越览（180）——精读硕士论文的4.1 软件供应商评价模型的框架构建

摘要：This issue of tweets will introduce 4.1 Framework construction of BIM software supplier evaluation model for construction enterpri

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“越览（180）——精读博士论文

《建筑施工企业BIM软件供应商的选择与评价研究》

的4.1 建筑施工企业BIM 软件供应商评价模型的框架构建

选择评价指标体系的构建欢迎您的访问！

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Today, the editor brings you

4.1 Framework construction of BIM software

supplier evaluation model for

construction enterprises

of "Yuelan (180)——Intensive reading of

the master’s thesis

‘Research on the selection and evaluation of BIM

software suppliers for

construction enterprises’".

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一、内容摘要（Summary of content）

本期推文将从思维导图、精读内容、知识补充三个方面介绍博士论文《建筑施工企业BIM软件供应商的选择与评价研究》的4.1建筑施工企业 BIM 软件供应商评价模型的框架构建。

This issue of tweets will introduce 4.1 Framework construction of BIM software supplier evaluation model for construction enterprises of the doctoral thesis "Research on Industrial Chain Resilience from the Perspective of Supply Chain Network Structure" from three aspects: mind mapping, intensive reading content, and knowledge supplement.

二、思维导图（Mind mapping）

三、精读内容（Intensive reading content）

在建筑施工企业的BIM软件采购实践中，供应商选择是保障项目顺利推进和信息化建设效果的关键环节。根据相关研究和工程实践，供应商选择通常经历两个主要阶段：初选（资格审查）与综合评价（评标）。

When purchasing BIM software for construction companies, supplier selection is crucial for ensuring smooth project progress and effective information technology development. Based on relevant research and engineering practice, supplier selection typically involves two main stages: preliminary selection (qualification review) and comprehensive evaluation (bid review).

（一）第一阶段：供应商初选（Phase 1: Supplier Preliminary Selection）

企业在发布招标信息后，需根据自身实际情况制定合理的采购标准，对意向投标供应商进行资格审查。通过这一过程，可以筛选出至少3家合格的候选单位进入正式的评标环节。初选阶段的科学性直接决定了后续评价的有效性。

After publishing a tender, companies must develop reasonable procurement standards based on their specific circumstances and conduct a qualification review of potential bidders. This process will narrow down at least three qualified candidates for the formal bid evaluation phase. The effectiveness of the preliminary selection process directly determines the effectiveness of the subsequent evaluation.

After the shortlist is determined, a systematic and comprehensive evaluation of the candidate suppliers is required:

指标量化处理：评价指标体系通常包含大量难以直接测度的定性指标，如技术创新能力、售后服务水平或团队协作效率。此时应通过合适的量化方将定性因素转化为可计算的数值数据，从而确保评价具备可比性与科学性。

Quantifying Indicators: Evaluation index systems often include numerous qualitative indicators that are difficult to measure directly, such as technological innovation, after-sales service, or team collaboration efficiency. Appropriate quantification methods should be used to convert these qualitative factors into calculable numerical data to ensure comparable and scientific evaluation results.

权重确定：各项指标在供应商综合能力中的重要性并不相同。例如，软件功能完善度可能比价格因素更为关键。因此需要借助科学的权重确定方法准确反映不同指标在整体评价中的影响力。

Weighting: The importance of various indicators in a supplier's overall capabilities varies. For example, software functionality may be more critical than price. Therefore, a scientific weighting method is needed to accurately reflect the influence of different indicators in the overall evaluation.

综合排序与决策：在获得指标评分与权重后，通过数学方法计算各供应商的综合得分，并进行排序，最终确定最优合作方。

Comprehensive ranking and decision-making: After obtaining the indicator scores and weights, the comprehensive scores of each supplier are calculated through mathematical methods, and they are ranked to ultimately determine the optimal partner.

四、知识补充（Knowledge supplement）

在建筑施工企业的BIM供应商选择过程中，初选与综合评价是相辅相成、层层递进的两个关键环节。初选阶段保证了候选供应商的基本资质和服务能力，避免了不具备核心条件的供应商进入后续环节；而综合评价阶段则通过量化与排序，确保最终选择具有最优综合能力的合作方。值得注意的是，BIM软件的采购不同于一般物资采购，其评价维度更为复杂，既涉及技术性能、实施能力，又涵盖成本控制、服务响应、信息安全等多元化指标，因此其科学评价过程尤为重要。

In the BIM supplier selection process for construction companies, preliminary selection and comprehensive evaluation are two key, mutually reinforcing, and progressive steps. The preliminary selection phase ensures the basic qualifications and service capabilities of candidate suppliers, preventing suppliers that lack core qualifications from entering subsequent stages. The comprehensive evaluation phase, on the other hand, ensures the ultimate selection of the partner with the best overall capabilities through quantification and ranking. It is worth noting that BIM software procurement differs from general material procurement in that its evaluation dimensions are more complex, encompassing not only technical performance and implementation capabilities, but also diverse indicators such as cost control, service responsiveness, and information security. Therefore, a scientific evaluation process is particularly important.

在量化处理方面，由于大量评价指标具有模糊性和主观性，如何通过科学的评价方法实现定性到定量的有效转化，是确保结果客观性的关键。目前常用的模糊数学方法、层次分析法以及熵权法等均能在不同程度上发挥作用，但其适用性仍需结合实际采购环境加以甄别。在权重设定方面，单纯依赖专家经验可能带来主观偏差，而完全依赖客观数据又可能忽视企业战略诉求，因此“主客观结合”的综合赋权思路，将是未来BIM供应商选择模型优化的重要方向。

In terms of quantification, since many evaluation indicators are ambiguous and subjective, achieving effective qualitative-to-quantitative transformation through scientific evaluation methods is key to ensuring the objectivity of the results. Commonly used methods such as fuzzy mathematics, the analytic hierarchy process, and the entropy weight method can all be effective to varying degrees, but their applicability still needs to be determined in the context of the actual procurement environment. Regarding weight setting, relying solely on expert experience can lead to subjective bias, while relying solely on objective data can overlook the company's strategic needs. Therefore, a comprehensive weighting approach that combines subjective and objective factors will be an important direction for optimizing BIM supplier selection models in the future.

综合评价阶段不仅是简单的排序，更是对不同指标间权衡关系的科学体现。例如，当企业处于数字化转型初期时，可能更重视软件的易用性与实施支持；而在转型深化阶段，则可能更看重技术创新与生态兼容性。因此，评价结果并非一成不变，而应体现一定的动态适应性，以支持企业在不同发展阶段做出最优决策。

The comprehensive evaluation phase involves more than a simple ranking; it also scientifically reflects the trade-offs between different indicators. For example, in the early stages of digital transformation, a company may prioritize software usability and implementation support; in the more advanced stages of transformation, however, technological innovation and ecosystem compatibility may be prioritized. Therefore, evaluation results are not static but should reflect a degree of dynamic adaptability to support companies in making optimal decisions at different stages of development.

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