Chapter
Nov 30, 2023

Exploring the Patterns of Prefabrication Technology Diffusion among Construction Enterprises: A Two-Stage Evolutionary Model on a Complex Network

ABSTRACT

Prefabrication technology (PT) is regarded as an effective way to reduce CO2 emissions from material and construction stages of buildings. However, constrained by the ambiguous patterns of PT diffusion, the application of this technology in China faces a lot of difficulties and lags far behind developed countries. To overcome this problem, this study proposes a two-stage evolutionary model based on complex network. The results show that: (1) Before 2016 was the initial stage of introducing PT into the Chinese market, and the diffusion rate is below 4.9%. (2) From 2016 to 2025 is the policy-driven stage. More adopters emerge under both incentive and mandatory policies proposed by governments, so the diffusion rate rapidly rises to around 33%. (3) From 2025 to 2035, the development of PT will enter a stage driven by both policies and market effects. The amount of market adoption grows steadily, which helps the overall diffusion rate increase to about 45%.

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REFERENCES

Barabási, A.-L., and Albert, R. (1999). “Emergence of scaling in random networks.” Science, 286(5439), 509-512.
Barlas, Y. (1996). “Formal aspects of model validity and validation in system dynamics.” System Dynamics Review: The Journal of the System Dynamics Society, 12(3), 183-210.
Beijing Municipal Government (2022). “Suggestions for further development of prefabricated buildings.” (in Chinese).
Building Energy Research Center of Tsinghua University (2022). “Annual report on the development of building energy saving in China 2022.” China Architecture & Building Press. (in Chinese).
Chen, H., Yu, J., and Wakeland, W. (2016). “Generating technology development paths to the desired future through system dynamics modeling and simulation.” Futures, 81, 81-97.
China National Bureau of Statistics (2016). “China statistical yearbook.” (in Chinese).
Du, H., Han, Q., Sun, J., and Wang, C. C. (2022). “Adoptions of prefabrication in residential sector in China: Agent-based policy option exploration.” Engineering, Construction and Architectural Management.
Edmonds, B., and Moss, S. “From KISS to KIDS–an ‘anti-simplistic’modelling approach.” Proc., Multi-Agent and Multi-Agent-Based Simulation: Joint Workshop MABS 2004, New York, NY, USA, July 19, 2004, Revised Selected Papers 5, Springer, 130-144.
Gan, X., Chang, R., Zuo, J., Wen, T., and Zillante, G. (2018). “Barriers to the transition towards off-site construction in China: An Interpretive structural modeling approach.” Journal of Cleaner Production, 197, 8-18.
General Office of the State Council (2016). “Guidance on vigorously developing prefabricated buildings.”. (in Chinese).
Hebei Provincial Department of Housing and Urban-Rural Development (2017). “The 13th five-year development plan of prefabricated buildings in hebei province.” (in Chinese).
Henan Provincial Department of Housing and Urban-Rural Development (2022). “Notice on further accelerating the development of prefabricated buildings.” (in Chinese).
Jiang, W., Luo, L., Wu, Z., Fei, J., Antwi-Afari, M. F., and Yu, T. (2019). “An investigation of the effectiveness of prefabrication incentive policies in China.” Sustainability, 11(19), 5149.
Jining Municipal Government (2022). “Implementation opinions on accelerating high-quality development of construction industry in Jining city.” (in Chinese).
Li, T., Li, Z., and Dou, Y. (2022). “Diffusion prediction of prefabricated construction technology under multi-factor coupling.” Building Research & Information, 1-21.
Li, Z., Zhang, S., and Meng, Q. (2021). “Modeling adoption behavior of prefabricated building with multiagent interaction: System dynamics analysis based on data of Jiangsu Province.” Computational Intelligence and Neuroscience, 2021.
Liu, H.-H., Song, Y.-Y., and Yang, G.-L. (2019). “Cross-efficiency evaluation in data envelopment analysis based on prospect theory.” European Journal of Operational Research, 273(1), 364-375.
Liu, Z., Deng, Z., He, G., Wang, H., Zhang, X., Lin, J., Qi, Y., and Liang, X. (2022). “Challenges and opportunities for carbon neutrality in China.” Nature Reviews Earth & Environment, 3(2), 141-155.
Mao, C., Shen, Q., Pan, W., and Ye, K. (2015). “Major barriers to off-site construction: The developer’s perspective in China.” Journal of Management in Engineering, 31(3), 04014043.
Mao, C., Shen, Q., Shen, L., and Tang, L. (2013). “Comparative study of greenhouse gas emissions between off-site prefabrication and conventional construction methods: Two case studies of residential projects.” Energy and Buildings, 66, 165-176.
MOHURD (2016). “Consumption quota of prefabricated construction works.” (in Chinese).
MOHURD (2017). “13th five-year prefabricated building action plan.” (in Chinese).
MOHURD (2022). ““14th five-year plan” for the development of construction industry.” (in Chinese).
MOHURD (2022). “List of replicable experiences for prefabricated building development (first batch).” (in Chinese).
Shi, Y., Wei, Z., Shahbaz, M., and Zeng, Y. (2021). “Exploring the dynamics of low-carbon technology diffusion among enterprises: An evolutionary game model on a two-level heterogeneous social network.” Energy Economics, 101, 105399.
Tam, V. W., Tam, C. M., Zeng, S., and Ng, W. C. (2007). “Towards adoption of prefabrication in construction.” Building and Environment, 42(10), 3642-3654.
Wu, G., Yang, R., Li, L., Bi, X., Liu, B., Li, S., and Zhou, S. (2019). “Factors influencing the application of prefabricated construction in China: From perspectives of technology promotion and cleaner production.” Journal of Cleaner Production, 219, 753-762.
Zhang, L., Xue, L., and Zhou, Y. (2019). “How do low-carbon policies promote green diffusion among alliance-based firms in China? An evolutionary-game model of complex networks.” Journal of cleaner production, 210, 518-529.
Zhou, N., Khanna, N., Feng, W., Ke, J., and Levine, M. (2018). “Scenarios of energy efficiency and CO2 emissions reduction potential in the buildings sector in China to year 2050.” Nature Energy, 3(11), 978-984.
Zou, H., Du, H., Broadstock, D. C., Guo, J., Gong, Y., and Mao, G. (2016). “China’s future energy mix and emissions reduction potential: A scenario analysis incorporating technological learning curves.” Journal of Cleaner Production, 112, 1475-1485.

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ICCREM 2023
Pages: 678 - 687

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Published online: Nov 30, 2023

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Junjie Chen [email protected]
Dept. of Supply Chain Management, Shandong Univ., Weihai, China. Email: [email protected]
Associate Professor, Dept. of Supply Chain Management, Shandong Univ., Weihai, China (corresponding author). Email: [email protected]
Assistant Professor, Institute for Urban Governance and Sustainable Development, Tsinghua Univ., Beijing, China. Email: [email protected]
Zhenyue Jiang [email protected]
Dept. of Supply Chain Management, Shandong Univ., Weihai, China. Email: [email protected]

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