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DTSTART:20240101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20251106T100000
DTEND;TZID=Asia/Singapore:20251106T113000
DTSTAMP:20260419T135023
CREATED:20251029T090126Z
LAST-MODIFIED:20251029T090126Z
UID:27283-1762423200-1762428600@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Vinayak Deshpande
DESCRIPTION:Name of Speaker\n\n\nVinayak Deshpande \n\n\n\n\nSchedule \n\n\n6 Nov 2025\, 10am – 11.30am \n (60 min talk + 30 min Q&A) \n\n\n\n\nVenue \n\n\nBIZ1 0304\n\n\n\n\nLink to register \n(via Zoom) \n\n\nhttps://nus-sg.zoom.us/meeting/register/MBGAcVExSZ2vrzd3MnrERg\n\n\n\n\nTitle\n\n\nData driven research for better Operations decisions\n\n\n\n\nAbstract \n\n\nThe explosion in availability of data has enabled organizations to collect wealth of information for their business operations. In this talk\, I will share my experience in using a data-driven approach for improving Operations decisions from two settings: Healthcare and Aviation. I will highlight the opportunities and challenges in a data driven research approach for operational decision making.\nIn the first half of the talk\, I will discuss the challenge of improving the efficiency of surgical procedures which account for approximately 60% of the operating cost of a hospital the United States. Hospitals spend several million dollars annually on instrument sterilization\, instrument tray assembly\, and instrument repurchase costs. However\, in a large majority of hospitals\, less than 20%–30% of reusable instruments supplied to a surgery are used on average. We obtained actual surgical instrument usage at a large multispecialty hospital in partnership with OpFlow\, a healthcare software company. We formulate a data-driven mathematical optimization model for surgical tray configuration and assignment with the goal of reducing costs of unused instruments\, such as sterilization\, instrument purchase\, and tray assembly costs. Our solution was implemented at the UNC Rex Hospital\, and we report on the results of our implementation. This analysis has quantified the value of collecting point-of-usage data to be at least $1.39 million per year from using the model-recommended solution at the hospital.\nIn the second half of the talk\, I will discuss the challenge of flight delays in the aviation sector which impacts airlines’ operating cost including increased expenses for crew\, fuel\, and maintenance. Propagated delays due to late arriving aircraft contribute to 40% of all flight delays as reported by the Bureau of Transportation Statistics. The aircraft assignment problem is to assign tail numbers on scheduled arriving flights at an airport to scheduled departing flights at the same airport with the objective of minimizing propagated delays. In this paper\, we propose a new data-driven approach for the aircraft assignment problem by formulating it as a balanced assignment problem between incoming and outgoing flights flown by the same aircraft type at the major hub airports. We propose a data-driven clustering method to account for factors such as the originating airport\, time of day\, and aircraft type that affect the primary delay distribution. These empirical cluster-based aircraft assignment costs serve as an input to our stochastic assignment model. These assignment costs are then used to derive the optimal stochastic aircraft assignment for an out-of-sample data set for Delta Airlines at its three largest hub airports. We show that the stochastic assignment derived from the data-driven approach performs 2.31% better than the benchmark FIFO assignment in total propagated delay at these hub airports.\n\n\n\n\nAbout the Speaker\n\n\nProfessor Deshpande is the Mann Family Distinguished Professor of Operations at the Kenan-Flagler business school at University of North Carolina.  He holds a Ph.D. in Operations Management from the Wharton School\, University of Pennsylvania. He also holds a M.S. in Operations Research from Columbia University\, New York\, and a B.Tech. in Mechanical Engineering from I.I.T.\, Mumbai.\n\nProf. Deshpande was awarded with the Dantzig Dissertation award for his Ph.D. dissertation for his work with the US Navy and DLA in optimizing the weapon systems spare parts supply chain. He has worked with the US Coast Guard on a series of projects for optimizing the supply chain used for aircraft service parts. His work with the US Coast Guard was selected as a finalist for the Edelman award and he was honored as an Edelman Award Laureate for an outstanding example of management science and operations research practice. His work on airline operations has been honored with the AGIFORS best contribution award by the Airline Operations Research Society AGIFORS. His research using data from Alibaba’s Cainiao network and JD.com on e-commerce logistics received the MSOM data driven research challenge finalist award. His recent work on surgical tray optimization was selected as a finalist for the Innovative Applications of Analytics Award by the INFORMS society.