Perceptions of Iraqi Building Specialists to Adopt TQM in P&MC and PPC Technology
Bibliographic record
Abstract
Total Quality Management (TQM) and innovative technologies like prefabricated and modular construction (P&MC), especially prestressed precast concrete, have been difficult to adopt in Iraq's construction sector (ICS).These practices have been slow to adopt due to limited digital infrastructure, organisational change resistance, skilled labour shortages, and weak regulatory enforcement.This study examines TQM integration in Iraqi P&MC practices, identifying enablers and barriers with expert input.The study was done to identify the relevant variables in P&MC evolution, the causes driving total quality management (TQM), and the critical problems of P&MC growth among Iraqi construction professionals, particularly regarding PPC technology.A primary cross-sectional quantitative study utilising online survey questionnaires (OSQs) is conducted.The SPSS analysis results indicated a statistically significant link between TQM and its influence on improving the productivity, efficiency, resilience, competency, and quality of the Integrated Control System (ICS).Consequently, the prospects for embracing innovative P&MC developments and viable technological PPC solutions are substantial.The poll highlighted elevated satisfaction levels with TQM, P&MC, and PPC's roles in providing swift accommodation options in response to significant population increase across developed, emerging, and undeveloped countries.The study offered practical implications to assist Iraqi construction consultants, project managers, and both local and international construction stakeholders in transforming damaged infrastructure.The paper critically delineates several significant impediments to TQM implementation and provides corresponding practical solutions.A comprehensive conceptual framework is developed, incorporating actionable plans to enhance and expedite the acceptance and advancement of P&MC and PPC technologies.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".