2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
344
TD31
202C-MCC
Information Economics in Operations
Sponsored: Manufacturing & Service Oper Mgmt, Service
Operations
Sponsored Session
Chair: Senthil Veeraraghavan, University of Pennsylvania, The
Wharton School, Philadelphia, PA, 19104, United States,
Co-Chair: Shiliang Cui, Georgetown University, 548 Rafik B. Hariri
Building, 37th and O Streets NW, Washington, DC, 20057, United
States,
1 - Listen To The Crowd: Network Effects And Online Reviews In
Restaurant SalesForecasting
Shawn Mankad, Cornell University, Ithaca, NY, United States,
Qiuping Yu, Masha Shunko
Using a comprehensive dataset from a major restaurant franchise, we forecast
weekly store sales using classical measures of service quality from internal surveys
at focal and neighboring stores, in addition to online ratings. Our results show
that higher quality at the neighboring stores leads to higher sales at the focal
store. We also find that the accumulation of online reviews reduces the
importance of internal quality surveys at focal and neighboring stores as
predictors.
2 - Information Sale And Competition
Kostas Bimpikis, Stanford University, ,
Davide Crapis, Alireza Tahbaz-Salehi
This paper studies the strategic interaction between a seller of information and a
set of firms competing in a downstream market. We show that the nature and
intensity of competition play a first-order role in determining the seller’s optimal
strategy. When firms’s actions are strategic complements (Bertrand competition),
it is optimal for the seller to trade with all her customers. In contrast, when
actions are strategic substitutes (Cournot competition), the seller maximizes her
profits by restricting the supply of information and/or distorting its content.
Furthermore we establish that her incentives to restrict the supply of information
grow stronger in the presence of information leakage.
3 - Efficient Information Heterogeneity In A Queue
Yang Li, CUHK Business School, Ming
Hu, Jianfu Wang
How would the growing prevalence of real-time delay information affect a service
system? We consider an M/M/1 queueing system in which only a fraction of
customers are informed about real-time delay. Perhaps surprisingly, we find that
throughput and social welfare can be unimodal in the fraction of informed
customers. In other words, some amount of information heterogeneity in the
population can lead to strictly more efficient outcomes, in terms of the system
throughput or social welfare, than information homogeneity. Moreover, we show
that the impacts of growing information prevalence on system performance
measures are determined by the equilibrium joining behavior of uninformed
customers.
4 - Multi-stage Intermediation In Display Advertising
Ozan Candogan, University of Chicago,
, Santiago Balseiro, Huseyin
Gurkan
We consider a setting where an advertiser seeks to acquire impressions from an
advertising exchange through a network of intermediaries, and characterize
mechanisms offered by strategic intermediaries when the advertiser’s value is
private. Our results indicate that the position in the intermediation process has a
significant impact on the profits of the intermediaries and the most profitable
position depends on the underlying value distribution. Intuitively, when the
private value distribution is heavy tailed, downstream intermediation positions
are more profitable, and otherwise upstream positions are more profitable. We
also analyze merger decisions of intermediaries.
TD32
203A-MCC
Revenue Mgt, Pricing IV
Contributed Session
Chair: Yanqiao Wang, UC Berkeley, Berkeley, CA, United States,
1 - Application Of Optimization Techniques And Survival Analysis On
Pricing And Revenue Management In Semiconductor Industry
Amir Meimand, Pricing Scientist, Zilliant Inc, 1781 Spyglass Drive,
Apt 359, Austin, TX, 78746, United States,
, Steve Tao, Lee Rehwinkel
Prices in some markets such as the semiconductor industries tend to decrease
over time due to market pressure, product life-cycle, etc. Hence, it is desirable to
reduce discounting behavior while maximizing sale/profit simultaneously. To
meet this goal, we present a novel two-phase method. The first phase is based on
an optimization model relies on elasticity estimation emerging from historical
transactions. The second phase is modification of optimization solution based on
price survival analysis to minimize the discount rate considering transaction date.
We also present the numerical result of model applied to a real world problem
with +2,000 products and +5,000 customers over a year.
2 - A Customized Dynamic Pricing Based Optimization Model For In-
house Electricity Consumption Scheduling With Energy Storage
Renewable Option
Goutam Dutta, Professor, Indian Institute of Management, Wing 3,
Room No 3H, Production Quantitive Methods Area, Ahmedabad,
Gujarat, 380015, India, , Krishnendra Mitra
In this paper we propose a scheduling model for electrical appliances in a dynamic
pricing environment. Initially we provide a vector of price points for the next
twenty four hours. Then we develop an optimization model that minimizes cost
to customer subject to different operating constraints of the appliances. We
consider five different cases of price variation. We also study the effects of
including energy storage and renewable energy generation at the consumer level.
In this case we propose a linear price function that helps in automatically
generating a price value for a time slot.
3 - Pricing Consumable Products To Maximize Profit
Randy Robinson, Assistant Professor, Bemidji State University,
1500 Birchmont Dr. #30, Bemidji, MN, 56601, United States,
An introduction of a new consumable product to market is expected to have a
sales growth rate that follows a sigmoid growth curve. If changes in price will
affect the growth rate of this curve, what price should the producer charge to
maximize profit over the time period in which they believe the product will
remain popular? This talk will explore an explicit solution for the optimal price
and the associated sensitivity analysis.
4 - Joint Optimization Of Capacitated Assortment And Pricing
Problem Under The Tree Logit Model
Yanqiao Wang, UC Berkeley, Berkeley, CA, United States,
, Zuo-Jun Max Shen
Assortment and pricing decisions are of significant importance to firms and have
huge influences on profit. How to jointly optimize over both assortment and
prices draws increasing attention recently. However, in the existing literature,
there is no flexible and comprehensive way to deal with the joint effects of
assortment and price since the tangle between them makes the joint optimization
problem less tractable. In this paper, we study the joint assortment and price
optimization problem under the d-level nested logit model. Assume there are k
lowest-level nests and each has n products, we develop an efficient algorithm that
runs in O(kn^2) time to locate the joint optimal assortment and prices.
TD33
203B-MCC
Queueing Models III
Contributed Session
Chair: Petra Vis, VU Amsterdam, De Boelelaan 1105, Amsterdam, 1081
HV, Netherlands,
1 - Meeting Service-level Constraints In Multi-class Service Systems
Rene Bekker, VU Amsterdam, De Boelelaan 1081a, Amsterdam,
1081 HV, Netherlands, , Ger M Koole, Petra Vis
In many service systems, the service level (SL) is defined in terms of the tail
probability of the waiting time. Different customer classes typically have different
SL constraints. We first study a call blending system with an urgent (inbound)
and best effort (outbound, email, call back) class, where the former has a severely
more stringent SL. For threshold control, we show that the waiting time
distribution is a mixture of exponentials. Second, we identify how to optimally
assign agents to customers by exploiting the waiting time process of the first
customer in line; we derive the value function for an isolated customer class and
then apply one-step policy improvement.
2 - A General Workload Conservation Law With Applications To
Queueing Systems
Muhammad A El-Taha, Professor, University of Southern Maine,
Department of Mathematics and Statistics, 96 Falmouth Street,
Portland, ME, 04104-9300, United States,
In the spirit of Little’s law L=\lambda W and its extension H=\lambda G we use
sample-path analysis to give a general conservation law. For queueing models the
law relates the asymptotic average workload in the system to the conditional
asymptotic average sojourn time and service times distribution function. This law
generalizes previously obtained conservation laws for both single and multi-server
systems, and anticipating and non-anticipating scheduling disciplines.
Applications to single and multi-class queueing and other systems that illustrate
the versatility of this law are given.
TD31