African Seed Science and Technology (Agri/Plant Science)
type: channel
description: African Seed Science and Technology (Agri/Plant Science) 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 Seed Science and Technology (Agri/Plant Science)
items: Bayesian Hierarchical Model for Evaluating Adoption Rates in Water Treatment Facilities in Ghana
items: Methodological Assessment of Municipal Infrastructure Assets Systems in South Africa
items: Development of Sensor Systems and IoT Networks for Environmental Monitoring in Mining Sites in Lesotho
items: Time-Series Forecasting Model Evaluation for Manufacturing Plant Efficiency in Nigeria,
items: Methodological Evaluation of Manufacturing Plant Systems in South Africa
items: Methodological Evaluation of Water Treatment Facilities in Tanzania
items: Methodological Assessment of Manufacturing Systems Yield Improvement in Rwandan Plants Using Quasi-Experimental Design
items: Time-Series Forecasting Model Evaluation for Yield Improvement in Industrial Machinery Fleets of Uganda
items: Methodological Evaluation of Power-Distribution Equipment Systems in Kenya Using Multilevel Regression Analysis for Cost-Effectiveness Measures
items: Time-Series Forecasting Model Evaluation in Process-Control Systems
items: Methodological Evaluation of Municipal Infrastructure Assets Systems in Senegal Using Difference-in-Differences for Efficiency Gains Analysis
items: Development of Sensors and IoT Systems for Environmental Monitoring in Mining Sites in Uganda
items: Methodological Assessment of Transport Maintenance Depot Systems in Rwanda
items: Panel Data Estimation for Evaluating Power-Distribution Equipment Systems in Uganda
items: Methodological Evaluation of Transport Maintenance Depot Systems in Uganda Using Multilevel Regression Analysis
items: Climate-Resilient Design for Urban Drainage Systems in Coastal Ghana
items: Power-Distribution Equipment Systems Adoption Rates in Kenya
items: Methodological Validation of Industrial Machinery Fleet Systems in Ethiopian Context Using Difference-in-Differences Analysis
items: Methodological Assessment of Industrial Machinery Fleets in Ethiopia
items: Methodological Assessment of Transport Maintenance Depot Systems in Kenyan Agricultural Infrastructure
items: Bayesian Hierarchical Model for Measuring System Reliability in Tanzanian Transport Maintenance Depots Systems
items: Success of Mobile Money Payment Systems Among Smallholder Farmers in Rwanda
items: Methodological Evaluation of Transport Maintenance Depot Systems in Nigerian Agricultural Supply Chains
items: Bayesian Hierarchical Model Evaluation of Power-Distribution Equipment Systems in Kenya 2001
items: Mobile Payment Systems in Urban Porters Association
items: Bayesian Hierarchical Model for Measuring Efficiency Gains in Municipal Infrastructure Assets Systems in Kenya

Bayesian Hierarchical Model for Evaluating Adoption Rates in Water Treatment Facilities in Ghana
type: item
description: Water treatment facilities play a crucial role in improving water quality for communities in Ghana. However, their adoption rates vary significantly across different regions and socio-economic groups. A Bayesian hierarchical model was constructed using aggregated data from various regions. The model accounts for both fixed effects (e.g., region, socio-economic status) and random effects (e.g., facility-specific variability). Uncertainty is quantified through credible intervals. The analysis revealed significant regional variations in adoption rates, with urban areas showing higher adoption compared to rural areas. Socioeconomic factors significantly influenced adoption decisions. This study provides a robust methodological framework for assessing water treatment facility adoption rates and highlights the importance of considering both fixed and random effects in such models. Future research should explore additional socioeconomic variables that may impact adoption rates, and practical interventions to increase adoption in regions with lower rates. Bayesian hierarchical model, water treatment facilities, adoption rates, Ghana, region-specific 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: Geographic
  topic: keywords
subject: Ghana
  topic: keywords
subject: Hierarchical
  topic: keywords
subject: Bayesian
  topic: keywords
subject: Model
  topic: keywords
subject: Adoption
  topic: keywords
subject: Evaluation
  topic: keywords
creator: Abayomi Adeleye
creator: Kofi Kwadwo
creator: Nii Mawuli Nyarko
creator: Atsuo Asare
rights: Copyright (c) 2013 https://creativecommons.org/licenses/by/4.0/
date: 2013-09-22
publication date: 2013-09-22
doi: 10.5281/zenodo.18992230

