ASSESSING BEHAVIOURAL INTENTIONS IN DRONE ADOPTION FOR GEOSPATIAL MAPPING: A QUANTITATIVE FOUNDATION FOR DECISION SUPPORT

Drones have become a pivotal advancement in the geospatial industry, offering notable improvements in efficiency, adaptability, and cost when compared to conventional surveying and mapping techniques. Despite these benefits, their successful implementation hinges on the willingness of geospatial professionals to adopt such technologies. This study investigates the intention to utilize drone-enabled geospatial tools and presents a quantitative approach to support strategic organizational decisions. Guided by the Unified Theory of Acceptance and Use of Technology (UTAUT), this study investigates the extent to which performance expectancy, effort expectancy, social influence, and facilitating conditions influence employees’ behavioural intentions. Several statistical methods, including as multiple regression, reliability testing, correlation analysis, and descriptive statistics, were used to analyze the survey data. Results indicate that social influence (β = 0.209, p < 0.001) and facilitating conditions (β = 0.382, p < 0.001) significantly enhance behavioural intention, whereas performance expectancy and effort expectancy showed no statistically significant impact. These outcomes support the development of targeted implementation strategies and emphasize the need for infrastructure and social encouragement in promoting drone adoption. The study contributes to both theoretical insights regarding the UTAUT model and practical applications for advancing technology uptake in a dynamic geospatial landscape.