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TZID:Asia/Singapore
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DTSTART:20230101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20240216T100000
DTEND;TZID=Asia/Singapore:20240216T113000
DTSTAMP:20260419T035059
CREATED:20240206T143510Z
LAST-MODIFIED:20240206T143549Z
UID:19647-1708077600-1708083000@iora.nus.edu.sg
SUMMARY:DAO-IORA Seminar Series - Kai Hoberg
DESCRIPTION:  \n\n\n\n\nName of Speaker\nKai Hoberg\n\n\nSchedule\n16 February 2024\, 10am – 11.30am\n\n\nVenue\nI4-01-03 Seminar Room\n\n\nLink to Register\nhttps://nus-sg.zoom.us/meeting/register/tZYuceusrjouE9P7Pu7BAYbWh7quOmNJ-xcw\n\n\nTitle\nUsing (inaccurate) data to drive better supply chain decision making\n\n\nAbstract\nMore and more data is available to improve supply chain decision making but it needs to be carefully applied considering human limitations. Against this background\, I will present two studies that focus on the role of human judgment in supply chain management decision making\, first exploring the influence of planners’ adjustments to AI-generated demand forecasts and second examining the effectiveness of human decision-making in inventory management subject to inaccurate data. Study 1 investigates the role of human judgment in demand forecasting. We analyze planners’ adjustments to AI-generated forecasts using a dataset containing 30 million SKU-store-day level forecasts and associated variables. We employ random forest and decision tree approaches to understand the drivers and quality of adjustments. Our findings suggest product characteristics such as price\, freshness\, and discounts are important factors in adjustments. Large positive adjustments are frequent but often inaccurate\, while large negative adjustments are accurate but less common which indicates behavioral biases. In Study 2\, we focus on decisions made under the inaccurate inventory data due to shrinkage and loss. We explore the trade-off between cleaning inventory data centrally and allowing decision makers to adjust ordering decisions based on their judgment. In light of human biases in decision making\, we present a set of hypotheses on the cleaning-adjustment trade-off and test them in a laboratory setting. The study raises questions about the effectiveness of normative models in determining whether to clean data centrally or rely on decision makers’ judgments\, providing insights into optimizing human knowledge utilization in supply chain management.\n\n\nAbout the Speaker\nKai Hoberg is Professor of Supply Chain and Operations Strategy at the Kühne Logistics University in Hamburg. His research focuses on supply chain analytics\, the role of technology in supply chains\, and supply chain strategy. His research findings have been published in academic journals like Journal of Operations Management\, Production and Operations Management or Journal of Supply Chain Management. Kai was a visiting researcher at international universities such as the National University of Singapore\, Cornell University\, the Israel Institute of Technology and the University of Oxford.  Prior to his return to academia\, he was a project manager in the operations team at Booz & Company. For the past 10 years he has supported the McKinsey Supply Chain practice in teaching and research.  His team at KLU is closely working industry partners such as Bayer\, Procter & Gamble\, Jungheinrich or Infineon.
URL:https://iora.nus.edu.sg/events/dao-iora-seminar-series-kai-hoberg/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20240226T100000
DTEND;TZID=Asia/Singapore:20240226T113000
DTSTAMP:20260419T035059
CREATED:20240221T025022Z
LAST-MODIFIED:20240221T025048Z
UID:20140-1708941600-1708947000@iora.nus.edu.sg
SUMMARY:DAO-IORA Seminar Series - Mohamed Mostagir
DESCRIPTION:Name of Speaker\nMohamed Mostagir\n\n\nSchedule\n26 February 2024\, 10am – 11.30am\n\n\nVenue \nBIZ1- 0203\n\n\nLink to Register\nhttps://nus-sg.zoom.us/meeting/register/tZUrc–gqj4uE9WGbEbpRoBVA4DGCZes88wN\n\n\nTitle\nA Theory of Ghosting\n\n\nAbstract\nGhosting is a phenomenon where communication between two parties abruptly stops after one side becomes deliberately unresponsive. This occurs in a variety of settings\, but the term entered the mainstream after its usage to describe an important aspect of the dating experience that has been sparsely studied. Both online dating platforms and their users report that ghosting is one of the primary drivers hurting user experience and preventing good outcomes. We develop a model of ghosting and study the efficacy of different policies that platforms have implemented to deal with this problem.\n\n\nAbout the Speaker\nMohamed Mostagir is an associate professor of Technology and Operations at the University of Michigan Ross School of Business. He is interested in social learning and belief formation and their applications in a wide variety of settings.
URL:https://iora.nus.edu.sg/events/dao-iora-seminar-series-mohamed-mostagir/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20240308T100000
DTEND;TZID=Asia/Singapore:20240308T113000
DTSTAMP:20260419T035059
CREATED:20240304T031806Z
LAST-MODIFIED:20240304T031806Z
UID:20807-1709892000-1709897400@iora.nus.edu.sg
SUMMARY:DAO-IORA Seminar Series - Kimon Drakopoulos
DESCRIPTION:Name of Speaker\nKimon Drakopoulos\n\n\nSchedule\n8 March 2024\, 10am – 11.30am\n\n\nVenue \nBIZ1- 0206\n\n\nLink to Register\nhttps://nus-sg.zoom.us/meeting/register/tZ0scuyqrT4vGtDnHl1AToXlPUExri0y7Suq\n\n\nTitle\nBlockchain Mediated Persuasion\n\n\nAbstract\nAn ex-post informed Sender wishes to persuade a rational Bayesian Receiver to take a desired action\, as in the classic Bayesian Persuasion model studied by Kamenica and Gentzkow (2011). However\, we consider settings in which Sender cannot reliably commit to a signal mechanism. An alternative approach is to consider a trustworthy mediator that receives a reported state of the world from Sender and then\, based on this report\, generates a signal realization for Receiver. Such mediation can be implemented via costly blockchain technology. Surprisingly\, we show that this cost differentiated mediation succeeds where free mediation fails. By requiring Sender to pay the mediator for different signal realizations\, we can effectively incentivize them to truthfully report\, which in turn allows for beneficial persuasion to take place. Joint with Justin Mulvany\, Irene Lo\n\n\nAbout the Speaker\nKimon Drakopoulos is an Associate Professor in Business Administration at the Data Sciences and Operations department at the USC Marshall School of Business. His research focuses on the operations of complex networked systems\, social networks\, stochastic modeling\, game theory and information economics. Kimon is currently serving in the high level advisory committee to the Greek government on AI regulation and implementation. In 2020 he served as the Chief Data Scientist of the Greek National COVID-19 Scientific taskforce and a Data Science and Operations Advisor to the Greek Prime Minister. He has been awarded the Wagner Prize for Excellence in Applied Analytics and the Pierskalla Award for contributions to Healthcare Analytics.
