Leveraging targeted marketing data in travel demand modeling: validation and applications

Targeted marketing data;Transportation planning

Kressner, Josephine D. ; Garrow, Laurie A Civil and Environmental Engineering French, Steven P Newman, Jeffrey Ross, Catherine Watkins, Kari E ; Garrow, Laurie A

University:Georgia Institute of Technology

Department:Civil and Environmental Engineering

关键词: Targeted marketing data;    Transportation planning;   

Others  :  https://smartech.gatech.edu/bitstream/1853/51870/1/KRESSNER-DISSERTATION-2014.pdf

美国|英语

来源: SMARTech Repository

【 摘 要 】

To date, the collection of comprehensive household travel data has been a challenge for most metropolitan planning organizations (MPOs) and state departments of transportation (DOTs) due mainly to high costs. Urban population growth, the expansion of metropolitan regions, and the general unwillingness of the public to complete surveys conflict with limited public funds. The purpose of this research is to leverage targeted marketing data, sometimes referred to as consumer data or just simply marketing data, for travel demand modeling applications. This research reveals a first step in exploring the use of targeted marketing data for representing population characteristics of a region. Four studies were completed: an aggregate validation, a household-level validation for hard-to-reach population groups, an airport passenger model, and a residential location choice model. The two validation studies of this work suggest that targeted marketing data are similar to U.S. Census data at small geographic levels for basic demographic and socioeconomic information. The studies also suggest that the existing coverage errors are at least similar, if not lower than, the levels of those in household travel surveys used today to build travel demand models. The two application studies of this work highlight the benefits of the targeted marketing data over traditional household travel surveys and U.S. Census data particularly well, including the additional behavioral information available at the household-level and the very large sample sizes. These results suggest that the combination of targeted marketing data with other third-party and non-traditional data could be particularly powerful. It offers tremendous opportunities to enhance, or even transform, existing travel demand modeling systems and data collection practices. Inexpensive, up-to-date, and detailed data would allow researchers and decision-makers alike to better understand travel behavior and to be more equipped to make important transportation-related decisions that affect our lives each day.