Consumer response to online behavioral advertising in a social media context: The role of perceived ad complicity
Abstract
Brands and social media platforms are two main players in online behavioral advertising (OBA), but the extant literature overlooks the interaction between them. Although advertising brands invest considerable resources to target potential consumers through social media advertising, our analysis indicates that publisher-platform-related activities can elicit negative consequences. Thus, we examined the role of perceived ad complicity, that is, consumers' perception regarding advertisers partnering with the social media platforms in the OBA process. We used perceived ad complicity as a moderator to explain the variation in consumers' negative responses to OBA in a social media context. Our results indicate that consumers with high perceived ad complicity experience greater perceived ad intrusiveness. This effect directly impacts their attitudes toward publisher platforms and advertising brands but consumers react more negatively toward brands (vs. publisher platforms) regarding this practice. Furthermore, we found that consumers who are more sensitive to social norms experience stronger perceived ad complicity and that informing consumers about why they are seeing specific ads on their social media platforms does not change their views on ad complicity.
Study specs
- Authors
- T Ghanbarpour,E Sahabeh
- Discipline
- Marketing,Consumer Behavior,Social Media Studies
- Year
- 2022
- Human Data Platform
- Prolific
- Source
- View Source DOI Google Scholar
Peer Review & Critical Discussion
Potential Selection Bias in 2023 Cohort
The participant pool shows a concerning overrepresentation of users from high-income demographics. Looking at Table 3, we can see that 78% of respondents had annual incomes above $75k, which significantly limits the generalizability of these findings to broader populations.
Non-naive Participants Issue
I've noticed a methodological concern regarding participant naivety. Given that Prolific users often complete multiple studies, there's a real risk that participants had prior exposure to similar experimental paradigms, which could confound the results.
RLHF Applicability to This Study Design
The implications for RLHF training pipelines are understated. If we accept the authors' conclusions about preference stability, this has direct consequences for how we should structure reward model training. The temporal decay effect described in Section 4.2 is particularly relevant.
Verify your expertise to join discussion
Create an account and verify your credentials to participate in peer discussions.