Author Identifier (ORCID)
Shahid Hussain: https://orcid.org/0000-0001-8200-7561
Violetta Wilk: https://orcid.org/0000-0001-7990-769X
Abstract
This research examines how perceived reciprocity and perceived ethical AI characteristics – fairness, accountability, and transparency (FAT principles) – shape consumers’ willingness to share personal information and its downstream consequences in AI-mediated consumer-brand interactions. Grounded in social exchange theory, we conceptualize personal information sharing as a behavioral gateway through which ethical exchange cues translate into perceived algorithmic legitimacy and intention to co-create value. Using a two-study design, consisting of a scenario-based experiment (n = 184) and a cross-sectional survey (n = 612), the findings of this research show that reciprocity and FAT principles robustly increase willingness to share personal information. Their effects on perceived algorithmic legitimacy and co-creation intentions operate primarily through information sharing rather than directly. Results further indicate that willingness to share personal information functions as a legitimacy-conferring act, supporting a bottom-up, interactional view of legitimacy formation in AI-mediated exchanges. By distinguishing information sharing-based participation from downstream value co-creation, this study advances a process-based account of engagement and offers actionable insights for designing ethically grounded AI systems that encourage voluntary data sharing and sustained consumer collaboration.
Keywords
AI, cross-sectional survey, ethical AI, experimental design, mixed method, reciprocity, social exchange theory, willingness to share personal information
Document Type
Journal Article
Date of Publication
7-1-2026
Volume
155
Publication Title
Technovation
Publisher
Elsevier
School
School of Business and Law
RAS ID
94337
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Comments
Hussain, S., Qazi, A., & Wilk, V. (2026). More than just fair: Legitimizing AI through reciprocity, ethical AI characteristics and personal information sharing. Technovation, 155, 103572. https://doi.org/10.1016/j.technovation.2026.103572