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X-WR-CALNAME:IORA - Institute of Operations Research and Analytics
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X-WR-CALDESC:Events for IORA - Institute of Operations Research and Analytics
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DTSTART:20250101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20260410T100000
DTEND;TZID=Asia/Singapore:20260410T113000
DTSTAMP:20260523T063247
CREATED:20260401T024941Z
LAST-MODIFIED:20260401T024941Z
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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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BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20260417T100000
DTEND;TZID=Asia/Singapore:20260417T113000
DTSTAMP:20260523T063247
CREATED:20260421T132906Z
LAST-MODIFIED:20260421T132906Z
UID:27587-1776420000-1776425400@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Kwok-Hao Lee
DESCRIPTION:Name of Speaker\n\n\nKwok-Hao Lee\n\n\n\n\nSchedule \n\n\n17 Apr 2026\, 10am – 11.30am \n (60 min talk + 30 min Q&A)\n\n\n\nVenue \n\n\nHSS 3-1\n\n\n\nLink to register \n(via Zoom)\n\nhttps://nus-sg.zoom.us/meeting/register/-DSUpgQWTeqmXSIHbsTGyA\n\n\n\n\nTitle\n\n\nTwo-Sided Markets Shaped By Platform-Guided Search\n\n\n\n\nAbstract \n\n\nWe investigate concerns that vertically integrated platforms like Amazon steer demand towards their own offers via algorithmic prominence\, potentially harming consumers. On Amazon\, for each product\, the Buybox prominence algorithm selects one seller to feature\, influencing which offers consumers consider. Using novel Amazon sales and Buybox (prominence) data\, we estimate a structural model capturing the effects of such algorithmic prominence on consumer choices\, seller pricing\, and entry. We find that the platform can indeed steer demand as 95% of consumers consider only the Buybox offer. The Buybox is highly price-elastic (−21)\, but skews towards Amazon’s own offers\, which are featured as frequently as observably similar offers priced 5% cheaper. Still\, as consumers prefer these offers\, this skew does not amount to self-preferencing in the sense of harming consumers: consumer surplus is roughly maximized at the estimated Amazon Buybox advantage\, which balances higher prices against showing consumers their preferred offers.\n\n\n\n\nAbout the Speaker\n\n\nLee Kwok Hao is an industrial organisation economist working at the intersection of digital markets and the smart city. He uses administrative and platform data to study how algorithms and policy rules govern search\, matching\, pricing\, and allocation\, with a focus on transportation systems and public housing. As an Assistant Professor (Presidential Young Professor) at the Department of Strategy & Policy at the National University of Singapore (NUS) Business School\, Kwok Hao has been a recipient of the Social Science and Humanities Research Fellowship under the Social Science Research Council of Singapore. Previously\, Kwok Hao was a Presidential Fellow at the NUS Business School\, during which he spent a postdoctoral stint at the Cowles Foundation at Yale University. He obtained my PhD from Princeton University after formative years at the University of Chicago and Washington University in St. Louis.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-kwok-hao-lee/
CATEGORIES:IORA Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20260424T100000
DTEND;TZID=Asia/Singapore:20260424T113000
DTSTAMP:20260523T063247
CREATED:20260421T133016Z
LAST-MODIFIED:20260421T133016Z
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SUMMARY:DAO-ISEM-IORA Seminar Series: Yanwei Jia
DESCRIPTION:Name of Speaker\n\n\nYanwei Jia\n\n\n\n\nSchedule \n\n\n24 Apr 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/QpOphmoURVCrbzjftZht4g\n\n\n\n\nTitle\n\n\nWhen to Quit a Venture: Normative Theory and Structural Identification of Decoupled Belief and Decision\n\n\n\n\nAbstract \n\n\nUnderstanding how agents learn and make decisions under uncertainty is a fundamental question in many fields\, with applications including real options\, R&D\, and entrepreneurial ventures. The conventional approach formulates this learning process as an optimal stopping problem within a Bayes framework\, assuming agents possess the cognitive sophistication to continuously update their beliefs based on statistical principles\, thereby rigidly locking their decisions to these updated beliefs and forcing a strict\, deterministic threshold rule. This paper develops a continuous-time reinforcement learning framework for sequential experimentation that formally separates beliefs from actions. By decoupling the evaluation and policy processes\, we provide a unifying framework that yields both normative benchmarks and flexible positive dynamics. Normatively\, using the workhorse Gaussian bandit model\, we prove that by properly tuning learning rates\, the framework achieves a logarithmic regret bound\, matching the efficiency of Bayesian rationality. Positively\, the decoupled policy generates distinct and testable predictions\, such as experience-driven\, path-dependent quitting dynamics\, even when the belief is consistent with its Bayesian counterpart. Crucially\, we prove the structural identifiability of these hidden learning dynamics. By utilizing the method of simulated moments\, we demonstrate how this framework can be structurally estimated directly from censored observational field data and extended to general jump-diffusion bandits.\n\n\n\n\nAbout the Speaker\n\n\nYanwei Jia is an assistant professor in the Department of Systems Engineering and Engineering Management at The Chinese University of Hong Kong. He obtained his Ph.D. degree from the National University of Singapore in 2020\, and B.Sc. from Tsinghua University in 2016. Prior to joining CUHK in 2023\, he was an associate research scientist and adjunct assistant professor in the Department of Industrial Engineering and Operations Research at Columbia University. His research interest falls broadly into financial decision-making problems and uses the structural approach to study the decision making and information aggregation mechanism.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-yanwei-jia/
