The influence of user affect in online information disclosure
In: The journal of strategic information systems, Band 22, Heft 2, S. 157-174
ISSN: 1873-1198
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In: The journal of strategic information systems, Band 22, Heft 2, S. 157-174
ISSN: 1873-1198
In: The journal of strategic information systems, Band 25, Heft 2, S. 140-156
ISSN: 1873-1198
In: The journal of strategic information systems, Band 15, Heft 3, S. 219-248
ISSN: 1873-1198
In: International journal of information management, Band 35, Heft 4, S. 377-393
ISSN: 0268-4012
In: Information, technology & people, Band 34, Heft 2, S. 496-525
ISSN: 1758-5813
PurposeSince 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.Design/methodology/approachA 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.FindingsThe 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.Originality/valueAt 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.