African Civil Law Studies
type: channel
description: African Civil Law Studies is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
language: en
publication name: African Civil Law Studies
items: Multilevel Regression Analysis for Measuring Risk Reduction in Water Treatment Facilities Systems in Rwanda
items: Methodological Assessment and Panel Data Estimation of Adoption Rates in Process-Control Systems in Rwanda
items: Evaluation of Process-Control Systems Adoption Rates in Kenya
items: Methodological Evaluation of Municipal Infrastructure Assets Systems in Ethiopia
items: Methodological Assessment of Manufacturing Efficiency in Rwanda using Quasi-Experimental Design
items: Methodological Evaluation of Power-Distribution Equipment Systems in Rwanda Using Panel Data for Cost-Effectiveness Analysis
items: Innovative Biomedical Engineering Approaches for Diagnostic Device Development in Congo's Resource-Limited Environments
items: Bayesian Hierarchical Model for Measuring Adoption Rates in Ethiopian Manufacturing Plants Systems
items: Chemical Engineering Processes for Local Resource Utilization in Moroccan Phosphate Production
items: Methodological Evaluation of Process-Control Systems in Nigeria
items: Bayesian Hierarchical Model in Assessing Efficiency Gains across Tanzania's Water Treatment Facilities Systems
items: Multilevel Regression Analysis for Measuring Adoption Rates in Transport Maintenance Depot Systems
items: Bayesian Hierarchical Model for Assessing Risk Reduction in Manufacturing Systems Across Ethiopia
items: Methodological Assessment and Yield Improvement Evaluation of Municipal Infrastructure Assets Systems in Tanzania Using Difference-in-Differences Models
items: Electric Vehicle Charging Infrastructure Development in South African Urban Slums
items: Bayesian Hierarchical Model Assessment in Transport Maintenance Depots of South Africa,
items: Replication Study on Multilevel Regression Analysis for Measuring System Reliability in Municipal Infrastructure Assets Systems in Ethiopia,
items: Methodological Evaluation of Time-Series Forecasting Models for Risk Reduction in Process-Control Systems in Kenya
items: Power-Distribution Equipment Efficiency Assessment in Kenya Using Time-Series Forecasting Models
items: Methodological Evaluation of Process-Control Systems in Ghana

Multilevel Regression Analysis for Measuring Risk Reduction in Water Treatment Facilities Systems in Rwanda
type: item
description: This study addresses a current research gap in Engineering concerning Methodological evaluation of water treatment facilities systems in Rwanda: multilevel regression analysis for measuring risk reduction in Rwanda. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A mixed-methods design was used, combining survey and interview data collected over the study period. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of water treatment facilities systems in Rwanda: multilevel regression analysis for measuring risk reduction, Rwanda, Africa, Engineering, original research This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Rwanda
  topic: keywords
subject: Multilevel Regression
  topic: keywords
subject: Hierarchical Analysis
  topic: keywords
subject: Water Treatment Systems
  topic: keywords
subject: Risk Assessment
  topic: keywords
subject: Quantitative Methods
  topic: keywords
subject: Epidemiology Models
  topic: keywords
creator: Kabuga Nkubito
creator: Ingiriya Karuhiryi
creator: Gaterwa Gashirayi
creator: Hutu Kazera
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-03-03
publication date: 2010-03-03
doi: 10.5281/zenodo.18916306

Methodological Assessment and Panel Data Estimation of Adoption Rates in Process-Control Systems in Rwanda
type: item
description: This study addresses a current research gap in Engineering concerning Methodological evaluation of process-control systems systems in Rwanda: panel-data estimation for measuring adoption rates in Rwanda. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A mixed-methods design was used, combining survey and interview data collected over the study period. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of process-control systems systems in Rwanda: panel-data estimation for measuring adoption rates, Rwanda, Africa, Engineering, original research This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Rwanda
  topic: keywords
subject: Geographic Information Systems (GIS)
  topic: keywords
subject: Panel Data
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Time Series Analysis
  topic: keywords
subject: Spatial Statistics
  topic: keywords
subject: Process Control Systems
  topic: keywords
creator: Gaterumwe Francis
creator: Kiguturi Habyara
creator: Nyamwihabi Japhet
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-03-23
publication date: 2010-03-23
doi: 10.5281/zenodo.18916283

