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Exploring determinants of consumers' attitudes toward real-time bidding (RTB) advertising

Sixuan Zhang (Beihang University, Beijing, China)
Robin Wakefield (Hankamer School of Business, Baylor University, Waco, Texas, USA)
Jinsong Huang (Beihang University, Beijing, China)
Xi Li (Beihang University, Beijing, China)

Information Technology & People

ISSN: 0959-3845

Article publication date: 24 June 2020

Issue publication date: 12 March 2021




Since its inception in 2009, the growth of real-time bidding (RTB) advertising has been dramatic. Yet, there is a dearth of research in the information system (IS) literature despite the potential for negative e-commerce outcomes. The purpose of this paper is to identify salient antecedents of users’ attitude toward RTB advertisements.


A research model was constructed and tested with data from 437 respondents. SmartPLS 3.0, a partial least square (PLS) structural equation modeling (SEM) tool, was used to evaluate the research model and test the hypotheses.


The findings indicate that user attitude is determined by opposing influences from the cognitive and affective attributes of an RTB advertisement. A surprise is found to elicit greater perception of advertisement personalization, timeliness and relevance, as well as privacy and intrusiveness concerns. While RTB advertisement relevance appears to lessen the effect of advertisement intrusiveness, privacy concern is exacerbated when the advertisement is more personalized. The authors discuss the implications of this study for click-through intentions and e-commerce.


At this point in the evolution of RTB advertising, the findings indicate that the surprise generated by the appearance of an RTB advertisement is not currently a “bad” surprise. In addition, the formation of positive user attitude toward RTB is complex because cognitive factors interact with users' concerns to strengthen or weaken the negative effects. The authors also demonstrate that attitude and stimulus–organism–response (S–O–R) theories are useful theoretical bases for the development of causal models to predict RTB attitude and click-through intentions.



This research was funded by the National Natural Science Foundation of China grant Nos. 71872009 and 71901009.


Zhang, S., Wakefield, R., Huang, J. and Li, X. (2021), "Exploring determinants of consumers' attitudes toward real-time bidding (RTB) advertising", Information Technology & People, Vol. 34 No. 2, pp. 496-525.



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