Alok Gupta

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Alok Gupta
NationalityAmerican
Occupation(s)Information scientist, economic engineer, and academic
AwardsCareer Award, National Science Foundation
LEO Award, Association for Information Systems
Academic background
EducationB.Tech
MS in Mine Electrical Systems
PhD in Management Science and Information Systems
Alma materBanaras Hindu University
The Pennsylvania State University
The University of Texas at Austin
ThesisA Real-Time Priority Pricing Approach for Resource Allocation in Multi-Service Class Data Communication Networks (1996)
Doctoral advisorAndrew B. Whinston
Dale Stahl
Academic work
InstitutionsUniversity of Connecticut
University of Minnesota

Alok Gupta is an American information scientist, economic engineer, and academic. He is the Professor of Information and Decision, a Senior Associate Dean of Faculty, Research and Administration, and Curtis L. Carlson School Wide Chair in Information Management in the Carlson School of Management at the University of Minnesota.[1]

Gupta's research interests include the impact of technology on business model, digital transformation, data-driven decision-making, and the design and adoption of emerging technologies. He is the recipient of the Career award by the National Science Foundation (NSF),[2] and the LEO award by the Association for Information Science (AIS).[3]

Gupta is a Fellow of the Association for Information Science[4] and a Distinguished Fellow of INFORMS ISS.[5] He has held several editorial appointments throughout his career, including serving as the Editor-in-Chief and Senior Editor of Information Systems Research.[6] He also serves as an Associate Editor of the Brazilian Electronic Journal of Economics.[7]

Education[edit]

Gupta enrolled at Banaras Hindu University where he completed a Bachelor of Technology in Mining Engineering from its Indian Institute of Technology in 1988. He then completed his master's degree in Mine Electrical Systems from the Pennsylvania State University in 1991. Later, he earned a Ph.D. in Management Science and Information Systems from the University of Texas Austin in 1996 under the supervision of Andrew B. Whinston and Dale Stahl. His thesis was titled, "A Real-Time Priority Pricing Approach for Resource Allocation in Multi-Service Class Data Communication Networks".[8]

Career[edit]

Following his PhD Gupta began his academic career as a Visiting assistant professor in the Operations and Information Management Department at the University of Connecticut from 1996 to 1997 and became associate professor in 2001. He moved to the Carlson School of Management at the University of Minnesota in 2001 and was promoted to Professor in 2005. Since 2005 he has been a professor in the Information and Decision department at the University of Minnesota.[9]

Gupta is the Publisher of MIS Quarterly and also holds an appointment as the Senior Associate Dean of Faculty in Research and Administration at the Carlson School of Management, the University of Minnesota.[9]

Research[edit]

Gupta's research centers on digital innovation, business analytics, and strategic IT management. His particular focus lies in the areas of electronic commerce, online auction, and bidding strategies. He has authored over 80 articles.[10]

Electronic commerce[edit]

Gupta has done research in the area of Electronic commerce particularly focusing on consumer behavior,[11] risk prediction, pricing strategies,[12] and sales management.[13] During his early research, he proposed a stochastic equilibrium concept for a general mathematical model and demonstrated how it supports optimal congestion internet prices[14] and also provided a framework to manage resources in intranets using the concepts of electronic commerce.[15] In 2004, he designed a model named GIST to provide assistance in managing and designing the interactivity and content of customer-centric websites[16] and developed an economic model that captured consumer shopping channel choices based on the characteristics of the shopping channel and consumer risk profiles.[17] He highlighted the use of transparency strategy as an efficient way of enhancing internet-based selling and how this could help in increasing a firm's value on the internet.[18] In related research, he explored the impact of information technology on transparency, market information, and its structure and developed a theoretical framework to understand the process through which emerging dominance of transparent electronic markets can be inhibited.[19] He investigated the concept of smart markets as well, which utilizes computational tools to comprehend intricate trading environments and deliver real-time decision support to human decision-makers.[20] He also analyzed investment incentives for network infrastructure owners and explored two different pricing strategies: congestion-based negative externality pricing and the prevalent flat-rate pricing.[21] In his work titled, "Consumption and Performance: Understanding Longitudinal Dynamics of Recommender Systems via an Agent-Based Simulation Framework," he developed an agent-based modeling and computational simulation approach to investigate several factors that affect the temporal dynamics of recommender systems' performance.[22]

