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An Investigation of the Contribution of Targeted Marketing Data to the Prediction of Attitudes

This project involves the use of machine learning methods to impute attitudes into the Georgia subsample of the 2016-17 National Household Travel Survey, training the algorithms on the responses to a 2017 attitudinal survey administered to a separate statewide sample in Georgia. The “common variables” needed to train the learning function will include socio-economic/demographic and other variables found in both samples, but will be augmented by (1) land use-related variables (obtained from multiple external sources) associated with respondents’ residential neighborhoods, and (2) (for the first time) lifestyle-oriented targeted marketing variables associated with the household/respondent that are purchased from a commercial provider. The project will evaluate the effectiveness of targeted marketing variables for this purpose. The objectives of this project are (1) to impute attitudes into the Georgia subsample of the 2016-17 NHTS, training the imputation functions using attitudinally-rich data collected in Fall 2017 from a sample that is (reasonably) representative of the urban and small-town population of the state of Georgia; and (2) to augment the set of “common variables” available for training the imputation process with information from targeted marketing databases. Achievement of both objectives will involve testing the efficacy of the imputed attitudes for predicting travel-related choices of interest, using a variety of comparisons.

Language

  • English

Project

  • Status: Active
  • Funding: $396,274
  • Sponsor Organizations:

    Center for Teaching Old Models New Tricks

    Arizona State University
    Tempe, AZ  United States  85287
  • Managing Organizations:

    Georgia Institute of Technology, Atlanta

    Georgia Tech Research Corporation
    505 10th Street, Suite 213
    Atlanta, GA  United States  30332
  • Project Managers:

    Pendyala, Ram

  • Performing Organizations:

    Georgia Institute of Technology, Atlanta

    School of Civil and Environmental Engineering
    790 Atlantic Drive
    Atlanta, GA  United States  30332-0355
  • Principal Investigators:

    Mokhtarian, Patricia

  • Start Date: 20170901
  • Expected Completion Date: 20210831
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers Program

Subject/Index Terms

  • TRT Terms: Mobility
  • Subject Areas: Passenger Transportation; Planning and Forecasting; TRAFFIC AND TRANSPORT PLANNING;

Filing Info

  • Accession Number: 01665593
  • Record Type: Research project
  • Source Agency: Center for Teaching Old Models New Tricks
  • Files: UTC, RiP
  • Created Date: Apr 3 2018 8:00PM