What Drives Residents Low Carbon Transportation Commuting? Evidence from China

  • Li, Liang (School of Business, Nanjing University of Information Science and Technology) ;
  • Tan, Meixuen (School of Business, Nanjing University of Information Science and Technology) ;
  • Sun, Huaping (School of Finance and Economics, Jiangsu University) ;
  • Sanitnuan, Nuttida (School of Business, Nanjing University of Information Science and Technology)
  • Received : 2021.03.10
  • Accepted : 2021.04.15
  • Published : 2021.08.30


Promoting low carbon transportation adoption is important for energy saving. Some prior studies have discussed on environmental values affect low carbon transportation commuting is inconclusive. This study has constructed the environmental values, utility value, and social influence-based low-carbon transportation adoption model through the theory of the technology acceptance model and VBN model and the IS success model. Through the SEM model and stepwise regression analysis, we have found that environmental values positively affect utility value, and utility value also positively affects the behavior adoption of low carbon transportation. The utility value as mediating effect in the relationship between environmental values and low carbon transportation commuting behavior. Besides, we also have found that social influence positively impacts the behavior adoption of low carbon transportation. It better enhances the level of household residents' environmental values and utility values, and social influence for promoting the adoption of low carbon transportation. This present research provides theoretical guidance and suggestions for promoting the development of low-carbon transportation innovation.



This study is supported by Social Science Foundation of Jiangsu, China (No. 19GLC015), Philosophy and Social Science Foundation for Colleges and Universities in Jiangsu Province (Nos. 2019SJA0160), the key program of National Social Science Fund of China (Grant No. 21AZD067), Research Start-up Fund of Nanjing University of Information Science and Technology (No. 2018r034), National Research Foundation of Republic of Korea (No. 2019K2A9A2A0602441012). Many thanks for Long, Wang, Cai, Ding, Jiang, Xie, Liang, Shin, Antonio and Zhu co-author in early studies.


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