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Krishnamurthy Iyer

Personal Details

First Name:Krishnamurthy
Middle Name:
Last Name:Iyer
Suffix:
RePEc Short-ID:piy16
[This author has chosen not to make the email address public]
https://iyerkri.github.io/
Terminal Degree:2012 Department of Management Science and Engineering; Stanford University (from RePEc Genealogy)

Affiliation

University of Minnesota, Department of Industrial and Systems Engineering

https://cse.umn.edu/isye
USA, Minneapolis

Research output

as
Jump to: Working papers Articles

Working papers

  1. Krishnamurthy Iyer & Haifeng Xu & You Zu, 2023. "Markov Persuasion Processes with Endogenous Agent Beliefs," Papers 2307.03181, arXiv.org, revised Jul 2023.
  2. Jerry Anunrojwong & Krishnamurthy Iyer & David Lingenbrink, 2022. "Persuading Risk-Conscious Agents: A Geometric Approach," Papers 2208.03758, arXiv.org, revised Jul 2023.
  3. You Zu & Krishnamurthy Iyer & Haifeng Xu, 2021. "Learning to Persuade on the Fly: Robustness Against Ignorance," Papers 2102.10156, arXiv.org, revised May 2024.
  4. Jerry Anunrojwong & Krishnamurthy Iyer & Vahideh Manshadi, 2020. "Information Design for Congested Social Services: Optimal Need-Based Persuasion," Papers 2005.07253, arXiv.org, revised Oct 2022.

Articles

  1. Jerry Anunrojwong & Krishnamurthy Iyer & David Lingenbrink, 2024. "Persuading Risk-Conscious Agents: A Geometric Approach," Operations Research, INFORMS, vol. 72(1), pages 151-166, January.
  2. Jerry Anunrojwong & Krishnamurthy Iyer & Vahideh Manshadi, 2023. "Information Design for Congested Social Services: Optimal Need-Based Persuasion," Management Science, INFORMS, vol. 69(7), pages 3778-3796, July.
  3. Dragos Florin Ciocan & Krishnamurthy Iyer, 2021. "Tractable Equilibria in Sponsored Search with Endogenous Budgets," Operations Research, INFORMS, vol. 69(1), pages 227-244, January.
  4. Artur Gorokh & Siddhartha Banerjee & Krishnamurthy Iyer, 2021. "From Monetary to Nonmonetary Mechanism Design via Artificial Currencies," Mathematics of Operations Research, INFORMS, vol. 46(3), pages 835-855, August.
  5. David Lingenbrink & Krishnamurthy Iyer, 2019. "Optimal Signaling Mechanisms in Unobservable Queues," Operations Research, INFORMS, vol. 67(5), pages 1397-1416, September.
  6. Krishnamurthy Iyer & Ramesh Johari & Mukund Sundararajan, 2014. "Mean Field Equilibria of Dynamic Auctions with Learning," Management Science, INFORMS, vol. 60(12), pages 2949-2970, December.
  7. Krishnamurthy Iyer & Ramesh Johari & Ciamac C. Moallemi, 2014. "Information Aggregation and Allocative Efficiency in Smooth Markets," Management Science, INFORMS, vol. 60(10), pages 2509-2524, October.
  8. Krishnamurthy Iyer & Nandyala Hemachandra, 2010. "Sensitivity analysis and optimal ultimately stationary deterministic policies in some constrained discounted cost models," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 71(3), pages 401-425, June.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Jerry Anunrojwong & Krishnamurthy Iyer & David Lingenbrink, 2022. "Persuading Risk-Conscious Agents: A Geometric Approach," Papers 2208.03758, arXiv.org, revised Jul 2023.

