Barriers to Climate-Smart Agriculture Adoption in Northeast China’s Black Soil Region: Insights from a Multidimensional Framework

Climate change threatens global food security, highlighting the necessity for Climate-Smart Agriculture (CSA) to enhance agricultural resilience and sustainability. Yet low adoption among farmers highlights gaps in understanding adoption barriers. Existing models often overlook the dynamic, multi-layered nature of farmers’ decisions. This study introduces the Multidimensional Dynamic Decision Analysis Framework (MDDAF), which integrates Sustainable Livelihoods Framework, Diffusion of Innovations, and Behavioral Economics, and applies it to conservation agriculture in Northeast China’s black soil region. We conducted 125 semi-structured interviews (100 farmers, stage-mapped into six groups; 20 leaders of agricultural socialized service organizations; 5 technical experts) and analyzed transcripts in NVivo using a hybrid deductive–inductive approach. Findings show stage-specific barriers: superficial knowledge and fragmented perceptions in awareness; traditional norms and social stigmatization in evaluation; biosecurity risks, ecological mismatches, and land tenure disputes during decision-making; economic constraints and policy inconsistencies during implementation; and operational failures, incomplete practices, and climate-driven volatility at confirmation. Priority implications are as follows: professionalize service provision; safeguard bundle fidelity and manage climate risk; reduce context and tenure risks; and counter misbeliefs via complement-focused demonstrations, diverse opinion leaders, and targeted training. MDDAF thus links dynamic, stage-specific barriers to actionable interventions, supporting more effective CSA scale-up.

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Publication Details

Journal
Agriculture
Published
2025-10-27
DOI
https://doi.org/10.3390/agriculture15212236
Primary Topic
Agricultural Innovations and Practices
Type
article
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article

Barriers to Climate-Smart Agriculture Adoption in Northeast China’s Black Soil Region: Insights from a Multidimensional Framework

Linpeng Yang, Zhao Wang, Yao Dai, Zhengsong Yu
Agriculture
Agricultural Innovations and Practices
article

Barriers to Climate-Smart Agriculture Adoption in Northeast China’s Black Soil Region: Insights from a Multidimensional Framework

Linpeng Yang, Zhao Wang, Yao Dai, Zhengsong Yu
article en

Abstract

Climate change threatens global food security, highlighting the necessity for Climate-Smart Agriculture (CSA) to enhance agricultural resilience and sustainability. Yet low adoption among farmers highlights gaps in understanding adoption barriers. Existing models often overlook the dynamic, multi-layered nature of farmers’ decisions. This study introduces the Multidimensional Dynamic Decision Analysis Framework (MDDAF), which integrates Sustainable Livelihoods Framework, Diffusion of Innovations, and Behavioral Economics, and applies it to conservation agriculture in Northeast China’s black soil region. We conducted 125 semi-structured interviews (100 farmers, stage-mapped into six groups; 20 leaders of agricultural socialized service organizations; 5 technical experts) and analyzed transcripts in NVivo using a hybrid deductive–inductive approach. Findings show stage-specific barriers: superficial knowledge and fragmented perceptions in awareness; traditional norms and social stigmatization in evaluation; biosecurity risks, ecological mismatches, and land tenure disputes during decision-making; economic constraints and policy inconsistencies during implementation; and operational failures, incomplete practices, and climate-driven volatility at confirmation. Priority implications are as follows: professionalize service provision; safeguard bundle fidelity and manage climate risk; reduce context and tenure risks; and counter misbeliefs via complement-focused demonstrations, diverse opinion leaders, and targeted training. MDDAF thus links dynamic, stage-specific barriers to actionable interventions, supporting more effective CSA scale-up.

AgricultureVol. 15(21)
Chinese Academy of Sciences (CN), China National Institute of Standardization (CN), Institute of Geographic Sciences and Natural Resources Research (CN), Shanghai Institute of Technology (CN), Lanzhou University (CN)
Openalex Percentile: Top 53%
Agricultural Innovations and Practices
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