Factors Impacting on CMMI Acceptance Among Software Development Firms: A Qualitative Assessment
Bibliographic record
Abstract
Productive firms try to deliver high-quality products to be globally competitive. Therefore, software development firms need to adhere to a set of best practices that improve their processes. Capability maturity model integration (CMMI) comprehensively assesses the maturity of a firm's processes. Representing a major departure from the traditional method of running quality management in software development firms, the adoption of CMMI has major ramifications and long-lasting effects on a company’s quality procedures. Unfortunately, the literature lacks information as to how firms should implement CMMI. Our research involved conducting an exploratory study examining the major factors that influenced CMMI adoption for Jordanian software development firms. Quality managers from eighteen software development organizations took an open-ended survey. The results show that the main factors in CMMI implementation in Jordanian software development firms were issues of its being too costly, having no time, dealing with market scope, and lack of top management support. Conclusions are also presented.
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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 | 0.001 |
| Open science | 0.002 | 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".