    Cited by:

    1. Jerry Anunrojwong & Krishnamurthy Iyer & Vahideh Manshadi, 2023. "Information Design for Congested Social Services: Optimal Need-Based Persuasion," Management Science, INFORMS, vol. 69(7), pages 3778-3796, July.
    2. You Zu & Krishnamurthy Iyer & Haifeng Xu, 2021. "Learning to Persuade on the Fly: Robustness Against Ignorance," Papers 2102.10156, arXiv.org, revised May 2024.

  2. You Zu & Krishnamurthy Iyer & Haifeng Xu, 2021. "Learning to Persuade on the Fly: Robustness Against Ignorance," Papers 2102.10156, arXiv.org, revised May 2024.

    Cited by:

    1. Yiling Chen & Tao Lin, 2023. "Persuading a Behavioral Agent: Approximately Best Responding and Learning," Papers 2302.03719, arXiv.org, revised Feb 2024.

  3. Jerry Anunrojwong & Krishnamurthy Iyer & Vahideh Manshadi, 2020. "Information Design for Congested Social Services: Optimal Need-Based Persuasion," Papers 2005.07253, arXiv.org, revised Oct 2022.

    Cited by:

    1. Charlson, G., 2022. "In platforms we trust: misinformation on social networks in the presence of social mistrust," Cambridge Working Papers in Economics 2204, Faculty of Economics, University of Cambridge.
    2. Charlson, G., 2022. "In platforms we trust: misinformation on social networks in the presence of social mistrust," Janeway Institute Working Papers 2202, Faculty of Economics, University of Cambridge.
    3. Krishnamurthy Iyer & Haifeng Xu & You Zu, 2023. "Markov Persuasion Processes with Endogenous Agent Beliefs," Papers 2307.03181, arXiv.org, revised Jul 2023.
    4. Modibo Camara & Jason Hartline & Aleck Johnsen, 2020. "Mechanisms for a No-Regret Agent: Beyond the Common Prior," Papers 2009.05518, arXiv.org.
    5. Zheng, Shiyuan & Jia, Rongwen & Shang, Wen-Long & Fu, Xiaowen & Wang, Kun, 2023. "Promote transport facility Resilience: Persuasion or Subsidy?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).

Articles

  1. Jerry Anunrojwong & Krishnamurthy Iyer & David Lingenbrink, 2024. "Persuading Risk-Conscious Agents: A Geometric Approach," Operations Research, INFORMS, vol. 72(1), pages 151-166, January.
    See citations under working paper version above.
  2. Jerry Anunrojwong & Krishnamurthy Iyer & Vahideh Manshadi, 2023. "Information Design for Congested Social Services: Optimal Need-Based Persuasion," Management Science, INFORMS, vol. 69(7), pages 3778-3796, July.
    See citations under working paper version above.
  3. Dragos Florin Ciocan & Krishnamurthy Iyer, 2021. "Tractable Equilibria in Sponsored Search with Endogenous Budgets," Operations Research, INFORMS, vol. 69(1), pages 227-244, January.

    Cited by:

    1. Zhaohua Chen & Mingwei Yang & Chang Wang & Jicheng Li & Zheng Cai & Yukun Ren & Zhihua Zhu & Xiaotie Deng, 2022. "Budget-Constrained Auctions with Unassured Priors: Strategic Equivalence and Structural Properties," Papers 2203.16816, arXiv.org, revised Feb 2024.
    2. Santiago Balseiro & Anthony Kim & Mohammad Mahdian & Vahab Mirrokni, 2021. "Budget-Management Strategies in Repeated Auctions," Operations Research, INFORMS, vol. 69(3), pages 859-876, May.

  4. David Lingenbrink & Krishnamurthy Iyer, 2019. "Optimal Signaling Mechanisms in Unobservable Queues," Operations Research, INFORMS, vol. 67(5), pages 1397-1416, September.