\n\nHis research interests are in the area of Supply Chain Management\, E-commerce logistics\, Service/Spare Parts Management\, Inventory Management\, Sustainable Operations\, and Healthcare Operations. His research has been motivated by contexts from various industry sectors such as defense\, aviation\, hi-tech\, retail\, e-commerce\, airlines\, and healthcare. His research has been published in premier academic journals such as Management Science\, Operations Research\, POMS\, and M&SOM. He recently served as the president of the supply chain college of the Production and Operations Management society.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-vinayak-deshpande/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20251114T100000
DTEND;TZID=Asia/Singapore:20251114T113000
DTSTAMP:20260419T135023
CREATED:20251110T050727Z
LAST-MODIFIED:20251110T050727Z
UID:27306-1763114400-1763119800@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Guillaume Roels
DESCRIPTION:Name of Speaker \n\n\nGuillaume Roels \n\n\n\n\nSchedule  \n\n\n14 Nov 2025\, 10am – 11.30am \n (60 min talk + 30 min Q&A) \n\n\n\n\nVenue  \n\n\nHSS 4-1 \n\n\n\n\nLink to register \n(via Zoom) \n\n\nhttps://nus-sg.zoom.us/meeting/register/SWlclpbGT6eV8q9w_dkijA\n\n\n\n\nTitle \n\n\nYou\, Me\, or We? Co-Productive Principal-Agent Dynamics\n\n\n\n\nAbstract  \n\n\nProblem Definition: Projects are often initiated by a single person – a principal – who then decides whether to execute it on their own (Single Execution) or to partner with someone else – an agent. If an agent is hired\, the project execution may be joint (Joint Execution) or undertaken only by the agent (Delegated Execution). How do the resulting co-productive dynamics compare to what would be optimal to do?\nMethodology/Results: We consider a co-productive principal-agent model with endogenous team formation. With financial transfers\, as is typical in inter-organizational contexts\, joint execution happens less frequently than optimally. Moreover\, the optimal contract under joint execution turns out to be a 50%-50% equity split under mild conditions. When financial transfers are not allowed\, as is typical in intra-organizational contexts\, there might be too much joint execution and too little delegation if the agent is very efficient. Overall\, the inefficiency created by moral hazard under delegated and joint execution is much less important than that created by the principal’s ability to engage in project hoarding and not form a team.\nManagerial Implications: The problem of under-delegation should really be framed as a problem of project hoarding\, i.e.\, principals do not partner enough. Moreover\, it is only relevant within – and not between – organizations. When principals partner with an agent\, they might delegate too much if agents are inefficient or contribute too much if agents are efficient. Although the principal-agent and team-production literature have essentially focused on setting incentives for effort exertion within a given operating mode\, a more critical issue appears to induce principals to form a team (or not)\, leading to inefficient operating modes.\n\n\n\n\nAbout the Speaker \n\n\nGuillaume Roels is the Timken Chaired Professor of Global Technology and Innovation at INSEAD. His research lies on the interface of operational excellence\, people-centric operations\, and the management of services. Recent work has focused on collaborative dynamics in organizations\, the design of service experiences\, and customer ownership in service systems. Prior to joining INSEAD\, Guillaume was an Associate Professor at the UCLA Anderson School of Management. He received an MS degree in Management Engineering and a DEA in Management from the Catholic University of Louvain\, Belgium\, and a PhD in Operations Research from MIT. \nHe is currently serving as the Editor-in-Chief of Service Science\, an INFORMS journal was a Department Editor at M&SOM. He also served as the President of the M&SOM Technology\, Innovation\, and Entrepreneurship (TIE) Specific Interest Group (SIG) and the President of the M&SOM Service Management (SIG). Recent research awards include a finalist position on the 2023 POMS College of Service Operations Management Best Student Paper Competition\, a finalist position in the 2023 INFORMS Social Media Analytics Best Student Paper Competition\, and a second place in the 2023 INFORMS Service Science Cluster Best Paper Competition.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-guillaume-roels/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20260130T100000
