Gaining Competitive Advantage through Marketing Strategies in Container Terminal: A Case Study on Shahid Rajaee Port in Iran
Bibliographic record
Abstract
Shahid Rajaee port complex at Bandar Abbas is the country’s principal gateway for containerized cargo. It has emerged as a leading regional commercial center and a world class business environment. It has now become the logical place to do business in the Middle East, providing investors with a unique value added platform. Ports have a significant role in today’s networked business environment. They are being regarded as hubs that are part of various logistics systems. The very essence of seaport is to link maritime networks and land network. These networks for the port are means of analyzing its competitiveness. The objective of this study is to find out the main factors which impact on competitiveness of container port in Shaied Rajaee. Port and enable it to suggest and apply the profound marketing strategy to get the huge load in this port. Based on our findings by employing the factor analysis is to reveal the vital competitiveness of the port. It reveal that that port strategy and policy, port logistics, hinterland condition, availability, shipping maritime service, port Regional center, shipping agreement and port service and connectivity are determining factors in the shahid Rajee port in Iran.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".