Exploring Decision-Making Methods for Sustainable Design in Commercial Buildings

During the building design process hundreds of decisions are made at different stages, and with multiple stakeholders. This includes choosing alternative materials, components, assemblies, systems, and buildings shapes. The design team faces many challenges in order to evaluate which alternative is more sustainable. The methods used in making those decisions must take the complexity of the design process into account and help the design team in understanding the trade-offs that must be made. This must be done based on context, and in a transparent and collaborative fashion. What is more, the design team may benefit from keeping decisions objective for as long as possible during the decision process to avoid unnecessary conflict and suboptimal decisions. Ultimately, the decision-making method used in those decisions will impact the final building design, and therefore, the building's social-, environmental -, and economic outcomes./nMuch like designers and engineers benefit from relying on specific modeling-, analysis-, and evaluation methods to inform their judgment in the course of the design, the design team would also benefit from relying on decision-making methods. However, the architecture-, engineering-, and construction-management literature provides almost no guidance to internal stakeholders (owner, architect, design specialists, etc.) on how to choose a sustainable alternative (e.g., choosing materials, components, assemblies, systems, building layouts)./nThis research evaluates the ability of Multiple-Criteria Decision-Making (MCDM) methods to help design teams choose a sustainable alternative during commercial building design. The researcher identified several types of MCDM methods in the literature. Those with potential application for the `choosing problem' studied in this research are (1) Goal-programming and multi-objective optimization methods, (2) Value-based methods (including Analytical Hierarchy Process (AHP) and Weighting Rating and Calculating (WRC)), (3) Outranking methods, and (4) Choosing By Advantages (CBA). The researcher compared these different types of methods and judged them on how they help in creating transparency, building consensus, and continuous learning for the problem of choosing a sustainable alternative in commercial building design. Thus far the literature contains no such comparison. The research method included interviews in the early exploratory phase and case-study research for testing the methods./nThe researcher further compared AHP vs. CBA and WRC vs. CBA through case studies. The researcher selected AHP for its prevalence in AEC decision-making literature, WRC for its widespread use in AEC design practice, and CBA for its potential support in creating transparency, building consensus, and continuous learning, better than either one of these two methods do./nFrom the four types of methods studied the researcher found that:/n(1) Goal-programming and multi-objective optimization methods are particularly suited to problems that require screening of a big or infinite number of alternatives according to ranked criteria. However, some multi-objective optimization methods avoid the use of explicit trade-offs by using a ranking of factors. This does not create transparency when comparing a small number of alternatives with known attributes./n(2) Value-based methods are widely used in building design practice and literature. However, such methods (e.g., AHP and WRC) may not help in creating transparency, building consensus, and continuous learning for group decision making. This is because they (a) may assume that factors have zero as a natural scale, (b) may assume that trade-offs between factors are linear functions, (c) may not differentiate between alternatives, (d) may be inconsistent when irrelevant factors are removed, (e) may mix `value' and cost, (f) may require conflicting judgments for weighting factors, and (g) may lack support for context-based analysis./n(3) Outranking methods are hard to apply to this problem since they lack an aggregation function, which makes it impossible to rank alternatives and evaluate `value' vs. cost. Even when these methods focus more on the differences between the alternatives than value-based methods do, they also require decision makers to weigh factors and attributes in order to build outranking relations./n(4) CBA focuses more on differentiating between alternatives, and better guides the design team to understand `value' vs. cost compared to the other MCDM methods studied. In addition, CBA avoids assuming that every increment in performance is equally valuable or that trade-offs between factors are linear./nAfter comparing the methods, this research proposes the use of Choosing By Advantages (CBA) to overcome the deficiencies of the value-based methods in regards to creating transparency, building consensus, and continuous learning in the design process. The researcher further tested CBA in three case studies for different applications in architecture and engineering firms in the San Francisco Bay Area./nThis work contributes to knowledge by providing: (1) A theoretical evaluation of the four types of MCDM methods being studied and illustrating relevant differences between them; (2) A practical evaluation of CBA vs. AHP and CBA vs. WRC presenting factors and criteria for evaluating their ability to assist practitioners in deciding which alternative is more sustainable in commercial building design; (3) A rationale for recommending the CBA method in the research context; and (4) An analysis of the application of CBA for different types of decisions. In addition, this research discusses: (5) How sustainable rating systems (e.g., LEED) affect decisions; (6) How cognitive biases may apply to group decision making in this context and how they may be overcome; and (7) How rhetoric can support the CBA application. Through these seven areas of contribution, the presented research provides a basis for discussing MCDM method selection in commercial building design that may be expanded to other applications, and for advancing our understanding of the relationship between decision-making methods and building outcomes.

Advisor: Tommelein, Iris D