Decision Science
Welcome
Decision Science explores the principles and methods that guide effective decision-making in complex and uncertain contexts. It builds on rationality, decision theory, and utility models, supported by probability and quantitative techniques for evaluating alternatives, analyzing risks, and improving outcomes.
The field also incorporates behavioral perspectives, recognizing the impact of cognitive biases, heuristics, and psychological factors, as well as strategic insights from game theory. With the growth of data, decision science integrates analytics, predictive modeling, and machine learning to strengthen evidence-based choices.
Beyond technical approaches, it emphasizes ethics, sustainability, and social responsibility, ensuring that decisions are effective and aligned with broader societal values. This integrated perspective equips students, researchers, and professionals to make informed, rational, and responsible decisions across diverse domains.
About the Authors
Dr. Rani C Ph.D., is a dynamic educator and analytics-driven HR Business Intelligence professional, passionate about transforming organizations and empowering people through innovative practices and evidence-based insights. With deep expertise spanning human resource management, training and development, compensation management, leadership, business law, HR analytics, and data visualization, she bridges the gap between classic management functions and modern business intelligence techniques. she has qualified the UGC NET in Management, reflecting her strong academic foundation.
Known for her mastery of Python, R, SPSS, Tableau, Power BI, and Excel, Dr. Rani crafts compelling analyses and translates complex workforce data into clear, actionable strategies for growth and performance. Her unique combination of practical HR knowledge and advanced data skills makes her a sought-after mentor, collaborator, and thought leader in both academic and industry circles.
Vijayakumar P is an accomplished educator and data professional with over eight years of teaching and research experience in business analytics, data science, and HR analytics. He is a UGC Junior Research Fellow (JRF) and has qualified the UGC NET and SET in Management multiple times, reflecting his strong academic foundation.
Proficient in Python, R, STATA, SPSS, AMOS, PLS-SEM, Tableau, Power BI, Google Looker Studio, GitHub, and Excel , he has guided students and professionals in transforming data into actionable insights. His teaching spans business analytics using R and Python, HR metrics and dashboards, business forecasting, and business research methods, and he has also developed interactive eBooks to enhance hands-on learning.
Reference books
- Smart Choices: A Practical Guide to Making Better Decisions by John S. Hammond, Ralph L. Keeney, Howard Raiffa.