Alignment of Business and IT and Its Association with Business Performance: The Case of Iranian Firms
Bibliographic record
Abstract
In recent years strategic alignment has become a hot topic and researchers have put strong effort to develop models and instruments in order to measure alignment. The significance and importance of the aligning business with information technology and its effects on business performance is clearly embedded in the existent literature. Unfortunately, very few works have been done among Iranian firms and competition environment of Iran. These researches are limited to some case studies in Iranian companies. So, this paper opens the gate on this topic by investigating the effects of strategic alignment of business and information technology on business performance in Iranian large companies, applying the famous model introduced by Chan et al.. The primary data collected from questionnaire collected from a long list of companies in Tehran Stock Exchange and were analyzed through using SPSS software. The results indicate that strategic alignment of IT and business strategy has a positive and significant effect on business performance and it is stronger than the effect of both business and IS strategic orientation. Finally, some suggestion for Iranian companies and also future researches are presented.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".