From Decision Theory to Informed Decision-Making in the Design of Sustainable High-Performance Buildings

Abstract

The design of sustainable high-performance buildings entails dealing with numerous decisions associated with the inclusion and assessment of design objectives and criteria made by multiple decision-makers (or design stakeholders). A more in-depth study of the decision-making fundamentals will, therefore, be effective and practical in this regard. Based on this underlying hypothesis, as a first attempt towards investigating the decision-making structures in the (early) design of sustainable high-performance buildings, and in addition to the empirical application of normative decision-making models, this paper presents the results of two rounds of assessment surveys through conducting semi-structured interviews with practitioners and professionals in Denmark on (a) when and with whom a decision is made, and (b) to what extent a decision can be made autocratically or participatorily. The research study is intended to enable practitioners and researchers to recognize the importance of decision-making characteristics in addressing highly complex sustainability criteria in the (early) design of high-performance buildings. The outcome ensures a systematic approach to involve the right decision-makers at the right time and with suitable decision-making styles. With its strong ability to formalize problems faced by sustainability requirements, the outcome can potentially become a research avenue in future building design contexts.

1. Introduction

Through increasing crises in energy in the 20th century, performance and performance-based design concept emerged, and the interest in overall building performance began to grow [1,2]. In this regard, Salama [3] discusses:

“…., the supremacy of consumerism and industrialization during the 1950s resulted in perceiving design knowledge as essential for improving production, developing processes to suit intended qualities in the end product, and implementing designs to accommodate users’ needs. Architecture and allied design and built environment disciplines considered performance as a goal, leading to a sustained quest by design researchers to make the design process more efficient and effective. Consequently, during the following decades and up to the late 1980s, a rational approach to knowledge acquisition, assimilation and accommodation in a systematic design process has dominated design discourse”.

Building performance can, through an epistemological interpretation, be described as an expression of how well a building carries out its functions [4]. Functions can be summarized as everything from energy, acoustics, lights, design, and fire safety to user satisfaction or indoor climate. As such, building performance can be addressed as a measurement of how a building functions within the context of certain criteria to meet the users’ needs and requirements [5]. As building-design evaluation criteria change to include social and environmental impacts, the importance of building performance increases significantly. It can be a powerful tool to better understand, design, and manage high-performance buildings. In this context, high-performance buildings can be described as sustainable buildings with economic, environmental, and sociocultural characteristics and a better performance than standard buildings. It must also be aesthetically pleasing, provide safety, health, and comfort, and be cost-effective throughout its life cycle [6].

Developing high-performance buildings to include and deal with broader themes/qualities corresponding to the building performance and sustainability requirements requires handling enormous complexity concerning numerous decisions related to the design objectives and criteria that need to be fulfilled [7]. These decisions are made by several design teams and decision-makers [8,9], and, eventually, address countless and highly interconnected design aspects that influence the performance of the final product [10]. The task requires implementing iterative processes that include the stakeholders in the early stages of design [11,12], utilizing the strength of multi- or interdisciplinary team decision-making [13]. The remaining issue, which, to the author’s knowledge, is not yet sufficiently investigated in both the current literature and actual practice, is that:

What happens to the quality of decisions when moving from sole-form design decisions to more collaborative, integrated, and participatory multi- or interdisciplinary design decisions in the (early) design stages?

The gap underlying the above question was noted by Sonnenwald [14] and re-iterated by Idi and Khaidzir [8]. The decision-making essence and its features can clearly alternate as the scale is raised. However, what about the quality of decisions? Is it a question of increasing or decreasing? A tentative answer, consistent with the existing literature, is that participation’s impact on decision quality is dependent on some characteristics of the decision situation [15]. It is determined by where the relevant knowledge or expertise exists, i.e., with the team leaders or their subordinates. It depends on the goals of the potential participants, especially the extent to which the group or team members support the project goals contained in a design problem [16]. Eventually, the synergy in team-based collaborative processes is determined by several factors, including the level of competencies, involvement, and abilities of the subordinates to collaborate effectively in solving design problems.

Today’s typical successful and yet evolving AEC (architecture, engineering, and construction) consultancies (e.g., ARUP, Rambøll, COWI, to mention a few) consist of multiple departments, divisions, teams (such as architecture, water, energy, structure, material, biodiversity, acoustic, HVAC, anthropology, sustainability with the focus on overall life cycle sustainability assessment of building projects via incorporating sophisticated rating/certification systems, etc.), and employees within a range of 50 to 5000 people, often located in multiple branches and different regions. Despite significant recent advances in developing and using digital solutions [17] and services such as BIM (Building Information Modelling) [18], BIM-based tools [19,20,21], and cloud-based collaborative platforms [22,23], this magnitude turns the collaboration and decision-making, especially in the early design stages, into a major challenge. Furthermore, as the standard practice for architectural and engineering firms to secure new building design projects is through participating in open and competitive bidding processes, the time is often very limited. Depending on the scope of the project, there is often a period of 3–6 months (sometimes shorter), in which the design firms must be able to submit their initial proposals, including the design concept and project portfolio, to be allowed to enter the competition. This deadline poses a major problem when making collaborative or group decisions between the multiple divisions and teams mentioned above. Therefore, in reality, early-stage design decisions are often made (or have to be made) by the division/team leaders or more experienced consulting firm staff. Other team members make or influence other decisions, depending on time availability, often with a more in-depth analysis of the particular decision context.

