Amirali Kani | Gordon S. Lang School of Business and Economics

Amirali Kani

Assistant Professor
Department of Marketing and Consumer Studies
Email: 
akani@uoguelph.ca
Phone number: 
52407
Office: 
Macdonald Institute (MINS), Room 259
Summary: 

Amirali Kani is an Assistant Professor of Marketing at the Department of Marketing and Consumer Studies. His research interests broadly cover modeling dynamics in relevant marketing problems; the evolution of consumer preferences for competing brands and the evolution of a competitive market structure.

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Faculty & Staff, marketing faculty

Ph.D., Marketing, Pennsylvania State University

M.Sc., Statistics, Pennsylvania State University

MBA, Sharif University of Technology

B.Sc., Electrical Engineering, Sharif University of Technology

  • Dynamic Segmentation
  • Competitive Market Structure
  • Bayesian Statistics

Dr. Amirali Kani is an assistant professor in the Department of Marketing and Consumer Studies. He specializes in modeling dynamics in marketing, focusing on the evolution of consumer preferences for competing brands and competitive market structures. Dr. Kani holds a Ph.D. in Marketing, and a Master of Science in Statistics from Pennsylvania State University, blending statistical analysis with marketing theory. 

In his paper, "Modeling the evolution of competitive market structure via competitive group dynamics," Dr. Kani examines the evolution of competitive market structures over time within the US banking industry. Using a novel hidden Markov modeling approach, the study considers three sources of competitive heterogeneity: managerial strategy, corporate performance, and the impact of strategy on performance. The model also incorporates observed "entry" and "exit" states to represent firms' market entry and exit, providing a comprehensive view of market dynamics. 

Dr. Kani's research reveals significant structural changes in the US banking industry over the past few decades, challenging prior findings of a relatively stable market structure. Employing a Bayesian framework and a reversible jump Markov chain Monte Carlo estimation procedure, the study determines the number of latent competitive groups and uncovers their characteristics. This methodology offers a nuanced understanding of market evolution by accounting for new entrants and struggling firms that exit the market. 

The paper takes a comprehensive approach to study market evolution, considering all three sources of intra-industry competitive heterogeneity and including firms that do not remain in the study panel throughout the observation period. Dr. Kani's work provides valuable insights for businesses navigating competitive landscapes, offering a deeper understanding of market dynamics and competitive group membership factors.

 

Kani, A., Fong, D. K., & S. DeSarbo, W. (2023). Modeling the evolution of competitive market structure via competitive group dynamics. Journal of Modelling in Management, 18(2), 457-479. https://doi.org/10.1108/JM2-11-2020-0309.