URL:https://iora.nus.edu.sg/events/dao-iora-seminar-series-kimon-drakopoulos/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20240311T100000
DTEND;TZID=Asia/Singapore:20240311T113000
DTSTAMP:20260419T035059
CREATED:20240304T032033Z
LAST-MODIFIED:20240304T032033Z
UID:20810-1710151200-1710156600@iora.nus.edu.sg
SUMMARY:DAO-IORA Seminar Series - Arnoud den Boer
DESCRIPTION:Name of Speaker\nArnoud den Boer\n\n\nSchedule\n11 March 2024\, 10am – 11.30am\n\n\nVenue \nBIZ1- 0304\n\n\nLink to Register \n \nhttps://nus-sg.zoom.us/meeting/register/tZcrdeytpjgsGtEen4nnptCLRFl85dvfKFvR\n\n\nTitle\nCan price algorithms learn to form a cartel?\n\n\nAbstract\nCan price algorithms learn to form a cartel instead of compete against each other\, potentially leading to higher consumer prices and lower social welfare? The question is controversial among economists and competition policy regulators. One the one hand\, concerns have been expressed that self-learning price algorithms do not only make it easier to form price cartels\, but also that this can be achieved within the boundaries of current antitrust legislation – raising the question whether the existing competition law needs to be adjusted to mitigate undesired algorithmic collusion. On the other hand\, a number of economists believe that algorithms learning to collude is science fiction\, except by using forms of signaling or communication that are already illegal\, and argue that there is no need to change antitrust laws. Motivated by this discussion\, I will present work that shows that under some market conditions\, price algorithms can learn to collude. Based on joint work with Janusz Meylahn\, Thomas Loots\, Maarten Pieter Schinkel\, Ali Aouad.\n\n\nAbout the Speaker\nArnoud is Associate Professor at the Korteweg-de Vries Institute for Mathematics of the University of Amsterdam. He studied Mathematics at Utrecht University (2006)\, Mathematics for Industry at Eindhoven University of Technology (2008) and wrote his PhD thesis `Dynamic Pricing and Learning’ (2013) about data-driven price algorithms at the CWI Centrum for Wiskunde and Computer Science in Amsterdam. Arnoud’s research focuses on the interface of learning and optimization\, with applications in dynamic pricing and revenue management. He is the recipient of several awards and grants\, including the 2015 Gijs de Leve prize for best PhD Thesis in operations research defended in the Netherlands in the period 2012-2014\, personal grants from the Dutch Science Foundation\, and the INFORMS Revenue Management & Pricing Section Prize. Arnoud serves as editor for Management Science\, M&SOM\, and POMS\, is board member of the Euro Working Group on Pricing and Revenue Management and board member of the INFORMS Revenue Management and Pricing Section.
URL:https://iora.nus.edu.sg/events/dao-iora-seminar-series-arnoud-den-boer/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20240313T100000
DTEND;TZID=Asia/Singapore:20240313T113000
DTSTAMP:20260419T035059
CREATED:20240307T031244Z
LAST-MODIFIED:20240307T031244Z
UID:20941-1710324000-1710329400@iora.nus.edu.sg
SUMMARY:DAO-IORA Seminar Series - Zhang Fuqiang
DESCRIPTION:  \n\n\n\nName of Speaker\nZhang Fuqiang\n\n\nSchedule\n13 March 2024\, 10am – 11.30am\n\n\nVenue \nBIZ1-0307\n\n\nLink to Register \n \nhttps://nus-sg.zoom.us/meeting/register/tZUvdu2grDItHdZl1LhIH4lgx0-lY42S7eks\n\n\nTitle\nThe Bright Side of Price Volatility in Global Commodity Procurement\n\n\nAbstract\nThis paper studies two competing firms’ choices between the contingent-price contract (CPC) and fixed-price contract (FPC) in global commodity procurement. The FPC price is determined when signing the contract\, whereas the CPC price is pegged to an underlying index and remains open until the delivery date. Under both contracts\, each firm determines its order quantity based on the updated belief about the market demand. The unrealized CPC price correlates with the market demand\, allowing a firm to update its belief about the CPC price using demand information\, thereby generating a price-learning effect. We find that\, contrary to conventional wisdom\, a larger price volatility could benefit the firms\, and\, under differentiated contracts\, a firm might benefit from the improvement of forecast accuracy at its rival. We further show that the price-learning effect plays a critical role in the firms’ contract choices. First\, significant price volatility forces the firms to pursue the responsiveness of the CPC. Second\, the firms may adopt differentiated contracts to enhance their responses to market changes and dampen competition\, and a higher competition intensity more likely leads to contract differentiation. Third\, the firms in a small market seek responsiveness and contract differentiation rather than cost efficiency. This study reveals the bright side of price volatility and takes a step toward understanding the effect of two-dimensional information updating.\n\n\nAbout the Speaker\nFuqiang Zhang is the Dan Broida professor of Supply Chain\, Operations\, and Technology (SCOT) at Olin Business School\, Washington University in St. Louis. He also serves as the SCOT area chair and academic director of MBA programs at Olin. Professor Zhang obtained his Ph.D. in Managerial Science and Applied Economics from the Wharton School\, University of Pennsylvania. His research interests focus on supply chain and technology innovation\, consumer analytics in operations management\, and sustainable operations. In recent years\, he has been working on research topics that are driven by empirical data. Professor Zhang’s research has appeared in top-tier academic journals such as Management Science\, Manufacturing & Service Operations Management\, Operations Research\, Marketing Science\, and Production and Operations Management.\n\n\n\n 