From this perspective, a more in-depth study of the decision-making fundamentals and theories [24,25,26] toward understanding the decision-making styles and logic behind the choices building design stakeholders will help improve decision quality and confidence. It will create more realistic expectations and control over making the most appropriate choices, eventually ensuring more informed decision-making. On the basis of this underlying hypothesis, and as a pivotal step towards conducting more fundamental research in this area in the future, this paper aims to analyze the normative decision theory styles by taking into account the situation and the importance of the design decisions in the (early) design decision-process of sustainable high-performance buildings. The motivation is inspired by the work of Vroom (Victor H. Vroom is a business school professor at Yale University who conducts research on motivation and leadership in organizations. He is the author of nine books and over fifty articles. His 1964 book Work and Motivation is considered a landmark in the field (and is still frequently cited by scholars) [27], where seven different decision styles based on another article by Tannenbaum and Schmidt [28] are addressed and examined. Vroom [27] begins his work by describing a scenario about an actual decision-making challenge in a large company—specializing in ecological control systems—and ends by raising two explicit aspects of solving problems and making decisions, as follows:

-

the first issue involves determining what solution or decision should be adopted, and

-

the second issue revolves around not what should be decided but how and with whom it should be decided.

The current research study (as the first of its kind) is built on the second issue above, believing that deciding how and with whom to make a decision is as important as what solution or decision should be adopted. This is notably critical when the challenges of a problem are of great complexity, uncertainty, and heterogeneity, as the challenge of designing more sustainable buildings is with multiple stakeholders from various disciplines and backgrounds [29]. From this perspective, the following research question (RQ) is posed:

RQ: To what extent and with whom should one participate in decision-making when (early stage) decisions are made relating to the design criteria in the design of sustainable high-performance buildings?

As a contribution to addressing the research question, this paper aims to analyze decision-making via conducting assessment surveys with actual practitioners, creating insights on (a) when and with whom a decision is made and (b) to what extent a decision is made autocratically or participatorily. The remaining part of the article is structured as follows. Section 2 provides the state of the art of decision theory and the model of normative decision-making used in this paper. Section 3 presents a comprehensive overview of the key concepts in designing sustainable high-performance buildings (i.e., the processes, stakeholders, and objectives) and sufficient details on the choices made about their assessment procedure as input within the assessment surveys. The methodology for conducting survey assessments is elaborated in Section 4, and the results are presented in Section 5. The outcome is discussed in Section 6, and finally, Section 7 outlines the conclusion, limitations, and plans for further research work in the future.

2. Decision-Making Theory

The dictionary [30] defines decision theory as “making decisions based on assigning probabilities to various factors and numerical consequences to the outcome”. The theory (through an epistemological interpretation) concerns the considerations underlying a person or agent’s decisions [24,25,26]. It helps understand the logic behind an agent (or person)’s choice on a given occasion, which is entirely determined by their beliefs, desires, or values [31]. The two distinct branches of decision theory are descriptive and normative decision theories [32,33], which have already been used in the highly pragmatic business world. Chandler [34] discusses that descriptive decision theory is concerned with characterizing and explaining regularities in people’s choices. On the other hand, normative decision theory accounts for the choices people ought to make. Therefore, normative models advise decision-makers about how they should make decisions/choices, and descriptive models portray how they make choices [34].

Normative decision theory is concerned with identifying optimal decisions, where, according to MacCrimmon [33], “optimality is often determined by the assumption of an ideal decision-maker who can calculate with perfect accuracy and is, in some sense, perfectly rational”. This feature makes it suitable for the context of the decision-making challenge in the current paper, as described in Section 1. The practical application of this prescriptive approach (on how people should make decisions) is called decision analysis. It aims to find tools, methods, and software (decision support systems) that improve decision quality and confidence [32,33].

2.1. Normative Model of Decision-Making

Fishburn [35] describes normative decision theory as the study of guidelines for right action and the effectiveness of decision procedures. It aims to structure principles of comparative evaluation and decision-making between often competing alternatives. It also addresses the implications of these principles both at the abstract level and by taking into account the decision situation [35]. The fundamentals of the normative decision theory have been presented in Vroom’s work, which anticipates the effectiveness of decision-making procedures [36,37,38] by matching the appropriate decision-making styles with relevant properties of problems. Figure 1 shows the five types of decision-making styles in Vroom’s model (referring to the Vroom–Yetton model in [38]), each distinguished by the degree of participation by the leader: from autocratic decisions on the left, where the leader makes the decisions by themselves, to consultative decisions in the middle, where the leader shares the problems with subordinates but still makes the decisions themselves, to group decisions on the right, where the leader shares the problems with subordinates and then lets the group make the decision.

To identify the process (or processes) that is prescribed for a particular problem or decision and thus implement Vroom’s model, there is a set of seven rules (as shown in

Table 1. Vroom’s seven rules (or situational factors), which are consistent with existing empirical evidence and the consequences of participation, are considered when selecting a decision style (from [39], based on [38]).

Rule No.	Rule Description
1. The Leader Information Rule	If the decision quality is important and the leader does not have enough information or expertise to solve the problem alone, then AI is excluded from the feasible set.
2. The Goal Congruence Rule	If the decision quality is important and the subordinates are unlikely to follow the organization’s goals in solving this problem, then GII is eliminated from the feasible set.
3. The Unstructured Problem Rule	In situations where the quality of the decision is important, the leader does not have the necessary information or expertise to solve the problem alone, and the problem is unstructured, the method for solving the problem should involve interaction among subordinates who are likely to have the relevant information. Accordingly, AI, AII, and CI, which give no interaction among subordinates, are excluded from the feasible set.
4. The Acceptance Rule	If acceptance of the decision by subordinates is important for effective implementation and when it is not reasonably certain that an autocratic decision will be accepted. AI and AII are eliminated from the feasible set.
5. The Conflict Rule	When acceptance of the decision is important, acceptance of an autocratic decision is not sufficiently certain, and agreement among subordinates on possible solutions is likely, the methods used to resolve the problem should allow those who disagree to resolve their differences with full knowledge of the problem. Accordingly, under these conditions, AI, AII, and CI, which do not allow interaction among subordinates and therefore do not provide an opportunity for the conflicting parties to resolve their differences, are eliminated from the group of possible solutions. Their use risks that some subordinates will show less than the required commitment to the final decision.
6. The Fairness Rule	When the quality of the decision is unimportant, but the acceptability of the decision is important and not sufficiently certain in the case of an autocratic decision, the decision process must generate the necessary acceptability. The decision process should allow subordinates to interact and negotiate about resolving differences, with full responsibility for deciding what is fair and equitable. Accordingly, AI, AII, CI, and CII are eliminated from the possible set under these circumstances.
7. The Acceptance Priority Rule	When acceptance is important, an autocratic decision cannot be reached with reasonable certainty, and subordinates are motivated to pursue the organizational goals presented in the problem, methods that provide equal partnership in the decision-making process can generate far greater acceptance without compromising the decision quality. Accordingly, AI, AII, CI, and CII are excluded from the set of possible solutions.

