2016 INFORMS Annual Meeting Program

MA56

INFORMS Nashville – 2016

2 - A Modified Age Replacement Model Maryam Hamidi, University of Arizona, mhamidi@email.arizona.edu

4 - Crisis Management Of Customer Sentiments In Social Media: Empirical Study Kyungsun Rhee, University of Washington, 4725 24th Avenue NE, # 405, Seattle, WA, 98105, United States, ksr22@uw.edu In this paper, we will examine how firms strategically bundle news reports in order to intervene diffusion patterns of negative sentiments in social media after the event occur in companies. By conducting text mining and estimating unique data set on Twitter empirically, this paper will contribute to literature by providing managerial insights of ways to control social media.

The classical age replacement model is revisited when the scheduled arrival time of the replacement is also a decision variable in addition to the scheduled preventive replacement time. The equipment is replaced as scheduled unless it breaks down earlier, in which case replacement is performed immediately. If the replacement arrives before it is needed, then inventory cost arises, and if it is not available when needed then shortage cost of delayed production is the loss of the company. The production cycle is repeated without any change, therefore the expected net cost per unit time is computed by renewal theory. The existence of finite optimum is proved and the computer method is introduced to find it. 3 - Maximizing Availability In Operations And Maintenance Planning Of Airline Fleet Javad Seif, Graduate Research Assistant, University of Tennessee- Knoxville, Tullahoma, TN, 37388, United States, jseif@utk.edu, Andrew Junfang Yu In this paper, operations and maintenance planning (OMP) is modeled as a mixed-integer linear program with a case study in the airline industry. The objective is to maximize the availability of a fleet of aircraft over a planning horizon subject to their operations and maintenance requirements. An existing flight and maintenance planning (FMP) model is significantly extended by generalizing it to an OMP model, which makes the model more practical and suitable for a wider range of applications in both manufacturing and service industries. Chair: Wael Jabr, Georgia State University, 35 Broad Street, Robinson College of Business, Atlanta, GA, 30303, United States, wjabr@gsu.edu 1 - Antecedents And Consequences Of Information Augmentation In Make-to-order Electronic Supply Chain Ling Xue, Georgia State University, lxue5@gsu.edu Arun Rai, Peijian Song, Cheng Zhang In this study, we consider a phenomenon of information augmentation: in addition to passing the demand information from the consumers to the supplier, the retailer generates ad hoc coordination information to direct the order- fulfilment processes at the supplier side. Using transaction-level data from an international make-to-order supplier chain, we find that information augmentation is positively associated with product customization level and negatively associated with supplier relationship. We also find that information augmentation leads to higher fulfilment costs and lower probabilities of product return, and higher net profits for the retailer. 2 - Opening The Black Box: The Impact Of Telehealth And Latent Health Status On Patient Readmissions Sezgin Ayabakan, The University of Baltimore, Baltimore, MD, We investigate the effect of unobserved patient health status on patient readmission rates and the impact of telehealth on patient health status. We implement a hidden Markov model with a large, inpatient panel dataset of Congestive Heart Failure patient visits along with the American Hospital Association IT Supplement data. We reveal latent health states of patients and find that telehealth exerts a positive impact only on patients in less healthy states, while this impact diminishes as patients’ health improves. These results suggest that focusing solely on readmission rates can be misleading, without regard to patients’ health status. 3 - Leveraging Customer Feedback Through App Reviews Kambiz Saffarizadeh, Georgia State University, Atlanta, GA, United States, ksaffarizadeh1@Student.gsu.edu, Wael Jabr, Mark Keil Online app markets (e.g. Apple App Store) exhibit heavy customer engagement in the form of reviews that could help software developers adjust to user needs and become more competitive in crowded app markets. Using a panel dataset on 12,231 apps and document similarity methods, we develop a model that relates app success to developers’ integration of user feedback. 21201, United States, sayabakan@ubalt.edu Indranil R Bardhan, Zhiqiang Eric Zheng MA56 Music Row 4- Omni Economics of IS in the Age of Big Data Sponsored: EBusiness Sponsored Session

MA57 Music Row 5- Omni

The George B. Dantzig Dissertation Prize Invited: The George B. Dantzig Dissertation Prize Invited Session

Chair: Henri Groenevelt, University of Rochester, W. E. Simon Graduate School of Business Administration, Rochester, NY, 14627, United States, groenevelt@simon.rochester.edu 1 - Dynamic Monitoring And Control Of Irreversible Chronic Diseases With Application To Glaucoma Pooyan Kazemian, Harvard Medical School, Boston, MA, United States, pooyan.kazemian@mgh.harvard.edu To effectively manage chronic disease patients, clinicians must know (1) how to monitor each patient (i.e., when to schedule the next office visit and which subset of tests to take), and (2) how to control the disease (i.e., what levels of controllable risk factors will sufficiently slow disease progression). Our research addresses these questions simultaneously and provides the optimal solution to a novel linear quadratic Gaussian state space model. Glaucoma is discussed as a case study. 2 - Multiple Criteria Decision Engineering To Support Management In Military Healthcare And Logistics Operations Nathaniel D. Bastian, Pennsylvania State University, 137 Arbor Bluff Drive, Pleasant Gap, PA, 16823, United States, nathaniel.bastian@fulbrightmail.org The U.S. Military Health System (MHS) is a unique, complex health system with many healthcare and logistics challenges requiring effective management. We introduce multiple criteria decision engineering methods to assist strategic decision-making and to support the complex planning and management of MHS resources, personnel, logistics, and financial incentives. This contribution has helped senior military leaders make better, more informed, quicker, data-driven resource management decisions amongst conflicting objectives, along with the risks and uncertainties associated with those decisions. 3 - Smarter Tools For (Citi) Bike Sharing Eoin O’Mahony, Uber, Itaca, NY, United States, eoin@uber.com Bike-sharing systems are becoming increasingly prevalent in urban environments. These systems generally consist of stations where users can take out or drop off bikes, and may return a bike to a free dock at any station. New York City launched the largest bike sharing system in North America, Citibike, in May 2013 with over 300 stations and 5000 bikes. We have worked with Citibike since launch, using analytics and optimization to change how they manage the system. In this talk we will cover two areas of our work with Citibike; planning through data and rebalancing with optimization. 4 - Optimizing A Menu Of Multi-format Subscription Plans For Ad-Supported Media Platforms Vamsi Krishna Kanuri, University of Miami, 501 Kosar Epstein Bldg, School of Business Administration, Coral Gables, FL, 33146, United States, vkanuri@bus.miami.edu Media content distribution has changed extensively in the past decade. Content, which was once distributed through traditional formats such as television, radio and print, is now available through contemporary digital formats such as smartphone and tablet apps, with many possible versions (e.g., presence or absence of ads.) Consequently, many media firms facing markets comprised of heterogeneous consumers with varying content consumption preferences are now offering ‘menus’ of multi format-version subscription bundles for their consumers to choose from. Yet, little systematic model-based guidance exists for configuring and pricing menu options. Moreover, most media firms are ‘audience- building platforms’ that serve at least two distinct customer groups (content consumers and advertisers) with inter-related demands. Therefore, constructing a menu of content subscription bundles that maximizes total profit from both consumers and advertisers is a formidable challenge. This research proposes a theory-driven implementable model-based approach that can aid media platforms in addressing this challenge.

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