2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
299
Privacy In Social Networks; Do People Care? A Regulatory
Focus Theory Perspective
Behrooz Davazdahemami, Doctoral Student, Oklahoma State
University, 4599 N Washington St, Apt 40A, Stillwater, OK, 74075,
United States, , Pankush Kalgotra
Relying on the Regulatory Focus Theory this study extends information privacy
literature to explain the reason for relatively low influence of individuals’
information privacy concerns on their intention to share information on social
networking websites. The proposed model was empirically tested (n=688) and
sufficient support was provided for all the hypothesized relationships in the
model. Results indicate that accounting for situational factors in assessing the
effect of privacy concerns on willingness to share can significantly better explain
the real behaviors of social network users.
Candidate List Strategies For Resource Constrained
Project Scheduling
Christopher Riley, Assistant Professor of Management, Delta State
University, DSU Box 3275 - Broom 252, 1003 West Sunflower
Road, Cleveland, MS, 38733, United States, ,
Cesar Rego
Certain metaheuristic methods can benefit greatly from an appropriate candidate
list strategy. We present our findings on the analysis of candidate lists for tabu
search and filter-and-fan approaches to solving the resource constrained project
scheduling problem. Both new candidate list strategies as well as strategies from
the literature are considered.
A Model Of Concession Tracking To Improve Fairness Of
Repetitive Shared Resource Use
Dmitry Gimon, Assistant Professor, Fort Hays State University,
600 Park St., Hays, KS, 67601, United States,
Fair use of a shared resource is a common task in everyday life and in industry.
We propose a model to improve its fairness using the theory of reciprocal
concessions and refined preference functions. Our simulation demonstrates that
our proposed model results in fairer use of shared resources.
I Have No Data! A Practical Introduction To Range Building
Gustavo Vinueza, Director of Custom Solutions, Palisade
Corporation, 798 Cascadilla Street, Palisade Corporation, Ithaca,
NY, 14850, United States,
Simulation models, they require a set of inputs translated into probabilistic
distributions. Fitting the data to a distribution or specific experience from expert
teams in the shape of 3-point estimation. Nevertheless, there are situations in you
say “I have no data, so I can t generate any distribution”. The work presented is
the beginning of a series of practical exercises aimed for people asked to give an
opinion, a report or a napkin draft of numerical values which don t necessarily
have organized supporting data. A step by step workflow is proposed along with a
framework on how to rapidly generate estimations that are on the same
wavelength of the people requiring them.
New Technologies And Women’s Empowerment
Jimin Han, SolBridge International School of Business,
Daejeon, Korea, Republic of,
Sung-Tae Kim
Prior research has claimed that energy poverty disempowers women in the ghetto
areas and tends to increase illiteracy among their children. Such research also
discovered that providing them ample access to energy and new technologies
might break unfair social norm on them. However, the major barrier for the fast
distribution of new technologies is the lack of understanding existing power
relations between genders and the weak bargaining power of women within the
households. In this regard, our study attempts to investigate (1) factors that might
help improve women’s decision-making power and (2) the relationship between
those factors and women’s decision-making power.
Voluntary Delisting & Executive Compensation
Juhi Bhardwaj Sapra, PhD Student, Rensselaer Polytechnic
Institute, 110 8th Street, Troy, NY, 12180, United States,
this paper explores the event of voluntary delisting in the us. Delisting is defined
as the process where the firm listed on an exchangeis removed. A firm can
voluntarily request to be delisted and become a privately traded firm. We
primarily explore the question: does executive compensation structure influence
the decision to delist? Since executive compensation can be aligned with
shareholder interests, we attempt to understand if it influences the managerial
decision to become a private firm. If the firms choose exit the public trading in
order to avoid costs, we try to explore the extent managerial compensation,
would explain the decision to delist.
Does The GLL-APS Model Reward Investor Over Time?
Maria Luisa Ceprini, Research Associate, Massachusetts Institute of
Technology, 100 Main Street, Cambridge, MA, 02142,
United States, , John D Little
Our goal is to create an investment portfolio that adapts to market conditions and
rewards customer expectations over time. Answers to an interview questionnaire
assess the key attributes creating a customer profile to guide the investor, trading
risk versus expected return over time. Afterwards, the Generalized Little’s Law-
Asset Picking System model selects assets and number of shares per asset to build
the portfolio according to the investor profile. Periodic updates check Average
Portfolio Expected Return and Average Asset Systematic Risk performances.
