Yuliya Yurova

Professor Yuliya Yurova serves as Professor of Research Methods and Decision Sciences at Nova Southeastern University's H. Wayne Huizenga College of Business & Entrepreneurship. She teaches graduate courses including QNT 5160 Analytical Modeling for Decision Making and QNT 5485 Data Mining and Predictive Analytics Fundamentals, leveraging her expertise in quantitative methodologies to prepare students for data-driven business environments.

Her educational background includes a Ph.D. in Business Administration/Statistics from University of Illinois-Chicago, an M.S. in Computer Information Systems from Eastern Michigan University, and a B.A. in Mathematical Economics from Novosibirsky State University. This interdisciplinary foundation supports her integrative research approach spanning business analytics, marketing, and organizational behavior.

Professor Yurova's research examines critical intersections of technology and human behavior in business contexts. She investigates how HR professionals adopt analytics, how mobile devices reshape retail experiences, and how organizational justice affects employee satisfaction - often through cross-cultural comparisons between US and Russian business environments. Her work consistently addresses practical challenges while employing rigorous quantitative methods.

Her publication record demonstrates sustained scholarly impact with recent articles in journals including International Journal of Information Systems and Supply Chain Management (2022), Management Decision (2021), and Journal of Marketing Education (2021). Her research trajectory shows increasing focus on pandemic-era business adaptations and ambidextrous organizational learning.

• Best Paper in Track, Southwest Academy of Management 2017
• Consistent publication in top-tier business journals since 2006
• Research cited for practical HR analytics implementation frameworks
• Methodologically rigorous quantitative studies with real-world applications

Professor Yurova actively bridges academic research and industry practice through studies of actual job market requirements, corporate technology adoption barriers, and retail consumer behavior. Her international collaborations, particularly with Russian institutions, provide unique comparative perspectives on business practices across different institutional environments. Students benefit from her practitioner-relevant research through coursework emphasizing analytical modeling and data mining applications.