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

Institutions

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
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Flying low for greener farms: Configurational pathways linking the low-altitude economy to agricultural green total factor productivity in China

Shenwei Wan, Shiyuan Wang, Lei Zhou, Yanbang Zhou
Technological Forecasting and Social Change
Digitalization and Economic Development in Agriculture
article

Flying low for greener farms: Configurational pathways linking the low-altitude economy to agricultural green total factor productivity in China

Shenwei Wan, Shiyuan Wang, Lei Zhou, Yanbang Zhou
article en

Abstract

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.

Technological Forecasting and Social ChangeVol. 235
Renmin University of China (CN)
Zero hunger, Decent work and economic growth, Industry, innovation and infrastructure, Climate action
Openalex Percentile: Top 9%
Digitalization and Economic Development in Agriculture
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.