Exploring the link between employee commitment, recruitment process, and performance of internal supply chain of manufacturing firms in UAE
Bibliographic record
Abstract
This paper investigates the impact of employee commitment as well as the recruitment process on the performance of internal supply chain.Additionally, the current study is intended to investigate the mediating role of the recruitment process on the relationship between employee commitment and firm supply chain performance.The main objective behind any recruitment process is to recruit committed employees to help a firm enhance the performance of the organizations.Therefore, the current study is carried out to fill a gap by exploring the relationship between recruitment processes, employee commitment, and firm supply chain performance.To achieve the research objective, the study has analyzed the data gathered from 284 mangers of manufacturing organizations of United Arab Emirates.284 questionnaires out of 550 are found useful, so the response rate is 52 percent.The structural equation modelling using AMOS is used to analyze the data.The results of the study show an agreement with the results of the hypotheses.The direct relationship between commitment types and firms' internal supply chain performance, and between recruitment process and firms' internal supply chain performance are found positive and significant.The results of the study will be helpful for HR practitioners, operation managers, researchers, and policy makers in understanding the impact of employee commitments and recruitment process on internal supply chains' performance of manufacturing firms.
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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 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 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".