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TZID:Asia/Singapore
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DTSTART:20240101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250117T100000
DTEND;TZID=Asia/Singapore:20250117T113000
DTSTAMP:20260417T123224
CREATED:20250110T035433Z
LAST-MODIFIED:20250110T035433Z
UID:23783-1737108000-1737113400@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Chen Mingliu
DESCRIPTION:Name of Speaker\n\n\n\n Chen Mingliu\n\n\n\n\n\nSchedule\n\n\n\n 17 January 2025\, 10am – 11.30am\n\n\n\n\n\nVenue\n\n\n\n BIZ1 03-02\n\n\n\n\n\nLink to Register\n\n\n\nhttps://nus-sg.zoom.us/meeting/register/H3CGlNujTwaHoiOLaaIkpw\n\n\n\n\nTitle\n\n\n\n Optimal Capacity and Price Designs under Ex Ante and Ex Post Theft\n\n\n\n\n\nAbstract\n\n\nInternal theft poses a significant challenge in retail firms’ operations. Owing to a lack of effective monitoring tools\, a firm cannot observe every action in daily operations from its employees\, providing room for wrongdoings\, such as capacity and cash stealing. As a result\, a common practice is to increase the price of goods to offset the loss in revenue due to the increasing threat of theft. However\, we show that such practices are not optimal. In this paper\, we model the internal theft problem in retailing as a principal-agent model\, where the principal (firm) contracts an agent (retail manager) for capacity planning and daily sales. The agent is subject to moral hazard and may steal the capacity (procurement budget or company asset) before demand realization (ex ante stealing) or steal the sales revenue after demand realization (ex post stealing). We solve for the optimal capacity\, price\, and agent’s commission decisions to maximize the principal’s utility. We find that capacity and price decisions are not monotone in terms of the severity of moral hazards. In particular\, the principal should first decrease and then increase (increase and then decrease) the price (the capacity) when ex post stealing becomes more prevalent. As a result\, simply increasing retail prices and shifting the margin to consumers to combat loss in revenue caused by internal theft can amplify the agency problem in some scenarios since it leads to a significant loss in demand and insufficient commission to the agent. Retail firms should instead focus on jointly optimizing capacity and price and providing their employees with appropriate commissions. Finally\, we investigate the sensitivities of price and capacity decisions to demand uncertainties in the presence of moral hazard.\n\n\n\n\n\nAbout the Speaker\n\n\nMingliu Chen is an Assistant Professor in Operations Management at Jindal School of Management\, the University of Texas at Dallas. He is interested in applying analytical and modeling techniques in market and mechanism design issues. He has contributed to the literature on contract designs and developed novel models describing problems in the sharing economy and online matching platforms. Recently\, his research focused on design problems in some emerging markets and the interface between contracting theory and operations.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-chen-mingliu/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250207T100000
DTEND;TZID=Asia/Singapore:20250207T113000
DTSTAMP:20260417T123224
CREATED:20250207T092300Z
LAST-MODIFIED:20250207T092300Z
UID:24759-1738922400-1738927800@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Chamsi Hssaine
DESCRIPTION:Name of Speaker\nChamsi Hssaine\n\n\nSchedule\n7 February 2025\, 10am\n\n\nVenue \nBIZ1-0302\n\n\nLink to Register\nhttps://nus-sg.zoom.us/j/84342221512?pwd=HlK2CjDj99BuaI5be4rJEIUxg9nh2F.1\n\n\nTitle\nTarget-Following Online Resource Allocation Using Proxy Assignments\n\n\nAbstract\nWe study a target-following variation of online resource allocation. As in classical resource allocation\, the decision-maker must assign sequentially arriving jobs to one of multiple available resources. However\, in addition to the assignment costs incurred from these decisions\, the decision-maker is also penalized for deviating from exogenously given\, nonstationary target allocations throughout the horizon. The goal is to minimize the total expected assignment and deviation penalty costs incurred throughout the horizon when the distribution of assignment costs is unknown. In contrast to traditional online resource allocation\, in our setting the timing of allocation decisions is critical due to the nonstationarity of allocation targets. Examples of practical problems that fit this framework include many physical resource settings where capacity is time-varying\, such as manual warehouse processes where staffing levels change over time\, and assignment of packages to outbound trucks whose departure times are scheduled throughout the day. We first show that naive extensions of state-of-the-art algorithms for classical resource allocation problems can fail dramatically when applied to target-following resource allocation. We then propose a novel “proxy assignment” primal-dual algorithm for the target-following online resource allocation problem that uses current arrivals to simulate the effect of future arrivals. We prove that our algorithm incurs the optimal sublinear regret bound when the assignment costs of the arriving jobs are drawn i.i.d. from a fixed distribution. We demonstrate the practical performance of our approach by conducting numerical experiments on synthetic datasets\, as well as real-world datasets from retail fulfillment operations. Joint with Huseyin Topaloglu and Garrett van Ryzin (link: https://arxiv.org/pdf/2412.12321)\n\n\nAbout the Speaker\nChamsi Hssaine is an assistant professor of Data Sciences and Operations at the University of Southern California’s Marshall School of Business. Prior to joining Marshall\, Chamsi was a postdoctoral scientist in the Supply Chain Optimization Technologies Group at Amazon\, working under the supervision of Garrett van Ryzin. She received her Ph.D. in Operations Research at Cornell University\, and before that graduated magna cum laude from Princeton University with a B.S.E. in Operations Research and Financial Engineering. Chamsi’s research interests lie broadly in data-driven decision-making\, with a special focus on pricing and inventory management. Much of her work focuses on the intersection of algorithmic decision-making and societal considerations such as fairness and social welfare. Chamsi’s work has received a number of recognitions\, including being named a Rising Star in EECS\, as well being a runner-up for the Minority Issues Forum and INFORMS Service Science Best DEIJ Paper Awards.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-chamsi-hssaine/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250214T100000
DTEND;TZID=Asia/Singapore:20250214T113000
DTSTAMP:20260417T123224
CREATED:20250207T093131Z
LAST-MODIFIED:20250207T093323Z
UID:24765-1739527200-1739532600@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Chao Xiuli
