Gendered cognition, intra-household preference divergence, and behavioral choice: How gender differences shape GM maize adoption in smallholder families
基于云南436对夫妻调查数据，发现女性对转基因玉米安全风险感知比男性强3-5倍，其风险抑制效应远超男性的利润促进效应，导致家庭决策延迟，为农业技术推广中的性别敏感政策提供依据。
Agricultural extension research has paid insufficient attention to intra-household heterogeneity, resulting in promotion strategies that often treat farm households as homogeneous decision-making units. Based on paired survey data from 436 smallholder couples in Yunnan Province, China, this study constructs a “gender cognition – preference divergence – behavioral choice” analytical framework to systematically examine how intra-household gender-based cognitive differences trigger disputes over planting decisions through divergent perceptions of safety risks and benefit evaluations, ultimately influencing Genetically Modified (GM) Maize adoption behavior. The study reveals three key findings: (1) Significant gender asymmetry exists in technology risk-benefit assessment, with women demonstrating 3–5 times stronger safety risk perception than men (p < 0.001). Their risk-inhibiting effect (−27.9%) substantially outweighs men's profit-promoting effect (+16.5%), consistent with the loss aversion principle in behavioral economics. (2) Household decisions exhibit gendered bargaining interactions, where cognitive differences create a “female risk veto → risk-priority bargaining (with a benefit-risk compensation threshold of 1.17) → adoption delay” pathway, collectively reducing technology adoption probability by 16.3 percentage points. (3) Household decision-making authority significantly moderates technology diffusion: male-dominant households exhibit a “patriarchal efficiency advantage” (Δ = −24.4), while female-dominant households display heightened risk sensitivity (Δ = −35.5). In contrast, joint-decision households develop a unique preference divergence-driven adoption pathway (+12 %). This study provides a theoretical foundation for designing gender-sensitive policies in agricultural technology extension, recommending optimized diffusion efficiency through differentiated communication strategies and participatory evaluation mechanisms.