2015 Informs Annual Meeting

MD25

INFORMS Philadelphia – 2015

MD22 22-Franklin 12, Marriott Joint Session Prize/CPMS: 2015 Informs Prize Winner Cluster: 2015 INFORMS Prize Presentation Invited Session Chair: Peter Buczkowski, Manager, Workforce Management, Disney Parks & Resorts, P.O. Box 10000, Lake Buena Vista, FL, 32830, United States of America, Peter.S.Buczkowski@disney.com 1 - 2015 Informs Prize Presentation by Chevron Margery Connor, Chevron, 6001 Bollinger Canyon, F-2080, San Ramon, CA, 94583, MHCO@chevron.com, Bill Klimack, Wen Chen Chevron, 2015 INFORMS Prize Winner for excellence in analytics and operations research, will present their long and innovative history of applying analytics and operations research across their worldwide energy company. Highlighted projects include: • Petro: Chevron’s refinery planning tool • Workforce forecasting to ensure the right people on the right projects • genOpt: Optimization model to maximize oil and gas production. Chevron will also share their journey applying decision analysis. Chair: Tolga Tezcan, Associate Professor, London Business School, Regent’s Park, London NW14SA, United Kingdom, ttezcan@london.edu Co-Chair: Neil Walton, University of Amsterdam, Science Park 904, Amsterdam, Netherlands, n.s.walton@uva.nl 1 - Risk Analytics David D. Yao, Columbia University, Department of Industrial Engineering, 500 West 120 St, New York, NY, 10027-6699, United States of America, yao@columbia.edu, Jose Blanchet, Paul Glasserman This year’s Markov lecture and discussions will provide a survey of risk analytics as a fundamental tool in operations research. While the focus of business analytics is on issues of productivity and efficiency: cost savings and revenue/profit optimization, risk analytics address the complementary issues of sustainability and resiliency: risk-return tradeoff and related resource allocation decisions and mitigation strategies. Some of the applications to be highlighted include: resilient urban infrastructures, production planning with risk hedging, financial systemic risk, and securitized insurance products. MD24 24-Room 401, Marriott Latent Variable Models in Biomedical Informatics Sponsor: Artificial Intelligence Sponsored Session Chair: Madeleine Udell, Postdoctoral Fellow, Caltech, CMS, Mail Code 9-94, Pasadena, CA, 91125, United States of America, madeleine.udell@gmail.com 1 - Computational Phenotyping from Electronic Health Records using Tensor Factorization Joyce Ho, University of Texas at Austin, 1 University Station A computational phenotype (a set of clinical features or clinical condition) can enable cohort identification, allow decision-makers to identify patients for interventions, and be integrated with systems for real-time clinical decision support. We developed sparse, nonnegative tensor factorization models to obtain phenotypes with minimal human supervision. Results on real EHRs demonstrate the effectiveness of our models to extract medically interpretable concepts from complex health data. C0803, Austin, TX, 78712, United States of America, joyceho@utexas.edu, Jimeng Sun, Joydeep Ghosh MD23 23-Franklin 13, Marriott Markov Lecture Sponsor: Applied Probability Sponsored Session

2 - Unfolding Physiological State: Mortality Modelling in Intensive Care Units

Marzyeh Ghassemi, MIT, 32 Vassar Street,, 32-257, Cambridge, MA, 02139, United States of America, mghassem@mit.edu Accurate knowledge of a patient’s disease state and trajectory is critical in modern clinical settings. We examined the use of latent variable models to decompose free-text hospital notes into meaningful features, and the predictive power of these features for patient mortality. We found that latent topic-derived features were effective in determining patient mortality both in-hospital and post- discharge, and a combination of structured and topic features performed best. 3 - Unsupervised Learning of Disease Progression Models David Sontag, Assistant Professor, NYU, 715 Broadway, Chronic diseases such as diabetes and COPD progress slowly over many years, causing increasing burden to patients and the healthcare system. Better understanding progression is instrumental to early diagnosis and precision medicine. Inferring disease progression from real-world evidence is challenging due to the incompleteness and irregularity of observations, as well as the heterogeneity of patient conditions. We propose a probabilistic disease progression model that address these challenges. 12th Floor, Room 1204, New York, NY, 10003, United States of America, dsontag@cs.nyu.edu

MD25 25-Room 402, Marriott

Economics of IS & OM Sponsor: Information Systems Sponsored Session

Chair: Lin Hao, University of Notre Dame, 351 Mendoza College of Business, Notre Dame, IN, United States of America, lhao@nd.edu 1 - Exploring a New Marketing Platform of Credit Card Companies Soohyun Cho, University of Florida, 355F STZ, Gainesville, FL, United States of America, soohyun.cho@warrington.ufl.edu, Subhajyoti Bandyopadhyay, Liangfei Qiu Some credit card companies (CCs) and partner merchants have launched an exclusive marketing platform for their cardholders. The platform provides either public promotion through Social Network Services (SNS) or targeted promotion through their websites. We examine which promotion is more profitable to CCs and to competitive partner merchants. 2 - Bundling of Digital Products in Music Industry: An Empirical Study Kyungsun Rhee, PhD Student, University of Washington, University of Washington, Seattle, WA, 98105, United States of America, ksr22@uw.edu, Yong Tan, Jianping Peng It is becoming increasingly competitive for music websites nowadays. Due to highly heterogeneous demand, offering music bundles is a popular strategy to attract consumers. In this work, we examine the effectiveness of various bundling strategies using a unique dataset from a music mobile application which contains variables such as music downloads, ringtone purchase logs and user behavior in monthly subscription. 3 - E-book Platform Competition in the Presence of Two-sided Network Externalities Yabing Jiang, Florida Gulf Coast University, 10501 FGCU Blvd, Fort Myers, FL, United States of America, yjiang@fgcu.edu The success of the Kindle e-book platform and the increased popularity of e-books among readers have attracted extensive competition in the e-book market. We model the direct competition in the e-book platform market through a two-sided network externality model and show that publishers can influence consumers’ e- book platform adoption decisions and the total e-book sales by strategically deciding the size of contents available on each platform. 4 - The Effect of Online “Following” on Contributions to Open Source Communities Mohammadmahdi Moqri, University of Florida, 299 Diamond Blvd, Apt. 5, Gainesville, United States of America, mahdi.moqri@warrington.ufl.edu, Liangfei Qiu, Subhajyoti Bandyopadhyay, Ira Horowitz Although numerous studies have examined members’ motivation to contribute to online communities, the positive effect of social factors has not been unanimously confirmed in different settings. In this study, we estimate the effect of social factors on members’ contributions in an open source software (OSS) community, using a large scale dataset of 4 million online members. The results have implications for online community designers and OSS scholars.

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