INFORMS Philadelphia – 2015
275
4 - Strategic Consumers, Revenue Management and the Design of
Loyalty Programs
So Yeon Chun, McDonough School of Business, Georgetown
University, 3700 O St. NW, Washington, DC, United States of
America,
sc1286@georgetown.edu, Anton Ovchinnikov
Several major airlines recently switched their loyalty programs from
``mileage/segment-based” toward ``spending-based”. We study the impact of this
switch on firm’s profit and consumer utility. We present a novel model of strategic
consumers’ response to firm’s pricing and loyalty program decisions, incorporate
such response into the firm’s pricing and loyalty program design problem,
compare the solutions under the mileage-based versus spending-based design,
and discuss managerial implications.
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51-Room 106B, CC
Economics of Innovation in Supply Chains
Sponsor: Manufacturing & Service Operations Management
Sponsored Session
Chair: Ayhan Aydin, Assistant Professor Of Operations Management,
George Mason University School of Business, 4400 University Drive MS
5F4, Fairfax, VA, 22030, United States of America,
aaydin2@gmu.edu1 - Product Quality in a Decentralized Supply Chain: Value of
Information Asymmetry
Narendra Singh,
Narendra.Singh@scheller.gatech.edu,
Stylianos Kavadias, Ravi Subramanian
We study an OEM’s optimal product design quality and sourcing strategies in a
supply chain consisting of an OEM, who has in-house option, and a supplier, who
has more favorable cost structure and the power to dictate contract terms. We
show that a two-part tariff contract, as opposed to a price-only contract, may
leave both the OEM and the supplier worse off. Further, we show that
asymmetric information about the OEM’s cost structure may lead to higher profits
for both the OEM and the supplier.
2 - Information Acquisition and Innovation in Competitive Markets
Yi Xu, Associate Professor, Smith School of Business, University
of Maryland, College Park, MD, 20742, United States of America,
yxu@rhsmith.umd.edu, He Chen, Manu Goyal
In this paper, we study firms’ information acquisition strategies and innovation
strategies in a competitive market with uncertainty. The firms can resolve the
market uncertainty through different information acquisition methods. We
highlight the strategic interactions between information acquisition and
innovation investments in such a market.
3 - Investment in Core Technologies and Consumer Markets
Ayhan Aydin, Assistant Professor Of Operations Management,
George Mason University School of Business, 4400 University
Drive MS 5F4, Fairfax, VA, 22030, United States of America,
aaydin2@gmu.edu, Rodney Parker
We consider a two-tier supply chain, an upstream tier composed of two
competing providers of a component that is used by multiple OEMS (integrators)
in the lower tier. Upstream firms invest to develop the technology of the
component further. We investigate the effects of downstream market factors, the
nature of technology, competition, and the level of uncertainties in the R&D
process on the level of upstream investments and the adoption of the higher
technologies by the downstream firms.
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52-Room 107A, CC
Consumer-driven Management Science
Sponsor: Marketing Science
Sponsored Session
Chair: Ricardo Montoya, Assistant Professor, University of Chile,
Republica 701, Santiago, Chile,
rmontoya@dii.uchile.cl1 - Product Showcasing in the Presence of Experience Attributes
Daria Dzyabura, Assistant Professor of Marketing, NYU Stern
School of Business, 40 West 4th Street, Tisch 805, New York, NY,
10012, United States of America,
ddzyabur@stern.nyu.edu,
Srikanth Jagabathula
We formalize a firm’s showcase decision, or selecting a subset of products to carry
in a physical store, while a ‘large’ product line is offered through the online
channel. Some customers visit the offline store to gain information about product
features. We formalize the showcase problem as an IP, which we show to be NP-
complete, derive closed-form solutions for special cases, and adapt the local search
heuristic to the general problem. We gather conjoint data to estimate the model
parameters.