Note: Rules 1–3 were designed to protect the quality or rationality of the decision, whereas Rules 4–7 were designed to protect the acceptance of commitment to the decision.

) that exclude alternatives that compromise either the quality or the acceptability of the decision.

In summary, Vroom’s seven rules (according to [39]) serve to protect the effects of decisions, which can be viewed as a function of three elements:

-

The technical quality or rationality of the decision.

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The acceptability of the decision or the commitment of those responsible for its execution.

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The time required to make the decision.

To facilitate applying the rules from Table 1 in actual decision-making situations, Vroom and Yetton [38] propose the decision-process model flow-chart in Figure 2, which is a list of A-H problem attributes expressed in terms of simple yes–no questions that a decision-maker must first diagnose about the status of that decision.

To use the model, start from the left and work to the right side of the tree and ask yourself questions about each field encountered, which in turn indicates one or more decision styles that might apply to that problem or decision. Ultimately, two pieces of information emerge. The first defines the problem as one of 14 “problem types” highlighted in Figure 2. In contrast, the second represents the set of appropriate decision processes, called the “feasible set”, for that problem type (see

Table 2. Problem types and the feasible set of decision methods in Vroom’s model [38] (the decision models related to the 1–14 problem types are indicated in Figure 2).

Problem Type	Acceptable Methods
1	AI, AII, CI, CII, GI
2	AI, AII, CI, CII, GI
3	GI
4	AI, AII, CI, CII, GI *
5	AI, AII, CI, CII, GI *
6	GI
7	CII
8	CI, CII
9	AII, CI, CII, GI *
10	AII, CI, CII, GI *
11	CII, GI *
12	GI
13	CII
14	CII, GI *

* Within the feasible set only when the answer to question G is yes.

). This “feasible set” consists of the processes that remain after applying the seven rules, each of which eliminates styles that are not considered applicable to certain problems [38].

Evidence for the normative validity of Vroom’s model amid the seven underlying rules in Table 1 can be found in [37]. When the model and its rules are applied and more than one decision style remains, Vroom [27] discusses some ways to choose between them, e.g., the so-called methods of Model A and Model B. Model A assumes that if the alternatives within the feasible set have equal probability of leading to a rational decision that is also accepted by the subordinates, then a choice between these alternatives based on their respective time requirements has a short-term benefit for the decision context. Assuming that more participatory processes require more time, Model A selects the most autocratic process within the feasible set (i.e., the decision styles with the farthest left input in Figure 1).

However, there are often other reasons for decision-making. A leader may want to choose the most participatory alternative that can be employed and still lead to rational and acceptable solutions to problems. Vroom [27] argues that such a stance may be based on humanistic considerations that emphasize the intrinsic value of participation or on pragmatic considerations, such as the benefits of participation in developing subordinates’ technical and managerial skills. A model based on these considerations is referred to as Model B and involves choosing the most participatory process within a feasible set (i.e., the farthest right input decision styles in Figure 1).

3. Design of Sustainable High-Performance Buildings

3.1. Design Process

The design process of sustainable high-performance buildings depends critically on the resources available in a given set of circumstances (at both micro and macro scales) [40]. Even a design solution that is far from perfect can be accepted if resources are utilized. Constructive design solutions emerge by replacing poor solutions with more efficient and effective ones by following patterns/mechanisms in the design process to cope with complexity [41]. In this light, design solutions can become better when (a) more attention and time is spent, (b) more options/solutions are considered and thoroughly evaluated, and (c) positive and negative synergies of decisions are carefully considered [10].

This adaptive nature identifies solutions/concepts and then gradually reshapes them to meet the project’s objectives, criteria, and target values. It emphasizes the heuristic and iterative essence of the design process, which must periodically recharacterize the original design intent to meet project needs. This discussion has formed the basis for the emerging, most recently used iterative–integrative design process versus the traditional linear ones [42]. In the more conventional design processes, the architect and client agree on an overall design concept. The structural, building physics, mechanical, and electrical engineers are then asked to implement the design and suggest appropriate systems [11], while the tendency in more recent designs is to utilize the strength of multidisciplinary design specialists and consultancies who work from the beginning of the design process to optimize the building design, promoting the idea of the architect as teamwork leader instead of the sole form designer, also often referred to the integrated design process (IDP) [12,43,44] and/or holistic building design [10].

The design of sustainable high-performance buildings includes multiple phases (i.e., initial design, design proposal, and detail phases) and stages and involves various stakeholders (see Section 3.3) who influence the design. To fulfill the project requirements, the need to exploit integrated processes, iterate between stages, and involve the design decision-makers is inevitable. This process also requires a more systematic approach with transparency and traceability of decisions and solutions at the early stages of decision-making in the project. Here, the impact of decisions on selecting and pursuing sustainability-focused aspects (i.e., corresponding to the need to find long-term solutions that ensure well-being and minimize the need for natural resources such as land use, biodiversity, water, air, and energy) is significantly high, as illustrated in the MacLeamy graph shown in Figure 3. In contrast, the impact of changes to the building and construction costs is low.

