An evaluation of customer perspectives on big data driven online advertising

Abstract

Big data has brought many changes to the business nowadays. Big data analytics has made online advertising more customized to the target market. With the help of data analysis and other techniques, online advertising has been more to the target. From the advertiser’s perspective, it is being applied to all advertisements. There is a lack of consumer feedback on the new trend in online advertising. This paper is to evaluate consumer’s perspectives toward online advertising that is based on big data analytics by applying TAM, TRA, and TPB. In this research, customer’s perspectives are reflected by attitude and intention. The research uses the theory of reasoned action (TRA) and the theory of planned behavior (TPB) to analyze consumer’s attitudes and intentions to look at online advertising. The technology acceptance model (TAM) is also adopted in the research to predict consumer behavior. As quantitative research, an online survey is displayed for data collection, the survey in this research has applied Likert Scale to measure consumer’s perceived usefulness, perceived ease of use, attitude and behavioral intention. Compared to the past, customer perspectives on advertising are generally positive. This research could give merchants some idea on the potential effectiveness and acceptance of online advertising.