Public willingness to pay for personal carbon trading of green travel: based on survey data from five capital cities in eastern China - Geng, Jichao; Yang, Na; Yang, Li; Long, Ruyin (Frontiers in Ecology and Evolution, 2023)
Personal carbon trading is a form of pollution rights trading that is worth exploring as an innovative tool to cut back carbon emissions from travel. This paper proposes a policy scenario in which car users who exceed the average distance traveled quota are required to purchase travel credits from those who do not reach the quota and pay for them on a per hundred kilometer basis. Willingness to pay (WTP) for personal carbon trading is introduced to calculate the travel cost and its influencing factors are analyzed from the perspective of green travel. Using the double-bounded dichotomous choice contingent valuation method (DBDC), 2712 residents’ data from five provincial capital cities in eastern China is obtained. Based on this, this study first uses a binary logistic regression model to analyze the characteristics of people who are not willing to pay for green travel carbon trading, and then leverages an interval regression model to explore the willingness and intrinsic motivation of being willing to pay more or less for green travel. The results suggest that perceived usefulness is a key influencing factor of residents’ willingness to pay or pay more for green travel; Personal habits have a significant positive effect among those willing to pay; Subjective norms and moral norms can well account for the unwillingness to pay; Attitudes, perceived behavioral control, and environmental awareness fail to predict the willingness to pay among those who are unwilling to pay. In addition, WTP is also affected by demographic variables such as income and educational background. The empirical results as well indicate that the final average level of respondents' WTP is 39.95 yuan per 100 km. The findings of this paper can provide a pricing basis while formulating personal travel carbon trading policies.