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Record W3031985534 · doi:10.71781/3017

Limits and opportunities of integrated design in sustainable buildings : the need for a more comprehensive project process

2019· dissertation· en· W3031985534 on OpenAlexaboutno aff
Ricardo Leoto

Bibliographic record

VenueOpen MIND · 2019
Typedissertation
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsProcess (computing)EngineeringDesign processArchitectural engineeringSystems engineeringConstruction engineeringProcess managementComputer scienceWork in processOperations management

Abstract

fetched live from OpenAlex

The quest to reduce national and global environmental impacts has had a significant impact on the construction industry. In most developed countries, the construction sector is responsible for 35% of waste generation, 32% of energy consumption, and 19% of greenhouse gas (GHG) emissions. Both theory and practice show that the traditional silo-type, linear, and fragmented design process is a significant barrier to innovation and the implementation of better practices in the built environment. Integrated Design (ID) is increasingly seen in Canada and abroad as a potential solution to the lack of collaboration and innovation. Contrary to the traditional design process, ID allows all participants to work together from the beginning of the project, making decisions collectively and integrating otherwise fragmented products and processes. Although ID’s potential is theoretically well-founded, there is little empirical evidence of its effectiveness. The objective of this dissertation is to examine – from both theoretical and empirical vantage points – the scope, strengths, limitations, and critical success factors of Integrated Design (ID) in creating sustainable buildings. The research is based on three case studies of recent building projects in Montreal that implemented Integrated Design processes. The analysis of over 350 architectural plans, press releases and documents produced during construction and operation phases, life cycle analyses, and 28 in-depth interviews allowed us to understand the processes involved, the outcomes obtained, and the stakeholders’ interest and expectations regarding ID. Findings reveal that ID enhanced collaboration and innovation, and helped to reduce buildings’ impacts when compared to the traditional processes. But ID failed to achieve its full potential. It did not completely reduce fragmentation between stakeholders and project phases. This research identified that a “wall” between design, construction and operation phases still exists in ID. As it is applied today, ID continues to underestimate the value of effective performance measurements, rigorous project feedback, and systematic post-occupation evaluations. Identifying the gaps between expectations and effective practice, this dissertation reveals areas where improvements are still needed in the building industry. The study suggests, for instance, that project managers and the design team can (and should) assume new roles, liabilities and responsibilities for project outputs. Effective carbon reductions will require that stakeholders develop deeper knowledge of life-cycle assessment and energy simulation tools. New contractual arrangements between stakeholders will also be needed to favour sustained stakeholder commitment to achieve positive outcomes during the entire project life cycle. From a theoretical point of view, the results demonstrate the relevance and usefulness of ID, but also identify its limits and the conditions that allow for the creation of value for all stakeholders and improvements in buildings. The gaps between theory and practice found here reveal the urgent need to change construction industry regulation (such as professional liability, traditional price-driven - lowest bidding - selection procedures, labeling building systems, building codes, standards, and certifications) in order to reduce buildings’ impacts and slow climate change. From a practical point of view, the results highlight ways in which stakeholders in the construction industry can improve interactions among themselves to reduce buildings’ impacts on the environment. All of this can help – and is needed to – create buildings that are more appropriate for today’s society and future generations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.663
Threshold uncertainty score0.948

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.070
GPT teacher head0.333
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2019
Admission routes1
Has abstractyes

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