A SAW–BASED DECISION SUPPORT MODEL FOR THE SELECTION OF NEW AND USED PASSENGER CARS

Abstract

The selection of a passenger car is a complex decision–making problem involving technical, economic, operational, safety and practical characteristics, together with individual buyer preferences. The problem becomes particularly complex when new and used vehicles of different ages are considered simultaneously. This paper proposes a decision–support model based on the Simple Additive Weighting (SAW) method. Sixteen anonymized SUV/crossover alternatives are considered: four new vehicles and twelve used vehicles divided into approximately three–, six–, and ten–year–old groups. Ten criteria are used, including effective acquisition cost, age, mileage, fuel consumption, maintenance cost, reliability, safety, performance, practicality, and equipment/comfort. Three weighting scenarios represent balanced, economy–oriented, and family/safety-oriented buyers. The results show different preferred alternatives for the three profiles and demonstrate that a recent used vehicle can outperform new alternatives under suitable buyer priorities. Weight–sensitivity and input–data uncertainty analyses further distinguish robustness to preference changes from robustness to uncertain input values.