Prefabricated buildings (PBs) represent a new type of construction method that take the path of sustainable development and are an important way to promote the transformation of China’s construction industry. In order to better promote the development of China’s PBs industry and help achieve the goal of “dual carbon” in the construction industry, this paper discusses the driving factors and driving paths for the development of PBs industry under the background of “dual carbon.” Using the literature review method and questionnaire survey method to construct a multi-dimensional driving index system for the development of the PBs industry, constructing a multi-dimensional driving model for the PBs industry based on the data, analyzing the driving path using the structural equation model, and calculating the comprehensive effect of each index. The results show that the development of PBs industry is driven by government support, economic level, technical specification, social environment and market environment, and the size of the driving force is in the following order: government support > market environment > economic level > technical specification > social environment.
HongYJiangXXuH, et al.The impacts of China’s dual carbon policy on green innovation: evidence from Chinese heavy-polluting enterprises. J Environ Manage2024; 350: 119620.
2.
GürTM. Carbon dioxide emissions, capture, storage and utilization: review of materials, processes and technologies. Prog Energy Combust Sci2022; 89: 100965.
3.
MaQTariqMMahmoodH, et al.The nexus between digital economy and carbon dioxide emissions in China: the moderating role of investments in research and development. Technol Soc2022; 68: 101910.
4.
LiuBDingCJAhmedAD, et al.Carbon emission allowances and green development efficiency. J Clean Prod2024; 463: 142246.
5.
AghasizadehSTabadkaniAHajirasouliA, et al.Environmental and economic performance of prefabricated construction: a review. Environ Impact Assess Rev2022; 97: 106897.
6.
LiuSLiZTengY, et al.A dynamic simulation study on the sustainability of prefabricated buildings. Sustain Cities Soc2022; 77: 103551.
7.
TanQYeM. Allocation of environmental responsibilities in the prefabricated construction supply chain: exploring the influence of government subsidies. J Constr Eng Manag2024; 150: 04024167.
8.
YuanZWangHYangY, et al.Improving the construction accuracy of precast components in prefabricated buildings by analyzing relevant factors from the perspective of supply chain: a system dynamics model. Archit Eng Des Manag2024; 20: 230–248.
9.
DuQYangMWangY, et al.Dynamic simulation for carbon emission reduction effects of the prefabricated building supply chain under environmental policies. Sustain Cities Soc2024; 100: 105027.
10.
WuXHanJCuiH, et al.A comparative review of recent research progress in prefabricated buildings in China and other countries. Buildings2024; 14: 1062.
11.
KnyziakP. The impact of construction quality on the safety of prefabricated multi-family dwellings. Eng Fail Anal2019; 100: 37–48.
12.
GanVJL. BIM-Based building geometric modeling and automatic generative design for sustainable offsite construction. J Constr Eng Manag2022; 148: 04022111.
13.
PanYZhangL. Integrating BIM and AI for smart construction management: current status and future directions. Arch Comput Methods Eng2023; 30: 1081–1110.
14.
XiaoYBholaJ. Design and optimization of prefabricated building system based on BIM technology. Int J Syst Assur Eng Manag2022; 13: 111–120.
15.
GhanbariMZolfaghariDYadegariZ. Mitigating construction delays in Iran: an empirical evaluation of building information modeling and integrated project delivery. J Eng Manag Syst Eng2023; 2: 170–179.
16.
KooHJO’ConnorJT. A strategy for building design quality improvement through BIM capability analysis. J Constr Eng Manag2022; 148: 04022066.
17.
UzairuddinSJaiswalM. Digital monitoring and modeling of construction supply chain management scheme with BIM and GIS: an overview. Mater Today Proc2022; 65: 1908–1914.
18.
HijaziAAPereraSCalheirosRN, et al.A data model for integrating BIM and blockchain to enable a single source of truth for the construction supply chain data delivery. Eng Constr Archit Manag2023; 30: 4645–4664.
19.
LeygonieRMotamediAIordanovaI. Development of quality improvement procedures and tools for facility management BIM. Dev Built Environ2022; 11: 100075.
20.
FanKWuZ. Incentive mechanism design for promoting high-level green buildings. Build Environ2020; 184: 107230.
21.
YangCXiongFHuQ, et al.Incentive mechanism of BIM application in prefabricated buildings based on evolutionary game analysis. Buildings2023; 13: 1162.
22.
XiaMZhaoLZhaoL. A comprehensive risk-assessment method for prefabricated buildings using EPC: a case study from China. Sustainability2022; 14: 1910.
23.
ShahpariMSaradjFMPishvaeeMS, et al.Assessing the productivity of prefabricated and in-situ construction systems using hybrid multi-criteria decision making method. J Build Eng2020; 27: 100979.
