Abstract
The main objective of this study is to analyze work travel-related behavior through a set of variables relative to socio-economic class, urban environment and travel characteristics. The Principal Component Analysis was applied in a sample consisting of workers of the S?o Paulo Metropolitan Area, based on the origin-destination home interview survey, carried out in 1997, in order to: 1) examine the interdependence between travel patterns and a set of socioeconomic and urban environment variables; 2) determine if the original database can be synthetized on components. The results enabled to observe relations between the individual’s socio-economic class and car usage, characteristics of urban environment and destination choices, as well as age and non-motorized travel mode choice. It is then concluded that the database can be adequately summarized in three components for subsequent analysis: 1) urban environment; 2) socio-economic class; and 3) family structure.
Highlights
Personal displacement behavior depends largely on two groups of variables: socioeconomic characteristics, and urban environment factors.The influence of individual socioeconomic and household characteristics on choosing travel patterns has been studied over the years [1]
The Principal Component Analysis (PCA) was applied to a sample of workers of the São Paulo Metropolitan Area (SPMA) in order to: 1) examine patterns or relations a priori unknown between travels and a large set of variables; 2) determine if the original database can be synthesized in a set of components
A sequence of steps was performed to examine three main hypotheses: 1) if characteristics related to the individual’s socio-economic class affect the modal choice and travel distances; 2) if variables related to the family structure affect the travel behavior; 3) if distribution and intensity of opportunities in the urban environment have effect on destination choice decisions
Summary
Personal displacement behavior depends largely on two groups of variables: socioeconomic characteristics, and urban environment factors (residential density, proximity of localities, spatial coverage of the transportation network, etc.). The influence of individual socioeconomic and household characteristics on choosing travel patterns has been studied over the years [1]. (2014) Study of Work-Travel Related Behavior Using Principal Component Analysis. The main objective is to analyze, through exploratory techniques, the individual work-travel behavior through a set of variables related to socioeconomic characteristics and to the urban environment (distribution and intensity of opportunities). The Principal Component Analysis (PCA) was applied to a sample of workers of the São Paulo Metropolitan Area (SPMA) in order to: 1) examine patterns or relations a priori unknown between travels and a large set of variables; 2) determine if the original database can be synthesized in a set of components
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