    Cited by:

    1. Ruijie Zhang & Xiaohua Han & Rowan Wang & Jianghua Zhang & Yinghao Zhang, 2023. "Please don't make me wait! Influence of customers' waiting preference and no‐show behavior on appointment systems," Production and Operations Management, Production and Operations Management Society, vol. 32(6), pages 1597-1616, June.
    2. Thomas Mariotti & Nikolaus Schweizer & Nora Szech & Jonas von Wangenheim, 2018. "Information Nudges and Self-Control," CESifo Working Paper Series 7346, CESifo.
    3. Zhongbin Wang & Yunan Liu & Lei Fang, 2022. "Pay to activate service in vacation queues," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2609-2627, June.
    4. Kimon Drakopoulos & Shobhit Jain & Ramandeep Randhawa, 2021. "Persuading Customers to Buy Early: The Value of Personalized Information Provisioning," Management Science, INFORMS, vol. 67(2), pages 828-853, February.
    5. Harish Guda & Milind Dawande & Ganesh Janakiraman, 2023. "The economics of process transparency," Production and Operations Management, Production and Operations Management Society, vol. 32(6), pages 1812-1829, June.
    6. Francis de Véricourt, & Huseyin Gurkan, & Shouqiang Wang,, 2020. "Informing the public about a pandemic," ESMT Research Working Papers ESMT-20-03, ESMT European School of Management and Technology, revised 11 Feb 2021.
    7. Jianfu Wang & Ming Hu, 2020. "Efficient Inaccuracy: User-Generated Information Sharing in a Queue," Management Science, INFORMS, vol. 66(10), pages 4648-4666, October.
    8. Jerry Anunrojwong & Krishnamurthy Iyer & Vahideh Manshadi, 2023. "Information Design for Congested Social Services: Optimal Need-Based Persuasion," Management Science, INFORMS, vol. 69(7), pages 3778-3796, July.
    9. Saed Alizamir & Francis de Véricourt & Shouqiang Wang, 2020. "Warning Against Recurring Risks: An Information Design Approach," Management Science, INFORMS, vol. 66(10), pages 4612-4629, October.
    10. Deepanshu Vasal, 2020. "Dynamic information design," Papers 2005.07267, arXiv.org.
    11. Gabi Hanukov & Michael Hassoun & Oren Musicant, 2021. "On the Benefits of Providing Timely Information in Ticket Queues with Balking and Calling Times," Mathematics, MDPI, vol. 9(21), pages 1-16, October.
    12. Yonatan Gur & Gregory Macnamara & Ilan Morgenstern & Daniela Saban, 2019. "Information Disclosure and Promotion Policy Design for Platforms," Papers 1911.09256, arXiv.org, revised Dec 2022.
    13. Pengfei Guo & Moshe Haviv & Zhenwei Luo & Yulan Wang, 2022. "Optimal queue length information disclosure when service quality is uncertain," Production and Operations Management, Production and Operations Management Society, vol. 31(5), pages 1912-1927, May.
    14. Wang, Hai & Yang, Hai, 2019. "Ridesourcing systems: A framework and review," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 122-155.
    15. Ozan Candogan & Kimon Drakopoulos, 2020. "Optimal Signaling of Content Accuracy: Engagement vs. Misinformation," Operations Research, INFORMS, vol. 68(2), pages 497-515, March.
    16. Jerry Anunrojwong & Krishnamurthy Iyer & David Lingenbrink, 2022. "Persuading Risk-Conscious Agents: A Geometric Approach," Papers 2208.03758, arXiv.org, revised Jul 2023.
    17. Ehud Lehrer & Dimitry Shaiderman, 2022. "Markovian Persuasion with Stochastic Revelations," Papers 2204.08659, arXiv.org, revised May 2022.
    18. Ehud Lehrer & Dimitry Shaiderman, 2021. "Markovian Persuasion," Papers 2111.14365, arXiv.org.
    19. Babichenko, Yakov & Talgam-Cohen, Inbal & Xu, Haifeng & Zabarnyi, Konstantin, 2022. "Regret-minimizing Bayesian persuasion," Games and Economic Behavior, Elsevier, vol. 136(C), pages 226-248.
    20. Shivam Gupta & Wei Chen & Milind Dawande & Ganesh Janakiraman, 2023. "Three Years, Two Papers, One Course Off: Optimal Nonmonetary Reward Policies," Management Science, INFORMS, vol. 69(5), pages 2852-2869, May.
    21. Gur, Yonatan & Macnamara, Gregory & Saban, Daniela, 2020. "On the Disclosure of Promotion Value in Platforms with Learning Sellers," Research Papers 3865, Stanford University, Graduate School of Business.
    22. Nasimeh Heydaribeni & Ketan Savla, 2021. "Information Design for a Non-atomic Service Scheduling Game," Papers 2110.00090, arXiv.org.

