The Role of Construction Management in Conflict Resolution in National Government-Funded Construction Projects in Uasin Gishu Kenya .
Bibliographic record
Abstract
National government-funded (NGF) construction projects in Kenya play a crucial role in fostering infrastructure development and economic growth. However, these projects are often marred by persistent conflicts arising from poor contract management, political interference, delayed payments, land acquisition disputes, and stakeholder disagreements. These conflicts lead to project delays, cost overruns, and in extreme cases, project abandonment. This study aimed to investigate the contributing factors to conflict in national government funded construction projects. Specifically, the study sought to examine the delays in payment, variation in design, misinterpretation of designs and delays in decision making by the stakeholders involved. The study adopted a mixed-methods research design, integrating both quantitative and qualitative approaches. Quantitative data was collected through self-administered questionnaires distributed to 173 respondents drawn from a target population of 185 professionals, including project managers, architects, quantity surveyors and contractors. Qualitative data was gathered through interviews with key industry players. The research utilized descriptive statistics such as means and standard deviations, alongside inferential techniques like correlation and regression analysis to interpret the findings. The study contributed valuable insights into how the contributing factors of conflict in national government funded project in uasin Gishu. The findings informed policy makers and practitioners, government agencies, construction managers, and other stakeholders on contributing factor of conflicts in NG funded projects in Uasin Gishu. Ultimately, the study revealed that the leading causes of conflict in national government-funded construction projects were late payment of contractors (M = 4.27), poor communication among stakeholders (M = 4.14), and design changes (M = 3.89The regression model indicated a strong and significant contribution of construction management to conflict resolution (R² = 0.770, p < .001). It was concluded that targeted management strategies, particularly those emphasizing communication, stakeholder involvement, and contract clarity, are effective in minimizing conflicts
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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 | 0.015 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".