Impact of Budgetary Participation and Organizational Commitment on Managerial Performance in Nigeria
Bibliographic record
Abstract
Following the prevailing uncertainties in Nigerian business environment, managers and stakeholders require the need to be poised, prepared and plan to compete favourably under the rapidly shifting condition in order to remain relevant and profitable. This study examines the relationship between budget participation, organizational commitment and managerial performance in Nigeria. Primary data were obtained from copies of questionnaire distributed to members of staff at managerial levels at Nestle NIG-food, Nigerian Breweries-drinks, Flour mills-food, 7up Bottling company-drinks, Cadbury-food, Unilever-food, Vitafoam NIG-others categorized based on the nature of their business and analysed through use of Statistical Package of Social Science (SPSS, Version 20) as correlation and regression were used to evaluate relationships among variables. Findings revealed that participation in budget activities and commitment to work done by individuals in an organization positively impacts managerial performance, hence this assertion cannot be overlooked or ignored as it supports the empirical body of positive impacts. It is therefore recommended that organizations should engage in activities that will promote budget participation and commitment and also consider other processes and events that could be explored upon towards enhancing managerial performance.
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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 | 0.002 | 0.006 |
| 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".