CATEGORIES:IORA Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20260520T100000
DTEND;TZID=Asia/Singapore:20260520T113000
DTSTAMP:20260523T063247
CREATED:20260513T081843Z
LAST-MODIFIED:20260513T081843Z
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SUMMARY:DAO-ISEM-IORA Seminar Series: Diwakar Gupta
DESCRIPTION:Name of Speaker\n\n\nDiwakar Gupta \n\n\n\n\nSchedule \n\n\n20 May 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/Wne_hIgXQ-qf4uJZ1Frn5Q\n\n\n\n\nTitle\n\n\nThe Impact of List Diving on Post-Transplant Outcomes\n\n\n\n\nAbstract \n\nTransplant programs often turn down deceased-donor kidney offers for their top-ranked potential transplant recipients (PTRs) and utilize them for lower-ranked PTRs. This practice is known as list diving. PTRs in the US are ranked based on an evidence- and consensus-based policy that reflects the collective judgment of stakeholders in the kidney transplant ecosystem. Because list diving upends the consensus ranking\, concerns have been raised about its impact on the national system. In this talk\, I will present an empirical analysis of the Organ Procurement and Transplantation Network (OPTN) data to quantify the impact of list diving decisions on short- and long-term survival of PTRs after accounting for the endogeneity of such decisions. I will also illustrate the impact of list diving on skipped candidates. The analysis shows that list diving worsens 1 and 3-year survival for transplants performed by centers with significant within-DSA competition. A significant minority of first-ranked skipped candidates do not receive transplants and either die or are removed from waitlist. Their average wait time is 8 months longer. The study highlights the need for greater oversight over transplant programs’ utilization decisions.\n\n\n\nAbout the Speaker\n\n\nDiwakar Gupta holds an appointment as the INBA–Stuart Centennial Professor of Information\, Risk\, and Operations Management at the McCombs School of Business of The University of Texas at Austin. His research spans healthcare operations\, supply chain finance and risk management\, and inventory and revenue management. He serves as the departmental editor of healthcare operations department at the Naval Research Logistics journal and as senior editor of healthcare operations management department at the POMS journal. He teaches healthcare analytics at UT Austin.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-diwakar-gupta/
CATEGORIES:IORA Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20260522T100000
DTEND;TZID=Asia/Singapore:20260522T113000
DTSTAMP:20260523T063247
CREATED:20260518T033949Z
LAST-MODIFIED:20260518T033949Z
UID:27604-1779444000-1779449400@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: George Shanthikumar
DESCRIPTION:Name of Speaker\n\n\nGeorge Shanthikumar \n\n\n\n\nSchedule \n\n\n22 May 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/nhLjyspHTpuCwf5OfrR7rg\n\n\n\n\nTitle\n\n\nFull Space (FS) Relative Valuations\, Risk Measures and Valuations of Risky Prospects\n\n\n\n\nAbstract \n\n\nThis paper proposes a unified mathematical infrastructure for the valuation of risky prospects:the Full-Space (FS) Relative Valuation framework. This framework generalizes and synthesizes disparate valuation paradigms in economics\, finance\, and insurance into a single\, coherent structure. We demonstrate that the FS framework is both general and tractable. Its core representation is characterized by necessary and sufficient conditions (i.e.\, modularity on the lattice of quantile or distribution functions) and we show it can be generalized to represent any valuation functional as an infimum over FS-type kernels. The framework also possesses desirable theoretical properties (e.g.\, monotonicity\, concave order preservation) and admits practical representations\, including certainty-equivalent construction and a computationally appealing Fenchel-type supremum form. By integrating these features\, FS valuations offer a powerful and versatile foundation for modeling and optimization across disciplines. \n\n\n\n\nAbout the Speaker\n\n\nProfessor Shanthikumar joined the Krannert faculty in 2009. Prior to coming to Purdue\, he was a Chancellor’s Professor of Industrial Engineering and Operations Research at the University of California\, Berkeley. His research interests are in integrated interdisciplinary decision making\, model uncertainty and learning\, production systems modeling and analysis\, queueing theory\, reliability\, scheduling\, semiconductor yield management\, simulation stochastic processes\, and sustainable supply chain management. He has written or co-written more than 250 papers on these topics. He is a co-author (with John A. Buzacott) of the book Stochastic Models of Manufacturing Systems and a co-author (with Moshe Shaked) of the books Stochastic Orders and Their Applications and Stochastic Orders. \nHe was a co-editor of Flexible Services & Manufacturing Journal and is (or was) a member of the editorial boards of the Asia-Pacific Journal of Operations Research\, IEEE Transactions on Automation Sciences and Engineering\, IIE Transactions\, International Journal of Flexible Management Systems\, Journal of Discrete Event Dynamic Systems\, Journal of the Production and Operations Management Society\, Operations Research\, Operations Research Letters\, OPSEARCH\, Probability in the Engineering and Information Sciences\, and Queueing Systems: Theory and Applications.\nProfessor Shanthikumar has extensively consulted for various companies\, including Applied Materials (AMAT)\, Bellcore\, IBM\, KLA-Tencor\, NTT (Japan)\, Intel\, Intermolecular\, ReelSolar\, Safeway\, and Southern Pacific. Through KLA-Tencor\, he has worked on joint development projects for Advanced Micro Devices\, IBM\, Intel\, LSI\, Motorola\, Texas Instruments\, Toshiba\, Fujitsu\, Taiwan Semiconductor Manufacturing Company\, and UMC.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-george-shanthikumar/
CATEGORIES:IORA Seminar Series
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