DESCRIPTION:Name of Speaker\nChao Xiuli\n\n\nSchedule\n14 February 2025\, 10am\n\n\nVenue\nHon Sui Sen Auditorium\, Hon Sui Sen Memorial Library\n\n\nZoom Link \nhttps://nus-sg.zoom.us/meeting/register/1694uQvqQeGDmm_T4VQ10g\n\n\nTitle\nJoint pricing and delayed empty relocation policies for ride-sourcing systems\n\n\nAbstract\nWith the development of shared mobility (e.g.\, ride-sourcing systems such as Uber\, Lyft and Didi)\, there has been a growing interest in pricing and empty vehicle relocation to maximize system performance. Although customers exhibit patience during their waiting for available driver\, it has been neglected in most studies due to the complexities it introduces. In this work\, we develop a provably near-optimal dynamic pricing and empty vehicle relocation mechanism for a ride-sourcing system with limited customer patience. We model the ride-sourcing system as a network of double-ended queues. To derive a near-optimal control policy\, we first establish a fluid limit for the network in a large market regime and show that the fluid-based optimal solution provides an upper bound of the performance of the original ride-sourcing system for all dynamic policies. Then\, we develop a simple dynamic policy for the original problem based on the fluid solution and show that its performance almost matches the upper bound. Among our results\, we answer two open questions raised in the literature: (i) the performance of our policy converges to that of the true optimal value exponentially fast in time when the market size is large; (ii) the customer loss of our proposed policy decreases to zero exponentially fast when market size increases. This talk is based on joint work with M. Abdolmaleki\, T. Radvand\, and Y. Yin at the University of Michigan.\n\n\nAbout the Speaker\nXiuli Chao is the Ralph L. Disney Professor of Industrial and Operations Engineering at the University of Michigan\, Ann Arbor. His research interests include queueing\, scheduling\, inventory control\, game theory\, supply chain management\, and online learning and optimization. He is the co-author of two books\, “Operations Scheduling with Applications in Manufacturing and Services” (Irwin/McGraw-Hill\, 1998)\, and “Queueing Networks: Customers\, Signals\, and Product Form Solutions” (John Wiley & Sons\, 1999). Chao received the Erlang Prize from the Applied Probability Society of INFORMS in 1998\, and the David F. Baker Distinguished Research Award from Institute of Industrial and Systems Engineers (IISE) in 2005. He also received the Jon and Beverly Holt Award for Excellence in Teaching from the University of Michigan. Chao is a co-developer of scheduling system Lekin. He is a fellow of INFORMS and IISE.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-chao-xiuli/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250220T100000
DTEND;TZID=Asia/Singapore:20250220T110000
DTSTAMP:20260417T123224
CREATED:20250214T070448Z
LAST-MODIFIED:20250214T070448Z
UID:25086-1740045600-1740049200@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Jong-Shi Pang
DESCRIPTION:Name of Speaker\nJong-Shi Pang\n\n\nSchedule\n20 February 2025\, 10am – 11am\n\n\nVenue \nE1-07-21/22 – ISEM Executive Classroom\n\n\nLink to Register \n \nhttps://nus-sg.zoom.us/j/89954075233?pwd=HWYCdpXSJy2T6aCirNUZgUJhO9RYHd.1\n\n\nTitle\nHeaviside Composite Optimization: A New Paradigm in Optimization\n\n\nAbstract\nThis talk introduces the topic of Heaviside composite optimization and briefly covers its many facets: breadth in modeling\, roles in old and new applications\, theory of optimizers and stationary solutions\, bridge with discrete optimization\, and the progressive integer programming method.   By definition\, a univariate Heaviside function is the (discontinuous) indicator of an interval.  By its name\, a Heaviside composite function is the composition of a Heaviside function with a continuous multivariate function that may be nonconvex and nondifferentiable.  While very natural in modeling many physical phenomena\, a Heaviside composite optimization problem\, possibly with Heaviside composite functional constraints\, has never been formally studied.  Our work aims to fill this void with a comprehensive research program covering the applications\, theory\, and algorithms for this novel class of very challenging optimization problems.\n\n\nAbout the Speaker\nElected a member of the National Academy of Engineering in February 2021 and appointed a Distinguished Professor in April 2023\, Jong-Shi Pang joined the University of Southern California as the Epstein Family Chair and Professor of Industrial and Systems Engineering in August 2013. Prior to this position\, he was the Caterpillar Professor and Head of the Department of Industrial and Enterprise Systems Engineering at the University of Illinois at Urbana-Champagne for six years between 2007 and 2013. He held the position of the Margaret A. Darrin Distinguished Professor in Applied Mathematics in the Department of Mathematical Sciences and was a Professor of Decision Sciences and Engineering Systems at Rensselaer Polytechnic Institute from 2003 to 2007. He was a Professor in the Department of Mathematical Sciences at the Johns Hopkins University from 1987 to 2003\, an Associate Professor and then Professor in the School of Management from 1982 to 1987 at the University of Texas at Dallas\, and an Assistant and then an Associate Professor in the Graduate School of Industrial Administration at Carnegie-Mellon University from 1977 to 1982. During 1999 and 2001 (full time) and 2002 (part-time)\, he was a Program Director in the Division of Mathematical Sciences at the National Science Foundation. Professor Pang has served as the Department Academic Advisor of the Department of Mathematics at the Hong Kong Polytechnic University. He has given many distinguished lectures at universities worldwide and plenary lectures at international conferences.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-jong-shi-pang/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250228T100000
DTEND;TZID=Asia/Singapore:20250228T113000
DTSTAMP:20260417T123224
CREATED:20250214T071455Z
LAST-MODIFIED:20250214T071455Z
UID:25091-1740736800-1740742200@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Dan Iancu
DESCRIPTION:Name of Speaker\nDan Iancu\n\n\nSchedule\n28 February 2025\, 10am – 11.30am\n\n\nVenue \nBIZ1-0302\n\n\nLink to Register\nhttps://nus-sg.zoom.us/meeting/register/R4hPhsB9S6y5EikHYbD48A\n\n\nTitle\nManaging Sustainable Food Systems\n\n\nAbstract\nWe discuss a set of problems arising in the management of global food systems where technology and data analytics combined with operational innovations and incentives can lead to substantial improvements. The first part of the talk focuses on the issue of tropical deforestation associated with the supply of agricultural commodities such as palm oil\, cocoa\, or coffee\, which causes alarming CO2 emissions and loss of biodiversity and ecosystem services. To prevent this\, governments and multinational commodity buyers are offering positive incentives for local communities conditional on preventing deforestation in a specified area. We propose and analyze alternative weaker conditions related to preventing the use of timber or cleared land for economic purposes. To compare various incentive schemes\, we propose a new robust solution concept for cooperative games with externalities and use it to characterize the best condition and the feasible incentives that prevent deforestation and compensate local community members for missed economic opportunities. We then leverage this framework to determine whether conditional price premiums for palm fruit would successfully prevent deforestation in the Indonesian palm oil supply chain. Using survey data from 58 villages in East Kalimantan and robust data envelopment analysis\, we find that the Roundtable on Sustainable Palm Oil (RSPO) price premium is too low\, but moderate price premiums combined with our novel conditions would prevent deforestation in most villages and would be remarkably robust to entry by outsiders. The second part of the talk considers problems related to food retail\, and more specifically the management of perishable foods prepared in stores. We show how retailers that optimize their operational policies — optimally choosing the shelf life of products\, the issuance rule\, the price\, and whether to add timestamps that inform customers about the age of products — can successfully boost profit as well as increase customer welfare and reduce food waste.\n\n\nAbout the Speaker\nDan Iancu is an Associate Professor of Operations\, Information and Technology at the Stanford Graduate School of Business. His research and teaching interests are in responsible analytics and AI and data-driven optimization\, with applications in global supply chain management\, FinTech\, and healthcare. Broadly speaking\, his work has two main threads: (i) improving existing methodological tools for data-driven decision-making (e.g.\, making them more scalable\, fair\, robust\, or transparent) and (ii) applying these to address complex operational problems where choices of material\, financial or information flows carry substantial impact on the lives of millions of people and on the natural environment. His research has received several best paper awards and has been published in the top journals in operations research and operations management\, and he serves on the editorial board of several of these journals. His teaching has received commendations at Harvard\, MIT\, Stanford\, and INSEAD.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-dan-iancu/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250307T100000
