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The diffusion of prefabrication technology and its potential for CO2 emissions reduction in China: A combined system dynamics and agent-based study

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  • Chen, Junjie
  • Liu, Pei
  • Lin, Borong
  • Zhou, Hao
  • Papachristos, George

Abstract

The building sector is one of the largest CO2 emitters. Prefabrication technology (PT) shows remarkable potential for reducing CO2 emissions during the material and construction phases of the building life cycle. However, the diffusion of PT in China is still in its infancy, and more targeted policies are necessary to accelerate the adoption of PT. This study proposes a combined system dynamics and agent-based modeling approach to include the technology adoption behavior of enterprises at the micro level, and the market effects and policies at the macro level. This approach provides a more comprehensive modeling approach and analysis for technology diffusion. Results show that the diffusion of PT has experienced three phases: (i) an initial phase that lasted until 2016, (ii) a mandatory adoption phase from 2016 to 2025, and (iii) a mandatory and market adoption phase that will last from 2025 to 2035 under appropriate policy mixes. A policy mix with moderate intensity is the most efficient in terms of balancing the policy effect and feasibility. The potential of CO2 reduction depends on both the diffusion rate of PT and the floor area of new buildings. Mandatory adoption is more effective than incentive-based policies in reducing CO2 emissions.

Suggested Citation

  • Chen, Junjie & Liu, Pei & Lin, Borong & Zhou, Hao & Papachristos, George, 2025. "The diffusion of prefabrication technology and its potential for CO2 emissions reduction in China: A combined system dynamics and agent-based study," Technological Forecasting and Social Change, Elsevier, vol. 210(C).
    • Handle: RePEc:eee:tefoso:v:210:y:2025:i:c:s0040162524006887
    DOI: 10.1016/j.techfore.2024.123890
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    as
    1. Fan, Ruguo & Dong, Lili, 2018. "The dynamic analysis and simulation of government subsidy strategies in low-carbon diffusion considering the behavior of heterogeneous agents," Energy Policy, Elsevier, vol. 117(C), pages 252-262.
    2. Dutta, Amitava & Puvvala, Abhinay & Roy, Rahul & Seetharaman, Priya, 2017. "Technology diffusion: Shift happens — The case of iOS and Android handsets," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 28-43.
    3. Zhao, Dan & Ji, Shou-feng & Wang, He-ping & Jiang, Li-wen, 2021. "How do government subsidies promote new energy vehicle diffusion in the complex network context? A three-stage evolutionary game model," Energy, Elsevier, vol. 230(C).
    4. Lin, Boqiang & Shi, Lei, 2022. "Do environmental quality and policy changes affect the evolution of consumers’ intentions to buy new energy vehicles," Applied Energy, Elsevier, vol. 310(C).
    5. Li, Fangyi & Cao, Xin & Ou, Rui, 2021. "A network-based evolutionary analysis of the diffusion of cleaner energy substitution in enterprises: The roles of PEST factors," Energy Policy, Elsevier, vol. 156(C).
    6. Kurdgelashvili, Lado & Shih, Cheng-Hao & Yang, Fan & Garg, Mehul, 2019. "An empirical analysis of county-level residential PV adoption in California," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 321-333.
    7. Gao, Jiayang & Zhang, Tao, 2022. "Effects of public funding on the commercial diffusion of on-site hydrogen production technology: A system dynamics perspective," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    8. Shi, Yingying & Wei, Zixiang & Shahbaz, Muhammad & Zeng, Yongchao, 2021. "Exploring the dynamics of low-carbon technology diffusion among enterprises: An evolutionary game model on a two-level heterogeneous social network," Energy Economics, Elsevier, vol. 101(C).
    9. Yu, Sisi & Liu, Yanfeng & Wang, Dengjia & Bahaj, AbuBakr S. & Wu, Yue & Liu, Jiaping, 2021. "Review of thermal and environmental performance of prefabricated buildings: Implications to emission reductions in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    10. Xu, Aiting & Zhu, Yuhan & Wang, Wenpu, 2023. "Micro green technology innovation effects of green finance pilot policy—From the perspectives of action points and green value," Journal of Business Research, Elsevier, vol. 159(C).
    11. Mehdizadeh, Milad & Nordfjaern, Trond & Klöckner, Christian A., 2022. "A systematic review of the agent-based modelling/simulation paradigm in mobility transition," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    12. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    13. Dalla Valle, Alessandra & Furlan, Claudia, 2011. "Forecasting accuracy of wind power technology diffusion models across countries," International Journal of Forecasting, Elsevier, vol. 27(2), pages 592-601, April.
    14. Dalla Valle, Alessandra & Furlan, Claudia, 2011. "Forecasting accuracy of wind power technology diffusion models across countries," International Journal of Forecasting, Elsevier, vol. 27(2), pages 592-601.
    15. Neij, Lena, 1997. "Use of experience curves to analyse the prospects for diffusion and adoption of renewable energy technology," Energy Policy, Elsevier, vol. 25(13), pages 1099-1107, November.
    16. John Sterman, 2018. "System dynamics at sixty: the path forward," System Dynamics Review, System Dynamics Society, vol. 34(1-2), pages 5-47, January.
    17. Ramshani, Mohammad & Li, Xueping & Khojandi, Anahita & Omitaomu, Olufemi, 2020. "An agent-based approach to study the diffusion rate and the effect of policies on joint placement of photovoltaic panels and green roof under climate change uncertainty," Applied Energy, Elsevier, vol. 261(C).
    18. Chen, Hongyi & Wakeland, Wayne & Yu, Jiang, 2012. "A two-stage technology foresight model with system dynamics simulation and its application in the Chinese ICT industry," Technological Forecasting and Social Change, Elsevier, vol. 79(7), pages 1254-1267.
    19. Fan, Ruguo & Bao, Xuguang & Du, Kang & Wang, Yuanyuan & Wang, Yitong, 2022. "The effect of government policies and consumer green preferences on the R&D diffusion of new energy vehicles: A perspective of complex network games," Energy, Elsevier, vol. 254(PA).
    20. Sahal, Devendra, 1985. "Technological guideposts and innovation avenues," Research Policy, Elsevier, vol. 14(2), pages 61-82, April.
    21. Liu, Hui-hui & Song, Yao-yao & Yang, Guo-liang, 2019. "Cross-efficiency evaluation in data envelopment analysis based on prospect theory," European Journal of Operational Research, Elsevier, vol. 273(1), pages 364-375.
    22. Wang, Yitong & Fan, Ruguo & Du, Kang & Bao, Xuguang, 2023. "Exploring incentives to promote electric vehicles diffusion under subsidy abolition: An evolutionary analysis on multiplex consumer social networks," Energy, Elsevier, vol. 276(C).
    23. Hirte, Georg & Tscharaktschiew, Stefan, 2013. "The optimal subsidy on electric vehicles in German metropolitan areas: A spatial general equilibrium analysis," Energy Economics, Elsevier, vol. 40(C), pages 515-528.
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