Ph.D, MS, MA, B-Tech

Dr. Deepak Gupta has been teaching at the Amrita School of Business for the past six years as a core member of the Marketing faculty. He has largely taught courses that lie at the intersection of economics and marketing. He also been involved with ASB's University alliance with SAP and earned a SAP BPERP certification. He has done extensive teaching at ASB's Management Development Programs and as invited faculty for different external programs. Currently he teaches in ASB's doctoral program, and facilitates the student-industry interaction. Prior to ASB he has had more than 10 years of combined teaching and research experience at UC Berkeley. He received his master’s degrees in Economics, Marketing Science, and an interdisciplinary Ph. D. in Economics, Sociology and Education from UC Berkeley. His doctoral work was on the post-Ph.D choices and career outcomes of foreign-born US Ph. D.s in Science and Engineering. He worked with several research projects in UC Berkeley both in the field's higher education and transportation research involving the econometric modeling of individual choice behavior. His publications include papers in international journals including "Transportation Research Record," "International Higher Education."Dr. Gupta worked for Ponds India Ltd around three years as Area Sales Manager, planning, implementing, and controlling the sales of Pond's products in specified geographical locations in the Southern and Eastern parts of India.

Positions Held

Worked with Ponds for three years as Area Sales Manager, planning, implementing, and controlling the sales of Pond's products in specified geographical locations in the Southern and eastern parts of India.

Professional Certification


Selected Publications

Publications include papers in international journals including "Transportation Research Record," "International Higher Education".


Publication Type: Conference Paper

Year of Publication Title


A. Mishra, Dr. Sangeetha G, Dr. Deepak Gupta, and N., K., “Influence of Product Perception and Discounts on the Preference of Online Payment”, in 2016 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2016, 2017.[Abstract]

The increasing mobile penetration and improving payment infrastructure have propelled the growth of digital payments in India. But e-Tailers are still struggling with declining growth rates contributed by cash on delivery payments. Despite the enormous research done on various factors of payment infrastructure and their influence on the adoption or use of online payments, the studies have not examined how consumer perception of products and offered discounts can influence their preference towards online payment methods. This study aims to evaluate product perception, discount buying behavior of consumer and cash back related perceptions as motivators of online payments. The data collected through an online survey across India was analyzed using logistic regression. The findings suggest that product perception influences consumers' choice of payment method. It was also found that discount buyers are more likely to prefer online payments and that the awareness of cash back offers improves the preference towards online payments, but additional discounts offered on card payments seem to work far better than cash backs to influence online payment for the purchase. © 2016 IEEE.

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A. Kaveri, Dr. Sangeetha G, Dr. Deepak Gupta, and Pratap, M., “Decoding Engagement in MOOCs: An Indian Learner Perspective”, in Proceedings - IEEE 8th International Conference on Technology for Education, T4E 2016, 2017, pp. 100-105.[Abstract]

Building on existing works that hold 'learner engagement' central to learning, this paper seeks to decode the constituents of student engagement in MOOC learning. Specifically we model the impact of preference for learning styles and the different motivations to learn on learner engagement in MOOCs. We propose that an inclination to learn new things, lifelong learning attributes and paying for a course will positively impact engagement. Treating learner engagement in MOOCs as a 'latent construct', we employ a Structural Equation Model (SEM) on a dataset of Indian MOOC learners to test our hypothesis. Our analysis shows that learners who indicate love for learning as a reason for learning are more engaged in MOOCs. The results also indicate that those learners who are comfortable with learning and understanding new things are more engaged in MOOCs. Learners who prefer learning by themselves show lesser engagement in MOOC learning. We have argued in this paper that the current discussion on learning outcomes in MOOCs is unidimensional in its focus on MOOC success as a 0-1 activity centered on completion. Learning is a multi-dimensional activity and in order to take our current understanding of MOOCs forward, it is important to consider broader aspects of learning and its outcomes. Measuring engagement and the factors that lead to engagement were a first step towards a developing a more holistic understanding of MOOC based learning. The results from this study - one of the first to focus on learner engagement in MOOCs - are encouraging as it proposes an alternate way to look at success in MOOCs. © 2016 IEEE.

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S. Rambhatla and Dr. Deepak Gupta, “Evidence Centred Approach to Measuring Learning Outcomes Amongst Management Students Using Epistemic Games”, in Proceedings - IEEE 8th International Conference on Technology for Education, T4E 2016, 2017, pp. 120-123.[Abstract]

Current teaching methods in business schools such as case studies, instructor-led teaching, and corporate internships have come under increasing scrutiny and questioning in the recent years. In response to the sense that these pedagogical approaches may no longer be working, newer student-centric approaches such as using serious games as a pedagogical tool have been gaining prominence. However, there is no clear definition as yet on what construes an effective game-based learning pedagogical methodology and no definitive method to capture learning outcomes.This paper contributes a learning framework that uses evidence-centered design in epistemic games to model learning outcomes for management students and practitioners. The authors also report on a pilot study involving a new simulation game - STRAT UP - based on the above framework, to explore how such games can help in capturing evidence to measure learning outcomes for the Human Resource function. © 2016 IEEE.

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A. Kaveri, Dr. Sangeetha G, Dr. Deepak Gupta, and Pratap, M., “Decoding the Indian MOOC learner”, in Proceedings of the 2015 IEEE 3rd International Conference on MOOCs, Innovation and Technology in Education, MITE 2015, 2015, pp. 182-187.[Abstract]

Massive Open Online Courses have been looked at both as disruptive innovation as well as the biggest experiment in education in recent times. 15 Million learners have turned to MOOCs as in 2014 and Indians constitute the second largest share of the MOOC user base. This paper attempts to understand some of the essential characteristics that distinguish a MOOC user from a non-user in India. A proprietary survey for understanding MOOC consumers has been used to draw insights on demographics of potential MOOC users including age, occupation, gender, educational backgrounds as well as some salient aspects of their personality, learning styles and life goals. Three logistic regression models have been tested. The first model investigates the impact of background demographic variables and internet skills of respondents on the choice to enroll in at least one MOOC course. The second model includes key personality traits that are hypothesized to influence the user adoption of MOOCs and the full modeladdsvariables pertaining to learning styles, learning environment and life goals. Those with better internet skills and an existing preference for learning through videos were seen to be significantly more likely to adopt MOOCs. Personality traits aligned with an openness to try new things were seen to influence the adoption decision but the learning styles and learning environment did not differentiate users from non-users. The results also indicate a significant influence of gender and age. © 2015 IEEE. More »»