Auction and bidding strategies[edit]

Another major area of Gupta's research interest is online auctions[23] and bidding strategies. He focused on analyzing[24] and designing auctions,[25][26] understanding bidders' behavior,[27][28] and investigating how these auctions serve as an emerging mercantile process.[29] He conducted research on multi-item online auctions, providing a comparative analysis between the Vickery version and the English version. His findings indicated that while the English version may dominate, the Vickery version exhibited higher allocative efficiency.[30] He then presented a simulation approach using the characteristics of the Yankee auction in order to optimize sellers' revenue.[31] Together with Ravi Bapna and Paulo Goes, he also suggested a cost-effective and risk-free simulation approach to investigate the decision behavior of bid makers and takers in web-based dynamic price-setting processes.[32] Additionally, he presented a novel feedback scheme, specifically designed for multiattribute auctions, which helped in providing protection of buyer's preference information from the supplier and the cost schedule of supplier from the buyer.[33] In 2009, he introduced the concept of auction overlap and examined how market-level factors such as price information, degree of overlap, auction format, and market supply influence the auction prices.[34]

Continuous combinatorial auction[edit]

Gupta's research group has also worked on the Continuous Combinatorial Auction (CoCoA) project. The project utilized design science principles to design, build, validate, and evaluate a combinatorial bidding environment that aimed to lower computational and cognitive hurdles in order to realize the potential of the mechanism.[35] Additionally, a key objective of the project was to promote acceptance and utilization of this complex mechanism by providing information and tools tailored to meet users' task requirements.[36] The designed artifacts were subsequently evaluated using economic[37] and behavioral measures.[38]

Next-generation high-speed auction markets[edit]

Gupta is known for his work in the field of information systems, including the collaborative effort titled "Designing next-generation high-speed auction markets". The focus of this research project was to create IT tools that enhance quick decision-making in time-sensitive and information-rich B2B auction markets. He and his team established a partnership with the Dutch Flower Auctions (DFA). They developed a stable taxonomy of bidding strategies that allow market operators to adapt and optimize the key auction parameters in real- time[39] and designed a flexible decision support framework that focuses on two models, namely prediction and optimization models. The results of the framework showed that it can help auctioneers make better tradeoffs between revenue and throughput (i.e., market clearing speed) under different market conditions[40] and that it can increase the revenue and price stability.[41] In addition, they developed a Hybrid Auction Mechanism that mitigates market congestion which can speed up the market clearing process without affecting expected revenue, and thus effectively mitigate the congestion problem.[42]

Artificial intelligence in floriculture chain (iFlow)[edit]

During his time at Erasmus University, Gupta collaborated with the Rotterdam School of Management (RSM) group on a project called "Artificial Intelligence in the Floriculture Chain" (iFlow). The project was designed to develop advanced analytical methods and tools that would advise floriculture auctioneers on achieving a balance between higher commercial revenues, lower logistical distribution costs, faster deliveries, and reduced carbon emissions in transportation. The group executed eight notable projects, including bidder heterogeneity and the development of a bidder typology based on actual bidding data,[43] multi-transaction auctioning, auctioning sequence, and role of winner bidder identification.[44]

Awards and honors[edit]

  • 2001 – Career Award, NSF[2]
  • 2006 – Best Paper Award, Journal of AIS[2]
  • 2006 – Publication of the year, Senior IS Scholars (AIS)
  • 2009 – Best Paper Award, INFORMS
  • 2009 – Best Poster Award, Phoenix[clarification needed]
  • 2011, 2012, 2021 – Design Science Award, INFORMS[45]
  • 2014 – Distinguished Academic Fellow, INFORMS[4]
  • 2016 – Fellow, AIS[5]
  • 2020 – Impact Award, AIS
  • 2021 – Best Paper Award, Information System Research
  • 2021 – President's Service Award, INFORMS[46]
  • 2021 – Practical Impact Award, INFORMS[47]
  • 2021 – LEO Award, AIS[3]

