
Department
Designation
Qualifications
Professional Pages
Dr. Raja Sankaran holds a Ph.D. from IIM Ranchi and currently serves as an Associate Professor at the Sri Sathya Sai Institute of Higher Learning (SSSIHL), Deemed-to-be University, Bengaluru. Prior to this, he held academic positions as Associate Professor at CMS Business School, ISME, and Alliance University, Bengaluru.
With over 35 years of combined industry and academic experience, Dr. Raja has held key management roles in multinational corporations, particularly in service delivery functions. During his tenure at CSC, he was based in the UK, serving as Account Lead and General Manager. In this role, he successfully implemented three Six Sigma projects that led to significant cost savings and enhanced service delivery for the National Grid UK account.
Earlier, during his association with NIIT, Dr. Raja conducted more than 100 corporate training programs in Enterprise Management across over 30 countries, including the USA, Asia-Pacific, and African nations. He was also posted in Australia and delivered trainings at renowned global organizations such as Microsoft (Dallas, USA) and in Seoul, South Korea.
Dr. Raja has facilitated over 100 training sessions, workshops, and Faculty Development Programs (FDPs) on a wide range of research and management topics. He is a member of the American Psychological Association (APA), USA.
His research has been published in reputed journals, including those indexed in ABDC such as the International Journal of Bank Marketing (IJBM), Marketing Intelligence & Planning (MIP), Emerald publications, and IIM Kozhikode Society & Management Review.
Areas of Teaching
Marketing Management, Research Methodology, Marketing Metrics, Business Statistics (for PhD research scholars) and various subjects in marketing (Services marketing, B2B marketing, Technology Marketing, Sales Management etc.).
Research Interests
Research interests are in the area of mobile technology, Consumer Behavior, Service Marketing, Brand Equity, Qualitative Techniques (Means-End Chain, Laddering), Quantitative Techniques (Structural Equation Modeling using SPSS & AMOS), Bibliometric analysis, Systematic Literature Review, Meta-analysis and Cryptocurrency.