URL:https://iora.nus.edu.sg/events/dao-iora-seminar-series-zhang-fuqiang/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20240319T100000
DTEND;TZID=Asia/Singapore:20240319T113000
DTSTAMP:20260419T035059
CREATED:20240311T030605Z
LAST-MODIFIED:20240311T030605Z
UID:21418-1710842400-1710847800@iora.nus.edu.sg
SUMMARY:DAO-IORA Seminar Series - Zhu Weiming
DESCRIPTION:  \n\n\n\n\nName of Speaker\nZhu Weiming\n\n\nSchedule\n19 March 2024\, 10am – 11.30am\n\n\nVenue\nBIZ1-0206\n\n\nLink to Register\nhttps://nus-sg.zoom.us/meeting/register/tZcvdu-rpzkuHNTHWtUz_oEaagwlXP1_FVHp\n\n\nTitle\nExtracting Efficiency from Chaos: Rider Behavior\, Performance and Negative Externality in Dockless Bike Sharing Systems\n\n\nAbstract\nIn recent years\, urban bike-sharing systems developed in two main forms: Dock-based systems that rely on fixed location docks to park at and pick up bicycles from\, and Dockless systems which allow users to pick up and drop off bikes anywhere. By eliminating reliance on fixed docks\, dockless systems provide significantly improved mobility and convenience to riders\, yet they have downsides such as high operational costs and occupying valuable sidewalk space. Collaborating with a major dockless bike-sharing platform\, we empirically analyze riders’ economic incentives\, explore the efficiency and measure the negative externality of this business model. Specifically\, we address the following questions: (i) What is the impact of the number of bicycles in the system on efficiency? (ii) How does the efficiency of dockless and dock-based systems compare? (iii) How can bike-share company minimize the negative externalities generated during service provision through smart relocation?\n\n\nAbout the Speaker\nWeiming Zhu is an Associate Professor in Innovation and Information Management at HKU Business School. Weiming obtained his bachelor’s degree in Physics from HKUST and Ph.D. in Operations Management from the Robert H. Smith School of Business at University of Maryland. Prior to joining the University of Hong Kong\, he was an Associate Professor in IESE’s Department of Production\, Technology and Operations Management. Weiming has also been a visiting professor in the Institute for Data\, Systems\, and Society (IDSS) at Massachusetts Institute of Technology and Kellogg School of Management at Northwestern University. Weiming’s research interests include operations in the platform economy\, urban mobility\, and supply chain finance. His work has been published at Management Science\, M&SOM and Journal of International Economics\, and has been recognized in M&SOM\, POMS\, Service Science and CSAMSE best paper award competitions.\n\n\n\n\n 
URL:https://iora.nus.edu.sg/events/dao-iora-seminar-series-zhu-weiming/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20240322T100000
DTEND;TZID=Asia/Singapore:20240322T113000
DTSTAMP:20260419T035059
CREATED:20240315T084423Z
LAST-MODIFIED:20240315T084423Z
UID:21570-1711101600-1711107000@iora.nus.edu.sg
SUMMARY:DAO-IORA Seminar Series - Sasa Zorc
DESCRIPTION:  \n\n\n\n\nName of Speaker\nSasa Zorc\n\n\nSchedule\n22 March 2024\, 10am – 11.30am\n\n\nVenue\nBIZ1-0206\n\n\nLink to Register \n \nhttps://nus-sg.zoom.us/meeting/register/tZIpce2srDwrHdyCUf-w1Rtdh_3c-YlU9nTz\n\n\nTitle\nSearch with Recall and Gaussian Learning\n\n\nAbstract\nThe classic sequential search problem rewards the decision maker with the highest sampled value\, minus a cost per sample. If the sampling distribution is unknown\, then a Bayesian decision maker faces a complex balance between exploration and exploitation. We solve the stopping problem of sampling from a Normal distribution with unknown mean and unknown variance and a conjugate prior\, a longstanding open problem. The optimal stopping region may be empty (it may be optimal to continue the search regardless of the offer one receives\, especially at the early stages)\, or it may consist of one or two bounded intervals. While a single reservation price cannot describe the optimal rule\, we do find a standardized reservation rule: stop if and only if the standardized value of the current offer is sufficiently high relative to the standardized search cost. We also introduce the index function\, which provides a computationally practical way to implement the standardized stopping rule for any given prior\, sampling history\, and sampling horizon.\n\n\nAbout the Speaker\nSasa Zorc is an assistant professor at the Darden School of Business\, University of Virginia. Sasa obtained his PhD in Management from INSEAD. He studies incentives in multi-agent systems such as health care and matching markets (both centralized and decentralized). Methodologically\, his research relies on stochastic dynamic games\, search theory\, dynamic mechanism design\, contract theory and data-driven simulations.
