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Cardinality Bundle Pricing

Cardinality bundle pricing -- where prices are based on the size of the bundles -- is quite common. Data prices are independent of whether you use video or email data, but they impose different cost for network providers; Similarly, some baseball teams allow you to buy tickets for a certain number of games. For these cases, we develop a fast solution approach to discover those prices.

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How Editorial Reviews Can Improve The Overall Content Quality?

We investigated an editorial review program where a review platform supplements the user reviews with editorial ones written by professional writers. Read our study on how supplementing high-quality editorial reviews with user reviews can improve the overall content quality of user reviews through a herding effect.

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Role of Frictions in Efficiency of a Generalized Second Price Auction

We studied the role of frictions in the outcome of the generalized second price auction. Specifically, we studied the following research questions: Do frictions lead to an increase or decrease in overbidding? What are the consequences for the auctioneer, for the advertiser, and for the allocative efficiency of the GSP?

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Best Response Fair Machine Learning Algorithm

Fairness in machine learning algorithms are extensively studied to overcome biases exhibited by a few implementations. Even then, they do not consider the best response behavior of subjects in response to the ML implementation. We develop an algorithm that considers the best response behavior.zzzzzzs

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Journal Articles

  • Zhang, N., Kannan, K., and Shanthikumar, G. (2020). Nudging Consumer Behavior: Recommender Systems with Capacity Constraints. Production and Operations Management,
  • Pamuru, V., Khern-am-nuai, W., and Kannan, K. (2020). The Impact of an Augmented Reality Game on Local Businesses: A Study of Pokemon Go on Restaurants. Information Systems Research,
  • Nguyen, T., and Kannan, K. (2020). Welfare Implications of Intermediary Networks. Information Systems Research,
  • Wu, J., Tawarmalani, M., and Kannan, K. (2019). Cardinality Bundles with SpenceMirelees Reservation Prices. Management Science, vol. 65 (4), 1455-1947.
  • Hashim, M., Kannan, K., and Wegener, D. (2018). Nudging the Digital Pirate: A Central Role for Moral Obligations in Determining Intentions to Engage in Digital Piracy. Journal of Management Information Systems, vol. 30 934-963.
  • Gupta, A., Kannan, K., and Sanyal, P. (2018). Research Commentary: Experimental  Economics  in  Information  Systems  Research. MIS Quarterly, vol. 42 (2), 595-606.
  • Khern-am-nuai, W., Kannan, K., and Ghasemkhani, H. (2018). Extrinsic versus Intrinsic Rewards to Participate in a Crowd Context: An Analysis of a Review  Platform. Information Systems Research, vol. 29 (4), 871-892.
  • Hashim, M., Kannan, K., and Maximiano, S (2017). Information Feedback, Targeting, and Coordination: An Experimental Study. Information Systems Research, vol. 28 (2), 289-308.
  • Kannan, K., Rahman, M., and Tawarmalani, M (2016). Implications of Restricted Patch Distribution. Management Science, vol. 62 (11), 3161-3182.
  • Overby, E., and Kannan, K (2015). Reduced Search Costs Bidder Distribution Auctions. Management Science, vol. 61 (6), 1398-1420.
  • Sha, Z., Kannan, K., and Panchal, J (2015). Behavioral Experimentation and Game Theory in Engineering Systems Design. Journal of Mechanical Design, vol. 137 (5),
  • Hashim, M., Kannan, K., Maximiano, S., and Rees, J (2014). Digital Piracy, Teens, and the Source of Advice: An Experimental Study. Journal of Management Information Systems, vol. 31 (2), 211-244.
  • Wang, T., Kannan, K., and Rees, J (2013). The Association between the Disclosure and the Realization of Information Security Risk Factors. Information Systems Research, vol. 24 (2), 201-218.
  • Wang, T., Kannan, K., and Rees, J (2013). The Textual Contents of Media Reports of Information Security Breaches and Profitable Short-Term Investment Opportunities. Journal of Organizational Computing and Electronic Commerce, vol. 23 (3), 200-223.
  • Kannan (2012). Effects of Revelation Policies under Cost Uncertainty. Information Systems Research, vol. 23 (1), 75-92.
  • Kim, A., Balachander, S., and Kannan, K (2012). Optimal Number of Slots in Search Auctions. Marketing Letters, vol. 23 (3), 851-868.
  • Cason, T., Kannan, K., and Siebert, R (2011). An Experimental Study of Information Revelation Policies in Sequential Auctions. Management Science, vol. 57 (4), 667-688.
  • Kannan (2010). Effects of Revelation Policies under Cost Uncertainty. Information Systems Research,
  • Kannan (2010). Declining Prices in Sequential Auctions with Complete Revelation of Bids. Economic Letters, vol. 108 (1),
  • Balachandar, Kannan, & Schwartz (2010). A Theoretical and Empirical Analyses of Alternate Auction Policies for Search Advertisements. Review of Marketing Science, vol. 7 (1),
  • Greenwald, A., Kannan, K., and Krishnan, R. (2009). On Evaluating Information Revelation Policies in E-marketplaces: A Markov Decision Process Approach. Information Systems Research, vol. 20 (4),
  • Tawarmalani, M., Kannan, K., and De, P. (2009). Allocating Objects in a Network of Caches: Centralized and Decentralized Analyses. Management Science, vol. 55 (1),
  • Arora, A., Greenwald, A., Kannan, K. and Krishnan, R. (2007). Effects of Information Revelation Policies under Market Structure Uncertainty. Management Science, vol. 53 (8),
  • Kannan, K., Rees, J., and Sridhar, S. (2007). Market Reactions to Information Security Breach Announcements: An Empirical Analysis. International Journal of Electronic Commerce, vol. forthcoming
  • Kannan, K., & Telang, R. (2005). Market for Vulnerabilities? Think Again. Management Science, vol. 51 (5), 726-740.