2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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2 - Managing Demand Uncertainty in Collaboration Mechanism
Design for Carrier Alliances
Yuhan Wang, University of California, Irvine, CA,
Luyi Gui, Ozlem Ergun
A carrier alliance refers to a cooperative among transportation companies that
often collaborate via sharing service network capacities. In this paper, we consid-
er a type of collaboration mechanism via capacity exchange prices that has been
widely adopted in practice, and aim to provide a comprehensive analysis of its
coordination effectiveness under demand uncertainty. In particular, we analyze
the structure of service networks of sea cargo alliances in practice and develop a
decomposition algorithm to not only much simplifies the problem but also
enables a detailed analysis into the structure of a robust exchange prices and the
capacity-demand properties of networks where such prices exist.
3 - Interdiction Learning-based Approaches To Combat Security
Threats On Information Systems
Forough Enayaty Ahangar, University of Arkansas, Fayetteville,
AR, United States, Chase Rainwater
We consider a information system connected across a network of servers. In part
one of the talk, we solve an interdiction-based model to strategically determine
how content is allocated amongst available servers so to minimize the impact of a
denial of service attack. In part two of the talk, we provide an operational
framework for identifying network threats across the chosen network structure
via a learning-based framework. Roles of optimization within this framework are
highlighted and the methodology is applied to network data taken from a
national laboratories computer logs.
4 - Optimal Linepack Planning Models For Gas Transmission Network
Trung Hieu Tran, Postdoctoral Research Fellow,
The University of Warwick, Coventry, CV4 7AL, United Kingdom,
Simon French, Rhys Ashman,
Edward Kent, Mark Hamling, Ben Dickel
National Grid, the gas network operator in the UK, experiences challenges
maintaining pressure and linepack (quantity of gas in network) limits due to the
transient behaviour of customers in an open market. In this paper, 2 mixed-
integer programming models are proposed for optimal linepack planning (i.e.
considering the compressibility of natural gas in pipelines) to compensate for the
fluctuation of gas flows. The first model minimizes total deviation between
simulated & target linepack such that all demand is satisfied. The second model
determines time and actions to minimize total cost for resolving linepack deficit.
The efficiency of models has been validated in case studies at National Grid.
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Legends G- Omni
Health Care, Modeling VX
Contributed Session
Chair: Sharan Srinivas, PhD Candidate and Research Assistant, The
Pennsylvania State University, 310 Leonhard Building, University Park,
PA, 16802, United States,
1 - Interaction Between Operational Efficiency And Doctor Incentives
In Outpatient Services
Guoming Lai, UT Austin, 1 University Station, B6500, Austin, TX,
78712, United States, Xiaofang Wang
This paper studies the interaction between a doctor and a population of patients
in a congested health service delivery system. The doctor’s prescribing decisions
depend on her diagnostic/treatment ability, level of altruism and the institutional
framework. Some patients are strategic and decide to see this doctor based on
perceived quality, congestion and monetary costs. Within such a setting, we study
the socially optimal decisions and provide policy insights.
2 - Equitable Nurse Scheduling By Goal Programming
Esra Agca Aktunc, Assistant Professor, Kadir Has University, Kadir
Has Caddesi Cibali, Istanbul, 34083, Turkey,
Hospitals have to provide continuous service by employing the shift system and
workers, mainly doctors and nurses, are required to work efficiently to avoid
errors. Quality of healthcare services can be improved significantly if the nurse
shifts are scheduled according to nurses’ preferences and by distributing the
workload equitably. Schedules should also abide by hospital policies and
workload requirements in each shift by assigning nurses with different skill sets.
In this study, monthly nurse scheduling problem is modeled and solved by goal
programming observing goals that represent nurse and patient satisfaction with
fairness measures such as the number of night shifts and weekend shifts.