DTEND;TZID=Asia/Singapore:20250307T113000
DTSTAMP:20260417T123224
CREATED:20250228T032545Z
LAST-MODIFIED:20250228T032545Z
UID:25858-1741341600-1741347000@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series : Nam Ho-Nguyen
DESCRIPTION:  \n\n\n\nName of Speaker\nNam Ho-Nguyen\n\n\nSchedule\n7 March 2025\, 10am – 11.30am\n\n\nVenue \nBIZ1-0302\n\n\nLink to Register \n \nhttps://nus-sg.zoom.us/meeting/register/LmEAt_ZaTS6N4MlO8pFnbg\n\n\nTitle\nMistake\, Manipulation and Margin Guarantees in Online Strategic Classification\n\n\nAbstract\nWe consider an online strategic classification problem where each arriving agent can manipulate their true feature vector to obtain a positive predicted label\, while incurring a cost that depends on the amount of manipulation. The learner seeks to predict the agent’s true label given access to only the manipulated features. After the learner releases their prediction\, the agent’s true label is revealed. Previous algorithms such as the strategic perceptron guarantee finitely many mistakes under a margin assumption on agents’ true feature vectors. However\, these are not guaranteed to encourage agents to be truthful. Promoting truthfulness is intimately linked to obtaining adequate margin on the predictions\, thus we provide two new algorithms aimed at recovering the maximum margin classifier in the presence of strategic agent behavior. We prove convergence\, finite mistake and finite manipulation guarantees for a variety of agent cost structures. We also provide generalized versions of the strategic perceptron with mistake guarantees for different costs. Our numerical study on real and synthetic data demonstrates that the new algorithms outperform previous ones in terms of margin\, number of manipulation and number of mistakes. \n(This is joint work with Lingqing Shen\, Khanh-Hung Giang-Tran and Fatma Kılınç-Karzan.)\n\n\nAbout the Speaker\nNam Ho-Nguyen is a Senior Lecturer in the Discipline of Business Analytics at The University of Sydney Business School. His research focuses on data-driven optimization models and scalable algorithms for decision-making problems under uncertainty. Prior to joining The University of Sydney\, he received his PhD in Operations Research from Carnegie Mellon University\, and was a postdoctoral researcher at the University of Wisconsin-Madison. He was a past recipient of the INFORMS Optimization Society Young Researchers’ Prize 2022\, and received a Discovery Early Career Researchers Award Fellowship from the Australian Research Council in 2024.\n\n\n\n 
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-nam-ho-nguyen/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250312T100000
DTEND;TZID=Asia/Singapore:20250312T113000
DTSTAMP:20260417T123224
CREATED:20250307T023504Z
LAST-MODIFIED:20250307T023504Z
UID:25880-1741773600-1741779000@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series : Lim Yun Fong
DESCRIPTION:Name of Speaker\nLim Yun Fong\n\n\nSchedule\n12 March 2025\, 10am – 11.30am\n\n\nVenue \nBIZ2-0413B\n\n\nLink to Register\nhttps://nus-sg.zoom.us/meeting/register/WYuc2F2xQmuBpvxASTlXcg\n\n\nTitle\nIntegrating EV Charging and Discharging into Power Grid Through Bilateral Negotiation\n\n\nAbstract\nTo deal with demand uncertainty on a power grid\, a power plant with limited ramping capability can collaborate with an electric vehicle (EV) company. With proper charging and discharging prices\, the EV company voluntarily withdraws electricity from or returns electricity to the power grid in suitable phases. We model the two parties’ interactions as a bargaining game on the prices\, followed by the EV company’s charging and discharging problem and the power plant’s electricity generation problem. To solve this bargaining game\, we propose a novel “Guess and Verify” approach. Specifically\, we first find an optimal solution within a restricted price set in which the two parties’ total cost is minimized\, and then verify its global optimality. Under an equilibrium contract\, we find that the power plant can reduce its expected cost from the collaboration. This is because the EV company fully charges in a low electricity demand phase\, reducing the power plant’s curtailment cost\, and fully discharges to the power grid in a high electricity demand phase\, lowering the power plant’s electricity generation cost. Based on real data\, our numerical experiments suggest that the EV company’s charging and discharging can substantially harmonize the power flow within the grid and save significant cost\, especially when the electricity demand gap across different phases increases or the power plant’s ramping capability decreases. Surprisingly\, the EV company’s percentage cost saving can exceed 100%\, implying that it can make a profit from the collaboration. For the power plant\, the percentage cost saving is 2-7%.\n\n\nAbout the Speaker\nYun Fong LIM is Professor of Operations Management at the Lee Kong Chian School of Business\, Singapore Management University (SMU). He has been a Chang Jiang Chair Professor\, Lee Kong Chian Fellow\, MPA Research Fellow\, and NOL Fellow. Yun Fong’s research has appeared in Operations Research\, Management Science\, Manufacturing and Service Operations Management\, and Production and Operations Management. He has delivered keynote and plenary speeches in several international conferences. In addition\, his work has received funding by MOE\, A*STAR\, RGC-HK\, and NNSF\, and media coverage by Financial Times\, The Business Times\, CNA938\, and Channel 8. His current research interests include online retailing (supply chains and fulfillment)\, online platforms (business model innovations)\, sustainable urban systems\, and flexible workforce and resource management. Yun Fong serves as Senior Editor for Production and Operations Management and Associate Editor for Naval Research Logistics. He has placed his PhD students and postdoc to CUHK (Shenzhen)\, USTC\, SUSS\, and ShanghaiTech as well as supervised some DBA students who lead influential firms in China. \nAt SMU\, Yun Fong founded the OM PhD Program. He also served as Academic Director of the Master of Science in Management (MiM) Program in 2020-2023 and played an instrumental role in elevating the program from 83rd to 41st worldwide in the Financial Times Rankings. Yun Fong is a recipient of the SMU Teaching Excellence Innovative Teacher Award. He teaches both undergraduate and postgraduate courses in Operations Management. He has provided consulting service and executive development to corporations such as Alibaba\, Maersk\, McMaster-Carr Company\, Resorts World Sentosa\, Schneider Electrics\, Temasek Holdings\, and Zalora. Yun Fong obtained both his PhD and MSc degrees in Industrial and Systems Engineering from the Georgia Institute of Technology.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-lim-yun-fong/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250314T100000
DTEND;TZID=Asia/Singapore:20250314T113000
DTSTAMP:20260417T123224
CREATED:20250307T023727Z
LAST-MODIFIED:20250307T023819Z