DTEND;TZID=Asia/Singapore:20260130T113000
DTSTAMP:20260419T135023
CREATED:20260122T062513Z
LAST-MODIFIED:20260122T062556Z
UID:27370-1769767200-1769772600@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Seungki Min
DESCRIPTION:Name of Speaker\n\nSeungki Min\n\n\n\nSchedule \n\n\n30 Jan 2026\, 10am – 11.30am \n (60 min talk + 30 min Q&A)\n\n\n\nVenue \n\n\nBIZ1 0302\n\n\n\nLink to register \n(via Zoom)\n\nhttps://nus-sg.zoom.us/meeting/register/psLI6qAmQPyKNZ3DOtqRvw\n\n\n\n\nTitle\n\n\nAn Information-Theoretic Analysis of Nonstationary Bandit Learning\n\n\n\n\nAbstract \n\nIn many real-world bandit learning problems\, the underlying environment evolves over time\, requiring decision-makers to continually acquire information and adapt their action selection accordingly. In this talk\, I study Bayesian formulations of nonstationary bandit problems\, where environmental dynamics are modeled as stochastic processes\, and develop an information-theoretic framework for analyzing attainable performance. \nOur analysis yields generic regret upper bounds that extend classical results from stationary Bayesian bandits to nonstationary settings. A key insight is that the entropy rate of the optimal action process naturally quantifies the intrinsic difficulty introduced by nonstationarity. I further connect our results to existing frequentist analyses of nonstationary bandits\, showing that several well-known regret bounds in the literature can be recovered as special cases within our unified framework.\n\n\n\n\nAbout the Speaker\n\n\nSeungki Min is an Assistant Professor of Operations Management at Seoul National University Business School. His research focuses on bandit optimization and reinforcement learning\, with an emphasis on principled frameworks for dynamic decision problems arising in business and engineering applications\, including online platforms\, pricing\, and finance. His research has appeared in Operations Research\, Management Science\, and leading AI/ML conferences such as ICML and NeurIPS. He earned his Ph.D. from Columbia Business School. Prior to academia\, he worked in high-frequency trading domain.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-30-jan-2026-10am-seungki-min/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20260206T100000
DTEND;TZID=Asia/Singapore:20260206T113000
DTSTAMP:20260419T135023
CREATED:20260128T061604Z
LAST-MODIFIED:20260203T030133Z
UID:27373-1770372000-1770377400@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Francis de Véricourt
DESCRIPTION:Name of Speaker\n\n\nFrancis de Véricourt\n\n\n\n\nSchedule \n\n\n6 Feb 2026\, 10am – 11.30am \n (60 min talk + 30 min Q&A) \n\n\n\n\nVenue \n\n\nHSS 4-2\n\n\n\n\nLink to register \n(via Zoom) \n\n\nhttps://nus-sg.zoom.us/meeting/register/KcwXsVRZSI2rLe4DvkXNFQ\n\n\n\n\nTitle\n\n\nBeyond the Black Box: Unraveling the Role of Explainability in Human-AI Collaboration\n\n\n\n\nAbstract \n\n\nExplainable Artificial Intelligence (AI) models have been proposed to mitigate overreliance and underreliance on AI\, which reduce the effectiveness of human-AI collaborative tools. Yet\, empirical evidence is mixed\, and the impact of explainable AI on a decision-maker (DM)’s cognitive load and fatigue is often ignored. This paper offers a theoretical perspective on these issues. We develop an analytical model that incorporates the defining features of human and machine intelligence\, capturing the limited but flexible nature of human cognition with imperfect machine recommendations. Crucially\, we represent how AI-based explanations influence the DM’s belief in the algorithm’s predictive quality. Our results indicate that explainable AI has varying effects depending on the level of explainability it provides. While low explainability levels have no impact on decision accuracy and reliance levels\, they lessen the cognitive burden of the DM. In contrast\, higher explainability levels enhance accuracy by improving overreliance but at the expense of increased underreliance. Further\, the relative impact of explainability (c.f. a black-box system) is higher when the DM is more cognitively constrained\, the decision task is sufficiently complex or when the stakes are lower. Importantly\, higher explainability levels can escalate the DM’s cognitive burden and hence overall processing time and fatigue\, precisely when explanations are most needed\, i.e. when the DM is pressed for time to complete a complex task and doubts the machine’s quality. Our study elicits comprehensive effects of explainability on decision outcomes and cognitive effort\, enhancing our understanding of designing effective human-AI systems in diverse decision-making environments.