URL:https://iora.nus.edu.sg/events/dao-iora-seminar-series-sasa-zorc/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20240405T100000
DTEND;TZID=Asia/Singapore:20240405T110000
DTSTAMP:20260419T035059
CREATED:20240401T015600Z
LAST-MODIFIED:20240401T015649Z
UID:22117-1712311200-1712314800@iora.nus.edu.sg
SUMMARY:DAO-IORA Seminar Series - Wang Guihua
DESCRIPTION:  \n\n\n\nName of Speaker\nWang Guihua\n\n\nSchedule\n5 April 2024\, 10am – 11am\n\n\nLink to Register\nhttps://nus-sg.zoom.us/meeting/register/tZ0ucOmorj8sEtZEDn8rf411mXUZJEvpgeaO\n\n\nTitle\nThe Spillover Effect of Suspending Non-essential Surgery: Evidence from Kidney Transplantation\n\n\nAbstract\nOrgan transplantation is a life-saving procedure for patients with end-stage organ disease; delaying transplantation can have life-or-death consequences. Between March and April 2020\, in the midst of the COVID-19 pandemic\, multiple state governors issued orders to temporarily suspend non-essential surgery. Although such suspensions were not intended for essential surgery (e.g.\, deceased-donor kidney transplants)\, the literature on service operations management suggests that these suspensions may have either a positive or a negative spillover effect on essential surgery\, depending on whether hospitals maintain or reduce resources in response to such suspensions. Motivated by this dichotomy\, we estimate the potential spillover effect of suspending nonessential surgery on deceased-donor kidney transplantation. Through analyzing a dataset of all U.S. kidney transplant procedures\, we observe a steep decline in the transplant volume in almost all states during the early months of the pandemic. However\, states that suspended nonessential surgery experienced steeper declines than those that did not. Using a difference-in-differences approach\, we estimate a state-level suspension of non-essential surgery led to a 23.6% reduction in transplant volume. This negative spillover effect is particularly pronounced for low-efficiency transplant centers with long cold ischemia times (CITs)\, but less so for high-efficiency centers. Our mediation analysis shows 38.7% of the spillover effect can be attributed to the change in healthcare employment. Our study suggests that in the event of a future public health crisis\, policymakers should consider more nuanced approaches to securing the healthcare workforce critical to supporting essential services\, especially for transplant centers with long CITs.\n\n\nAbout the Speaker\nGuihua is an Assistant Professor of Operations Management and a Sydney Smith Hicks Faculty Fellow at the Naveen Jindal School of Management\, The University of Texas at Dallas. He obtained his PhD from the University of Michigan\, MSc from the Georgia Institute of Technology\, MSc and BEng from the National University of Singapore. Prior to his PhD study\, Guihua worked as a supervisor of the industrial engineering department at UPS Asia headquartered in Singapore.  Guihua’s research focuses on the intersection of empirical econometrics and machine learning with application to personalized healthcare. More specifically\, Guihua has developed new empirical machine learning techniques such as instrumental variable forest and first-difference causal tree for heterogeneous treatment effect analysis using observational healthcare data. Guihua’s research has been published at Management Science\, Manufacturing & Service Operations Management\, Production and Operations Management\, Advances in Applied Probability\, Surgery\, and Annals of Thoracic Surgery\, and received media coverage by Associate Press\, Crain’s Detroit\, Houston Chronicle\, Medical Xpress\, National Interest\, NPR\, PRI\, Science Daily\, Simply Flying\, The Conversation\, and Yahoo! News. His research was named a finalist of both the Pierskalla Best Paper Award and the MSOM Service Management SIG Best Paper Award\, a runner-up of both the Financial Times Responsible Business Education Award and the INFORMS Service Science Best Cluster Paper Award\, the winner of the INFORMS Health Applications Society Student Paper Competition\, two-time finalists of the MSOM Student Paper Competition\, and a finalist of the INFORMS Service Section Best Student Paper Competition.\n\n\n\n 
URL:https://iora.nus.edu.sg/events/dao-iora-seminar-series-wang-guihua/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20240412T100000
DTEND;TZID=Asia/Singapore:20240412T113000
DTSTAMP:20260419T035059
CREATED:20240403T063341Z
LAST-MODIFIED:20240403T063341Z
UID:22241-1712916000-1712921400@iora.nus.edu.sg
SUMMARY:DAO-IORA Seminar Series - Michael Freeman
DESCRIPTION:Name of Speaker\nMichael Freeman\n\n\nSchedule\n12 April 2024\, 10am – 11.30am\n\n\nVenue \nHon Sui Sen Memorial Library HSS 3-1\n\n\nLink to Register\nhttps://nus-sg.zoom.us/meeting/register/tZIofu-hqTosGdL3UD4H6gyub6ROFYIUrSpf\n\n\nTitle\nFrom full-time to flexi: Investigating the impact of workforce shifts in primary care on service provision and quality\n\n\nAbstract\nPrimary care practices worldwide are experiencing a shift away from traditional full-time roles toward increased part-time and temporary staffing models. This transformation necessitates understanding the implications for primary healthcare delivery. Our paper provides an empirical analysis examining the evolving work patterns and schedules of general practitioners (GPs) in the UK over the past decade. Using primary care records\, we first examine how GP work volume impacts healthcare service utilization and patient outcomes. We also explore factors that may mediate this relationship. Going further\, given the seeming inevitability of more flexible staffing models\, our investigation also aims to inform effective workforce strategies that optimise healthcare delivery. Specifically\, we examine scheduling approaches that may allow primary care practices to adapt to part-time and locum GPs. Our findings aim to inform healthcare leaders seeking to adapt to emerging flexible staffing models while maintaining high-quality and accessible primary care.\n\n\nAbout the Speaker\nMichael Freeman is an Assistant Professor of Technology and Operations Management at INSEAD. His research focuses on healthcare operations\, leveraging large empirical datasets and rigorous analysis to uncover actionable insights that inform practices to enhance healthcare delivery. This work centers on two key themes – improving patient routing and care continuity and assessing the impacts of organisational changes and predictive technologies on healthcare productivity and quality. He has published several papers in Management Science and M&SOM\, and his research has also been recognized with various awards\, including winning the 2016 MSOM Student Paper Competition. His research has also earned attention from media outlets (BBC\, The Guardian\, and others) and healthcare leaders\, including the UK’s Royal College of Emergency Medicine and College of General Practitioners. Alongside research\, Michael is an award-winning teacher at INSEAD\, where he directs and teaches in executive education\, the EMBA\, MBA\, and PhD programmes.
