Article ID Journal Published Year Pages File Type
351214 Computers in Human Behavior 2013 12 Pages PDF
Abstract

Previous studies have sought insights into how websites can effectively draw sustained attention from internet users. Do different types of information presentations on webpages have different influences on users’ perceptions of the information? More precisely, can combinations of an ever greater number of advertising elements on individual websites increase consumers’ purchase intentions? The aim of this study is to explore changes in web advertising’s verbal and visual stimulation of surfers’ cognitive process, and to provide valuable information for the successful matching of advertising elements to one another. We examine optimal website design according to the personality-trait theory and resource-matching theory. Study 1 addresses the effects that combinations of various types of online advertising can have on web design factor, and to this end, we use a 2 (visual complexity: 3D advertising with an avatar, 2D advertising) × 2 (verbal complexity: with or without self-referencing that is an advertising practice to express product claims in words) factorial design. Study 2 treats personality traits (i.e., need-for-cognition and sensation seeking) as moderating variables to build the optimal portfolio regarding the “online-advertising effects” hypothesis. Our results suggest that subjects prefer medium-complex advertising comprising “3D advertising elements with an avatar” or “2D advertising elements with self-referencing”: high-sensation seekers and low-need-for-cognition viewers prefer the former, whereas low-sensation seekers and high-need-for-cognition viewers prefer the latter.

• We explored the effects of avatar and self-referencing in 2D or 3D AD. • We adopted personality-trait theory and resource-matching theory. • The subjects prefer “3D with an avatar” or “2D with self-referencing”. • The high sensation and low NFC viewers prefer 3D with an avatar. • The low sensation and high NFC viewers prefer 2D with self-referencing.

Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
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