为实现“双碳”目标, 中国大力推动清洁能源项目建设, 加速能源绿色低碳转型。清洁能源项目涉及复杂的技术、经济、社会和环境风险, 涵盖设计、采购、施工、运营各个阶段。鉴于利益相关方合作和数字化技术应用对于清洁能源项目风险管理的重要性, 该文从数字化和伙伴关系双元视角, 构建了清洁能源项目风险管理影响机理模型, 并通过问卷、访谈和案例分析进行了实证。模型检验结果表明, 项目数字化水平、伙伴关系、知识管理、参建企业能力和项目风险管理共同对项目绩效有显著的影响作用。通过调研深入分析了清洁能源项目风险管理及相关管理因素的现状、问题及成因, 明确了当前清洁能源项目风险管理应重点关注的因素, 提出了相应风险管理建议。该研究可为清洁能源项目风险管理提供理论与实践参考。

Objective: In the past years, the Chinese government has promoted the implementation of clean energy projects to accelerate the transition to green and low-carbon energy in accordance with its "Dual Carbon" target. Clean energy projects involve complex technical, socioeconomic, and environmental risks that cover all stages of engineering, procurement, construction, and operation. Thus, enhancing risk management is essential for effectively mitigating various risks and improving project performance. Studies on the risk management of clean energy projects often focus on specific perspectives and lack systematic investigations of related management issues of clean energy projects. Given the importance of stakeholder collaboration and the application of digital technology in risk management for clean energy projects, this study constructs and empirically validates a conceptual risk management model from the dual perspectives of digitalization and partnering. Methods: A mixed-method design was adopted, combining qualitative and quantitative approaches to conduct an empirical investigation. To collect quantitative data, a risk management survey questionnaire for clean energy projects was designed based on a literature review and expert interviews and distributed to management and technical personnel from various clean energy projects. Qualitative data were then gathered through expert interviews, field studies, and the collection of project materials, including digital management materials, engineering contracts, risk management cases, and risk management documents. This study also employed structural equation modeling to verify the relationships between variables in the risk management impact relationship model, including knowledge management, project digitization, partnering, participant capability, project performance, and risk management. The questionnaire survey results were analyzed to assess the current state of various management factors, thus providing insights into clean energy project management and identifying key risk management factors. Results: The results obtained after validating the conceptual risk management impact relationship model reveal that project digitization can directly influence risk management and can also indirectly enhance risk management by promoting knowledge management and improving participant capability. Furthermore, partnering can improve risk management by strengthening enterprise capabilities and facilitating knowledge management. Finally, risk management has a significant positive effect on project performance. Conclusions: This study proposes and validates a risk management impact relationship model for clean energy projects and reveals the mechanisms influencing risk management from the perspectives of digitization and partnering. The findings indicate that project digitization, partnering, knowledge management, participant capability, and risk management collectively have a significant impact on project performance. Furthermore, this study establishes a measurement indicator system for factors related to clean energy project risk management, facilitating systematic analysis of the current status, obstacles, and causes of these factors. The outcomes of our industry survey also reveal key aspects that should be prioritized in current risk management efforts. From our findings, several risk management strategies for clean energy projects are proposed, including the establishment of a systematic risk management system to strengthen comprehensive risk management, acceleration of the digital transformation of projects to enhance intelligent risk management, improvement of the partnering among project participants to promote collaborative risk management, implementation of a comprehensive knowledge management system to create a learning organization, and enhancement of participant capability to continuously improve project risk management.