UID:25882-1741946400-1741951800@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series : Dong Lingxiu
DESCRIPTION:Name of Speaker\nDong Lingxiu\n\n\nSchedule\n14 March 2025\, 10am – 11.30am\n\n\nVenue \nBIZ1-0302\n\n\nLink to Register\nhttps://nus-sg.zoom.us/meeting/register/bA-KLhL7Tzibr9SRmbZpGg\n\n\nTitle\nRole of Wellness Valuation Uncertainty and Operational Cost Structure in Product Line Design\n\n\nAbstract\nThe rise of wellness-conscious consumers has led to record demand for products with wellness attributes\, such as low-sugar foods and ultraviolet-protective clothing. This market trend presents a profit-growth opportunity for established companies\, which have dominated the market based on traditional attributes\, such as the taste of food and the appearance of clothing. Yet\, taking advantage of this opportunity is challenging due to the increased operational costs associated with delivering products with wellness attributes and the lack of information on consumers’ valuation of wellness. We present a model of a monopolist developing and producing conventional and wellness products to serve a two-segment market consisting of wellness-conscious and wellness-neutral consumers.  We propose a two-dimensional differentiation-contingency framework to depict the rich set of possible optimal strategies the firm could use to segment the market and explore how the market environment and the firm’s operational environment affect the firm’s choice of the optimal product strategy. We find that while the high expected wellness valuation drives the optimal strategy to be differentiated\, variability in the wellness valuation drives contingency. The contingency dimension is a novel feature in product line design research and enables the firm to hedge its risk of low customer wellness valuation. The firm’s operational cost structure further leads to different prioritization within the wellness product’s quality dimensions: high development cost (resp. high coupling cost between the two quality dimensions) induces prioritization of the traditional (resp. wellness) quality of a wellness product. Examining consumer wellness consumption under the firm’s optimal product strategy offers insights for policy interventions such as consumer educational initiatives and financial incentives to foster innovation.\n\n\nAbout the Speaker\nLingxiu Dong is the Frahm Family Chair Professor of Supply Chain\, Operations\, and Technology at the Olin Business School\, Washington University in St. Louis. Her research focuses on supply chain management\, with particular interests in supply chain control and design\, operational flexibility\, and integrated risk management. Her recent work explores technology-enabled innovation\, sustainability\, food and agriculture supply chains\, and the interface of operations and finance.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-dong-lingxiu/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250321T100000
DTEND;TZID=Asia/Singapore:20250321T113000
DTSTAMP:20260417T123224
CREATED:20250317T022549Z
LAST-MODIFIED:20250317T022549Z
UID:25888-1742551200-1742556600@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Ling Chun Kai
DESCRIPTION:Name of Speaker\nLing Chun Kai\n\n\nSchedule\n21 March 2025\, 10am – 11.30am\n\n\nVenue \nBIZ1 – 0302\n\n\nLink to Register\nhttps://nus-sg.zoom.us/meeting/register/WpZ4beTPQUqSyE-w-DZcPA\n\n\nTitle\nGame Theory: The Art and Science of Strategy\n\n\nAbstract\nGame Theory has emerged as one of the primary tools for multi-agent decision making\, with applications ranging from expert or even superhuman performance in recreational games (e.g.\, Poker\, Starcraft\, Stratego\, Diplomacy) to optimal scheduling of security patrols. Compared to their single agent counterparts\, the multiagent setting is much richer\, with agents exhibiting strategic behavior such as lying\, coercion\, and collusion. In this talk\, I will first introduce basic game theoretic concepts such as the Nash equilibrium. To illustrate the effectiveness of game theoretic approaches\, a series of real-world applications are examined\, including some recent work on optimal patrolling and contested logistics. Finally\, I will briefly cover some problems I am currently working on\, including potential applications in cybersecurity.\n\n\nAbout the Speaker\nChun Kai Ling is an Assistant Professor in the Department of Computer Science in NUS. His research is on multiagent systems and computational game theory. He develops methods in machine learning and optimization to problems in security and logistics. He currently works on modeling and solving large games\, featuring multiple players or general-sum utilities. His work on inverse game theory and multi-defender security games were best papers in IJCAI 2018 and GameSec 2023\, 2024. He was awarded the Sung Kah Kay Assistant Professorship in 2024 and NUS development grant from 2022-2024. Prior to joining NUS\, he was a Postdoc at Columbia University working with Christian Kroer and Garud Iyengar. He completed his PhD at Carnegie Mellon University under the supervision of Zico Kolter and Fei Fang.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-ling-chun-kai/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250401T100000
DTEND;TZID=Asia/Singapore:20250401T113000
DTSTAMP:20260417T123224
CREATED:20250321T031632Z
LAST-MODIFIED:20250321T031700Z
UID:25939-1743501600-1743507000@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Vinod Singhal
DESCRIPTION:Name of Speaker\nVinod Singhal\n\n\nSchedule\n1 April 2025\, 10am – 11.30am\n\n\nVenue \nBIZ1 02-06\n\n\nLink to Register\nhttps://nus-sg.zoom.us/meeting/register/KIy_WyM9SIioyfk8l5-XzQ\n\n\nTitle\nThe Bullwhip Effect and Stock Returns\n\n\nAbstract\nThe bullwhip effect (BWE) is an important phenomenon in the operations and supply chain management field. Although it is commonly accepted that the BWE is widespread and can have a significant adverse impact on financial performance\, there is surprisingly limited objective evidence on the financial consequences of the BWE. This paper examines the impact of the BWE on financial performance by examining the relationship between the BWE and stock price performance. The empirical analysis is based on data from 1985 to 2018 from about 7\,200 publicly traded firms and about 64\,000 firm-years. We find that most results on the impact of the BWE on stock returns are statistically indistinguishable from zero. The few marginally significant results that we find suggest a positive relationship between the BWE and stock returns rather than the expected negative relationship. However\, these marginally significant results do not hold when alternate methods are used to test the relationships. These conclusions are robust when we segment the sample by size\, industry\, and time periods. We also do not find a significant relationship between the BWE and stock returns for samples based on the propagation of the BWE from customers to suppliers. We do find some evidence to suggest that the BWE has a negative impact on inventory turnover. However\, we do not find similar evidence for capacity utilization. The relationships between the BWE and return on assets measures are statistically insignificant. For margin measures\, the relationships are positive and statistically significant but not economically significant.\n\n\nAbout the Speaker\nVinod Singhal is the Charles W. Brady Chair Professor of Operations Management at the Scheller College of Business at Georgia Institute of Technology\, Atlanta\, USA. He has a Ph.D. from University of Rochester\, Rochester\, USA. Prior to joining Georgia Tech.