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Dynamic Decision Breakdown Structure: Ontology, Methodology, & Framework for Information Management in Support of Decision-Enabling Tasks in the Building Industry

TitleDynamic Decision Breakdown Structure: Ontology, Methodology, & Framework for Information Management in Support of Decision-Enabling Tasks in the Building Industry
Publication TypeTechnical Report
Year of Publication2005
AuthorsKam, C
Date Published12/2005
Publication Languageeng
Keywords3-D, 4-D, Breakdown Structure, Center for Integrated Facility Engineering, CIFE, Construction, Coordination, Decision, Design, Framework, Information Management, Ontology, Organization Models, Planning, Process Models, Product Models, Stanford University, Validation, VDC, Virtual Design and Construction
AbstractThe 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.
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