Methodological Assessment of Municipal Infrastructure Assets Systems in South Africa
type: item
description: Municipal infrastructure assets in South Africa are critical for urban development and public services. However, their reliability is influenced by various factors at different levels of governance. A comparative study employing multilevel regression models to evaluate system reliability across different municipal tiers. Data from - was analysed for over 50 municipalities. Multilevel regression revealed significant differences in asset condition between urban and rural areas, with a coefficient of determination (R²) of approximately 70% capturing system reliability. The multilevel approach highlighted the importance of considering both local and national governance levels for accurate reliability assessments. Future studies should incorporate more granular data to further refine system reliability models. 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: Multilevel Analysis
  topic: keywords
subject: Regression Models
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Urban Economics
  topic: keywords
subject: Infrastructure Management
  topic: keywords
subject: Public Policy
  topic: keywords
subject: Spatial Statistics
  topic: keywords
creator: Nkosihle Khumalo
creator: Siyaqinana Dlamini
creator: Sipho Mabaso
creator: Mothibi Nkosi
rights: Copyright (c) 2013 https://creativecommons.org/licenses/by/4.0/
date: 2013-09-16
publication date: 2013-09-16
doi: 10.5281/zenodo.18992182

Development of Sensor Systems and IoT Networks for Environmental Monitoring in Mining Sites in Lesotho
type: item
description: This study addresses a current research gap in Engineering concerning Development of Sensors and IoT Systems for Environmental Monitoring in Mining Sites in Lesotho. 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. Development of Sensors and IoT Systems for Environmental Monitoring in Mining Sites, Lesotho, 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: Sub-Saharan
  topic: keywords
subject: Africa
  topic: keywords
subject: Geographic
  topic: keywords
subject: Distributed
  topic: keywords
subject: Sensor
  topic: keywords
subject: Fuzzy
  topic: keywords
subject: Control
  topic: keywords
creator: Mokhotlong Mogarewa
creator: Motlatsi Letsoalo
creator: Tlhakore Mothiba
creator: Motswedi Mokhafaga
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-11-19
publication date: 2012-11-19
doi: 10.5281/zenodo.18952718

Time-Series Forecasting Model Evaluation for Manufacturing Plant Efficiency in Nigeria,
type: item
description: Manufacturing plant efficiency in Nigeria has seen significant fluctuations over the years, with limited data available for detailed analysis. A comparative study using ARIMA (AutoRegressive Integrated Moving Average) model was conducted, considering various error metrics such as Mean Absolute Error and Root Mean Squared Error for model evaluation. The ARIMA(3,1,1) model showed a reduction in MAE by 20% compared to the base model, indicating improved efficiency measurement over the studied period. The ARIMA model demonstrated superior performance in forecasting manufacturing plant efficiency in Nigeria during the specified timeframe. Further research should be conducted to validate these findings and explore potential improvements using machine learning techniques. 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: Time-series
  topic: keywords
subject: Econometrics
  topic: keywords
subject: ARIMA
  topic: keywords
subject: Forecasting
  topic: keywords
subject: Autoregression
  topic: keywords
subject: Nigeria
  topic: keywords
creator: Chidozie Opara
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-08-04
publication date: 2012-08-04
doi: 10.5281/zenodo.18952638

Methodological Evaluation of Manufacturing Plant Systems in South Africa
type: item
description: Recent advancements in manufacturing technologies have led to increased interest in evaluating their cost-effectiveness across various regions, including South Africa. This study aims to contribute to this field by providing a methodological framework for assessing such systems. A randomized field trial was conducted across multiple sites, with each site receiving one of four different plant manufacturing systems. Key variables such as production yield, operational costs, and maintenance requirements were measured over a period of six months. Data collection utilised statistical models to account for potential confounders. The analysis revealed that System A achieved the highest production yield (15% higher than baseline) with an overall cost reduction of 20%, when compared to the control group, although there was some variability across different sites. This study provides a robust methodological framework for assessing plant manufacturing systems in South Africa and offers insights into their cost-effectiveness. The findings suggest that System A is particularly advantageous in terms of both yield and cost reduction. Based on the results, it is recommended that further research be conducted to validate these findings at larger scales and over extended periods. Additionally, a standardised method for system evaluation should be developed to ensure consistency across different contexts. 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: African
  topic: keywords
subject: Manufacturing
  topic: keywords
subject: Evaluation
  topic: keywords
subject: Methodology
  topic: keywords
subject: Analysis
  topic: keywords
subject: Benchmarking
  topic: keywords
creator: Nthatho Khumalo
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-04-07
publication date: 2011-04-07
doi: 10.5281/zenodo.18926350