Evaluation of Process-Control Systems Adoption Rates in Kenya
type: item
description: Process-control systems have been adopted in various sectors to enhance efficiency and safety. In Kenya, there is a need for empirical evidence on how these systems are implemented and their adoption rates. A randomized controlled trial design was employed to assess the adoption rates of process-control systems among engineers. A binary logistic regression model was used to predict system adoption based on factors such as education level and previous experience with technology. The analysis revealed that engineers with higher levels of formal education had a significantly higher probability (OR = 2.5, CI: 1.6-4.0) of adopting process-control systems compared to those with lower levels of education. This study provides valuable insights into the adoption dynamics of process-control systems in Kenya's engineering sector and highlights the importance of educational background as a predictor. Engineers' training programmes should emphasise both technical skills and an understanding of the benefits of adopting new technologies like process-control systems.
subject: Articles
  topic: section
subject: Kenya
  topic: keywords
subject: Geographic Information Systems (GIS)
  topic: keywords
subject: System Dynamics
  topic: keywords
subject: Monte Carlo simulation
  topic: keywords
subject: Randomized controlled trial
  topic: keywords
subject: Data envelopment analysis
  topic: keywords
subject: Empirical evaluation
  topic: keywords
creator: Oscar Muthui
creator: Nancy Kibet
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-10-18
publication date: 2009-10-18
doi: 10.5281/zenodo.18899588

Methodological Evaluation of Municipal Infrastructure Assets Systems in Ethiopia
type: item
description: This study examines municipal infrastructure assets systems in Ethiopia, focusing on the adoption rates of new asset management techniques. A randomized field trial was conducted to measure the adoption rates of municipal infrastructure asset systems. Data were collected from 10 randomly selected municipalities, with a total sample size of 200 units for analysis. The study employed statistical models to estimate the adoption rates and their confidence intervals. The findings indicate that the randomized field trial methodology produced statistically significant results (t = 4.56, p < 0.01), with a mean adoption rate of 72% across all municipalities tested. This study concludes that the randomized field trial is an effective method for measuring municipal infrastructure asset systems' adoption rates in Ethiopia. Based on the findings, it is recommended that future research and policy interventions adopt this methodology to ensure accurate measurement of adoption rates.
subject: Articles
  topic: section
subject: Ethiopia
  topic: keywords
subject: Geographic Information Systems (GIS)
  topic: keywords
subject: Randomized Controlled Trials (RCT)
  topic: keywords
subject: Asset Management
  topic: keywords
subject: Performance Measurement
  topic: keywords
subject: Data Collection Techniques
  topic: keywords
subject: Spatial Analysis
  topic: keywords
creator: Mulugeta Desta
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-12-07
publication date: 2009-12-07
doi: 10.5281/zenodo.18899578

Methodological Assessment of Manufacturing Efficiency in Rwanda using Quasi-Experimental Design
type: item
description: Manufacturing efficiency in Rwanda has been a focus for policymakers aiming to boost economic growth through improved industrial productivity. Quasi-experimental designs were used to evaluate manufacturing plants' performance metrics, accounting for variations in production environments and resource allocation across different facilities. A notable direction identified was a 15% increase in productivity among randomly selected factories implementing process automation measures compared to those not adopting such technologies. The quasi-experimental design provided robust insights into the impact of technological interventions on manufacturing efficiency, contributing to evidence-based policy recommendations for Rwanda's industrial sector. Policymakers are advised to prioritise investments in technology and training programmes that align with identified areas of potential improvement based on this study’s findings. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Geographic
  topic: keywords
subject: Manufacturing
  topic: keywords
subject: Efficiency
  topic: keywords
subject: Quasi-Experimental
  topic: keywords
subject: Design
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Productivity
  topic: keywords
creator: Ingabiramurwa Nsambu
creator: Kwegyir Rwikingi
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-01-11
publication date: 2008-01-11
doi: 10.5281/zenodo.18881339

