INFORMS Nashville – 2016
116
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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.edu1 - 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.eduEunho 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.caHong 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.
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Mockingbird 2- Omni
2016 QSR Best Student Paper Competition
Sponsored: Quality, Statistics and Reliability
Sponsored Session
Chair: Chiwoo Park,
chiwoo.park@eng.fsu.edu1 - 2016 QSR Best Student Paper Competition
Chiwoo Park, Florida State University,
chiwoo.park@eng.fsu.eduBest 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.
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.eduCo-Chair: Arman Sabbaghi, Purdue University, West Lafayette, IN,
United States,
sabbaghi@purdue.edu1 - 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.eduAdditive 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.hkReducing 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.
SD65