2016 INFORMS Annual Meeting Program

SD65

INFORMS Nashville – 2016

SD65 Mockingbird 1- Omni Analytical Models Sponsored: Information Systems Sponsored Session Chair: Zhe Zhang, University of Texas Dallas, University of Texas Dallas, Richardson, TX, 75080, United States, zxz145430@utdallas.edu 1 - Altruism or Shrewd Business? Implications Of Technology Openness on Platform Innovations And Competition Hongyan Xu, Chongqing University, School of Economics & Business Admin, Chongqing, 400030, China, xuhongyan@cqu.edu.cn, He Huang, Geoffrey Parker, Yinliang Tan There is a growing number of platforms that commit to open their technologies. In contrast to the previous literature focusing on the network effect, our study reveals a novel explanation on why firms are willing to open their technologies. The main intuition is due to the fact that technology openness can alleviate the unwarranted innovation competition caused by the uncertainty belonging to technology closeness. We also discuss the impact of technology openness on individual and total innovations and illustrate that this intuition is robust under several extended models. 2 - Share Your Health Information And Help Me Save Your Life: Effects Of Hie Use On Healthcare Outcomes – An Empirical Investigation Emre Demirezen, School of Management, Binghamton University, Binghamton, NY, United States, edemirezen@binghamton.edu Eunho Park, Ramkumar Janakiraman, Subodha Kumar In the last decade, the U.S. government has been aggressively promoting the use of electronic health records and the establishment of regional healthcare information exchanges (HIEs). HIEs facilitate the exchange of electronic health information among healthcare practitioners that is considered to be beneficial for the society. However, the real benefits of HIEs are not well understood. Hence, we work with an HIE provider based in the state of New York to investigate the benefits of HIEs. 3 - Platform Integration In The Age Of The Internet Of Things Burcu Tan, Tulane University, btan@tulane.edu, Edward G Anderson, Geoffrey Parker Many two-sided platforms (e.g., eBay, Google, iOS, Android, Twitter, Amazon) provide development tools, such as software development kits (SDKs) and application programming interfaces (APIs), to facilitate third party content development. While crucial to platform success, these tools are costly to create. We develop an analytic model to explore the key trade-offs behind investment in development tools and how that investment coordinates with pricing decisions in a two-sided market. We model these decisions under various scenarios including monopoly and competitive platforms as well as symmetric and asymmetric platforms. 4 - Interoperability, Organization Form And Cooperative Games In Public Safety Networks Barrie R Nault, University of Calgary, nault@ucalgary.ca Hong Guo, Yipeng Liu We analyze tradeoffs in the provision of public safety networks when network assets are distributed across districts, causing a district to value network assets in other districts as well as in its own district. Modeling centralized and decentralized organization forms we incorporate interoperability among distributed network assets. We find that the optimal/equilibrium interoperability increases in the cross-district spillovers from network assets. We show that the districts’ incentive to adopt centralized provision depends on the sharing rule for the cost of interoperability effort, and we find that certain sharing rules have a corresponding cooperative game analogue.

SD67 Mockingbird 3- Omni Foundations of Accuracy for Additive Manufacturing Sponsored: Quality, Statistics and Reliability Sponsored Session Chair: Qiang Huang, University of Southern California, Los Angeles, CA, United States, qiang.huang@usc.edu Co-Chair: Arman Sabbaghi, Purdue University, West Lafayette, IN, United States, sabbaghi@purdue.edu 1 - Deformation Model Transfer Via Equivalent Effects Of Lurking Variables In Additive Manufacturing Arman Sabbaghi, Assistant Professor, Purdue University, 150 N. University Street, West Lafayette, IN, 47907, United States, sabbaghi@purdue.edu, Qiang Huang The transfer of a deformation model across different settings of lurking variables in additive manufacturing is addressed with a novel framework that fuses the Rubin causal model with the effect equivalence concept. Model transfer in this general framework is formulated through the total equivalent amount of the lurking variables in terms of a base factor with respect to a key model feature. The weakest sufficient condition on the data-generating and assignment mechanisms in a new setting is identified that permits inference for its total equivalent amount with respect to the mean. Bayesian methodology for modeling the total equivalent amount are developed under this condition. 2 - Implications Of Assuming Incorrect Model Equivalence For Additive Manufacturing Matthew Plumlee, University of Michigan, mplumlee@umich.edu Additive manufacturing control is often limited by the few number of homogeneous parts produced. Thus purely data-driven approaches can fail to give anything but large uncertainty quantification bounds for producing a new part. One solution to this problem is to let additive manufacturing systems to learn from each other by assuming that they could produce exactly the same resulting parts. In this talk, some preliminary results are used to explain the potential ramifications of assuming that a model for one additive manufacturing system can produce similar results as another system under a specialized design plan. 3 - Prescriptive Analytics For Understanding Of Out-of-plane Deformation In Additive Manufacturing Yuan Jin, University of Southern California, Los Angeles, CA, 90089, United States, yuanjin@usc.edu, Joe Qin, Qiang Huang Geometric accuracy control is crucial to fulfill the promise of additive manufacturing (AM). We have been establishing a generic methodology to represent, predict and compensate 3D deformation of AM built products. Built upon our previous study, this work aims at 1) developing a prescriptive approach to understand the out-of-plane deformation due to complex inter-layer interactions; 2) establishing a Bayesian approach to infer the predictive deformation model for out-of-plane complex shapes. Experiments are conducted to validate the prescriptive model. 4 - Shape Deviation Modeling For Additive Manufacturing With Different Process Parameters Longwei Cheng, HKUST, lchengae@connect.ust.hk Reducing the dimensional error of the fabricated products is a critical quality issue for the wide application of additive manufacturing (AM) technologies in industry. Process parameters in fabrication significantly affect the shape deviation of products. In this work, we establish an in-plain shape deviation prediction scheme that predicts the final shapes of products with the information of both process parameters and 2D input shapes. The corresponding shape error compensation strategy is derived, which greatly improves the dimensional accuracy of products. The methodology is validated through experimental studies of fused deposition modeling (FDM) process.

SD66 Mockingbird 2- Omni 2016 QSR Best Student Paper Competition Sponsored: Quality, Statistics and Reliability Sponsored Session Chair: Chiwoo Park, chiwoo.park@eng.fsu.edu 1 - 2016 QSR Best Student Paper Competition

Chiwoo Park, Florida State University, chiwoo.park@eng.fsu.edu Best Student Paper Award recognizes excellence among QSR student members. Four finalists for the Best Student Paper Award will make presentations. The winner will be announced at the QSR business meeting during the conference.

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