\, he worked as a Senior Research Scientist at General Motors Research Labs. \nVinod’s research has focused on the impact of operating decisions on accounting and stock market-based performance measures. His research has been supported through grants from the US Department of Labor\, National Science Foundation\, the American Society of Quality\, and the Sloan Foundation. He has published extensively in academic journals and has made more than 200 presentations at different universities. His research has been recognized in the practitioner community through his many articles in industry-practitioner journals and frequent invited presentations as keynote speaker at practitioner conferences. His research has been cited over 200 times in practitioner publications such as Business Week\, The Economist\, Fortune\, Smart Money\, CFO Europe\, Financial Times\, Investor’s Business Daily\, and Daily Telegraph.  His research has been extensively cited in academic publications\, with nearly 15\,000 citations. His paper “An empirical analysis of the effect of supply chain disruptions on long‐run stock price performance and equity risk of the firm” was voted by the POMS members in 2024 as one of the top-ten papers published in Production and Operations Management in the last 30 years. \nVinod is a Departmental Editor of Production and Operations Management\, and Associate Editor of Management Science. He is a Fellow of the Production and Operations Management Society.  He served on the Academic Advisory Board of the European School of Management and Technology\, Germany. \nVinod’s teaching interests include operations strategy and supply chain management. He has contributed to teaching at an international level\, as well\, by offering research workshops in countries including Australia\, China\, France\, Germany\, Hong Kong\, India\, New Zealand\, Singapore\, South Korea\, Spain\, Sweden\, and United Kingdom.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-vinod-singhal/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250403T100000
DTEND;TZID=Asia/Singapore:20250403T113000
DTSTAMP:20260417T123224
CREATED:20250413T134538Z
LAST-MODIFIED:20250413T134609Z
UID:26141-1743674400-1743679800@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Yuan Jun
DESCRIPTION:Name of Speaker\nYuan Jun\n\n\nSchedule\n3 April 2025\, 10am – 11.30am\n\n\nVenue \nE1A-06-21/22 ISEM Conference Room\n\n\nLink to Register\nhttps://nus-sg.zoom.us/j/86085218517?pwd=dsPDs32AiGCCrD8kYeSb0hgd1WbHj2.1\n\n\nTitle\nOptimal Planning of Electric Ship Charging Station Using Noisy-Expensive Constrained Bayesian Optimization\n\n\nAbstract\nShipping plays a critical role in global transportation and is also a significant contributor to global carbon emissions. As environmental concerns continue to grow\, the maritime industry faces increasing pressure to reduce its carbon footprint. In this context\, electric ships\, with their potential for low emissions and environmental sustainability\, have garnered considerable attention. However\, their application for long-distance transportation is currently limited by challenges such as battery capacity constraints and a lack of charging infrastructure. The strategic placement of charging stations is therefore essential for advancing the use of electric ships. This paper aims to design an on-shore electric ship charging station that integrates renewable energy sources—namely wind and photovoltaic power—with an energy storage system. Planning for these charging stations is complex due to the uncertainty of power generation from renewable sources and the fluctuating demand for charging services. Additionally\, the developed model is intricate\, time-consuming\, and subject to noisy and expensive constraints. To address these challenges\, this study proposes a Bayesian optimization method tailored to noisy and expensive constrained environments\, enabling efficient optimization of the complex simulation model. The findings of this research offer valuable insights for decision-making regarding the development of on-shore electric ship charging stations. Furthermore\, they provide a foundation for exploring business models that align with the growth of the electric shipping industry\, fostering mutually beneficial outcomes for all stakeholders involved.\n\n\nAbout the Speaker\nYuan Jun is an Associate Professor with China Institute of FTZ Supply chain\, Shanghai Maritime University. He received his B.E. degree in Industrial Engineering and Management from Shanghai Jiao Tong University in 2008\, and the Ph.D. degree in Industrial and Systems Engineering from National University of Singapore in 2013. From 2014-2017\, he worked as a Research Fellow at National University of Singapore. He got the Young Oriental Scholar in 2017. In the past five years\, he has published more than 20 SCI papers in Energy\, Applied Energy\, IISE Transactions\, TOMACS etc.\, held or participated in more than 15 scientific research projects funded by the National Natural Science Foundation of China\, the Shanghai Municipal Science and Technology Commission\, the U.S. Energy Fund etc. His research interests include energy systems modeling\, shipping energy systems\, integrated port energy systems\, computer simulation and optimization.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-yuan-jun/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250404T100000
DTEND;TZID=Asia/Singapore:20250404T113000
DTSTAMP:20260417T123224
CREATED:20250321T031337Z
LAST-MODIFIED:20250321T031337Z
UID:25936-1743760800-1743766200@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Paat Rusmevichientong
DESCRIPTION:Name of Speaker\nPaat Rusmevichientong\n\n\nSchedule\n4 April 2025\, 10am – 11.30am\n\n\nVenue \nBIZ1 03-02\n\n\nLink to Register\nhttps://nus-sg.zoom.us/meeting/register/Lapg-26pTU620yd5j7DDAw\n\n\nTitle\nAn Endogenous Multinomial Logit Model with Population-Based Purchase Feedback\n\n\nAbstract\nWe develop a choice model that incorporates feedback from a population of customers making a purchase within the assortment of offered products. Each customer posts feedback on the product that she purchases within an offered product assortment. The feedback is obtained by applying a feedback function to the utility that the customer derives from her purchased product. When another customer is to make a purchase within the assortment\, she uses the expected feedback from the customers with purchases to form a reference point. Therefore\, the utility of a product has three components: intrinsic deterministic utility\, Gumbel distributed idiosyncratic term and reference effect. The utility of a product is determined through a fixed point\, as the utility depends on the reference effect\, which\, in turn\, depends on the utilities of the products in the assortment. We give a closed-form expression for the choice probabilities for a broad class of feedback functions that can even have discontinuities. We develop an efficient algorithm to compute the revenue-maximizing assortment when the customers choose under our choice model. We study the pricing problem under our choice model\, giving structural properties of the optimal prices\, which ultimately yield an efficient algorithm for computing the revenue-maximizing prices. We also provide necessary and sufficient conditions for the convexity of the negative log-likelihood function. Our computational experiments demonstrate that our choice model can help predict the choices of the customers better than a number of benchmarks.\n\n\nAbout the Speaker\nPaat Rusmevichientong is the Justin Dart Professor of Operations Management and Professor of Data Sciences and Operations in the Marshall School of Business at the University of Southern California. Prior to joining the Marshall School\, he was a faculty in the School of Operations Research and Information Engineering at Cornell University. His research interests focus on revenue management\, choice modeling\, pricing\, assortment optimization\, and large-scale dynamic programming. From 2003 through 2004\, he worked in the data mining and personalization group at Amazon.com. He received BA (1997) in Mathematics from University of California\, Berkeley\, and MS (1999) and PhD (2003) in Operations Research from Stanford University. He is a member of INFORMS.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-paat-rusmevichientong/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250423T100000
