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Sponsored Projects 2011
“Analyzing Agent Productivity in Service Delivery Systems”
The goal of this research is to analyze factors that drive agent productivity in service delivery systems and utilize this information to improve efficiency in the allocation of work. More specifically, Yina Lu (2013), a PhD candidate in the Decision, Risk, and Operations division, advised by Marcelo Olivares, Associate Professor at Columbia Business School, wants to analyze how factors such as workload, multi-tasking, agent skill level, and skill-and-job matching would affect agents’ productivity using primary objective data, and based on this design a more efficient job routing scheme.
“Competition and Market Structure in Online Display Advertising with Ad Exchange”
Internet Display Advertising has become a multi-billion dollar industry. While in the past, advertisers would purchase display ad placements by negotiating long term contracts directly with publishers, the emergence of Ad Exchanges in recent years has significantly altered the industry landscape. Advertisers may now purchase ad placements in real-time based on specific viewer information. In this work, Santiago Balseiro (2013), a PhD candidate in the Decision, Risk, and Operations division, advised by Omar Besbes, Assistant Professor at Columbia Business School, and Gabriel Y. Weintraub, Associate Professor at Columbia Business School, intend to study various aspects associated with Ad Exchanges. In particular, they study how advertisers should run a campaign in such an exchange and the impact of the indirect competition among advertisers, in addition to investigating the type of mechanisms that are best suited to match advertisers with viewers.
“Endogeneity and Price Sensitivity in Customized Pricing”
Endogeneity occurs in customized pricing when a seller uses unrecorded customer characteristics that are correlated with price-sensitivity in setting the price. Endogeneity can lead traditional regression approaches to under-estimate price elasticity. In this study,Ahmet Serdar Simsek (2013), a PhD candidate in the Decision, Risk, and Operationsdivision, working with Robert L. Phillips, Professor of Professional Practice, and Garrett van Ryzin, Paul M. Montrone Professor of Private Enterprise, and Chair of Decision, Risk, and Operations division, use two sources of data from auto loan pricing: one from an on-line lender and one from an indirect lender to test for endogeneity. They present their results as well as recommendations for how to detect and control for endogeneity in the estimation process.
“Enhancing Healthcare OM Research via Collaboration with Kaiser Permanente”
The objective of this project is to learn how to use available quantitative tools in the most effective way to improve capacity planning and resource allocation in hospitals. Hailey Song-Hee Kim (2013), a PhD candidate in the Industrial Engineering & Operations Research division, working with Carri W. Chan, Assistant Professor at Columbia Business School, and Marcelo Olivares, are studying hospital settings and operations in order to correctly structure the models, estimate the parameters, and develop performance objectives and to find ideas for potential research questions. Additionally, there are two specific questions they are trying to answer: (1) examining whether the occupancy levels of the available recovery units with different levels of care play a role in deciding what type of recovery unit a patient is routed to after a surgery or a visit to ER and if so, how this routing pattern further affects patient outcomes and (2) developing an optimal policy for giving a preventative therapy which is done in the Intensive Care Unit (ICU) to patients with a particular disease given the prevalent shortages of ICU beds in hospitals.
“Portfolio Execution with Short-Term Predictability”
In this project, Mehmet Saglam (2013), a PhD candidate in the Decision, Risk, and Operations division, advised by Ciamac C. Moallemi, Associate Professor at Columbia Business School, would like to test whether linear decision rules can be tractable in complex and realistic portfolio execution problems. If there exists any performance gain, they would like to quantify the improvement over current algorithmic practices used in the industry. In a recent working paper, they lay out the theoretical background of using linear decision rules in large class of dynamic portfolio choice problems and in this project, they would like to apply this methodology to optimal portfolio execution problems with realistic parameters. Model parameters will be estimated from real data and using the calibrated model they will compute the best linear execution policy and compare its performance to those of current algorithms used in the industry.
“Structural Estimation of a Large-Scale Procurement Combinatorial Auction: The Chilean School-meal Project”
Combinatorial auctions are particularly useful in procurement when items exhibit cost synergies. However, allowing bidders to bundle items that do not exhibit synergies may hurt the efficiency of the allocation. In this study, Sang Won Kim (2012), a PhD candidate in the Decision, Risk, and Operations division, working with Marcelo Olivares and Gabriel Y. Weintraub, develop a structural estimation method to uncover the bidders’ cost structure of a large-scale combinatorial auction; the Chilean auction for school meals. Based on these estimates they analyze and suggest important improvements to the auction design.