URL:https://iora.nus.edu.sg/events/dao-iora-seminar-series-michael-freeman/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20240531T100000
DTEND;TZID=Asia/Singapore:20240531T113000
DTSTAMP:20260419T035059
CREATED:20240517T034742Z
LAST-MODIFIED:20240517T034742Z
UID:22703-1717149600-1717155000@iora.nus.edu.sg
SUMMARY:DAO-IORA Seminar Series - Tauhid Zaman
DESCRIPTION:  \n\n\n\nName of Speaker\nTauhid Zaman\n\n\nSchedule\n31 May 2024\, 10am – 11.30am\n\n\nVenue \nBIZ1- 0307\n\n\nLink to Register\nhttps://nus-sg.zoom.us/meeting/register/tZMlduChqDoiGNbvqS_7q_XH-E66BMzMMYIl\n\n\nTitle\nSocial Media Suspensions and Shadow Banning: Political Bias or Genuine Disinformation Control?\n\n\nAbstract\nSocial media platforms like Twitter and TikTok wield significant influence over the visibility and reach of content\, raising critical questions: Are certain voices marginalized based on political leanings\, or are platform interventions primarily aimed at mitigating the spread of disinformation? Recent discussions highlight allegations of political bias in account suspensions and “shadow banning\,” a subtle mechanism where certain content is less visible to users\, often without their knowledge. \nDrawing from a field study on Twitter\, we investigate these claims. Our findings suggest that while some account suspensions may appear biased\, there is equally strong evidence indicating that these actions are strategic efforts to combat the spread of disinformation. \nWe then delve into the issue of shadow banning\, demonstrating how this mechanism can be used to shape opinions into arbitrary distributions by solving a linear program. Through simulations on real social network topologies\, we show that if shadow banning were driven by partisanship\, its implementation could be so subtle that overt political biases remain undetected. This underscores the imperative for rigorous transparency and oversight in the actions of social media platforms. \nThis talk is based on the following papers: \n\n Analysis: Trade-offs between reducing misinformation and politically-balanced enforcement on social media: https://osf.io/preprints/psyarxiv/ay9q5\n Shaping Opinions in Social Networks with Shadow Banning: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0299977\n\n\n\n\nAbout the Speaker\nTauhid is an Associate Professor of Operations Management at the Yale School of Management. He received his BS\, MEng\, and PhD degrees in electrical engineering and computer science from MIT.  His research focuses on information operations problems in the context of social media.  Some of the topics he has studied include combating online extremists\, identifying bots\, and designing influence campaigns.  His broader interests cover data driven approaches to investing in startup companies\, algorithmic sports betting\, and biometric data.  His work has been featured in the Wall Street Journal\, Wired\, Mashable\, the LA Times\, Bloomberg\, and Time Magazine. \nWebsite: https://www.zlisto.com/\n\n\n\n 
URL:https://iora.nus.edu.sg/events/dao-iora-seminar-series-tauhid-zaman/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20240823T100000
DTEND;TZID=Asia/Singapore:20240823T113000
DTSTAMP:20260419T035059
CREATED:20240817T125552Z
LAST-MODIFIED:20240817T125552Z
UID:23044-1724407200-1724412600@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series - Daewon Sun
DESCRIPTION:Name of Speaker\nDaewon Sun\n\n\nSchedule\n23 August 2024\, 10am – 11.30am\n\n\nVenue \nBIZ1- 0305\n\n\nLink to Register \n \nhttps://nus-sg.zoom.us/meeting/register/tZckdu-tqzsiGdVFbEmxw3iRRCw-MKTKz2pe\n\n\nTitle\nCo-Developing Technology Products by Asymmetric Competitors\n\n\nAbstract\nTechnology products often have vital components owned or patented by different firms\, each of whom also seeks to compete in the end-user market. Consequently\, firms engage in a hybrid of collaboration and competition\, where one firm might provide a crucial component or capability to another that sells a competing end-market product. For instance\, Samsung sells smartphones and supplies organic light-emitting diode displays for Apple’s smartphones. The component buyer firm (i.e.\, firm A) may consider co-investing to improve the quality of a shared component (made by firm B). But how do firms gain strategic benefits in such arrangements? What factors govern their investment level? Who benefits\, and who loses? This paper addresses these questions. We find that $B$’s own investment is motivated more by increased partnership profit than by higher profit in the end-user market because competition limits the gains from a better product. Indeed\, when A has sufficient end-product superiority\, B exits the end-user market and becomes more aggressive in improving the quality of the shared capability. A strategic reason for A to co-invest in the shared capability is the desire for a higher performance level than that chosen by B (on its own) which self-throttles its own investment because it cannot fully monetize the gains in a competitive market. In doing so\, both A and B make higher-quality end-user products and earn higher profits. Still\, B gains more because it can extract part of A’s gains through an higher component unit price. Crucially\, firm A co-invests even though the investment prolongs firm B’s ability to maintain an end-user market presence in direct competition with A. Finally\, we demonstrate that B could limit its Stackelberg leadership power to further improve the joint investment in an asymmetric partner relationship\, which can yield a win-win outcome for both firms.