复杂设计-建造基础设施项目风险评估和分配的影响因素;得克萨斯州的经验

Vassiliki Demetracopoulou, William J. O’Brien, N. Khwaja
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引用次数: 0

摘要

导言:设计-施工(DB)交付方法用于交付日益复杂的交通基础设施项目,其不确定性较高。因此,在业主和设计-施工单位之间的合同中分配风险就变得非常具有挑战性,往往会导致更高的初始投标、更多的意外开支或索赔。从世界范围内的实施经验来看,有必要改进设计-建造合同中的风险分配。大多数现有研究都涉及风险分配机制,以管理合同层面的意外开支。其他研究则认识到业主有必要调整其流程,以更好地分配 DB 合同中的风险。本研究探讨了复杂的 DB 基础设施项目风险评估和分配的影响因素,探讨了在选择设计-施工方和授予 DB 合同之前改进交通业主风险分配流程的机会:通过对德克萨斯州交通部和私营部门专家的 20 次访谈收集到的经验数据,实现了这项工作的目标。访谈数据采用归纳和轴向编码法进行分析。归纳式编码允许在没有预先存在的框架的情况下出现主题,确定了复杂 DB 项目的六个影响因素和六个相关风险:这些因素包括:(i) DB 团队的素质;(ii) 前期调查的程度;(iii) 出租时间的限制;(iv) 设计优化机会;(v) 项目特定要求;以及 (vi) 与第三方的关系。通过轴向编码,还研究了因素与风险之间的相互作用和频率。编码后的交互作用显示了已确定的因素如何影响六个相关风险的分配,包括路权获取、利益相关者批准、场地条件、许可和第三方协议、铁路互动以及公用事业调整和协调。研究结果表明,对这些相互作用的评估可以将风险分配从机构制定的基线规范中转移出来,以满足项目的特定需求:在对基础设施项目管理的贡献方面,这是首次研究影响复杂 DB 项目风险分配的因素,并研究与相关风险的相互作用,为根据项目特定需求优化分配奠定基础。在实践中,本研究的结论可以指导业主调整其分配实践、管理和制定战略计划,以交付复杂的 DB 项目。研究结果还可以帮助承包商更有效地进行风险定价,提高投标竞争力。
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Influential factors for risk assessment and allocation on complex design-build infrastructure projects; the Texas experience
Introduction: The design-build (DB) delivery method is used to deliver increasingly complex transportation infrastructure projects associated with higher uncertainty. As such, allocating risks in the contract between the owner and design-builder becomes challenging and often leads to higher initial bids, increased contingency, or claims. Learnings from implementation worldwide have underlined the need for improving risk allocation in DB contracts. Most existing studies address risk allocation mechanisms to manage contingency at the contract level. Other studies have recognized the need for owners to adapt their processes to better allocate risks in DB contracts. This study explored the influential factors for risk assessment and allocation for complex DB infrastructure projects, addressing the opportunity to improve transportation owners’ risk allocation processes before the design-builder is selected and the DB contract is awarded.Method: The objectives of this work were achieved by utilizing empirical data collected through 20 interviews with Texas Department of Transportation and private sector experts. The interview data were analyzed using inductive and axial coding. Inductive coding allowed themes to emerge without a pre-existing framework, identifying six influential factors and six pertinent risks on complex DB projects.Results: These factors include the (i) Quality of DB teams, (ii) Level of up-front investigation, (iii) Limitations on the timing of letting, (iv) Design optimization opportunities, (v) Project-specific requirements, and (vi) Relationships with third parties. Through axial coding, the interaction and frequency between the factors and risks were also examined. The coded interactions demonstrated how the identified factors influence allocation for six pertinent risks including right-of-way acquisition, stakeholder approval, site conditions, permits and third-party agreements, railroad interaction, and utility adjustments and coordination. Findings indicate that the evaluation of these interactions can shift the risk allocation from baseline norms established by an agency to correspond to project-specific needs.Contribution: In contributing to the infrastructure project management, this is the first study to examine the factors that influence risk allocation in complex DB projects and examine interactions with pertinent risks, setting the foundation for optimizing allocation based on project-specific needs. In practice, the findings presented in this study can guide owners in adapting their allocation practices, managing, and developing their strategic plan for delivering complex DB projects. The findings can also assist contractors in pricing risks more efficiently and increase competitive bidding.
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