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Multi-group analysis on the mechanism of residents' low-carbon behaviors in Beijing, China

Author

Listed:
  • Wang, Chao
  • Zhan, Jinyan
  • Wang, Huihui
  • Yang, Zheng
  • Chu, Xi
  • Liu, Wei
  • Teng, Yanmin
  • Liu, Huizi
  • Wang, Yifan

Abstract

Understanding the factors that influence low-carbon behaviors can help policy makers formulate and implement low-carbon regulations and policies. Limited research has been conducted on the mechanisms that influence low-carbon behaviors for multi-groups with different demographic factors. To address this research gap, a questionnaire survey was carried out in Beijing, China. A hypothetical structural model of low-carbon behaviors was built, and a structural equation modeling was used to verify the hypotheses. The main results are as follows. Firstly, the residents of the study area have relatively high levels of low-carbon attitudes and behaviors. The average scores of the items ranged from 3.31 to 4.72, and those of the internal factors were higher than those of external factors and behaviors. Secondly, the proposed hypothetical structural model is valid, and all of the eight hypotheses were accepted. Personal and social norms have significant, positive, and direct effects on both private and public low-carbon behaviors. Thirdly, demographic factors (i.e., gender, age, family size, marital status, education, income, and owning private car) play an important role in the mechanisms that influence low-carbon behaviors. Specific policy implications were proposed, which can contribute to the promotion of low-carbon behaviors and the achievement of low-carbon development.

Suggested Citation

  • Wang, Chao & Zhan, Jinyan & Wang, Huihui & Yang, Zheng & Chu, Xi & Liu, Wei & Teng, Yanmin & Liu, Huizi & Wang, Yifan, 2022. "Multi-group analysis on the mechanism of residents' low-carbon behaviors in Beijing, China," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    • Handle: RePEc:eee:tefoso:v:183:y:2022:i:c:s0040162522004772
    DOI: 10.1016/j.techfore.2022.121956
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    as
    1. Geng, Jichao & Long, Ruyin & Chen, Hong & Li, Wenbo, 2017. "Exploring the motivation-behavior gap in urban residents’ green travel behavior: A theoretical and empirical study," Resources, Conservation & Recycling, Elsevier, vol. 125(C), pages 282-292.
    2. Barr, Stewart & Gilg, Andrew W & Ford, Nicholas, 2005. "The household energy gap: examining the divide between habitual- and purchase-related conservation behaviours," Energy Policy, Elsevier, vol. 33(11), pages 1425-1444, July.
    3. Asensio, Omar Isaac & Delmas, Magali A., 2016. "The dynamics of behavior change: Evidence from energy conservation," Journal of Economic Behavior & Organization, Elsevier, vol. 126(PA), pages 196-212.
    4. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    5. Yongliang Yang & Yiyang Guo & Suqing Luo, 2020. "Consumers’ Intention and Cognition for Low-Carbon Behavior: A Case Study of Hangzhou in China," Energies, MDPI, vol. 13(21), pages 1-19, November.
    6. Zhang, Fan & Deng, Xiangzheng & Phillips, Fred & Fang, Chuanglin & Wang, Chao, 2020. "Impacts of industrial structure and technical progress on carbon emission intensity: Evidence from 281 cities in China," Technological Forecasting and Social Change, Elsevier, vol. 154(C).
    7. Wan, Bingyue & Tian, Lixin & Zhu, Naiping & Gu, Liqin & Zhang, Guangyong, 2018. "A new endogenous growth model for green low-carbon behavior and its comprehensive effects," Applied Energy, Elsevier, vol. 230(C), pages 1332-1346.
    8. Andrew D. Grotzinger & Mijke Rhemtulla & Ronald Vlaming & Stuart J. Ritchie & Travis T. Mallard & W. David Hill & Hill F. Ip & Riccardo E. Marioni & Andrew M. McIntosh & Ian J. Deary & Philipp D. Koel, 2019. "Genomic structural equation modelling provides insights into the multivariate genetic architecture of complex traits," Nature Human Behaviour, Nature, vol. 3(5), pages 513-525, May.
    9. Bai, Yin & Liu, Yong, 2013. "An exploration of residents’ low-carbon awareness and behavior in Tianjin, China," Energy Policy, Elsevier, vol. 61(C), pages 1261-1270.
    10. Gadenne, David & Sharma, Bishnu & Kerr, Don & Smith, Tim, 2011. "The influence of consumers' environmental beliefs and attitudes on energy saving behaviours," Energy Policy, Elsevier, vol. 39(12), pages 7684-7694.
    11. Vainio, Annukka & Paloniemi, Riikka, 2014. "The complex role of attitudes toward science in pro-environmental consumption in the Nordic countries," Ecological Economics, Elsevier, vol. 108(C), pages 18-27.
    12. Jin, Gui & Guo, Baishu & Deng, Xiangzheng, 2020. "Is there a decoupling relationship between CO2 emission reduction and poverty alleviation in China?," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    13. Claudia F. Nisa & Jocelyn J. Bélanger & Birga M. Schumpe & Daiane G. Faller, 2019. "Meta-analysis of randomised controlled trials testing behavioural interventions to promote household action on climate change," Nature Communications, Nature, vol. 10(1), pages 1-13, December.
    14. Girod, Bastien & Mayer, Sebastian & Nägele, Florian, 2017. "Economic versus belief-based models: Shedding light on the adoption of novel green technologies," Energy Policy, Elsevier, vol. 101(C), pages 415-426.
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    1. Zhan, Jinyan & Wang, Chao & Wang, Huihui & Zhang, Fan & Li, Zhihui, 2024. "Pathways to achieve carbon emission peak and carbon neutrality by 2060: A case study in the Beijing-Tianjin-Hebei region, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    2. Tan, Yang & Ying, Xiaoyu & Ge, Jian & Gao, Weijun & Zhang, Li & Wang, Shuai, 2024. "Driving role of perceived psychological factors in households’ low-carbon behaviors: A study based on the Chinese household carbon generalized system of preferences," Energy, Elsevier, vol. 303(C).

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