01473946

Component

https://doi.org/10.3141/2354-04

http://scholar.google.com...+Kim&publication_year=2013

National and regional household travel surveys have conventionally sampled landline telephone households through list-assisted random digit dialing. However, recent increases in "mobile phone–only" households result in either noncoverage or undercoverage of a growing segment of the population. This result could cause a substantial bias in the representativeness of travel behavior toward the target population. To cover mobile phone–only households, an address-based sampling method is of interest. This study explores whether the characteristics and travel behavior of mobile phone–only households differ from those of households with landline telephones. In addition, this study quantifies the extent of noncoverage errors in the surveys in respondents’ travel behavior. Along with census data, the mobile phone–only sample (N = 2,988) was compared with the landline telephone sample (N = 7,774) drawn from the 2008 National Capital Region Household Travel Survey. Results show that the mobile phone–only sample consisted of relatively more single-person households; younger individuals; and Blacks, Asians, and Hispanics, who were generally identified as hard-to-reach groups. Statistical models were estimated to examine differences in travel behavior and suggested that the mobile phone–only households made more transit (41%) and walking (29%) trips. This study shows that the inclusion of the mobile phone–only households can reduce the noncoverage errors, especially for alternative modes. The implications for travel survey methods are discussed.

01496622

13-2028

English

pp 29–39

2013

Transportation Research Record: Journal of the Transportation Research Board

9780309286701

Print

Figures (2) ; References (25) ; Tables (6)

Cellular telephones; Data quality; Demographics; Public transit; Statistical sampling; Traffic distribution; Travel behavior; Travel surveys; Walking

Data and Information Technology; Highways; Pedestrians and Bicyclists; Planning and Forecasting; Public Transportation; I70: Traffic and Transport; I72: Traffic and Transport Planning

PRP, TRIS, TRB, ATRI

Feb 5 2013 12:27PM

• Application of Geographic Perturbation Methods to Residential Locations in the Oregon Household Activity Survey: Proof of Concept
• Examining Estimation Bias and Efficiency for Pseudopanel Data in Travel Demand Analysis
• Future Mobility Survey: Experience in Developing a Smartphone-Based Travel Survey in Singapore
• Longitudinal Global Positioning System Travel Data and Breach of Privacy via Enhanced Spatial and Demographic Analysis
• Methodology to Gather Multimodal Trip Generation Data in Smart-Growth Areas
• On New Measures for Detection of Data Quality Risks in Mobility Panel Surveys
• Open Versus Closed: Effects of Question Form on Transit Rider Expressions of Policy Preferences in Arequipa, Peru
• Quantifying Key Errors in Household Travel Surveys: Comparison of Random-Digit-Dial Survey and Address-Based Survey
• Risk-Based Corridor Asset Management: Applying Multiattribute Utility Theory to Manage Multiple Assets
• Route Choice Characteristics for Truckers
• Stochastic Imputation of Missing Physical Commodity Trade Information Using Monetary Trade Data
• Strategic Total Highway Asset Management Integration