This conference explores the cutting-edge intersection of behavioral economics and big data analytics to design hyper-personalized nudges that accommodate individual cognitive biases, preferences, and situational contexts. Traditional nudging uses broad default settings or cues, but leveraging AI and real-time behavioral data enables tailoring interventions for higher efficacy and ethical precision. The event covers theoretical foundations, technological innovations, ethical considerations, and case studies across digital finance, health, and sustainability domains where personalized nudging can enhance decision-making without compromising autonomy.
Keynote Speakers: Experts in behavioral economics, AI ethics, and data science share theoretical and applied insights.
Session Chairs: Facilitate sessions, moderate discussions, and manage participant engagement.
Presenters: Academics, data scientists, policy makers, and industry practitioners present research, case studies, and emerging methods.
Participants: Engage in Q&A, workshops, and networking opportunities.
Technical Review Committee: Screens submissions for relevance and academic rigor.
Participate and Contribute (Who Benefits):
Behavioral Scientists and Economists: Advance methods to integrate individual biases into nudge design.
AI and Data Analysts: Explore ethical use of personal data in hyper-personalized interventions.
Policy Makers and Regulators: Understand frameworks for transparency and consent in behavioral targeting.
Business and Healthcare Innovators: Apply personalized nudging to improve customer outcomes and compliance.
Academics and Students: Present research and publish findings in top-tier indexed journals.
Benefits:
Certificate of Participation issued based on completed feedback.
Commemorative momento acknowledging contribution and participation.
Abstracts and selected papers published in Scopus, CrossRef, Web of Science (WoS), Elsevier, and SCI-indexed journals.
Abstract Topics / Call for Papers (CFP) Tracks:
Theoretical Models for Personalized Behavioral Nudges
Big Data Techniques for Capturing Individual Biases
AI-Powered Real-Time Behavioral Interventions
Ethical Considerations and Data Privacy in Personalization
Measuring Effectiveness: Metrics and Long-Term Impact
Case Studies: Finance, Health, Environmental Sustainability
User Autonomy and Informed Consent in Digital Nudging
Algorithmic Fairness and Avoiding Bias Amplification
Regulation and Policy Development for Personalized Nudges
Future Directions in Hyper-Personalized Behavioral Design
Registration:
Online registration for researchers, practitioners, and students.
Clear abstract submission guidelines, deadlines, and review processes.
Participants receive access to live sessions, recordings, certification, and publication.
Detailed Program Grid (2 Half Days, 9 AM to 1 PM)
Time
Day 1
Day 2
09:00 – 09:15
Opening Remarks & Conference Introduction
Recap and Keynote Address
09:15 – 10:00
Keynote Session I: Foundations of Personalized Nudging
Keynote Session III: Ethical and Privacy Dimensions
10:00 – 10:45
Technical Session I: Data-Driven Identification of Biases
Technical Session III: Measuring Nudge Impact Across Domains
10:45 – 11:00
Q&A and Networking Break
Q&A and Networking Break
11:00 – 11:45
Technical Session II: AI and Real-Time Behavioral Adjustments
Panel Discussion: Regulation, Transparency, and User Consent
11:45 – 12:30
Case Studies and Research Presentations
Technical Session IV: Future Research and Emerging Technologies
12:30 – 13:00
Participant Feedback and Interactive Discussion
Closing Remarks and Certificate Distribution
This conference provides a platform for exploring the frontier of behavioral personalization through big data, enabling precise yet ethical nudging strategies aligned with individual cognitive profiles, supplemented with certification and publication in leading academic journals.