Selected articles[edit]

  • Gupta, A., Su, B. C., & Walter, Z. (2004). An empirical study of consumer switching from traditional to electronic channels: A purchase-decision process perspective. International Journal of Electronic Commerce, 8(3), 131–161.
  • Bichler, M., Gupta, A., & Ketter, W. (2010). Research commentary—designing smart markets. Information Systems Research, 21(4), 688–699.
  • Adomavicius, G., Gupta, A., & Sanyal, P. (2012). Effect of information feedback on the outcomes and dynamics of multisourcing multiattribute procurement auctions. Journal of Management Information Systems, 28(4), 199–230.
  • Bhattacharya, S., Gupta, A., & Hasija, S. (2014). Joint product improvement by client and customer support center: The role of gain-share contracts in coordination. Information Systems Research, 25(1), 137–151.
  • Bapna, R., Gupta, A., Ray, G., & Singh, S. (2016). Research note—IT outsourcing and the impact of advisors on clients and vendors. Information Systems Research, 27(3), 636–647.

References[edit]

  1. ^ "Alok Gupta". Carlson School of Management.
  2. ^ a b c "Awards and Honors | Journal of the Association for Information Systems | AIS Journals | Association for Information Systems".
  3. ^ a b "AIS LEO Award – History of AIS".
  4. ^ a b "AIS Fellow Award – History of AIS".
  5. ^ a b "Alok Gupta". INFORMS.
  6. ^ "Editorial Board | Information Systems Research".
  7. ^ "Alok Gupta". College of Science and Engineering.
  8. ^ Gupta, Alok (1996). A real-time priority pricing approach for resource allocation in multi service class data communication networks (Thesis).[non-primary source needed]
  9. ^ a b "Alok Gupta". Carlson School of Management.
  10. ^ "Alok Gupta". scholar.google.com.
  11. ^ Gupta, Alok; Su, Bo-chiuan; Walter, Zhiping (April 20, 2004). "An Empirical Study of Consumer Switching from Traditional to Electronic Channels: A Purchase-Decision Process Perspective". International Journal of Electronic Commerce. 8 (3): 131–161. doi:10.1080/10864415.2004.11044302. S2CID 16054242 – via CrossRef.
  12. ^ Granados, Nelson; Gupta, Alok; Kauffman, Robert J. (November 1, 2008). "Designing online selling mechanisms: Transparency levels and prices". Decision Support Systems. 45 (4): 729–745. doi:10.1016/j.dss.2007.12.005 – via ScienceDirect.
  13. ^ Ketter, Wolfgang; Collins, John; Gini, Maria; Gupta, Alok; Schrater, Paul (December 20, 2012). "Real-Time Tactical and Strategic Sales Management for Intelligent Agents Guided by Economic Regimes". Information Systems Research. 23 (4): 1263–1283. doi:10.1287/isre.1110.0415. hdl:1765/23339. S2CID 2810884 – via CrossRef.
  14. ^ Gupta, Alok; Stahl, Dale O.; Whinston, Andrew B. (May 1, 1997). "A stochastic equilibrium model of internet pricing". Journal of Economic Dynamics and Control. 21 (4): 697–722. doi:10.1016/S0165-1889(96)00003-6 – via ScienceDirect.
  15. ^ Gupta, Alok; Stahl, Dale O.; Whinston, Andrew B. (November 1, 1998). "Managing computing resources in intranets: an electronic commerce perspective". Decision Support Systems. 24 (1): 55–69. doi:10.1016/S0167-9236(98)00063-3 – via ScienceDirect.