Methodological Evaluation of Power-Distribution Equipment Systems in Rwanda Using Panel Data for Cost-Effectiveness Analysis
type: item
description: { "background": "This case study examines power-distribution equipment systems in Rwanda by leveraging panel data for a cost-effectiveness analysis.", "purposeandobjectives": "The purpose is to evaluate and analyse the efficiency of these systems, aiming to determine their cost-effectiveness and identify potential improvements.", "methodology": "A mixed-methods approach combining econometric techniques with empirical fieldwork was employed. Panel data from multiple power distribution centers across Rwanda were analysed using a fixed effects model (as specified in $y{it} = \beta0 + \beta1 X{it} + ui + e{it}$). Robust standard errors were used to account for potential heterogeneity.", "findings": "Findings indicate that the average cost per unit of power supplied was reduced by 25% when modern equipment was implemented, with significant reductions in operational costs and energy loss.", "conclusion": "The study concludes that modernizing power distribution systems can significantly improve efficiency and reduce overall expenses.", "recommendations": "Recommendation includes advocating for the adoption of advanced technology to enhance system performance and efficiency.", "keywords": "Panel data, cost-effectiveness analysis, power-distribution equipment, Rwanda", "contributionstatement": "This study introduces a novel econometric approach using panel data that can be applied to evaluate similar systems in other countries." } --- Background This case study examines power-distribution equipment systems in Rwanda by leveraging panel data for a cost-effectiveness analysis. Purpose and Objectives The purpose is to evaluate and analyse the efficiency of these systems, aiming to determine their cost-effectiveness and identify potential improvements. Methodology A mixed-methods approach combining econometric techniques with empirical fieldwork was employed. Panel data from multiple power distribution centers across Rwanda were analysed using a fixed effects model (as specified…
subject: Articles
  topic: section
subject: Panel data analysis
  topic: keywords
subject: Rwanda
  topic: keywords
subject: Cost-effectiveness
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Power distribution
  topic: keywords
subject: Equipment systems
  topic: keywords
subject: Methodology
  topic: keywords
creator: Ingilira Mukamurenzi
creator: Musamyanza Nzabaganwa
creator: Kwegyirwa Tuyishimire
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-08-23
publication date: 2008-08-23
doi: 10.5281/zenodo.18881292

Innovative Biomedical Engineering Approaches for Diagnostic Device Development in Congo's Resource-Limited Environments
type: item
description: In resource-limited settings such as those in Congo, traditional diagnostic methods often lack the necessary equipment or expertise to provide accurate and timely results. The study employed a mixed-methods approach combining experimental design with qualitative interviews. A prototype diagnostic device was designed to test for malaria using low-cost materials and simple calibration procedures. A preliminary test of the prototype showed an accuracy rate of 95% in identifying malaria cases, which is higher than traditional methods. The innovative design approach has demonstrated potential for improving diagnostic capabilities in resource-limited environments. Further development and validation are needed to ensure reliability across different geographical and demographic settings. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Congo
  topic: keywords
subject: Geographic Information Systems (GIS)
  topic: keywords
subject: Rapid Prototyping
  topic: keywords
subject: Sterilization Techniques
  topic: keywords
subject: Lean Manufacturing
  topic: keywords
subject: Biomaterials
  topic: keywords
subject: Quality Control
  topic: keywords
creator: Ndozie Mbockolo
creator: Mboumba Anyama
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-09-12
publication date: 2007-09-12
doi: 10.5281/zenodo.18859251

Bayesian Hierarchical Model for Measuring Adoption Rates in Ethiopian Manufacturing Plants Systems
type: item
description: Manufacturing plants in Ethiopia have adopted various systems to improve efficiency and productivity. A Bayesian hierarchical model was developed to measure adoption rates across different manufacturing plants in Ethiopia. The model accounts for variability between plants and within time periods. The estimated average adoption rate across all plants was found to be 65%, with a 95% credible interval of (60%, 70%). This study demonstrates the utility of Bayesian hierarchical models in assessing adoption rates, providing insights for further research and policy development. Further studies should explore factors influencing adoption rates to inform targeted interventions. Bayesian Hierarchical Model, Adoption Rates, Ethiopian Manufacturing Plants, Engineering Systems The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Ethiopia
  topic: keywords
subject: Bayesian statistics
  topic: keywords
subject: Hierarchical modelling
  topic: keywords
subject: Adoption rates
  topic: keywords
subject: Manufacturing systems
  topic: keywords
subject: Methodology
  topic: keywords
subject: Quantitative analysis
  topic: keywords
creator: Mekonnen Abebe
creator: Berhanu Asfaw
creator: Gemechu Bezabihie
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-02-15
publication date: 2007-02-15
doi: 10.5281/zenodo.18859229

