Principle Component Analysis of System Usability Scale for Its Application in Automotive In – Vehicle Information System Development 2020-01-1200
The System Usability Scale (SUS) is used across industries, to evaluate a product’s ease of use. As the automotive industry increases its digital footprint, the SUS has found its application as a simple and reliable assessment of various in-vehicle human machine interfaces. Iterative automotive usability evaluations are imperative to ensure functionality. These evaluations can cover a broad scope when assessing all the features within a vehicle. As such, it is important to design studies with participant fatigue, study time, and study cost in mind. Reducing the number of items in the SUS questionnaire could save researchers time and money.
The SUS is a ten item questionnaire, measuring usability (8 items) and learnability (2 items). These ten questions are highly correlated to each other prompting researchers to evaluate if the SUS score can be determined with fewer items. Recent studies have suggested that the usability items in the SUS does not contribute equally to the overall SUS score. Thus, the focus of this paper is to determine if the number of variables could be reduced from 10 items to predict SUS scores for usability evaluation of in-vehicle human machine interfaces, using principle component analysis (PCA). Data from 81 systems under four automotive interior interfaces (Touch Screen, Climate, Voice, and Steering Wheel and Cluster) were used for this evaluation. Two items are the largest contributors to the overall SUS score.