China
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Sustainability 2026, 18(11), 5448; https://doi.org/10.3390/su18115448
Submission received: 4 April 2026 / Revised: 25 May 2026 / Accepted: 26 May 2026 / Published: 29 May 2026
(This article belongs to the Special Issue Circular Economy and Green Technology for Sustainable Development)

Abstract

Against the backdrop of intensifying global climate change and the digital transformation of agriculture, promoting the adoption of digital technologies among new agricultural operators is a crucial pathway to enhancing agricultural climate resilience and achieving sustainable agricultural development. Based on survey data from 516 new agricultural operators in typical agricultural regions such as Northeast China, Hunan, and Hebei, this study employs Logit models, moderation effects, and heterogeneity analysis to examine the impact of digital technology cognition and climate risk on operators’ technology adoption behavior, as well as the underlying mechanisms. The findings reveal the following: First, digital technology cognition has a significant positive impact on the adoption of digital technologies, whereas climate risk perception and experiences with extreme weather significantly inhibit adoption behavior. Second, the perception of multidimensional barriers—comprising technical, economic, social, and policy obstacles—significantly moderates the positive effect of digital technology cognition on adoption behavior. Third, these effects exhibit significant heterogeneity across business scale, years in operation, and entity type. These conclusions remain valid after robustness tests and endogeneity control. This study enriches theories of agricultural technology diffusion and sustainable development from a climate resilience perspective, providing empirical evidence to promote the use of digital technologies for agricultural climate adaptation, refine differentiated extension policies, and enhance the level of agricultural sustainability.
Keywords: digital technology adoption; digital technology cognition; climate risk perception; sustainable agricultural development; multidimensional barriers digital technology adoption; digital technology cognition; climate risk perception; sustainable agricultural development; multidimensional barriers

Share and Cite

MDPI and ACS Style

Guo, H.; Wu, Z.; Xia, Y.; Mao, Z.; Fu, W.; Wang, Y. A Study on the Adoption of Digital Technologies by New Agricultural Operators Under Climate Adaptation and Sustainable Development Goals: Digital Technology Cognition, Climate Risk Perception, and Multidimensional Barriers as Moderators. Sustainability 2026, 18, 5448. https://doi.org/10.3390/su18115448

AMA Style

Guo H, Wu Z, Xia Y, Mao Z, Fu W, Wang Y. A Study on the Adoption of Digital Technologies by New Agricultural Operators Under Climate Adaptation and Sustainable Development Goals: Digital Technology Cognition, Climate Risk Perception, and Multidimensional Barriers as Moderators. Sustainability. 2026; 18(11):5448. https://doi.org/10.3390/su18115448

Chicago/Turabian Style

Guo, Hongpeng, Zihan Wu, Yujie Xia, Zirou Mao, Wenyu Fu, and Yingcheng Wang. 2026. "A Study on the Adoption of Digital Technologies by New Agricultural Operators Under Climate Adaptation and Sustainable Development Goals: Digital Technology Cognition, Climate Risk Perception, and Multidimensional Barriers as Moderators" Sustainability 18, no. 11: 5448. https://doi.org/10.3390/su18115448

APA Style

Guo, H., Wu, Z., Xia, Y., Mao, Z., Fu, W., & Wang, Y. (2026). A Study on the Adoption of Digital Technologies by New Agricultural Operators Under Climate Adaptation and Sustainable Development Goals: Digital Technology Cognition, Climate Risk Perception, and Multidimensional Barriers as Moderators. Sustainability, 18(11), 5448. https://doi.org/10.3390/su18115448

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