\n\n\nAbout the Speaker\nDaewon Sun is a professor in Department of IT\, Analytics\, and Operations at Mendoza College of Business\, University of Notre Dame. He holds a Ph.D. in Management Science and Information Systems from the Pennsylvania State University. Professor Sun’s primary research interests are in pricing strategies and resource management\, including IT Product Pricing and Launching Strategies\, eBusiness Strategies\, Operations Management and Marketing Interfaces\, and Supply Chain Conflict and Coordination. Professor Sun’s published papers appear in top-tier journals and his research was recognized by several professional awards including 2013 AIS Best Information Systems Publications Award of the Year. He is a senior editor for Production and Operations Management and an associate editor for Decision Sciences journals. Professor Sun teaches information systems\, operations management\, and business analytics core courses\, including Systems Analysis and Design\, IS Capstone Project\, Introduction to Process Analytics\, Business Intelligence\, and predictive analytics.\n\n\n\n 
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-daewon-sun/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240828
DTEND;VALUE=DATE:20240830
DTSTAMP:20260419T035059
CREATED:20240808T022259Z
LAST-MODIFIED:20240808T023501Z
UID:22986-1724803200-1724975999@iora.nus.edu.sg
SUMMARY:Analytics for X 2024
DESCRIPTION:The Institute of Operations Research and Analytics (IORA)\, Department of Industrial Systems Engineering and Management (College of Design and Engineering) and Department of Analytics and Operations (NUS Business School) of the National University of Singapore are proud to jointly host the Analytics for X 2024 conference in conjunction with the  Next-Gen Scholars Symposium on 28-29 August 2024. \nAnalytics for X is an Annual Conference hosted by IORA that brings together researchers\, educators\, consultants\, practitioners\, and students to contribute to the Fourth Industrial Revolution conversation. After a successful international event in 2023 in Chongqing\, China\, this year\, the conference is back in Singapore. As an annual event\, the conference aims to promote the regular enhancement and dissemination of knowledge related to operations research and analytics\, as well as efficient industrial practices. \nDuring this year’s event\, we are excited to announce the inaugural Next-Gen Scholars Symposium. This symposium\, exclusive to PhD students\, aims to recognize outstanding scholars in Analytics\, Operations Research (OR) and Operations Management (OM) who are nearing the completion of their PhD\, typically within a year or two. It is dedicated to honoring and accelerating the paths of outstanding young scholars who find themselves at a pivotal stage in their academic journey. The symposium will feature the groundbreaking research of these emerging scholars\, and offer them a platform to engage with and learn from the Analytics & OR/OM community\, as well as efficient industrial practices through networking opportunities.
URL:https://iora.nus.edu.sg/events/analytics-for-x-2024/
LOCATION:Innovation 4.0\, Level 1\, 3 Research Link\, 117602\, Singapore
CATEGORIES:Analytics For X
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20240830T090000
DTEND;TZID=Asia/Singapore:20240830T130000
DTSTAMP:20260419T035059
CREATED:20240808T025522Z
LAST-MODIFIED:20240808T025522Z
UID:22997-1725008400-1725022800@iora.nus.edu.sg
SUMMARY:IORA Industry Day 2024
DESCRIPTION:The Institute of Operations Research and Analytics (IORA) is proud to host the inaugural IORA Industry Day 2024. This half-day event will highlight innovative applications of Operations Research and Data Analytics in addressing real-world industry challenges. \nThis year’s program will showcase six pioneering projects\, developed in partnership with research collaborators from the airline\, manufacturing\, charity/food\, and data center sectors. These projects address critical issues including the food distribution supply chain\, pricing engines\, human-AI collaboration\, pilot training\, and energy consumption optimization. \nWe are pleased to welcome guest speakers from Optimisation Analytics Technology\, who will present their innovative work with McDonald’s China. \nAdditionally\, the event will feature an engaging panel discussion with esteemed experts: Marc Dragon (Managing Director\, Reefknot Investments)\, Dr. Simon See (Senior Director\, NVIDIA Global Technology Centre)\, and Dr. Yang Nan (Senior Economist and Head of Economics and Decision Sciences at Amazon Japan). They will discuss future opportunities for Operations Research in solving industry problems. The session will be moderated by Prof. Jussi Keppo\, Research Director (Industry) at IORA. \nWe invite you to join us for this exciting event. Please register by 26th August 2024 (Mon) to reserve your seats.
