The impact of residential neighborhood type on travel behavior: A structural equations modeling approach

Abstract

Abstract. Using a system of structural equations, this paper empirically examines the relationship of residential neighborhood type to travel behavior, incorporating attitudinal, lifestyle, and demographic variables. Data on these variables were collected from residents of five neighborhoods in the San Francisco Bay Area in 1993 (final N ¼ 515), including ''traditional'' and ''suburban'' as well as mixtures of those two extremes. A conceptual model of the interrelationships among the key variables of interest was operationalized with a nineequation structural model system. The nine endogenous variables included two measures of residential location type, three measures of travel demand, three attitudinal measures, and one measure of job location.In terms of both direct and total e¤ects, attitudinal and lifestyle variables had the greatest impact on travel demand among all the explanatory variables. By contrast, residential location type had little impact on travel behavior. This is perhaps the strongest evidence to date supporting the speculation that the association commonly observed between land use configuration and travel patterns is not one of direct causality, but due primarily to correlations of each of those variables with others. In particular, the results suggest that when attitudinal, lifestyle, and sociodemographic variables are accounted for, neighborhood type has little influence on travel behavior.

Reducing car use: changing attitudes or relocating? The influence of residential dissonance on travel behavior

“…Urban dissonants are consequently more capable of realizing their preferred travel behavior than suburban dissonants Mokhtarian 2005a, 2005b). Bagley and Mokhtarian (2002), however, claim that both urban dissonants and suburban dissonants have to adjust their travel behavior. In both cases, the built environment can impose restrictions on the travel mode choice.…”

“…Concepts such as New Urbanism (in the USA) and the Compact City (in Europe) aim to reduce car use and travel distances by creating neighborhoods with a high density, a high diversity and a design oriented toward public transit and non-motorized travel (Cervero, 1996;Friedman et al, 1994;Schwanen and Mokhtarian, 2005a). The popularity of these concepts resulted in numerous empirical studies investigating the influence of the built environment on travel behavior, thereby statistically controlling for differences in socio-economic factors such as income, car ownership and household composition (Bagley and Mokhtarian, 2002;Chen et al, 2008;Mokhtarian and Cao, 2008;Van Acker et al, 2011a;van Wee et al, 2002). However, more recent research has shown that within homogeneous socio-economic groups different travel behavior can still be observed, indicating that not only 'objective' (or hard) variables, like the built environment and socio-economic factors, influence travel behavior, but that 'Subjective' (or soft) variables should also be included in the analysis (Mokhtarian and Cao, 2008;Van Acker et al, 2011b;van Wee et al, 2002).…”

“…However, more recent research has shown that within homogeneous socio-economic groups different travel behavior can still be observed, indicating that not only 'objective' (or hard) variables, like the built environment and socio-economic factors, influence travel behavior, but that 'Subjective' (or soft) variables should also be included in the analysis (Mokhtarian and Cao, 2008;Van Acker et al, 2011b;van Wee et al, 2002). According to various studies, personal lifestyles and attitudes have an important impact on travel behavior (Anable, 2005;Bagley and Mokhtarian, 2002;Kitamura et al, 1997;Mokhtarian, 2005a, 2005b;Steg, 2005;Steg et al, 2001). Certain lifestyles have a direct relationship with the mode choice of leisure trips.…”

La ville compacte remise en cause ? Formes urbaines et mobilités de loisirs

“…Elles sont souvent décrites comme significativement déterminantes pour expliquer certains paramètres des mobilités, telles que la durée, la fréquence et la variété des déplacements réalisés. Aux États-Unis, plusieurs auteurs soulignent, par exemple, l'existence de différences significatives entre des quartiers périurbains présentant une hiérarchie routière marquée et une séparation forte des activités (« standard suburban ») et des quartiers plus anciens, avec une trame viaire classique, une mixité fonctionnelle et une conception axée autour des accessibilités en transports en commun (« traditional », « neo-traditional », et « transit oriented ») (Bagley et Mokhtarian, 2002 ;Cao et Schoner, 2014 ;Cervero et Gorham, 1995 ;Cervero et Kockelman, 1997 ;Crane et Crepeau, 1998 ;Ewing et Hamidi, 2015 ;Friedman et al, 1994 ;Holtzclaw, 1990 ;Kulash, 1990 ;McNally et Kulkarni, 1997). Les quartiers plus anciens et mixtes apparaissent nettement moins générateurs de déplacements.…”

Characterization of Truck Traffic in California for Mechanistic–Empirical Design

“…However, they modeled only a single causal direction (from the built environment to travel behavior), which is too simplistic a representation of the interactions among the built environment, travel behavior, and attitudes. Bagley and Mokhtarian (2002) employed a structural equations model (SEM) to investigate the relationships among those variables. They found that with respect to direct and total effects, attitudinal and lifestyle variables had the greatest impact on travel demand among all explanatory variables, while residential location type had little separate influence on travel behavior.…”