Using the kano quality model to evaluate the functions of automotive smart head-up displays

Abstract

The development of novel technologies has resulted in changes in the functions offered by head-up displays (HUDs), which differ considerably from conventional digital dashboard displays. This study aimed to create a scientific framework for automotive services for automobile manufacturers to review their service models and solutions as they transition to developing autonomous vehicles. This study used the two-dimensional Kano quality model to identify and classify quality characteristics of HUDs. A Kano questionnaire survey was conducted to collect data on customer satisfaction with different quality characteristics. These characteristics were then ranked in the order of their importance to consumers, thereby identifying quality characteristics that must be prioritized for providing high-quality services with HUDs. Data were collected on their emphases on and satisfaction with 32 quality characteristics belonging to seven factors across two dimensions, namely tangible specific functions and intangible value-added services. The seven factors were speed and distance support, driver alerts, information and communication, display settings, active matching, automatic systems, and software–hardware integration. A statistical analysis was performed to determine the presence of significant differences in the customers’ perception of the quality characteristics. On the basis of the analysis results, 11 quality characteristics were classified as attractive quality, four as one-dimensional quality, six as must-be quality, seven as indifferent quality, and four as reverse quality. By referencing the classification of quality characteristics in their products, automotive companies can adopt the product improvement priority scheme proposed in this study to effectively enhance customer satisfaction with their services.