Power Distance Culture and Organizational Performance of Small and Medium Scale Enterprises in Bayelsa State
Bibliographic record
Abstract
Abstract-This study examined Power Distance Culture and Organizational performance of small and medium scale enterprises in Bayelsa State. The study was necessitated by the fact that, SMEs are considered as engines for economic growth and development. Although, government has made significant effort in the establishment and development of the sector, there is still much to be desired in meeting and reaping the expected benefits. The study population consisted of officially registered SMEs in Bayelsa State, numbering 1450. The sample size of 313 respondents was selected using multi-stage sampling techniques. The internal reliability of the items was determined using Cronbach Alpha and reliability coefficient of 0.71 was obtained. Quantitative data were analyzed using statistical package for social sciences (SPSS). Descriptive and inferential statistics were used to describe and interpret the data. The research hypotheses were tested using Spearman Rank Order correlation coefficient (Rho). With 217 questionnaires that was retrieved out of 313 questionnaires distributed, findings were made and following conclusions drawn. The study shows that, there is positive relationship between power distance culture and the measures of performance. Therefore, the following recommendations were made: SMEs should put in place organizational structures. It recommends that rules and regulations should be put in place in organizations and decision making should be sole responsibility of management in order to enhance the performance of SMEs.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".