Home

Ph.D. Candidate – Management, Indian Institute of Management, Lucknow


Master of Business Administration (M.B.A.), Indian Institute of Management Jammu


Bachelor of Technology (B.Tech.), Indian Maritime University

Prof. (Dr.) Ariit Sengupta

Lecturer

Email ariit.sengupta@jgu.edu.in
Connect with me
ORCID ID 0009-0000-8453-6467
Key Expertise Dynamic pricing, demand learning, behavioral operations, pricing fairness and consumer perception, drip pricing and hidden fees, exploration–exploitation trade-offs, sequential search and optimal stopping, game theory in pricing and markets, algorithmic and AI-driven pricing, econometric analysis of pricing data, experimental methods in operations management, airline and platform pricing, competition policy and market regulation, law and economics of pricing practices, consumer protection and disclosure regulation

Ph.D. Candidate – Management, Indian Institute of Management, Lucknow


Master of Business Administration (M.B.A.), Indian Institute of Management Jammu


Bachelor of Technology (B.Tech.), Indian Maritime University


Biography

Ariit Sengupta is a researcher and academic specializing in Operations Management, pricing strategy, and behavioral decision-making, with a strong interdisciplinary orientation toward pricing regulations, public policy, and political economy. He is a PhD candidate in Operations Management from the Indian Institute of Management Lucknow, where his doctoral research examined the interplay between exploration–exploitation trade-offs and dynamic pricing under information asymmetry.

His research lies at the intersection of analytical modelling, behavioral economics, and empirical analysis. His doctoral work makes three core contributions: (i) a novel dynamic pricing policy for new experiential products that integrates demand learning with fairness perceptions using Construal Level Theory; (ii) large-scale empirical evidence from airline pricing data employing OLS and instrumental variable techniques to study the impact of drip pricing and hidden fees on consumer demand; and (iii) a sequential search model that reframes consumer behavior under drip pricing using dynamic programming, optimal stopping rules, and bandit processes. His work challenges classical assumptions such as Diamond’s Paradox by demonstrating systematic consumer sensitivity to fully revealed prices.

Methodologically, he combines analytical proofs, numerical simulations, lab experiments, and econometric techniques including 2SLS and longitudinal regression. His research interests extend to game theory, algorithmic pricing, AI applications in pricing, and the regulation of pricing practices, with a particular interest in how law and policy interact with firm-level pricing strategies.
Prior to academia, he trained as a naval architect and ocean engineer and holds an MBA in Supply Chain Management and Finance. This engineering-to-management trajectory informs his structured, model-driven approach to social science research.

At Jindal Global Law School, his broader academic agenda is to bridge operations research with legal studies, competition policy, and regulatory design, contributing to evidence-based legal scholarship on markets, pricing, and consumer protection.
 

Business Psychology & Organizational Behavior

Principles of Accounting

University Gold Medal, 2015

VPT-GVMC General Proficiency Prize, 2011-2014

International Mathematics Olympiad - State Rank 2, 2004

Peer reviewer: Journal of Retailing and consumer services, 2025

Centre for Advancing Research in Management and Law

Unraveling the research landscape of dynamic pricing and learning: insights and future research directions (Forthcoming), International Journal of Revenue Management 2026

Ariit Sengupta, Himanshu Rathore & Suresh K Jakhar, Optimal stopping and search rules for sequential search in drip pricing, IMRC, IIM Ahmedabad 2025

Ariit Sengupta & Himanshu Rathore Causal factors leading to the success of drip pricing, IMRC, IIM Ahmedabad 2025

Decrease the price now, increase it later: A novel approach to demand learning and dynamic pricing of new experiential products through the lens of construal level theory (DOI: https://link.springer.com/article/10.1057/s41272-024-00505-6 ), Journal of Revenue and Pricing Management 2024

Ariit Sengupta & Himanshu Rathore Dynamic pricing with experimentation and fairness concerns,INFORMS Annual Meeting 2023

Ariit Sengupta, Utkarsh Shivam & Devpriya Sarkar A system dynamics view of agricultural diplomacy of India, 5th International Conference on Globalization & International Relations 2022
Email ariit.sengupta@jgu.edu.in
ORCID ID 0009-0000-8453-6467
Key Expertise Dynamic pricing, demand learning, behavioral operations, pricing fairness and consumer perception, drip pricing and hidden fees, exploration–exploitation trade-offs, sequential search and optimal stopping, game theory in pricing and markets, algorithmic and AI-driven pricing, econometric analysis of pricing data, experimental methods in operations management, airline and platform pricing, competition policy and market regulation, law and economics of pricing practices, consumer protection and disclosure regulation
Apply Now