مقاله انگلیسی رایگان در مورد خودرو پیک و افزایش بازده: روند مسافرت با خودرو – الزویر ۲۰۱۷

Per capita car travel reached a plateau or began to decline in several OECD countries after the millennium, following more than half a century of continuous growth (Schipper, 2011; Van Dender and Clever, 2013). In Great Britain (GB), per capita car travel reached a peak in 2002 and fell by 9% over the subsequent decade. Although the 2008 financial crisis accelerated this trend, it was clearly established several years before. There has been much debate about the causes of this so-called ‘peak car’ phenomenon and the extent to which it represents a permanent or merely a temporary break with historic trends (Goodwin, 2012; Goodwin and Van Dender, 2013; Millard-Ball and Schipper, 2011; Newman and Kenworthy, 2011; Puentes and Tomer, 2008). Some authors, such as Bastian et al. (2016), argue that simple economic models based solely on changes in income and fuel prices ‘‘… are able to predict the plateau and decrease of car travel with quite remarkable accuracy…” (Bastian et al., 2016). Others consider these economic factors to be insufficient and focus instead on changes in demographics, spatial patterns, social norms and other variables (Garikapati et al., 2016; Metz, 2013; Wee, 2015). For example, Goodwin and Van Dender (2013) argue that: ‘‘…an aggregate model focusing on GDP effects and fuel prices is too crude to catch the diversity and dynamics underlying aggregate car travel demand and how it changes…”. Bastian et al. (2016) emphasise that their conclusions do not rule out the existence of alternative explanations, or imply that there been no changes in other variables such as lifestyle and attitudes, or demonstrate that those variables have no effect on travel patterns. Instead, they simply argue that there is no ‘‘…compelling evidence that one needs to assume something else than fuel price and GDP to explain the aggregate VKT development after 2003…”. Wadud and Baierl (2017) question Bastian et al’s findings, arguing that their use of ‘out of sample’ forecasts is invalid. But in response, Bastian et al. (2017) argue that a longer time series is preferred for estimation and that a model estimated with a shorter time period nevertheless gives consistent results