Monetary Valuation of Privacy
Springer International Publishing (Verlag)
978-3-031-84238-2 (ISBN)
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This book explores the complex domain of personal data valuation, uncovering how individuals perceive the worth of their privacy in an era dominated by digital information exchange. The book delves into the largely scattered empirical research domain of how users value their own data, analyzing how companies like Google and Facebook rely heavily on the continuous collection of personal data to run their business models. By examining concepts like 'Willingness to Pay' and 'Willingness to Accept' in the context of privacy, the book offers a comprehensive overview of how people navigate the often-ambiguous trade-offs between sharing personal information and safeguarding their privacy. Through an empirical analysis supported by 14 crowdsourcing and two field experiments, the author investigates the influence of various factors-such as Privacy Concerns, Privacy Behavior, and Privacy Literacy-on the monetary assessment of privacy. The book also contrasts different methodological approaches to determine which yields the most reliable results, shedding light on the behavioral biases that can skew data valuation. This book is ideal for anyone interested in the intersection of privacy, economics, and digital ethics. The author not only offers insights into the current landscape but also proposes robust models for understanding and predicting how people value their privacy in different contexts. Whether you are a researcher, policymaker, or simply a concerned digital citizen, this book provides valuable perspectives on the monetization of personal data and the future of privacy in the digital age.
Vera Schmitt studied at the University of Konstanz, where she developed a keen interest in statistics and co-founded CorrelAid, a non-profit organization of data science enthusiasts. Afterward, she pursued her passion for data science by enrolling in a Master's program in Data Science at Leuphana University in Lüneburg. As a member of the ChangemakerXchange she actively contributed to projects of CorrelAid in various countries, including Malaysia, Japan, and Singapore. In 2019, Vera successfully defended her Master's thesis titled "The Ethical Dimension of Autonomous Machines: An Algorithmic Analysis of Artificial Moral Agents." Following this, she started a Ph.D. at the Q&U Labe at the TU Berlin, concerning the topic of economic aspects of privacy. Throughout her time at the Q&U Lab, Vera explored diverse areas of interest, where she focuses mainly on disinformation detection, Natural Language Processing (NLP), Human-Computer Interaction (HCI), and ethical and legal considerations concerning machine learning and AI systems. Her dedication to advancing the responsible and ethical application of AI has been evident in her work and research. She builds up and is leading the XplaiNLP group at the QUL, based on the acquired funding from third-party projects.
Chapter 1 Introduction.- Chapter 2 Literature Review and Fundamentals.- Chapter 3 Experimental Setup and Comparison of Contextual Factors.- Chapter 4 Person-Related Privacy Influencing Factors.- Chapter 5 Person-Related General Influencing Factors.- Chapter 6 Empirical Investigation of the Economic Perspective of Privacy Taxonomy.- Chapter 7 Conclusion and Outlook.
| Erscheint lt. Verlag | 22.7.2025 |
|---|---|
| Reihe/Serie | T-Labs Series in Telecommunication Services |
| Zusatzinfo | X, 206 p. 65 illus., 52 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Netzwerke ► Sicherheit / Firewall |
| Informatik ► Software Entwicklung ► User Interfaces (HCI) | |
| Technik ► Elektrotechnik / Energietechnik | |
| Technik ► Nachrichtentechnik | |
| Schlagworte | Contingent Valuation Method • discrete choice experiments • generalized additive model • Modelling privacy behavior • Monetary Assessment of Privacy • Multinomial Logit Model • Online Privacy Literacy Scale • Principal Component Analysis • Privacy Management Theory • Privacy Protection Behavior • usable privacy |
| ISBN-10 | 3-031-84238-3 / 3031842383 |
| ISBN-13 | 978-3-031-84238-2 / 9783031842382 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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