Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Vashist, Dev Dutt; Sharma, Manjari; Pandey, Pallavi Title A name given to the resource The role of behavioral finance in shaping economic decision-making: Insights from AI and big data integration Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Understanding Human Decision-Making in Economic Models;pp.27-64 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3693-8166-3.ch002" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3693-8166-3.ch002</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105007398160?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105007398160?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Vashist D.D., Christ University, India; Sharma M., Christ University, India; Pandey P., Christ University, India Description An account of the resource This chapter examines how behavioral biases and institutional factors influence investment decisions, bridging gaps in behavioral finance literature. It explores cognitive biases like overconfidence, loss aversion, and herd behavior alongside institutional elements such as regulations and market stability. A mixed-methods approach combines survey data from 320 investors and 30 interviews. Findings show a strong link between biases and decisions, with overconfidence and loss aversion as key drivers. Regulatory transparency reduces bias impact, while uncertainty amplifies emotional reactions. The study highlights the need for clear policies, financial education, and future research on AI's role in mitigating biases. 2025, IGI Global Scientific Publishing. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-836938168-7; 979-836938166-3; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online