Evaluating the impact of scope, time, cost, and quality management on project performance and business overall performance in Jordanian financial sector ,
Bibliographic record
Abstract
Within the context of the financial industry, the purpose of this research is to investigate the influence that management of scope, time, cost, and quality has on the performance of projects and business overall performance in the financial sector. Following the collection and examination of the study materials, a total of 331 samples were deemed appropriate for analysis by means of the PLS software. According to the findings, the implementation of scope, time, cost, and quality management has a direct and beneficial impact on the enhancement of project performance in the organization that deals with financial matters. As an additional point of interest, the project scope has a favorable impact on the performance of the project through the implementation of work breakdown structure, project scope definition, and scope change control. The formulation of a timetable, the estimation of the duration of activities, and the critical path analysis are all ways in which project time can have an impact on the performance of the project. Additionally, the cost of a project has an impact on the performance of the project through the processes of cost estimation, budgeting, and cost control. And finally, project quality effects positively on project performance and business overall performance through Based on the findings, it appears that the successful management of these four knowledge domains greatly improves the outcomes of the project. To be more specific, Scope Management ensures that the company's goals are aligned with the expectations of the organization, Time Management assists in meeting deadlines, Cost Management optimizes budgets, and Quality Management guarantees that high standards are maintained. Based on the findings of the study, it is concluded that combining these areas results in higher project performance, highlighting the crucial importance of these areas in projects involving the financial industry.
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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 | 0.008 | 0.018 |
| 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) | 0.001 | 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".