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SA37 ■ SA37 37- North 226 A- CC Revenue Management and Pricing in Practice Sponsor: Revenue Management & Pricing Sponsored Session Chair: Tugrul Sanli, Director, R&D, SAS Institute Inc., SAS Campus Drive, Cary, NC, 27513, United States of America, Tugrul.Sanli@sas.com 1 - Randomized Linear Programming Approach to Revenue Management Vijay Desai, Opertations Research Specialist, SAS Institute Inc., SAS Campus Dr, Cary, NC, 27513, United States of America, VijayV.Desai@sas.com, Altan Gulcu We provide a high-level overview of our approach to RM using RLP. Following are the key features of our methodology: a) Pricing of price-dependent products. b) Handles network-level overbooking as opposed to resource-level overbooking typically found in practice. c) Allows for imposition of service level constraints. d) Computes ancillary outputs such as occupancy forecast, revenue forecast and service levels, which are useful metrics for a revenue manager. 2 - Dynamic Pricing and Revenue Management Maarten Oosten, SAS Institute, World Headquarters, SAS Campus Drive, Cary, NC, 27513, United States of America, maarten.oosten@sas.com New technologies allow for pricies to be changed continuously, and optimal dynamic pricing algorithms take this freedom explicitly into account. In this presentation we explore several directions in which this can be taken. 3 - Estimation of Nested Logit Models using Data from a Single Firm Jeff Newman, Research Engineer, Georgia Institute of Technology, 790 Atlantic Drive, Civil Engineering, Atlanta, GA, 30332, United States of America, jeff@newman.me, Laurie Garrow, Mark Ferguson We examine identification issues for estimating parameters for discrete choice models with censored data. Most work in revenue management using such models has been focused on simple multinomial logit models, because the unique IIA property of this model makes estimating and applying parameters convenient. However, IIA is not usually consistent with actual choice behaviors. We examine the benefits and drawbacks of employing a nested logit model, which does not exhibit IIA. 4 - Improving the Forecasting Accuracy of Hotel Arrivals: A New Non-homogeneous Poisson Approach Misuk Lee, IHG, 3 Ravinia Drive, Atlanta, GA, 30327, United States of America, Misuk.Lee@ihg.com Demand forecast is one of key components of hotel revenue management. This study develops a new non-homogenous Poisson process approach to short-term demand forecast. By considering seasonality and heterogeneous booking curve patterns, we find better estimates for demand processes and thus improve forecasting accuracy. We present validation results on IHG hotel data along with a comparison to other benchmark models. ■ SA38 38- North 226 B- CC Impact of Customer Behavior on Service Sponsor: Service Science Sponsored Session Chair: Margaret Pierson, Assistant Professor, Tuck at Dartmouth, Hanover, NH, United States of America, mpierson@hbs.edu 1 - How Do Customers Respond to Service Quality Competition? Ryan Buell, Assistant Professor, Harvard Business School, Morgan Hall T37, Boston, MA, 02163, United States of America, rbuell@hbs.edu, Dennis Campbell, Frances Frei When does increased service quality competition lead to customer defection, and which customers are most likely to defect? We find that customers defect at a higher rate from the incumbent following increased service quality (price) competition when the incumbent offers high (low) quality service relative to existing competitors in a local market. We further show that it is the high quality incumbent’s most profitable customers who are the most attracted by superior quality entrants. INFORMS Phoenix – 2012 68 2 - Modeling Customer Behavior in Multichannel Customer Support Services: An Information Stock Approach Serguei Netessine, Professor, INSEAD, Boulevard de Constance, Fountainbleau, 77305, France, Serguei.Netessine@insead.edu, Kinshuk Jerath, Anuj Kumar We analyze multichannel customer support environment of a health insurance firm in the US. We build a structural probability model to understand the customers’ query arrival and channel choice processes. Our estimates suggest the telephone channel in our setting on average provides 20 times more information than the Web channel and that the Web on average provides information need instead of information gain – Web in our setting seems to confuse customers. 3 - Customer Response to Short-Term Price Fluctuations Margaret Pierson, Assistant Professor, Tuck at Dartmouth, Hanover, NH, United States of America, mpierson@hbs.edu Transactions at 15 gasoline stations in Massachusetts over two years are used to estimate consumer elasticity with respect to price on a transaction basis. A significant proportion of the observed transactions display high sensitivity to price. This customer behavior results in congestion at pumps during high prices, a counterintuitive result which constrains stations’ price choices in practice. ■ SA39 39- North 226 C- CC Service Scripting and Value Co-Creation Sponsor: Service Science Sponsored Session Chair: Gregory Heim, Associate Professor, Mays Business School at Texas A&M University, 320 Wehner Building, 4217 TAMU, College Station, TX, 77843-4217, United States of America, gheim@mays.tamu.edu 1 - Scripting and Improvisation in Service Environments Enrico Secchi, University of Victoria, Peter B. Gustavson School of Business, Business & Economics Building Room 254, Victoria, BC, V8P 5C2, Canada, esecchi@clemson.edu, Rohit Verma, Aleda Roth Using the insights of the research on scripting and organizational improvisation, we develop an econometric model of the impact of different degrees of scripting and improvisation on services financial outcomes. We test our model using survey data and self reported financial performance from the hospitality industry. 