DTEND;TZID=Asia/Singapore:20250423T113000
DTSTAMP:20260417T123224
CREATED:20250413T134048Z
LAST-MODIFIED:20250413T134048Z
UID:26138-1745402400-1745407800@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Bernhard von Stengel
DESCRIPTION:  \n\n\n\nName of Speaker\nBernhard von Stengel\n\n\nSchedule\n23 April 2025\, 10am – 11.30am\n\n\nVenue \nBIZ1 03-02\n\n\nLink to Register\nhttps://nus-sg.zoom.us/meeting/register/AWc8AlsiQo67S7-kKnLwmQ\n\n\nTitle\nFinding an Empirical Equilibrium by Machine Learning in a Pricing Game\n\n\nAbstract\nWe apply machine learning to a classical multi-period pricing game. The game is a duopoly with demand inertia\, introduced by Selten in 1965 and studied around 1990 with economic experiments. Its strategies are too complex to represent explicitly. Unlike standard multi-agent reinforcement learning of training agents against each other\, our framework is that of a Policy-Space Response Oracle (PSRO) and the “double oracle” method. A few initial strategies that play against each other define a “meta-game”. A Nash equilibrium of this meta-game is computed and defines the training environment for a learning agent. Once the agent is sufficiently trained to get a higher payoff than in the current equilibrium\, it is added as a new strategy to the meta-game\, which expands in this way\, and the process repeats. Various learning methods such as SAC (Soft Actor Critic) and PPO (Proximal Policy Optimisation) lead to different limit equilibria in this setup\, namely either competitive pricing or cooperative price collusion in the duopoly. \n(Joint work with Sahar Jahani and Rahul Savani)\n\n\nAbout the Speaker\nBernhard von Stengel is Professor of Mathematics at the London School of Economics which he joined in 1998\, after studies in Germany and the USA. He has been communications officer of the Game Theory Society\, and was program chair of the GAMES 2016 congress (held jointly with EC’2016) in Maastricht. He is interested in mathematical questions of game theory. The geometry and computation of Nash equilibria is one of his research specialities.\n\n\n\n 
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-bernhard-von-stengel/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250507T100000
DTEND;TZID=Asia/Singapore:20250507T113000
DTSTAMP:20260417T123224
CREATED:20250417T055739Z
LAST-MODIFIED:20250417T055739Z
UID:26146-1746612000-1746617400@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Erick Delage
DESCRIPTION:Name of Speaker\nErick Delage\n\n\nSchedule\n7 May 2025\, 10am – 11.30am\n\n\nVenue \nBIZ1 03-02\n\n\nLink to Register\nhttps://nus-sg.zoom.us/meeting/register/GTx5hsDMTAep_DVlLOLRAA\n\n\nTitle\nData-driven Conditional Robust Optimization\n\n\nAbstract\nConditional Robust Optimization (CRO) is a decision-making framework that blends the flexibility of robust optimization (RO) with the ability to incorporate additional information regarding the structure of uncertainty. This approach solves the RO problem where the uncertainty set structure adapts to account for the most recent information provided by a set of covariates. In this presentation\, we will introduce two data-driven approaches to CRO: a sequential predict-then-optimize method and an integrated end-to-end method. We will also show how hypothesis testing can be integrated to the training in order to improve the quality of conditional coverage of the produced uncertainty sets.\n\n\nAbout the Speaker\nErick Delage is a professor in the Department of Decision Sciences at HEC Montréal\, a chairholder of the Canada Research Chair in decision making under uncertainty\, and a member of the College of New Scholars\, Artists and Scientists of the Royal Society of Canada. His research interests span the areas of robust and stochastic optimization\, decision analysis\, reinforcement learning\, and risk management with applications to portfolio optimization\, inventory management\, energy\, and transportation problems.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-erick-delage/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250815T100000
DTEND;TZID=Asia/Singapore:20250815T113000
DTSTAMP:20260417T123224
CREATED:20250818T044156Z
LAST-MODIFIED:20250818T044156Z
UID:26974-1755252000-1755257400@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series : Daniel Russo
DESCRIPTION:Name of speaker\n\n\n\nDaniel Russo\n\n\n\n\n\nSchedule\n\n\n15 August 2025\, 10am – 11.30am\n\n\n\n\n\nVenue\n\n\n\nBIZ2 – 0413C\n\n\n\n\n\nLink to register\n\n\n\nhttps://nus-sg.zoom.us/meeting/register/rT3lbgWGQB-LnXjhOw84MA\n\n\n\n\n\nTitle\n\n\nActive Exploration via Autoregressive Generation of Missing Data\n\n\n\n\nAbstract\n\n\nWe cast the challenges of uncertainty quantification and exploration in online decision-making as a problem of training and generation from an autoregressive sequence model\, an area experiencing rapid innovation. Central to our approach is viewing uncertainty as arising from missing outcomes that would be revealed through appropriate action choices\, rather than from unobservable latent parameters of the environment. This reformulation aligns naturally with modern machine learning capabilities: we can i) train generative models through next-token prediction rather than fit explicit priors\, ii) assess uncertainty through autoregressive generation rather than parameter sampling\, and iii) adapt to new information through in-context learning rather than explicit posterior updating. To showcase these ideas\, we formulate a challenging informed bandit learning task where effective performance requires leveraging unstructured prior information (like text features) while exploring judiciously to resolve key remaining uncertainties. We validate our approach through both theory and experiments. Our theory establishes a reduction\, showing success at offline next-outcome prediction translates to reliable online uncertainty quantification and decision-making\, even with strategically collected data. Semi-synthetic experiments show our insights bear out in a news-article recommendation task where article text can be leveraged to minimize exploration.\n\n\n\n\n\nAbout the Speaker\n\n\nDaniel Russo is a Philip H. Geier Jr. Associate Professor in the Decision\, Risk\, and Operations division of the Columbia Business School. His research lies at the intersection of machine learning and online decision making\, mostly falling under the broad umbrella of reinforcement learning. Outside academia\, Dan works as an Amazon scholar applying reinforcement learning to supply chain optimization. He previously spent five years working with Spotify to apply reinforcement learning and large language models to audio recommendations.  Dan completed his undergraduate studies in Math and Economics at the University of Michigan\, doctoral studies at Stanford University under the supervision of Benjamin Van Roy\, and worked as a postdoctoral researcher at Microsoft Research in New England. His research has been recognized by the Erlang Prize\, the Frederick W. Lanchester Prize\, a Junior Faculty Interest Group Best Paper Award\, and first place in the George Nicholson Student Paper Competition.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-daniel-russo/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250822T100000
DTEND;TZID=Asia/Singapore:20250822T113000
DTSTAMP:20260417T123224
CREATED:20250818T043934Z
LAST-MODIFIED:20250821T021329Z
UID:26971-1755856800-1755862200@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series : Alminas Žaldokas
