Perceived quality estimation by the design of discrete-choice experiment and best–worst scaling data: An automotive industry case

“Which product attributes do engineers have to focus on to receive the highest level of a customer’s appreciation?” In other words, can we design for high perceived quality? In this paper, discrete-choice experiment design is presented with the combination of best–worst scaling method to evaluate the perceived quality of the complete vehicle in application to the premium automotive industry. The application of Perceived Quality Framework (PQF) and Perceived Quality Attributes Importance Ranking (PQAIR) method to measure the importance of perceived quality attributes for the automotive engineers and customers depicted commonalities and differences in perception. This information and approach can significantly improve engineering practices regarding the perceived quality of cars.