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Mohammed Murtuza Soofi

Quick facts

Prof. Soofi is an Assistant Professor of Marketing specializing in brand gender, anthropomorphism, and inclusive branding. He has obtained his Ph.D. from the University of Bologna, Italy, with a visiting research appointment at UBC Sauder School of Business, Canada. He employs experimental methods, implicit association tests, and text analytics to study consumer behavior. He further teaches marketing and consumer behavior, with research presented at ACR and COBIIR. His research interests include stigmatized consumers, psycholinguistics, and emerging branding strategies.

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Mohammed Murtuza Soofi

Assistant Professor

Prof. Mohammed Murtuza Soofi is an Assistant Professor of Marketing at Mahindra University. He previously served as Assistant Professor at NMIMS Hyderabad and MICA Ahmedabad, and has held teaching and research roles at the University of Bologna and Bologna Business School.
His research focuses on brand gender, inclusive branding, and consumer responses to anthropomorphized brands. He examines how gendered perceptions influence brand strategy, including cross-gender product extensions and communication styles such as humor and sarcasm. He is also interested in psycholinguistics, particularly how language shapes consumer attitudes and decision-making.
Methodologically, his work integrates experiments, implicit association tests, survey research, and text analysis to uncover implicit biases in consumer behavior. His research has been presented at leading conferences such as the Association for Consumer Research (ACR) and COBIIR, and has received awards including Best Doctoral Paper at COBIIR 2023.
He earned his Ph.D. in Marketing from the University of Bologna and was a visiting research scholar at the Sauder School of Business, University of British Columbia. Prior to academia, he worked at Amazon (Hyderabad) and Impakter (Rome), gaining industry experience in operations and market research.

  • Nov 2020 – June 2025
    Ph.D. in Management (Marketing), University of Bologna, Italy
  • May 2024 – Jan 2025
    Visiting International Research Scholar, Sauder School of Business, University of British Columbia, Canada
  • Sep 2018 – Oct 2020
    Master of Science in Business Management, Sapienza University of Rome, Italy
  • Aug 2016 – May 2017
    Post Graduate Diploma in Business Management, University of Hyderabad, India
  • Sep 2011 – Jun 2015
    Bachelor of Technology (Civil Engineering), Jawaharlal Nehru Technological University Hyderabad, India

  • Mohammed, Murtuza S., & Pizzi, Gabriele (2024). “To be or not to be Sarcastic! Gender Stereotypes about a Brand’s Humour.” Advances in Consumer Research, Vol. 51, pp. 366–367.
  • Mohammed, Murtuza S., & Vazrapu, Ravikanth. “Debunking Consumer’s Misbeliefs.” Journal of Marketing Research (Scholarly Insights, AMA DocSIG).
  • Manuscripts Under Review / Revise & Resubmit:

  • Nov 2025 – Present
    Assistant Professor of Marketing, MICA Ahmedabad
  • March 2025 – Oct 2025
    Assistant Professor of Marketing, NMIMS Hyderabad
  • Dec 2023 – May 2024
    Lecturer, Bologna Business School
  • Aug 2022 – Apr 2024
    Academic Tutor, University of Bologna
  • Dec 2021 – May 2022
    Research Associate
  • Dec 2016 – Aug 2018
    Business Operations Specialist, Amazon India

  • His research lies at the intersection of branding, consumer psychology, and social identity. He focuses on:
    • Brand Gender and Strategy: Understanding how gendered brand perceptions shape consumer responses and influence brand extensions.
    • Inclusive Branding: Examining how brands engage with stigmatized and underrepresented consumer groups.
    • Anthropomorphism: Studying how human-like brand representations affect trust, engagement, and forgiveness.
    • Psycholinguistics in Marketing: Investigating how linguistic cues (e.g., verbs, tone, humor) influence consumer judgment and behavior.
  • His current work explores vulnerable consumer segments, entitlement perceptions, and intersectional invisibility in advertising, using a mix of experimental and computational methods.
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