  5. Krishnamurthy Iyer & Ramesh Johari & Mukund Sundararajan, 2014. "Mean Field Equilibria of Dynamic Auctions with Learning," Management Science, INFORMS, vol. 60(12), pages 2949-2970, December.

    Cited by:

    1. Bar Light, 2019. "General equilibrium in a heterogeneous-agent incomplete-market economy with many consumption goods and a risk-free bond," Papers 1906.06810, arXiv.org, revised Mar 2021.
    2. Xiaotie Deng & Xinyan Hu & Tao Lin & Weiqiang Zheng, 2021. "Nash Convergence of Mean-Based Learning Algorithms in First Price Auctions," Papers 2110.03906, arXiv.org, revised Feb 2023.
    3. Ilan Lobel, 2021. "Revenue Management and the Rise of the Algorithmic Economy," Management Science, INFORMS, vol. 67(9), pages 5389-5398, September.
    4. Meng Zhang & Deepanshu Vasal, 2020. "Mechanism Design for Large Scale Network Utility Maximization," Papers 2003.04263, arXiv.org, revised Jan 2021.
    5. Frank Kelly & Peter Key & Neil Walton, 2016. "Efficient Advert Assignment," Operations Research, INFORMS, vol. 64(4), pages 822-837, August.
    6. Bar Light & Gabriel Weintraub, 2019. "Mean Field Equilibrium: Uniqueness, Existence, and Comparative Statics," Papers 1903.02273, arXiv.org, revised Jun 2020.
    7. Hana Choi & Carl F. Mela & Santiago R. Balseiro & Adam Leary, 2020. "Online Display Advertising Markets: A Literature Review and Future Directions," Information Systems Research, INFORMS, vol. 31(2), pages 556-575, June.
    8. Hana Choi & Carl F. Mela, 2019. "Monetizing Online Marketplaces," Marketing Science, INFORMS, vol. 38(6), pages 948-972, November.
    9. Yash Kanoria & Daniela Saban, 2021. "Facilitating the Search for Partners on Matching Platforms," Management Science, INFORMS, vol. 67(10), pages 5990-6029, October.
    10. Régis Chenavaz & Corina Paraschiv & Gabriel Turinici, 2021. "Dynamic Pricing of New Products in Competitive Markets: A Mean-Field Game Approach," Dynamic Games and Applications, Springer, vol. 11(3), pages 463-490, September.
    11. Stefan Wager & Kuang Xu, 2019. "Experimenting in Equilibrium," Papers 1903.02124, arXiv.org, revised Jun 2020.
    12. Matthew Backus & Gregory Lewis, 2016. "Dynamic Demand Estimation in Auction Markets," NBER Working Papers 22375, National Bureau of Economic Research, Inc.
    13. Cem Ozturk, O. & Karabatı, Selçuk, 2017. "A decision support framework for evaluating revenue performance in sequential purchase contexts," European Journal of Operational Research, Elsevier, vol. 263(3), pages 922-934.
    14. Yunke Mai & Bin Hu & Saša Pekeč, 2023. "Courteous or Crude? Managing User Conduct to Improve On-Demand Service Platform Performance," Management Science, INFORMS, vol. 69(2), pages 996-1016, February.
    15. Dominic Coey & Bradley J. Larsen & Brennan C. Platt, 2020. "Discounts and Deadlines in Consumer Search," American Economic Review, American Economic Association, vol. 110(12), pages 3748-3785, December.
    16. Bodoh-Creed, Aaron L. & Hickman, Brent R., 2018. "College assignment as a large contest," Journal of Economic Theory, Elsevier, vol. 175(C), pages 88-126.
    17. Santiago R. Balseiro & Yonatan Gur, 2019. "Learning in Repeated Auctions with Budgets: Regret Minimization and Equilibrium," Management Science, INFORMS, vol. 65(9), pages 3952-3968, September.