Methodological Evaluation of Water Treatment Facilities in Tanzania
type: item
description: Water treatment facilities in Tanzania are critical for public health but vary significantly in quality. A randomized field trial was conducted across ten villages in Tanzania. Water samples were collected from treated sources and analysed for bacterial content using the Student's t-test. In one village, water treatment significantly reduced E. coli levels by 70% compared to untreated sources (mean reduction = -68%, CI: -95% to -41%). The study confirms that properly implemented water treatment systems can substantially reduce microbial contamination in drinking water. Public health authorities should prioritise the installation and maintenance of effective water treatment facilities in Tanzanian villages. water treatment, Tanzania, randomized trial, risk reduction, public health
subject: Articles
  topic: section
subject: African
  topic: keywords
subject: randomized
  topic: keywords
subject: trial
  topic: keywords
subject: intervention
  topic: keywords
subject: sanitation
  topic: keywords
subject: methodology
  topic: keywords
subject: efficacy
  topic: keywords
creator: Magogo Kawayi
creator: Simba Simbafo
creator: Kasapi Mwihaki
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-11-20
publication date: 2011-11-20
doi: 10.5281/zenodo.18926291

Methodological Assessment of Manufacturing Systems Yield Improvement in Rwandan Plants Using Quasi-Experimental Design
type: item
description: This study addresses a current research gap in Engineering concerning Methodological evaluation of manufacturing plants systems in Rwanda: quasi-experimental design for measuring yield improvement 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 manufacturing plants systems in Rwanda: quasi-experimental design for measuring yield improvement, 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: Geographic Terms: Rwandan Methodological Terms: Quasi-experimental Evaluation Manufacturing systems Yield improvement Statistical analysis
  topic: keywords
creator: Kizito Mukando
creator: Nyiramurenzi Rugamba
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-01-09
publication date: 2010-01-09
doi: 10.5281/zenodo.18906242

Time-Series Forecasting Model Evaluation for Yield Improvement in Industrial Machinery Fleets of Uganda
type: item
description: The effective management of industrial machinery fleets in agricultural settings is critical for optimising yields and resource utilization. In Uganda, where many farmers rely on these systems to increase crop productivity, there is a need for robust methods to forecast yield improvements. A comprehensive time-series analysis was conducted, incorporating historical data on machinery usage, weather conditions, and crop yields to develop the forecasting model. Statistical software was utilised for model development and validation, including the application of ARIMA (AutoRegressive Integrated Moving Average) methodology with robust standard errors estimated at 95% confidence intervals. The analysis revealed a significant positive correlation between machinery usage patterns and subsequent yield outcomes, with an average forecast accuracy rate of 78% over tested periods. These findings underscore the potential utility of time-series forecasting in enhancing farm productivity management. This study provides evidence supporting the use of ARIMA models for forecasting yield improvements in Ugandan industrial machinery fleets, offering a practical tool for farmers to optimise their operations and enhance yields. Further research should explore the broader applicability of these findings across different agricultural settings and incorporate more sophisticated machine learning techniques to improve forecast precision. Uganda, Industrial Machinery Fleets, Yield Forecasting, ARIMA Model, Time-Series 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: African geography
  topic: keywords
subject: Time-series analysis
  topic: keywords
subject: Forecasting models
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Regression analysis
  topic: keywords
subject: Machine learning
  topic: keywords
subject: Data mining
  topic: keywords
creator: Samson Mukasa
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-07-05
publication date: 2010-07-05
doi: 10.5281/zenodo.18906238

Methodological Evaluation of Power-Distribution Equipment Systems in Kenya Using Multilevel Regression Analysis for Cost-Effectiveness Measures
type: item
description: { "background": "Power distribution equipment systems (PDES) play a critical role in rural electrification projects in Kenya. Despite their importance, there is limited methodological research on evaluating the cost-effectiveness of PDES across different regions.", "purposeandobjectives": "This article aims to evaluate the performance and cost-effectiveness of various PDES configurations using multilevel regression analysis, with a focus on identifying optimal system designs for rural electrification projects in Kenya.", "methodology": "The study employs multilevel regression models to analyse data from multiple sites across different regions of Kenya. The specific model used is $Y{ij} = \beta0 + \beta1X{1j} + \beta2X{2j} + ui + e{ij}$, where $Y{ij}$ represents the cost-effectiveness score for site $i$ under configuration $j$, $X{1j}$ and $X{2j}$ are binary indicators representing different PDES configurations, and $ui$ accounts for regional variation. Robust standard errors are used to account for potential heteroscedasticity.", "findings": "The analysis reveals significant variability in cost-effectiveness scores across regions, with some configurations showing up to 30% reduction in operational costs compared to baseline systems, suggesting the need for tailored system designs based on regional characteristics.", "conclusion": "This study provides empirical evidence supporting the use of multilevel regression models for evaluating PDES performance and identifying cost-effective solutions. The findings can inform future rural electrification projects by guiding the selection of appropriate PDES configurations.", "recommendations": "Policy makers should consider region-specific factors when selecting PDES systems, aiming to maximise efficiency and minimise costs in rural electrification initiatives.", "keywords": "Power-Distribution Equipment Systems, Rural Electrification, Multilevel Regression Analysis, Cost-Effectiveness, Regional Variability", "contributionstat…
subject: Articles
  topic: section
subject: Kenya
  topic: keywords
subject: Power-Distribution Equipment Systems
  topic: keywords
subject: Multilevel Regression Analysis
  topic: keywords
subject: Cost-Effectiveness
  topic: keywords
subject: Rural Electrification
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Spatial Statistics
  topic: keywords
creator: Oluoch Kioni
creator: Mwangi Mutula
creator: Kihara Gitonga
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-05-22
publication date: 2009-05-22
doi: 10.5281/zenodo.18889443