The design phases and stages presented in Figure 3 are according to the Danish Description of Services [46,47], followed by building design practitioners in Denmark and used as a financial and legal framework. As the author of the current paper is a researcher in Denmark, the stages shown in Figure 3 are used as the common foundation and act as a scale for the design stages used and assessed in the current study. Meanwhile, due to the importance of the early design stages, only the stages from the initial design and design proposal phases (i.e., pre-design, concept design, schematic design, outline proposal, and project proposal stages) are used as the basis for the decision stages, and so the survey assessment of the professionals. A short description of the activities related to each stage (according to [46,47]) is presented as follows:

• Pre-design: the principal consultant (lead architect/project manager) consults with the client to establish project goals and requirements.
• Concept design: the initial architectural design is developed, e.g., through an architectural competition for general contract projects or through requests for proposals for design-build projects.
• Schematic design: architectural proposal and possibly other requirements, depending on the RFP.
• Outlined proposal: the design is a substantiated proposal for the completion of the project, including a description and sketches of the design principles and major systems for technical facilities.
• Project proposal: a revision of the approved outline proposal to the extent that all key decisions for the project have been made and are included in the proposal.

3.2. Design Stakeholders

The design and construction of sustainable high-performance buildings are recognized as highly complex, with multiple stakeholders with direct or indirect decision-making related to the various preferences, experiences, and decision-making policy [7]. A typical AEC project involves architects, engineers (e.g., structure, mechanical, electrical, geotechnical, etc.), contractors, and sub-contractors, who work together to meet the client’s and the project’s needs [48]. Over the last decade, due to the crucial trends corresponding to Green and Digital, the twin transitions/transformations of the AEC sector [49], many relatively new design specializations have emerged, among which sustainability engineers, energy and indoor climate engineers, lighting and day-lighting engineers, form-finding and computational designers, various BIM-oriented specialists, etc., have become very popular nowadays. These new emerging design specializations can be broadly categorized within the architectural engineering discipline and are regularly being hired in AEC consultancies, and depending on the design stages, become involved in the decision-making process and so impact design decisions.

As highlighted in the previous section and illustrated in Figure 3, more informed and impactful design decisions can be made by involving stakeholders as early as possible in the design stages. In other words, if a project is well planned, sustainable criteria are set, and design decisions are made early in the design stages, the possibility of reaching a more sustainable final product is increased [16]. Therefore, in this paper, the view of involving as many of the design stakeholders as possible within the early design stages is presumed, in contrast to the more traditional approach in which the stakeholders are mapped in a linear fashion, moving from the initial design to the proposal, and then detailed design phases (see Figure 3).

3.3. Sustainable Design Objectives and Criteria

Sustainability is based on contemporary information and communication systems. Interests repeatedly show the need for a deep understanding of sustainability as a pattern with a set of themes and criteria defined by relevant key performance indicators [50]. In response, there are now a variety of methods for assessing sustainability. In recent years, sustainability ratings and certification systems for buildings have become the most important step in the process of designing sustainable buildings. They have made the sustainable building process more manageable and strive to combine all the necessary work into one framework to ensure that sustainability is addressed at all project stages. They can measure and document sustainability and support integrated design and multi- and inter-disciplinary collaboration [51].

The certification systems have been expanded alongside the environmental requirements, which mainly concern the environmental aspects, with the latest assessment methods attempting to consider and evaluate equally the environment, economy, and social relations [52]. Today, there are many sustainability certifications around the world, with some more common than others, e.g., LEED (Leadership in Energy and Environmental Design) from the United States of America, and BREEAM (Building Research Establishment Environmental Assessment Methodology) from the United Kingdom are among the most well-known certifications worldwide. In addition, the German Sustainable Building Council (DGNB) has recently attracted attention in the EU, including Denmark (DGNB-DK). There are already several published scientific articles and reports that have compared the aforementioned certifications’ pillars and criteria (i.e., LEED, BREEAM, and DGNB), among which the work by Jensen et al. [51] and the very recent work by Ferreira et al. [53] are cited so that they can be read for further information.

Despite the author’s substantial experience in the last decade in both establishing and assessing sustainability criteria and also related rating/certification systems [54,55,56], in this paper, the DGNB sustainability criteria from the German Green Building Council (2020) [57] are used as the basis for the decision context and the survey assessment of professionals in Section 5. The reason is: (a) the author is a researcher in Denmark, and as was mentioned earlier, DGNB has been adopted and is being used in Denmark since 2011, and (b) there is free access to the criteria and their purposes, definitions, and indicators on the DGNB website and manuals, which eventually will be essential for further information. Otherwise, similar studies can be performed with other sustainability design criteria and in different decision contexts.

The primary aim of the DGNB system is to be holistic. The system (as illustrated in Figure 4) includes an assessment of the three classic pillars of sustainability, social (SOC), economic (ECO), and environment (ENV), and they are weighted equally (with 22.5% of the overall score for each). This makes DGNB unique compared to the other available certification systems that focus more on the environmental or social aspects of sustainability [58]. Besides the three central sustainable pillars (or areas), the DGNB system also evaluates the technical (TEC), process (PRO), and site (SITE) qualities (with 15% of the overall score for TEC, 12.5% for PRO, and 5% remaining for SITE qualities). These qualities contribute to interdisciplinarity across the three classic pillars, and they all together (referring to the six overall DGNB qualities, i.e., ENV, ECO, SOC, TEC, PRO, and SITE) form the backbone of the total 38 criteria of the DGNB assessment for new construction buildings. The criteria differ based on their importance versus each other and the context in which they are being assessed (refer to specific building types, e.g., residential, hotel, office, etc.) [57].