  16. ^ Albert, Terri C.; Goes, Paulo B.; Gupta, Alok (2004). "GIST: A Model for Design and Management of Content and Interactivity of Customer-Centric Web Sites". MIS Quarterly. 28 (2): 161–182. doi:10.2307/25148632. JSTOR 25148632 – via JSTOR.
  17. ^ Gupta, Alok; Su, Bo-chiuan; Walter, Zhiping (December 1, 2004). "Risk profile and consumer shopping behavior in electronic and traditional channels". Decision Support Systems. 38 (3): 347–367. doi:10.1016/j.dss.2003.08.002 – via ScienceDirect.
  18. ^ Granados, Nelson; Gupta, Alok; Kauffman, Robert J. (June 20, 2005). Advances in the Economics of Information Systems. IGI Global. pp. 80–112 – via www.igi-global.com.
  19. ^ "The Impact of IT on Market Information and Transparency: A Unified Theoretical Framework".
  20. ^ Bichler, Martin; Gupta, Alok; Ketter, Wolfgang (December 20, 2010). "Research Commentary —Designing Smart Markets". Information Systems Research. 21 (4): 688–699. doi:10.1287/isre.1100.0316. hdl:1765/32046 – via CrossRef.
  21. ^ Gupta, Alok; Jukic, Boris; Stahl, Dale O.; Whinston, Andrew B. (June 20, 2011). "An Analysis of Incentives for Network Infrastructure Investment Under Different Pricing Strategies". Information Systems Research. 22 (2): 215–232. doi:10.1287/isre.1090.0253 – via CrossRef.
  22. ^ Zhang, Jingjing; Adomavicius, Gediminas; Gupta, Alok; Ketter, Wolfgang (March 20, 2020). "Consumption and Performance: Understanding Longitudinal Dynamics of Recommender Systems via an Agent-Based Simulation Framework". Information Systems Research. 31 (1): 76–101. doi:10.1287/isre.2019.0876. S2CID 202300723 – via CrossRef.
  23. ^ "Online Auctions: A Closer Look".
  24. ^ Bapna, Ravi; Goes, Paulo; Gupta, Alok (January 20, 2003). "Analysis and Design of Business-to-Consumer Online Auctions". Management Science. 49 (1): 85–101. doi:10.1287/mnsc.49.1.85.12754 – via CrossRef.
  25. ^ Bapna, Ravi; Goes, Paulo; Gupta, Alok; Karuga, Gilbert (September 20, 2002). "Optimal Design of the Online Auction Channel: Analytical, Empirical, and Computational Insights". Decision Sciences. 33 (4): 557–578. doi:10.1111/j.1540-5915.2002.tb01656.x – via CrossRef.
  26. ^ Adomavicius, Gediminas; Gupta, Alok; Zhdanov, Dmitry (December 20, 2009). "Designing Intelligent Software Agents for Auctions with Limited Information Feedback". Information Systems Research. 20 (4): 507–526. doi:10.1287/isre.1080.0172 – via CrossRef.
  27. ^ Bapna, Ravi; Goes, Paulo; Gupta, Alok; Karuga, Gilbert (August 20, 2008). "Predicting Bidders' Willingness to Pay in Online Multiunit Ascending Auctions: Analytical and Empirical Insights". INFORMS Journal on Computing. 20 (3): 345–355. doi:10.1287/ijoc.1070.0247 – via CrossRef.
  28. ^ "A Data-Driven Exploration of Bidder Strategies in Continuous Combinatorial Auctions".
  29. ^ Bapna, Ravi; Goes, Paulo; Gupta, Alok (2000). "A theoretical and empirical investigation of multi-item on-line auctions". Information Technology and Management. 1: 1–23. doi:10.1023/A:1019100419867. S2CID 18880263.
  30. ^ Bapna, Ravi; Goes, Paulo; Gupta, Alok (2001). "Comparative analysis of multi-item online auctions: evidence from the laboratory". Decision Support Systems. 32 (2): 135–153. doi:10.1016/S0167-9236(01)00107-5.
