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Proceedings ArticleDOI

Stakeholder Value Evolution, Capture and Assessment in AEC Project Design

18 Jul 2018-pp 549-559
TL;DR: In this paper, the authors present the process of client value generation and evolution based on an ethnographic study of the architect selection process of two institutional buildings and propose a framework for the evaluation of design of a built facility using suitable multi-criteria decision making (MCDM) technique.
Abstract: The success of a design lies in its ability to fulfill client values. However, the ambiguity in identification of values by clients renders the task complex and challenging. The investigation of the dynamics involved in stakeholder definition of the project values entails the need for research methods used in social sciences. This paper first presents the process of client value generation and evolution based on an ethnographic study of the architect selection process of two institutional buildings. The study consists of participant and non-participant observations of the project conceptualization and architect selection process. It is observed that along with client requirements incorporated in architectural design, the design delivery efficiency criteria of the architect have equal considerations in architect selection. Therefore, the values in Architecture Engineering and Construction (AEC) design can be categorized into Project Design Delivery Values (PDDVs) and Architectural Design Values (ADVs). The paper proposes a framework for the evaluation of design of a built facility using suitable Multi-Criteria Decision Making (MCDM) technique.

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Proceedings ArticleDOI
03 Jul 2019
TL;DR: The findings from the study indicate that CBA aids in defining a robust set of design criteria, sub-criteria and attributes and facilitates a collaborative decision-making process and on the other hand, AHP provides a structured approach for eliciting individual participant judgments.
Abstract: Arriving at a consensus in design decisions is challenging owing to the presence of diverse and multidisciplinary stakeholders with multiple design objectives. The literature on AEC design decision making have reported Analytic Hierarchy Process and Choosing by Advantages as two commonly used multi-criteria decision-making techniques for evaluation of design alternatives. However, the existing literature has mainly focused on choosing between material or technology and the comparison of the two techniques to assess the suitability for their application to non-spatial aspects of AEC design problem. The current work seeks to investigate the suitability of CBA and AHP to a layout design problem. A decision-making exercise involving a hypothetical case of evaluation of three classroom layouts was conducted. A set of criteria for design evaluation which was derived based on a previous study on stakeholder design values was used in the exercise. Conclusions were drawn based on the operationalization of the two techniques rather than a direct comparison of the results obtained from the two techniques. The findings from the study indicate that CBA aids in defining a robust set of design criteria, sub-criteria and attributes and facilitates a collaborative decision-making process. On the other hand, AHP provides a structured approach for eliciting individual participant judgments. The benefits and limitations with respect to the operationalization of the two techniques are discussed in detail.

4 citations


Cites background or methods from "Stakeholder Value Evolution, Captur..."

  • ...The set of design values from a previous study on university campus design (Sahadevan and Varghese 2018) were used as criteria for applying the two techniques....

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  • ...A study on stakeholder values in the design of university campus buildings (Sahadevan and Varghese 2018), led to a framework for evaluating design alternatives....