\n\n\n\n\nAbout the Speaker\n\n\nFrancis de Véricourt is Professor of Management Science and the founding Academic Director of the Institute for Deep Tech Innovation (DEEP) at ESMT Berlin. He also holds the Joachim Faber Chair in Business and Technology\, and is the co-author of Framers\, a Penguin Random House book listed on Financial Times’ Best Books. He lived and worked in France\, USA\, Germany and Singapore.\n\nFrancis was the first Associate Dean of Research and holder of the President’s Chair at ESMT Berlin. He held faculty positions at Duke University and INSEAD\, where he was the Paul Dubrule Chaired professor in Sustainable Development\, and was a post-doctoral researcher at Massachusetts Institute of Technology (MIT).  His general research interest is in the area of decision science\, analytics and operations\, with applications in health care\, sustainability and human-AI interaction. He is the author of numerous academic articles in prominent management\, analytics and economics journals such as Management Science\, Operations Research\, American Economics Review and others. He received several outstanding research awards and is currently an Area Editor at Operations Research.\n\nFrancis has been the recipient of many teaching awards for delivering classes to MBA and Executive MBA students at ESMT and INSEAD. He has extensive experience in executive education and corporate learning solutions\, and is a regular speaker in academic and industry forums.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-francis-de-vericourt/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20260213T100000
DTEND;TZID=Asia/Singapore:20260213T113000
DTSTAMP:20260419T135023
CREATED:20260212T024504Z
LAST-MODIFIED:20260227T013050Z
UID:27384-1770976800-1770982200@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Lu Jiaqi
DESCRIPTION:Name of Speaker \n\n\nLu Jiaqi \n\n\n\n\nSchedule  \n\n\n13 Feb 2026\, 10am – 11.30am \n (60 min talk + 30 min Q&A) \n\n\n\n\nVenue  \n\n\nBIZ1 0302 \n\n\n\n\nLink to register \n(via Zoom) \n\n\nhttps://nus-sg.zoom.us/meeting/register/FGZiBt3mT9CHxWWr-w6t5Q \n\n\n\n\nTitle \n\n\nBandit Allocational Instability \n\n\n\n\nAbstract  \n\n\n \n\n\n\n\nAbout the Speaker \n\n\nJiaqi Lu is an assistant professor in the School of Data Science and the School of Management and Economics (joint appointment) at the Chinese University of Hong Kong\, Shenzhen. Her research aims at understanding when and how do agents’ colliding incentives and complex dynamics lead to market inefficiencies\, and how to mitigate them. The types of applications usually involve matching platforms and supply chain. For example\, recently\, she studies bandit algorithms’ unintended side effect on downstream tasks\, such as allocational instability in platform operations and sample bias in post-policy inference. Her papers typically appear in Journals including Management Science\, Operations Research\, Mathematics of Operations Research\, and conferences such as ACM EC and WINE. \nJiaqi Lu obtained her Ph.D. in the Decision\, Risk\, and Operations division at Columbia Business School\, and her B.E. in Industrial Engineering\, B.A. in English (double major) at Tsinghua University.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-lu-jiaqi/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20260227T100000
DTEND;TZID=Asia/Singapore:20260227T113000
DTSTAMP:20260419T135023
CREATED:20260203T030056Z
LAST-MODIFIED:20260203T030156Z
UID:27376-1772186400-1772191800@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Georgina Hall
DESCRIPTION:Name of Speaker\n\n\nGeorgina Hal\n\n\n\n\nSchedule\n\n\n27 Feb 2026\, 10am – 11.30am \n (60 min talk + 30 min Q&A) \n\n\n\n\nVenue\n\n\nBIZ1 0302\n\n\n\n\nLink to register \n(via Zoom) \n\n\nhttps://nus-sg.zoom.us/meeting/register/MSVeTEDGTSGxi0TGgyLmNg\n\n\n\n\nTitle\n\n\nSum of Squares Submodularity\n\n\n\n\nAbstract\n\n\nWe introduce the notion of t-sum of squares (sos) submodularity\, which is a hierarchy\, indexed by t\, of sufficient algebraic conditions for certifying submodularity of set functions. We show that\, for fixed t\, each level of the hierarchy can be verified via a semidefinite program of size polynomial in n\, the size of the ground set of the set function. This is particularly relevant given