Quantitative Analysis Of User Interfaces For Large Electronic Home Appliances And Mobile Devices Based On Lifestyle Categorization Of Older Users

摘要

Background/Study Context: The increasing longevity and health of older users as well as aging populations has created the need to develop senior-oriented product interfaces. This study aims to find user interface (UI) priorities according to older user groups based on their lifestyle and develop quality of UI (QUI) models for large electronic home appliances and mobile products.Methods: A segmentation table designed to show how older users can be categorized was created through a review of the literature to survey 252 subjects with a questionnaire. Factor analysis was performed to extract six preliminary lifestyle factors, which were then used for subsequent cluster analysis. The analysis resulted in four groups. Cross-analysis was carried out to investigate which characteristics were included in the groups. Analysis of variance was then applied to investigate the differences in the UI priorities among the user groups for various electronic devices. Finally, QUI models were developed and applied to those electronic devices.Results: Differences in UI priorities were found according to the four lifestyles (money-oriented, innovation-oriented, stability- and simplicity-oriented, and innovation- and intellectual-oriented). Twelve QUI models were developed for four different lifestyle groups associated with different products. Three washers and three smartphones were used as an example for testing the QUI models.Conclusion: The UI differences of the older user groups by the segmentation in this study using several key (i.e., demographic, socioeconomic, and physical-cognitive) variables are distinct from earlier studies made by a single variable. The differences in responses clearly indicate the benefits of integrating various factors of older users, rather than single variable, in order to design and develop more innovative and better consumer products in the future. The results of this study showed that older users with a potentially high buying power in the future are