Artificial Intelligence in Neurofinance and Behavioral Finance Decision Making for Sustainable Business Management

Chapter 1 Development of Artificial Intelligence in Financial Services:  Pathway   towards Digitalization  for Sustainability  Chapter 2 Artificial Intelligence in Financial Services: Structural Transformation, Emerging Risks, and the Question of Social Legitimacy Chapter 3 Green Ledgers and Carbon Algorithms: Deconstructing the Environmental Impact of AI in Financial Planning Chapter 4 The Role of Artificial Intelligence in Neurofinance and Behavioural Finance: Transforming Financial Decision-Making in the Digital Era Chapter 5 A Behavioral and AI-Driven Framework for Financial Behavior Prediction Chapter 6 Behavioral Biases and Neurofinance Perspectives in Sustainable (ESG) Investing: A Study on Indian Youth Chapter 7 Role of Artificial Intelligence  in Sustainable Investment  Toward Development  of  ESG  Framework  Chapter 8 Role of Artificial Intelligence in Data Collection: Analysis and Comparative Analysis  For  Sustainability  Chapter 9 Efficiency vs Accountability: AI Enhanced Strategic Decision Framework in Long Term Planning Chapter 10 AI, Sustainability & Global Equity: Impact of Artificial Intelligence in Long Term Planning Chapter 11  Artificial  Intelligence  in Strategic Decisions :  Opportunities and futuristic challenges   Chapter 12 AI-Enhanced Strategic Framework for Supply Chain Risk Prediction and Operational Optimization Chapter 13 Building Ethical and Sustainable Enterprises through Generative AI and Behavioural Finance Chapter 14 Financial Behaviour and Neurofinance :  AI Data  Driven  Approach  for Development of  ESG  Framework \ Chapter 15 Profitability and Purpose: leveraging the metaverse for financial and social impact (for-profit and non-profit organizations Chapter 16 FinTech Adoption Among Students: Examining the Impact of Self-Efficacy and Perceived Risk 

Biography

Sachi Nandan Mohanty (Senior Member, IEEE) received the Ph.D. degree from Indian Institute of Technology Kharagpur, India, in 2015, with MHRD Scholarship from the Government of India. He is currently a Professor, School of Computer Science & Engineering, VIT-AP University, Amaravati, Andhra Pradesh, India. His research areas include Data mining, Big Data Analysis, Cognitive Science, Fuzzy Decision Making, Brain-Computer Interface, Cognition, and Computational Intelligence.

Dr. Rakesh Kumar is an Assistant Professor at the School of Computer Science and Engineering (SCOPE) at VIT-AP University, Amaravati, Andhra Pradesh, India. He holds a PhD from IISc Bangalore and has expertise in areas including machine learning, civil engineering applications, and sustainable technology research. Dr. Kumar is actively involved in academic research and has contributed to publications on topics such as Industry 5.0, sustainable manufacturing practices, and the integration of AI and IoT technologies. He has been recognized for his work in structural equation modeling (SEM), ISM, and Fuzzy TOPSIS research methodologies, demonstrating his commitment to advancing both theoretical knowledge and practical applications in computer science and engineering.

Dr. Isaías Scalabrin Bianchi is a distinguished academic and researcher at the Federal University of Santa Catarina (UFSC) in Brazil. He holds expertise in computer science and engineering, with particular focus on artificial intelligence, machine learning, and computational systems. Dr. Bianchi has contributed significantly to the academic community through his research publications and involvement in various technological innovation projects. His work at UFSC involves both teaching and conducting cutting-edge research that bridges theoretical computer science concepts with practical applications in emerging technologies. He is recognized for his contributions to the advancement of computational intelligence and his role in fostering academic excellence at one of Brazil's leading federal universities.