existing hardness results around testing whether a set function is submodular (Crama\, 1989). We derive several equivalent algebraic characterizations of t-sos submodularity and identify submodularity-preserving operations that also preserve t-sos submodularity. We further present a complete classification of the cases for which submodularity and t-sos submodularity coincide\, as well as examples of t-sos-submodular functions. We demonstrate the usefulness of t-sos submodularity through three applications: (i) a new convex approach to submodular regression\, involving minimal manual tuning; (ii) a systematic procedure to derive lower bounds on the submodularity ratio in approximate submodular maximization\, and (iii) improved difference-of-submodular decompositions for difference-of-submodular optimization. \nThis is joint work with Anna Deza (Georgia Tech). \n\n\n\n\nAbout the Speaker\n\n\nGeorgina Hall is an Assistant Professor at INSEAD in the Decision Sciences Area. Her research focuses on convex relaxations of NP-hard problems\, particularly those that arise in polynomial optimization and problems on graphs. Prior to joining INSEAD in 2019\, she was a postdoctoral student at INRIA. She completed her PhD in Operations Research and Financial Engineering at Princeton University in 2018. She is the recipient of the 2018 INFORMS Optimization Society Young Researcher’s Prize and the 2020 Information Theory Society Paper Award\, among other awards.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-georgina-hall/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20260311T100000
DTEND;TZID=Asia/Singapore:20260311T233000
DTSTAMP:20260419T135023
CREATED:20260227T013022Z
LAST-MODIFIED:20260227T013124Z
UID:27490-1773223200-1773271800@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Peng Sun
DESCRIPTION:Name of Speaker\n\nPeng Sun\n\n\n\nSchedule \n\n11 Mar 2026\, 10am – 11.30am \n(60 min talk + 30 min Q&A)\n\n\n\nVenue \n\n\nBIZ2 0511\n\n\n\nLink to register \n(via Zoom)\n\nhttps://nus-sg.zoom.us/meeting/register/8WAQ86W5TMW5MZzaiDBNiQ\n\n\n\n\nTitle\n\n\nOptimal Push\, Pull\, and Failure Funding for Global Health\n\n\n\n\nAbstract \n\n\nMalaria and tuberculosis each cause over half a million deaths annually\, yet commercial incentives to develop treatments for these and other diseases concentrated in low-income countries remain weak. Governments and nonprofits address this gap through push (e.g.\, grants) and pull (e.g.\, prizes) mechanisms. We propose a third approach: the funder pays only if the firm fails\, reimbursing part of its testing costs. This failure insurance is optimal when markets are large enough to reward success but too small to justify initial investment. We model the problem as an infinite-dimensional optimization problem with adverse selection and moral hazard constraints\, and use duality theory to characterize optimal funding mechanisms.  Failure insurance is preferred for tuberculosis if testing costs are below \$1 billion. For most tropical diseases\, including malaria\, the optimal policy is pull funding with supplemental push support. These results challenge current push-heavy practice and offer broader insights for global health and innovation policy.\n\n\n\n\nAbout the Speaker\n\n\nPeng Sun is a JB Fuqua Professor in the Decision Sciences area at the Fuqua School of Business\, Duke University. He researches mathematical theories and models for resource allocation decisions under uncertainty\, and incentive issues in dynamic environments. His work spans a range of applications areas\, from operations management\, economics\, finance\, marketing\, to health care and sustainability. He has served as a Department Editor at Management Science\, and an Associate Editor at Operations Research.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-11-mar-2026-10am/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20260318T100000
DTEND;TZID=Asia/Singapore:20260318T113000
DTSTAMP:20260419T135023
CREATED:20260309T081250Z
LAST-MODIFIED:20260309T081250Z
UID:27566-1773828000-1773833400@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Robert Shumsky
