Determinants of Corporate Sustainability in the Malaysian Construction Industry
Bibliographic record
Abstract
Corporate sustainability is a key concern for corporation. This research intends to evaluate: (1) the influences of training and development and the components of human governance (i.e., transformational leadership, integrity and collectivism) on the corporate sustainability; (2) the impact of the components of human governance on training and development; and (3) the role of training and development in mediating the relationship between the components of human governance and corporate sustainability. Through an online questionnaire survey, 283 responses were collected from the Malaysia construction industry by using non-probability sampling technique. Statistical inferential analyses were carried out by utilising both SPSS Version 25.0 and SmartPLS 3.0. The results represented a significant positive relationship between the components of human governance, training and development, and corporate sustainability. This research also found that only transformational leadership and integrity (but not collectivism) have positive relationship on training and development. The research findings likewise evinced that training and development partially mediates the relationship between the components of human governance (i.e., transformational leadership and integrity but not collectivism) and corporate sustainability. This research contributes an unabridged theoretical perspective on corporate sustainability by providing a deeper understanding of how training and development and the components of human governance determine corporate sustainability as well as the relationships between transformational leadership, integrity and collectivism with corporate sustainability through the mediating role of training and development. Lastly, this research also promotes a better system and policies for organisations to achieve their goals of corporate sustainability.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".