DESCRIPTION:Name of Speaker\n\n\n\nAlminas Žaldokas\n\n\n\n\n\nSchedule\n\n\n\n22 August 2025\, 10am – 11.30am\n\n\n\n\n\nVenue\n\n\n\nHSS 4 – 7 (Hon Sui Sen Memorial Library\, level 4 Seminar Room)\n\n\n\n\n\nLink to Register\n\n\n\nhttps://nus-sg.zoom.us/meeting/register/zUMnlP9MRy2HoqduBcxjmA\n\n\n\n\nTitle\n\n\nESG Shocks in Global Supply Chains\n\n\n\n\nAbstract\n\n\nWe show that U.S. firms cut imports by 31.8% when their international suppliers experience environmental and social (E&S) incidents. These trade cuts are larger for publicly listed U.S. importers facing high E&S investor pressure and lead to crosscountry supplier reallocation\, suggesting that E&S preferences in capital markets can be privately costly but have real effects for foreign suppliers. Larger trade cuts around the incident result in better supplier E&S performance in subsequent years\, and in the eventual resumption of trade. Our results highlight the role of investors in ensuring suppliers’ E&S compliance along global supply chains.\n\n\n\n\n\nAbout the Speaker\n\n\nAlminas Žaldokas is currently an Associate Professor in Finance at the National University of Singapore (NUS). Prior to this appointment\, Alminas Žaldokas has been teaching at the Hong Kong University of Science and Technology (HKUST) since 2012 with the primary focus on corporate finance and corporate valuation. Apart from the undergraduate and MSc courses\, he was teaching in the HKUST-NYU MSc in Global Finance\, HKUST bilingual EMBA\, and Kellogg-HKUST EMBA programmes. He has also previously taught corporate valuation for the MBAs at the University of Texas in Austin McCombs School of Business in 2017/8 academic year.\n\n\nProfessor Žaldokas received his PhD in Finance at INSEAD in 2012. His previous academic degrees include MSc in Finance and Economics from London School of Economics and BSc in Business and Economics from Stockholm School of Economics in Riga. \nProfessor Žaldokas’s research focuses on the interaction between firm decisions in the financial and in the product markets. In particular\, he studies corporate finance decisions that relate to the firm investment in innovation\, the formation of collusive arrangements between firms\, and the facilitation of ESG practices. This research has been published in top academic journals such as Journal of Financial Economics\, Review of Financial Studies\, Journal of Accounting Research\, Management Science\, RAND Journal of Economics\, Journal of International Economics\, and Journal of Financial Intermediation.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-alminas-zaldokas/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250829T100000
DTEND;TZID=Asia/Singapore:20250829T113000
DTSTAMP:20260417T123224
CREATED:20250821T021303Z
LAST-MODIFIED:20250821T021303Z
UID:26990-1756461600-1756467000@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Sean Zhou
DESCRIPTION:Name of Speaker\nSean Zhou\n\n\nSchedule\n29 August 2025\, 10am – 11.30am\n\n\nVenue \nHSS 4 – 7 (Hon Sui Sen Memorial Library\, level 4 Seminar Room)\n\n\nLink to Register \n \nhttps://nus-sg.zoom.us/meeting/register/HB2NQ5ZjRpuRwFiBsxDOxg\n\n\nTitle\nLearning and Pricing for Consumer Electronics Trade-in Program\n\n\nAbstract\nWe consider a dynamic pricing problem for a two-sided consumer electronics trade-in program\, where a firm acquires and re-sells multiple types of pre-owned (used) products over a finite selling horizon. There are customers trading in their used products for new products at discounted prices and customers buying refurbished products. The firm sets trade-in prices and resale prices to maximize its total expected profit. We first discuss the scenario that the firm knows the choice models of customers. Due to the high-dimensional state space\, deriving the optimal policy using dynamic programming is computationally intractable. To circumvent this\, we develop simple and provably effective heuristic policies based on the solution to a deterministic upper-bound problem. We design a dynamic policy called the Batched-Adjustment Control (BAC) policy\, under which the selling horizon is divided into different consecutive and disjoint batches for different products and the prices in one batch are updated based on the realized uncertainties in the previous batch. The profit loss of BAC relative to the optimal one is in the order of  . When the firm does not know the choice model parameters of customers\, it has to learn while making pricing decisions over time. We develop an algorithm called Parametric-Batched-Adjustment Control (PBAC)\, in which the firm first uses Maximum Likelihood Estimation to learn the trade-in and demand models’ parameters\, and then adopt a similar pricing policy akin to BAC while using the estimated parameters. With carefully chosen algorithm parameters (e.g.\, length of exploration phase\, batch size)\, we show that PBAC has a regret in the order of  . This is based on joint work with Zhuoluo Zhang (Xiamen University)\, Murray Lei (Queen’s University)\, and Wenhao Li (SUFE).\n\n\nAbout the Speaker\nSean Zhou is Professor and Chair of Department of Decisions\, Operations and Technology\, CUHK Business School\, and Professor in Department of Systems Engineering and Engineering Management (by courtesy)\, at The Chinese University of Hong Kong (CUHK). He has held visiting positions at National University of Singapore and University of Toronto. He received his Ph.D. in Operations Research from North Carolina State University. His main research interests are inventory management\, pricing\, sustainable operations\, data-driven supply chain optimization\, and operations and marketing interface. He serves as Area Editor (Inventory and Supply Chain Optimization) of OR Letters and Associate Editor of various journals including Naval Research Logistics and Service Science.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-sean-zhou/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250904T100000
DTEND;TZID=Asia/Singapore:20250904T113000
DTSTAMP:20260417T123224
CREATED:20250901T085532Z
LAST-MODIFIED:20250901T085532Z
UID:27043-1756980000-1756985400@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Nur Sunar
DESCRIPTION:Name of Speaker\n Nur Sunar\n\n\nSchedule\n 4 September 2025\, 10am – 11.30am\n\n\nVenue\n HSS 3 – 2 (Hon Sui Sen Memorial Library\, level 3 Seminar Room)\n\n\nLink to Register\nhttps://nus-sg.zoom.us/meeting/register/lZ34DiDOTh6rI4zJehKPIQ\n\n\nTitle\nDesigning Renewable Power Purchase Agreements: Impact on Green Energy Investment\n\n\nAbstract\nThis paper studies a long-term power purchase agreement (PPA) between a firm and a new renewable energy generator. The firm must dynamically satisfy uncertain electricity demand beyond its existing energy sources\, while wholesale electricity prices evolve stochastically over time. Upon signing a PPA\, a new renewable facility becomes operational\, and the firm owns its output for the contract duration. The new facility’s capacity is determined based on PPA terms. The firm dynamically chooses when to initiate the PPA and how much to pay to maximize its expected total discounted benefit. We show that the firm’s optimal timing follows a (time-dependent) threshold policy. Our results offer key insights for policymakers and renewable energy developers. We find that\, contrary to common wisdom\, reducing investment costs for renewable technologies can lead to smaller renewable capacity\, output\, and emissions savings when projects are developed under PPAs. This finding calls for caution in applying investment tax credits in such contexts. We also show that total renewable energy generation and emissions savings may decrease with higher site productivity. Therefore\, restricting renewable facility development to most productive sites might be counterproductive under PPAs. We establish the robustness of our findings across a broad range of practical scenarios. \n(joint work with Zuguang Gao and John R. Birge)\n\n\nAbout the Speaker\nNur Sunar is an Associate Professor of Operations and Sarah Graham Kenan Scholar at the Kenan-Flagler Business School of the UNC at Chapel Hill. She received her Ph.D. from Stanford Graduate School of Business with a thesis titled “Management Problems in Energy and Sustainability.” Her current research interest is to study innovative business models\, technologies\, and policies\, with a focus on sustainability\, energy\, and digital platforms. A key theme of her recent research is doing good with management science. \nDr. Sunar is particularly interested in innovative business models and novel challenges related to renewable energy technologies (e.g.\, rooftop solar panels\, large-scale renewable energy technologies\, online solar marketplaces)\, sustainability practices of companies/organizations (e.g.\, voluntary carbon offsetting) and smart city technologies (e.g.\, the Internet of Things\, smart meters\, electric vehicles\, and residential batteries). She is also passionate about innovative business solutions for inclusive health. \nFor more information\, please see https://sites.google.com/view/nur-sunar/home
