Modeling Behavioral and Cognitive Drivers of FinTech Adoption: Trust, Emotion and Digital Decision-Making
A special issue of FinTech (ISSN 2674-1032).
Deadline for manuscript submissions: 20 January 2026 | Viewed by 36
Special Issue Editors
Interests: behavioral finance; technology acceptance models; fintech adoption; sustainable consumption; psychological modeling; cognitive models; trust in technology; human-computer interaction; neuromarketing; eye-tracking
Special Issues, Collections and Topics in MDPI journals
Interests: cryptography; trust and privacy in digital systems; cybersecurity; algorithmic decision-making; risk modeling; fintech security and governance
Special Issues, Collections and Topics in MDPI journals
Interests: quantitative research in finance and education; behavioral modeling; optimization methods; neural network training; educational data analysis; burnout and engagement metrics
Special Issue Information
Dear Colleagues,
The global financial landscape is undergoing a profound transformation, driven not only by rapid technological innovation but also by how individuals cognitively, emotionally, and behaviorally engage with digital financial systems. This Special Issue aims to explore the psychological, behavioral, and cognitive mechanisms underlying FinTech adoption and resistance, with a special focus on trust, emotion, digital decision-making, and user modeling.
We welcome theoretical, empirical, and mixed-method contributions from a wide range of disciplines, including behavioral finance, psychology, information systems, HCI, and cognitive science. Topics may include (but are not limited to) the following: trust in AI-driven financial services, emotional and cognitive responses to robo-advisors, resistance to persuasive FinTech interfaces, and behavioral intention modeling in mobile banking, blockchain platforms, and crowdfunding systems.
Through this Special Issue, we aim to advance understanding of the human side of FinTech and offer actionable insights into the design, implementation, and regulation of financial technologies that align with user psychology, well-being, and trust.
We look forward to your contributions!
Dr. Stefanos Balaskas
Prof. Dr. Yannis C. Stamatiou
Prof. Dr. George S. Androulakis
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. FinTech is an international peer-reviewed open access quarterly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- behavioral FinTech
- digital trust and perceived risk
- cognitive biases in financial decision-making
- emotional engagement in FinTech
- technology acceptance and behavioral models
- AI-driven personalization and persuasion
- resistance to digital nudging
- FinTech UX and HCI
- financial psychology
- robo-advising and user behavior
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