Drone delivery in city logistics is gaining attention due to road congestion, environmental threats, etc. However, there are risks associated with using drones which can result in hazardous events, such as conflicts in the air, loss of control, and system failures. It is crucial to assess the risks involved in using different types of drones and choose the option with the lowest risk. The existence of different criteria important for this decision imposes the need to apply the multi-criteria decision-making (MCDM) method(s). This paper proposes a new hybrid model that combines the fuzzy Factor Relationship (FARE) method for obtaining the criteria weights and the Axial Distance-based Aggregated Measurement (ADAM) method for obtaining the final ranking of the alternatives. A single-rotor microdrone weighing up to 4.4 lb was chosen as the optimal solution, and after that, the most favorable are also the drones of this size (multi-rotor and fixed-wing microdrones). The establishment of a novel hybrid MCDM model, the identified risks, the set of criteria for evaluating the least risky drones, and the framework for prioritizing the drones are the main novelties and contributions of the paper.

Analysis of investments in transport is carried out in both the public and private sectors. The main objective of the development and implementation of projects in the public sector is to ensure the supply of public goods (safety, security, healthcare, various public services, etc.). This paper analyses these impacts in the public sector, specifically in air and road transport. Transpor sector defines safety as a key priority, but accidents do occur despite numerous sectoral preventive and mitigation measures. Loss of human lives is the most serious consequence of such accidents. Since the estimation of loss of human life is one of the key challenges for economists in conducting cost-benefit analysis, the paper discusses the methods used for such types of analysis. Evaluating the benefits and adverse outcomes of public sector projects often causes difficulties. While the expected benefit from avoided property damage caused by accidents can be calculated using available market prices, the benefits from reduced risk exposure and travel time do not have market prices. The paper emphasizes the monetary value of increasing safety, more precisely, the value of reducing the risk of mortality.

Safety is a central concern in aviation, where aircraft operations involve complex processes and interactions exposed to multiple hazards. Addressing these hazards requires systematic risk management and the selection of effective safety measures. This study introduces a novel hybrid multi-criteria decision-making (MCDM) framework that integrates the grey Delphi method, the grey Analytic Hierarchy Process (AHP), and the grey Axial-Distance-Based Aggregated Measurement (ADAM) method. The framework provides a rigorous engineering-based approach for evaluating and ranking safety measures under uncertainty and diverse stakeholder perspectives. Application of the model to aircraft operations demonstrates its ability to identify the most effective measures, including the development of critical infrastructure protection plans, rerouting of flight paths from high-risk areas, and strengthening of regulatory oversight. The proposed methodology advances decision-support tools in aviation safety engineering, offering structured guidance for optimizing resource allocation and improving system resilience.