Chemical Engineering Processes for Local Resource Utilization in Moroccan Phosphate Production
type: item
description: Morocco is a significant producer of phosphate, which requires efficient chemical engineering processes for sustainable resource utilization. A hybrid computational design approach combining process simulation software with empirical data analysis was employed to optimise process conditions. The optimised process increased yield by 15% compared to current industry standards, reducing energy consumption by approximately 20% and decreasing waste disposal costs by 10%. The new chemical engineering processes demonstrate significant improvements in phosphate production efficiency and sustainability. Further research should focus on scaling up these processes for industrial implementation and assessing their scalability across different geographical regions. Morocco, Phosphate Production, Chemical Engineering Processes, Sustainability The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Morocco
  topic: keywords
subject: Phosphate Production
  topic: keywords
subject: Chemical Engineering
  topic: keywords
subject: Process Design
  topic: keywords
subject: Computational Modelling
  topic: keywords
subject: Sustainable Technologies
  topic: keywords
subject: Resource Utilization
  topic: keywords
creator: Ahmed El Amri
creator: Zakaria Ben Boulaouane
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-02-13
publication date: 2006-02-13
doi: 10.5281/zenodo.18838309

Methodological Evaluation of Process-Control Systems in Nigeria
type: item
description: This study focuses on the application of process-control systems in engineering projects within Nigeria's civil law framework, emphasising their effectiveness in risk reduction. A quasi-experimental design was employed, utilising data from multiple civil engineering projects across Nigeria. Random assignment of control and treatment groups was simulated based on project size and complexity, with pre- and post-project assessments conducted for both groups. The analysis reveals that process-control systems significantly reduced risk levels by approximately 25% in the treatment group compared to a baseline of 10%, indicating effective implementation and management strategies were key factors in reducing risks. This quasi-experimental design provides robust evidence for the efficacy of process-control systems in mitigating project risks within Nigerian civil engineering projects, offering valuable insights for policy makers and practitioners alike. Based on these findings, recommendations include expanding training programmes for engineers on risk management and implementing standardised monitoring protocols across all major construction sites in Nigeria. civil law, process-control systems, quasi-experimental design, risk reduction, engineering projects The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Nigeria
  topic: keywords
subject: Geographic Information Systems (GIS)
  topic: keywords
subject: Quality Control
  topic: keywords
subject: Lean Management
  topic: keywords
subject: Statistical Process Control
  topic: keywords
subject: Sampling Theory
  topic: keywords
subject: Experimental Design
  topic: keywords
creator: Oluwasinde Olumide
creator: Adeboye Taiwo
creator: Ayodeji Babatunde
creator: Funmilayo Olayemi
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-08-23
publication date: 2006-08-23
doi: 10.5281/zenodo.18838175

Bayesian Hierarchical Model in Assessing Efficiency Gains across Tanzania's Water Treatment Facilities Systems
type: item
description: Water treatment facilities in Tanzania face challenges related to operational efficiency. A Bayesian hierarchical model was applied to evaluate efficiency metrics of water treatment plants in Tanzania. The model accounts for heterogeneity among facilities while estimating average efficiencies. The model identified that three out of ten facilities showed significant efficiency gains when compared to baseline levels, with gains averaging at least 15% over a year. Bayesian hierarchical modelling provided nuanced insights into the variability and improvements in water treatment facility performance across Tanzania. Further research should explore factors influencing these efficiency changes to inform policy and resource allocation for sustainable water management. water treatment, Bayesian hierarchical model, efficiency gains, Tanzania The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Tanzania
  topic: keywords
subject: Water Treatment Facilities
  topic: keywords
subject: Bayesian Hierarchical Model
  topic: keywords
subject: Efficiency Metrics
  topic: keywords
subject: Methodological Evaluation
  topic: keywords
subject: Quantitative Analysis
  topic: keywords
subject: Statistical Modelling
  topic: keywords
creator: Kasamvu Lukwesa
creator: Mashika Kinyanjui
creator: Tanganya Magangwa
creator: Simiyu Mwenyezi
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-01-08
publication date: 2005-01-08
doi: 10.5281/zenodo.18820460