DGNB is committed to laying the groundwork for certification early in the design process for the same reasons mentioned in connection with the importance of decision-making in Section 3.1 (see Figure 3). Therefore, a joint application can be submitted for both the pre-certificate and the certificate, based on which an agreement with a fee schedule is established. In doing so, the selected criteria for the final review can also be used at the pre-certification stage, based on which the DGNB will make its final assessment for the certificate.

4. Methodology

The outcome of the current study culminates based on two rounds of assessment surveys through conducting interviews with practitioners and professionals in Northern Europe on:

(a)

when and with whom a decision is made in the design of sustainable high-performance buildings (refer to the round one assessment survey), and

(b)

to what extent a decision can be made autocratically or participatorily in the design of sustainable high-performance buildings (refer to the round two assessment survey).

4.1. Study Design and Respondents

For the round one survey, the data were collected through semi-structured interviews with 23 professionals for the initial screening. For the reasons discussed in Section 3.3, DGNB sustainability criteria (see Figure 4) are used as the basis for the assessment. Therefore, the main inclusion criteria for screening the participants contacted were set to have working experience with DGNB-certified construction projects and their professional background related to the Danish construction industry. In order to obtain a broad and diverse range of responses, the pool of professionals interviewed included different age groups, genders, educational backgrounds, graduation periods, company sizes, working positions, sectors (public, private), experience levels with DGNB (newly introduced and veterans with many years of DGNB experience). Participants held the following positions: sustainability consultant, sustainability specialist, director and technical business unit manager, department manager, DGNB consultant, technical director, technical consultant, bid manager, sustainability manager, project manager, project associate, partner, executive director, member of the construction and innovation department. All interviews were conducted in Denmark from June 2021 to March 2022, either in physical presence or via Skype, and each lasted approximately 35–45 min.

For the round two survey, a number of professionals were contacted concerning their relationship to the overall design decision process. To ensure that the assessment was as inclusive as possible, efforts were put in place to identify professionals with a significant amount of experience as design project managers in various building projects and with different scales (occasionally referred to as design facilitators) and with a sufficient overview of key design concepts, sustainability objectives, and experienced in terms of working with the related stakeholders from multiple departments, divisions, and teams. With this in mind, three architects and four engineers were interviewed, who currently work as project leaders with backgrounds in either engineering or architecture in Northern Europe with over 25–35 years of experience within the field and who are therefore considered experts. All the interviews were conducted from February 2022 to August 2022 in their physical presence and lasted approximately 2.5–3 h each.

4.2. Analytical Strategy

For the round one survey, a five-point Likert scale was used to score the outcome, in which: 1 = the criterion has a very low relevancy, 2 = the criterion has low relevancy, 3 = the criterion has medium relevancy, 4 = the criterion has high relevancy, and 5 = the criterion has very high relevancy. The survey consists of assessing the relevancy degree of the DGNB criteria with the decision-stages and decision-makers by estimating their mean score (MS) obtained from the assessment survey on three levels, including (a) individual DGNB criteria, (b) individual DGNB qualities (i.e., ENV, ECO, SOC, TEC, PRO, and SITE), and (c) their total MS obtained. The cumulative MS is estimated as the scoring of the relevancy degree that ranks decision stages and decision-makers by the sum of all points scored for each DGNB criterion or quality. In this regard, a bigger cumulative MS indicates a higher degree of relevancy and vice versa.

For the round two survey, the mean participation level (MPL) from Vroom and Yetton [38] is used to assess the outcome. The authors [38] discuss that the five normative decision-making styles presented in Figure 1 can be ranked on a one-dimensional scale representing the extent of opportunities for subordinates to engage in decision-making. The numerical values assigned to these processes are as follows: AI = 0, AII = 1, CI = 5, CII = 8, and GI = 10. By aggregating the scale values for an individual, the MPL (0 to 10) is calculated to reflect the tendency toward autocracy or participation in decision-making. Additionally, the standard deviation (SD) is also estimated for each item, reflecting how dispersed the values are concerning the MPL. A bigger SD indicates the vote values are more spread out from the mean, demonstrating the interviewees’ different opinions/votes on the decision styles selected.

5. Results

5.1. Round One Survey: Assessment of the Design Process, Stakeholders, and Sustainability Criteria

To engage and better understand the decision-making structure and background presented in Section 3, including the design process, stakeholders, and sustainability criteria, this section aims to assess their correlations by conducting an assessment survey with professionals. In doing so, the initial screening of the relevancy degree of each sustainability criterion with the decision stages (refer to the design process stages) and decision-makers (refer to the key design stakeholders) is carried out.

DGNB has been certified in Denmark since 2011. Therefore, there is not a large part of the industry that has qualified experience with DGNB certification. Due to the small number of professionals and this relatively new topic in the Danish context, participants were first asked to give their views on the application and implementation of DGNB certification in Denmark. In doing so, the interviews began with: (i) what is your professional background and connection to DGNB certification? and then, the list of DGNB criteria was presented to the participants, followed by two questions: (ii) which decision stage (refer to the design stages discussed in Section 3.1) can/should each listed DGNB criterion be introduced within the decision-making process, and (iii) which decision-maker (refer to the design stakeholders discussed in Section 3.2) can/should be involved within the decision-making process associated to each listed DGNB criterion.

Table 3. The alternatives used in the survey assessments.

Decision-Stages	Decision-Makers
(a) Pre-design	(a) Architect(s) (incl. architect designer, parametric modeling and form finding designer, landscape designer, anthropologist, etc.)
(b) Concept design	(b) Architect engineer(s) (incl. energy, indoor climate, air quality, material, biodiversity, acoustic, LCA, etc.)
(c) Schematic design	(c) Engineer(s) (structure)
(d) Outlined proposal	(d) Engineer(s) (incl. mechanical, electrical, installations, HVAC, etc.)
(e) Project proposal	(e) Contractor(s)
	(f) Owner (and client)
	(g) Occupant(s)

presents the alternatives.

