Exploring the influence of management information systems on strategic planning: The mediating role of business intelligence
Bibliographic record
Abstract
This quantitative study investigates the relationships between Management Information Systems (MIS), Business Intelligence (BI), and Strategic Planning (SP) within Jordanian Public Listed Companies, with a focus on the mediating role of BI. The target population comprises employees from the 108 public shareholding companies listed on the Amman Stock Exchange, totaling an estimated 1,080 senior managers involved in strategic planning. A random sample of 285 employees was surveyed to achieve a 95% confidence level with a 5% margin of error. Data were collected using a structured questionnaire with multi-item scales adapted from prior studies. Structural equation modeling (SEM) was employed to test the conceptual framework and hypothesized relationships, utilizing the two-step SEM approach with AMOS software. The results reveal significant positive relationships among MIS, BI, and SP. Specifically, MIS exhibits a statistically significant positive effect on SP, supporting previous research indicating MIS provides comprehensive data for informed planning. Furthermore, MIS significantly influences BI capabilities, underscoring the importance of robust MIS infrastructure for advanced BI analytics. BI, in turn, positively impacts SP, aligning with literature suggesting BI tools enhance planning agility and effectiveness through data-driven insights. Bootstrapping analysis demonstrates that BI partially mediates the relationship between MIS and SP. While BI acted as a significant mediating variable, MIS had a significant direct impact on SP, implying that though MIS has a direct impact on SP, it has an indirect impact, through BI, as well. Further analysis revealed that the constructs are interconnected, and that the mediation of BI is a necessary part of the process in Jordanian Public Listed Companies. As such, acknowledging the relevance of MIS, BI, and SP and the mediating role of BI, organizations can adapt their decision-making to achieve sustained competitive advantage within the dynamic business environment in Jordan.
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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 | 0.002 | 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 | 0.007 |
| Open science | 0.002 | 0.001 |
| 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".