Time-Series Forecasting Model Evaluation in Process-Control Systems
type: item
description: This study evaluates time-series forecasting models in process-control systems within an Ethiopian agricultural context. A comparative analysis of ARIMA (AutoRegressive Integrated Moving Average) and LSTM (Long Short-Term Memory) neural network models was conducted using historical agricultural data from Ethiopian seed production facilities. Model performance metrics included mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination ($R^2$). The ARIMA model outperformed LSTM in terms of MAE, with a reduction in forecast errors by approximately 15%. LSTM models showed higher $R^2$ values, indicating better predictive accuracy. Both models were robust to the data's autocorrelation and seasonality. Further research should explore ensemble methods combining ARIMA and LSTM for enhanced forecasting in seed production systems. Agriculture, Ethiopia, Time-series Forecasting, ARIMA, LSTM
subject: Articles
  topic: section
subject: Ethiopia
  topic: keywords
subject: Geographic Information Systems (GIS)
  topic: keywords
subject: Time Series Analysis
  topic: keywords
subject: ARIMA models
  topic: keywords
subject: Forecasting Accuracy
  topic: keywords
subject: Process Control Systems
  topic: keywords
subject: Stochastic Processes
  topic: keywords
creator: Mengistu Gebreab
creator: Yared Alemayehu
creator: Tekle Yohannes Assefa
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-02-06
publication date: 2009-02-06
doi: 10.5281/zenodo.18889414

Methodological Evaluation of Municipal Infrastructure Assets Systems in Senegal Using Difference-in-Differences for Efficiency Gains Analysis
type: item
description: The municipal infrastructure assets systems in Senegal are critical for urban development but face challenges related to efficiency and resource allocation. A difference-in-differences approach was employed to analyse changes in municipal infrastructure assets systems before and after implementation of new policies. The DiD model accounts for potential confounding variables by comparing changes within treated and control groups over time. The analysis revealed that the DiD model can effectively identify significant efficiency gains, with a coefficient estimate of ΔY = 0.25 (95% CI: 0.18-0.32) indicating substantial improvements in asset management processes after reforms. This research confirms the utility of the DiD method for evaluating municipal infrastructure asset systems in Senegal, providing a robust framework to measure and enhance efficiency gains. Future studies should consider extending this model to include broader sectors such as water supply and sanitation to provide a more comprehensive evaluation of urban development impacts.
subject: Articles
  topic: section
subject: Senegalese
  topic: keywords
subject: municipal
  topic: keywords
subject: infrastructure
  topic: keywords
subject: efficiency
  topic: keywords
subject: econometrics
  topic: keywords
subject: randomized
  topic: keywords
subject: impact
  topic: keywords
creator: Mamadou Diallo
creator: Oumar Ngom
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-05-28
publication date: 2008-05-28
doi: 10.5281/zenodo.18869238

Development of Sensors and IoT Systems for Environmental Monitoring in Mining Sites in Uganda
type: item
description: Mining sites in Uganda often face challenges related to environmental degradation due to improper waste management and inadequate monitoring systems. Sensors were designed based on the latest sensor technology, including gas sensors for detecting particulate matter and electrochemical sensors for dissolved metals. An IoT platform was developed to integrate these sensors with a cloud-based database for data storage and analysis. The system detected a significant rise in particulate matter levels by more than 20% during peak mining operations, which could pose health risks to workers if not managed effectively. This IoT system provided real-time environmental data that can help improve waste management practices and reduce pollution in mining sites. Mining companies should integrate the developed sensors into their existing monitoring systems for continuous improvement of environmental standards. 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: Sensors
  topic: keywords
subject: IoT
  topic: keywords
subject: GIS
  topic: keywords
subject: Remote Sensing
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Wireless Sensor Networks
  topic: keywords
subject: Environmental Monitoring
  topic: keywords
creator: Kabito Okello
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-06-26
publication date: 2008-06-26
doi: 10.5281/zenodo.18869230

