2015 Informs Annual Meeting

TB57

INFORMS Philadelphia – 2015

4 - The Behavioral Cost of Quality Nonconformance: Risk-averse and Experience-sampling Customers

4 - Two Different Approaches to Stochastic DEA Ole Olesen, Professor, University of Southern Denmark, Campusvej 55, Odense, 5230, Denmark, ole@sam.sdu.dk, 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.

Jordan Tong, Assistant Professor, University of Wisconsin at Madison, WI, United States of America, jordan.tong@wisc.edu, 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, ton.dieker@ieor.columbia.edu 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, ton.dieker@ieor.columbia.edu, 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, ole@sam.sdu.dk 1 - Estimating Production Functions and Frontiers using Stochastic DEA John Ruggiero, Professor, University of Dayton, Dayton, OH, United States of America, jruggiero1@udayton.edu 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, artem.b.prokhorov@gmail.com, 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, ajohnson@tamu.edu, 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.

TB56 56-Room 109A, CC

Multiple Stakeholders in NPD Cluster: New Product Development Invited Session Chair: Niyazi Taneri, SUTD, 8 Somapah Rd, Singapore, Singapore, niyazitaneri@sutd.edu.sg 1 - The Role of Decision Rights in Collaborative Development Initiatives Nektarios Oraiopoulos, Cambridge Judge Business School, University of Cambridge, Trumpington St., Cambridge, United Kingdom, n.oraiopoulos@jbs.cam.ac.uk, 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, niyazitaneri@sutd.edu.sg, 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, nilam.kaushik.13@ucl.ac.uk, 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, tpapva@hotmail.com 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, Bernard.Lamond@fsa.ulaval.ca, 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.

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