Investigation and Empirical Analysis of Personal Information Collected by Digital Business Platforms
From the Perspective of Big Data Discriminatory Pricing (BDDP)
- 10.2991/978-94-6463-064-0_44How to use a DOI?
- Algorithmic Consumer; Information Collection; Big Data Discriminatory Pricing (BDDP); Informed Consent; Price Discrimination
The rapid development of big data and artificial intelligence is changing the traditional economic model. By collecting a wealth of personal information from the consumer manipulated by algorithms and then using algorithmic technology to accurately profile them, digital business platforms provide greater scope for their pricing activities, thus giving rise to the phenomenon of “big data discriminatory pricing (BDDP)”. The research revealed that the consumer manipulated by algorithms are not fully aware of exactly of what personal details are being collected from them and are not enjoying the full rights of informed consent, resulting in a lack of consent to price discrimination. The correlation analysis of the data suggests that digital business platforms should disclose the personal details collected from individual the consumer manipulated by algorithms to safeguard their rights of informed consent, so as to build a platform of trust between the two parties and adopt reasonable price discrimination under the premise of legal compliance.
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Huali Chen AU - Fei Wang PY - 2022 DA - 2022/12/27 TI - Investigation and Empirical Analysis of Personal Information Collected by Digital Business Platforms BT - Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022) PB - Atlantis Press SP - 410 EP - 420 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-064-0_44 DO - 10.2991/978-94-6463-064-0_44 ID - Chen2022 ER -