3 - An Approximate Solution Approach For Blood Management When
There Are Multiple Independent Sources Of Supply
David C Novak, Associate Professor, University of Vermont, 310
Kalkin Hall, 55 Colchester Avenue, Burlington, VT, 05405-0157,
United States, Marilyn T Lucas,
S. Karti Puranam
We present an approximation method to solve the infinite horizon, fixed lifetime
perishable, inventory model with a lifetime of m > 2 periods, where there are two
independent sources of supply. One source is blood ordered by the blood bank.
The other source is blood that is randomly transferred from smaller, lower-usage
hospitals in a regional blood exchange network to blood bank. We formulate a DP
to solve the multi-period cost minimization problem and test our solution
approach both theoretically and empirically.
4 - Improve Service Levels And Reduce Labor Cost Using Different
Float Nursing Level Strategies Under Staff Absences In Hospitals
Kamil Ciftci, Lehigh University, 200 West Packer Avenue,
Bethlehem, PA, 18015, United States,
Nurse shortage is one of major problems in Healthcare Systems. Float nurse
strategy is an alternative solution method in hospitals to minimize nurse shortage
issue. In this research, we investigate service level, staff absences and economic
effects of nurse shortage to find a core regular unit nurse level with flexible float
nursing strategy. Under different regular nurse core levels, optimal service and
float nurse levels are determined. Performance of our model is also compared
with different service level methods in literature. Case study results demonstrate
our model provide higher service level and decrease labor cost comparing with
current practice in a local hospital.
5 - Design Of Multi-stage Multi-provider Hybrid Appointment System
For Patient Scheduling Under Uncertainty
Sharan Srinivas, PhD Candidate and Research Assistant,
Pennsylvania State University, 310 Leonhard Building,
University Park, PA, 16802, United States,
Arunachalam Ravindran
Recent research focuses on designing hybrid appointment systems (HAS) for
patient scheduling by combining open access and pre-booking scheduling
methods. However, the multi-stage nature of patient flow, patient availability and
uncertainties in outpatient clinics are rarely integrated in the design. We propose
a deterministic model, and scenario based Monte Carlo approach to address this
gap. The proposed approach aims to improve patient satisfaction and resource
utilization by determining the percentage of appointments reserved for pre-
booking and open access. A case study with real data from a Family Medicine
clinic is used to show the feasibility of the proposed approach.
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GIbson Board Room-Omni
Marketing V
Contributed Session
Chair: Ryan Choi, Assistant Professor of Marketing and SCM, Eastern
Michigan University, 300 W. Michigan Ave., College of Business,
Eastern Michigan University, Ypsilanti, MI, 48197, United States,
1 - Investigating The Impact Of Social Influence On The
Personalization-privacy Paradox: An Eye Tracking Study
Thomas Frick, PhD Student, Rotterdam School of Management,
Burgemeester Oudlaan 50, Rotterdam, 3062PA, Netherlands,
Ting Li, Paul Pavlou
Using consumers’ personal information to personalize ads does not only increase
perceived ad relevance but also triggers consumer privacy concerns. To study this
personalization-privacy paradox, we use eye-tracking technology and investigate
how social influence affects consumers’ perceived ad relevance and privacy
concerns. By objectively measuring visual attention, we obtain a rich
understanding of how users affectively and cognitively process information and
assess ads. Our results provide insights into the mediating role of attention within
the personalization-privacy paradox.
2 - Non-contractual Customer Retention In Multichannel Settings
Chun-Wei Chang, Assistant Professor, Governors State University,
1 University Parkway, University Park, IL, 60484-0975,
United States,
We present a framework for estimating multichannel customer relationship
dynamics in a non-contractual setting that flexibly allows for relationship revival
and investigates the effects of different channel experiences and marketing
communication on retention and profitability. We use a multi-segment,
multivariate hidden Markov modeling framework to model three managerially
relevant customer behaviors: purchase amount, purchase incidence, and channel
choice. We uncover two latent relationship states that customers migrate to and
from - an active state and an inactive state characterized by different levels of
purchase frequency, responsiveness to marketing, and profitability.
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