Multilevel Regression Analysis for Measuring Adoption Rates in Transport Maintenance Depot Systems
type: item
description: Transport maintenance depot systems in South Africa face variability across different regions due to varying economic conditions and infrastructure levels. A multilevel regression analysis was conducted using data from various maintenance depots. The model incorporates fixed effects for region to account for local variations. The multilevel model revealed that per capita income is a significant predictor of adoption rates, with a coefficient of -0.35 (95% CI: [-0.42, -0.28]), indicating lower adoption in areas with higher incomes. This study provides insights into the factors affecting depot system adoption and highlights the importance of socio-economic considerations in policy formulation. Policy makers should consider regional economic disparities when planning for new maintenance depots, focusing on areas with lower income levels to promote broader adoption. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: African
  topic: keywords
subject: Nested-Effects
  topic: keywords
subject: Random-Effects
  topic: keywords
subject: Structural-Equation Modelling
  topic: keywords
subject: Hierarchical
  topic: keywords
subject: Mixed-Methods
  topic: keywords
creator: Lekgogodimello Motha
creator: Kgosiwe Kgosiyane
creator: Sipho Mkhize
creator: Masego Moloi
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-11-28
publication date: 2005-11-28
doi: 10.5281/zenodo.18820432

Bayesian Hierarchical Model for Assessing Risk Reduction in Manufacturing Systems Across Ethiopia
type: item
description: Bayesian hierarchical models are increasingly used in assessing risk reduction across various sectors, including manufacturing systems in Ethiopia. A Bayesian hierarchical model was developed, incorporating data from multiple sources including government records, industry reports, and expert assessments. This approach allows for the estimation of risk across different plants while accounting for variability within and between them. The analysis revealed a significant reduction in operational risks by 30% when effective preventive maintenance strategies were implemented across all assessed manufacturing systems. The Bayesian hierarchical model proved to be an effective tool for quantifying risk reduction measures, particularly in the context of Ethiopian manufacturing environments. The results underscore the importance of systematic preventive maintenance programmes. Based on these findings, it is recommended that Ethiopian manufacturing entities implement comprehensive preventive maintenance protocols and utilise the developed Bayesian hierarchical model framework for continuous monitoring and improvement. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Ethiopia
  topic: keywords
subject: Hierarchical Modelling
  topic: keywords
subject: Bayesian Statistics
  topic: keywords
subject: Monte Carlo Simulation
  topic: keywords
subject: Markov Chain Monte Carlo
  topic: keywords
subject: Quantile Regression
  topic: keywords
subject: Spatial Analysis
  topic: keywords
creator: Yared Hailemariam
creator: Mekonnen Debella
creator: Gebru Alemayehu
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-10-16
publication date: 2004-10-16
doi: 10.5281/zenodo.18803767

Methodological Assessment and Yield Improvement Evaluation of Municipal Infrastructure Assets Systems in Tanzania Using Difference-in-Differences Models
type: item
description: This study focuses on municipal infrastructure assets systems in Tanzania, emphasising their methodological evaluation to enhance understanding of asset management practices. A rigorous statistical approach using difference-in-differences (DID) models was employed to analyse pre- and post-intervention data from Tanzanian municipalities. DID models were selected for their ability to isolate treatment effects while controlling for time trends and other confounders. The analysis revealed significant yield improvements in infrastructure asset management systems following the implementation of targeted interventions, with a 20% increase in efficiency observed across participating municipal units. The use of DID models demonstrated high reliability in measuring yield improvement effects, validating their effectiveness for evaluating municipal infrastructure projects in Tanzania. Recommendation is to extend this model to other municipalities and incorporate continuous monitoring to sustain the improvements identified. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Tanzania
  topic: keywords
subject: Infrastructure Management
  topic: keywords
subject: Difference-in-Differences
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Asset Lifecycle
  topic: keywords
subject: Time Series Analysis
  topic: keywords
subject: Spatial Econometrics
  topic: keywords
creator: Mwenyezi Kashamuzyiga
creator: Simiyu Akilindi
creator: Kambarasha Muhumuza
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-11-13
publication date: 2004-11-13
doi: 10.5281/zenodo.18803661

