Abstract

Enhancing Decision-Making through the Application of Behavioral Economics and Data Science

Dr. K. B. Ratna Kumari

Volume: 15 Issue: 2 2025

Abstract:

Big data has revolutionized the field of behavioral economics, enabling researchers to analyze vast amounts of data to understand consumer behavior, preferences, and decision-making processes. By integrating big data with behavioral economics, organizations can gain valuable insights into human behavior, predict future trends, and develop effective marketing and policy strategies. Predictive Analytics: Big data enables predictive analytics, which can forecast consumer behavior based on historical data, allowing companies to tailor their marketing strategies and improve customer engagement. Personalization: Companies use big data to personalize experiences and products, such as Netflix's recommendation algorithm, which suggests shows and movies based on a user's viewing history. Real-Time Feedback: Big data provides real-time feedback on consumer behavior, enabling businesses to adjust their strategies instantaneously, such as social media platforms tracking user engagement with content. Behavioral Segmentation: Machine learning models can segment populations into clusters based on similar behaviors or preferences, allowing retailers to personalize marketing efforts and improve customer engagement. This study explores the integration of behavioral economics and data science to enhance decision-making in various contexts. By combining insights from behavioral economics with data-driven approaches, organizations can develop more effective strategies to influence behavior, improve outcomes, and drive success. The application of behavioral economics principles, such as nudges and framing effects, can be optimized through data science techniques, including machine learning and predictive analytics. This integration enables more accurate predictions, personalized interventions, and data-informed decision-making. The findings highlight the potential of this interdisciplinary approach to improve decision-making in fields such as marketing, public policy, and healthcare

DOI: http://doi.org/10.37648/ijrssh.v15i02.014

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