24.
D’AgostinoDD’AgostinoPMinelliF, et al.Proposal of a new automated workflow for the computational performance-driven design optimization of building energy need and construction cost. Energy Build2021; 239: 110857.
25.
LiLXiaoSLiuZ, et al.Study of the factors influencing the life cycle cost of green buildings using SEM-SD method. J Asian Archit Build Eng2025; 24: 1860–1877.
26.
ChenLChanAPCOwusuEK, et al.Critical success factors for green building promotion: a systematic review and meta-analysis. Build Environ2022; 207: 108452.
27.
GuribieFLKheniNASuleM. Structural equation modeling of the critical driving forces of offsite construction in Ghana. Built Environ Proj Asset Manag2022; 12: 667–683.
28.
LiuYZhangYBatistaL, et al.Green operations: what’s the role of supply chain flexibility?Int J Prod Econ2019; 214: 30–43.
29.
LiXWangCKassemMA, et al.Evaluation method for quality risks of safety in prefabricated building construction using SEM-SDM approach. Int J Environ Res Public Health2022; 19: 5180.
30.
YangLHongyuC. Research on factors influencing total carbon emissions of construction based on structural equation modeling: a case study from China. Build Environ2025; 275: 112396.
31.
WangZLShenHCZuoJ. Risks in prefabricated buildings in China: importance-performance analysis approach. Sustainability2019; 11: 3450.
32.
AhmadTGunduzMMadkoorA. Green building adoption in Qatar: PLS-SEM-based analysis of drivers and barriers. Eng Constr Archit Manag2024.
33.
LiuWFanGLiuZ. Driving factors in carbon emission reduction in prefabricated building supply chains based on structural equation modelling. Sustainability2024; 16: 3150.
34.
TangiLJanssenMBenedettiM, et al.Digital government transformation: a structural equation modelling analysis of driving and impeding factors. Int J Inf Manag2021; 60: 102356.
35.
XiCCaoSJ. Challenges and future development paths of low carbon building design: a review. Buildings2022; 12: 163.
36.
BohlinJTurberfieldAJLouisAA, et al.Designing the self-assembly of arbitrary shapes using minimal complexity building blocks. ACS Nano2023; 17: 5387–5398.
37.
RimbonoRSupriatnaJKoestoerRHS, et al.Economic viability and policy imperatives of carbon capture, utilisation and storage in Indonesia’s pathway to net-zero emissions. Chall Sustain2025; 13(2): 236–253.
38.
LinnéussonGBoldtS. Towards assessing the economic sustainability of reconfigurable modularization in semi-automatic assembly systems: a system dynamics perspective. Systems2024; 12: 218.
39.
ZhangDMohsinMRasheedAK, et al.Public spending and green economic growth in BRI region: mediating role of green finance. Energy Policy2021; 153: 112256.
40.
WangXXieSWeiZ, et al.A study on the impact of China’s prefabricated building policy on the carbon reduction benefits of China’s construction industry based on a difference-in-differences method. Sustainability2024; 16: 7606.
41.
LuJWangJSongY, et al.Influencing factors analysis of supply chain resilience of prefabricated buildings based on PF-DEMATEL-ISM. Buildings2022; 12: 1595.
42.
ChenLHuangLHuaJ, et al.Green construction for low-carbon cities: a review. Environ Chem Lett2023; 21: 1627–1657.
43.
ZhouJXShenGQYoonSH, et al.Customization of on-site assembly services by integrating the internet of things and BIM technologies in modular integrated construction. Autom Constr2021; 126: 103663.
44.
GuoS. Exploring low-carbon pilot city policy implementation: evidence from China. Clim Policy2023; 23: 1045–1057.
45.
MagnoFCassiaF. Predicting restaurants’ surplus food platform continuance: insights from the combined use of PLS-SEM and NCA and predictive model comparisons. J Retail Consum Serv2024; 79: 103820.
46.
SunYHaoSLongX. A study on the measurement and influencing factors of carbon emissions in China’s construction sector. Build Environ2023; 229: 109912.
47.
AwamlehFTAlarabiatYABustamiAN. Enhancing sustainable development through international performance indicators: the role of business intelligence techniques. CiS2024; 12(3): 203–218.
48.
LiZZhangSMengQ, et al.Barriers to the development of prefabricated buildings in China: a news coverage analysis. Eng Constr Archit Manag2021; 28: 2884–2903.
49.
SunHFangYYinM, et al.Research on the restrictive factors of vigorous promotion of prefabricated buildings in Yancheng under the background of “Double Carbon”. Sustainability2023; 15: 1737.
