2016 INFORMS Annual Meeting Program

469 / 561

INFORMS Nashville – 2016
469
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209A-MCC
Network Economics II
Sponsored: Simulation
Sponsored Session
Chair: Bruno Tuffin, INRIA, TBD, Rennes Cedex, France,
Co-Chair: Patrick Maillé, Telecom Bretagne, 2, rue de la
Cha^taigneraie, Cesson Sévigné, 35576, France,
1 - On Revenue-oriented Content Delivery Networks And Their
Impact On Net Neutrality
Patrick Maillé, Telecom Bretagne, Rennes, 35510, France,
, Gwendal Simon,
Bruno Tuffin
We investigate the decisions made by a CDN actor willing to maximize revenue
through the management of its cache servers. Through simple models, we
highlight that revenue-oriented management policies can affect the user-
perceived quality of experience, impacting the competition among content
providers (and also among network access providers) in favor of the incumbent.
Since this goes in the opposite direction to the one aimed by net neutrality
proponents and it seems that CDNs are not discussed much in the net neutrality
debate, we wonder about the need for a definition of what a “neutral” CDN
should look like.
2 - An Optimization Approach For Long-term Network Planning With
Protection Constraints
Nicolas Stier-Moses, Facebook, Menlo Park, CA, United States,
, Josue Kuri
We present an optimization approach for strategic, long-term network planning.
We forecast supply (network assets), demand (network traffic) and possible
failures, and employ a robust optimization approach to optimize which assets to
use and how much capacity must be turned up in each of them. A key element of
this model is its dynamic nature which allows us to consider inter-temporal
constraints (e.g., turned up capacity is monotone over time) and the amortization
of fixed costs.
3 - Profit, Welfare, And Consumer Surplus Implications Of Sponsored
Data Plans
Jialin Song, University of Illinois at Urbana-Champaign, 117
Transportation Building, 104 S Mathews Ave, Urbana, IL, 61801,
United States, , Qiong Wang
Major Mobile Service Providers are now offering sponsored data plans that allow
Content Providers to pay for the access of their contents by end users. How such
practice affects profit, social welfare, and consumer surplus is a critical question in
the network neutrality debate. We address this issue from the perspective of
commodity bundling: without a sponsored data plan, users purchase data blocks
to access all contents, which corresponds to pure bundling; sponsored data plans
separate some contents from the bundle. We develop a two-stage model,
involving both Nash bargaining solution and Nash equilibrium, to analyze and
compare the two situations.
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209B-MCC
Revenue Management and Marketing
Sponsored: Revenue Management & Pricing
Sponsored Session
Chair: Denis Saure, University of Chile, Beaucheff 851, Santiago, Chile,
Co-Chair: Juan Pablo Vielma, Massachusetts Institute of Technology, 30
Memorial Dr, Cambridge, MA, 02142, United States,
1 - Ellipsoidal Methods For Choice-based Conjoint Analysis
Denis Saure, Universidad de Chile, Republica 701, Santiago,
8370439, Chile, Juan Pablo Vielma
In this talk we introduce a variant of the polyhedral method by Toubia, Hauser
and Simester (2004) that uses ellipsoids instead of polyhedral. This change allows
the method to (1) include approximate Gaussian priors on the parameters, (2)
explicitly consider respondent error, and (3) perform quick approximate posterior
updates whose quality nearly matches a full Bayesian update. We also introduce a
practical question selection method that is optimal with respect to the D-
efficiency criterion for one question, and leads to an extremely effective one-step
look-ahead policy for multiple questions.
2 - Capturing Multitaste Preferences: A Machine Learning Approach
Daria Dzyabura, New York University, ,
Liu Liu
In diverse product categories, a consumer’s preferences may include several
tastes. For example, one may enjoy cooking American and Chinese recipes, with
different specific criteria for each. We propose a model that allows for multiple
tastes and an efficient estimation algorithm. In a numerical study, we simulate
multi-taste consumers and demonstrate the proposed algorithm accurately
recovers parameters, while benchmark models underfit. We test the algorithm on
recipe texts, after extracting attributes from recipe text using text mining. We
achieve significant improvements in prediction over single-taste benchmarks.
3 - Estimating Customer Spillover Learning Of Service Quality:
A Bayesianhierarchical
Andres I Musalem, Universidad de Chile, Beauchef 851, Santiago,
8370456, Chile, , Yan Shang, Jeannette Song
We propose a Bayesian framework for estimating customer “spillover learning,”
— the process by which customers’ learn from previous experiences of similar but
not necessarily identical services. We apply our model to a data set containing
shipping and sales historical records provided by a world-leading third-party
logistics company.
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209C-MCC
Various Pricing Topics for Revenue Management
Sponsored: Revenue Management & Pricing
Sponsored Session
Chair: Elcin Ergin, McGill, 3465 Hutchison Street, Apt 905, Montreal,
QC, H2X 2G3, Canada,
1 - Better Late Than Now: Delayed Vs. Instantaneous Price Discounts
With Repeat Customers
Monire Jalili, PhD Student, University of Oregon, 1455 East 25th
Ave, Eugene, OR, 97403, United States, ,
Michael Pangburn
In this paper, we contrast the delayed versus instantaneous discounting policies in
a repeat purchase setting with rational and forward-looking consumers. We first
establish that if consumer spending is consistent over time, then there is no
benefit to the firm (or consumers) from delayed discounts. With varied spending,
we prove that when the firm can target individual consumers with their optimal
discount percentage, delaying discounts increases profits only for a limited range
of transition shoppers. However, when the same discount percentage applies to all
customers, delayed discounting outperforms the instantaneous discounting, thus
motivating the prevalence of this policy in practice.
2 - Competitive Pricing With Stockouts And Satisficing Customers
Varun Gupta, Penn State Erie, The Behrend College, 5101 Jordan
Rd, Burke 281, Penn State Erie, The Behrend College, Erie, PA,
16563, United States, , Metin Cakanyildirim
Stockouts for high inventory turnover products lead to loss of sales as customers
may substitute their preferred product (stocked out) with another product
(available). We study single period equilibrium prices for competing retailers
selling to satisficing customers with stockout-based substitution under lost sales
and backorders.
3 - Pricing Decisions In Fast Fashion Retailing Using Discrete Choice
Dynamic Programming Model
Elcin Ergin, McGill, 3465 Hutchison Street, Apt 905,
Montreal, QC, H2X 2G3, Canada, ,
Mehmet Gumus
We study the pricing decisions in fast-fashion retailing firms under a forward-
looking setting utilizing the dynamic nature of the problem. In this context, we
consider a discrete choice dynamic programming model to estimate the optimal
pricing decisions throughout the life cycle of a product. We develop
decomposition approaches based on different functional forms and assess their
performances in terms of computational complexity and objectives of the problem
on a large real-life dataset taken from a fast-fashion company.
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