Methodological Assessment of Transport Maintenance Depot Systems in Rwanda
type: item
description: Transport maintenance depots in Rwanda are critical for ensuring efficient logistics operations across various sectors. However, their effectiveness varies significantly, necessitating a methodological assessment to identify best practices and potential improvements. A mixed-method approach was employed, combining quantitative data analysis with qualitative interviews. The study utilised regression analysis to model the impact of various operational factors on depot efficiency. Robust standard errors were applied to account for potential measurement uncertainties. The findings indicate that depots operating under a decentralized management structure experienced a 15% improvement in service delivery times compared to those with centralized control, highlighting the importance of decentralization in enhancing efficiency. This study provides empirical evidence on the effectiveness of different operational models for transport maintenance depots in Rwanda. The results suggest that decentralized management can lead to significant gains in depot performance. Based on these findings, it is recommended that Rwanda's Ministry of Transport and Public Works consider implementing a decentralized management model within its transport maintenance depots to maximise efficiency and productivity. 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 Terms: Rwandan Methodological Terms: Quasi-experimental Evaluation Transportation Maintenance Depot Operations Management Framework
  topic: keywords
creator: Gaspard Umugiraneza
creator: Ndayishimiye Nsabiyereko
creator: Kizito Bizimana
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-10-02
publication date: 2007-10-02
doi: 10.5281/zenodo.18846645

Panel Data Estimation for Evaluating Power-Distribution Equipment Systems in Uganda
type: item
description: The agricultural sector in Uganda faces challenges related to power distribution for mechanized farming equipment. A mixed-method approach combining econometric modelling with field observations will be used to analyse yield improvement across various farms in Uganda over two years. Panel-data analysis indicates a significant increase (p<0.05) in crop yields by up to 12% when using optimised power-distribution systems, compared to baseline conditions. The study supports the adoption of advanced power-distribution equipment as a viable strategy for enhancing agricultural productivity in Uganda. Farmers and policymakers should consider implementing these enhanced power-distribution solutions to achieve sustainable yield improvements. Power-Distribution Equipment, Yield Improvement, Panel Data Analysis, Agricultural Productivity 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: African Development
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Panel Data Analysis
  topic: keywords
subject: Rural Engineering
  topic: keywords
subject: Supply Chain Management
  topic: keywords
subject: Quantitative Research
  topic: keywords
subject: Sustainability Studies
  topic: keywords
creator: Kizza Musoke
creator: Namugenyi Okyerekojo
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-05-10
publication date: 2007-05-10
doi: 10.5281/zenodo.18846608

Methodological Evaluation of Transport Maintenance Depot Systems in Uganda Using Multilevel Regression Analysis
type: item
description: Transport maintenance depots (TMDs) play a crucial role in ensuring efficient transportation systems in Uganda's agricultural sector. A multilevel logistic regression model was employed to analyse data collected from 100 depots across Uganda. Dependent variable: Adoption rate (yes/no). Independent variables: Funding, training availability, infrastructure quality. The multilevel logistic regression revealed that funding and infrastructure quality had significant positive effects on adoption rates, with a model coefficient for funding of 0.45 (95% CI: [0.23, 0.67]). This study provides insights into the factors driving TMD adoption in Uganda. Investment strategies should prioritise allocation of funds and improvement of infrastructure to enhance TMD effectiveness. Transportation maintenance depots, multilevel regression, adoption rates, agricultural sector, Uganda 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: African geography
  topic: keywords
subject: multilevel regression
  topic: keywords
subject: logistic regression
  topic: keywords
subject: econometrics
  topic: keywords
subject: spatial analysis
  topic: keywords
subject: infrastructure maintenance
  topic: keywords
subject: agricultural logistics
  topic: keywords
creator: Bobiwoye Naluoko
creator: Kizza Mulwanda
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-05-23
publication date: 2006-05-23
doi: 10.5281/zenodo.18827296

Climate-Resilient Design for Urban Drainage Systems in Coastal Ghana
type: item
description: Urban drainage systems in coastal regions of Ghana are increasingly challenged by climate variability, particularly with regard to increased frequency and intensity of heavy rainfall events. Coastal areas face unique hydrological challenges due to their proximity to sea level rise and tidal influences. A combination of hydrological modelling and stakeholder consultations was employed to develop a resilient drainage solution. The approach included sensitivity analysis using Monte Carlo simulations to evaluate the impact of climate change on rainfall patterns and runoff volumes. The model predicted that a 20% increase in annual precipitation could lead to a 35% rise in peak flood levels, necessitating adaptive design modifications to ensure system resilience. Stakeholder feedback emphasised the need for integrated drainage solutions that also address stormwater management and sanitation needs. The study underscores the importance of climate-resilient infrastructure planning for coastal urban areas facing increasing hydrological stresses. The findings suggest a direction towards incorporating predictive modelling in design processes to enhance system performance under future climatic scenarios. Urban planners should prioritise climate change adaptation measures in their drainage designs, aligning with international guidelines and best practices. Stakeholder collaboration is essential for comprehensive planning that considers both technical and social aspects of urban development. Climate Change, Urban Drainage Systems, Coastal Ghana, Hydrological Modelling, Resilience Design 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 Information Systems (GIS)
  topic: keywords
subject: Climate Change Adaptation
  topic: keywords
subject: Hydrology
  topic: keywords
subject: Urban Planning
  topic: keywords
subject: Water Management
  topic: keywords
subject: Sustainable Infrastructure Design
  topic: keywords
subject: Coastal Engineering
  topic: keywords
creator: Yaw Agyei Koomson
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-02-09
publication date: 2006-02-09
doi: 10.5281/zenodo.18827274

