Flying low for greener farms: Configurational pathways linking the low-altitude economy to agricultural green total factor productivity in China
The low-altitude economy is increasingly viewed as a new technological frontier for agricultural transformation, yet its relationship with agricultural green total factor productivity remains poorly understood. This study examines how low-altitude economy-related conditions are associated with high agricultural green total factor productivity in China. We develop an institutional-technological-scenario framework and apply a sequential mixed-method design that combines qualitative coding, necessary condition analysis and dynamic fuzzy-set qualitative comparative analysis. The empirical analysis uses a balanced panel of 30 Chinese provinces from 2014 to 2022, covering 270 province-year observations. The period is treated as a formative and pre-consolidation stage of the low-altitude economy rather than as a fully mature integrated system. The results show that no single condition constitutes a statistically supported necessary condition for high agricultural green total factor productivity. Exploratory bottleneck analysis nevertheless reveals descriptive threshold patterns at higher outcome levels. The dynamic configurational analysis identifies three pathways associated with high agricultural green total factor productivity, namely technology-application coupling, institution-innovation coupling and scale-application diffusion. The non-high productivity configuration further shows that enterprise development, policy support and market support may fail to translate into green productivity improvement when industrial application is absent. Regional and temporal analyses reveal substantial spatial and temporal heterogeneity. The findings suggest that the low-altitude economy is better understood as an emerging socio-technical enabling system rather than as a single UAV-based technology, and that agricultural green transformation depends on the configuration of institutional support, technological capacity and application scenarios.
Authors
- Shenwei Wan (ORCID: https://orcid.org/0009-0000-1962-6132)
- Shiyuan Wang
- Lei Zhou
- Yanbang Zhou
Institutions
- Renmin University of China (CN)
Publication Details
- Journal
- Technological Forecasting and Social Change
- Published
- 2026-10-15
- DOI
- https://doi.org/10.1016/j.techfore.2026.124918
- Primary Topic
- Digitalization and Economic Development in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00