2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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2 - Scenario Generation Assessment For Stochastic Programs
Didem Sari, Iowa State University, 3219 Roy Key Avenue, Unit
207, Ames, IA, 50010, United States, ,
Sarah M Ryan
We propose an approach for assessing the reliability of a scenario generation
method using historical outcomes. The distances among scenarios and the
observed value are measured by fixing first-stage decisions to a common value
and computing second-stage costs. A rank histogram constructed from these
distances, motivated by mass transportation metrics, can diagnose bias or other
defects. The method is demonstrated using unit commitment case studies and
server location simulations.
3 - Route Optimization: A Risk Averse Shortest Path Problem
Marcelo Ricardo Figueroa, Rutgers University,
93 Marvin Lane, Piscataway, NJ, 08854, United States,
, Melike Baykal-Gursoy
We study a risk-averse shortest path route optimization problem on a vehicular
traffic setting, to inform users of optimal routing decisions under particular levels
of risk-aversion. We make use of specialized travel-time distributions derived
from analytic queueing models with Markov modulated service times to model
random traffic interruptions.
4 - Developing A CCHP-microgrid Operation Decision Model
Under Uncertainty
Md Abdul Quddus, PhD Student, Mississippi State University,
Department of Industrial & Systems Engineering, PO Box 9542,
Starkville, MS, 39762, United States, ,
Carlos Marino, Mohammad Marufuzzaman, Mengqi Hu
A combined cooling, heating, and power (CCHP) system provides a cost efficient
solution for energy demand, energy security supply along with sustainability. The
power grid is heavily vulnerable to breakdowns, natural disaster and targeted
attacks. Researchers have proposed stochastic optimization models for CCHP
operation for small scale (i.e. single buildings). However little attention has given
for modeling CCHP units operation that satisfy multiple energy demand nodes.
This study bridges the research gap by developing a scalable two stage stochastic
programming model for large scale micro-grid operation under uncertainty
considering a larger number of scenarios.
TC86
GIbson Board Room-Omni
Marketing VII
Contributed Session
Chair: Rajeev Kumar Tyagi, Professor, University of California, Irvine,
5 Murasaki, Irvine, CA, 92697, United States,
1 - Showrooming And The Length Of Product Line
Yilong Luo, Illinois Institute of Technology, 6716 Idaho Avenue,
Hammond, IN, 46323, United States, ,
Jiong Sun
Showrooming is a strategy that consumers touch and feel the products in the
offline store but purchase from online store which usually offer a lower price. As
the improvement of technology, like high speed internet and mobile phone,
showrooming are widely applied by consumers. Thus offline stores always regard
showrooming as something evil and attribute the sales decline to this effect. In
our paper, however, we explore the strategy that brick store can actually benefit
from showrooming effect by partially carrying the product line. We also show that
the presence of showrooming behavior may or may not induce the brick-and-
mortarretailer to reduce the length of the product line it carries.
2 - A Model Of Cause-related Marketing
Sreya Kolay, Assistant Professor, University of California, Irvine,
Irvine, CA, 92697, United States,
Cause-related marketing (CRM) is the popular practice of linking purchases to
donations made to charitable causes. They include price-based CRM policies
wherein a firm donates a percentage of revenues or profits for every purchase
made, or quantity- or unit-based CRM policies wherein the firm donates a unit of
its own product for every unit purchased. In this paper, we develop an analytical
model to examine conditions on consumer valuations and seller’s cost structure
that determine the optimality of CRM, price-based CRM, and quantity-based
CRM from the perspective of a seller. We also compare and contrast these
conditions with those that maximize donations and social welfare.
3 - Optimal Pricing Of Multiple Events
Rajeev Kumar Tyagi, Professor, University of California, Irvine,
5 Murasaki, Irvine, CA, 92697, United States,
Event organizers often sell a series of events that occur sequentially over time. For
example, concert series with multiple performers and sports tournaments.
Consumers may enjoy more than one event in the series, and the events may
differ in popularity with the audience (e.g. two operas of different popularity in
successive months, pre-season games followed by more popular regular-season
games). In this paper, we analytically characterize the optimal pricing and
bundling strategy of such an event organizer. We allow for sellers who can
commit to future prices as well as those who cannot.
TC87
Broadway A-Omni
Minority Issues Forum Paper Competition
Sponsored: Minority Issues
Sponsored Session
Chair: Karen T Hicklin, University of North Carolina at Chapel Hill,
308 Bynum Hall, Chapel Hill, NC, 27599, United States,
TC88
Broadway B-Omni
Service Science Best Student Paper Competition III
Award Session
Chair: Robin Qiu, Penn State University, 30 E. Swedesford Road,
Malvern, PA, 19355, United States,
1 - Managing Service Systems With Unknown Quality And Customer
Anecdotal Reasoning
Hang Ren, University College London, London, United Kingdom,
, Tingliang Huang
In this paper, we study a service system where customers estimate service quality
from anecdotal evidence. We characterize the service provider’s pricing, quality
information disclosure, and quality control decisions. We find that the service
provider adopts a pricing strategy very different from the fully rational
benchmark. Moreover, she should reserve quality information when queueing is
more costly, and she may disclose one type of service quality anecdote but not the
other type. Lastly, the service provider may reduce service quality when
customers obtain more anecdotes.
2 - The Use And Value Of Social Network Information In
Selective Selling
Ruslan Momot, INSEAD, Fontainebleau, France,
, Elena Belavina, Karan Girotra
We consider the use and value of social network information in selectively selling
goods and services whose value derives from exclusive ownership among
network connections. Our model accommodates customers who are
heterogeneous in their number of friends (degree) and proclivity for social
comparisons (conspicuity). We show how the firm with information on either (or
both) of these traits can use it to increase profits making a product selectively
available to the firm’s best targets - high-conspicuity customers within
intermediate-degree segments. We find that information about degree is more
valuable than information about conspicuity and that the two are substitutes.
3 - Embedding Assignment-Routing Constraints through Multi-
Dimensional Network Construction For Solving Multi-Vehicle
Routing With Pickup & Delivery Time Windows
Monireh Mahmoudi, Arizona State University, Tempe, AZ, United
States, , Junhua Chen, Xuesong Zhou
Optimization of ride-sharing services in on-demand transportation systems
involves solving a class of complex vehicle routing problems with pickup and
delivery with time windows. In this paper, by embedding complex assignment-
routing constraints through constructing a multi-dimensional network, we intend
to reach optimality for local clusters derived from a reasonably large set of
passengers on real world transportation networks. In addition, by the aid of the
passengers’ cumulative service patterns defined in this paper, our solution
approach is able to tackle the symmetry issue which is a common issue in the
combinatorial problems.
4 - Using Patient-centric Quality Information To Unlock Hidden
Health Care Capabilities
Guihua Wang, Ross School of Business, University of Michigan,
Ann Arbor, MI, 48105, United States, ,
Jun Li, Wallace J Hopp
We document a wide variation in quality among 188 surgeons at 35 hospitals in
New York state that perform mitral valve surgery. Our analysis shows that
patients of different demographics and levels of acuity benefit differently from
elite surgeons. In this paper, we develop an approach for computing patient-
centric information from outcome data and evaluate the potential health benefits
from using such information to guide patients to surgeons. We estimate that the
total societal benefits from using patient-centric information are comparable to
those achievable by enabling the best surgeons to treat 40% more patients under
population-average information.
TC88