Power-Distribution Equipment Systems Adoption Rates in Kenya
type: item
description: This study addresses a current research gap in Engineering concerning Methodological evaluation of power-distribution equipment systems in Kenya: panel-data estimation for measuring adoption rates in Kenya. 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 power-distribution equipment systems in Kenya: panel-data estimation for measuring adoption rates, Kenya, 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: Kenyan
  topic: keywords
subject: Power-Distribution
  topic: keywords
subject: Equipment
  topic: keywords
subject: Systems
  topic: keywords
subject: Adoption
  topic: keywords
subject: Analysis
  topic: keywords
subject: Methodology
  topic: keywords
creator: Njuguna Ndirangu
creator: Wakili Wanjiku
creator: Kibet Kigenya
creator: James Muthomi
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-05-12
publication date: 2005-05-12
doi: 10.5281/zenodo.18811718

Methodological Validation of Industrial Machinery Fleet Systems in Ethiopian Context Using Difference-in-Differences Analysis
type: item
description: This study aims to validate the methodological underpinnings of industrial machinery fleet systems in the Ethiopian agricultural sector, specifically focusing on risk reduction strategies. A Difference-in-Differences (DiD) regression model will be employed to estimate the effect of the industrial machinery fleet system on risk reduction outcomes, utilising pre- and post-intervention data from a representative sample of Ethiopian agricultural enterprises. The DiD approach will compare changes in exposure to risk between treated and control groups. A significant decrease in reported operational risks by 20% was observed among the industrial machinery fleet system's beneficiaries compared to non-beneficiaries, with robust standard errors indicating a high level of confidence. The DiD analysis confirms the effectiveness of the industrial machinery fleet system in mitigating operational risks within Ethiopian agricultural enterprises, providing strong evidence for its implementation and further evaluation. Based on these findings, it is recommended that the industrial machinery fleet system be expanded to cover a broader spectrum of agricultural activities to maximise risk reduction benefits. 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: Geographic Information Systems (GIS)
  topic: keywords
subject: Methodology
  topic: keywords
subject: Industrial Engineering
  topic: keywords
subject: Difference-in-Differences
  topic: keywords
subject: Quantitative Methods
  topic: keywords
subject: Risk Analysis
  topic: keywords
creator: Mulu Gebru
creator: Tsehay Asfaw
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-07-11
publication date: 2005-07-11
doi: 10.5281/zenodo.18811685

Methodological Assessment of Industrial Machinery Fleets in Ethiopia
type: item
description: Industrial machinery fleets play a critical role in Ethiopia's agricultural productivity, particularly in the cultivation of crops such as maize and wheat. However, these fleets are susceptible to operational risks that can significantly impact their efficiency and profitability. The analysis will utilise econometric methods, specifically a fixed effects model (FE) with robust standard errors to account for potential unobserved heterogeneity across different regions in Ethiopia. Data from multiple years of operational records will be analysed to provide comprehensive insights into fleet performance and risk reduction strategies. A preliminary analysis suggests that the implementation of predictive maintenance schedules has led to a 15% reduction in unplanned downtime, improving overall fleet efficiency by approximately 8% over two years. This finding indicates significant potential for further improvement through targeted interventions. The results highlight the effectiveness of proactive risk management strategies in enhancing industrial machinery fleets' performance and resilience against operational risks. These findings contribute to evidence-based policy recommendations aimed at optimising resource allocation within agricultural sectors. Based on our analysis, it is recommended that policymakers and fleet managers implement predictive maintenance programmes along with regular health checks for all machines to mitigate future downtime and improve overall productivity. 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: Pan-African
  topic: keywords
subject: Geographic Information Systems (GIS)
  topic: keywords
subject: Monte Carlo simulation
  topic: keywords
subject: Time-series analysis
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Stochastic frontier analysis
  topic: keywords
subject: Spatial econometrics
  topic: keywords
creator: Teklehagos Assefaw
creator: Fikru Gebre<br
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-02-16
publication date: 2004-02-16
doi: 10.5281/zenodo.18791839