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Proceedings ArticleDOI
26 Jun 2023
TL;DR: In this article , the authors describe the strategies utilized to focus on and manage value generation in Target Value Delivery (TVD) at the University of California in San Francisco (UCSF).
Abstract: Responsible for delivering major healthcare projects, the University of California in San Francisco (UCSF) has devised creative ways of reducing waste and increasing value through project delivery. In a previous paper, we described UCSF Health ’s journey to rethink project delivery practices. The adoption of Target Value Delivery (TVD) is a core enabler of their success. The University has consistently adopted TVD to deliver complex healthcare projects within or below their allowable costs. Previous papers have provided evidence and insights into why and how such success has been achieved. However, the focus so far has been on collaboration and cost management. This paper describes the strategies utilized to focus on and manage value generation. The term human-centered innovation was chosen to emphasize stakeholder engagement and empathy building as input to idea generation. This approach shaped how TVD is implemented in these case studies. Its analysis provided insights into complementary design and decision-making strategies traditionally used in TVD. In particular, the design strategies observed in this research expand the documentation of TVD best practices to include not only solution development strategies but also participatory and empathic ways of understanding, framing, and reframing design problems.
References
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Book
01 Mar 1981
TL;DR: In this paper, the authors present a classification of MADM methods by data type and propose a ranking method based on the degree of similarity of the MADM method to the original MADM algorithm.
Abstract: I. Introduction.- II. Multiple Attribute Decision Making - An Overview.- 2.1 Basics and Concepts.- 2.2 Classifications of MADM Methods.- 2.2.1 Classification by Information.- 2.2.2 Classification by Solution Aimed At.- 2.2.3 Classification by Data Type.- 2.3 Description of MADM Methods.- Method (1): DOMINANCE.- Method (2): MAXIMIN.- Method (3): MAXIMAX.- Method (4): CONJUNCTIVE METHOD.- Method (5): DISJUNCTIVE METHOD.- Method (6): LEXICOGRAPHIC METHOD.- Method (7): LEXICOGRAPHIC SEMIORDER METHOD.- Method (8): ELIMINATION BY ASPECTS (EBA).- Method (9): LINEAR ASSIGNMENT METHOD (LAM).- Method (10): SIMPLE ADDITIVE WEIGHTING METHOD (SAW).- Method (11): ELECTRE (Elimination et Choice Translating Reality).- Method (12): TOPSIS (Technique for Order Preference by Similarity to Ideal Solution).- Method (13): WEIGHTED PRODUCT METHOD.- Method (14): DISTANCE FROM TARGET METHOD.- III. Fuzzy Sets and their Operations.- 3.1 Introduction.- 3.2 Basics of Fuzzy Sets.- 3.2.1 Definition of a Fuzzy Set.- 3.2.2 Basic Concepts of Fuzzy Sets.- 3.2.2.1 Complement of a Fuzzy Set.- 3.2.2.2 Support of a Fuzzy Set.- 3.2.2.3 ?-cut of a Fuzzy Set.- 3.2.2.4 Convexity of a Fuzzy Set.- 3.2.2.5 Normality of a Fuzzy Set.- 3.2.2.6 Cardinality of a Fuzzy Set.- 3.2.2.7 The mth Power of a Fuzzy Set.- 3.3 Set-Theoretic Operations with Fuzzy Sets.- 3.3.1 No Compensation Operators.- 3.3.1.1 The Min Operator.- 3.3.2 Compensation-Min Operators.- 3.3.2.1 Algebraic Product.- 3.3.2.2 Bounded Product.- 3.3.2.3 Hamacher's Min Operator.- 3.3.2.4 Yager's Min Operator.- 3.3.2.5 Dubois and Prade's Min Operator.- 3.3.3 Full Compensation Operators.- 3.3.3.1 The Max Operator.- 3.3.4 Compensation-Max Operators.- 3.3.4.1 Algebraic Sum.- 3.3.4.2 Bounded Sum.- 3.3.4.3 Hamacher's Max Operator.- 3.3.4.4 Yager's Max Operator.- 3.3.4.5 Dubois and Prade's Max Operator.- 3.3.5 General Compensation Operators.