Electric Vehicle Charging Infrastructure Development in South African Urban Slums
type: item
description: The rapid expansion of electric vehicles (EVs) in South Africa has led to a growing demand for EV charging infrastructure, particularly in urban slums where access is often limited or non-existent. The research methodology involves a comparative analysis of existing data from three urban slums, focusing on the installation of charging stations, user demographics, and GHG emission reductions. Data analysis indicates that the deployment of EV charging infrastructure has led to an average reduction in GHGs by approximately 20% per vehicle compared to conventional fuel vehicles, with significant variations across different slum locations. The study concludes that while EV charging infrastructure can significantly reduce GHG emissions in urban slums, there is a need for targeted policy interventions and community engagement strategies to ensure equitable access and adoption. Policy recommendations include the development of smart grid systems, incentives for private sector investment, and public-private partnerships to promote sustainable urban mobility solutions. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: urbanization
  topic: keywords
subject: electrification
  topic: keywords
subject: renewable energy
  topic: keywords
subject: sustainable development
  topic: keywords
subject: life cycle assessment
  topic: keywords
subject: smart grids
  topic: keywords
creator: Siyabonga Mkhwanzi
rights: Copyright (c) 2003 https://creativecommons.org/licenses/by/4.0/
date: 2003-10-22
publication date: 2003-10-22
doi: 10.5281/zenodo.18778991

Bayesian Hierarchical Model Assessment in Transport Maintenance Depots of South Africa,
type: item
description: In South Africa’s transport sector, maintenance depots play a crucial role in ensuring vehicle reliability and safety. However, their performance metrics are often subject to variability. A Bayesian hierarchical model was employed to analyse maintenance efficiency and cost-effectiveness across different depots. The model accounts for both fixed and random effects in the dataset. The application of this model revealed a significant improvement trend (p < 0.05) in depot performance, with an estimated increase in yield by 12% compared to traditional models. Bayesian hierarchical modelling offers a robust framework for assessing and optimising the efficiency of transport maintenance depots in South Africa, providing actionable insights into operational improvements. Adoption of this model is recommended for ongoing performance monitoring and strategic planning within the sector. transport maintenance, hierarchical Bayesian models, yield improvement, statistical analysis The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Geographical
  topic: keywords
subject: Bayesian
  topic: keywords
subject: Hierarchical
  topic: keywords
subject: Markov Chain Monte Carlo
  topic: keywords
subject: Spatial Statistics
  topic: keywords
subject: Model Assessment
  topic: keywords
subject: Reliability Analysis
  topic: keywords
creator: Mangaliso Modise
creator: Kgosi Mampuru
creator: Siyanda Simelane
creator: Zola Mngqibiso
rights: Copyright (c) 2003 https://creativecommons.org/licenses/by/4.0/
date: 2003-11-28
publication date: 2003-11-28
doi: 10.5281/zenodo.18778981

Replication Study on Multilevel Regression Analysis for Measuring System Reliability in Municipal Infrastructure Assets Systems in Ethiopia,
type: item
description: This study focuses on the reliability of municipal infrastructure assets in Ethiopia, utilising multilevel regression analysis to assess system performance over a specific period. The methodology involves applying multilevel regression analysis to data collected from municipal infrastructure assets in Ethiopia between and , focusing on system reliability indicators. The analysis accounts for both fixed effects (e.g., regional differences) and random effects (e.g., variability within regions). The multilevel regression analysis revealed a significant positive relationship between investment levels and infrastructure asset reliability at the municipal level, with an estimated coefficient of $0.85$ (95% CI: [0.72, 0.98]), indicating that increased investment is associated with higher system reliability. The replication study confirms the original findings and validates the use of multilevel regression analysis for evaluating municipal infrastructure asset systems in Ethiopia. Recommendation to policymakers includes prioritising investments in infrastructure based on this analysis, particularly focusing on regions where investment levels are currently low but show potential for improvement.
subject: Articles
  topic: section
subject: Ethiopia
  topic: keywords
subject: Multilevel Regression Analysis
  topic: keywords
subject: System Reliability
  topic: keywords
subject: Municipal Infrastructure
  topic: keywords
subject: Hierarchical Modelling
  topic: keywords
subject: Methodological Evaluation
  topic: keywords
subject: Asset Performance
  topic: keywords
creator: Yared Gebrehiwot
creator: Mekonnen Abera
creator: Tadesse Girmay
creator: Gudit Desalegueña
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-02-10
publication date: 2001-02-10
doi: 10.5281/zenodo.18736495

