2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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3 - Queue Now Or Queue Later
Brett Hathaway, Doctoral Candidate, UNC Chapel Hill, Chapel Hill,
NC, United States, , Seyed
Emadi, Vinayak Deshpande
We study caller redial behaviors using call center data from a US-based bank. We
show which factors affect the probability of redialing and the time between queue
abandonment and redial. Using structural estimation, we show through
counterfactual experiments how a center with callers who redial performs under
various routing policies.
4 - Access Times In Appointment-driven Systems And Level-
dependent MAP/G/1 Queues
Petra Vis, VU Amsterdam, De Boelelaan 1105, Amsterdam, 1081
HV, Netherlands,
Petra Vis, Centrum Wiskunde & Informatica, Amsterdam,
Netherlands, , Rene Bekker
We study access times in appointment-driven systems. The access time is the
number of days between a request for an appointment and the day that the
appointment can take place. To meet target access times, we allow for
overbookings, as they often occur in practice. Applications of this type of systems
can be found in health care; e.g., patients making appointments with a doctor. We
argue that such a system can naturally be modelled as an MAP/G/1 queue; the
level corresponds to the access time and the phase to the dynamics of the number
of free slots at the first available day. To allow for overbookings, we analyze a
level-dependent version of the MAP/G/1 queue, leading to intuitively appealing
results.
TD34
204-MCC
Joint Session HAS/MSOM-HC: Care Transition Policy
and Management
Sponsored: Manufacturing & Service Oper Mgmt, Healthcare
Operations
Sponsored Session
Chair: Nan Kong, Purdue University, West Lafayette, IN, United States,
1 - System Modeling For Patient Transitions Within Hospital
Hyo Kyung Lee, University of Wisconsin Madison, 1, Madison, WI,
1, United States, Jingshan Li, Albert J.
Musa, Philip A. Bain
Among various issues in healthcare delivery, many complex and critical problems
occur at the interfaces of healthcare systems. A patient’s hospital stay may
encompass various care units, but due to limited capacity, substantial amount of
patients experience delay during the transition. This not only impacts the care
quality and patient satisfaction, but in some cases is directly associated with
mortality risk. Thus, to contribute to this end, we present a Markov chain model
to study the transitions between emergency department, intensive or critical care
unit, and hospital ward in community hospitals. Furthermore, an iteration
method is introduced to evaluate the performance.
2 - Reduce COPD Readmission - Risk Identification And Patient-
centered Intervention
Xiang Zhong, University of Wisconsin, 1513 University Avenue,
Room 3235, Madison, WI, 53706, United States,
Cong Zhao, Philip Bain, Albert Musa,
Craig Sommers
30-day hospital readmission has been established as a critical performance
indicator in promoting quality and patient-centered care. Individuals with serious
chronic conditions such as chronic obstructive pulmonary disease (COPD) suffer
high readmission risks and incur significant hospital penalty cost. To reduce COPD
readmission, it’s important to provide tools for physicians and hospitals to manage
patients post discharge. In this study, we build statistical models to identify the
risk factors for COPD readmission. Based on patients’ risk levels, different patient-
centered intervention policies prior to discharge and post discharge are developed.
3 - Optimal Inpatient Discharge Planning Under Uncertainty
Maryam Khatami, Texas A&M University, 4050 ETB, College
Station, TX, 77840, United States,
Mark Lawley, Nan Kong, Michelle M. Alvarado
We study the inpatient discharge planning problem to enable efficient design of
optimal discharge plans on a daily basis. If some of the discharge processes are
delayed, the ensuing backup in the upstream units will cause inpatient admission
delays. Hence, it is critical to tradeoff competing issues of upstream patient
boarding (e.g. Emergency Department (ED) boarding), inpatient discharge
lateness, and Inpatient Unit (IU) workload integration. We develop a novel two-
stage stochastic programming model with uncertain IU discharge processing time
and IU bed request time. Using data from a Texas hospital, we calibrate our model
and fine-tune our solution method.
TD35
205A-MCC
On Demand Services
Sponsored: Manufacturing & Service Oper Mgmt, Service
Operations
Sponsored Session
Chair: Pnina Feldman, University of California-Berkeley, Haas School of
Business, Berkeley, CA, 94720, United States,
Co-Chair: Robert Swinney, Duke University, Fuqua Drive, Durham,
NC, 27708, United States,
1 - Drivers, Riders And Service Providers: The Impact Of The Sharing
Economy On Mobility
Harald Bernhard, Singapore University of Technology and Design,
Singapore, Singapore, , Saif
Benjaafar, Costas Courcoubetis
We study a heterogeneous population of agents interacting through a platform
that facilitates on-demand ride-sharing. We build an equilibrium model to
analyze the impact of key parameters such as car usage and ownership costs on
traffic volume and welfare. Furthermore we define and find conditions to
differentiate between a ‘need’ and ‘profit’ driven sharing economy.
2 - The Role Of Surge Pricing On A Service Platform With Self-
scheduling Capacity
Gerard P Cachon, University of Pennsylvania,
, Kaitlin Daniels, Ruben Lobel
Recent platforms, like Uber and Lyft, offer service to consumers via “self-
scheduling” providers who decide for themselves how often to work. These
platforms may charge consumers prices and pay providers wages that both adjust
based on prevailing demand conditions. We study the effectiveness of different
contractual forms, from the perspective of platform profit, provider surplus and
consumer surplus. We find that while surge pricing is not optimal, it is nearly so.
We describe conditions under which all parties benefit from the use of surge
pricing.
3 - Bike-share Systems: Accessibility And Availability
Ashish Kabra, INSEAD, Boulevard de constance, Fontainebleau,
77305, France, Elena Belavina, Karan
Girotra
This paper estimates the relationship between ridership of a bike-share system
and its design aspects— station accessibility and bike-availability. Our analysis is
based on a structural demand model that considers the random-utility
maximizing choices of spatially distributed users, and it is estimated using high-
frequency system-use data from the bike-share system in Paris and highly
granular data on sources of bike-share demand. A novel model separates the
long-term and short-term effects of higher bike-availability. Because the scale of
our data render traditional numerical estimation techniques infeasible, we
develop a novel transformation of our estimation problem.
TD36
205B-MCC
MSOM/Supply and Procurement
Sponsored: Manufacturing & Service Oper Mgmt, Supply Chain
Sponsored Session
Chair: Zhixi Wan, University of Oregon, 1208 University of Oregon,
Eugene, OR, 97403, United States,
1 - Optimal Procurement In Assembly Supply Chains
Bin Hu, University of North Carolina, Chapel Hill, NC, 27519,
United States, , Anyan Qi
We consider an OEM’s contracting mechanism to procure multiple components
from different suppliers and assemble them into products under simultaneous and
sequential contracting. We derive optimal mechanisms in both cases, and show
that they can be implemented by simple quantity flexibility contracts.
Furthermore, we find that optimal simultaneous and sequential contracting are
revenue-equivalent for all parties, despite them having different asymmetric
information structures. All results are extended to general convex costs and
concave revenues, confirming that the results capture fundamental properties of
optimal procurement in assembly supply chains.
TD36