Informs 2015

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INFORMS Philadelphia – 2015
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WA40
40- Room 101, CC
Marketing III
Contributed Session
Chair: Fouad El Ouardighi, ESSEC Business School, BP 105,
Cergy Pontoise, 95021, France,
1 - Segment’s Competitive Environment and Dynamics of Segment
Entry and Segment Exit
Setiadi Umar, PhD Candidate, Rutgers Business School,
1 Washington Park, Newark, NJ, 07102, United States of
America, Sengun Yeniyurt
This study examines how segment’s competitive conditions influence firms’
patterns of segment selection: which segment to enter to and which segment to
exit from in the context of business ecosystems. The study showed that high
concentration and low density segment attract potential entrants to enter the
segment and inhibit incumbents in the segment to exit. However, competitors’
competitive moves might counter this condition.
2 - Optimal Promotion Strategies
Krista Foster, PhD Candidate, University of Pittsburgh, Katz
Graduate School of Business, 241 Mervis Hall, Pittsburgh, PA,
15260, United States of America, , Jennifer Shang
Given a portfolio of three products and a fixed pool of consumers, which form of
promotion will maximize a seller’s profits? We consider a number of promotional
strategies to determine if and when each is strategy is optimal.
3 - The Marketing Dilemma: To Market or Not to Market During a
Competitor’s Product Harm Crises
Amirhossein Alamdar Yazdi, PhD Student, 121 Presidents Drive,
24 Rolling Green Drive, Amherst, MA, 01003, United States of
America, , Adams Steven
What is the impact of advertising on a firm’s performance during unfavorable
news coverage of a close competitor? Positive? Likely. Negative? Possible. This
study investigates the effect of advertising intensity on a firm’s marketing and
financial performance and the moderating influence of a competitor’s product
recalls.
4 - Advertising and Quality-Dependent Word-of-Mouth in a
Contagion Sales Model
Fouad El Ouardighi, ESSEC Business School, BP 105, Cergy
Pontoise, 95021, France, , Dieter Grass,
Richard Hartl, Peter Kort, Gustav Feichtinger
The omission of negative evaluations by current customers in contagion sales
models and, more importantly, of the originating factors of such negative
evaluations, may lead to prescribing of improper communication policy and
therefore poor brand building strategy. This paper bridges the gap by suggesting a
sales model where both positive and negative word-of-mouth affect the attraction
rate of new customers, along with advertising.
WA41
41-Room 102A, CC
Healthcare Operations Management
Sponsor: Manufacturing & Service Oper
Mgmt/Healthcare Operations
Sponsored Session
Chair: Andrew Trapp, Assistant Professor, Worcester Polytechnic
Institute, 100 Institute Rd., Worcester, MA, 01609, United States of
America,
1 - Impact of Breast Density on Designing Mammography
Screening Policies
Mucahit Cevik, University of Wisconsin - Madison, 1513
University Avenue, Madison, WI, 53706, United States of
America, , Burhaneddin Sandikci
Mammography screening is the golden standard for breast cancer screening, but it
is also known to be less accurate for women with dense breasts. Therefore, some
patients are often referred to receive supplemental screenings. We incorporate the
breast density information to the breast cancer screening decisions and use a
discrete-time partially observable Markov decision process model to assess the
effectiveness of the supplemental screening tests.
2 - A Simulation Model for the Heart Allocation Process
Farhad Hasankhani Kohneh Sh, PhD Graduate Assistant,
Clemson University, #4, 129 Freeman Hall, Clemson University,
Clemson, SC, 29631, United States of America,
Amin Khademi
Heart failure occurs when a heart loses its ability to properly circulate blood in the
body. Over 5.8 million people in the US are suffering from heart failure. Heart
transplantation is a life-saving treatment for such patients. The Number of donors,
the only source of hearts, is limited, and demand far exceeds supply. In this study
we create a simulation model to investigate the impacts of a variety of allocation
policies on several outcomes such as expected life-years of the population.
3 - Scheduling with Stochastic Processing Times in a Medical Clinic
David Phillips, , Marcus Colyer,
Marisa Molkenbuhr
We consider the problem of scheduling patients in a medical clinic. Patients must
see one of the clinic’s doctors and some must also receive a scan prior to seeing
the doctor. Complications of the problem include stochastic processing times and
model selection based on the decision problem of interest. We present models as
well as computational results based on both integer programming and
approximation algorithms approaches.
4 - Optimal Adjusted Panel Size for Balancing Patient and
Physician Risk
Zelda Zabinsky, Professor, University of Washington, Industrial
and Systems Engineering, Box 352650, Seattle, WA, 98195,
United States of America, David Linz,
Hao Huang, Paul Fishman, Joseph Heim
An issue in healthcare is sizing physician adjusted panels. Patient concerns (wait
time, disruption of care, inequitable care) as well as physician concerns
(inequitable workload, panel size preference) need to be balanced in any fair
strategy for adjusted panel size. This paper proposes a multi-objective
optimization model for minimizing the risk of patient and physician concerns that
accounts for acute instances of inequality and risk. We provide an efficient
frontier for administrative use.
WA43
43-Room 103A, CC
Choice Modeling Applications in
Revenue Management
Sponsor: Revenue Management and Pricing
Sponsored Session
Chair: Adam Elmachtoub, Assistant Professor, Columbia IEOR, 500
West 120th St, New York, NY, United States of America,
1 - Revenue Managament under the Markov Chain Choice Model
Huseyin Topaloglu, Professor, Cornell University,
223 Rhodes Hall, Ithaca, NY, 14853, United States of America,
, Jacob Feldman
We consider static assortment, network revenue management and single-leg
revenue management problems under the Markov chain choice model. For static
assortment problem, we give structural properties of the optimal assortment. For
network revenue management, we give a tractable linear programming
formulation. For single-leg revenue management, we characterize the optimal
policy as a protection level policy.
2 - A Multi-attempt Approximation of Choice Model
Hakjin Chung, Stephen M. Ross School of Business, University of
Michigan, Ann Arbor, MI, United States of America,
Boying Liu, Hyun-soo Ahn, Stefanus Jasin
We consider the problem of approximating an arbitrary mixture of logits with a
series expansion. The degree of the expansion can be interpreted as the number
of attempts that a customer is willing to make before leaving the system because
his preferred product is not available. There are at least two benefits of using this
approximation: the optimization problem becomes tractable and its parameters
can be estimated using linear regression. We derive some bounds.
3 - Managing Product Transitions via Strategic Customer Selection
Roger Lederman, IBM, T. J. Watson Research Center, Yorktown
Heights, NY, United States of America, ,
Adam Elmachtoub
The talk will discuss tools for shaping demand to better match supply capabilities,
with a specific focus on product transitions. We describe a framework for
managing transitions, including the role that sales targeting can have in shaping
customer decisions. We then formulate as a customer selection problem in which
a seller with limited inventories must prioritize sales effort across a set of
heterogeneous customers with differing historical patterns of adoption.
WA40