Informs 2015

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INFORMS Philadelphia – 2015
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45-Room 103C, CC
Social Learning and Revenue Management
Sponsor: Revenue Management and Pricing
Sponsored Session
Chair: Costis Maglaras, Columbia Business School, New York, NY,
10027, United States of America,
Co-Chair: Alireza Tahbaz-Salehi, Columbia Business School,
3022 Broadway, Uris Hall 418, New York, NY, 10023,
United States of America,
1 - Monopoly Pricing in the Presence of Social Learning
Davide Crapis, Columbia Business School, 3022 Broadway,
New York, NY, 10027, United States of America,
, Bar Ifrach, Costis Maglaras,
Marco Scarsini
A monopolist offers a product to a market of consumers with heterogeneous
preferences. Consumers are uninformed about product quality and learn from
reviews of others. First, we show that learning eventually occurs. Then, we
characterize the learning trajectory via a mean-field approximation that highlights
how the learning process depends on price and heterogeneity. Finally, we solve
the pricing problem and show that policies that account for social learning
increase revenues considerably.
2 - Networks, Shocks, and Systemic Risk
Alireza Tahbaz-Salehi, Columbia Business School, 3022
Broadway, Uris Hall 418, New York, NY, 10023, United States of
America, , Daron Acemoglu, Asu Ozdaglar
We develop a unified framework for the study of how network interactions can
function as a mechanism for propagation and amplification of microeconomic
shocks. The framework nests various classes of games over networks, models of
macroeconomic risk originating from microeconomic shocks, and models of
financial interactions.
3 - Market Entry under Competitive Learning
Kimon Drakopoulos, , Asu Ozdaglar,
Daron Acemoglu
We consider a market entry game with two players, an incumbent and an
entrant. The market can be of two types: (a)bad in which case the demand is fully
elastic at a price \bar{p} or(b) good in which case there is a positive arrival rate of
consumers who are willing to buy at higher prices. The entrant is learning the
type of the market by observing the flow of prove that the problem
has the structure of a war of attrition game and study its weak perfect Bayesian
equilibria.
4 - Social Learning with Differentiated Products
Arthur Campbell, Associate Professor, Yale University, School of
Management, 135 Prospect Street, P.O. Box 208200, New Haven,
CT, 06520-8200, United States of America,
This paper embeds social learning in a model of firms producing differentiated
products. We consider how the structure of social relationships between
consumers influence pricing and welfare. The model considers how a variety of
characteristics of the social network influence these outcomes. It also serves to
highlight the challenges one faces in using metrics such as consumer awareness
and the sensitivity of demand to prices as measures of informational efficiency in
markets.
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46-Room 104A, CC
Empirical Research in Supply Chains and
Service Management
Sponsor: Manufacturing & Service Oper Mgmt/Service Operations
Sponsored Session
Chair: Marcelo Olivares, Assistant Professor, Universidad de Chile,
Republica 701, Santiago, Chile,
1 - Estimating Customer Spillover Learning of Service Quality:
A Bayesian Approach
Andres Musalem, Universidad de Chile, Republica 701, Santiago,
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.
2 - Spatial Competition and Preemptive Entry in the Discount
Retail Industry
Fanyin Zheng, Columbia Business School, 3022 Broadway, New
York, NY, United States of America,
I study the competitive store location decisions of discount retail chains in this
paper. I model firms’ entry decisions using a dynamic duopoly location game and
allow stores to compete over the shopping-dollars of close-by consumers. I use
various economic modeling technics to make the model tractable and infer
market divisions from data using a clustering algorithm. The empirical analysis
suggests that dynamic competitive considerations are important in chain stores’
location decisions.
3 - Using Real-time Operational Data to Increase Labor
Productivity in Retail
Marcelo Olivares, Assistant Professor, Universidad de Chile,
Republica 701, Santiago, Chile,
We develop a methodology to re-assign sales employees across departments in a
large retail store in order to improve productivity. Our method seeks to maximize
the effectiveness of labor by allocating employees to departments that require
inmediate assistance and where this assistance has a larger impact of sales. The
method combines empirical methods to measure the impact of assistance and
store operational data collected through video analytics to reassign employees in
real-time.
4 - Consumer Search and the Structure of Personal Networks
Raghuram Iyengar, Associate Professor, The Wharton School,
University of Pennsylvania, 3730 Walnut Street Suite 700,
Philadelphia, PA, 19104, United States of America,
We study how consumers’ information search for and purchase of new products
are affected by structure of their personal network. To address threats to internal
validity common in network studies, we conduct a randomized experiment in
which we manipulate the similarity of preference among consumers and their
network contacts. We estimate consumers’ utility function and determine how
network antecedents moderate the weight on others’ information.
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47-Room 104B, CC
Sustainability in Food Supply Chains
Sponsor: Manufacturing & Service Oper Mgmt/Sustainable
Operations
Sponsored Session
Chair: Erkut Sonmez, Assistant Professor, Boston College,
140 Commonwealth Ave, Fulton Hall, Chestnut Hill, MA, 02446,
United States of America,
1 - Supply Chain Analysis of Contract Farming
A. Serdar Simsek, Cornell ORIE, 282 Rhodes Hall, Ithaca, NY,
14853, United States of America, Awi
Federgruen, Upmanu Lall
Contract farming sustains the operations of vulnerable farmers while better
positioning the manufacturers to manage their supply risks. In this setting, a
manufacturer who owns several production plants -each with a random demand
for the crop- selects the set of farmers that minimizes her expected procurement
and distribution costs before the growing season. We present two solution
methods to this problem. We applied our model to a company contracting with
hundreds of small farmers in India.
2 - Processed Produce: Introduction, Pricing, and Profit Orientation
Omkar Palsule-desai, Faculty, Indian Institute of Management
Indore, Rau Pithampur Road, Indore, India,
Muge Yayla-Kullu, Nagesh Gavirneni
We examine product characteristics and market dynamics to identify conditions
under which it is optimal to introduce the processed produce, and it should be
managed by cooperatives instead of private firms. We develop a mathematical
model capturing (i) competition between non-profit and for-profit firms, (ii)
consumers’ valuation discount, and (iii) product perishability. We provide ample
evidences to policy makers promoting processed products offered by cooperatives.
3 - Converting Retail Food Waste Into By-product
Deishin Lee, Assistant Professor, Boston College, 140
Commonwealth Ave,, Fulton Hall 344, Chestnut Hill, MA, 02467,
United States of America, , Mustafa Tongarlak
By-product synergy (BPS) is a form of joint production that uses the waste stream
from one (primary) process as useful input into another (secondary) process. We
investigate how BPS can mitigate food waste in a retail grocer setting, and how it
interacts with other mechanisms for reducing waste (i.e., waste disposal fee and
tax credit for food donation). We derive the retailer’s optimal order policy under
BPS, showing how it affects the amount of waste.
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