A choice model for mass customisation of lower-cost and higher-performance housing in sustainable development /
Bibliographic record
Abstract
Market demand for housing changes over time, in response to the wants and needs of both individuals and society. Changes in socio-demographics highlight the emergence of non-traditional households in Canada and influence the configuration of a house (or product) which meets buyers' individual requirements. In turn, this affects the design approach (or process). At the same time, society today requires sustainability in housing development, since building a house consumes large amounts of energy during construction and after occupancy. Technology that improves the cost and performance of housing has advanced over time. Although some innovative design and construction systems (or approaches) that attempt to meet societal and individual demands for housing are available in today's market, homebuilders tend not to apply unfamiliar approaches to their housing developments, since their business operation is often based on convention. Another reason, which inhibits a builder's adoption of new housing technology, is the extra cost required for seeking and analysing information. Thus, the homebuilders' decision-making processes for the adoption of 'familiar' and 'unfamiliar' design and construction systems (or housing systems) which affect the configuration of housing need to be well programmed. Accordingly, this study, composed of four parts, focuses initially on identifying housing market trends and issues in Quebec, as well as introducing the new concept of mass customisation that encourages homebuilders to standardise parts of a house---i.e. the creation of mass custom homes. Then, in consideration of this new concept, as well as a value analysis approach that helps facilitate homebuilders' buying decisions, it proposes a choice model for the design and construction approaches to the delivery of 'lower-cost and higher-performance' housing. Thirdly, to assess its practicality, the proposed decision-making model is demonstrated in collaboration with a selected homebuilder in Quebec. Finally, the results of this study are discussed in depth in order to identify future research opportunities. In view of the demonstration project conducted in this study, the author concluded that the proposed 'choice model' could function effectively as a practical decision-making support tool (or system) that helps open the door for homebuilders to generate and select alternatives that aid them to produce lower-cost and higher-performance housing. As a consequence of programming the homebuilders' buying decision-making process, the goal identification uncertainty and goal/purchase matching uncertainty, which often hinder their adoption of unfamiliar, innovative housing systems, could be reduced, or eliminated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.046 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".