2 - Price Drop Protection Policy with Partial Refunds
Dinah Cohen-Vernik, Assistant Professor Of Marketing,
Rice University, 6100 Main St, Houston, TX, 77006,
United States of America,
dv6@rice.edu, Amit Pazgal
Many retailers now offer to refund customers the full price difference as long as
the price drop occurred within a specified short period of time after the purchase.
Despite the popularity of such policy, the existing marketing research on the topic
is scarce. In this paper we investigate the price difference refund policy (referred
to as price drop protection) and demonstrate how it can improve retailer’s profits.
3 - Clicks and Editorial Decisions: How Does Popularity Shape Online
News Coverage?
Pinar Yildirim, Assistant Professor Of Marketing, The Wharton
School. University of Pennsylvania, 748 Huntsman Hall,
Philadelphia, PA, 19104, United States of America,
pyild@wharton.upenn.edu,Ananya Sen
Using online news data from a large Indian English daily newspaper, this paper
analyzes how demand side incentives shape news media reporting. To establish a
causal link, we instrument the views of articles using days with rain and days
with electricity shortage as exogenous shocks to reader attention. We provide
evidence for extended coverage and higher resource allocation to issues which
receive high number of clicks.
4 - Stock-out Detection System Based on Sales Transaction Data
Ricardo Montoya, Assistant Professor, University of Chile,
Republica 701, Santiago, Chile,
rmontoya@dii.uchile.cl,
Andres Musalem, Marcelo Olivares
We present a methodology based on real-time point-of-sales data to infer on-shelf
product availability. We develop our methodology using process control theory an
apply it to a big-box retailer. We use historical transactional data to develop our
methodology and empirically test it in two field studies. We analyze the results
and implications.
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53-Room 107B, CC
Behavior in Operational Contexts
Sponsor: Behavioral Operations Management
Sponsored Session
Chair: Anton Ovchinnikov, Queen’s University, 143 Union Str, West,
Kingston, Canada,
anton.ovchinnikov@queensu.ca1 - Behavioral Ordering: Inventory, Competition and Policy
Bernardo Quiroga, Assistant Professor, Business And Behavioral
Science, Clemson University, 100 Sirrine Hall, Clemson, SC,
29634, United States of America,
bfquirog@gmail.com,
Anton Ovchinnikov, Brent Moritz
We study the effect of observed inventory decisions on performance. Our goal is
to measure and understand profit losses due to behavioral (intuitive but
suboptimal) ordering. The current literature, primarily focused on a newsvendor
making decisions in isolation, reports results implying profit losses of 1-5%
compared to the analytical optimum. In contrast, we show that when a
behavioral inventory manager competes against a management-science-driven
competitor, profit losses are much larger.
2 - Inequity and Loss Aversion in Pay What You Want
Yulia Vorotyntseva, PhD Candidate, The University of Texas at
Dallas, Richardson, United States of America,
Yulia.Vorotyntseva@utdallas.edu,Ozalp Ozer
Pay-What-You-Want pricing is an exemplar of fairness-driven behavior in a
business context: the price for a product is fully determined by a buyer, and the
seller cannot reject any offer. The objective of our work is to find out key factors
affecting the buyers’ selection of prices under PWYW. We use a distributional
fairness approach and build a hierarchical Bayesian model of buyers’ behavior.
We then test it in a controlled laboratory experiment.
3 - Inventory Decisions in the Presence of Strategic Consumers
Yaozhong Wu, National University of Singapore, NUS Business
School, Singapore, Singapore,
yaozhong.wu@nus.edu.sg,Yang Zhang, Benny Mantin
In the presence of strategic consumers, who may delay their purchase to the
markdown season, a retailer is faced with an extra consideration in addition to
the traditional newsvendor setting: excess inventory may induce strategic
consumers to delay their purchase and may further harm the revenue. We
develop a model that accounts for both the strategic consumers and the retailer’s
inventory decisions. We design behavioral experiments to test our model
predictions.
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