During the semi-structured interviews, the participants finished screening the criteria using the five-point Likert scale, following the instructions in Section 4.2.

Table 4. The cumulative bar charts present the assessment survey outcome related to the relevancy degree of the DGNB qualities and criteria with the design decision stages and the design decision-makers.

Design Decision-Stage Relevancy	Design Decision-Maker Relevancy
(a) - Cumulative MS for the individual DGNB criteria within each quality -
(b) - Cumulative MS for the individual DGNB qualities -
(c) - Total MS for all DGNB qualities -

demonstrates the assessment outcomes, including the relevancy degree of the DGNB criteria with the decision stages and decision-makers. The list of criteria and their corresponding rounded mean vote values of the 23 participants are provided in Appendix A.

From the comparisons shown in the above table, several results and insights can be produced. Depending on the individual view of each criterion and its associated DGNB qualities (refer to ENV, ECO, SOC, TEC, PRO, and SITE), one can relatively identify what, when, and with whom decisions can be made. The following relevant key findings are highlighted:

• Reading from part “a” in Table 4: The DGNB criteria with the highest weighting factor, including ENV1, ENV2, ECO1, SOC1, SOC2, SOC8, TEC1, TEC3, TEC6, PRO2, PRO3, SITE4 have, individually, the strongest relevancy degree to the pre-design stage, as well as the tendency toward knowledge sharing, which often requires more interaction with the listed stakeholders.
• Reading from part “b” in Table 4: Architects and architectural engineering teams have the greatest relevancy degree associated with the criteria in the ENV, SOC, and SITE qualities. Occupant relevancy is strongest concerning the criteria in SOC quality, whereas owners have a significant degree of decision-making relevancy with the criteria in the ECO, ENV, and SITE qualities.
• Reading from part “c” in Table 4: It is evident that almost all the decision stages and decision-makers are relatively relevant and must be involved when necessary. The rank order of the decision stages from highly relevant to less includes (1) pre-design, (2) concept design, (3) schematic design, (4) outlined proposal, and (5) project proposal stages, which is in every detail identical to that presented in Figure 3, i.e., the MacLeamy graph, reiterating the relevancy and importance of decision-making in the early design stages. In addition, architecture and architectural engineering teams, besides the owner (and client), have received the strongest relevancy degree. In contrast, engineering teams and contractors are in second place, and finally, occupants are at the end.

5.2. Round Two Survey: Empirical Application of the Normative Decision-Making Model in the (Early) Design Decision Process of Sustainable High-Performance Buildings

To apply the normative model presented in Section 2.1, the initial plan at this stage of the research work was to investigate a real building case study with relevant stakeholders and actual decisions. However, collecting information in that regard was very challenging, if not impossible, due to (a) confidentiality issues and (b) access to the entire project team. Therefore, it was decided to conduct an assessment survey through semi-structured interviews instead, following the instructions in Section 4.2.

The participants were aware that the current research study intended to examine the decision-making characteristics and structures in the design of sustainable buildings. Prior to the interviews, they were provided with a summary of the normative decision-making model shown in Figure 1 and Figure 2 and the seven rules presented in Table 1. There was a brief introduction to the method at the time of the interviews. Then, together with the lead author, the participants finished the screening of the DGNB criteria by answering the following question: which decision-making styles in Vroom’s model based on normative decision theory (as shown in Figure 1) best fit the decision-making related to each DGNB sustainability criterion in the (early) design stage of building projects? The following cases are two examples of the application of the model (see the model in Figure 2) corresponding to decision-making characteristics related to SOC2 and PRO3 criteria:

- Example 1

Analysis: SOC2 (Indoor air quality) criterion

Questions: A (quality?) =       yes

B (leaders info?) =           no

C (subordinates info?) =         yes

D (structured?) =             no

E (acceptance?) =            yes

F (prior probability of acceptance?) =    no

G (trust?) =              no

Problem type (see Table 2):       13

Feasible set (see Table 2):        CII

Rule violations (see Table 1):       AI violates rules 1, 4, and 7

                   AII violates rules 3, 4, and 7

                   CI violates rules 3 and 7

                   GI violates rule 2

- Example 2

Analysis: PRO3 (Documentation for sustainable management) criterion

Questions: A (quality?) =          yes

B (leaders info?) =           yes

C (subordinates info?) =         yes

D (structured?) =             yes

E (acceptance?) =             yes

Problem type (see Table 2):       5

Feasible set (see Table 2):          AI, AII, CI, CII, GI

Rule violations (see Table 1):       none

The list of criteria and their corresponding frequency of choice values are provided in Appendix B. Figure 5 illustrates the mean participation level (MPL) required for the decision-making related to the DGNB qualities and criteria as the outcome of assessment surveys conducted with the seven experienced professionals.

Similar to the previous section, the assessment survey above can produce several results and insights, and depending on the individual view of each criterion and its associated qualities and their ranking of Vroom’s decision styles, one can reasonably identify how decision-making can be made. The following relevant key findings are highlighted:

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The decision-making features related to the criteria in SOC (with MPL = 7.3 and SD = 0.55) and PRO (with MPL = 3.52 and SD = 1.05) qualities have the strongest tendency toward participation and autocracy, respectively. That denotes the decision-making tendency associated with the SOC criteria (e.g., SOC6 criterion with the most significant trend toward participation) is more towards knowledge integration and knowledge sharing, which often requires more interaction and dialog and is more time consuming, while the tendency associated with the PRO criteria (e.g., PRO5 criterion with the most significant trend toward autocracy) is for design/team leaders to make the decisions. In the latter case, leaders often obtain the necessary information from their subordinates (or team/group members) and then decide how to proceed with the situation. Leaders may discuss with their subordinates the purpose of the questions or provide information about the decision situation they are dealing with. Thus, the subordinates’ contribution is a reaction to providing certain information. As a result, subordinates do not play a role in defining the situation or problem, nor in developing or considering alternative solutions.