DESCRIPTION:Name of Speaker\n\n\nRobert Shumsky\n\n\n\n\nSchedule \n\n\n18 Mar 2026\, 10am – 11.30am \n (60 min talk + 30 min Q&A) \n\n\n\n\nVenue \n\n\nBIZ2 0511\n\n\n\n\nLink to register \n(via Zoom) \n\n\nhttps://nus-sg.zoom.us/meeting/register/fjT0SX_zQPCBsBv0ciBjsw\n\n\n\n\nTitle\n\n\nUse it or Slowly Lose it: Expertise Atrophy with Organizational AI Usage\n\n\n\n\nAbstract \n\n\nAs organizations adopt generative AI\, its use can improve productivity but reliance can lead to atrophy of worker knowledge and skills over time. The challenge is how to incentivize human oversight and maintain long-run expertise. Using a principal-agent framework\, we study optimal incentive design when workers can exert costly effort to verify and correct imperfect AI output\, where effort both improves current performance and preserves expertise. A central managerial challenge is that improving AI quality makes oversight harder to motivate\, since acceptable outcomes increasingly occur even when workers shirk. Consequently\, profit-maximizing compensation can be non-monotonic in AI quality\, skill\, or return on effort\, and organizations may even be better off\, in terms of profitability\, with worse AI systems. More subtle implications arise when skills decay with AI reliance. First\, due to contracting frictions\, we find that firms may (rationally) allow expertise to deteriorate by substituting higher effort from non-experts for expertise\, leading to significant performance losses compared to a system in which both effort and expertise can be prescribed. Second\, when tasks are relatively less complex with short learning curves and high returns on effort for low-skilled workers\, then the risk of skill atrophy can mitigate these frictions. For such tasks workers are self-motivated to preserve expertise\, so that higher rates of potential skill loss can\, counterintuitively\, increase profit. These insights highlight a managerial “danger zone” in which low-to-moderate skill decay is easily overlooked yet leads to substantial long-term losses\, underscoring when proactive investment in human expertise is most valuable.\n\n\n\n\nAbout the Speaker\n\n\nRobert Shumsky is a Professor of Operations Management at the Tuck School of Business at Dartmouth and is faculty co-director of Health Care Management Education at Dartmouth. His research focuses on the improvement of service operations\, and he has written about capacity estimation and control\, how to allocate work to improve quality\, and how to coordinate service supply chains. He has conducted research on the U.S. air traffic management system and studied transportation operations for state agencies and the Federal Aviation Administration. He has also served as a consultant for both manufacturing and service operations\, including call centers and health care providers. Professor Shumsky has published articles in many academic journals including Operations Research\, Management Science\, and the Proceedings of the National Academy of Science. He currently serves in various editorial positions for several academic journals. He received his PhD degree in Operations Research from MIT.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-robert-shumsky/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20260320T100000
DTEND;TZID=Asia/Singapore:20260320T233000
DTSTAMP:20260419T135023
CREATED:20260312T140809Z
LAST-MODIFIED:20260312T140809Z
UID:27568-1774000800-1774049400@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Ignacio Rios
DESCRIPTION:Name of Speaker\n\n\nIgnacio Rios\n\n\n\n\nSchedule \n\n\n20 Mar 2026\, 10am – 11.30am \n (60 min talk + 30 min Q&A)\n\n\n\nVenue \n\n\nBIZ1 0302\n\n\n\nLink to register \n(via Zoom)\n\nhttps://nus-sg.zoom.us/meeting/register/-QjsYdlrQXyy-bdAfa6zlg\n\n\n\n\nTitle\n\n\nDesigning Effective Fundraising Campaigns: The Role of Incentives and Solicitation Mechanisms\n\n\n\n\nAbstract \n\n\nCharitable donations are a vital source of funding for nonprofit organizations\, enabling them to carry out their mission of addressing social issues and providing support to those in need. To boost contributions\, third parties often donate large sums that fundraisers use to incentivize individual donations\, with one-to-one matching being the most common mechanism. However\, alternative designs may lead to even higher contributions. This paper investigates the effectiveness of two design choices in the context of fundraising: (i) the incentive mechanism\, focusing on the two most prevalent ones (i.e.\, matching and gift unlock); and (ii) the solicitation mechanism\, i.e.\, whether donations occur simultaneously or sequentially. We introduce a stylized game-theoretical model where a fundraiser decides the design choices and corresponding design parameters to maximize overall donations. Following the fundraiser’s decision\, donors make their one-time contribution. For each design choice\, we characterize the equilibrium donations and find the fundraiser’s optimal policy. We find that gift unlock consistently outperforms matching. Moreover\, sequential solicitation is the optimal choice with gift unlock\, whereas simultaneous solicitation yields higher overall contributions with matching. Furthermore\, our simulations indicate that the effectiveness of gift unlock is robust to peer effects and donor participation uncertainty. Our findings indicate that fundraisers should prioritize gift unlock over matching\, align the selected incentive mechanism with the optimal solicitation format\, and calibrate campaign parameters to maximize donation outcomes.