ORIGINAL RESEARCH article
Front. Sustain. Food Syst.
Sec. Agricultural and Food Economics
Modeling Determinants of Farmers' Attitudes and Adoption Willingness Toward Agricultural Drones: A PLS-SEM Study in India
Provisionally accepted
- Indian Agricultural Research Institute (ICAR), New Delhi, India
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Precision agriculture technologies, particularly agricultural drones, are increasingly recognized for their potential to enhance farming efficiency, reduce labor burdens, and improve decision-making. Despite their growing availability, adoption among farmers remains limited due to a complex interplay of psychological, economic, and social factors. This study aims to examine the factors influencing farmers' attitude toward agricultural drone technology and their willingness to adopt it by modeling the effects of perceived benefits, challenges, and social influences. A structured survey was administered to 320 farmers across selected regions in Haryana and Uttar Pradesh. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), relationships among ten latent constructs, including perceived usefulness, ease of use, economic viability, environmental and social impacts, risks, and promotional efforts, were analyzed. Perceived usefulness, promotional efforts, peer pressure, and perceived viability had significant positive effects on farmers' attitude and adoption willingness. The findings offer valuable insights into the behavioral mechanisms that shape drone adoption in agriculture. By understanding the psychological and contextual drivers of adoption, policymakers, extension agents, and technology developers can design more effective awareness, training, and support strategies to accelerate precision agriculture adoption among smallholder farmers.
Keywords: unmanned aerial vehicles (UAVs), Agricultural drones, Technology Adoption, Attitude, Willingness to adopt, PLS-SEM
Received: 29 Aug 2025; Accepted: 31 Oct 2025.
Copyright: © 2025 Barman, Singh, Padaria, Nain and Quader. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Bikram Barman, bikram.agriext@outlook.com
Rashmi Singh, rashmisinghiari@gmail.com
Sk Wasaful Quader, skwasafull.24@gmail.com
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