Strategies for Mitigating Risks of Government-Led Energy Retrofitting Projects in China

Ling Jia*, Queena K. Qian, Frits Meijer, Henk Visscher

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Residential energy retrofitting projects in the hot summer and cold winter (HSCW) zone of China face various risks related to project activities, which incur transaction costs (TCs), such as search, negotiation, and monitoring costs. As the leader in project implementation, the Chinese government is responsible for project planning, organisation, and coordination. However, TCs impede the government’s ability to execute risk-related project activities effectively, subsequently increasing the probability of the occurrence of risk. Drawing on transaction cost economics (TCE), this study proposes a theoretical framework to understand the barriers—such as asset specificity, uncertainty, and frequency—that prevent the government from performing project activities and mitigating risks effectively. An artificial neural network (ANN) is applied to verify the hypotheses. The results underscore experience and operational maturity in project activities, cost and time constraints, and the immature retrofitting market as significant impediments to the government’s execution of risk-related activities. Considering the varying roles of the government in reducing different risks, this study concludes by offering policy recommendations to alleviate these activity barriers and mitigate risks. By employing a TCs perspective, this study not only identifies key barriers but also deepens our understanding of risk mitigation mechanisms, providing robust policy insights tailored to the specific regional context of China, thereby enhancing both the execution and the framework of government-led retrofitting projects.
Original languageEnglish
Article number1663
Number of pages26
JournalBuildings
Volume14
Issue number6
DOIs
Publication statusPublished - 2024

Keywords

  • residential energy retrofitting
  • government strategies
  • risk mitigation
  • transaction costs
  • artificial neural network

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