2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
492
WE26
110B-MCC
Information Systems IV
Contributed Session
1 - Information System that Implements Shapley Algorithm For The
Evaluation Of The Competitive Value at a Cluster And
Enterprise Level
Miguel Jimenez, Information systems and technologies leader,
Universidad de la Costa, Barranquilla, 08002, Colombia,
, Luis Eduardo Ramirez,
Luis Eduardo Ramirez, Lauren Castro, Lauren Castro,
Diana Gineth Ramirez-Rios, Orlando Bustamante,
Stefanie Cortina, Dionicio Neira, William Manjarres De Avila
Based on the strategic and financial valuation of enterprises that wish to
participate in a cluster, we developed an information system that allows the
enterprises evaluate their competiive value with or without their participation in
the cluster, by implementing Shapley algorithm to solve a cooperative game
model for supply chains.
2 - Advertising Competition With Third Party Cookies
Arslan Aziz, Carnegie Mellon University, 5624 Fifth Ave, Apt C16,
Pittsburgh, PA, 15232, United States, ,
Rahul Telang
Tracking of online consumer behavior by third party data vendors has become
ubiquitous. Data from such tracking is made available to advertisers to help
increase the returns from targeting. However, such information may also increase
competition among advertisers seeking to target the same consumers. We describe
a duopoly model of brand advertisers competing for consumers with uncorrelated
brand preferences in a second-price auction. We find the conditions under which
availability of third party tracked data might reduce brand surplus by intensifying
competition.
WE27
201A-MCC
DMA Business Analytics
Contributed Session
Chair: Byeong-Yun Chang, Ajou University, San5 Woncheon-dong,
Yeongtong-gu, Suwon, 443-749, Korea, Republic of,
1 - Relationship Between R2 And F Statistic In Linear Regression
Nizar Zaarour, Assistant Teaching Professor, Northeastern
University, Boston, MA, 02115, United States,
Emanuel Melachrinoudis
There are several misconceptions in interpreting the value of R2 in Regression
Analysis. R2 is heavily dependent on the sample size n while outliers may skew
its value. In this paper, we comment on these observations and express the
relationship between the R2 and the F statistic to derive the range of values of R2
that provide consistent results with the Hypothesis Testing of the slope. This
analysis is done by considering the Simple Linear Regression case, where there is
only one independent variable k.
2 - Heuristic Search For Good Decisions In Generalized Quadratic
Assignment Problems
Steven Orla Kimbrough, Professor, University of Pennsylvania,
103 Bentley Avenue, Bala Cynwyd, PA, 19004, United States,
, Monique Guignard-Spielberg,
Frederic H Murphy
We discuss decision sweeping of optimization models, in which we collect a
number of judiciously chosen decisions (feasible and infeasible settings of the
decision variables) from the larger space of decisions. We focus on the resulting
insights, especially with regard to Generalized Quadratic Assignment Problems
with soft constraints. In particular, we explore alternative heuristics for generating
decisions of interest.
3 - Predicting Urban Blight Using A Data Science Approach
Naveen Kumar, University of Memphis, Memphis, TN, United
States, , William J Kettinger, Chen Zhang
The existence of blighted neighborhoods is detrimental to public health, safety,
and economic growth of urban areas. Identifying properties where early blight
interventions would result in improvement of neighborhoods can have
tremendous value to property owners, policymakers, and society. However,
understanding urban blight is a complex problem demanding advanced data
science. A wide variety of evolving social, economic, and political factors interact
with each other causing the problem. We propose to predict blight incidences
using data analytics and recommend early interventions to reduce blight
incidences in the City of Memphis.
4 - Does Information Transparency Help Retain Customers? Evidence
From The Insurance Industry
Zhi Cheng, Temple University, Philadelphia, PA, United States,
Ting Li, Paul Pavlou
This work investigates whether and how information transparency affects
customer churn. Two competing theories predict this effect, price elasticity (that
induces churn) and high product informedness (that reduces churn). To address
this tension, we use a unique dataset from a major European insurance company
to show that customers acquired from channels with higher information
transparency (a price comparison website) are less likely to churn than those from
lower transparent channels by 3%, implying that information transparency helps
reduce customer churn. Our findings suggest managers better allocate resources
across channels to reduce churn by considering information transparency.
5 - A Study On Stock Prices Forecasting
Byeong-Yun Chang, Associate Professor, Ajou University, San 5
Woncheon-dong, Yeongtong-gu, Suwon, 443-749, Korea,
Republic of, Yucong Chen
Stock price forecasting is a very popular issues in nowadays, which can make a
contribution to the investing technologies and facilitate those who want to get a
better understanding of stocks’ trend line in the future so as to make their
investment decisions. this research is going to use a modified two stage EWMA
and classical method, ARIMA and MAR to do prediction for companies’ stock
price and electricity. For further work, we are going to propose a hybird model
which combine TS-EWMA, ARIMA, and MARS.
WE28
201B-MCC
Retail Operations I
Sponsored: Manufacturing & Service Oper Mgmt
Sponsored Session
Chair: Jan C Fransoo, Eindhoven University of Technology,
Eindhoven, Netherlands,
1 - Optimal Channel Choices Of Traditional Retail
Jiwen Ge, PhD Candidate, Eindhoven University of Technology,
Eindhoven, Netherlands, Dorothee Honhon,
Jan C Fransoo, Lei Zhao
Nanostores are small retail stores which are prevalent in the mega-cities of
emerging markets. We consider one CPG manufacturer selling one product to a
cluster of nanostores either via the wholesale or the direct channel. We provide
optimality conditions for each channel strategy when market demand is constant
or grows deterministically within a finite time horizon.
2 - Coordinated Delivery To Nanostores In Megacities
Ruidian Song, Tsinghua University, Beijing, 100084, China,
, Lei Zhao, Jan C Fransoo,
Tom Van Woensel
In megacities in emerging economies, there exists a large amount of
independently operated, traditional format, small grocery stores (nanostores). The
limitation in store space and cash flow force them to order frequently with small
order sizes, which results in high delivery cost. We study potential strategies to
coordinate these deliveries and examine their impact.
3 - Demand Estimation Under Multi-store Multi-product Substitution
In High Density Traditional Retail
Tianhu Deng, Tsinghua University, Beijing, China,
, Mingchao Wan, Lei Zhao, Jan C Fransoo
In large cities in emerging economies, traditional retail is present in a very high
density, with multiple independently owned small stores in each city block.
Consequently, when faced with a stockout, consumers may not only substitute
with a different product in the same store, but also switch to a neighboring store.
We study this problem using both Nested Logit Model and Exogenous Model.
Furthermore, we estimate the parameters of the two models using a Markov
chain Monte Carlo algorithm in a Bayesian manner. We numerically find that the
Nested Logit model outperforms the Exogenous Substitution model in estimating
substitution probabilities.
WE26