Challenges of Implementing Infrastructure Megaprojects through Public-Private Partnerships in Nigeria: A Case Study of Road Infrastructure
Bibliographic record
Abstract
Nigeria’s infrastructure deficit, especially in transport sector is appalling. This triggered the Lagos state government to start addressing its infrastructure deficit through PPPs. The purpose of this paper is to identify the challenges at both development phase and implementation (construction) phase of PPP road infrastructure megaproject, and identify the critical success factors that \nactually made the project successful. The paper adopted case study approach within a mixed method paradigm employed to collect data. Semi structured interviews were used to collect data from the participants involved in the case study with a view to identifying the challenges and success \nfactors. The identified challenges and success factors were incorporated into the questionnaire survey administered to the participants involved in the development and implementation stages of the case study. Data collected were analysed using descriptive and inferential statistics. The results of the Relative Significant Index ranking indicate that perceptions of Nigeria as a high risk economy by foreign investors, bureaucratic nature of the state government, schedule delay by administrative procedures, threat of expropriation and reluctance to tender/bid, and \npublic/political opposition are the most highly ranked challenges experienced at development phase. The paper further identified unexpected increased quantity, bottleneck in securing execution of the federal government support agreement, resistance by residents, and problem of access to the right-of-way as the most ranked challenges witnessed at implementation (construction) phase. The \nresults of factor analysis grouped the identified twenty two challenges into seven major factors at development phase, and grouped twelve identified challenges into four principal factors at implementation phase. The paper further identified four critical success factors using factor analysis that made the PPP project successful. These include enabling legislation with due diligence, strong commitment of both public and private sectors, strong financial package, and enabling environment and allocation of risk.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".