Evaluation the Satisfaction of Employees through Account Fund Transfer of Pay at Bank for Agriculture and Rural Development - Ha Giang Branch (Agribank Ha Giang)
Bibliographic record
Abstract
Agribank Ha Giang Branch is a state owned enterprise – A Subsidiary of the Agribank Vietnam. The main task of the branch is to manage and operate the commercial banking network and banking operation for agriculture and rural areas in Ha Giang Province. The Branch has a workforce of 652 employees (recorded up to March 2013) working in 7 units located in 1 city, and 6 district Towns ; 2 other additional units are building and assembly workshop, testing and repairing workshop, design workshop and offices. Like other banks system and the branches in the Bank for Investment and Development of Vietnam system. Agribank was reconstructed to the joint stock bank since April 23th 2012. Before that time, Agribank was known as the biggest State-owned bank in Vietnam. Hence, the objective of this study is to critically examine the concepts of Employee Satisfaction and Fund transfer of Pay, to evaluate the relationship between Employee Satisfaction on Fund transfer of Pay and its antecedents, and to provide recommendations based on the key findings. To support these research objectives, quantitative research method is applied in order to measure the relationship between Remunerations and Benefits to Employees’ Satisfaction. The research strategy which is applied in this study is survey of questionnaire on a sample of 50 employees at Agribank Ha Giang. Achieved results show that adjusted R-Square equal to 0.466, and F-Test indicated that these relationships were statistical significant at 5% of confidence interval. Furthermore, Remunerations and Benefits impacted positively to Employees Satisfaction whether partial correlation coefficients of these factors were estimated at 0.231and 0.307. It meant that when Agribank Ha Giang can improve Remuneration and Benefit to its employees by 1%, Employees’ Satisfaction level will be improved by 0.231% and 0.307% respectively.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".