This article offers recommendations for companies’ managers connected to the application of unmanned aerial vehicles (UAV) in tourism. This is based on the analysis of data and the utilization of predictive modelling techniques (including exponential smoothing, machine learning). The set of scientific methods applied included a structured literature review for three areas studied (a) description of managerial decision-making, (b) econometric models created to predict future course of variables, (c) application of UAV technology in tourism. Literature review was accompanied by a comparison, synthesis and procedures of deduction and induction, which were needed for the conclusions to be drawn and the practical steps to be defined. Using time series data in a particular ski resort, the attendance and occupancy of the chairlifts were researched. The analyses led to the option of achieving higher customer satisfaction with the service via swifter processing of their requests. This is dependent on the ability to ensure the optimal number of employees serving customers at individual facilities. Following this point, drones find their application in tourism, generating the real-time data. When such data points are analysed and correctly interpreted, it is possible to set the processes in a more efficient way and achieve a higher level of the customers’ satisfaction. The results presented in this article are followed by concrete recommendations connected to the assessment of the application of drones in the operations performed by economic entities providing touristic services.
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