Short Programs

Discrete Choice Analysis: Predicting Demand and Market Shares [14.61s]

Date: June 14-18, 2010 | Tuition: $3,900 | Continuing Education Units (CEUs): 2.9 (tentative)

Overview  |  Learning Objectives  |  Who Should Attend  |  Outline of the Program  | 
Topics Covered Include the Following  |  Schedule  |  Included in Tuition  | 
Comments from Previous Participants  |  About the Presenters  |  Scholarships  |  Updates

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Overview

Discrete choice models are widely used for the analysis of individual choice behavior. Recent applications to predict changes in demand and market shares include areas such as: choice of travel mode, coffee brand, telephone service, soft drinks and other foods, and choice of durables such as automobiles, air conditioners and houses. Discrete (or qualitative) choice analysis was initially developed by researchers in psychology, but has been extended to apply to choice problems in many fields. It is used in marketing research to guide product positioning, pricing, product concept testing, and many other areas of strategic and tactical interest.

This one-week program undertakes an in-depth study of discrete choice models and their applications. It provides participants with the practical tools necessary for applying new discrete choice techniques. By examining actual case studies of discrete choice methods, students will be familiarized with problems of data collection, model formulation, testing, and forecasting, and will gain hands-on application experience by applying freely available software to estimate and test discrete choice models from real databases.

Learning Objectives

• Understand discrete choice models and their applications.
• Learn to apply new discrete choice techniques.
• Understand problems of data collection, model formulation, testing, and forecasting, as learned through case studies of discrete choice methods.
• Utilize commonly available software to estimate and test discrete choice models from real data bases.
• Evaluate theories of choice, random utility models, probabilistic choice models, alternative model formulations, statistical estimation procedures appropriate for alternative data sources, currently available computer software, tests of validity, and forecasting procedures.

Who Should Attend

This program is intended for marketing researchers and analysts, economists, operations researchers, engineers, planners, managers and industry, government and academic researchers who are interested in understanding and predicting consumer choices, demand and market share. Participants should have a working knowledge of basic statistical methods.

Outline of the Program

The course consists of a series of lectures and recitations that develop the concepts and techniques of discrete choice and demonstrate their applications. The course also includes labs, scheduled for the afternoons on Monday through Thursday. The goal of the labs is to apply the material covered in the lectures by using freely available discrete choice software and data sets.

Topics Covered Include the Following

The material covered includes: theories of choice, random utility models, probabilistic choice models, alternative model formulations, statistical estimation procedures appropriate for alternative data sources, currently available computer software, tests of validity, forecasting procedures and examples of empirical applications.

More specifically, the following subjects will be addressed during the course:

• Choice Behavior
• Binary Choice Models
• Stated Preference Surveys
• Multinomial Choice Models: Properties of Probit, Logit and Discriminant Analysis
• Specification and Estimation of Discrete Choice Models
• Statistical Tests of Discrete Choice Models
• Forecasting and Micro-Simulation
• Nested Logit Models
• Multi-variate (Generalized) Extreme Value Models
• Mixture Models, such as Logit Kernel or Mixed Logit
• Simulation-based Estimation
• Bayesian Estimation
• Discrete Panel Data
• Combining Revealed and Stated Preferences
• Sampling Strategies for Discrete Choice Analysis
• Joint Discrete / Continuous Models
• Choice from a Menu
• Choice Models with Latent Variables

Course schedule, registration times and Special Events

Class runs 9:30 am - 5:30 pm every day except Friday when it ends
at 4:00 pm (variable based on course participant questions).

Registration is on Monday morning from 8:30 - 9:15 am.

Special events include a reception for course participants and faculty on Monday night and a dinner on Thursday evening. All evening activities are included in tuition.

Please note that laptops are required for this course.

Included in Tuition

On the first day of class, participants will receive a copy of Discrete Choice Analysis by Moshe Ben-Akiva and Steven R. Lerman (MIT Press) and a set of additional reading materials covering recent developments and new applications.

Comments from Previous Participants

"Discrete choice analysis is one of the most valuable new tools available to marketers interested in understanding and predicting consumers' choices ... It goes beyond current textbook treatments of discrete choice analysis with discussions of state-of-the-art developments in the area and experimental applications." Colleen Collins-Dodd, Assistant Professor of Marketing, Simon Fraser University, British Columbia

"The MIT Summer Session in Discrete Choice Analysis is without doubt the most valuable course on the topic offered anywhere. Being taught by the very persons who have developed and implemented the field, the course strikes a perfect balance between theory and practice. To me, it was an intellectual thrill." Lasse Fridstrom, Research Economist, Institute of Transport Economics, Norway

"Discrete choice analysis is an effective way to evaluate a new service and forecast future demand. I have applied it to the estimation of userÆs preference ... in order to develop new telecommunication services." Akiya Inoue, Senior Research Engineer, NTT Telecommunications Networks Laboratories

"This course is an excellent review and introduction to discrete analysis theory, ... provides opportunities for hands-on applications. Further, the instructors are major contributors to this area. I highly recommend it." Terence J. La Du, Member of Technical Staff, Bellcore

About the Presenters

The course director and principal lecturer is Moshe Ben-Akiva. Guest lecturers may include Professors Denis Bolduc (Laval University, Canada) and Joan Walker (Boston University). All of the instructors have extensive experience in the diverse applications of discrete choice models in both the public and private sectors. All have taught at the graduate level in discrete choice methods and have in their own work developed many of the techniques covered in the course.

Discounts for Faculty

A limited number of partial-tuition scholarships are available for teaching faculty, rank of instructor or higher, at other educational institutions. You may submit a scholarship request by filling out the Scholarship Request Form after your application to the course has been submitted. Please note that these scholarships are only for tuition and do not cover travel, lodging, or other expenses associated with the course.

If you have any questions please contact the Short Programs office.

Updates

Please note that laptops are required for the afternoon lab sessions.