Informs Annual Meeting 2017

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INFORMS Houston – 2017

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expected net present value, subject to investor participation constraints and platform fees. We use approximate firm solutions in a game-theoretic setting to analyze the platform’s problem, which sets its optimal pricing structure, in the form of origination and servicing fees, to maximize its net present value, subject to firm participation constraints. 2 - Guarantor Financing in a Three-stage Supply Chain Gangshu Cai, Santa Clara University, Department of OMIS, 216n Lucas Hall, Santa Clara, CA, 95053, United States, gcai@scu.edu, Weihua Zhou, Tiantian Lin Based on a supply chain model with a manufacturer, a capital-constrained retailer, a third-party logistics (3PL) firm, and a bank, this paper investigates two types of guarantor financing, manufacturer guarantor and 3PL guarantor, and compares them to traditional bank financing. 3 - Inventory Risk and Financing Frictions for SME Suppliers Fasheng Xu, Washington University in St. Louis, Saint Louis, MO, 63130, United States, fasheng.xu@wustl.edu, Panos Kouvelis, Wenhui Zhao Most of the financing initiatives revolve around post-shipment approved-invoice financing. But SME suppliers would have cash flow difficulty financing production activities upfront. To fill this gap, we study a pull-structure supply chain with a large retailer and a SME supplier. The bank offers a fairly-priced loan for relevant operational risks and failure of loan repayment leads to costly bankruptcy. We identify the Stackelberg equilibrium and find the supplier’s riskiness always dampen the retailer’s profit, however may benefit the supplier itself. Interestingly, the supplier’s riskiness may benefit the system and increase the supply chain’s expected profit. 4 - Financial Pooling in a Supply Chain S. Alex Yang, London Business School, Regent’s Park, London, NW1 4SA, United Kingdom, sayang@london.edu, Qu Qian, Ming Hu We study a supply chain in which the buyer uses trade credit to purchase from the supplier. The embedded stretch option of trade credit allows supply chain partners to pool their liquidity buffers. Due to this pooling effect, even as the supplier’s financing costs are higher than the buyer’s, trade credit can be more effcient than cash on delivery when the supplier’s cost for collecting trade credit is low or when the supplier does not have access to a low-cost financing channel when facing liquidity shocks. The benefit of pooling increases as the buyer has a more diversified supplier portfolio. As an innovative financing scheme, reverse factoring further enhances the effciency of this pooling effect. 332F Operations Management Contributed Session Chair: Li Haiyan, Harbin Engineering University, Harbin, China, 643076746@qq.com 1 - Innovation Opportunities Emerging from Responsiveness and Co- located Manufacturing Lauri Saarinen, University of Lausanne, Bâtiment Anthropole 3016, Lausanne, CH-1015, Switzerland, lauri.saarinen@unil.ch Co-locating manufacturing with either the market or with R&D encourages innovation: Customer ideas are more easily communicated, and product and process innovations are more rapidly tested. We develop a system dynamics model of the interaction between responsiveness and innovation. We demonstrate that the real options created when responsiveness makes it possible to postpone the decision about what will be produced until demand information is available also generate follow-on options through innovation. 2 - Antecedents of New Venture Financing Thomas Zehren, Assistant Lecturer and PhD Candidate, Technical University of Dortmund, Vogelpothsweg 87, Dortmund, 44227, Germany, Thomas.Zehren@udo.edu It is widely acknowledged that traditional capital market theories do not apply to the initial capital structure of new ventures. However, empirical evidence on the actual behavior is very limited. Drawing on a novel sample of over 4,000 new business owners, this paper examines the influence of founder- and venture- related characteristics on the initial capital structure. Our central contribution is that the provision of personal assets by the owner represents a central element of start-up financing. Additionally, we demonstrate that the access of external capital sources is mainly related to venture and not - as one would expect - to founder- related characteristics. TA16

332D Personalized Medicine Sponsored: Manufacturing & Service Oper Mgmt, Healthcare Operations Sponsored Session

Chair: John Silberholz, University of Michigan, josilber@mit.edu 1 - Personalized Medicine in Cost-effective Management of Diffuse Large B-cell Lymphoma Qiushi Chen, Massachusetts General Hospital, 101 Merrimac St., 10th FL, Boston, MA, 02114, United States, qchen@mgh-ita.org, Turgay Ayer, Christopher Flowers Diffuse large B cell lymphoma (DLBCL) is the most common type of aggressive lymphoma. There are various treatment options available, and evidence shows that patients with DLBCL experience widely divergent outcomes. Recent findings imply that treatment tailored by biological subtypes represents a promising treatment strategy for DLBCL patients. In this study we assess the potential benefit of personalized treatment based on subtype with respect to health and cost outcomes, and compare with the one-size-fits-all treatment strategies. 2 - Personalized Treatments for Breast Cancer Patients Emma L.Gibson, MIT, 60 Woodsworth Street, Cambridge, MA, 02142, United States, emgibson@mit.edu There are many treatment options available to breast cancer patients, but it is often difficult to predict how successful these treatments will be for individual cases. We have developed a personalized treatment algorithm to select and evaluate treatment options based on individual diagnostic factors and existing medical conditions. When applied to cases in the SEER-Medicare dataset, our algorithm recommended alternative treatment options for approximately 10% of test subjects, resulting in an average estimated increase in survival time of 8 months within the first 8 years after diagnosis. 3 - The Price of Simplicity in Personalized Prostate Cancer Screening Strategies John M.Silberholz, Assistant Professor, University of Michigan, 701 Tappan Street R5468, Ann Arbor, MI, 48109, United States, josilber@umich.edu Patient preferences for different health states can significantly impact their best course of action in screening for diseases like prostate cancer. Patients with a relatively small disutility for treatment side effects might benefit from aggressive screening, while others might benefit from less aggressive screening or no screening at all. In this work, we use a mathematical model to quantify the benefit of fully personalized prostate cancer screening versus a one-size-fits-all strategy. Further, we identify simpler, more interpretable personalized screening strategies that could be easier to implement in practice, and we quantify the price of this simplicity in strategies. 4 - Personalised Treatment for Coronary Heart Disease Patients using Electronic Medical Records and Machine Learning Agni Orfanoudaki, MIT, 77 Massachusetts Avenue, Cambridge, MA, United States, agniorf@mit.edu Coronary Heart Disease is the most common type of heart disease and the leading cause of death in the United States. However, a common approach to determine which treatment to prescribe to which patient has not yet been established. On that basis, we recognized the substantial benefit that machine learning and algorithmic approaches could bring to this field. We developed a personalized prescriptive algorithm that uses EMR to maximize the expected time to an adverse event from the time diagnosis. Overall, we achieve 15,2% improvement for the overall population, performing particularly well in the female (17,5% improvement) and in the Hispanic subpopulation (24,8% improvement). 332E Operations-Finance Interface Sponsored: Manufacturing & Service Oper Mgmt, Supply Chain Sponsored Session Chair: S. Alex Yang, London Business School, London, NW1 4SA, United Kingdom, sayang@london.edu 1 - Crowdfunding via Revenue-sharing Contracts Soraya Fatehi, University of Washington, 5215 15th Avenue, Apt 15, 15, Seattle, WA, 98105, United States, sfatehi@uw.edu, Michael R.Wagner We present a new model of crowdfunding where a platform acts as a matchmaker between a firm needing funds and a crowd of investors willing to provide capital. Once the firm is funded, it pays back the investors using revenue sharing contracts. The firm determines its optimal contract parameters to maximize its TA15

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