1999
DOI: 10.1111/0033-0124.00158
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Gender and Individual Access to Urban Opportunities: A Study Using Space–Time Measures

Abstract: Conventional accessibility measures based on the notion of locational proximity ignore the role of complex travel behavior and space-time constraints in determining individual accessibility. As these factors are especially significant in women's everyday lives, all conventional accessibility measures suffer from an inherent "gender bias." This study conceptualizes individual accessibility as space-time feasibility and provides formulations of accessibility measures based on the space-time prism construct. Usin… Show more

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Cited by 463 publications
(302 citation statements)
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References 57 publications
(61 reference statements)
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“…For many geographers and planners, the empowering aspect of mobility is straightforward; it comes from seeing mobility as a means of access to opportunity, enabling people to get to the places, the destinations (schools, jobs, hospitals, stores, parks) where they want or need to go (e.g., Hanson and Hanson 1980;Kwan 1999). Jennifer Mandel's (2004) study of women traders in Benin provides clear evidence of the empowering benefits of mobility; she found a strong relationship between women's physical mobility (ability to travel to wholesalers in specific other places and to access distant social networks) and livelihood: Women traders who were able to travel about had higher incomes.…”
Section: How Does Mobility Shape Gender?mentioning
confidence: 99%
See 1 more Smart Citation
“…For many geographers and planners, the empowering aspect of mobility is straightforward; it comes from seeing mobility as a means of access to opportunity, enabling people to get to the places, the destinations (schools, jobs, hospitals, stores, parks) where they want or need to go (e.g., Hanson and Hanson 1980;Kwan 1999). Jennifer Mandel's (2004) study of women traders in Benin provides clear evidence of the empowering benefits of mobility; she found a strong relationship between women's physical mobility (ability to travel to wholesalers in specific other places and to access distant social networks) and livelihood: Women traders who were able to travel about had higher incomes.…”
Section: How Does Mobility Shape Gender?mentioning
confidence: 99%
“…In the US context, examples of the former are the National Personal Travel Survey (which does have data on travel for all purposes, not only the work trip), the American Time Use Survey, and the American Housing Survey; all of these data sets are for national samples and are very sketchy on variables measuring the geographic context of sample individuals. 6 In some cases travel diary data for a metropolitan area are accompanied by detailed spatial data bases describing the nature of the urban environment at a fine spatial scale; the Uppsala Household Travel Survey, collected in 1971 in the days before GIS, was the first to include detailed data on the urban environment (e.g., Hanson and Hanson 1980;Hanson 1982), but the current availability of urban GIS has made including such data as a part of travelactivity studies increasingly feasible (Kwan 2004). Regardless of the data source, however, gender enters analyses in this strand of the literature usually, though not always, as a binary male/female variable in a data matrix, whereas mobility is carefully measured along multiple dimensions (for example, distance and time traveled, mode of travel, linkages among trips, reasons for travel).…”
Section: How Does Mobility Shape Gender?mentioning
confidence: 99%
“…Authors have brought together several of these (and other) dimensions in their research (e.g. Kwan, 1999;Schwanen et al, 2004). In sociology, MTS is increasingly gaining recognition as shown by the rise of the journal Mobilities.…”
Section: Introductionmentioning
confidence: 99%
“…Attributes which define an individual's social role (e.g. gender) (Kwan, 1999), social position (e.g. income or education) (Krivo et al, 2013, Kestens et al, 2010, Christian, 2012, Paez et al, 2010, or one's relation to others (e.g.…”
Section: Daily Mobility Patternsmentioning
confidence: 99%