URL:https://iora.nus.edu.sg/events/iora-industry-day-2024/
LOCATION:Innovation 4.0\, Level 1\, 3 Research Link\, 117602\, Singapore
CATEGORIES:IORA Industry Day
ATTACH;FMTTYPE=image/jpeg:https://iora.nus.edu.sg/wp-content/uploads/2024/08/IORA-Industry-Day_web-banner.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20241003T100000
DTEND;TZID=Asia/Singapore:20241003T113000
DTSTAMP:20260419T035059
CREATED:20240926T024637Z
LAST-MODIFIED:20240926T024637Z
UID:23184-1727949600-1727955000@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Song-Hee Kim
DESCRIPTION:Name of Speaker\nSong-Hee Kim\n\n\nSchedule\n3 October 2024\, 10am – 11.30am\n\n\nVenue \nHSS 3-2 (Hon Sui Sen Memorial Library\, level 3\, Seminar Room 2)\n\n\nLink to Register\nhttps://nus-sg.zoom.us/meeting/register/tZMkfu2vqzovHdT3wuo-DasFqx2x7PnDzw1V\n\n\nTitle\nTo Each Their Own (Shifts): Incorporating Heterogeneous Worker Preferences into Shift Work Schedules\n\n\nAbstract\nShifts are the dominant way to organize work in many contexts requiring 24/7 coverage. While the detriments of shift work are well-documented both at the individual and organizational levels\, its deployment is often unavoidable given round-the-clock staffing needs. We explore a potential operational lever-incorporating heterogeneous preferences over shift characteristics\, which we refer to as the shift choice system-to mitigate ramifications of shift work on worker well-being and turnover. Leveraging rich and novel survey\, shift\, and administrative data\, we document that inpatient nurses exhibit heterogeneous preferences over shift schedules\, driven by both pecuniary and non-pecuniary considerations. We also show that nursing managers largely reflect preferences into scheduled shifts\, albeit imperfectly. We find that the shift choice system improves worker well-being\, as measured by self-reported fatigue and work-life balance. Using a difference-in-differences approach\, we also estimate a 0.58 p.p. decrease in probability of quitting\, but only among more experienced nurses. We find these effects are not driven by differences in the degree to which preferences are reflected in scheduled shifts\, but rather by corresponding improvements in fatigue and work-life balance that are concentrated among more experienced nurses. We do not find evidence to suggest that the shift choice system affects care quality. Our results indicate that allowing for shift choice is an effective responsible scheduling strategy that can improve worker well-being and reduce turnover for highly experienced nurses. Paper available at https://ssrn.com/abstract=4750664.\n\n\nAbout the Speaker\nSong-Hee Kim is the CS Wind Associate Professor of Operations Management at SNU Business School of Seoul National University in South Korea. Her research focuses on making data-driven and evidence-based decisions within service systems\, with an emphasis on problems related to healthcare delivery. She has received several academic awards\, including the Best OM Paper in Management Science Award (winner)\, MSOM Best Paper Award (finalist)\, and INFORMS Pierskalla Award (finalist). She currently serves as an associate/senior editor for the journals Management Science\, Operations Research\, Manufacturing & Services Operations Management\, Production and Operations Management\, Service Science\, and Health Care Management Science. She received her BS from Cornell University and her PhD from Columbia University. Prior to joining SNU Business School\, she was a postdoctoral associate at the Yale School of Management and an assistant professor at the Marshall School of Business\, University of Southern California.\n\n\n\n 
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-song-hee-kim/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20241011T100000
DTEND;TZID=Asia/Singapore:20241011T113000
DTSTAMP:20260419T035059
CREATED:20241002T062242Z
LAST-MODIFIED:20241002T062242Z
UID:23187-1728640800-1728646200@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series : Negin Golrezaei
DESCRIPTION:  \n\n\n\nName of Speaker\nNegin Golrezaei\n\n\nSchedule\n11 October 2024\, 10am – 11.30am\n\n\nVenue \nBIZ1 – 0201 (Mochtar Riady Building\, level 2 Seminar Room)\n\n\nLink to Register \n \nhttps://nus-sg.zoom.us/meeting/register/tZYvd-iuqjksG937fGGVd2M-Dn16gT0CImgP\n\n\nTitle\nOnline Learning via Offline Greedy Algorithms: Applications in Market Design and Optimization\n\n\nAbstract\nIn today’s digital landscape\, the ability to make timely and informed decisions is paramount. Our research addresses the challenge of adapting offline algorithms to dynamic online scenarios\, presenting a versatile framework with wide-reaching implications. We focus on combinatorial problems that lend themselves to efficient approximations through robust greedy algorithms. Our framework leverages the concept of “Blackwell approachability” to seamlessly transform these algorithms from offline to online settings. \nUnder full information conditions\, our online algorithms exhibit approximate regrets of 𝑂(√𝑇). Taking our approach further\, we introduce “Bandit Blackwell approachability\,” extending its applicability to dynamic online decision-making. In the bandit setting\, our framework achieves approximate regrets of 𝑂(𝑇^{2/3}). \nOur research extends to various domains\, including revenue management\, market design\, and online optimization. We tackle challenges such as product ranking optimization\, auction reserve price optimization\, and submodular maximization. Moreover\, we apply our techniques to first-order methods in continuous optimization\, facilitating efficient solutions in various contexts. Numerical simulations demonstrate that our approach outperforms theoretical expectations in real-world scenarios.\n\n\nAbout the Speaker\nNegin Golrezaei is the W. Maurice Young (1961) Career Development Associate Professor of Management and an Associate Professor of Operations Management at the MIT Sloan School of Management. Her research focuses on advancing online marketplaces—such as e-commerce\, online advertising\, and emissions trading systems—by designing and implementing data-driven strategies and algorithmic innovations. She aims to create more resilient\, equitable\, and sustainable digital ecosystems. Before joining MIT\, Negin was a postdoctoral fellow at Google Research in New York\, where she collaborated with the Market Algorithm team to develop and test new mechanisms for online marketplaces. She holds a BSc (2007) and MSc (2009) in electrical engineering from Sharif University of Technology\, Iran\, and a PhD (2017) in operations research from the University of Southern California. Negin serves as an associate editor for Operations Research\, Production and Operations Management\, Operations Research Letters\, and Naval Research Logistics. Her recognitions include the 2021 ONR Young Investigator Award\, the 2018 Google Faculty Research Award\, the 2017 George B. Dantzig Dissertation Award\, the INFORMS Revenue Management and Pricing Section Dissertation Prize\, and the USC Outstanding Teaching Award (2017).\n\n\n\n 
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-negin-golrezaei/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20241014T170000
DTEND;TZID=Asia/Singapore:20241014T180000
DTSTAMP:20260419T035059
CREATED:20241009T032344Z
LAST-MODIFIED:20241009T032344Z
UID:23205-1728925200-1728928800@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series : Zhang Xiaoge
