Liner shipping cascading effect on Southern African Development Community port strategies
Bibliographic record
Abstract
Background: The cascading effect in the liner shipping industry has forced the ply of larger ships to Southern African Development Community (SADC) ports. This requires these ports to revise their strategic development to accommodate the resulting shifts in cargo flows to and from these strategic ports in conjunction with hinterland corridor development.Objectives: The purpose of this research was to understand the changing landscape of strategic SADC ports and develop future strategies with regard to liner shipping services.The main objective was to assess the future development needs of the SADC port system in relation to the cascading effect in liner shipping, linked to the development of hinterland corridors, identifying the limitations and opportunities of each port.Method: Descripto-exploratory research and analysis of secondary data were used. An extensive research of 552 sources (journal articles, research reports, books, newspaper and magazine articles and webpages) dating mostly from the year 2000 onwards were analysed.Results: Durban will remain the preferred container hub port for the foreseeable future if the port can increase its capacity and offer superior customer service in relation to competing ports in the region, such as Maputo, Walvis Bay and Ngqura. Durban is well adapted to accommodate the port and landside requirements resulting from the cascading effect. This is most evident in the depth of the port and port-side handling equipment. The findings confirm that the success of other SADC ports and corridors are subject to regional cooperation and integration without which the dominance of the port of Durban and the Maputo and North–South corridors will continue.Conclusion: The findings of the research indicate that Durban is ideally suited to develop further as a container hub port for the SADC region. This development is subject to a more competitive port landscape in the region as other ports such as Maputo, Walvis Bay and Ngqura improve their liner shipping service offering.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".