\n\n\n\n\nAbout the Speaker\n\n\nIgnacio Ríos is an Assistant Professor of Operations Management at the Jindal School of Management\, University of Texas at Dallas. He holds a Ph.D. in Operations\, Information\, and Technology and an M.A. in Economics from Stanford University\, as well as degrees in Operations Management and Industrial Engineering from the University of Chile. His research expertise lies in behavioral market design\, with a focus on how incentives\, information\, allocation rules and users’ behavior shape outcomes in markets without money. Ignacio has played a leading role in the reform of Chile’s school choice and college admissions systems\, and also in designing other two-sided matching markets. His work has been recognized with numerous awards\, including the Poets & Quants “40 Under 40 Best Business School Professors” distinction\, the IFORS Prize for OR in Development\, and the BOM Best Paper Award.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-ignacio-rios/
CATEGORIES:IORA Seminar Series
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DTSTART;TZID=Asia/Singapore:20260327T100000
DTEND;TZID=Asia/Singapore:20260327T113000
DTSTAMP:20260419T135023
CREATED:20260325T031142Z
LAST-MODIFIED:20260325T031142Z
UID:27572-1774605600-1774611000@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Yael Grushka-Cockayne
DESCRIPTION:Name of Speaker\n\n\nYael Grushka-Cockayne \n\n\n\n\nSchedule \n\n\n27 Mar 2026\, 10am – 11.30am \n (60 min talk + 30 min Q&A)\n\n\n\nVenue \n\n\nHSS 4-2\n\n\n\nLink to register \n(via Zoom)\n\nhttps://nus-sg.zoom.us/meeting/register/51hGI1hiRe-T473GjiQA1w\n\n\n\n\nTitle\n\n\nDecision-making with Ordinal Ratings\n\n\n\n\nAbstract \n\n\nExperts often provide judgments on an ordinal scale\, which are easy to generate and are intuitive. Ordinal ratings\, however\, are not trivial to aggregate across multiple experts\, as they provide neither the strict preference ordering of a ranking\, nor the intensity of preference of cardinal scores. In addition\, ordinal rating judgments often map to a broad set of outcomes\, which are not expressed through the ordinal\, discrete set of choices elicited. In this way\, ordinal ratings also neglect to express the degree of uncertainty that may exist when rankings are interpreted as forecasts. We offer a framework for mapping ordinal ratings to continuous outcome distributions\, allowing for the aggregation of ratings and the expression of the uncertainty that may exist in the forecasts. Finally\, our framework allows for rendering the aggregate distributional forecasts back to the original ordinal scale\, providing again an intuitive set of judgements\, to be used by the decision maker. We demonstrate our framework in the context of National Football League (NFL) scout assessments of players performance. These assessments\, treated as forecasts\, are utilized by general managers when making player selection decisions in the annual NFL draft.\n\n\n\n\nAbout the Speaker\n\n\nYael Grushka-Cockayne \nLandmark Communication Incorporated Professor of Business Administration\, Vice Dean and Senior Associate Dean for Professional Degree Programs\, Academic Co-Director of the LaCross Institute for AI.\nProfessor Yael Grushka-Cockayne’s research and teaching activities focus on data science\, artificial intelligence\, forecasting\, project management and behavioral decision-making. Her research is published in numerous academic and professional journals\, and she is a regular speaker at international conferences in the areas of decision analysis\, project management and management science. Prof. Grushka-Cockayne is an award-winning teacher\, winning the Darden Morton Leadership Faculty Award in 2011\, the University of Virginia’s Mead-Colley Award in 2012\, the Darden Outstanding Faculty Award in 2013 and 2022\, University of Virginia All University Teaching Award in 2015\, the Faculty Diversity Award in 2013 and 2018\, and the Transformational Faculty Award in 2024. Prof. Grushka-Cockayne teaches the core “Decision Analysis” course\, an elective she designed on project management\, an elective on data science and a new course on coding with ChatGPT. \nBefore starting her academic career\, she worked in San Francisco as a marketing