DESCRIPTION:Name of Speaker\nZhang Xiaoge\n\n\nSchedule\n14 October 2024\, 5pm\n\n\nVenue \nE1-07-21/22 – ISEM Executive Classroom\n\n\nLink to Register\nhttps://nus-sg.zoom.us/j/88657161589?pwd=lDmwUK7HFFbONVA8anheLis4tqTVrB.1\n\n\nTitle\nReliability Engineering in the era of AI: An Uncertainty Quantification Framework\n\n\nAbstract\nEstablishing trustworthiness is fundamental for the responsible utilization of medical artificial intelligence (AI)\, particularly in cancer diagnostics\, where misdiagnosis can lead to devastating consequences. However\, there is currently a lack of systematic approaches to resolve the reliability challenges stemming from the model limitations and the unpredictable variability in the application domain. In this work\, we address trustworthiness from two complementary aspects—data trustworthiness and model trustworthiness—in the task of subtyping non-small cell lung cancers using whole side images. We introduce TRUECAM\, a framework that provides trustworthiness-focused\, uncertainty-aware\, end-to-end cancer diagnosis with model-agnostic capabilities by leveraging spectral-normalized neural Gaussian Process (SNGP) and conformal prediction (CP) to simultaneously ensure data and model trustworthiness. Specifically\, SNGP enables the identification of inputs beyond the scope of trained models\, while CP offers a statistical validity guarantee for models to contain correct classification. Systematic experiments performed on both internal and external cancer cohorts\, utilizing a widely adopted specialized model and two foundation models\, indicate that TRUECAM achieves significant improvements in classification accuracy\, robustness\, fairness\, and data efficiency (i.e.\, selectively identifying and utilizing only informative tiles for classification). These highlight TRUECAM as a general wrapper framework around medical AI of different sizes\, architectures\, purposes\, and complexities to enable their responsible use.\n\n\nAbout the Speaker\nDr. Xiaoge Zhang is an Assistant Professor in the Department of Industrial and Systems Engineering (ISE) at The Hong Kong Polytechnic University. His research interests center on risk management\, reliability engineering\, and safety assurance of AI/ML systems using uncertainty quantification\, knowledge-enabled AI\, and fail-safe measures. He received his Ph.D. in Systems Engineering and Operations Research at Vanderbilt University\, Nashville\, Tennessee\, United States in 2019. He has won multiple awards\, including Peter G. Hoadley Best Paper Award\, Chinese Government Award for Outstanding Self-Financed Students Studying Abroad\, Bravo Zulu Award\, Pao Chung Chen Fellowship\, among others. He has published more than 70 papers in leading academic journals\, such as Nature Communications\, IEEE Transactions on Information Forensics and Security\, IEEE Transactions on Reliability\, IEEE Transactions on Cybernetics\, IEEE Transactions on Industrial Informatics\, Reliability Engineering & Systems Safety\, Risk Analysis\, Decision Support Systems\, and Annals of Operations Research\, among others. He is on the editorial board of Journal of Organizational Computing and Electronic Commerce\, Journal of Reliability Science and Engineering. He is a member of INFORMS\, IEEE and IISE.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-zhang-xiaoge/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20241108T100000
DTEND;TZID=Asia/Singapore:20241108T110000
DTSTAMP:20260419T035059
CREATED:20241030T042231Z
LAST-MODIFIED:20241030T042231Z
UID:23267-1731060000-1731063600@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series | 8 Nov | 10am
DESCRIPTION:Name of Speaker\nWang Shixin\n\n\nSchedule\n8 November 2024\, 10am\n\n\nVenue \nE1-07-21/22 – ISEM Executive Classroom\n\n\nTitle\nSimple Menus in Single- and Multi-item Robust Screening\n\n\nAbstract\nThis talk explores simple menus in robust screening. In the first part\, we address a robust selling problem where a seller\, uncertain about the buyer’s valuation distribution\, aims to sell one item. While robust screening offers stronger guarantees than deterministic pricing\, it often requires complex menus with infinite options. Our research introduces simple mechanisms with finite menus\, balancing performance and implementation simplicity. We propose a tractable framework for various ambiguity sets\, including support\, mean\, and quantile\, and derive optimal mechanisms and performance ratios for different menu sizes. We show a modest menu size can deliver similar benefits to those achieved by the optimal infinite-menu mechanism. Notably\, even a two-option menu significantly improves the performance ratio over deterministic pricing. \nThe second part discusses multi-item mechanism design\, where characterizing the optimal mechanism is challenging\, even when the seller knows the buyer’s valuation distributions. A key result in the literature shows that separable mechanisms (where items are sold independently) are robustly optimal when only marginal distributions are known. However\, separate selling may fail to capture a substantial portion of the optimal revenue. To improve performance while retaining simplicity\, we introduce “semi-separable mechanisms\,” where allocation and payment rules for each item depend solely on that item’s valuation\, but leverage joint distributional information. We prove that semi-separable mechanisms achieve the optimal performance ratio among all incentive-compatible and individually rational mechanisms when only marginal support information is available. Our framework also extends to scenarios where sellers have information on the aggregate valuations of product bundles.\n\n\nAbout the Speaker\nShixin Wang is an Assistant Professor in the Department of Decisions\, Operations and Technology at The Chinese University of Hong Kong (CUHK) Business School. Before joining CUHK\, she obtained her doctoral degree in Operations Management from NYU Stern School of Business. Her research interests lie in developing simple and robust pricing policies in revenue management\, and designing sparse and reliable networks in supply chain and service systems. Her works have been published in Management Science\, Operations Research\, and Manufacturing & Service Operations Management.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-8-nov-10am/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250117T100000
DTEND;TZID=Asia/Singapore:20250117T113000
DTSTAMP:20260419T035059
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:20260419T035059
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:20260419T035059
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:20260419T035059
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:20260419T035059
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:20260419T035059
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:20260419T035059
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:20260419T035059
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:20260419T035059
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:20260419T035059
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:20260419T035059
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:20260419T035059
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:20260419T035059
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
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