Application of Motivation in Nigeria Construction Industry: Factor Analysis Approach
Why this work is in the frame
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Bibliographic record
Abstract
Motivation application by industry players is expedient for effective workforce towards meeting organisation goal. This study identified motivation variables in accordance with Herzberg theory. This was used to survey factors that influence supervisors’ productivity as well as determining its application by contractors in Nigeria construction firms. Quantitative research design approach was employed with same questionnaire to supervisors and contractors. 174 questionnaires were administered to supervisors and 105 was filled and returned which constitute 60% success rate. Moreover, 16 questionnaires were administered to contractors and 12 was filled and returned which constitute 75% success rate. Analysis was done by descriptive statistics and Exploratory Factor Analysis (EFA). The outcome reveals that supervisors are mostly motivated by job security with mean score of 4.11 and standard deviation of .95 and least motivated by overtime with mean value of 2.82 and standard deviation of 1.14. Moreover, the most potent factor influencing their productivity is financial reward. However, the analysis of contractors’ application of motivation reveals that they operate non financial reward. The paper recommends relating motivation application to workers needs as a way of enhancing productivity in the sector. Furthermore, enactment of employment protection legislations for job security should be enhanced to guide against arbitrary dismissal or retrenchment in the sector.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it