2 - Co-Creation of Value for IT-Enabled Services: A Case of Geocaching Tuure Tuunanen, University of Oulu, Department of Information Processing Science, P.O. 3000, 90014 University of Oulu, Finland, tuure@tuunanen.fi, Tero Vartiainen This study uses laddering interviews to explore how value is co-created for ITenabled services, more precisely geocaching. The results reveal that geocaching is distinctly hedonic in nature. The results also demonstrate how the consumer information systems framework can be applied for understanding which factors influence value co-creation for IT-enabled services. 3 - Analysis of Role of Service Variety and Real Options in Resort Timeshare Service Value Gregory Heim, Associate Professor, Mays Business School at Texas A&M University, 320 Wehner Building, 4217 TAMU, College Station, TX, 77843-4217, United States of America, gheim@mays.tamu.edu Although a major class of hospitality/travel experience service, little empirical research has examined timeshares or other fractional hospitality services. This paper examines whether service variety, in terms of breadth of vacation service experiences, or real options more strongly affect the perceived quality, valuation, and ownership of resort hotel timeshare services. We analyze hypotheses using both cross-sectional and longitudinal data sets.
■ SA40 40- North 227 A- CC Dynamic Models for Sustainable Energy Policy Analysis Sponsor: Energy, Natural Res & the Environment/Energy Sponsored Session Chair: Pedro Linares, Comillas P. University, Alberto Aguilera 25, Madrid, 28015, Spain, pedro.linares@upcomillas.es 1 - Canadian Energy Supply and Demand with ENERGY 2020: Scenarios and Sensitivity Cases Matthew Hansen, Market Analyst, National Energy Board, 444-7th Ave., SW, Calgary, AB, T3C 0T1, Canada, Matthew.Hansen@neb-one.gc.ca The National Energy Board periodically releases long-term projections of Canadian energy supply and demand as part of its Energy Futures series. Since 2007, the ENERGY 2020 model has been central to this analysis. This presentation will describe how the National Energy Board uses ENERGY 2020 to create the scenarios and sensitivity cases featured in the Energy Futures reports. 2 - Multi-stage Stochastic Optimization of an Energy System Model Joseph DeCarolis, Assistant Professor, North Carolina State University, 2501 Stinson Drive, Campus Box 7908, Raleigh, NC, 27695, United States of America, jdecarolis@ncsu.edu, Kevin Hunter, Sarat Sreepathi We perform multi-stage stochastic optimization of a simplified energy system. The system consists of roughly 30 technologies used to supply primary energy resources, refine petroleum, generate electricity, and serve end use demands. The model incorporates crude oil, natural gas, and coal prices as stochastic parameters. Results indicate that the energy system requires little recourse as uncertainty is revealed over a multi-decadal time horizon. 3 - Incorporating Endogenous Demand into Capacity Expansion Models for Developing Countries Rhonda Jordan, PhD Candidate, Massachusetts Institute of Technology, 143 Albany Street, #201A, Cambridge, MA, 02139, United States of America, rjordan@mit.edu Using a novel combination of approximate dynamic programming, system dynamics and linear programming, this research develops a power system capacity expansion model that incorporates both the technical details of power grid operation and the salient features of electricity demand in developing countries. Unlike traditional planning models, demand is represented endogenously. The capacity expansion strategies identified in this research are compared against that of more traditional approaches. 4 - A Dynamic Model for Sustainable Energy Policy Making in Spain Alvaro Lopez-Peña, Comillas P. University, IIT, Santa Cruz de Marcenado 26, Madrid, 28015, Spain, alvaro.lopezpena@iit.upcomillas.es, Pedro Linares, Ignacio Pérez-Arriaga Today, there is an important need for sound sustainable energy policies. For assessing them, mathematical models are needed, which allow to represent energy systems’ evolution over the long term under different policy assumptions (trajectories). We present a dynamic model applied to Spain, which aims at representing realistic trajectories. By realistic, we mean that it takes into account important aspects of energy systems such as imperfect markets, investor’s myopia and risk aversion. ■ SA41 41- North 227 B- CC Models in Energy Investment Contributed Session Chair: Carlos Ruiz, École Centrale Paris and SupÈlec, Grande Voie des Vignes, Ch‚tenay-Malabry, 92295, France, carlosruizmora@gmail.com 1 - On the Value of Improved Models for the Electricity