Human capital and organizational performance: a study of Egyptian software companies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose The paper seeks to test empirically a variety of hypotheses related to human capital and organizational performance within software companies in Egypt. Design/methodology/approach A valid research instrument was utilized to conduct a survey of 38 software companies who are representative of the 107 members of the Software Industry Chamber of Egypt. A correlation analysis and stepwise regression were conducted to ascertain the validity of the hypotheses. Findings Statistical support was found for six of the nine hypotheses tested. Research limitations/implications One of the limitations of this study is that human capital metrics were based on CEO self‐reported scores. Thus, the ability to generalize is limited to this context. Practical implications Of all the human capital metrics collected, the number of superstar developers seems to be the most critical variable in predicting export intensity. Superstar developers are those individuals whose productivity equals four times that of the other developers and twice that of the star developers. Originality/value This paper tests empirically the relationship between human capital and organization performance in the Egyptian software industry context and provides support for the recruitment and development of superstar developers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it