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-nur-sunar/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250905T100000
DTEND;TZID=Asia/Singapore:20250905T113000
DTSTAMP:20260417T123224
CREATED:20250901T085409Z
LAST-MODIFIED:20250901T085409Z
UID:27041-1757066400-1757071800@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Victor Martínez de Albéniz
DESCRIPTION:Name of Speaker\nVictor Martínez de Albéniz\n\n\nSchedule\n5 September 2025\, 10am – 11.30am\n\n\nVenue \nHSS 4 – 7 (Hon Sui Sen Memorial Library\, level 4 Seminar Room)\n\n\nLink to Register \n \nhttps://nus-sg.zoom.us/meeting/register/kZSaUc7SR_GuEKdg2LC_SA\n\n\nTitle\nDigital Nudges at the Van Gogh Museum Increase Engagement\, Pace Visitors\, and Reduce Congestion\n\n\nAbstract\nDigital nudges have the potential to enrich experiential services\, but little is known about how they affect behaviors in the field. From 2022 to 2024\, we run field experiments at the Van Gogh Museum\, testing the effect of interventions on the multimedia tour on visitor content consumption and movements. We find that providing that providing a highlight selection with a simple information architecture can increase consumption\, coverage of the collection\, without requiring more visit duration\, thereby containing museum fatigue. Furthermore\, faster visitor flows reduce congestion\, creating a positive externality on others. Thus\, well-designed digital nudges can produce more effective visits\, that improve both consumer and service provider outcomes.\n\n\nAbout the Speaker\nVictor Martínez de Albéniz is a Full Professor in the Operations\, Information and Technology Department at IESE Business School. He joined IESE in 2004 after earning a PhD from the Operations Research Center at the Massachusetts Institute of Technology (MIT) and an engineering degree from École Polytechnique in France. \nHis research spans a broad spectrum of Operations Management. He began his career working on supply chain management\, optimizing inventory and purchasing systems to combine low costs with flexibility and innovation. He then moved into the retail sector\, developing fashion trend forecasts\, leveraging big data to respond to demand shocks\, and optimizing the in-store customer experience. More recently\, he has applied his expertise to improving education systems. \nFor more information\, please see https://blog.iese.edu/martinezdealbeniz/
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-victor-martinez-de-albeniz/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250917T100000
DTEND;TZID=Asia/Singapore:20250917T113000
DTSTAMP:20260417T123224
CREATED:20250908T023547Z
LAST-MODIFIED:20250908T023547Z
UID:27074-1758103200-1758108600@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Chen Ningyuan
DESCRIPTION:Name of Speaker\n\n\n\nChen Ningyuan\n\n\n\n\n\nSchedule\n\n\n\n17 September 2025\, 10am – 11.30am\n\n\n\n\n\nVenue\n\n\n\nBIZ1 – 0202\n\n\n\n\n\nLink to Register\n(Via Zoom)\n\n\nhttps://nus-sg.zoom.us/meeting/register/n1RflnWjRwyd5RSu7W6rag\n\n\n\n\nTitle\n\n\nPost-Estimation Adjustments in Data-Driven Decision-Making with Applications in Pricing\n\n\n\n\nAbstract\n\n\nThe predict-then-optimize (PTO) framework is a standard approach in data-driven decision-making\, where a decision-maker first estimates an unknown parameter from historical data and then uses this estimate to solve an optimization problem. While widely used for its simplicity and modularity\, PTO can lead to suboptimal decisions because the estimation step does not account for the structure of the downstream optimization problem. We study a class of problems where the objective function\, evaluated at the PTO decision\, is asymmetric with respect to estimation errors. This asymmetry causes the expected outcome to be systematically degraded by noise in the parameter estimate\, as the penalty for underestimation differs from that of overestimation. To address this\, we develop a data-driven post-estimation adjustment that improves decision quality while preserving the practicality and modularity of PTO. We show that when the objective function satisfies a particular curvature condition\, based on the ratio of its third and second derivatives\, the adjustment simplifies to a closed-form expression. This condition holds for a broad range of pricing problems\, including those with linear\, log-linear\, and power-law demand models. Under this condition\, we establish theoretical guarantees that our adjustment uniformly and asymptotically outperforms standard PTO\, and we precisely characterize the resulting improvement. Additionally\, we extend our framework to multi-parameter optimization settings. Numerical pricing experiments demonstrate that our method consistently improves revenue\, particularly in small-sample regimes where estimation uncertainty is most pronounced. This makes our approach especially well-suited for pricing new products or in settings with limited historical price variation.\n\n\n\n\nAbout the Speaker\n\n\nDr. Ningyuan Chen is currently an associate professor at the Department of Management at the University of Toronto\, Mississauga and at the Rotman School of Management\, University of Toronto. Before joining the University of Toronto\, he was an assistant professor at the Hong Kong University of Science and Technology. Prior to that\, he was a postdoctoral fellow at the Yale School of Management. He received his Ph.D. from the Industrial Engineering and Operations Research (IEOR) department at Columbia University in 2015. His studies have been published in Management Science\, Operations Research\, Annals of Statistics\, NeurIPS and other journals and proceedings. His research is supported by the UGC of Hong Kong and the Discovery Grants Program of Canada. He is the recipient of the Roger Martin Award for Excellence in Research and the IMI Research Award.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-chen-ningyuan/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20251106T100000
DTEND;TZID=Asia/Singapore:20251106T113000
DTSTAMP:20260417T123224
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:20260417T123224
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:20260417T123224
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
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BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20260206T100000
DTEND;TZID=Asia/Singapore:20260206T113000
DTSTAMP:20260417T123224
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:20260417T123224
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:20260417T123224
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:20260417T123224
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:20260417T123224
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:20260417T123224
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:20260417T123224
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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