Development of Motivational Strategies to Enhance Productivity in Small and Medium Scale Construction Firms in Ghana
Bibliographic record
Abstract
The study sought to recommends and quantifies the effect of the effective motivational strategies on the productivity of small and medium scale construction firms in Ghana. Also to develop a framework for motivating employee of small and medium construction firms. Data collection was through well structured questionnaire administered to 164 respondents selected through simple random and systematic sampling techniques. The methods of analysis used were descriptive statistics and production function analysis using the Ordinary Least Square (OLS) criterion to estimate the parameters of the production function. The result showed that, majority of the respondents, 21% said job security was the most important driving force in their life so long as job is concern. Besides, it was realised that, an increase in the level of some motivational strategies: Job security, Opportunity for further studies, Employers? good relationship with employees, Involving employees in decision making and Employers? recognition of employees will improve productivity by 0.0255, 0.0342, 0.073, 0.067 and 0.036 respectively. A model for motivating employees was also developed base on the results. Workers of all organisations need to be motivated to facilitate their input towards the attainment of organisational goals. Construction workers like all other worker groups need this sort of motivation to enable them give off their best. It?s incumbent upon management to be able to identify superior performances and reward them accordingly. This would lead to greater effort towards goal attainment.
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 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 | 0.011 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".