director of an Israeli ERP company. As an expert in the areas of project management\, Prof. Grushka-Cockayne has served as a consultant to international firms in the aerospace and pharma industries. She is a UVA Excellence in Diversity fellow and a member of INFORMS\, the President of the Decision Analysis Society\, and a member of the Operational Research Society and the Project Management Institute (PMI). She served an associate editor at Management Science and is currently as associate editor at Operation Research. \nGrushka-Cockayne was named one of “21 Thought-Leader Professors” in Data Science. Her course “Fundamentals of Project Planning and Management” Coursera MOOC has over 300\,000 enrolled\, across 200 countries worldwide. Her “Data Science for Business” Harvard Online course\, launched in 2021\, has taught hundreds of learners around the world.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-yael-grushka-cockayne/
CATEGORIES:IORA Seminar Series
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DTSTART;TZID=Asia/Singapore:20260410T100000
DTEND;TZID=Asia/Singapore:20260410T113000
DTSTAMP:20260419T135023
CREATED:20260401T024941Z
LAST-MODIFIED:20260401T024941Z
UID:27574-1775815200-1775820600@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Park Sinchaisri
DESCRIPTION:Name of Speaker\n\n\nPark Sinchaisri \n\n\n\n\nSchedule \n\n\n10 Apr 2026\, 10am – 11.30am \n (60 min talk + 30 min Q&A)\n\n\n\nVenue \n\n\nBIZ1 0204\n\n\n\nLink to register \n(via Zoom)\n\nhttps://nus-sg.zoom.us/meeting/register/oo0ElW4xSIu9BcdsAyKQ2A\n\n\n\n\nTitle\n\n\nAlgorithmic Advice\, Human Compliance\, and Learning\n\n\n\n\nAbstract \n\n\nProblem definition:Organizations increasingly deploy algorithmic tools to support complex operational decisions\,raising a practical design question: how should these tools be built when designers care not only about immediate performance\, butalso about preserving and building human skill that remains valuable when advice is unavailable\, imperfect\, or requires genuineoversight? We study how theprecisionof algorithmic advice shapes this trade-off.Methodology/results:We develop a stylized modelof advice-taking and learning. The model characterizes a reward-learning frontier: precise\, action-level advice is easier to implementand improves payoffs while available through higher compliance\, whereas broad\, strategic advice requires interpretation\, inducesgreater exploration\, and generates knowledge that is portable\, even when decision environments differ. We test the model’s predictionsin two online experiments in an electric-vehicle routing and charging task\, representing typical characteristics of sequential decisiontasks. Consistent with the theory\, precise numerical advice delivers the strongest gains during the advice phase\, whereas broaderadvice can yield more robust performance after advice is removed\, specifically if the new environment differs substantially\, butnot completely. We use inverse reinforcement learning to recover interpretable latent objective components from action traces\,distinguishing transient compliance from persistent internalization.Managerial implications:Our results provide design guidancefor advice systems that balance short-run operational efficiency with the development of long-run human capability. They also helpvalidate inverse reinforcement learning as an effective tool for estimating human behaviors in complex sequential tasks\n\n\n\n\nAbout the Speaker\n\n\nPark Sinchaisri is an Assistant Professor of Operations and IT Management at the Haas School of Business\, University of California\, Berkeley. His research draws on operations management\, economics\, machine learning\, and behavioral science to study human decision-making in complex environments\, design human-AI systems that improve decision-making\, and develop strategies for managing the future of work. His work has been published in Management Science and Manufacturing & Service Operations Management\, and has also appeared in leading human-computer interaction venues including CSCW. He received his PhD in Operations\, Information and Decisions and an AM in Statistics from the Wharton School of the University of Pennsylvania\, an SM in Computational Science and Engineering from MIT\, and an ScB in Computer Engineering and Applied Mathematics-Economics from Brown University. Originally from Bangkok\, Thailand\, he hopes his research can help address urban challenges and improve outcomes for marginalized workers.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-park-sinchaisri/
CATEGORIES:IORA Seminar Series
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