2016 INFORMS Annual Meeting Program

WA55

INFORMS Nashville – 2016

WA53 Music Row 1- Omni New Product Development and Process Development in Healthcare Sponsored: Technology, Innovation Management & Entrepreneurship Sponsored Session Chair: Zhili Tian, Florida International University, 11200 SW 8th St, Miami, FL, 33199, United States, zhili.a.tian@gmail.com 1 - An Empirical Analysis Of The Barriers To And Optimal Use Of Clinical Decision Support Systems In Health Care Xiaojin Liu, University of Minnesota, Minneapolis, MN, United States, liux1591@umn.edu, Susan Goldstein, Karen Soderberg, Kingshuk K Sinha Clinical Decision Support (CDS) systems provide critical clinical information for health care processes, and development of capabilities related to their use enable provide knowledge related to both the current workflow and for process improvement. Yet, little is known about the barriers and outcomes of the development of these capabilities. We empirically investigate the barriers to CDS use and the consequences of using CDS features, controlling for organizational characteristics in the clinical setting. 2 - Management Of Cancer Drug Shortage Under Demand And Supply Uncertainty Shanling Li, McGill University, shanling.li@mcgill.ca, Dali Zhang, Xiaowen Chang, Huifu Xu In this research, we aim at developing an optimization model that characterizes the supply chain disruption of a generic cancer drug resulted from operational problems. We consider the trade-off between generic and brand name drugs and uncertainties in demand and supply. The cancer drug shortage problem is formulated as a chance-constrained model. Our aim is to investigate the severe impact of short supply of the generic cancer drug on supply chain decisions and to propose optimal purchasing plans to mitigate the drug shortage risk. 3 - Outsourcing Stategy For Intermediate Production Steps Yang Wang, UC Berkeley, 4174 Etcheverry Hall, University of California Berkeley, Berkeley, CA, 94720, United States, yangwang0803@berkeley.edu, Philip Kaminsky Small biopharmaceutical firms often outsource their final filling and labeling operations to a third party, but these firms use a variety of different outsourcing strategies. In particular, we consider two types of strategies. In the first, the firm orders when inventory position is low, so that its order is triggered by inventory level. In the second, the firm reserves a limited amount of capacity at the outsourcer at repeated fixed intervals, so that its order is triggered by time. These strategies impact inventory management at the biopharma firm, as well as capacity utilization at the outsourcer, and we develop models to explore the trade-off between these two types of strategies. 4 - Clinical Trials And New Drug Development: Optimal Investment Policies And Application Zhili Tian, Florida International University, 11200 S.W. 8th Street, Miami, FL, 33199, United States, zhili.a.tian@gmail.com Firms conduct Phase 3 trials by enrolling and treating patients who meet certain conditions. Opening test centers and finding patients to participate in trials are expensive and time consuming, with a great deal of uncertainty around these. We develop a dynamic recruitment policy for clinical trials, which depends on the available information on drug quality, potential market size, and likelihood of FDA approval. It also takes into account the costs of the clinical testing and the current success in enrolling patients. We consider cases with and without interim analysis of the clinical data. We develop structural results and provide conditions for accelerating or suspending a clinical study. WA54 Music Row 2- Omni Agent-based Modeling in Management Sciences and Economics Sponsored: Service Science Sponsored Session Chair: Wei Zhang, Tianjin University, Tianjin, China, weiz@tju.edu.cn Co-Chair: Shu-Heng Chen, National Chengchi University, 64, Chih-nan Rd.,Sec. 2, Wenshan, Taipei 11623, Taipei, 11623, China, chen.shuheng@gmail.com Co-Chair: Silvano Cincotti, University of Genoa, via Opera Pia, 15 - 16145 Genova, ITALY, Genova, 16145, Italy, silvano.cincotti@unige.it

1 - Agent-based Modeling Of Chinese University Admission Mechanisms: From The Boston Mechanism To The Chinese

Parallel Mechanism, Mission Accomplished? Shu-Heng Chen, National Chengchi University, chen.shuheng@gmail.com

Between 1952 and 2003, all provinces in China used the algorithms equivalent to the Boston mechanism to admit college students. However, after a prolonged period of experimentation, the Boston mechanism has been criticized for its invoking “justified envy.” In response, since 2003, some Chinese provinces have gradually promulgated a new system called the Chinese parallel mechanism, aiming to allocate students based more on their abilities than on their choices in order to answer the criticism of justified envy. Has this policy reform accomplished its mission? In this article, we use the agent-based model to evaluate the admission policy reform in Chinese higher education. 2 - An Empirical Zero-intelligence Model Of Chinese Stocks Wei-Xing Zhou, East China University of Science and Technology, 130 Meilong Road, Shanghai, 200237, China, wxzhou@ecust.edu.cn, Gao-Feng Gu, Xiong Xiong, Wei Zhang, Yong-Jie Zhang, Wei Chen Computational experimental finance is an important topic in finance. Order- driven models constructed based on the statistical properties of order flows are able to reproduce the main stylized facts of financial variables. In this talk, we will introduce a microscopic model based on the order flows of Chinese stocks. We will also discuss the potential applications of order-driven models in stock market micro structures and financial engineering. For instance, we study the optimal trading strategy problem of large orders and the impact of asymmetric price limits on stock price evolution. 3 - Nonlinear Transient Shock, Implementation Shortfall Optimum Strategy And Market Influences: Based On The Framework Of Computational Finance Haifei Liu, Nanjing University, Nanjing, China, hfliu@nju.edu.cn, Xindan Li, Xiong Xiong This paper builds an artificial stock market to simulate the real market, and make sure that the artificial market has the same statistical features with the real market. The mechanism of information sharing will also play an important role in the artificial market. Then the paper proposes a nonlinear quadratic IS (Implementation Shortfall) algorithm. We will analysis the impact on market when perform the algorithm and the different effects when compared with linear IS and Minimum Risk Volume Weighted Average Price. To conduct robust test, this paper also analysis the performance of the above algorithms under the different levels of private information in the market. 4 - Biased Information, Peer Pressure And Expectation Formation Dehua Shen, Tianjin University, Tianjin, China, dhs@tju.edu.cn, Yongjie Zhang, Andrea Teglio, Wei Zhang Behavior economics has relaxed the assumption on perfect rationality and recognized the impact of psychological biases on the expectation formation. However, existing literature mainly postulates the unbiased information generated by information sources. In that sense, the information reporting behavior is hugely simplified. In this paper, we address this issue by simulating an agent-based computational model with the consideration of the diffusion of biased information and investigate its influence on expectation formation. Meanwhile, the peer pressure mechanism is introduced to depict the social learning behavior among investors. WA55 Music Row 3- Omni Inventory Management VII Contributed Session Chair: Sepideh Alavi, University of Wisconsin Milwaukee, 1559 N Prospect Ave. Apt 309, Milwaukee, WI, 53202, United States, alavi@uwm.edu 1 - Inventory Replenishment Decision Support Matthew D. Dean, University of Southern Maine, Portland, ME, Contact: matthew.dean1@maine.edu We describe an MBA-led project to help a local glass and metal fabricator improve its inventory replenishment system. Historically, it relied on a manual inventory system controlled by a single person with many years of experience. The MBA team developed a spreadsheet-based linear programming model to rec- ommend purchasing decisions. This tool was then migrated to a user-friendly web-based application.

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