Critical factors that impact on the efficiency of the Lagos seaports
Bibliographic record
Abstract
Background: Since the past two decades, the Lagos seaports have experienced vessel and storage yard cargo congestion, resulting in dwell times of about 30 days for containerised imports and high trade logistics costs.Objectives: The purpose of this study was to identify the critical factors that impact the operational efficiency of the Lagos seaports with a view to improving liner trade activities.Method: The study adopted an operational-based approach to understand the dynamics of the various interfaces of the port value chain. The research paradigm adopted for the study was therefore a combination of constructivism and post-positivism paradigms, which entailed the exploration and understanding of the various stakeholders in the port value chain. The epistemology of the research relied on the use of the exploratory sequential mixed method research technique (i.e. the qualitative approach followed by the quantitative approach) at the operational level of port operations.Results: The result of the research showed that significant challenges exist and that some of these challenges cut across all functions of port operations. Challenges are experienced in the areas of corruption, trade fraud, transport infrastructure deficits, the absence of a supply chain culture and shortcomings in the execution of the ‘contract of customs’. Additionally, these factors include the deficiencies in services and facilities provided by state agencies and government-appointed service providers and private sector companies such as truckers, inland container depots, Inland Container Depots (ICDs) and terminal operators.Conclusion: Specific recommendations are made to address the issues identified which, if implemented, could significantly address the current inefficiencies observed in the Lagos seaport’s operations.
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.
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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".