From Technology Acceptance to Actual Use: Determinants of Agricultural Drone Adoption for Digital Agriculture and Crop Monitoring in Thailand’s Eastern Economic Corridor
Year: 2026
Type: article
Abstract: Agricultural drones are increasingly important for digital agriculture and crop monitoring; however, behavioral intention to use the technology does not necessarily translate into actual use. This study developed and empirically tested an integrated model combining the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) to examine agricultural drone adoption in Thailand’s Eastern Economic Corridor (EEC) and the surrounding agricultural area of Prachin Buri. A quantitative cross-sectional survey was conducted with 400 farmers and agricultural practitioners across four provinces using quota sampling. The data were analyzed using partial least squares structural equation modeling (PLS-SEM) with 5000 bootstrap resamples. Seven of the nine hypothesized relationships were supported. Perceived usefulness positively influenced attitude and behavioral intention, while perceived ease of use positively influenced attitude but did not have a significant direct effect on behavioral intention. Attitude positively influenced both behavioral intention and actual use, and behavioral intention positively influenced actual use. Facilitating conditions significantly influenced actual use but did not significantly influence behavioral intention. The model explained 65.0% of the variance in attitude, 63.0% in behavioral intention, and 74.9% in actual use. Positive Q2_predict values and statistically significant cross-validated predictive ability test (CVPAT) results further supported the model’s predictive relevance and predictive performance relative to the indicator-average benchmark. These findings highlight that the factors associated with behavioral intention and actual agricultural drone use are not necessarily identical, emphasizing the importance of distinguishing psychological acceptance from practical implementation conditions. The findings suggest that agricultural drone promotion should demonstrate practical benefits while also addressing technical support, infrastructure, operational knowledge, and access to necessary resources. The findings should be interpreted in light of the study’s regional scope, non-probability quota-sampling approach, self-reported measure of actual use, and cross-sectional design.
Source: Applied Sciences
DOI: 10.3390/app162211200
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W7225849285