Empirical Identification of Latent Classes in the Assessment of Information Asymmetry and Manipulation in Online Advertising
Abstract
:1. Introduction
- •
- Are e-consumers aware of information asymmetry and manipulation in advertising?
- •
- Do latent data affect e-consumers’ (respondents’) declared answers, and how?
Previous Literature and Research
2. Methods and Materials
2.1. Method
- Introductory questions about experiences and ways of using the Internet regarding the frequency and extent of social networking, online shopping, and goals and rationale for using the Internet.
- Rating the intentions of advertisers and the advertising message in light of their own experience and presence in the world of online advertising.
- Evaluation of the impact of advertising on the e-consumer in the context of individual and social assessments.
- The subjective perception of the role of advertising in the process of online shopping.
- Evaluation of respondents’ knowledge in the field of online marketing and their digital competences.
2.2. Participants
3. Results
3.1. Data Analysis
3.2. Empirical Findings
- Professionalization of Internet use (Y18, Y20).
- Trust in social proof of rightness (Y22, Y28, Y32, Y53).
- Attitude towards online advertising (Y38, Y40, Y43, Y44, Y46, Y86).
- Attitude towards personalization of online advertising content (Y49, Y56, Y59, Y67).
- Willingness to share personal information online (Y77, Y80).
- Attitude towards state intervention in the regulation of online advertising (Y104).
4. Discussion
“Just as our computers need protection against malware, so too we need protection against phishing for phools more broadly defined”.[75]
Author Contributions
Funding
Conflicts of Interest
References
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Selected Characteristics of the Students | Number of Participants and PercentAges | ||
---|---|---|---|
Total | 138 | 100% | |
Sex | Female | 109 | 79% |
Male | 29 | 21% | |
Age | 18–25 | 132 | 96% |
26–35 | 6 | 4% |
Variable | Variable Characteristics |
---|---|
Y 61 | “I have the impression that my personal data are often used to create per-sonalized offers” |
Y 62 | “I feel manipulated by online advertising” |
Y 63 | “I leave online traces that can be used to manipulate my behavior” |
Y 64 | “Advertising has an information advantage over me” |
Template | AIC | BIC |
---|---|---|
One-cluster Model | 1583.32 | 1630.156 |
Two-cluster Model | 1499.838 | 1596.438 |
Three-cluster Model | 1449.675 | 1596.038 |
Four-clusters Model | 1452.034 | 1648.16 |
Latent Class | Proposed Name | Characteristics of Probability |
---|---|---|
1 | Aware N = 85 | High awareness of the use of personal data, the sense of manipulation by online advertising, and leaving digital footprints, and a moderate awareness of the information superiority of advertising. |
2 | Careful and experienced N = 26 | Very high awareness of the use of personal data, a high sense of manipulation by online advertising, a very high awareness of leaving digital footprints, and greater awareness of the information superiority of advertising. |
3 | Inexperienced N = 27 | Low awareness of personal data use, low sense of manipulation by online advertising and leaving digital footprints, and low awareness of advertising information superiority. |
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Sanak-Kosmowska, K.; Wiktor, J.W. Empirical Identification of Latent Classes in the Assessment of Information Asymmetry and Manipulation in Online Advertising. Sustainability 2020, 12, 8693. https://doi.org/10.3390/su12208693
Sanak-Kosmowska K, Wiktor JW. Empirical Identification of Latent Classes in the Assessment of Information Asymmetry and Manipulation in Online Advertising. Sustainability. 2020; 12(20):8693. https://doi.org/10.3390/su12208693
Chicago/Turabian StyleSanak-Kosmowska, Katarzyna, and Jan W. Wiktor. 2020. "Empirical Identification of Latent Classes in the Assessment of Information Asymmetry and Manipulation in Online Advertising" Sustainability 12, no. 20: 8693. https://doi.org/10.3390/su12208693