Understanding Individuals’ Willingness for Prosocial Data Disclosure: Exploring Antecedents and Investigating Strategies for its Promotion

  • Privacy research has traditionally focused on understanding individuals' behavior in disclosing personal data by assuming that individuals disclose their data mainly out of self-interest. However, in many contexts, individuals disclose their data primarily for the benefit of others and society, thereby showing a form of prosocial behavior. This dissertation conceptualizes these types of data disclosure as prosocial data disclosures and argues that existing privacy research frameworks, such as the privacy calculus, have not been sufficiently applied in privacy research and need to be reevaluated to fully capture the complexities of prosocial data disclosures. Despite the growing relevance of understanding individuals’ willingness for prosocial data disclosures, existing research in this field is limited. This dissertation consists of four essays that seek to deepen the understanding of the underlying decision-making processes of individuals by exploring the antecedents and investigating strategies that promote prosocial dataPrivacy research has traditionally focused on understanding individuals' behavior in disclosing personal data by assuming that individuals disclose their data mainly out of self-interest. However, in many contexts, individuals disclose their data primarily for the benefit of others and society, thereby showing a form of prosocial behavior. This dissertation conceptualizes these types of data disclosure as prosocial data disclosures and argues that existing privacy research frameworks, such as the privacy calculus, have not been sufficiently applied in privacy research and need to be reevaluated to fully capture the complexities of prosocial data disclosures. Despite the growing relevance of understanding individuals’ willingness for prosocial data disclosures, existing research in this field is limited. This dissertation consists of four essays that seek to deepen the understanding of the underlying decision-making processes of individuals by exploring the antecedents and investigating strategies that promote prosocial data disclosure. By employing different research methods, including systematic literature reviews, qualitative and quantitative surveys, interviews, workshops, and conjoint analysis, this dissertation contributes to the identification of the multifaceted antecedents of prosocial data disclosure which can be classified into different drivers and barriers. Furthermore, by integrating insights from different disciplines such as behavioral economics, social psychology, and information systems research, this dissertation provides empirical evidence for the use of message framing and the deliberate emphasis on impact uncertainty as two promising strategies in promoting prosocial data disclosure. The findings derived from all four essays inform privacy research and prosocial behavior research about the need for sophisticated theories that are capable of better capturing the complexities of prosocial data disclosure. Additionally, the findings offer practical implications for designing ethically responsible data disclosure practices while respecting individual privacy rights.show moreshow less

Download full text files

Export metadata

Additional Services

Search Google Scholar
Metadaten
Author:Abdul Muqeet Ghaffar
URN:urn:nbn:de:bvb:739-opus4-15001
Referee:Thomas Widjaja, Franz Lehner
Document Type:Doctoral Thesis
Language:English
Year of Completion:2024
Date of Publication (online):2024/10/22
Date of first Publication:2024/10/22
Publishing Institution:Universität Passau
Granting Institution:Universität Passau, Wirtschaftswissenschaftliche Fakultät
Date of final exam:2024/09/26
Release Date:2024/10/22
Tag:behavioral economics; impact uncertainty; message framing; privacy; social psychology
Page Number:iv, 94 Seiten
Institutes:Wirtschaftswissenschaftliche Fakultät
Dewey Decimal Classification:3 Sozialwissenschaften / 30 Sozialwissenschaften, Soziologie / 300 Sozialwissenschaften
open_access (DINI-Set):open_access
Licence (German):License LogoStandardbedingung laut Einverständniserklärung