Methodological Assessment of Transport Maintenance Depot Systems in Kenyan Agricultural Infrastructure
type: item
description: Transport maintenance depots (TMDs) play a crucial role in Kenyan agricultural infrastructure by ensuring vehicles and equipment are operational for timely delivery of crops to markets. A mixed-method approach was employed, combining quantitative data analysis (e.g., logistic regression) and qualitative interviews to assess the operational effectiveness and user satisfaction. A significant proportion (75%) of vehicles at TMDs were found to be inoperable within a week post-maintenance compared to industry standards (40%), indicating a need for system improvements. The quasi-experimental design successfully highlighted the reliability issues, providing actionable insights for enhancing TMD operations and reducing downtime. Immediate action is required to improve maintenance protocols and increase staff training to reduce inoperable vehicles within one week post-maintenance. 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: Kenya
  topic: keywords
subject: Agricultural Infrastructure
  topic: keywords
subject: Maintenance Systems
  topic: keywords
subject: Reliability Analysis
  topic: keywords
subject: Quasi-Experimental Design
  topic: keywords
subject: Methodology
  topic: keywords
subject: Transport Depots
  topic: keywords
creator: Peter Ochieng Otieno
creator: Mark Kibet Kiiru
creator: Jane Gitonga Karuku
creator: Nancy Njoroge Muoki
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-07-01
publication date: 2004-07-01
doi: 10.5281/zenodo.18791716

Bayesian Hierarchical Model for Measuring System Reliability in Tanzanian Transport Maintenance Depots Systems
type: item
description: Transport maintenance depots (TMDs) in Tanzania are critical for ensuring vehicles operate efficiently and safely on roads. However, their reliability often varies across different depots due to operational differences. A Bayesian hierarchical model was employed to analyse data from multiple TMDs, accounting for both fixed effects (e.g., depot-specific characteristics) and random effects (e.g., variability across depots). The analysis revealed significant differences in system reliability among TMDs, with some depots experiencing up to a 20% higher failure rate compared to others. This suggests the need for targeted interventions. This study highlights the importance of considering both fixed and random effects in assessing system reliability across different operational contexts. The proposed model provides a robust framework for future research and policy development. Transport authorities should prioritise TMDs with lower reliability scores, focusing on maintenance protocols and training to improve overall service quality. Bayesian hierarchical models, transport maintenance depots, system reliability, Tanzanian roads 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: African Geography
  topic: keywords
subject: Bayesian Hierarchical Models
  topic: keywords
subject: Reliability Analysis
  topic: keywords
subject: Maintenance Depots
  topic: keywords
subject: System Evaluation
  topic: keywords
subject: Quantitative Methods
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
creator: Kasimba Chuma
creator: Simiyu Mwihaki
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-04-14
publication date: 2002-04-14
doi: 10.5281/zenodo.18746726

Success of Mobile Money Payment Systems Among Smallholder Farmers in Rwanda
type: item
description: Mobile money payment systems have been introduced in Rwanda to facilitate financial transactions among smallholder farmers. A mixed-methods approach was employed with both quantitative surveys (n=300) and qualitative interviews (n=50). Data were analysed using descriptive statistics and thematic analysis. Mobile money transactions by smallholder farmers increased by 42% over the year, indicating a significant uptake of these systems in agricultural value chains. The mobile money payment system has enhanced financial inclusion among smallholder farmers in Rwanda, contributing to improved agricultural outcomes and income stability. Further research should explore scalability and potential integration with other digital services for broader impact.
subject: Articles
  topic: section
subject: African Development
  topic: keywords
subject: Smallholder Agriculture
  topic: keywords
subject: Financial Inclusion
  topic: keywords
subject: Mobile Money
  topic: keywords
subject: Payment Systems
  topic: keywords
subject: Transaction Analysis
  topic: keywords
subject: Case Study
  topic: keywords
creator: Tuyi Musindemuka
creator: Habyarimana Nsizi
creator: Kabesee Rwihanga
creator: Ingabira Nwambya
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-02-15
publication date: 2002-02-15
doi: 10.5281/zenodo.18746678

Methodological Evaluation of Transport Maintenance Depot Systems in Nigerian Agricultural Supply Chains
type: item
description: In Nigeria, agricultural supply chains face significant logistical challenges that affect yield stability and farmer income. The inefficiencies in transport maintenance depots (TMDs) have been identified as critical bottlenecks. A DiD model was employed to analyse yield data from two sets of farms: those that benefitted from improved TMD services and a control group. Data collection included pre- and post-intervention periods for comprehensive analysis. The DiD analysis revealed a statistically significant increase in yields by approximately 15% among the beneficiary farms, indicating substantial improvements attributable to enhanced TMD maintenance. The findings confirm that improved TMD systems have a measurable positive impact on agricultural yield, providing empirical evidence for policy support and investment in these infrastructure enhancements. Based on this study, it is recommended that Nigerian policymakers consider investing in comprehensive TMD upgrades to ensure stable and increased crop yields across the country’s agricultural sectors. 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: African geography
  topic: keywords
subject: supply chain management
  topic: keywords
subject: maintenance depots
  topic: keywords
subject: transport logistics
  topic: keywords
subject: difference-in-differences
  topic: keywords
subject: econometrics
  topic: keywords
subject: agricultural economics
  topic: keywords
creator: Salihu Lawal
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-12-28
publication date: 2001-12-28
doi: 10.5281/zenodo.18729303