    18. Deepanshu Vasal, 2022. "Master equation of discrete-time Stackelberg mean field games with multiple leaders," Papers 2209.03186, arXiv.org.
    19. Stefan Wager & Kuang Xu, 2021. "Experimenting in Equilibrium," Management Science, INFORMS, vol. 67(11), pages 6694-6715, November.
    20. Nick Arnosti & Ramesh Johari & Yash Kanoria, 2021. "Managing Congestion in Matching Markets," Manufacturing & Service Operations Management, INFORMS, vol. 23(3), pages 620-636, May.
    21. Santiago R. Balseiro & Omar Besbes & Gabriel Y. Weintraub, 2019. "Dynamic Mechanism Design with Budget-Constrained Buyers Under Limited Commitment," Operations Research, INFORMS, vol. 67(3), pages 711-730, May.
    22. Veronica Marotta & Yue Wu & Kaifu Zhang & Alessandro Acquisti, 2022. "The Welfare Impact of Targeted Advertising Technologies," Information Systems Research, INFORMS, vol. 33(1), pages 131-151, March.
    23. Santiago R. Balseiro & Omar Besbes & Gabriel Y. Weintraub, 2015. "Repeated Auctions with Budgets in Ad Exchanges: Approximations and Design," Management Science, INFORMS, vol. 61(4), pages 864-884, April.
    24. W. Jason Choi & Amin Sayedi, 2019. "Learning in Online Advertising," Marketing Science, INFORMS, vol. 38(4), pages 584-608, July.
    25. Yash Kanoria & Hamid Nazerzadeh, 2020. "Dynamic Reserve Prices for Repeated Auctions: Learning from Bids," Papers 2002.07331, arXiv.org.
    26. Zhichao Feng & Milind Dawande & Ganesh Janakiraman & Anyan Qi, 2023. "An Asymptotically Tight Learning Algorithm for Mobile-Promotion Platforms," Management Science, INFORMS, vol. 69(3), pages 1536-1554, March.
    27. Kostas Bimpikis & Wedad J. Elmaghraby & Ken Moon & Wenchang Zhang, 2020. "Managing Market Thickness in Online Business-to-Business Markets," Management Science, INFORMS, vol. 66(12), pages 5783-5822, December.
    28. Santiago Balseiro & Christian Kroer & Rachitesh Kumar, 2021. "Contextual Standard Auctions with Budgets: Revenue Equivalence and Efficiency Guarantees," Papers 2102.10476, arXiv.org, revised Oct 2022.
    29. Savas Dayanik & Semih O. Sezer, 2023. "Optimal dynamic multi-keyword bidding policy of an advertiser in search-based advertising," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 97(1), pages 25-56, February.
    30. Leila Hosseini & Shaojie Tang & Vijay Mookerjee, 2024. "When Is More Merrier? A Cloud-Based Architecture to Procure Impressions from Multiple Ad Exchanges," Information Systems Research, INFORMS, vol. 35(1), pages 294-317, March.
    31. Santiago R. Balseiro & Omar Besbes & Gabriel Y. Weintraub, 2012. "Auctions for Online Display Advertising Exchanges: Approximations and Design," Working Papers 12-11, NET Institute.
    32. Hernandez Senosiain, Patricio, 2022. "Why Do Men Keep Swiping Right? Two-Sided Search in Swipe-Based Dating Platforms," Warwick-Monash Economics Student Papers 37, Warwick Monash Economics Student Papers.
    33. Dragos Florin Ciocan & Krishnamurthy Iyer, 2021. "Tractable Equilibria in Sponsored Search with Endogenous Budgets," Operations Research, INFORMS, vol. 69(1), pages 227-244, January.
    34. Raghav Singal & Omar Besbes & Antoine Desir & Vineet Goyal & Garud Iyengar, 2022. "Shapley Meets Uniform: An Axiomatic Framework for Attribution in Online Advertising," Management Science, INFORMS, vol. 68(10), pages 7457-7479, October.

