Texas Tech University

S. Arunachalam

S. Arunachalam

Assistant Professor

Marketing and Supply Chain Management

Room Number: W350

806.834.4387

Research Expertise

  • Marketing & Sales Strategy
  • Marketing - Finance Interface
  • Latent Variable & Multilevel Modeling

Education

  • BE CSE , PSG Tech, Coimbatore, India
  • PGPM, Great Lakes, Chennai, India
  • PhD, Iowa State University, Ames , IA, USA

About

Assistant Professor of Marketing at the Rawls College of Business at Texas Tech. Before joining Rawls College in 2022, Arun was an Assistant Professor at the Indian School of Business (ISB), India, and was the Academic Director of ISB's Centre for Business Innovation. 

Arun is an awarding-winning researcher and teacher. He recently won the prestigious ‘2020 Sheth Foundation Best Paper Award' for his research on New product introductions for low-income consumers in emerging markets. At ISB, he was a three-time winner of the 'Professor of the Year' award for 2019, 2020, and 2021.  

As the Director of ISB's Centre for Business Innovation, Arun, in partnership with Intel India, had secured grants worth $ 275,000 for setting up a virtual centre named Emerging Technology Centre (ETC). ETC aims to address Governance challenges that can be solved by emerging technologies such as Artificial Intelligence, Internet of Things (IoT), drone-based solutions, Machine Learning (ML)-based offerings, etc.  

Before his Ph.D., Arun worked in the industry in different capacities as chief operating officer, Executive Assistant to the MD, and software engineer.
His research is either published or forthcoming in the Journal of the Academy of Marketing Science, International Journal of Research in Marketing, and Production and Operations management. Arun's research broadly focuses on a firm's marketing and sales strategies and their impact on firm-level outcomes. Another focus area includes the interface between the firm's marketing capabilities and innovation outcomes. He uses various quantitative techniques, including Bayesian structural equation modeling, causal inference, and econometric modeling.