2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
137
2 - Reining In Onion Prices By Introducing A Vertically Differentiated
Substitute: Models, Analysis, And Insights
Muge Yayla-Kullu, Associate Professor, University of Central
Florida, Orlando, FL, United States,
Omkar D Palsule-Desai, Nagesh Gavirneni
We examine the pricing ordeal in India’s onion markets caused by the fresh
produce traders. As a remedy, policy makers have been proposing to establish
processed produce competition in the market by either cooperatives or private
firms. We formulate and analyze this situation in a mathematical model that
captures (i) competition between non-profit and for-profit organizations, (ii)
consumers’ valuation discount for the processed produce, and (iii) perishability of
the fresh produce. We identify and discuss the conditions under which (i) it is
optimal to introduce the processed produce; and (ii) the processed onion should
be managed by cooperatives instead of private firms.
3 - Impact Of Encroachment When Competing Manufacturers Sell
Through A Common Retailer
Parshuram Hotkar, Doctoral Student, University of Texas, Austin,
University Station, B6500, Austin, TX, 78712, United States,
, Steve Gilbert
We consider a setting in which two manufacturers sell partially substitutable
products through a common retailer, and examine the impact of the development
of a direct sales channel for one of the manufacturers. We find that the retailer’s
ability to purchase from another manufacturer can alter many of the results that
have been obtained for how encroachment affects the interactions between a
manufacturer and a retailer. In addition, we find that the non-encroaching
manufacturer can benefit from his rival’s direct channel.
4 - Effectiveness Of Targeted Return Management On
Retailer’s Profitability
Tolga Aydinliyim, Assistant Professor, Baruch College, CUNY,
New York, NY, United States,
Mehmet Sekip Altug
As retailers offer more flexible return policies, customer abuse and fraudulent
returns are also on the rise. In order to combat that situation, instead of changing
the return policies for everyone, retailers started to implement a tool that
identifies those “renters”. In a price-setting newsvendor framework, we first study
the retailer’s uniform return policy in which the retailer offers the same return
policy to everyone; then we study a targeted return policy where the retailer
identifies the renters segment and offers a different return policy to that segment.
We argue how and when targeted return management leads to improvement in
retailer’s profitability.
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209C-MCC
Optimizing Pricing for Multiple Substitutable
Products
Sponsored: Revenue Management & Pricing
Sponsored Session
Chair: Candace Arai Yano, University of California-Berkeley, IEOR
Dept. and Haas School of Business, Berkeley, CA, 94720, United States,
1 - Dynamic Pricing And Replenishment Of Vertically Differentiated
Products With Customer Upgrades
Oben Ceryan, Drexel University, Philadelphia, PA, 19104,
United States, , Izak Duenyas, Ozge Sahin
We study the impact of product upgrades on a firm’s pricing and replenishment
policies by considering a multiple period, two-stage model where the firm first
sets prices and replenishment levels, and after observing the demand, it decides
whether to upgrade any customers to a higher quality product. We characterize
the structure of the optimal upgrade, pricing, and replenishment policies and find
that offering upgrades assists in preserving the vertical price differentiation
between products.
2 - Dynamic Pricing Of Vertically Differentiated Products With
Sales Milestones
Chi-Guhn Lee, University of Toronto,
Sajjad Najafi
We study the dynamic pricing of multiple substitutable products over a finite
horizon subject to sales milestone constraints. Customers are utility maximizer
and consider the relative importance between the price and the quality of
product. We formulate the problem as a Markov decision process with
probabilistic constraints and relax the constraints following the Lagrangian
relaxation to apply KKT conditions. The proposed model is specifically suitable for
applications in which the achievement of sale targets plays a crucial role for
managers such as residential real estate sales and penetration strategy.
3 - Optimizing Pricing For Multiple Substitutable Products
Kevin Li, University of California - Berkeley,
We address a retailer’s problem of setting prices, including promotion prices, over
a multi-period horizon for substitutable products within a category, considering
the effects of reference prices on customers’ strategic buying behavior, including
stockpiling. We utilize an embedded model in which customers make purchasing
and consumption decisions over multiple periods to maximize utility. We present
structural results and examples that provide insights into the properties of optimal
policies.
4 - Pricing Two Substitutable Products With Limited
Demand Information
Zhi-Long Chen, Professor, University of Maryland, 691 Market
Street East, College Park, MD, 20742, United States,
, Ming Chen
We consider a practical dynamic pricing problem with two substitutable products
involving a number of business rules and constraints commonly seen in practice.
There is limited demand information. A case with inter-product substitution only,
and a case with both inter-product substitution and intertemporal substitution are
studied. We propose DP algorithms for both cases, and for the latter, more
general, case, we develop a fully polynomial time approximation scheme. We
derive a number of managerial insights.
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210-MCC
Social Media Analytics for Business Applications
Invited: Social Media Analytics
Invited Session
Chair: Yuheng Hu, University of Illinois-Chicago, 601 S Morgan St,
Chicago, IL, 60607, United States,
1 - Content Complexity, Similarity, And Consistency In Social Media:
A Deep Learning Approach
Gene Moo Lee, University of Texas at Arlington,
Arlington, TX, United States,
Donghyuk Shin, Shu He, Andrew B Whinston
We investigate the effect of social media content on customer engagement using
company-generated posts from Tumblr. We employ state-of-the-art machine
learning approaches to extract features from textual and visual sources that
effectively capture their semantics. With such semantic representations, we
develop novel complexity, similarity, and consistency measures of social media
content. The results show that proper visual stimuli, complementary textual
content, and consistent themes have positive effects on the engagement, and that
content demanding significant concentration levels have the opposite effects. This
work shows how unstructured data can be translated into insights.
2 - Does Twitter Sentiment Move Stock Prices: Evidence From An
Event Study Of The Amsterdam Exchange
Yixin Lu, George Washington University,
The tremendous amount of information that accumulates and propagates via
social media has profound impact on individual businesses as well as the entire
market environment. This research focuses on the impact of twitter sentiment on
leading stocks traded on the Amsterdam Exchange. By combining event study
and sentiment analysis, we demonstrate that twitter peaks are strongly associated
with abnormal returns. However, such association is asymmetric with respect to
the valence of the sentiment.
3 - Patient Base And Price Premium For Online Health Consultations
Liwei Chen, University of Cincinnati, ,
Arun Rai, Xitong Guo
Online health consultation communities (OHCCs) enable physicians to signal
professional competence and compassionate care for patients, and allow patients
to spread online reviews with peer patients. We examine the interactions between
the signaling and online feedback mechanisms that explain how physicians build
trust with patients and gain social and economic advantages in healthcare
services. We scraped multilevel data and traced physicians biweekly over one year
from an OHCC in China. Using mixed effects modeling, we find interesting
interaction effects between trustworthiness signals and properties of feedback on
online patient base and price premium.
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