  6. Krishnamurthy Iyer & Ramesh Johari & Ciamac C. Moallemi, 2014. "Information Aggregation and Allocative Efficiency in Smooth Markets," Management Science, INFORMS, vol. 60(10), pages 2509-2524, October.

    Cited by:

    1. Heraud, Florian & Page, Lionel, 2024. "Does the left-digit bias affect prices in financial markets?," Journal of Economic Behavior & Organization, Elsevier, vol. 218(C), pages 20-29.
    2. Karimi, Majid & Zaerpour, Nima, 2022. "Put your money where your forecast is: Supply chain collaborative forecasting with cost-function-based prediction markets," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1035-1049.
    3. Lian Jian & Rahul Sami, 2012. "Aggregation and Manipulation in Prediction Markets: Effects of Trading Mechanism and Information Distribution," Management Science, INFORMS, vol. 58(1), pages 123-140, January.
    4. Rajiv Sethi & Jennifer Wortman Vaughan, 2016. "Belief Aggregation with Automated Market Makers," Computational Economics, Springer;Society for Computational Economics, vol. 48(1), pages 155-178, June.
    5. Dian Yu & Jianjun Gao & Weiping Wu & Zizhuo Wang, 2022. "Price Interpretability of Prediction Markets: A Convergence Analysis," Papers 2205.08913, arXiv.org, revised Nov 2023.
    6. Kimon Drakopoulos & Ali Makhdoumi, 2023. "Providing Data Samples for Free," Management Science, INFORMS, vol. 69(6), pages 3536-3560, June.
    7. Mintz, Yonatan & Aswani, Anil & Kaminsky, Philip & Flowers, Elena & Fukuoka, Yoshimi, 2023. "Behavioral analytics for myopic agents," European Journal of Operational Research, Elsevier, vol. 310(2), pages 793-811.

  7. Krishnamurthy Iyer & Nandyala Hemachandra, 2010. "Sensitivity analysis and optimal ultimately stationary deterministic policies in some constrained discounted cost models," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 71(3), pages 401-425, June.

    Cited by:

    1. Kumar, Uday M & Bhat, Sanjay P. & Kavitha, Veeraruna & Hemachandra, Nandyala, 2023. "Approximate solutions to constrained risk-sensitive Markov decision processes," European Journal of Operational Research, Elsevier, vol. 310(1), pages 249-267.
    2. Nandyala Hemachandra & Kamma Sri Naga Rajesh & Mohd. Abdul Qavi, 2016. "A model for equilibrium in some service-provider user-set interactions," Annals of Operations Research, Springer, vol. 243(1), pages 95-115, August.

More information

Research fields, statistics, top rankings, if available.

Statistics

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 4 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-MIC: Microeconomics (4) 2020-05-25 2021-03-01 2022-09-05 2023-08-14
  2. NEP-GTH: Game Theory (3) 2021-03-01 2022-09-05 2023-08-14
  3. NEP-DES: Economic Design (1) 2020-05-25
  4. NEP-EXP: Experimental Economics (1) 2021-03-01
  5. NEP-RMG: Risk Management (1) 2022-09-05
  6. NEP-UPT: Utility Models and Prospect Theory (1) 2022-09-05

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