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The overall rankings of the five processes for all criteria from most to least frequently used are CI (with 122 votes, MPL = 3.21, SD = 0.93), CII (with 104 votes, MPL = 2.73, SD = 1.26), AII (with 91 votes, MPL = 2.39, SD = 1.58), GII (with 72 votes, MPL = 1.89, SD = 1.44), and AI (with 67 votes, MPL = 1.76, SD = 1.71). This indicates that the general decision-making style, with an overall MPL = 5.11 and SD = 1.78, tends toward CI, with team leaders discussing the problem with the affected subordinates individually, soliciting their responses and recommendations without bringing them together as a group, and then making the decision. Given this background, the decision may or may not reflect the influence of subordinates.

6. Discussion

Let us first review what is at stake regarding the extent to which and how others should be involved in problem-solving and decision-making. The primary crucial issue is the decision quality. Before everything else, decisions need to be rational, well-reasoned, analytically sound, and consistent with the aims to be achieved. In addition, with available information about the consequences of alternative means of achieving those aims. This is a very challenging task in building design as a complex, multidisciplinary activity that must make difficult compromises to balance competing multi-objectives and parameters [48]. In this framework, IDP approaches (as discussed in Section 3.1) are required to include integrated processes with iteration between stages and early involvement of the design decision-makers to improve collaboration and knowledge sharing, which ultimately can cause more effective design decisions [40,42]. However, based on [59,60], the current IDP guidance only addresses the why and the what, not the how of using the guidance. Landgren et al. [45] argue that the existing guides all describe the integration regarding desired outcomes. However, they do not describe how to carry out the process, ensure integration, manage communication, and determine what interactions are essential for stakeholders [45]. The authors suggest that this lack of focus might be due to the need to leave room for interpretation, as there are different contexts, types of knowledge, and reasons for using IDPs. Perhaps it is enough to note that collaborative-based decision-making processes and guides poorly describe the collaboration processes. Ultimately, the authors [45] leave the topic of knowledge incorporation in IDPs as an open research question.

The results of the assessment surveys in this article, in line with the research question and objectives projected in Section 1 and on addressing when, with whom, and to what extent a decision can be made autocratically or participatorily in the (early) design of sustainable high-performance buildings, provide a sound basis for answering some of the issues raised by Landgren et al. [45]. For example, the assessment outcome related to the decision-making aspects of the DGNB criteria in the Economy (ECO) quality illustrated in Figure 6, emphasizes: (a) the need to introduce the criteria within the process as early as possible, i.e., within the pre-design stage (with MS = 4.76 out of 5), (b) the need to have the owner (and client), architecture, and architectural engineering team involved in the decision-making process (with MS = 4.56, 3.96, and 3.73 out of 5); and (c) due to the former, the general decision-making style tends toward AII and CI (with MPL = 4.23 out of 10), so the team/division leaders are recommended to discuss the problem with the subordinates concerned (referring to the need for knowledge sharing), yet, without the need of bringing them together as a group, to make a decision. In doing so, using the right degree of subordinate participation will improve the quality of decisions and the extent to which subordinates accept and are committed to the decisions, i.e., show buy-in.

Such findings are a starting point for developing a normative model to help the project/division/team leaders choose the style that best fits a given decision situation. Likewise, the outcome can be extended to crucially help AEC consultancies to develop and evolve into more adequate and sophisticated management and organizational processes in dealing with the extensive list of sustainable design objectives and criteria, ensuring a systematic approach for (a) their inclusion and assessment within the design processes, (b) better alignment and prioritization, and therefore, better time management for assessing and improving them within the early design as well as the entire design process stages, and (c) vital involvement of the required design stakeholders in addressing them (that cause sorting out the need and tendency toward participation and autocracy decision styles among the team leaders and their subordinates), all of which can eventually lead toward more informed decision-making [61] in the (earlier) design stages.

Concerning the discussion above, however, one might argue that it is premature for (especially experienced) design team leaders (or key stakeholders) in (often well-established) consultancies to begin to rely on the outcome of similar research work in their decision-making (as an attempt to be prescriptive towards decision-making), given that the decision-making analysis performed is to some extent subjective in nature, and from one person/team/division to another might be different. To answer, it should be highlighted that:

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Existing knowledge is too limited, and the problems are too complex to justify explicit normative models (such as Vroom’s decision-making styles in Figure 1) to solve decision-making issues in designing sustainable, high-performance buildings. Common questions may arise: Are the results in their current form an adequate guide to practice? Would those involved in planning make fewer mistakes in their decision-making choices if the results guided them? It would not be entirely honest to claim that such questions’ answers are known. But, as emphasized by Vroom and Yetton [38], the reader should be prepared that the issues surrounding the application and assessment of the normative or prescriptive model results are complex, and the methodology for answering questions of validity through empirical research has not yet been developed within the scope of this work.

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As articulated in Section 1, current research aims to improve the early design decision stages, where decision-making is often more challenging. Therefore, the goal is to support the decision-making process, not to make the decision itself. In other words, the vision is not about perfection but an improvement in present practices. Any actions, even with minor impacts on the early stage of decision-making processes, might cause significant consequences later and thus be worth trying. On promoting and applying normative decision models, as was performed in this study, Vroom [27] argues that:

“…Moving from the autocratic to highly participative styles increases the potential value of the group or team to the organization in three ways: (1) It develops the knowledge and competence of individual members by providing them with opportunities to work through problems and decisions typically occurring at higher organizational levels. (2) It increases teamwork and collaboration by providing opportunities to solve problems as part of a team. (3) It increases identification with organizational goals by giving people “a voice” in making significant decisions in their organizations…”

There was a general agreement among the interviewees that the research area and the holistic view of the problem are attractive, that is, working with all the criteria at once. Nevertheless, it was still challenging for some participants to work and vote on all criteria. The interviewees mentioned various project stakeholders with whom knowledge could be shared. Some participants discussed whether the outcome could further be developed and expanded within the AEC industry, e.g., in the form of decision-support tools, ensuring inclusion and assessment of sustainability criteria. This was raised in connection with a popular issue against applying sustainability certification tools as documentation tools rather than practical design decision tools for driving sustainability and innovation within building projects from early stages throughout the design and construction processes.

