Sudip Bhattacharjee, Ph.D.
Professor, University of Connecticut; Senior Research Fellow, US Census Bureau | University of Connecticut
Storrs, CT, UNITED STATES
Extensive research consulting experience with Fortune 100 and US govt on “Big Data” driven decision making in IT and operations.
Biography
Sudip Bhattacharjee is a Professor in the School of Business, University of Connecticut. He currently serves as the Chief, Center for Big Data Research and Applications, US Census Bureau. He is Visiting Faculty at EM Lyon School of Business, France, and Indian School of Business. He was a Visiting Professor at GE Global Research Center, USA. He has previously served as the Assistant Dept. Head of Operations and Information Management, and as the Executive Director of MBA Programs, both in the School of Business, University of Connecticut.
His research interests include information systems economics, energy informatics, digital goods and markets, data analytics in IT and operations, and closed loop supply chains. His research has appeared in premier journals such as Management Science, INFORMS Journal on Computing, Journal of Business, Journal of Law and Economics, ACM Transactions, Journal of Management Information Systems, IEEE Transactions, and other leading peer-reviewed publications. He serves or has served as Associate Editor for Information Systems Research (for 5 years), Special Issue Editor for ACM Transactions on Management Information Systems, guest AE for MIS Quarterly and Decision Sciences Journal, and in prestigious committees such as INFORMS Edelman Award, INFORMS Selects, and various conferences and workshops. He co-chaired CIST 2014 (Conference on Information Systems and Technology), Review Coordinator, WITS 2015 (Workshop on Information Technology and Systems).
He has extensive research consulting experience with Fortune 100 firms on “Big Data” driven decision making in IT and operations. He also teaches a semester-long live data analytics graduate course in partnership with private and govt. organizations.
His research has been highlighted in various media outlets such as Business Week, Washington Post, San Francisco Chronicle, Der Spiegel, Christian Science Monitor, slashdot.org, Business 2.0 Web Guide, and others.
Areas of Expertise (8)
Energy INformatics
Operations Research
Information Systems Economics
Machine Learning
Big Data
Business Analytics
Sustained Closed Loop Supply Chains
Economics of Digital Goods and Intellectual Property Rights
Education (1)
State University of New York - Buffalo: Ph.D. 1999
Links (1)
Media
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Media Appearances (5)
Op-Ed: Respond to the 2020 Census to Save Money, Save Lives, and Be Counted
UConn Today online
2020-04-07
Would you be willing to help save billions of dollars for the United States if you knew that those funds could potentially be redirected to medical research, repairing highways, or paying for mental health services?
7 Big Data Stocks Fighting Coronavirus On and Off the Charts
Markets Insider online
2020-03-27
Big data can play an integral role in this. By making the medical system more efficient, artificial intelligence can help governments and companies make more of the resources they already have. In addition, investments in IT can, in many cases, be more effective than other approaches. Investorplace spoke via e-mail with University of Connecticut Business Professor Sudip Bhattacharjee, Ph.D., about how tech companies are using big data amid the coronavirus pandemic.
Study: Faster internet not a boon to all of CT
Hartford Business Journal online
2018-07-16
“Just having high-speed broadband internet is not enough,” said Sudip Bhattacharjee, a UConn business professor who co-authored the paper. Bhattacharjee said he hopes local officials will use the model to assess the potential economic payback of broadband investments.
Broadband companies, public officials set sights on super-fast internet
Stamford Advocate online
2018-01-07
“Gigabit is the future,” said Sudip Bhattacharjee, a professor in the University of Connecticut’s business school and chief of U.S. Census Bureau’s Center for Big Data Research. “Any business that needs extremely fast internet connections will benefit. And it will be a huge asset for any cities or towns here in Connecticut...”
To Gigabit or Not
UConn Business online
2015-10-14
Professor Sudip Bhattacharjee and graduate students in UConn’s Business Analytics and Project Management (MSBAPM) program ranked each municipality on a three-tier scale, highlighting which are most likely to benefit from adding broadband service.
Research Focus (1)
Data Analytics & Machine Learning
Leading research projects in data analytics and machine learning in US Census Bureau. Have shown value of new data sources and innovative modeling to improve current data products and processes, reduce cost, and create innovation by using alternative data sources and techniques. Extensive research consulting experience with Fortune 100 firms on “Big Data” driven decision making in IT and operations.
Articles (7)
Using Public Data to Generate Industrial Classification Codes
Submitted to CRIW 20192019 Statistical agencies face increasing costs, lower response rates, and increased demands for timely and accurate statistical data. These increased demands on agency resources reveal the need for alternative data sources, ideally data that is cheaper than current surveys and is available within a short time frame.
Predictive models to measure the impact of fiber-optic broadband speeds on local towns and communities
Telematics and Informatics2018 Internet availability and speed can impact a local community’s education, healthcare, safety, and economic development. Currently, there are few, if any, formal analyses to help communities make informed decisions on investments in internet and bandwidth expansion.
Growth Projections and Assortment Planning of Commodity Products Across Multiple Stores: A Data Mining and Optimization Approach
Informs Journal On Computing2015 Product assortment and availability are important determinants of sales success for firms of industrial commodity products. Well-known pricing and promotion strategies for differentiated products do not translate well to such products where price is closely tied to the cost of the products. Consequently, firms with multiple stores of commodity products are faced with the problem of product assortment that incorporates varying geographic and demographic conditions of locations they serve.
Economic sustainability of closed loop supply chains: A holistic model for decision and policy analysis
ScienceDirect2015 We develop an end-to-end model of a closed-loop supply chain (CLSC), and identify the systemic decision making required for economic viability of participants in this chain. Economic viability is a key ingredient for environmentally sustainable behavior and policies, and our decision making framework includes producers, refurbishers and recyclers.
Same Coin, Different Sides: Differential Impact of Social Learning on Two Facets of Music Piracy
Journal of Management Information Systems2014 We demonstrate that two intertwined activities of music piracy, unauthorized obtaining and unauthorized sharing, are differentially influenced by the same social learning environment. We develop a structural model and test it using survey data from a prime demographic set of respondents who engage in music piracy.
Product Assortment Decisions for a Network of Retail Stores using Data Mining with Optimization
Department of Operations and Information Management, University of Connecticut,2012 Retailers with multiple stores of commodity products commonly face the problem of product assortment selection, especially when these stores are spread over several different geographic locations. Given a network of stores, the problem becomes how to incorporate varying market conditions of store locations and at the same time take into account the possible transportation of products between stores, to decide on the right product assortment for a given store location.
Digital goods and markets: Emerging issues and challenges
Journal ACM Transactions on Management Information Systems2011 This research commentary examines the changing landscape of digital goods, and discusses important emerging issues for IS researchers to explore. We begin with a discussion of the major technological milestones that have shaped digital goods industries such as music, movies, software, books, video games, and recently emerging digital goods. Our emphasis is on economic and legal issues, rather than on design science or sociological issues.
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