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handle: 10017/53234
PurposeThe study of the background to programmatic advertising is of great interest in the context of digital marketing. Therefore, the main aim of this research is to define a structural equation modelling (SEM) model, which allows studying the relationship between the usefulness and privacy of online ads to increase the effectiveness and efficiency of campaigns through the use of computation and big data.Design/methodology/approachA cross-sectional descriptive study based on the Web Browsers Survey was carried out on a sample of 24,062 Internet users by the Association for Media Research. The partial least squares structural equation modelling method (PLS-SEM) was applied to evaluate the model with the study constructs and test the hypotheses.FindingsThe result of this research allows us to know how perceived usefulness (U) and perceived annoyance (A) affect users' privacy concerns (P) and concerns about the storage and use of their data through cookies (C). The authors also seek if there is any relationship between privacy concerns (P) and cookies (C) on users' level of Internet usage (IU).Originality/valueOne of the novelties of this study is the consideration not only of Internet user perceptions but also their concerns about privacy and the use of cookies, as key variables in the strategic management of the use of programmatic advertising in digital marketing.
Perceived annoyance, Digital marketing, Perceived usefulness, Usability, PLS-SEM model, Programmatic advertising, Cookies, Management science, Privacy, Internet usage, Empresa
Perceived annoyance, Digital marketing, Perceived usefulness, Usability, PLS-SEM model, Programmatic advertising, Cookies, Management science, Privacy, Internet usage, Empresa
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 8 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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