Informs 2015

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INFORMS Philadelphia – 2015
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3 - Assessing the Relationship of Supply Chain Risk Management to
Quality Management
Tyler Florio, East Carolina University, College of Business,
Greenville, NC, 27858, United States of America,
Scott Dellana
This research explores the relationship between an organization’s supply chain
risk management maturity (SCRMM) and quality management (QM) practices.
QM practices and SCRMM were measured using a survey questionnaire of
organizations in the USA. ISO 9001 status was also determined. Preliminary
results suggest that ISO 9001 is not related to SCRMM, while QM is related to
SCRMM. Organizations with more mature quality management programs appear
to also have more mature risk management programs.
4 - Mitigating Contagion Risk in Supply Chains
Alireza Azimian, Wilfrid Laurier University, 55 Hickory St,
E, Waterloo, ON, N2J 3J5, Canada,
Hamid Noori, Marc Kilgour
Rivals often benefit from each other’s failures because of demand shifts; however
some incidents may adversely affect an entire industry causing all firms to suffer.
We explore whether investment in the safety measure of the rivals who just
comply with minimum standards can be employed as a risk mitigation strategy.
5 - Information Security Investments: Better Together?
Lisa Yeo, Assistant Professor, Loyola University Maryland, 4501
N. Charles St., Sellinger Hall 306, Baltimore, MD, 21210, United
States of America, , Erik Rolland, Bora Kolfal,
Raymond Patterson, Hooman Hidaji
Security breaches are often the result of the weakest link in a chain of related
businesses; a firm may have strong security practices and yet still experience a loss
due to a weaker business partner. We propose allocating some firm resources to a
supplier in order to improve that supplier’s security posture with possible positive
spillover to a competitor. In a symmetric duopoly setting, where demand reacts to
breach notification, we find the conditions in which a shared supplier is desirable.
SC79
79-Room 302, CC
Software Demonstration
Cluster: Software Demonstrations
Invited Session
1 - Provalis Research – How to Analyze Big Text Data with Provalis
Text Analytics Tools
Normand Peladeau, CEO, Provalis Research
Provalis Research will showcase its integrated collection of text analytics software.
QDA Miner is an easy to use qualitative and mixed methods software that meets
the needs of researchers performing qualitative data analysis and would like to
code more quickly and more consistently larger amounts of documents. It offers
high level computer assistance for qualitative coding with innovative text search
tools that help users speed up the coding process as well as advanced statistical
and visualization tools. Users with even bigger text data, can also take advantage
of WordStat. This add-on module to QDA Miner can be used to analyze huge
amounts of unstructured information, quickly extract themes, find trends over
time, and automatically identify patterns and references to specific concepts using
categorization dictionaries.
2 - SAS Education Practice – Introduction to SAS Data Mining
Tom Bohannon, Analytical Consultant, SAS,
, F. Michael Spped, PhD,
Analytical Consultant, SAS,
This introduction covers the basic skills required to assemble analysis flow
diagrams using the rich tool set of SAS Text Mining. Also, participates will be
shown how unstructured data can be converted into numeric data that can
utilized for pattern discovery and predictive modeling. Simple example will be
used to illustrate the basic concepts of text mining.
Sunday, 4:30pm - 6:00pm
SD01
01-Room 301, Marriott
Military O.R. and Applications II
Sponsor: Military Applications
Sponsored Session
Chair: Michael Hirsch, ISEA TEK, 620 N. Wymore Rd., Ste. 260,
Maitland, FL, 32751, United States of America,
1 - Efficient Information Distribution in the Presence of Unknown
Cognitive Capacity in HRI
Siddhartha Mehta, Research Assistant Scientist, University of
Florida, 1350 N. Poquito Rd., Shalimar, FL, 32579, United States
of America, , Monali Malvankar,
Eduardo Pasiliao
In military applications, unmanned aerial vehicles (UAVs) remotely operated by a
ground crew may require significant human interaction. UAVs share information
with human operators to perform geographically-dispersed priority-based tasks
within a specified time. Asymmetric information including cognitive capacity and
efficacy exists within the groups of operators. We develop a model incorporating
asymmetric information to optimally share information by maximizing efficiency
of the entire system.
2 - Robust and Adaptive Optimization Applied to Operator
Task Scheduling
Luca Bertuccelli, UTRC, 411 Silver Lane, East Hartford, 06107,
United States of America, ,
Taimoor Khawaja, Cali Fidopiastis
This work is concerned with human-in-the-loop decision making when the
human is interacting with robust scheduling systems. We provide a
comprehensive literature review of the area of robust optimization as applied to
human-in-the-loop scheduling. We then demonstrate the impact of uncertainty
in scheduling problems solved in both a “one-shot” optimization and a receding
horizon framework with a simulated user-in-the-loop.
3 - A Bayesian Framework for Integrating Human and
Machine Perceptions
Emily Doucette, Air Force Research Laboratory,
101 W. Eglin Blvd., Eglin AFB, United States of America,
Current methods for human-autonomy interaction are largely implemented
through rigid schemes that transfer control between humans and autonomy. The
authors propose a generalizable framework utilizing Bayesian estimation and
decision theory that incorporates the concepts confidence and consequence in all
agents in a human-autonomous system to yield a decision structure for
heterogeneous teams, where a human supervisor is aided by a risk-based
representation of the target state estimate.
4 - A Framework Supporting the Separation of Cognitive
Performance from Execution Environment
Katie Mcconky, Assistant Professor, Rochester Institute of
Technology, 81 Lomb Memorial Dr, Rochester, NY, 14623,
United States of America, Moises Sudit,
Hector Ortiz-pena
This project aims to enhance a decision maker’s mission planning capabilities by
providing decision aids that predict anticipated human performance based on
civil, environmental and physical conditions. A framework is presented that
isolates human performance factors from environmental and situational mission
characteristics that facilitates the ability to estimate the capability of units to
accomplish tasks to expected standards under specified conditions.
SD01