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Predicting the factors influencing construction enterprises’ adoption of green development behaviors using artificial neural network

Author

Listed:
  • Xingwei Li

    (Sichuan Agricultural University)

  • Jinrong He

    (Sichuan Agricultural University)

  • Yicheng Huang

    (Sichuan Agricultural University)

  • Jingru Li

    (Sichuan Agricultural University)

  • Xiang Liu

    (Sichuan Agricultural University)

  • Jiachi Dai

    (Sichuan Agricultural University)

Abstract

The construction industry occupies a high proportion of the global economy. However, with the energy consumption of construction enterprises, it still brings a series of serious environmental problems. Construction enterprises should take active green development behavior to respond. Based on enterprises’ green development behavior, this paper explores the influencing factors of green development behavior adopted by construction enterprises in China. Through literature analysis, this paper identifies that construction enterprises’ adoption of green development behaviors is influenced by technological, organizational and environmental factors. Then this paper constructs an index system of the influencing factors of green development behaviors adopted by enterprises. According to the data of construction enterprises from 2000 to 2020 of National Bureau of Statistics, an artificial neural network is used to construct the prediction model of influencing factors of green development behavior adopted by construction enterprises. The conclusions are as follows. (1) Construction enterprises’ adoption of green development behavior shows an upward trend over time. (2) Market share of construction enterprises is the most important factor to promote construction enterprises’ adoption of green development behavior. (3) The prediction model of influencing factors constructed in this paper is verified to be effective by the technology-organization-environment framework. This paper provides a reference for construction enterprises and the government to promote enterprises to adopt green development behavior, which is beneficial for construction enterprises to achieve green development faster.

Suggested Citation

  • Xingwei Li & Jinrong He & Yicheng Huang & Jingru Li & Xiang Liu & Jiachi Dai, 2022. "Predicting the factors influencing construction enterprises’ adoption of green development behaviors using artificial neural network," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-12, December.
    • Handle: RePEc:pal:palcom:v:9:y:2022:i:1:d:10.1057_s41599-022-01253-x
    DOI: 10.1057/s41599-022-01253-x
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    References listed on IDEAS

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    1. Xingwei Li & Jianguo Du & Hongyu Long, 2019. "Green Development Behavior and Performance of Industrial Enterprises Based on Grounded Theory Study: Evidence from China," Sustainability, MDPI, vol. 11(15), pages 1-19, July.
    2. Zhengxia He & Yanqing Zhou & Jianming Wang & Cunfang Li & Meiling Wang & Wenbo Li, 2021. "The impact of motivation, intention, and contextual factors on green purchasing behavior: New energy vehicles as an example," Business Strategy and the Environment, Wiley Blackwell, vol. 30(2), pages 1249-1269, February.
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    7. Iulia Dumitrașcu-Băldău & Dănuț-Dumitru Dumitrașcu & Gabriela Dobrotă, 2021. "Predictive Model for the Factors Influencing International Project Success: A Data Mining Approach," Sustainability, MDPI, vol. 13(7), pages 1-18, March.
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    Cited by:

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    2. Xingwei Li & Jiachi Dai & Jinrong He & Jingru Li & Yicheng Huang & Xiang Liu & Qiong Shen, 2022. "Mechanism of Enterprise Green Innovation Behavior Considering Coevolution Theory," IJERPH, MDPI, vol. 19(16), pages 1-19, August.
    3. Ksenia V. Ekimova, 2023. "Development of the potential of the digital economy of Russian regions through artificial intelligence humanisation," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-9, December.

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