About

The page provides information about the NYU Stern Center for Research Computing (SCRC), which is devoted to providing world-class computational facilities and services to researchers at the Stern School of Business at New York University. The center offers a variety of services including a moderately sized Slurm HPC cluster, Cloud Computing (Virtual Machines), data acquisition and storage, research software, and access to WRDS (Wharton Research Data System). The research software suite is designed to facilitate advanced computational research and data analysis, while the datasets are sourced from diverse disciplines through collaborations with data repositories, platforms, and academic institutions. The compute services and storage systems support faculty and researchers' projects with high-speed, robust, and scalable solutions. The page emphasizes the center's role in supporting computational research but does not provide specific details about Professor Eitan Zemel's personal research focus, background, or key contributions.

Research topics

• Mathematics
• Combinatorics
• Computer science
• Mathematical optimization
• Mathematical economics

Selected publications

• Unintended Acceleration: Toyota’s Recall Crisis

  Kellogg School of Management Cases · 2017-01-20 · 12 citations

  articleSenior author

  In late 2009 Toyota became the subject of media and U.S. government scrutiny after multiple deaths and injuries were attributed to accidents resulting from the unintended and uncontrolled acceleration of its cars. Despite Toyota's voluntary recall of 4.2 million vehicles for floor mats that could jam the accelerator pedal and a later recall to increase the space between the gas pedal and the floor, the company insisted there was no underlying defect and defended itself against media reports and regulatory statements that said otherwise. As the crisis escalated, Toyota was further criticized for its unwillingness to share information from its data recorders about possible problems with electronic throttle controls and sticky accelerator pedals, as well as braking problems with the Prius. By the time Toyota Motor Company president Akio Toyoda apologized in his testimony to the U.S. Congress, Toyota's stock price had declined, in just over a month, by 20 percent---a $35 billion loss of market value. Understand the strategic and reputational nature of crises Recognize the challenges of managing a crisis Learn the requirements for building trust in a crisis Understand the challenges of managing a crisis that may not be the company's fault Identify the strategic business problem in a crisis Understand how corporate structure may help or hinder effective crisis management Understand the media landscape and its impact on crisis management

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• Managing Business Process Flows: Pearson New International Edition PDF eBook

  2013-01-01

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• Unintended Acceleration: Toyota's Recall Crisis

  Kellogg School of Management eBooks · 2012-01-01 · 25 citations

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• A note on the properties of the optimal solution(s) of the Greed and Regret problem

  European Journal of Operational Research · 2009-11-24

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• Corporate Governance in the Modern Financial Sector

  2009-03-09 · 16 citations

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• Corporate Governance in the Modern Financial Sector

  Financial Markets Institutions and Instruments · 2009-03-05 · 32 citations

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• Understanding Supplier Quality in Decentralized Supply Chains

  The Faculty Digital Archive (New York University) · 2008-03-03

  articleOpen accessSenior author

  Operations Management Working Papers Series

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• Sourcing Through Auctions and Audits

  Production and Operations Management · 2008-03-01 · 34 citations

  articleSenior author

  Buyers often find that obtaining complete information about suppliers is costly. In such scenarios, there is a trade‐off between the costs of obtaining information and the benefits that accrue to the owners of such information. There are also various ways in which the missing information can be obtained or inferred. In this paper, we compare the efficiency of obtaining information via the classical mechanism design approach, which relies on the information available before the contracts are designed, with that of an “audit‐based” approach, which relies on the information obtained after the fact. In our model, a single buyer (the Stackelberg leader) wishes to procure a package of products or services from various competing suppliers that possess private cost information. We allow for arbitrary cost and revenue functions and can incorporate multiple cost and revenue drivers. We show how the buyer can optimize her profit and at the same time coordinate the channel by using a contract scheme involving auctions, audits, and profit sharing. We also examine the behavior of this mechanism when the supplier can exert effort to reduce cost but the cost of effort cannot be verified. We propose several mechanisms for different precontract informational scenarios and compare their performance.

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• Costly Enforcement of Quality Standards in Decentralized Supply Chains

  The Faculty Digital Archive (New York University) · 2008-02-19 · 2 citations

  articleOpen accessSenior author

  We consider a supply chain where the quality level can be observed by the buyer(s) only after the purchase is completed (experience good). If the delivered quality is below the levels agreed in the contract, the buyer(s) may take action to seek remedy, but this effort is costly. Obviously, this fact can be exploited by the seller. In the case of a single buyer, we show that the buyer may not be motivated to appropriate all the channel profits but, rather, is able to pay a higher purchase price in order to induce the seller to provide higher quality. The set of purchase prices that support trade split into different regions. We identify regions where counterintuitive behavior is exhibited, for example, the buyer prefers higher purchase price, while the seller prefers lower purchase price. For the case of more than one buyer, we examine and contrast the behavior of two remedy regimes: In the case of individual enforcement, each buyer must work individually to enforce her own quality. In the case of joint enforcement, all buyers benefit from enforcement by a single buyer. We examine the externalities that arise in this supply chain and identify how the market share, enforcement costs and purchase price affect the quality level.

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• The Greed and Regret Problem

  The Faculty Digital Archive (New York University) · 2007-01-01 · 1 citations

  articleOpen accessSenior author

  In this paper, we study a model, called the Greed and Regret (GR) problem that provides a unified approach for analyzing numerous situations in a wide range of areas including studies of crime, fraud, aggression and threats, “take it or leave it” offers and ultimatums, optimal bidding, service levels, buffers, and inventory, sales force compensation, and more. We model these situations as continuous decision problems, where the decision maker seeks to set the level of his activity as high as possible without crossing the line and going overboard. A special case of this problem, which we call the Market Price Newsvendor (MNV), involves a Newsvendor whose selling price depends on whether the supply or demand is tight. The (MNV) problem bears an interesting and surprising relation to the “Selling to the Newsvendor ” problem studied by Lariviere and Porteus (2001). In general, the (GR) problem need not be concave. Our main results are to prove several monotonicity properties for the (GR) problem and to identify a sufficient condition for uniqueness of the optimal solution, which we call Increasing Composite Failure Rate (ICFR), and study its properties. The condition is a relaxation of the IGFR property introduced by Lariviere and Porteus (2001) but is stronger than the IFR property. We extend the analysis to a larger class of incentive and disincentive functions and to the finite horizon version of the problem.

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Frequent coauthors

• Ehud Kalai

  Northwestern University

  15 shared

• Nimrod Megiddo

  9 shared

• Egon Balas

  7 shared

• Itzhak Gilboa

  6 shared

• Refael Hassin

  Tel Aviv University

  5 shared

• Anshul Sheopuri

  IBM (United States)

  5 shared

• Zvi Drezner

  California State University, Fullerton

  4 shared

• Ravi Anupindi

  4 shared

Awards & honors

• Department of Marketing, Leadership Excellence Award (2024)