Mode use in long-distance travel

Abstract

This paper focuses on mode use in long-distance travel. Long-distance travel is responsible for more than 50 percent of climate impact. Nevertheless, it is usually excluded from analyses that examine travel behavior. Whereas studies on daily travel prove that the rural population covers longer distances in daily travel, recent studies (e.g., Holz-Rau, Scheiner, and Sicks 2014; Brand and Preston 2010) show a different picture in long-distance travel. Here, the urban population undertakes more long-distance trips, especially by air. The aim of this paper is to analyze the mode use in long-distance travel in different spatial settings by using multivariate regression models. The (underlying) data derive from a nationwide survey with a sample size of 60,713 respondents, Mobility in Germany 2008 (MiD). A broad range of socio-demographic and socioeconomic characteristics are thereby included as control variables. The results show that even when household income, car accessibility, and education level are considered, the urban population undertakes more long-distance trips, in particular by train and by air. These differences are found in business as well as in private travel.

Why do urbanites travel more than do others? A review of associations between urban form and long-distance leisure travel

“…Bivariate analyses show large regional differences in long-distance travel behavior between settlements of distinct size and density levels, with residents of the largest cities and metropolitan areas traveling the most (Brand and Boardman 2008, Nicolas and David 2009, Heinonen et al 2013a. After controlling for demographic, socioeconomic or sociopsychological variables, the effects of settlement size, agglomeration level, and urban density remain significant and positive in most studies (Frändberg and Vilhelmson 2003, Brand 2009, Brand and Preston 2010, Reichert and Holz-Rau 2015, Reichert et al 2016, Bruderer Enzler 2017, with only one study from outside of Europe showing lack of association with population density (Boucher 2016).…”

“…Besides travelled distances, there may be differences in rates of participation in certain types of travel. In the study of Reichert and Holz-Rau (2015), the higher amount of long-distance travel among residents of agglomerations and large cities was found to be largely due to the higher proportion of people who travel by train or airplane. According to Reichert and Holz-Rau (2015), the propensity to take train trips instead of car or airplane trips is partly explained by access to inter-urban train stations.…”

“…In the study of Reichert and Holz-Rau (2015), the higher amount of long-distance travel among residents of agglomerations and large cities was found to be largely due to the higher proportion of people who travel by train or airplane. According to Reichert and Holz-Rau (2015), the propensity to take train trips instead of car or airplane trips is partly explained by access to inter-urban train stations. The authors did not directly test the effect of airport accessibility, but it may be captured in their models by agglomeration level and municipality size.…”

“…Frändberg and Vilhelmson (2003) similarly show that people living in large Swedish cities tend to take more international trips than people living in rural areas. The results of a German study , Reichert and Holz-Rau 2015, Reichert et al 2016 found that residents of large cities are more likely to participate in long-distance travel, travel further for leisure purposes, and cause higher emissions from long-distance travel than those who live in smaller settlements. The results also hold true for agglomeration level, with the size of the municipality held constant (Reichert et al 2016).…”

“…In one study, the time-span for long-distance trips was less than one week (Limtanakool et al 2006a) and in seven from two weeks up to a month (Dargay and Clark 2012, Ottelin et al 2014, Arbués et al 2016, Heinonen et al 2011, Heinonen et al 2013a, 2013b, Ottelin et al 2017. Frändberg and Vilhelmson (2003), Nicolas and David (2009), Holz-Rau et al (2014) Reichert and Holz-Rau (2015) and Reichert et al (2016) utilized data collected over a 2-3 month span, whereas in 11 studies the time span was 12 months (Høyer and Holden 2003, Naess 2006, Ornetzeder et al 2008, Brand and Boardman 2008, Brand and Preston 2010, Bruderer Enzler 2017, Czepkiewicz et al 2018. In the rest of the studies reviewed the data collection time spans are not explained.…”