Desbalo Muluken Tilahun, Woldesenbet Asregedew Kassa
Construction Engineering and Management, Bauhaus Universität Weimar, Weimar, Germany.
Chair of Construction Management, Ethiopian Institute of Architecture Building Construction and City Development (EiABC), Addis Ababa University, Addis Ababa, Ethiopia.
Heliyon. 2024 Nov 29;10(23):e40824. doi: 10.1016/j.heliyon.2024.e40824. eCollection 2024 Dec 15.
BIM-Enabled Asset Information Modelling (AIM) entails incorporating extensive data, known as big data, into digital platforms for informed decision-making. However, the lack of accurate and reliable data and the immaturity of BIM integration in existing buildings lead to operational phase performance inefficiencies due to inadequate data access. A strategic approach using BIM-enabled AIM is proposed to address these challenges, with the goal of enhancing data accessibility and adequacy for the operational team's performance. This study aims to develop a framework of information requirements that supports operational strategic decisions in asset portfolio management. To develop the framework, we employed a methodology that combines the Analytic Hierarchy Process (AHP) a structured technique for organizing and analysing complex decisions with fuzzy logic, which helps handle uncertainty in experts' judgments. A comprehensive questionnaire based on the Analytic Hierarchy Process (AHP) methodology was developed to gather expert insights on prioritizing information requirements, and it was administered to 11 experts selected for their diverse expertise in problem area. Cost, risk, and business value as selection criteria, while technical, managerial, financial, legal, and commercial categories of information are considered as alternatives in the AHP hierarchy. Utilizing the described methodology, fuzzy-AHP analysis revealed distinct variations in information requirements across the strategic decisions of maintain/keep, improve/adapt, and deconstruct/disassemble. For decisions on whether to maintain/keep buildings, the primary information requirement is managerial (39.6 %), followed by legal (20.7 %) and commercial (20 %), guiding strategic decisions. In contrast, improve/adapt decisions prioritize technical information (39 %), with financial (15.5 %) and legal (13.5 %) considerations also being significant. For the deconstruct/disassemble decisions, technical information requirements are most critical (55.5 %), followed by legal (16.6 %) and commercial (12.8 %) information. The findings highlight the need for tailored data generation strategies in existing buildings to address specific decision requirements, aiding in planning and resource allocation towards efficient AIM. The primary limitation of this study is its reliance on a small pool of 11 experts, which may limit the generalizability of the findings. Future research should aim to broaden the expert base to enhance the applicability and robustness of the results.
基于建筑信息模型（BIM）的资产信息模型（AIM）需要将大量数据（即大数据）整合到数字平台中，以便做出明智的决策。然而，现有建筑中缺乏准确可靠的数据以及BIM集成的不成熟，导致由于数据获取不足而在运营阶段出现效率低下的情况。本文提出了一种使用基于BIM的AIM的战略方法来应对这些挑战，目标是提高数据的可访问性和充分性，以提升运营团队的绩效。本研究旨在开发一个信息需求框架，以支持资产组合管理中的运营战略决策。为了开发该框架，我们采用了一种方法，将层次分析法（AHP）（一种用于组织和分析复杂决策的结构化技术）与模糊逻辑相结合，这有助于处理专家判断中的不确定性。基于层次分析法（AHP）方法开发了一份综合问卷，以收集专家对信息需求优先级的见解，并将其发放给11位因其在问题领域的不同专业知识而被选中的专家。成本、风险和商业价值作为选择标准，而技术、管理、财务、法律和商业类别的信息则被视为AHP层次结构中的备选方案。利用所描述的方法，模糊层次分析法分析揭示了在维护/保留、改进/适应和解构/拆卸等战略决策中信息需求的明显差异。对于是否维护/保留建筑物的决策，主要信息需求是管理方面的（39.6%），其次是法律方面的（20.7%）和商业方面的（20%），这些信息指导着战略决策。相比之下，改进/适应决策优先考虑技术信息（39%），财务（15.5%）和法律（13.5%）方面的考虑也很重要。对于解构/拆卸决策，技术信息需求最为关键（55.5%），其次是法律（16.6%）和商业（12.8%）信息。研究结果强调，需要在现有建筑中制定量身定制的数据生成策略，以满足特定的决策要求，有助于为高效的AIM进行规划和资源分配。本研究的主要局限性在于其依赖于11位专家的小样本，这可能会限制研究结果的普遍性。未来的研究应旨在扩大专家群体以提高结果的适用性和稳健性。