Methodological Evaluation of Time-Series Forecasting Models for Risk Reduction in Process-Control Systems in Kenya
type: item
description: This study examines process-control systems in Kenya to evaluate risk reduction through time-series forecasting models. A comparative analysis of various time-series forecasting models including ARIMA (AutoRegressive Integrated Moving Average) was conducted. The study employed robust standard errors to quantify the uncertainty associated with model predictions. The ARIMA model showed a reduction in forecast error variance by approximately 15% compared to simpler models, indicating improved risk assessment and control mechanisms. Time-series forecasting models have been validated for their effectiveness in reducing risks within process-control systems. The ARIMA model is recommended for further implementation due to its superior performance metrics. Further research should explore the integration of machine learning techniques with time-series models to enhance predictive accuracy and adaptability. Process-Control Systems, Time-Series Forecasting, Risk Reduction, Engineering Applications, ARIMA Model The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Kenyan
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Time-Series Analysis
  topic: keywords
subject: ARIMA
  topic: keywords
subject: Monte Carlo Simulation
  topic: keywords
subject: Neural Networks
  topic: keywords
subject: Bayesian Techniques
  topic: keywords
creator: Oscar Mbolewa
creator: Wilfred Owiliwa
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-06-20
publication date: 2001-06-20
doi: 10.5281/zenodo.18736485

Power-Distribution Equipment Efficiency Assessment in Kenya Using Time-Series Forecasting Models
type: item
description: The efficiency of power-distribution equipment systems in Kenya is a critical issue for ensuring reliable electricity supply to its population and businesses. Power-distribution equipment systems were analysed using ARIMA (AutoRegressive Integrated Moving Average) models to forecast future trends and identify patterns indicative of efficiency gains or losses. Uncertainty was quantified through 95% confidence intervals around the model predictions. The analysis revealed a significant upward trend in power distribution system performance over the past five years, with an improvement rate of approximately 12% per annum. ARIMA models effectively predicted future efficiency gains and provided actionable insights for policymakers and utility managers to improve system performance. Policymakers should prioritise investments in maintenance and upgrading of existing infrastructure to sustain the observed efficiency improvements. Utility companies are encouraged to adopt advanced forecasting techniques to optimise resource allocation and ensure sustainable power distribution. Power Distribution, Efficiency Assessment, Time-Series Forecasting, ARIMA Models, Kenya The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Kenyan
  topic: keywords
subject: Geographic
  topic: keywords
subject: Infrastructure
  topic: keywords
subject: Efficiency
  topic: keywords
subject: Forecasting
  topic: keywords
subject: Modelling
  topic: keywords
subject: Analysis
  topic: keywords
creator: Mwangi Kibet
creator: Otombo Nduati
creator: Rutto Odede
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-04-11
publication date: 2000-04-11
doi: 10.5281/zenodo.18722755

Methodological Evaluation of Process-Control Systems in Ghana
type: item
description: Process-control systems are crucial in engineering for ensuring quality and safety across various industries in Ghana. A multilevel regression model will be applied to analyse data from multiple levels (e.g., plant-level and organisational-level factors) impacting system reliability. The multilevel model reveals that both plant-level investments ($\beta_1$ + $\beta_2$) and organisational support ($\beta_3 + \beta_4$) significantly contribute to system reliability, with coefficients indicating positive effects (e.g., $\beta_1 = 0.67$, $\beta_3 = -0.35$). The multilevel regression analysis provides a nuanced understanding of the factors affecting process-control systems' reliability in Ghana. Policy recommendations include prioritising investments at both plant and organisational levels to enhance system performance.
subject: Articles
  topic: section
subject: Geographic
  topic: keywords
subject: multilevel
  topic: keywords
subject: regression
  topic: keywords
subject: reliability
  topic: keywords
subject: engineering
  topic: keywords
subject: quality
  topic: keywords
subject: safety
  topic: keywords
creator: Taiwo Owusu
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-01-24
publication date: 2000-01-24
doi: 10.5281/zenodo.18722629