In the context of route choice, modeling the process that generates the set of available alternatives in the mind of the individual is a complex and not fully explored issue. Route choice behavior is influenced by variables that are observable, such as travel time and cost, and unobservable, such as attitudes, perceptions, spatial abilities, and network knowledge. In this study, attitudinal data were collected with a web-based survey addressed to individuals who habitually drive from home to work. The paper proposes a methodology to conduct a proper application of factor analysis to the route choice context and describes the preparation of an appropriate data set through measures of internal consistency and sampling adequacy. The paper shows that, for the data set obtained from the web-based survey, six latent constructs affecting driver behavior were extracted and scores of each driver on each factor were calculated.
Methodology for exploratory analysis of latent factors influencing drivers' behaviour / Prato, C; Bekhor, S; Pronello, Cristina. - In: TRANSPORTATION RESEARCH RECORD. - ISSN 0361-1981. - STAMPA. - 1926:(2005), pp. 115-125. [10.3141/1926-14]
Methodology for exploratory analysis of latent factors influencing drivers' behaviour
PRONELLO, CRISTINA
2005
Abstract
In the context of route choice, modeling the process that generates the set of available alternatives in the mind of the individual is a complex and not fully explored issue. Route choice behavior is influenced by variables that are observable, such as travel time and cost, and unobservable, such as attitudes, perceptions, spatial abilities, and network knowledge. In this study, attitudinal data were collected with a web-based survey addressed to individuals who habitually drive from home to work. The paper proposes a methodology to conduct a proper application of factor analysis to the route choice context and describes the preparation of an appropriate data set through measures of internal consistency and sampling adequacy. The paper shows that, for the data set obtained from the web-based survey, six latent constructs affecting driver behavior were extracted and scores of each driver on each factor were calculated.Pubblicazioni consigliate
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https://hdl.handle.net/11583/1740846
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