Business Research Methods is a course designed for future business leaders to harness the power of Evidence-Based Management (EBM)—an approach that uses the best available scientific evidence to make informed decisions. Through practical exercises, students will learn essential skills such as data collection and analysis, interpretation of findings, and assessment of evidence quality. Emphasis is placed on foundational research techniques, including deductive and inductive reasoning and distinguishing between descriptive and causal questions.

This course focuses on the practical applications of EBM, teaching you how to ask the right questions, gather and interpret data, and evaluate evidence to make sound managerial decisions. This course will present the necessary tools required to objectively approach and solve financial problems. This course will discuss and teach the tools required to objectively make capital budgeting, capital structure and working capital decisions. Through case studies, lectures, videos, readings and exams, students learn the basic concepts and how to apply them in financial decision making.

Sylvia Ng is an Associate Professor of Marketing and the Faculty Head for Action Learning at the Asia School of Business. She is also an International Faculty Fellow and Research Affiliate at the MIT Sloan School of Management. Sylvia’s research focuses on services marketing, examining how service providers create value through customer interactions and exploring service exclusion practices. She has published in the Journal of Service Research and won the Best Paper Award at the Frontiers in Service conference in 2023 for her work in the Journal of Services Marketing.

Alexander Eng is an Associate Professor I of Organizational Behavior at the Asia School of Business. His research centers on the intersection of technology and human behavior, with a focus on the Psychology of Technology, Algorithm Aversion, and the Future of Work. He addresses critical questions such as the psychological effects of automation, the influence of AI on employee values, and the emotional responses to technology failures.