A Trilevel Optimization Model For Resilient Transportation
Network Design
Mohammad Rahdar, Iowa State University, 3130 Turnberry CT,
Unit 195, Ames, IA, 50014, United States, ,
Guiping Hu, Jing Dong, Lizhi Wang, Xuesong Zhou
We propose a trilevel optimization model for transportation network design,
which improves the resiliency of the network against uncertain disruptions. The
middle and bottom levels are the network interdiction problem, in which we
identify the worst-case scenario disruptions that could lead to a maximal cost to
the transportation system. The top level takes the system perspective, which
designs the optimal strategy to expand the existing transportation network so that
it confronts the worst-case scenario disruptions in the most resilient manner.
Team Coordination In Service Organizations: Antecedents And
Consequences Of Customer Involvement
Onyi Nwafor, University of Houston, 5710 Ballina Canyon Ln,
Houston, TX, 77041, United States,
Service encounters demand both employee and customer participation. As a
result, coordination in the service context should involve the integration of
customer contributions (knowledge, skills, and abilities) and employee
contributions to service production and delivery. Yet, existing coordination studies
set in service environments continue to focus on how best to integrate employee
contributions alone. This study explores the effects of customer involvement on
coordination in service environments. I also propose and test how organizations
can promote customer involvement. Results of my analyses have important
implications for both theory and practice.
Decision Support For Dynamic Adjusting Emergency
Department Workforce
Phichet Wutthisirisart, Mayo Clinic, 200 First Street SW, Harwick
Bldg. 2, Rochester, MN, 55905, United States,
Mustafa Y Sir, David Nestler,
Thomas Hellmich, Kalyan Pasupathy
Emergency departments (EDs) often face changes in number of patients and level
of illness severities throughout a day. The goal of this study is to develop a
method to best allocate available resources, such as residents and scribes, to each
physician-led care team considering patient demand volume and severity. An
optimization model was proposed to minimize the number of patient care hours
in excess of the team capacity. The proposed model was implemented into a
decision support system through the ED Clinical Engineering Learning Lab. It
compares the original master schedule with the optimized schedule based on the
changes in resource availability, and provides severity index as decision measure.
Predictive Analytics Approach To Analyze Vectorcardioram To
Discern Myocardial Infarcted And Healthy Heart
Rupesh Agrawal, Research Assistant, Oklahoma State University,
408 Business Building, Spears School of Business, stillwater, OK,
74078, United States, Rahim Sewani,
Bruce Benjamin, Dursun Delen
Heart disease causes 610,000 deaths among the US population per year. Coronary
heart disease: myocardial infarction causes ~60% of deaths. This study uses
predictive modeling on Vectorcardiogram (VCG) derived RR and QT features to
discern healthy and diseased patients. Neural networks (ANN), Support vector
machine (SVM), Decision tree (C5), and Ensemble model were developed and
tested on a 10 K cross-validation data sample. SVM and ANN models resulted in
88.14% and 86.4% overall accuracy. C5 algorithm led to a sensitivity of 100%,
specificity of 96.55% and overall accuracy of ~98%. Ensemble models led to a
sensitivity of 96.67%, specificity of 100.00% and overall accuracy of ~98%.
A Tale Of Three States Factors Influencing Public Private
Partnership Acceptance
Vandit Shah, California State University-Fullerton, 2404 Nutwood
Avenue, Apt K-12, Fullerton, CA, 92831, United States,
, Deepak Kanhaiyalal Sharma
Several infrastructure projects have been successfully pursued through Public
Private Partnerships (PPPs) across the United States. While the PPPs remain same,
the PPP acceptance rate across the US has been significantly different. While
major emphasis has been laid to identify PPP success factors little has been done
to identify factors differentiating states’ PPP acceptance. This poster presents the
factors that differentiate the states’ PPP acceptance. Using Principal Component
Analysis (PCA) we found average education, gender distribution, traffic volume
and daily vehicle miles traveled as the most influential factors affecting PPP
acceptance.
POSTER SESSION