数字赋能秦巴山区农民防止返贫监测的优化路径研究——以N县为例

Research on the Optimization Path of Digitally Empowered Monitoring for Preventing Farmers from Returning to Poverty in the Qinba Mountain Area—A Case Study of N County

摘要: 防止规模性返贫是巩固拓展脱贫攻坚成果同乡村振兴有效衔接的底线任务。在数字化驱动乡村治理现代化的战略背景下，数字技术赋能基层防止返贫监测的效能转化机制亟待深入探究。研究以陕西省A市N县为典型案例场域，基于技术–制度–环境适配性分析框架，采用问卷调查法获取有效样本，综合运用描述性统计、信效度检验、单因素方差分析、Pearson相关分析及多元线性回归等方法开展实证研究。研究发现：第一，N县数字防返贫监测系统整体运行效能为中等偏上水平，但制度协同性维度得分最低，跨部门数据共享壁垒与基层资源约束构成系统效能提升的主要瓶颈；第二，技术适配性、制度协同性与社会接受度均对整体效能感知具有显著正向影响，其中制度协同性的边际贡献最大，揭示了制度重于技术的基层治理逻辑；第三，不同角色群体的效能评价呈现显著梯度差异，县级干部与乡镇干部的评分显著高于普通农户，反映出山区基层数字鸿沟与信息落差的结构性张力。基于上述发现，文章从技术调适、制度创新、能力建设与社会融合四个维度提出系统优化路径，为推动数字治理工具从技术叠加向效能融合转型、实现同类山区地区巩固脱贫成果与乡村振兴有效衔接提供学理参考与政策启示。

Abstract: Preventing large-scale relapse into poverty is a fundamental task for consolidating and expanding the achievements of poverty alleviation while ensuring an effective transition to rural revitalization. Against the strategic backdrop of digital technologies driving the modernization of rural governance, the mechanism through which digital technologies empower grassroots monitoring systems for preventing poverty relapse requires further investigation. Taking N County, A City, Shaanxi Province as a representative case, this study constructs an analytical framework based on the Technology-Institution-Environment (TIE) fit model. Questionnaire survey data were collected as valid samples, and empirical analyses were conducted using descriptive statistics, reliability and validity tests, one-way analysis of variance (ANOVA), Pearson correlation analysis, and multiple linear regression. The findings indicate that: First, the overall operational performance of the digital monitoring system for preventing poverty relapse in N County is above the medium level. However, institutional coordination receives the lowest evaluation, with barriers to cross-departmental data sharing and constraints on grassroots resources constituting the primary bottlenecks to improving system effectiveness. Second, technological adaptability, institutional coordination, and social acceptance all exert significant positive effects on the perceived overall effectiveness of the monitoring system. Among these factors, institutional coordination demonstrates the greatest marginal contribution, highlighting the governance logic that institutional arrangements play a more decisive role than technology itself in grassroots governance. Third, significant differences exist in effectiveness evaluations among different stakeholder groups. County-level and township-level officials assign significantly higher ratings than ordinary farmers, reflecting the structural tensions arising from the digital divide and information asymmetry in mountainous rural areas. Based on these findings, this study proposes a systematic optimization framework from four dimensions—technological adaptation, institutional innovation, capacity building, and social integration. The proposed framework aims to facilitate the transformation of digital governance from simple technological application to integrated governance effectiveness, and provides both theoretical insights and policy implications for consolidating poverty alleviation achievements and promoting effective rural revitalization in other mountainous regions with similar characteristics.