Research On The Mechanism And Paths Of Social Interaction On Residents′ Low-carbon Travel Behaviors——An Embeddedness Perspective

Global climate change caused by greenhouse gas emissions poses a major threat to global sustainable development and causes the premature death of a large number of people.Among them,the global contribution rate of carbon dioxide emissions from the transportation sector is as high as 25%,and with the increase in car ownership and residents’ living standards,it shows a rapid average annual growth trend.How to curb the continuous rapid growth of carbon emissions in the transportation sector has become a key issue for China to respond to climate change and achieve sustainable development.Although residents’ low-carbon travel behavior can quickly reduce carbon dioxide emissions in the transportation sector,due to China’s highly contextualized social culture,residents’ low-carbon travel decisions are severely restricted by social interaction.Through extensive literature research,existing studies focusing on the "Planned Behavior Paradigm" ignore the social impact mechanism of individual low-carbon travel behavior to a certain extent.Therefore,this study attempts to explore the social influence mechanism and paths differences of Chinese residents’ low-carbon travel behaviors based on social interaction theory and embeddedness perspective.Based on the existing mature scales and self-designed scales,this study uses two channels,the "Volunteer-Agent" model and the third-party platform sample service,to obtain a total of 510 sample data of Chinese residents by the sampling.On this basis,based on the embeddedness perspective,social interaction theory,and innovation diffusion theory,the analysis method of multi-stage structural equation model is adopted to analyze the influence mechanism and action paths of social interaction on residents’ low-carbon travel behavior.The research determined the formal scale through a small-scale pre-test,and then verified the hypothesis through three stages of empirical analysis: direct model verification,second-order model verification,and first-order model verification.In order to further analyze the influence of demographic characteristics and regional characteristics on the above mechanism,we use a multigroup model and two self-developed "Conversion Rate" indicators to analyze the population differences in the action path.Through empirical analysis,the research has initially reached the following conclusions:（1）Social interaction can directly affect and significantly promote residents to practice low-carbon travel behaviors.This conclusion directly proves the importance of social interaction for residents to practice low-carbon travel behaviors,and also verified the correctness of the direct effect hypothesis.（2）Social interaction can significantly promote residents’ low-carbon travel behaviors through the continuous mediating effect of low-carbon cognition and low-carbon attitude.This conclusion shows that social interaction can effectively promote the formation of residents’ lowcarbon cognition,and further promote the formation of their low-carbon attitudes,and finally effectively promote the practice of low-carbon travel behaviors.（3）Residents can effectively acquire three types of knowledge about low-carbon cognition through the three dimensions of social interaction,thereby significantly promoting the formation of low-carbon attitudes and promoting low-carbon travel behaviors.（4）The characteristics of the population have a greater impact on the mechanism and paths of social interaction on the low-carbon travel behaviors.The demographic characteristics and regional characteristics of residents have brought greater differences in the abovementioned paths.This research not only integrates the innovation perspective into the low-carbon travel behaviors research based on the diffusion of innovation theory,but also uses the embeddedness perspective and social interaction theory to broaden the insufficiency of the planned behavior paradigm for the discussion of social impact mechanisms.Based on the empirical results,this study gives policy recommendations aimed at promoting low-carbon travel behaviors for residents:（i）improve social interaction conditions and increase residents’ willingness to socialize;（ii）build a scientific publicity system to reduce blind spots in low-carbon knowledge;（iii）strengthen the operability of travel and enhance the practical and friendly experience;（iv）implement social interventions to improve residents’ low-carbon travel accurately,etc.Problems such as memory awakening,scale design,and sampling process have brought certain limits to the research design.In the next step,measures such as adopting various strategies to collect samples,expanding the scope of sampling,and focusing on diffusion networks can be used to reduce the reliability and validity risks.