2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
442
2 - When Suppliers Climb Value Chain: A Theory Of Value Distribution
In Vertical Relationships
Zhixi Wan, University of Oregon, Eugene, OR, United States,
, Brian Wu
Offshore outsourcing gives rise to the phenomenon of value chain climbing -
suppliers in emerging markets can develop capabilities by supplying, with
aspirations to compete with the buyers in the product market. We build an
analytical model to study the impact of value chain climbing on value distribution
in vertical relationships. The analysis identifies a set of dominant relationships,
characterizes how the buyer’s optimal choice among these relationships depends
on firms’ relative competitiveness in the product market and the supplier’s speed
of capability development, and shows how the optimal choice evolves with the
dynamics of the supplier’s capability development.
3 - Strategic Investment In Common Assets Under Uncertainty
Dharma Kwon, Associate Professor, University of Illinois at
Urbana-Champaign, Champaign, IL, United States,
, Youngsoo Kim, George Georgiadis
We investigate the game of investment in common assets under uncertainty as a
two-player stochastic war of attrition in continuous time. We characterize the
equilibrium when there are indefinitely many opportunities of investment. We
focus on the impact of stochasticity and the asymmetry between the two players.
4 - Playing A Dominated Strategy In A Simple Bankruptcy Case:
Field And Experimental Data
Steven A Lippman, Univ of California-Los Angeles,
, Sushil Bikhchandani
We consider a real life bankruptcy case in which the judge asked unsecured
creditors the least they would accept in full satisfaction of their claims. Even
when real money is at stake, creditors play dominated strategies. An even greater
percentage of MBAs play dominated strategies.
WC45
209A-MCC
Network Economics I
Sponsored: Simulation
Sponsored Session
Chair: Bruno Tuffin, INRIA, Rennes Cedex, France,
Co-Chair: Patrick Maillé, Telecom Bretagne, 2, rue de la
Cha^taigneraie, Cesson Sévigné, 35576, France,
1 - Auctions For Online Ad Space Among Advertisers Mixing
Pay-per-view And Pay-per-click
Bruno Tuffin, INRIA, , Patrick Maillé
Advertisement in dedicated webpage spaces or in search engines sponsored slots is
usually sold using auctions, with a payment rule that is either per view or per
click. But advertisers can be both sensitive to being viewed and being clicked. We
generalize the auction mechanism by including both pricing components.
Applying VCG auctions, we show how to compute payments to ensure incentive
compatibility from advertisers as well as maximize the total value of the
advertisement slot(s). We provide bounds for the loss of efficiency due to applying
only pay-per-click (or pay-per-view) pricing instead of our scheme. We also
describe how the generalized second price auction can be extended to this
context.
2 - Investment And Competition With Shared Spectrum
Randall Berry, Northwestern University,
Meeting the exploding demand for wireless data services will require access to
new wireless spectrum. This in turn has led to much interest in approaches for
sharing spectrum among different users. These approaches raise not only
technical challenges but also can fundamentally change the economic interactions
among wireless service providers. We consider such effects by adapting models for
price competition with congestible resources. We also study how such sharing can
impact a service provider’s incentives to invest in shared spectrum bands.
3 - Data Bundling And Pricing In The Internet Of Things
Maurizio Naldi, University of Rome Tor Vergata, Roma, Italy,
Luis Guijarro, Vicent Pla,
José Ramon Vidal
The upcoming Internet of things will generate a massive amount of data. Much of
them will be distributed and traded in a marketplace. Brokering third-parties may
ease the relationship between data producers and data consumers. Brokers take
care of bundling data coming from different sources and delivering them to
consumers within a single commercial offer. In this context, pricing data is an
extremely important decision, impacting both the broker’s role feasibility and the
success of the distributing scheme. Optimal pricing strategies are derived and
discussed, considering their impact on all the stakeholders.
WC46
209B-MCC
Demand Learning with Strategic Customers
Sponsored: Revenue Management & Pricing
Sponsored Session
Chair: Xi Chen, New York University, Stern, New York, NY,
United States,
Co-Chair: Zizhuo Wang, University of Minnesota, Minneapolis, MN,
United States,
1 - Nonparametric Algorithms For Joint Pricing And Inventory Control
With Lost-sales And Censored Demand
Beryl Boxiao Chen, University of Illinois at Chicago, Chicago, IL,
United States, , Xiuli Chao, Cong Shi
We consider the classical joint pricing and inventory control problem with lost-
sales and censored demand in which the customer’s response to selling price and
the demand distribution are not known a priori, and the only available
information for decision-making is the past sales data. A major difficulty lies in
the fact that the estimated profit function from observed sales data is multimodal
even when the expected profit function is concave. We develop a nonparametric
data-driven algorithm and show that the algorithm converges to the optimal
policy as the planning horizon increases, and obtain the convergence rate of
regret.
2 - Bayesian Dynamic Learning And Pricing With
Strategic Customers
Xi Chen, New York University, ,
Zizhuo Wang
In this talk, we study a pricing problem when the customer is aware of the seller’s
policy, and thus may behave strategically when making a purchase decision. We
first show that a naive myopic Bayesian policy (MBP) by the seller may lead to
incomplete learning —- the seller may never be able to ascertain the true type of
the customer and the regret may grow linearly in time. To resolve this issue, we
propose a randomized Bayesian policy (RBP), which updates the posterior belief
of the customer in each period with a certain probability. We show that the seller
can learn the customer type exponentially fast with the RBP even if the customer
is strategic, and the regret is bounded by a constant.
3 - Operational Implications Of Choice Paralysis
Srikanth Jagabathula, New York University,
Rene A Caldentey, Anisha Patel
We consider the operational implications of the “choice paralysis” effect, which
states that customers are less likely to choose as the number of choices becomes
large. The choice paralysis effect has been established in various lab studies, but so
far has received little attention in the operations community. To address that, we
first carry out an empirical study with supermarket data and observe that, at the
aggregate-level, the choice paralysis effect varies across different product
categories. Based on this evidence, we propose a modification to the multinomial
logit (MNL) model to capture the choice paralysis effect. In the context of the
model, we discuss the operational implications.
WC47
209C-MCC
Unique Applications in Pricing and Revenue
Management
Sponsored: Revenue Management & Pricing
Sponsored Session
Chair: Jon A Higbie, Revenue Analytics Inc, Atlanta, GA, United States,
1 - Emerging Topics In Revenue Management For The
Cruise Industry
Gregory Vogel, Holland America Line,
Much research has been done in traditional travel and hospitality industries such
as Airlines, Hotels, Resorts, Casinos etc. Very little has been done in regards to the
specific problem that are cruise lines. In this talk we discuss similarities and
differences between traditional OR research into these industries and the cruise
industry and then delve into the problems that the industry is most interested in
solving along with an overview of problems that are currently being investigated.
WC45