Research has shown that the perceived credibility of mobile web design can be largely determined by the two dimensions of visual aesthetics: classical and expressive. However, there is limited research on how users’ education moderates the relationships between both dimensions of visual aesthetics and perceived credibility. To bridge this gap, we conducted an empirical study among 526 subjects to investigate how education moderates the influence of classical and expressive aesthetics on the perceived credibility of mobile website. Specifically, we focused on four visual designs of a mobile website homepage, in which products and/or services are laid out. Our results show that, irrespective of the level of education of users and the visual design of the mobile website, the perception of both dimensions of visual aesthetics has a significant impact on perceived credibility, with classical aesthetics having a stronger impact than expressive aesthetics overall. Moreover, we found that the effect of classical aesthetics on perceived credibility is stronger for higher education users than for lower education users, while the effect of expressive aesthetics on perceived credibility is stronger for lower education users than for higher education users. Our findings suggests that classical aesthetics(perceived visual clarity) is more likely to influence higher education users than lower education users to perceive a mobile website as credible, while expressive aesthetics(perceived visual enrichment) is more likely to influence lower education users than higher education users to perceive a mobile website as credible. Web designers of e-commerce mobile websites can leverage these findings to enhance the perceived credibility of their websites by the respective user groups.
CITATION STYLE
Oyibo, K., Adaji, I., & Vassileva, J. (2019). Mobile Web Design: The Effect of Education on the Influence of Classical and Expressive Aesthetics on Perceived Credibility. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11584 LNCS, pp. 66–79). Springer Verlag. https://doi.org/10.1007/978-3-030-23541-3_6
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