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Dynamic decision breakdown structure: Ontology, methodology, and framework for information management in support of decision-enabling tasks in the building industry.

机译:动态决策分解结构:信息管理的本体论,方法和框架,用于支持建筑行业中的决策支持任务。

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摘要

The development of AEC (architecture-engineering-construction) projects depends on the ability of decision makers to make informed and quick decisions. This requires the AEC decision facilitators to carry out decision-enabling tasks using methods and tools that are informative and rapid, so that they can integrate discipline-specific information from heterogeneous project stakeholders, evaluate choices, identify alternatives, refine decision criteria, and iterate these tasks throughout the decision-making processes. My research on industry case studies shows that current decision-support tools do not enable decision makers to make informed and quick decisions, because a structured and explicit approach to represent and organize heterogeneous information is lacking. My studies also demonstrate that current methods do not give facilitators the flexibility to manage this information while completing decision-enabling tasks. Consequently, facilitators cannot build on prior decision-enabling tasks to resume the decision process when the decision context changes.; To address these limitations, I have developed the Dynamic Decision Breakdown Structure (DBS) Framework with three underlying contributions. First, my formalization of an AEC Decision Ontology allows facilitators to establish an explicit, informative, and hierarchical representation of heterogeneous decision information and its interrelationships. Second, I formalized a dynamic methodology---the Decision Method Model (DMM)---that interacts with the Ontology and enables facilitators to combine, evaluate, and recombine formally represented information, and to complete other decision-enabling tasks flexibly and quickly. Finally, I contribute an AEC decision-making framework that formalizes the sequences, characteristics, and requirements of information management throughout the changing decision context. This framework leverages the application of the hierarchical DBS and the dynamic DMM to support the continuity of decision-enabling tasks as the decision process evolves.; I validated my contributions by evaluating the relative performance of the Decision Dashboard, a prototype computer application implemented with my ontology and methodology, with respect to a variety of methods and tools, used by renowned professionals involved in large-scale industry projects across the nation. Based on validation using six industry cases, eight decision-enabling tasks, and by twenty-one professionals and researchers, I claim that the Dynamic Decision Breakdown Structure enables more informative, flexible, resumable, and faster management of decision information than current methods.
机译:AEC(建筑工程设计)项目的开发取决于决策者做出明智和快速决策的能力。这就要求AEC决策者使用信息迅速的方法和工具来执行决策支持任务,以便他们可以整合来自不同项目利益相关者的特定于学科的信息,评估选择,确定备选方案,完善决策标准并对其进行迭代。整个决策过程中的任务。我对行业案例研究的研究表明,当前的决策支持工具无法使决策者做出明智而又迅速的决策,因为缺乏一种结构化和显式的方法来表示和组织异构信息。我的研究还表明,当前的方法并不能使协调人在完成决策支持任务时灵活地管理这些信息。因此,当决策环境发生变化时,协调人无法基于先前的决策支持任务来恢复决策过程。为了解决这些局限性,我开发了具有三个基本功能的动态决策分解结构(DBS)框架。首先,我对AEC决策本体的形式化使协调人可以建立异构决策信息及其相互关系的显式,信息化和层次化表示。其次,我确定了一种动态方法学-决策方法模型(DMM)-与本体论进行交互,使协调人能够组合,评估和重组正式表示的信息,并灵活,快速地完成其他决策支持任务。最后,我贡献了一个AEC决策框架,该框架将整个变化的决策环境中信息管理的顺序,特征和要求形式化。该框架利用分层DBS和动态DMM的应用程序来支持随着决策过程的发展而进行决策的任务的连续性。我通过评估Decision Dashboard的相对性能来验证自己的贡献,Decision Dashboard是用我的本体和方法实现的原型计算机应用程序,相对于参与全国范围内大型行业项目的著名专业人员所使用的各种方法和工具。基于使用六个行业案例,八个决策支持任务以及二十一个专业人员和研究人员的验证,我声称,动态决策分解结构比当前方法能够提供更多信息,灵活,可恢复和更快的决策信息管理。

著录项

  • 作者

    Kam, Calvin Ka Hang.;

  • 作者单位

    Stanford University.;

  • 授予单位 Stanford University.;
  • 学科 Engineering Civil.; Architecture.; Information Science.
  • 学位 Ph.D.
  • 年度 2005
  • 页码 258 p.
  • 总页数 258
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 建筑科学;建筑科学;信息与知识传播;
  • 关键词

  • 入库时间 2022-08-17 11:42:05

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