Integrating Drone‑Based Decision Support Systems in Precision Farming: An Econometric Simulation of Management Efficiency and Cost‑Benefit Analysis

Precision agriculture increasingly relies on advanced technological solutions to enhance productivity, management efficiency, and sustainability. This paper investigates the economic and managerial implications of integrating drone-based decision support systems (DSS) into precision farming practices. Through econometric simulation, the study evaluates the cost-benefit ratio, return on investment (ROI), and productivity gains resulting from drone technology adoption in a medium-sized farm. A detailed econometric database was constructed using simulated and real farm-level data from 20 Romanian agricultural holdings, incorporating variables such as drone utilization, yield outputs, production costs, labor efficiency, climatic conditions, and market dynamics. The applied methodology includes regression analysis, ROI computation, and sensitivity analysis across multiple scenarios reflecting partial and full drone implementation. Results indicate a statistically significant increase in yield productivity with a rapid amortization of drone investment. Sensitivity analyses reveal that operational drone maintenance costs, crop market prices, and climatic variability significantly influence economic outcomes. This research underscores the economic justification and managerial advantages of drone-based DSS in precision agriculture, recommending further studies for varied crop systems and broader geographic contexts.