-
作者：Schwab, Stephen D.
作者单位：University of Texas System; University of Texas at San Antonio
摘要：When a member of a work team leaves, some knowledge is lost to the organization. Exploiting quasi-random turnover among military physicians because of deployments, I estimate the effects of turnover on patients and other providers in the same care team. I find that a discontinuity in primary care leads to a 3%-5% increase in costs driven primarily by an increase in the use and intensity of specialty care with no observable benefit to the patient as measured by potential reductions in hospitali...
-
作者：Choi, Jay Pil; Kim, Kyungmin; Mukherjee, Arijit
作者单位：Michigan State University; Yonsei University; Emory University
摘要：Platform-run marketplaces may exploit third-party sellers' data to develop competing products, but the threat of future competition can deter sellers' entry. We explore how this trade-off affects the platform's entry on the marketplace and the referral fee it charges to the third-party sellers. We first characterize the platform's optimal fee under different degrees of commitment on its own entry policy. We show that full commitment maximizes not only the platform's payoff but also consumer su...
-
作者：Han, Eojin; Nohadani, Omid
作者单位：University of Notre Dame
摘要：Sequential decision making often requires dynamic policies, which are computationally not tractable in general. Decision rules provide approximate solutions by restricting decisions to simple functions of uncertainties. In this paper, we consider a nonparametric lifting framework where the uncertainty space is lifted to higher dimensions to obtain nonlinear decision rules. Current lifting-based approaches require predetermined functions and are parametric. We propose two nonparametric liftings...
-
作者：Bapna, Sofia; Funk, Russell J.
作者单位：University of Minnesota System; University of Minnesota Twin Cities; University of Minnesota System; University of Minnesota Twin Cities
摘要：This article may be used only for the purposes of research, teaching, and/or private study. Commercial use or systematic downloading (by robots or other automatic processes) is prohibited without explicit Publisher approval, unless otherwise noted. For more information, contact permissions@informs.org. The Publisher does not warrant or guarantee the article's accuracy, completeness, merchantability, fitness inclusion of an advertisement in this article, neither constitutes nor implies a guaran...
-
作者：Hillenbrand, Adrian; Hippel, Svenja
作者单位：Leibniz Association; Zentrum fur Europaische Wirtschaftsforschung (ZEW); Helmholtz Association; Karlsruhe Institute of Technology; University of Bonn
摘要：Rapid technological developments in online markets fundamentally change relationship between consumers and sellers. Online platforms can easily gather data consumers' search behavior, allowing for price discrimination. Therefore, product becomes a strategic choice. Consumers face a tradeoff: Search intensely and receive fit at a potentially higher price or restrict search behavior, be strategically inattentive, receive a worse fit but maybe a better deal. We study the resulting strategic buyer...
-
作者：Lo, Andrew W.; Zhang, Ruixun
作者单位：Massachusetts Institute of Technology (MIT); Massachusetts Institute of Technology (MIT); The Santa Fe Institute; Peking University; Peking University
摘要：We propose a new performance attribution framework that decomposes a constrained portfolio's holdings, expected returns, variance, expected utility, and realized returns into components attributable to (1) the unconstrained mean-variance optimal portfolio; (2) individual static constraints; and (3) information, if any, arising from those constraints. A key contribution of our framework is the recognition that constraints may contain information that is correlated with returns, in which case im...
-
作者：August, Terrence; Noh, Daehoon; Shamir, Noam; Shin, Hyoduk
作者单位：University of California System; University of California San Diego; University of San Diego; Tel Aviv University
摘要：With the increased frequency and magnitude of cyberattacks, policymakers and the private sector search for ways to counter this threat. One of the main initiatives suggested to achieve this goal is sharing cybersecurity-related information. Although the general belief is that information sharing can increase both industry profit and social welfare, it is unclear whether firms would voluntarily share such information. In this paper, we examine the incentives of firms to share cybersecurity-rela...
-
作者：Zeithammer, Robert; Choi, W. Jason
作者单位：University of California System; University of California Los Angeles; University System of Maryland; University of Maryland College Park
摘要：Online advertising impressions are traded through a multitiered network of intermediaries. We model the revenue optimization of a publisher that auctions off advertising impressions to intermediary exchanges, which, in turn, run their own internal auctions among the advertisers they represent. We show that the resulting auction-of-auctions market arrangement suffers from a double marginalization problem: the multitier bid shading prompts the publisher to raise the reserve price above the level...
-
作者：Simchi-Levi, David; Zheng, Zeyu; Zhu, Feng
作者单位：Massachusetts Institute of Technology (MIT); University of California System; University of California Berkeley; Massachusetts Institute of Technology (MIT)
摘要：We study the stochastic multi-armed bandit problem and design new policies that enjoy both optimal regret expectation and light-tailed risk for regret distribution. We first find that any policy that obtains the optimal instance-dependent expected regret could incur a heavy-tailed regret tail risk that decays slowly with T. We then focus on policies that achieve optimal worst-case expected regret. We design a novel policy that (i) enjoys the worst-case optimality for regret expectation and (ii...
-
作者：Lyu, Jiameng; Xie, Jinxing; Yuan, Shilin; Zhou, Yuan
作者单位：Tsinghua University; Tsinghua University
摘要：Stochastic gradient descent (SGD) has proven effective in solving many inventory control problems with demand learning. However, it often faces the pitfall of an infeasible target inventory level that is lower than the current inventory level. Several recent works have been successful in resolving this issue in various inventory systems. However, their techniques are rather sophisticated and difficult to apply to more complicated scenarios, such as multiproduct and multiconstraint inventory sy...
