Informs Annual Meeting 2017

WA32

INFORMS Houston – 2017

2 - Stock Market Spoofing Jussi Keppo, National University of Singapore, Mochtar Riady Building, BIZ 1 8-69, 15 Kent Ridge Drive, Singapore, 119245, Singapore, keppo@nus.edu.sg, Xianhua Peng We use a unique trading dataset of one week to analyze the behavior of high- frequency traders. About 8% of institutional traders intentionally or unintentionally first enter and then quickly cancel a buy (or sell) limit order without actually buying (or selling) before the trader actually sells (or buys) a security. We show that the p-value for testing that all this behavior is a random event, and thus unintentional, is extremely small, equal to the probability of observing a 53-standard deviation event. Therefore, most likely at least part of the behavior is intentional and an indication of so-called “spoofing”, an attempt to manipulate prices. 3 - Public Information, Investor Trading and Stock Bubble: Evidence from Chinese Stock Market Kun Chen, Assistant Professor, Southern University of Science and Technology, China, 518055, China, chenk@sustc.edu.cn, Sisi Wu, Leon Zhao, Jian Yin According to the resale option theory, asset bubble is caused by investor heterogeneous beliefs which are reflected in investor trading behaviors. In this study, we want to explain the formation of heterogeneous beliefs from the information processing perspective, and investigate the circular relations among public information, investor trading, and stock bubble. We focus on the 2015 Chinese stock bubble, and find that different sources of information, such as news, discussion boards, and analyst reports, and different measures of information, i.e. sentiment, coverage, and dispersion, have different impacts on trading behaviors of different investors. 4 - A Generalized Real Estate Pricing Model with Exogenous Affine-form Variables Hiroshi Ishijima, Professor, Chuo University, 1-18 Ichigaya-tamachi Shinjuku, Tokyo, 1628478, Japan, hiroshi.ishijima.jp@gmail.com, Akira Maeda, Tomohiro Tsuruga We develop a generalized real estate pricing model that incorporates hedonic attribute variables of real estate as well as exogenous variables in an affine form. We then conduct an empirical analysis to understand Japanese house prices by exogenous variables with hedonic variables controlled. Our analysis reveals that the financial asset prices and conventional hedonic variables serve as the major determinants of Japanese house prices. We also show evidence that low interest rates under the Abenomics monetary policy successfully stimulate Japanese house prices. 351B Supply Chain, Managing Disruptions Contributed Session Chair: Hoda Sabeti, West Virginia University, Morgantown, WV, United States, hoda.sabeti@gmail.com 1 - Flexible Supply Chain Network Design under Uncertainty through Capacity Planning Nima Salehi Sadghiani, PhD Candidate, University of Michigan, 3735 GreenBrier Boulevard, Apt 223C, Ann Arbor, MI, 48105, United States, nsalehi@umich.edu, Mark Stephen Daskin Managing uncertainty is one of the challenging issues in supply chains. Deviations from the expected values of key input parameters can make the deterministic formulations infeasible and/or inefficient much of the time. In this study, we address the need for an effective tool to incorporate potential uncertainties associated with the model parameters into sourcing decisions. In particular, we consider the effects of demand, exchange rate, and freight cost uncertainty into sourcing decisions of a manufacturing company. The solutions are compared to those of the current implementations in practice to show the inadequacy of the deterministic formulations in making real-world decisions. 2 - A Quantitative Foundation for Asset-based Design with Application to Supply Chains RaSheka N. Robinson, Graduate Student, North Carolina A&T State University, 3217 Pleasant Garden Rd, Apt. 1G, Greensboro, NC, 27406, United States, rnrobins@aggies.ncat.edu Traditionally system performance is measured by common metrics, such as cost, quality and delivery that measure the limitations of the system to ‘fix’ them. This paper will build upon these metrics by providing a quantitative basis for strength- based design of systems, using supply chains as a primary motivator. This asset-based approach will measure the assets in the system to determine their contributions. Asset-based views the participants in the supply chain as assets. These assets contribute to system function through various modes. The measures are aggregated according to mean and variance and analyzed to offer a greater understanding of supply chain formation and participant development. WA32

3 - The Decision on Stimulating Shared Supplier Innovation under Market Competition Cong Liu, Huazhong University of Science and Technology, Wuhan, China, cong_liu@hust.edu.cn This paper construct a cost-sharing game model between the manufacturers and the shared-supplier, discussing the influence of competition degree and innovation cost on the equilibrium solution under different situation. The results show that when the competition degree of market is less, the cost-sharing ratio provided by the manufacturer is higher than that of non-cooperation, and the supplier’s innovation level and the manufacturer’s profit are higher than the non- cooperative situation. When the market competition degree is high, the cost-sharing ratio provided by the manufacturer is less than that of non- cooperation. 4 - Distributed Subset Reconfiguration Decisions for Fair Demand and Capacity Sharing in Collaborative Network Ibrahim Yilmaz, State University of New York at Binghamton, Binghamton, NY, 13902, United States, iyilmaz1@binghamton.edu This research aims a distributed subset reconfiguration decisions to enhance fairness and efficiency among a collaborative network of enterprises (CNEs) by Dynamic-distributed sharing protocol (D2-SP). D2-SP is inspired by the principles of Collaborative Control Theory and Contract Net Protocol. A novel protocol is investigated for control of CNEs. The performance of the proposed D2-SP is evaluated by comparing three sharing protocols (SPs): 1) Static-centralized, 2) Static-distributed, and 3) Dynamic-centralized SP. Experiments are conducted to analyze D2-SP in terms of efficiency, fairness, scalability, utilization of resources, and communication overhead. 5 - Flow Time Variability Estimation using Kriging-based Methods to Integrate Simulation and Real Data Hoda Sabeti, West Virginia University, 390 Gilmore St., Morgantown, WV, 26505, United States, hoda.sabeti@gmail.com Quoting a competitive and reliable lead time upon arrival a new order, is a key competitive advantage for manufacturers. Precise lead time quotation requires a good prediction for the mean and variability of the flow time. Due to the uncertainties in manufacturing processes, heteroscedasticity of the variance, and insufficient real time manufacturing data, it is challenging to provide high quality flow time estimation for a new order at its arrival time. This research focuses on predicting the flow time variability. To increase the accuracy, simulation data is integrated with the real data. A stochastic kriging based framework is adopted for infusing the data and predicting the flow time variance. 351C Operation Research Empowering Airline Crew Scheduling and Crew Planning Sponsored: Aviation Applications Sponsored Session Chair: Abdelouahab Zaghrouti, GERAD Research Center, Université de Montréal Campus, 2920, Chemin de la Tour, Montreal, QC, H3T 1J4, Canada, abdelouahab.zaghrouti@gerad.ca 1 - Constraints Aggregation for Large-scale Airline Crew Pairing Problems Francois Soumis, Professor, Polytechnique, Polytechnique, C.P. 6079, Montreal, QC, H3C 3A7, Canada, francois.soumis@gerad.ca, Mohammed Saddoune, François Lessard The crew-pairing problem is modelled as a set-partitioning problem solved by columns generation. However solving a master problem of 50 000 constraints at each of the thousands iterations of the column generation in the branching tree request to much time. In some airlines the Rolling-Horizon heuristic (RH) divides the horizon into 2 days overlapping time slices. However solving 30 problems of 3000 flights requires many days and the quality of solutions in not so good. We introduce the Dynamic Constraints Aggregation to speed-up the master problem and permit to solve a weekly window of 14 000 flights in few hours. The rolling horizon with weekly windows produces solutions improved by up to 5% on salaries. WA33

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