Towhidul Islam | Gordon S. Lang School of Business and Economics

Towhidul Islam

University Research Leadership Chair and Professor
Department of Marketing and Consumer Studies
Phone number: 
519 824 4120 ext. 53835
Macdonald Institute (MINS), Room 206B

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Dr. Towhid Islam ( is Professor of Marketing and Consumer Studies and University Research Leadership Chair at the Gordon S. Lang School of Business and Economics, University of Guelph, Canada. His PhD is in Management Science under supervision of Professor Nigel Meade from Imperial College Business School, University of London, UK. His doctoral dissertation was in areas of modeling and forecasting diffusion of innovations. Professor Islam started working with Professor Jordan Louviere, the pioneer of discrete choice in 1998 as Louviere's Post-doctoral student at the University of Sydney, Australia. Since then, both are closely working in areas in discrete choice experiments, advanced choice models, and preference stability combining stated and revealed preference data from longitudinal studies among other theoretical and methodological issues. He has held research and faculty positions at the University of Sydney, Australia; University of Technology, Australia; Dalhousie University, Canada; and the University of Northern BC, Canada.

His work has appeared in leading journals including Management Science, Journal of Consumer Research, Journal of Consumer Psychology, European Journal of Operational Research, the International Journal of Research in Marketing, Decision, Journal of Choice Modeling, Journal of Consumer Affairs, and the International Journal of Forecasting among other outlets. His publications have received over 4000 citations to date from journals across the globe, and his h-index is 30; an indicator of lifetime achievement that accounts for both productivity and impact. The originality and novelty of his research approach has directly contributed to being awarded three Social Sciences and Humanities Research Council of Canada (SSHRC) grants plus major funding from the Australian Research Council (ARC).

At the University of Guelph, he taught Research Methods, Multivariate Research Methods, Marketing Analytics, Structural Equation Modeling, Applied Statistics, and New Product Development and Forecasting. He has offered invited workshops at Seoul National University, S. Korea; Zhejiang University of Finance and Economics, China; University of Technology Sydney, Australia; Vienna University of Economics and Business, Austria; and University of Sao Paulo, Brazil.

Towhid islam is the lead researcher and instructor of DataOrbit (, a leader in advancing decision intelligence.


Google Scholar Citations:                                                             (

  • Ph.D. Imperial College Business School, University of London, UK.
  • Cert. in Machine Learning and Artificial Intelligence, MIT
  • D.I.C. Diploma of Imperial College, London, UK.
  • M.B.A. Institute of Business Administration (IBA), Dhaka University, Bangladesh.
  • M.Sc. in Telecommunications Eng. Sofia, Bulgaria.



Innovation Adoption and Diffusion 

  • Economic Attractiveness and Market Potential in the Segmentation of International Smartphone and Mobile Broadband Markets
  • Technologial Convergence in Emerging Markets
  • Mobile Money and Internet of Things (IoTs)
  • Multi-generations of Technological Innovations of Renewable Technologie
  • Forecasting Price Decline during  Stages of Mobile Phone Penetrations Across Nations
  • Link between Innovation Diffusion and Evolution of Technological Performance
  • International Market Entry Decisions by Telecom Operators

Choice Experiments and Choice Models

  • Evaluating Consumer Choice by Comparing and Combining Survey and Real Purchase Data
  • Stated Preference Volumetric Choice Experiments (VCE): Design, Analysis and Example
  • Modeling Stockpilable Product Purchase Decisions Using Volumetric Choice Experiments

Machine Learning and Artificial Intelligence (AI) in Predictions 

  • The Role of Sociodemographic Variables in Predicting Purchase Decisions: Can Machine Learning Procedures (MLP) Improve Their Usefulness in Targeting?  


Open to advising MSc students:  YES

Open to advising PhD students:  YES