The Extent of Applying Value Chain Analysis to Achieve and Sustain Competitive Advantage in Jordanian Manufacturing Companies
Why this work is in the frame
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Bibliographic record
Abstract
This study aims at identifying the extent of applying value chain analysis (VCA) to achieve and sustain competitive advantage in manufacturing companies in Jordan. To achieve the study’s objectives, a questionnaire was developed and pre -tested. The population of the study consists of the (93) company which are listed in the Amman Stock Exchange of Jordan in the end of the 2012, (65) companies of them accepted to fill the questionnaires. (81.5)% of the distributed questionnaires was received. Descriptive and analytical statistical techniques such as frequencies, percentages, standard deviation, means, one sample T test and one way ANOVA were applied to test the study’s hypotheses. The study revealed the following results: manufacturing companies in Jordan apply VCA, but don’t use it to achieve and sustain competitive advantage and there is no statistically significant effect of the respondents’ demographic characteristics on their perceiving the importance of applying VCA to achieve competitive advantage. The study recommends manufacturing companies in Jordan train their employees on strategic analysis of the company's internal and external environment, exercise the value chain analysis, calculate the unit cost of production and enter them in courses for achieving and sustaining competitive advantage through cost reduction and differentiation strategies.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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 it