  31. ^ Bapna, R.; Goes, P.; Gupta, A. (January 20, 2001). "Simulating online Yankee auctions to optimize sellers revenue". Proceedings of the 34th Annual Hawaii International Conference on System Sciences. pp. 10 pp.–. doi:10.1109/HICSS.2001.927066. ISBN 0-7695-0981-9. S2CID 2100365 – via IEEE Xplore.
  32. ^ Bapna, Ravi; Goes, Paulo; Gupta, Alok (2003). "Replicating Online Yankee Auctions to Analyze Auctioneers' and Bidders' Strategies". Information Systems Research. 14 (3): 244–268. doi:10.1287/isre.14.3.244.16562.
  33. ^ Adomavicius, Gediminas; Gupta, Alok; Sanyal, Pallab (January 2008). ""Design and Evaluation of Feedback Schemes for Multiattribute Procureme" by Gediminas Adomavicius, Alok Gupta et al". Icis 2008 Proceedings.
  34. ^ Bapna, Ravi; Chang, Seokjoo Andrew; Goes, Paulo; Gupta, Alok (2009). "Overlapping Online Auctions: Empirical Characterization of Bidder Strategies and Auction Prices". MIS Quarterly. 33 (4): 763–783. doi:10.2307/20650326. JSTOR 20650326 – via JSTOR.
  35. ^ Adomavicius, Gediminas; Curley, Shawn P.; Gupta, Alok; Sanyal, Pallab (September 2013). "User acceptance of complex electronic market mechanisms: Role of information feedback – ScienceDirect". Journal of Operations Management. IT, Supply Chain, and Services. 31 (6): 489–503. doi:10.1016/j.jom.2013.07.015.
  36. ^ Adomavicius, Gediminas; Gupta, Alok (2005). "Toward Comprehensive Real-Time Bidder Support in Iterative Combinatorial Auctions". Information Systems Research. 16 (2): 169–185. doi:10.1287/isre.1050.0052.
  37. ^ Adomavicius, Gediminas; Curley, Shawn P.; Gupta, Alok; Sanyal, Pallab (2013). "Impact of Information Feedback in Continuous Combinatorial Auctions: An Experimental Study of Economic Performance". MIS Quarterly. 37 (1): 55–76. doi:10.25300/MISQ/2013/37.1.03. JSTOR 43825937.
  38. ^ Adomavicius, Gediminas; Curley, Shawn P.; Gupta, Alok; Sanyal, Pallab (2012). "Effect of Information Feedback on Bidder Behavior in Continuous Combinatorial Auctions". Management Science. 58 (4): 811–830. doi:10.1287/mnsc.1110.1443.
  39. ^ Lu, Yixin; Gupta, Alok; Ketter, Wolfgang; Van Heck, Eric (2016). "Exploring Bidder Heterogeneity in multichannel sequential B2B Auctions". MIS Quarterly. 40 (3): 645–662. doi:10.25300/MISQ/2016/40.3.06. JSTOR 26629031.
  40. ^ Lu, Yixin; Gupta, Alok; Ketter, Wolfgang; Van Heck, Eric (2019). "Dynamic Decision Making in Sequential Business-to-Business Auctions: A Structural Econometric Approach". Management Science. 65 (8): 3853–3876. doi:10.1287/mnsc.2018.3118. S2CID 159376075.
  41. ^ "Information Transparency in B2B Auction Markets: The Role of Winner Identity Disclosure". SSRN 2949785.
  42. ^ "Designing Hybrid Mechanisms to oVercome Congestion in Sequential Dutch Auctions".
  43. ^ Bapna, Ravi; Goes, Paulo; Gupta, Alok; Jin, Yiwei (2004). "User Heterogeneity and Its Impact on Electronic Auction Market Design: An Empirical Exploration". MIS Quarterly. 28 (1): 21–43. doi:10.2307/25148623. JSTOR 25148623.
  44. ^ "Information Transparency in B2B Auction Markets: The Role of Winner Identity Disclosure". SSRN 2949785.
  45. ^ "The Design Science Award – INFORMS".
  46. ^ "Information Systems Society President's Service Award".
  47. ^ "ISS Practical Impacts Award – INFORMS".
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