Abstract
People’s actions are always accompanied with multiple motives. How to estimate the role of the pro-environment motivation under the interference of other motivations will help us to better interpret human environmental behaviors. On the basis of classical motivation theories and travel mode choice research backgrounds, the concepts of pro-environmental and self-interested motivation were defined. Then based on survey data on 1244 urban residents in the Jiangsu Province in China, the multinomial logistic regression model was constructed to examine the effects of multiple motivations, government measures, and demographic characteristics on residents’ travel mode choice behaviors. The result indicates that compared to car use, pro-environmental motivation certainly has a significant and positive role in promoting green travel mode choices (walking, bicycling, and using public transport), but this unstable green behavior is always dominated by self-interested motivations rather than the pro-environmental motivation. In addition, the effects of gender, age, income, vehicle ownership, travel distance, and government instruments show significant differences among travel mode choices. The findings suggest that pro-environmental motivation needs to be stressed and highlighted to ensure sustainable urban transportation. However, policies aimed to only increase the public awareness of environment protection are not enough; tailored policy interventions should be targeted to specific groups having different main motivations.
Highlights
With the rapid development of the traffic industry all over the world, energy consumption and greenhouse gas emissions from the transport sector account for about 1/3 and 1/4 of global energy consumption and greenhouse gas emissions, respectively [1]
Some researchers hold the view that if no control measures are imposed on the use of vehicles, especially private cars, in China, it will be difficult to support large energy consumption and gas pollution after the following decades [4]
The basic purpose of factor analysis is to use a few factors to describe the connections between many elements, i.e., to classify some closely related items; each type of variable becomes a factor, which can reflect the majority of the original information
Summary
With the rapid development of the traffic industry all over the world, energy consumption and greenhouse gas emissions from the transport sector account for about 1/3 and 1/4 of global energy consumption and greenhouse gas emissions, respectively [1]. It is reported that the total energy consumption of China’s transport sectors increased by 309% from 1990 to 2006, which had an annual growth rate of 9.2% [4]. China’s CO2 emissions in the urban transportation sector increased by about 9.7 times at an average annual growth rate of 7.4% from 1980 to 2012 [7]. Some researchers hold the view that if no control measures are imposed on the use of vehicles, especially private cars, in China, it will be difficult to support large energy consumption and gas pollution after the following decades [4]
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