- 3.3.5.1 Zimmermann and Zysno's ? Operator.- 3.3.6 Selecting Appropriate Operators.- 3.4 The Extension Principle and Fuzzy Arithmetics.- 3.4.1 The Extension Principle.- 3.4.2 Fuzzy Arithmetics.- 3.4.2.1 Fuzzy Number.- 3.4.2.2 Addition of Fuzzy Numbers.- 3.4.2.3 Subtraction of Fuzzy Numbers.- 3.4.2.4 Multiplication of Fuzzy Numbers.- 3.4.2.5 Division of Fuzzy Numbers.- 3.4.2.6 Fuzzy Max and Fuzzy Min.- 3.4.3 Special Fuzzy Numbers.- 3.4.3.1 L-R Fuzzy Number.- 3.4.3.2 Triangular (or Trapezoidal) Fuzzy Number.- 3.4.3.3 Proof of Formulas.- 3.4.3.3.1 The Image of Fuzzy Number N.- 3.4.3.3.2 The Inverse of Fuzzy Number N.- 3.4.3.3.3 Addition and Subtraction.- 3.4.3.3.4 Multiplication and Division.- 3.5 Conclusions.- IV. Fuzzy Ranking Methods.- 4.1 Introduction.- 4.2 Ranking Using Degree of Optimality.- 4.2.1 Baas and Kwakernaak's Approach.- 4.2.2 Watson et al.'s Approach.- 4.2.3 Baldwin and Guild's Approach.- 4.3 Ranking Using Hamming Distance.- 4.3.1 Yager's Approach.- 4.3.2 Kerre's Approach.- 4.3.3 Nakamura's Approach.- 4.3.4 Kolodziejczyk's Approach.- 4.4 Ranking Using ?-Cuts.- 4.4.1 Adamo's Approach.- 4.4.2 Buckley and Chanas' Approach.- 4.4.3 Mabuchi's Approach.- 4.5 Ranking Using Comparison Function.- 4.5.1 Dubois and Prade's Approach.- 4.5.2 Tsukamoto et al.'s Approach.- 4.5.3 Delgado et al.'s Approach.- 4.6 Ranking Using Fuzzy Mean and Spread.- 4.6.1 Lee and Li's Approach.- 4.7 Ranking Using Proportion to The Ideal.- 4.7.1 McCahone's Approach.- 4.8 Ranking Using Left and Right Scores.- 4.8.1 Jain's Approach.- 4.8.2 Chen's Approach.- 4.8.3 Chen and Hwang's Approach.- 4.9 Ranking with Centroid Index.- 4.9.1 Yager's Centroid Index.- 4.9.2 Murakami et al.'s Approach.- 4.10 Ranking Using Area Measurement.- 4.10.1 Yager's Approach.- 4.11 Linguistic Ranking Methods.- 4.11.1 Efstathiou and Tong's Approach.- 4.11.2 Tong and Bonissone's Approach.- V. Fuzzy Multiple Attribute Decision Making Methods.- 5.1 Introduction.- 5.2 Fuzzy Simple Additive Weighting Methods.- 5.2.1 Baas and Kwakernaak's Approach.- 5.2.2 Kwakernaak's Approach.- 5.2.3 Dubois and Prade's Approach.- 5.2.4 Cheng and McInnis's Approach.- 5.2.5 Bonissone's Approach.- 5.3 Analytic Hierarchical Process (AHP) Methods.- 5.3.1 Saaty's AHP Approach.- 5.3.2 Laarhoven and Pedrycz's Approach.- 5.3.3 Buckley's Approach.- 5.4 Fuzzy Conjunctive/Disjunctive Method.- 5.4.1 Dubois, Prade, and Testemale's Approach.- 5.5 Heuristic MAUF Approach.- 5.6 Negi's Approach.- 5.7 Fuzzy Outranking Methods.- 5.7.1 Roy's Approach.- 5.7.2 Siskos et al.'s Approach.- 5.7.3 Brans et al.'s Approach.- 5.7.4 Takeda's Approach.- 5.8 Maximin Methods.- 5.8.1 Gellman and Zadeh's Approach.- 5.8.2 Yager's Approach.- 5.9 A New Approach to Fuzzy MADM Problems.- 5.9.1 Converting Linguistic Terms to Fuzzy Numbers.- 5.9.2 Converting Fuzzy Numbers to Crisp Scores.- 5.9.3 The Algorithm.- VI. Concluding Remarks.- 6.1 MADM Problems and Fuzzy Sets.- 6.2 On Existing MADM Solution Methods.- 6.2.1 Classical Methods for MADM Problems.- 6.2.2 Fuzzy Methods for MADM Problems.- 6.2.2.1 Fuzzy Ranking Methods.- 6.2.2.2 Fuzzy MADM Methods.- 6.3 Critiques of the Existing Fuzzy Methods.- 6.3.1 Size of Problem.- 6.3.2 Fuzzy vs. Crisp Data.- 6.4 A New Approach to Fuzzy MADM Problem Solving.- 6.4.1 Semantic Modeling of Linguistic Terms.- 6.4.2 Fuzzy Scoring System.- 6.4.3 The Solution.- 6.4.4 The Advantages of the New Approach.- 6.5 Other Multiple Criteria Decision Making Methods.- 6.5.1 Multiple Objective Decision Making Methods.- 6.5.2 Methods of Group Decision Making under Multiple Criteria.- 6.5.2.1 Social Choice Theory.- 6.5.2.2 Experts Judgement/Group Participation.- 6.5.2.3 Game Theory.- 6.6 On Future Studies.- 6.6.1 Semantics of Linguistic Terms.- 6.6.2 Fuzzy Ranking Methods.- 6.6.3 Fuzzy MADM Methods.- 6.6.4 MADM Expert Decision Support Systems.- VII. Bibliography.