The assessment surveys conducted with the seven experienced professionals in Section 5.2 were somewhat challenging because the participants were exposed to the exercise for the first time and were unfamiliar with the methods and decision-making models and the time limit for finishing the assessment. Interviewees, in particular, suggested performing similar work in the form of a focus group study by conducting workshops with multiple participants instead. However, finding and gathering such a professional community will be a significant challenge. This is a limitation in the current study, and it remains a potential path for further research work in the future.

7. Conclusions and Further Research Work

This study was built on the belief that deciding how and with whom to make a decision is as vital as what solution or decision should be adopted. The research question was: To what extent and with whom should one participate in decision-making when making decisions related to sustainable high-performance buildings’ design criteria? The assessments showed that the early design stages, i.e., pre-design and concept design, have the highest importance and, in every detail, are identical to the MacLeamy graph in Figure 3. Architects and architectural engineering teams have the greatest relevancy degree associated with the criteria in the ENV, SOC, and SITE qualities; occupants with the criteria in the SOC quality; and owners with the criteria in the ECO, ENV, and SITE qualities. Furthermore, the generally preferred decision-making style tends toward CI, whereby team leaders individually discuss the problem and the situation with the subordinates, solicit their responses and recommendations without bringing them together as a group, and decide afterward.

Decision-making is the process of selecting between alternative courses of action, including inaction. In contrast, design management can be said to be decision-making in which many managerial decisions can fail. Therefore, increasing effectiveness in decision-making is an essential part of improving the end product to put the entire system on a sustainable path. Overall, the results of this study can be used as a decision-support and decision-helper system for AEC consultancies and stakeholders to deal and work with sustainability and performance in its whole sense and associated decision-making characteristics. It helps involve the right decision-makers at the right time and with suitable decision-making styles, where the design leaders are encouraged to make the decisions themselves, and/or through consultative decisions, and/or group decisions. According to the normative decision theory used in this study, the right level of employee involvement improves the quality of decisions and the extent to which employees accept and feel committed to the decisions, i.e., their buy-in. Successful implementation of this entails appropriate decision-making structures being in place besides decision training.

Siebert et al. [62] discuss that decision training is not only theoretical but also practically relevant and that positive decision training affects proactive cognitive skills and decision satisfaction. Thus, decision-makers can benefit from decision training. From this perspective, the results of this paper and similar studies can help AEC actors familiarize themselves with decision-making styles and their importance while describing and clarifying the roles of the leaders and team members and whether and when to share their decision-making power. This could result in improving the decision quality and making most beneficial choices in the context of the decisions they get involved. With its mighty ability to formalize problems faced by sustainability requirements and real challenges in the industry, decision analysis and training promise to become a major inspiration for studies in the design of building projects for a sustainable tomorrow.

Limitations and Future Work

This study is viewed as an enabling mechanism (a conceptual and/or positioning paper) for practitioners and researchers to identify the importance of the decision-making domain in addressing highly complex challenges of sustainability in the design of sustainable buildings, e.g., related to its multiple themes and criteria, required standards, regulations, needs, actors, etc. In line with the limitations of the current study, there are many feasible perspectives yet to be explored, which are briefly discussed in the following:

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The surveys conducted were very challenging because of the need to consider all sustainability criteria at once and to find experts who are knowledgeable about all criteria and willing to invest time in the surveys. This is an obvious limitation of the current study, as only a limited number of interviews were conducted. Similar work can be completed with more participants focusing on specific sustainability qualities/criteria/indicators and associated decision stages. Similarly, further studies can be conducted with a more in-depth analysis of decision makers, e.g., focusing individually on multiple design professionals in architecture and civil engineering, owners and developers, contractors, subcontractors, and suppliers (which was not the case in the current study).

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The present study avoids giving a specific decision-making situation or example of the participants and professionals interviewed in order to ensure the objectivity of the results. However, similar research can be conducted to analyze actual design decisions in actual design projects with actual project participants. This will require a great deal of passion, time, and resources, as it will be challenging to collect data from multiple stakeholders, with limited time and multiple levels of confidentiality in data collection.

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This paper examined design stakeholders based on their role, expertise, and involvement in the design process; however, from the perspective of normative decision theory, similar research can be implemented with a focus on the descriptive types of decision-makers, such as being a brand-centric decision-maker, or multifocal decision-maker, aggregator, charismatic, skeptic, follower, etc., and how these features can influence design decisions towards improving the decision qualities and effectiveness. Likewise, further work can be completed related to behavioral decision-making [32,63] by studying the psychological underpinnings of human judgment, decision-making, and behavior, and how eventually people (in this case, design stakeholders) make decisions. That could also be extended towards further study of decision models from other views, such as rational, bounded rationality, intuitive, or creative decision-making.

In the end, I present a list of potential research questions that can be tackled in the future that are relevant to the context of this paper on the decision-making that takes place in the sustainable design of buildings, or neighborhoods, or cities, and the built environment, as follows:

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What does informed decision-making mean?

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Who is an appropriate decision maker?

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How can a decision be made quickly and with greater accuracy?

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Can decision-making be simplified?

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Do stakeholders who have more information make better decisions?

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Does the way the information is presented change the decision impact?

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What is the best way to structure decision-making?

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Does design context affect decision-making in terms of design and performance variables?

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Does the effectiveness of information in decision-making differ by project context?