Strategic alignment maturity criteria as a catalyst for enhancing operational excellence in Jordanian industrial companies
Bibliographic record
Abstract
High convergence level of strategic alignment between business and information technology helps companies enhance operational excellence. This research aims to identify strategic alignment maturity criteria level and their impacts on operational excellence in Jordanian industrial companies. The population of the study consists of all managers at top and middle management and a purposive sample is used to answer questionnaire items. In this survey, 288 valid responses are collected for analysis using SPSS (20) and smart PLS "V. 3". The study reveals that there is a significantly positive impact of strategic alignment maturity criteria (communication, competency-value Measurement, governance, partnership, scope & architecture and skills) on operational excellence. The most maturity criteria have a mid-level of maturity except scope & architecture and competency-value measurement criteria which maintain a low level. Thus, the study concluded that the researched companies have to recognize the business value of information technology (IT) investment and harmonizing IT architecture with business structure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".