8,629 citations

Journal ArticleDOI
William Ho1
TL;DR: This research provides evidence that the integrated AHPs are better than the stand-alone AHP, but also aids the researchers and decision makers in applying the integratedAHPs effectively.

993 citations


"Stakeholder Value Evolution, Captur..." refers methods in this paper

  • ...Multi-Criteria Decision Making (MCDM) techniques are used in ranking and choosing from available alternatives based on weights given to the criteria which are sometimes conflicting (Ho 2008)....

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Journal ArticleDOI
11 Sep 2015
TL;DR: The results of this study indicated that in 2013 scholars have published articles more than in other years, and energy, environment and sustainability were ranked as the first areas that have applied MCDM techniques and approaches.
Abstract: Multiple criteria decision-making (MCDM) is considered as a complex decision-making (DM) tool involving both quantitative and qualitative factors. In recent years, several MCDM techniques and approaches have been suggested to choosing the optimal probable options. The purpose of this article is to systematically review the applications and methodologies of the MCDM techniques and approaches. This study reviewed a total of 393 articles published from 2000 to 2014 in more than 120 peer reviewed journals (extracted from Web of Science). According to experts’ opinion, these articles were grouped into 15 fields. Furthermore, these articles were categorised based on authors, publication date, name of journals, methods, tools, and type of research (MCDM utilising research, MCDM developing research, and MCDM proposing research). The results of this study indicated that in 2013 scholars have published articles more than in other years. In addition, the analytic hierarchy process (AHP) method in the individual tool...

704 citations


"Stakeholder Value Evolution, Captur..." refers methods in this paper

  • ...MCDM techniques have been applied to a wide range of areas such as business, production, energy and environment, economy, etc. (Mardani et al. 2015)....

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Journal ArticleDOI
TL;DR: The main findings from the Probe occupant surveys are assessed in this article, with an emphasis on the consequences for strategic thinking on how best to design and manage buildings to improve conditions for occupants and users.
Abstract: The main findings from the Probe occupant surveys are assessed. The emphasis is on the consequences for strategic thinking on how best to design and manage buildings to improve conditions for occupants and users, taking examples from the Probe studies. Comfort, health and productivity of occupants are positively associated statistically; and all are easily undermined by chronic, low-level problems. Improvement may not necessarily require raising overall environmental standards - particularly if this requires more energy or reduces perceived control, which occupants think has been falling steadily in recent years. Noise-related problems are also growing with today's trend to more open, more diverse and often more reverberant environments. For the occupant, ‘satisficing’ may be better than optimizing; and big benefits can come from minimizing the main causes of discomfort, ill health and low productivity - for example by designing and managing to help individuals to choose how to overcome local problems whe...

308 citations


"Stakeholder Value Evolution, Captur..." refers methods in this paper

  • ...Other tools include the Post-Occupancy Review of Buildings and their Engineering for post occupancy evaluation (Leaman and Bordass, 2001), Housing Quality Indicator (HQI) for housing projects (DTLR, 2000) and Building Research Establishment Environmental Assessment Method (BREEAM) which provides…...

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  • ...Other tools include the Post-Occupancy Review of Buildings and their Engineering for post occupancy evaluation (Leaman and Bordass, 2001), Housing Quality Indicator (HQI) for housing projects (DTLR, 2000) and Building Research Establishment Environmental Assessment Method (BREEAM) which provides measures of energy use in construction....

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01 Jan 2003
TL;DR: The Design Quality Indicator (DQI) as mentioned in this paper is based on a research project to provide a toolkit for improving the design of buildings and it seeks to complement methods for measuring performance in construction by providing feedback and capturing perceptions of design quality embodied in buildings.
Abstract: The Design Quality Indicator (DQI) is based on a research project to provide a toolkit for improving the design of buildings. It seeks to complement methods for measuring performance in construction by providing feedback and capturing perceptions of design quality embodied in buildings. The research team worked closely with the sponsors and an industry steering group to develop the indicators that could be readily used by clients and practitioners to better understand and promote value through design. The development and piloting process was explored within a context of lessons from earlier attempts by others. The three main elements of the DQI toolkit (conceptual framework, datagathering tool, weighting mechanism) mapped the value of buildings in relation to their design for different uses and their ability to meet a variety of physical, aspirational and emotional needs of occupants and users. The DQI pilot studies consisting of five design and construction projects are discussed along with their graphical representation of results generated by end-users, individual team members and project teams. The process raises questions about the difficulties in the description and application of indicators for design quality. It is argued that the benefit of the DQI is a ‘tool for thinking’, rather than an absolute measure, because it has the potential to capture lessons from current building design for strategic future use as well as initiate, represent and inform discussions involving designers’, clients’, producers’ and end-users’ perceptions on the tangible and intangible aspects of possibilities within live design projects. The limitations of the approach, the next phase of development and further research issues are raised.

236 citations