Pubblicazioni

Autori:

Nišević, Maja

Titolo:

Profiling consumers through Big Data Analytics: The interplay between the GDPR and Unfair Commercial Practice Directive

Anno:

2022

Tipologia prodotto:

Doctoral Thesis

Lingua:

Inglese

Parole chiave:

Big Data, AI, ML, profiling, data protection, data subject, conusmer, consumer protection, the GDPR, the UCPD

Abstract (italiano):

It is intuitively understood that the age of Big Data – and the technological phenomenon of Big Data Analytics - is upon us. Undoubtedly, they have opened up a new perspective on reality; it is through technological changes such as these that nowadays we try to understand the world. In the digital world, for commercial business-to-consumer transactions, the consumer is in a weaker position than the business The consumer shops at a distance and increasingly relies on online platforms to come to a decision. In addition, many traders provide products or services in exchange for the consumer’s personal data, which are then used to further profile consumers. This state-of-the-art should be reflected in the law, ensuring the transparency of online marketplaces, giving enforceable rights to consumers, and providing dissuasive sanctions against rogue traders. In light of the impact of Big Data Analytics, this thesis investigates the profiling of consumers through Big Data Analytics, with the main focus on the interplay between the European Union General Data Protection Regulation (GDPR) and European Union Unfair Commercial Practice Directive (UCPD). Hence, this research project involves a detailed analysis of the GDPR and UCPD in consumer profiling via Big Data Analytics, addressing the issue of consumer and data protection law as it may be applied comparably and in a complementary manner to the data economy. Considering the interplay between the GDPR and the UCPD, this research project maps out the existing regulatory rules applicable inside European Union concerning consumer profiling via Big Data Analytics. The mapping of the current regulatory rules relating to consumer profiling by Big Data Analytics includes comprehensive data collection, comprising norms for data protection and the meaning of unfair commercial practice in the European Union. Therefore, the research project generates comprehensive information on the legal status quo – what is permitted and what is not, what may be legally contentious, and where there are legal uncertainties or gaps. The project conducts a normative inquiry on whether and how data protection and the meaning of unfair commercial practice inside the European Union address consumer data and consumer profiling questions through Big Data Analytics. In addition, this research project takes a comparative approach regarding the application of the UCPD and the processing of personal data inside the European Union. The importance of this research is not confined to the legal sphere. It is also significant in the economic area because personal consumer data, in the digital market, are economic assets. They are used to develop market services, consumer profiles, and, ultimately, to influence consumer behaviour. Additionally, research may be helpful in the sphere of technology science. Predictive Big Data Analytics, indeed, depends on the data collected. The quality of the collected data is the main risk in terms of accuracy and completeness. If the data collected for Big Data Analytics and its ability to forecast behaviour excludes some consumers due to bias, the quality of the data and reliability of the foecasts becomes questionable. This may have discriminatory effects on consumers. In relation to the quality of the collected consumer data used in Big Data Analytics, data protection law and the meaning of privacy play a very significant role. Further interpretation of consumer profiling by Big Data Analytics can be useful to develop new and better solutions for the application of Big Data Analytics as a technology tool. Consequently, the research aims to reach a solid conclusion from the data, available to the public and easily accessible and reusable by scientists and experts.

Id prodotto:

125186

Handle IRIS:

11562/1059028

ultima modifica:

4 novembre 2022

Citazione bibliografica:

Nišević, Maja, Profiling consumers through Big Data Analytics: The interplay between the GDPR and Unfair Commercial Practice Directive

Consulta la scheda completa presente nel repository istituzionale della Ricerca di Ateneo