Informs 2015

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INFORMS Philadelphia – 2015
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4 - The Behavioral Cost of Quality Nonconformance:
Risk-averse and Experience-sampling Customers
Jordan Tong, Assistant Professor, University of Wisconsin at
Madison, WI, United States of America, ,
Greg Decroix
Why do customers purchase less when quality is inconsistent? A common
explanation is that customers have risk-averse preferences: they inherently prefer
less uncertainty. Another explanation, however, is that tendencies towards low-
variance alternatives are due to a learning process from experience. We show that
optimal pricing and promotion decisions can differ significantly depending on
which explanation is modeled, thereby illuminating the costs of nonconformance
and how to mitigate them.
TB54
54-Room 108A, CC
Approximations of Queueing Performance for
Rapid Systems Design
Cluster: Tutorials
Invited Session
Chair: Ton Dieker, Columbia University, 500 W 120 St, New York, NY,
United States of America,
1 - Tutorial: Approximations of Queueing Performance for Rapid
Systems Design
Ton Dieker, Columbia University, 500 W 120 St, New York, NY,
United States of America, ,
Steve Hackman
Recent advances in queueing analysis have yielded tractable approximations of
performance metrics that can be used to quickly explore initial designs, to reduce
computational burdens associated with simulation, or even to eliminate the need
for simulation altogether. This TutORial takes you on an accessible tour of these
recent methods, shows you how to apply them using numerical examples drawn
from real applications, and discusses implementation challenges and potential
opportunities.
TB55
55-Room 108B, CC
Stochastic Methods in Efficiency Analysis
Cluster: Data Envelopment Analysis
Invited Session
Chair: Ole Olesen, Professor, University of Southern Denmark,
Campusvej 55, Odense, 5230, Denmark,
1 - Estimating Production Functions and Frontiers using
Stochastic DEA
John Ruggiero, Professor, University of Dayton, Dayton, OH,
United States of America,
In this paper, we present two methods to estimate production functions and
frontiers (deterministic and stochastic). We constrain the technology using the
Afriat conditions and consider minimizing the sum of absolute and/or squared
errors. We extend this method using locally weighted least squares in the spirit of
loess (local regression.)
2 - Endogeneity in Stochastic Frontier Models
Artem Prokhorov, U Sydney, CIREQ, St. Petersburg State U,
Business School, Sydney, NS, 2006, Australia,
, Peter Schmidt, Christine Amsler
Stochastic frontier models are typically estimated by MLE or corrected OLS. The
consistency of either estimator depends on exogeneity of the explanatory
variables (inputs, in the production frontier setting). We will investigate the case
that one or more of the inputs is endogenous, in the simultaneous equation sense
of endogeneity. We will consider modifications of standard procedures under
endogeneity for the stochastic frontier setting.
3 - Shape Constrained Kernel Weighted Least Squares for the
Estimation of Production Functions
Andrew Johnson, Texas A&M, College Station, TX,
United States of America, , Daisuke Yagi
This paper proposes a unifying model and estimator we call Shape Constrained
Kernel-weighted Least Squares (SCKLS). We show the relationship between the
SCKLS estimator and both the Convex Nonparametric Least Squares (CNLS) and
Du’s estimators. Specifically, the SCKLS estimator converges to the CNLS
estimator as the bandwidth goes to zero. We compare the performance of the
three estimators (SCKLS, CNLS, and Du’s estimator) via Monte Carlo simulations.
4 - Two Different Approaches to Stochastic DEA
Ole Olesen, Professor, University of Southern Denmark,
Campusvej 55, Odense, 5230, Denmark, ,
Niels Chr. Petersen
Focus is on different views on extending DEA to a stochastic setting. The
management science framework does not focus to model performance using a
statistical model based on a specific Data Generating Process (DGP). Some
stochastic DEA models focus on replacing the observed input output observations
with DMU specific distributions. The statistical framework insists on an axiomatic
approach to a statistical model, including a specification of a DGP. We illustrate
these differences.
TB56
56-Room 109A, CC
Multiple Stakeholders in NPD
Cluster: New Product Development
Invited Session
Chair: Niyazi Taneri, SUTD, 8 Somapah Rd, Singapore, Singapore,
1 - The Role of Decision Rights in Collaborative
Development Initiatives
Nektarios Oraiopoulos, Cambridge Judge Business School,
University of Cambridge, Trumpington St., Cambridge, United
Kingdom, , Vishal Agrawal
In this paper, we study initiatives for co-development of new products and
technologies. In such settings, it may be difficult a priori to specify contracts
contingent on the outcome. Therefore, we investigate the efficacy of different
contractual structures, which instead specify the decision-making process.
2 - Structuring New Product Development Partnerships
Niyazi Taneri, SUTD, 8 Somapah Rd, Singapore, Singapore,
, Arnoud De Meyer
New product development partnerships involve a high degree or risk, information
and incentive problems across various stakeholders. Partners structure their
alliances to address such concerns. We identify factors that affect the structure of
the partnership and the performance of the partnership.
3 - The Impact of Continuous Product Development and Customer
Feedback on Mobile App Performance
Nilam Kaushik, University College London, University College
London, London, United Kingdom,
Bilal Gokpinar
Mobile application development differs from traditional product development
owing to low barriers of entry, the ability to provide continuous software updates,
and ease of access to customer feedback. Using a dataset from the App Store, and
drawing from a combination of text mining techniques and econometric methods,
we investigate the impact of incorporating customer feedback on mobile app
performance.
TB57
57-Room 109B, CC
Assorted Topics in Renewable Energy
Sponsor: ENRE – Energy II – Other (e.g., Policy, Natural Gas,
Climate Change)
Sponsored Session
Chair: Anthony Papavasiliou, Université Catholique de Louvain,
Voie du Roman Pays 34, Louvain la Neuve, Ou, 1348, Belgium,
1 - A Controlled Approximation Scheme for Managing Hydroelectric
Generation with Multiple Reservoirs
Bernard Lamond, Professor, Universite Laval, Dep. Operations &
Systemes de Decision, 2325, Rue de la Terrasse #2620, Quebec,
QC, G1V 0A6, Canada, ,
Pascal Lang, Pascal Cote, Luckny Zephyr
We present an approach for adaptive approximation of the value function in
stochastic dynamic programming. We use a simplicial partition of the state space
to construct a nonseparable piecewise affine approximation which is refined
iteratively using lower and upper bounds on the value function. The proposed
scheme is experimented numerically in the context of hydroelectric production
across multiple reservoirs and power plants.
TB57