Construction stakeholders’ perceived benefits and barriers for environment-friendly modular construction in a hospitality centric environment
Bibliographic record
Abstract
Modular construction techniques can not only significantly contribute to improved project cost, schedule, and quality performance, but also sustainability by reducing site disruption and waste generated, creating better relocatability and reusability. However, there are still difficulties in developing and implementing modularization in a hospitality centric environment. Thus, the primary goal of this research is to identify the opportunities and challenges of implementing sustainable modular construction techniques in a hospitality-centric environment. In this study, the approach includes the formulation of a survey, which was distributed to 600 industry professionals in Las Vegas and completed by 63 industry professionals, followed by three personal interviews. The results showed that: 1) 85% percent of survey participants expected an improvement in schedule, and 65% of that elected to use a form of modularization actually experienced an improved schedule; 2) 62% of the participants claimed that they would keep using modular methods in the next 12 months, whereas 44% of the participants claimed they would increase their use of modularization in the next five years; 3) two of the top five expected benefits achieved included less site disruption (noise/traffic and dust) and reduced waste, which contribute towards sustainable construction; 4) transportation/logistics was selected by industry professionals as a key barrier in the implementation of modular construction; 5) to implement more sustainable construction, practitioners require additional research to improve and overcome the key barrier of transportation/logistics; 6) if construction professionals gain more modular project experience, their perceived benefits and barriers could increase and decrease, respectively. The results from this research provide valuable insights for implementing sustainable modular methods in hospitality-centric environments.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".