2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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3 - Dynamic Pricing With Stochastic Reference Price Effects
Xin Chen, UIUC, Zhenyu Hu, Yuhan Zhang
We study a dynamic pricing problem of a firm facing stochastic reference price
effect. Randomness is incorporated in the formation of reference prices to capture
exogenous factors that affect consumers’ memory processes. We derive an explicit
expression for the optimal pricing strategy which allows us to obtain the
distribution of the steady state reference price. We compare the expected steady
state reference price to the steady state reference price in a deterministic model
and we find that the former one is always higher. A transformation technique is
presented to show how one can extend the analysis to higher dimensional
problems in which consumers have heterogeneous reference prices.
4 - Hidden City Travel And Its Impact On Airfare: The Case With
Competing Airlines
Jaelynn Oh, University of Utah,
Tim Huh
We study the impact of hidden-city ticketing on airfare pricing in a setting where
two airlines compete on a hub-and-spoke flight network.
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209C-MCC
New Topics in Revenue Management
Sponsored: Revenue Management & Pricing
Sponsored Session
Chair: Stefanus Jasin, University of Michigan, Ann Arbor, MI,
United States,
1 - Managing Dynamic Mobile Push Advertisements At Alibaba
Van Anh Truong, Columbia IEOR,
In recent years, e-commerce companies are seeing an increasing amount of
transactions completed via mobile platforms, such as apps in iOS and Android
systems. In China, the e-commerce market share of a mobile app developed by
Alibaba Group, which has been installed on several hundred million devices, is
rapidly replacing that of traditional e-commerce markets hosted on webpages. We
study the problem of managing the allocation of push notifications sent to users
by this app which recommends products tailored to every user.
2 - Efficient Algorithms For Dynamic Pricing Problem With Reference
Price Effect
Zhenyu Hu, National University of Singapore (NUS),
We analyze a dynamic pricing model in which demand at each period depends on
not only the current price but also past prices through reference prices. A unique
feature but also a significant challenge in this model is the asymmetry in
reference price effect which implies the underlying optimization problem is non-
smooth and no standard optimization methods can be applied. We identify a few
key structural properties of the problem, which enable us to develop strongly
polynomial time algorithms to compute the optimal prices for several plausible
scenarios. We further conduct numerical experiments to study the optimal price
path and demonstrate the value of dynamic pricing when demands are seasonal.
3 - Optimal Stopping And Worker Selection In Crowdsourcing:
An Adaptive Sequential Probability Ratio Test Framework
Xi Chen, Stern, NYU,
In this talk, we propose an adaptive sequential probability ratio test (Ada-SPRT)
that obtains the optimal experiment selection rule, stopping time,and final
decision rule under a single Bayesian decision framework. Our motivating
application comes from binary labeling tasks in crowdsourcing, where the
requestor needs to simultaneously decide which worker to choose to provide the
label and when to stop collecting labels to save for budget. We characterize the
structure of the optimal adaptive sequential design that minimizes the Bayes risk
through log-likelihood ratio statistic and develop dynamic programming based
algorithms for both non-truncated and truncated tests.
4 - Dynamic Joint Pricing And Order Fulfillment For
E-commerce Retailers
Yanzhe Lei, University of Michigan, Ann Arbor, MI, United States,
Stefanus Jasin, Amitabh Sinha
We consider a dynamic joint pricing and order fulfillment optimization problem
in the e-commerce retailing context, where a retailer sells a catalog of products to
customers from different locations and fulfills orders through multiple fulfillment
centers. The objective is to maximize the total expected profits, defined as
revenues minus shipping costs. We propose two heuristics that are easily
implementable, and show both theoretically and numerically their good
performances compared to reasonable benchmarks.
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210-MCC
Social Media in Marketing and Talent Management
General Session
Chair: Fujie Jin, Indiana University, 1309 East Tenth Street, Suite 4100,
Bloomington, IN, 47405, United States,
1 - Social Media Marketing In Product Harm Crisis
Shu He, University of Connecticut,
We conceptualize the dual roles of a firm’s social media strategy—-offensive and
defensive marketing strategies—-and study how non-focal firms adjust these two
components of strategy in response to a product-harm crisis. We use daily social
media activity of 56 major airlines on Twitter around the time of an airplane crash
to study how non-focal airlines harness these two functions before and after the
crisis. We find that a non-focal airline increases its defensive marketing effort but
decrease its offensive marketing effort after the crash. The adjustment of offensive
marketing decrease is significantly attenuated by whether the non-focal airline
directly competes with the focal airline.
2 - Influence Of Social Media On Flash Sales: An Empirical Analysis
Karthik Kannan, Georgia Tech,
Jeffrey Hu,
Sridhar Narasimhan
The emergence of e-commerce platforms has democratized both the production
and consumption of goods and services. While anyone can offer their services
through these platforms, sellers with little brand recognition have to overcome
high search cost faced by prospective buyers in order to succeed in these markets.
We study two mechanisms - flash sales and social media - used by sellers to
promote their products by collecting sales and social media data from 24,446
products sold in a popular e-commerce platform.
3 - Does Reputation Management On Social Media Boost Career?
Evidence From The Market For Executives
Yanzhen Chen, University of Texas at Austin, Austin, TX,
United States, , Huaxia Rui,
Andrew Whinston
Our paper studies the impact of reputation management (RM) on executives’
careers gathering evidence from their Twitter usage. Our structural model, which
is based on a Two-Sided Matching Model, is able to exploit the characteristics of
all of the candidates so as to identify separate RM’s influences in bargaining
power as well as sorting during the hiring process. The results show that in the
recruiting process of CEO and CMO markets, both out-/underperformed
applicants benefit from RM. However, in compensation bargaining, RM is
profitable only for outperformed candidates. RM can help more than 40% of
CEOs and may increase their compensation by more than $10 million per year.
4 - Gravity In Open Source Software Production
Xuan Ye, New York University, New York City, NY,
United States, Prasanna Tambe
Using data on over 2 million hourly contributions contributed over eight years to
, this paper investigates how the geographic organization of
contributors influences open source production in corporate sponsored projects.
Specifically, we test the extent to which time zones play a role in open source
software contribution. We find strong evidence of such a bias in open source
software production. Concentration of contributors within the same time zone is
correlated with greater contribution levels, and this is robust to user fixed-effects.
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211-MCC
Social, Political, and Economic Applications of Social
Media Analysis
Invited: Social Media Analytics
Invited Session
Chair: Amanda Andrei, MITRE Corporation, 7515 Colshire Dr,
Mclean, VA, 22102, United States,
1 - Characterizing Traffic Accident Detection Through Twitter And
Open Data
Jared Mowery, MITRE Corporation,
Several recent studies have shown that Twitter can be used to detect traffic
disruptions with high precision. This study builds on those results by
incorporating open data including real-time traffic speed sensor measurements
and weather data, measuring the recall of traffic accident detection against New
York City police records, and by characterizing the probability of detection as a
function of the severity of the accident.
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