Examining the Impact of Strategy Management and Information Technology on Organizational Performance of Sharjah Police
Bibliographic record
Abstract
The primary aim of this study is to investigate the effects of IT management and strategy management on the performance of organizations. Based on a solid theoretical basis and a thorough literature review, the author developed the study model, with the models adopted being the Resource-Based View of the Firm (RBV), Knowledge-Based View (KBV) and the Innovation theories. The study carried out an analysis of the effects of IT management and strategy management on the performance of organizations. For the purpose of this analysis, three hundred and forty-one (341) questionnaires were distributed to random selected Sharjah Police departments, in Sharjah, UAE. From the total questionnaires distributed, two hundred and forty-five (245) were returned, the data from which was analyzed using SPSS. The results of the analysis showed that IT management and strategy management had a positive and significant effect on organizational performance of Sharjah Police departments. The study recommends the effective implementation of IT management and strategy management for effective and successful performance of Sharjah police departments. The study confirmed the applicability of both the Resource-Based View and the Knowledge-Based View on examining organizational 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 | 0.008 |
| 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".