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Abstract
Scholars argue that everyday travel behavior is related less to location than to individual choice, due to the space–time convergence evident with increasing individual mobility. Yet, very few studies have empirically measured trends in the relative significance of location for travel habits over time. This article uses multilevel models based on official register data covering the total Swedish working population to explore how home–work distance varied among workers and across residential areas between 1990 and 2010. The results indicate growing variation in home–work distance for workers living in the same residential neighborhoods and that the significance of residential location for the home–work distance decreased throughout the studied period. The results may suggest that there is less scope now than in the early 1990s for shaping commuting behavior by altering the built environment in Sweden.
Notes
1. The author has complemented Gil Sola’s (Citation2013) findings with calculations from the Swedish National Travel Survey 2011.
2. Sandow (Citation2011) and Swärdh (Citation2009) are examples of studies that apply similar measures.
3. Apparicio, Abdelmajid, Riva, and Shearmur (Citation2008) compared differences in results regarding geographical accessibility to health care services computed using various distance types, including Euclidian distance. All four distance constructs were strongly correlated with each other, but with some local variations in more densely populated suburban areas. In a similar study, Sparks, Bania, and Leete (Citation2011) found that Euclidean distances were generally 35–38% larger than street network distances, though highly correlated with them. In a Swedish context, Reneland (Citation1998) estimated that the Euclidian distance can be multiplied by 1.3 to produce the network distance.
4. Thirty nine percent, according to the Swedish National Travel Survey, 2005–2006 (SIKA, Citation2007).
5. Unfortunately, neither car ownership nor possessing a driving license is included in the data set.
6. Since work location was earlier also found to influence the home–work distance (Shuttleworth & Gould, Citation2010), models were initially tested with workers nested in workplace areas. The results suggested that the workplace end also provided a source of variation in the home–work distance, but indicated residential location to be the main source. Furthermore, trends in workplace VPCs over time were similar to the VPCs from residential neighborhoods.
7. Small-area market statistics (SAMS) areas are based on classifications made by Statistics Sweden; there are 9,200 SAMS areas in Sweden, with an average of approximately 1,000 inhabitants each.
8. Several variables at the residential location level were initially tested. The final setup of variables presented in the models is the one that explained the most variation in home–work distance. Other relevant indicators, such as various population density measures, were not significant after controlling for the present variables.