Ramesh Shankar

Associate Professor

Operations and Information Management

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Education

• Ph.D., NYU Stern School of Business, New York
• MBA, IIM Ahmedabad, India
• B.Tech., IIT Madras, India

Expertise

Research areas: Pricing and Licensing of Software and Digital Goods; Environmental Impact of Durable Goods; Online User Behavior.

Research methods: Game Theory, Industrial Organization Economics, Experimental Methods, Econometrics.

Biography

Ramesh Shankar is Associate Professor of Information Systems at the School of Business, University of Connecticut. His current research focuses on Big Data analytics, social media analytics, and the strategic analysis of durable goods innovation, and digital goods such as software, music and video games. His research has appeared in leading journals such as Information Systems Research, MIS Quarterly, Production & Operations Management, Marketing Science, and ACM Transactions. He has served as Associate Editor for MIS Quarterly, and has served as reviewer for ISR, MIS Quarterly, Management Science, Marketing Science, POMS, JMIS, DSS, and ACM Transactions. He has served as a management consultant with multinational corporations including ICICI, GE, and Morgan Stanley. He has also taught courses on IT Strategy, Big Data Analytics, Business Information Systems and Database Management at UConn and NYU Stern. Ramesh has a Ph.D. from the Leonard N. Stern School of Business, NYU, an MBA from the Indian Institute of Management, Ahmedabad, and a B.Tech. from the Indian Institute of Technology-Madras, Chennai, India.

View Ramesh’s research on Google Scholar, Semantic Scholar and SSRN

Selected publications

1. K.Sudhir, Ramesh Shankar, Yuan Jin. “Can Rising Eco-sensitivity Hurt Sustainability? Eco-Impact of Durable Goods Innovations”, Marketing Science. Accepted May 2025.
2. Ramesh Shankar. “Tethered Durable Goods and Installed Base Degradation via Software Updates: Implications for Product Policy.” Journal of Management Information Systems (JMIS), Journal of Management Information Systems 41 (3), 839-865 (Sep 2024). Accepted April 2024.
3. Ramesh Shankar, Lei Wang, Kunter Gunasti, Hongfei Li. “Nonverbal Peer Feedback and User Contribution in Online Forums: Experimental Evidence of the Role of Attribution and Emotions.” Journal of the Association for Information Systems (JAIS) 2 (2024): 267-303. Accepted July 2023.
4. Ramesh Shankar. “Online Reputational Loss Aversion: Empirical evidence from StackOverflow.com.” Decision Support Systems 158 (2022): 113793.
5. Lei Wang, Ram Gopal, Ramesh Shankar, Joseph Pancras. “Forecasting Venue Popularity on Location-Based Services Using Interpretable Machine Learning.” Production & Operations Management 7 (2022): 2773-2788.
6. “Impact of Gamification on Perceptions of Word-of-Mouth Contributors and Actions of Word-of-Mouth Consumers.” Lei Wang, Kunter Gunasti, Ramesh Shankar, Joseph Pancras, Ram Gopal. MIS Quarterly 44:4 (Dec 2020): 1987-2011.
7. Li, Hongfei, Ramesh Shankar, and Jan Stallaert. “Invested or Indebted: Ex-ante and Ex-post Reciprocity in Online Knowledge Sharing Communities.” ACM Transactions on Management Information Systems (TMIS)1 (2020): 1-26.
8. Lee, Ho Cheung Brian, Jose M. Cruz, and Ramesh Shankar. “Corporate Social Responsibility (CSR) Issues in Supply Chain Competition: Should Greenwashing Be Regulated?” Decision Sciences 49.6 (2018): 1088-1115.
   • Best paper finalist, Decision Sciences Journal, November 2019.
9. Aggarwal, Rohit, Ram Gopal, Ramesh Sankaranarayanan, Param Vir Singh. “Blog, blogger, and the firm: Can negative employee posts lead to positive outcomes?” Information Systems Research 23.2 (June 2012): 306-322.
10. Amit Mehra, Ram Bala, Ramesh Sankaranarayanan. “Competitive Behavior-Based Price Discrimination for Software Upgrades.” Information Systems Research. December 2011, Vol.22, No.4.
11. Ramesh Sankaranarayanan, Arun Sundararajan. “Electronic Markets, Search Costs and Organizational Scope.” Information Systems Research. March 2010, Vol.21, No.1.
12. Ramesh Sankaranarayanan. “Innovation and the durable goods monopolist: the optimality of frequent new-version releases.” Marketing Science, November-December 2007, 26(6), 774 – 791.
13. Gediminas Adomavicius, Ramesh Sankaranarayanan, Shahana Sen, Alexander Tuzhilin. “Incorporating Contextual Information in Recommender Systems using a Multidimensional Approach.” ACM Transactions on Information Systems, January 2005, 23(1) 103-145

Syllabi for recent and upcoming courses:

OPIM 5502: Big Data Analytics with Cloud Computing (Fall 2024)

OPIM 5512: Data Science using Python (Fall 2024)