Sector Alberto Lamadrid, Graduate Student, Cornell University, 419 Warren Hall, Ithaca, NY, 14850, United States of America, ajl259@cornell.edu, Tim Mount, Ray Zimmerman, Robert Thomas This paper measures the value of the stochastic solution for a system with high penetration of renewable energy sources, contrasting it to a deterministic formulation with fixed reserves, as used by System Operators (SO). The performance analysis focuses on measures of the system economic costs. Our model has a SO minimizing the expected cost of providing both energy and ancillary services with a security constrained OPF. Uncertainty is reproduced using a Markovian transition probability matrix. INFORMS Phoenix – 2012 69 SA42 2 - Mathematical Model for Planning Investments in Energy Sources for Argentina Julio Rolando Flores, Becario, INGAR, Eva Peron 2660, Santa Fe, SF, 3000, Argentina, jflores@santafe-conicet.gov.ar, Jorge M. Montagna, Aldo Vecchietti This paper presents a mathematical programming model for planning investment in energy sources for Argentina. The model considers the use of renewable and not renewable sources and uncertainties in demands, costs, and the amount of reserves of fossil fuels. The objective function of is to minimize the investment and operation costs of the energy supply. The results provide the visualization of the investments made: time periods in and their amounts and also how the energy matrix is affected. 3 - Biomass Based Energy Logistics System Wooseung Jang, Professor, University of Missouri, E3437 Lafferre Hall, Columbia, MO, 65211, United States of America, jangw@missouri.edu, Rana Afzali Baghdadabadi, Cerry Klein, James Noble, Zhongwei Yu, Kurt Ehlers We develop an optimization model supporting the multi-stage decision making of infrastructure investment and operation of the biomass logistics system. In addition, we build a database for biomass availability, cost and other supply information. Our work is applied to the biomass power plants scheduled to operate in Missouri. 4 - Transmission Expansion Planning using an AC Model: Formulations and Possible Relaxations Hui Zhang, Research Associate, Arizona State University, 1223 S Dorsey Ln, Apt 101, Tempe, AZ, 85281, United States of America, hui.zhang@asu.edu, Hans Mittelmann, Vijay Vittal, Gerald Heydt Starting with two MINLP models, this paper explores the possibility of applying AC-based models to the transmission expansion planning (TEP) problem. Two NLP relaxation models are then proposed by relaxing the binary decision variables. A reformulation-linearization-technique (RLT) based relaxation model is also presented in the paper. The simulation results show that by using proper reformulations or relaxations, it is possible to apply the AC models to TEP problems and obtain a good solution. 5 - Robust Reliability Optimization by System Design and Components Allocation Carlos Ruiz, École Centrale Paris and Supèlec, Grande Voie des Vignes, Châtenay-Malabry, 92295, France, carlosruizmora@gmail.com, Rodrigo Mena, Enrico Zio, Yanfu Li We address the problem of power system design and components allocation under multiple sources of uncertainty. We consider a set of fixed buses with uncertain demand loads and we seek to identify the electrical lines and generating units that should be installed in order to minimize the system operational cost and maximize its reliability. The optimization relies on a bilevel model that is robust against generation capacity variability as well as unit and line failures. ■ SA42 42- North 227 C- CC Strategic Issues in Freight Transportation Contributed Session Chair: Zhougeng Lin, PhD Student, University of Portsmouth, Lion Gate Building, Lion Terrace, Portsmouth, PO1 3HF, United Kingdom, Zhougeng.Lin@Port.Ac,Uk 1 - Mixed Fleet Dispatching Optimization in Truckload Transportation Hector A. Vergara, Visiting Assistant Professor, Oregon State University, 204 Rogers Hall, Corvallis, OR, 97331, United States of America, vergarah@onid.orst.edu, Sarah Root In a mixed fleet dispatching system for truckload transportation some truckloads are sent direct point-to-point while others are routed through a network of relay points where drivers are exchanged allowing them to return home more frequently. We propose a mathematical formulation for strategic relay network design and dispatch mode selection that incorporates several operational constraints within the variable definition. Computational results are presented along with areas for future research. 2 - Freight Network Design with Pricing and Economies of Scale Panagiotis Ypsilantis, PhD Candidate, RSM, Erasmus University, Burgemeester Oudlaan 50, Rotterdam, Netherlands, pypsilantis@rsm.nl, Rob Zuidwijk The freight service network design in a strategic level is formulated as a bi-level mathematical program; the pricing, design and economies of scale are considered in a competitive environment. The net revenues of a TOC that operates barge and train connections to inland terminals according to the extended gate concept are maximized while the total costs faced by the users of the network are minimized. A solution approach for this problem and some numerical results are presented and discussed.
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