Impact of human resource management practices on enterprises' competitive advantages and business performance: Evidence from telecommunication industry
Bibliographic record
Abstract
Human resource is the core issue of socio-economic development all over the world and human resource practice can serve as a sustainable competitive advantage, which are considered central in the company's performance. In the field of telecommunications services, there exists a need for research on human resource management practices to lay the groundwork for improving the human resource management regime in enterprises, which has received great interest of both business executives and researchers. The current paper aims to assess the impact of human resource management practices on enterprises' competitive advantages and business performance for the case of Vietnam Post and Telecommunications Group enterprises. This study uses structural equation modeling with 117 parameters to be estimated when the total sample size is 773 observations. Research results show that: (1) Functional activities of human resource management, leading and encouraging changes, team and group activities, employee involvement, administrative activities are positively correlated with human resource management practices at Vietnam Post and Telecommunications Group enterprises. Moreover, the quality of human resources, human resource behavior, human resource management practices have a positive effect on the competitive advantage of human resources at Vietnam Post and Telecommunications Group enterprises. Furthermore, human resource management practices are found to have a positive effect on the business performance of Vietnam Post and Telecommunications Group enterprises.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".