Effect of Intellectual Capital on Competitive Advantage in the Jordanian Pharmaceutical Companies
Bibliographic record
Abstract
The current study is considered as a quantitative explanatory study aims to examine the effect of intellectual capital (human, relational and structural capital) on competitive advantage in Jordanian pharmaceutical companies.In addition, it aims to explore awareness of the importance of intellectual capital and dimensions of competitive advantage in the targeted companies A survey strategy was applied thorough a self-administrated questionnaire as the data collection method.13 pharmaceutical companies that were registered in the Jordanian Association of Pharmaceutical manufacturers (JAMP) in 2016 were targeted in this study.The total number of all general managers, deputy managers, head of departments and head of divisions in the 13 companies was 220 they were all targeted, however, 207 questionnaires were returned.Statistical tests within SPSS package were used to analyze the data.Results show strong statistical significant effect of intellectual capital (human capital, relational capital and structural capital) on competitive advantage in the Jordanian pharmaceutical companies at level ( 0.05).Findings also indicate that each of the intellectual capital constructs has its own effect on the competitive advantage.According the results indicated for the awareness of the management in these companies to the importance of managing intellectual capital.For the awareness of competitive advantage dimensions the results revealed a moderate level of importance as addressed by the respondent of the study.The study has made significant contributions to the body of knowledge at academic and practical levels by extending knowledge regarding the effect of intellectual capital on competitive advantage .this study answers the call by many researchers for more studies to address the relationship the study constructs in emerging economies.Practically the study recommends that Jordanian pharmaceutical companies must provide training programs to support staff with specialized skill related to their jobs and tasks.It is also recommended that recruiting and selection employees' process should consider professional and social applicants' competencies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".