Bayesian Hierarchical Model Evaluation of Power-Distribution Equipment Systems in Kenya 2001
type: item
description: Power-distribution equipment systems in Kenya have been evaluated for their impact on agricultural yields. Previous studies have focused on yield improvements but lacked a comprehensive statistical framework to quantify these effects. A Bayesian hierarchical model was employed to analyse data from multiple fields across Kenya. The model accounts for spatial and temporal variability, providing robust estimates of yield improvements attributable to the use of power-distribution equipment. The analysis revealed a significant proportion (35%) of increased yields in irrigated plots compared to non-irrigated ones when using power-distribution systems optimised for water management. This study provides evidence that Bayesian hierarchical models can effectively quantify the impact of power-distribution equipment on agricultural yield improvements, offering insights for policy and investment decisions. Policy makers should consider investing in power-distribution infrastructure that is optimised for water management to maximise yield improvements in Kenya's agricultural sector. 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: Kenya
  topic: keywords
subject: Bayesian
  topic: keywords
subject: Hierarchical
  topic: keywords
subject: Model
  topic: keywords
subject: Estimation
  topic: keywords
subject: Evaluation
  topic: keywords
subject: Methodology
  topic: keywords
creator: Oscar Mbugua Nyangwaa
creator: Mugambi Kinyanjui Muiruri
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-01-08
publication date: 2001-01-08
doi: 10.5281/zenodo.18729288

Mobile Payment Systems in Urban Porters Association
type: item
description: Urban porters in Dar es Salaam, Tanzania face significant financial challenges related to irregular earnings from their daily work. Microfinance providers are seeking innovative ways to enhance financial inclusion among this group through mobile payment systems. A mixed-methods approach was employed, including quantitative surveys to measure financial inclusion rates and qualitative interviews to understand user experiences and perceptions. Data collection took place over a six-month period. Among the surveyed participants, 75% reported an increase in their ability to save money through mobile payments, with a notable theme of reduced cash handling risks identified as a key benefit. The introduction of mobile payment systems has significantly improved financial inclusion rates among urban porters, though challenges such as high initial costs and technical literacy barriers persist. Further training on the use of mobile payments should be provided to address remaining user concerns. Microfinance providers could consider subsidizing or offering low-interest loans for hardware purchases. 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: Urban
  topic: keywords
subject: Geography
  topic: keywords
subject: Microfinance
  topic: keywords
subject: Payment Systems
  topic: keywords
subject: Methodology
  topic: keywords
subject: Financial Inclusion
  topic: keywords
subject: Tanzania
  topic: keywords
creator: Mwihigo Simon Mrema
creator: Kibet Benedict Kamau
creator: Mushtaq Ali Binnoi
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-09-20
publication date: 2000-09-20
doi: 10.5281/zenodo.18712767

Bayesian Hierarchical Model for Measuring Efficiency Gains in Municipal Infrastructure Assets Systems in Kenya
type: item
description: The efficiency of municipal infrastructure assets systems in Kenya is crucial for urban development and service provision. However, current methods often lack precision and can be biased due to variability across different asset types and jurisdictions. A Bayesian hierarchical model was developed to estimate performance metrics of municipal infrastructure assets, considering both fixed effects (such as jurisdictional differences) and random effects (asset-specific variations). The model revealed significant efficiency gains in the water supply sector compared to other sectors, with an estimated improvement rate of around 15% across all jurisdictions. This study demonstrated that the proposed Bayesian hierarchical model can effectively quantify efficiency improvements in municipal infrastructure systems, providing a robust framework for future research and policy development. Municipal authorities should prioritise investments in sectors where substantial gains are observed to maximise resource allocation efficiency. Bayesian Hierarchical Model, Municipal Infrastructure, Efficiency Gains, 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: Bayesian
  topic: keywords
subject: Hierarchical
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Asset Management
  topic: keywords
subject: Efficiency
  topic: keywords
subject: Optimization
  topic: keywords
creator: Koinange Gitonga
creator: Njoroge Ochieng
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-06-22
publication date: 2000-06-22
doi: 10.5281/zenodo.18712675