A Structural Equation Model of Transformational Leadership for Industrial in Thailand
Bibliographic record
Abstract
This study attempted to investigate and search for the appropriate structure model of leadership in industrial organization of Thailand by comparison between leadership of two industry groups. The study relied on the data collected from 338 managers in Group awarded TQA / TQC (Thailand Quality Award / Thailand Quality Class) and Survival industries group according to the classification of the NESDB (Office of the National Economics and Social Development Board). A questionnaire 5 scale was used to collect the data which was analyzed using AMOS program v.18.0, the total response rate is 97.04 %. The study revealed that there is significant different of leadership between groups. Furthermore, the results light out that the transformational leadership is positively influenced with organization performance especially finance area. In the same line, transformational leadership is found to be not only positively effected with organization commitment but also as stronger effect on empowerment factor. The finding also shows the indirect effect between transformational leadership and organization performance via mediating factors. With believing of different leadership level and its effect, future study can be conducted in different research context. This research has figured out the weakness of empirical study in organization management literatures by connecting the leadership behavior, empowerment, and how they are associated to employee commitment to increase organization performance. In the same way, it has provided a guideline for the public sectors in general and particularly in industrial context on how to successfully implement change phenomena as well as how to get effective and efficient leadership with change management.
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 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".