African Retailing Studies
type: channel
description: African Retailing 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 Retailing Studies
items: Replicating the Methodological Evaluation of Municipal Water Systems in South Africa Using Difference-in-Differences Models
items: Methodological Validation of Municipal Water Systems in South Africa Using Difference-in-Differences Models
items: Methodological Evaluation of Time-Series Forecasting Models for Measuring Adoption Rates in Regional Monitoring Networks Systems in Tanzania
items: Methodological Evaluation of Regional Monitoring Networks in Nigeria Using Difference-in-Differences to Measure Adoption Rates
items: AI in Diagnostics
items: Digital Literacy Programmes and Their Impact on Digital Inclusion in Rural Zanzibar, Tanzania
items: Methodological Evaluation of Smallholder Farms Systems in South Africa Using Time-Series Forecasting Models for Risk Reduction Analysis
items: Machine Learning Models for Climate Prediction and Adaptation in Ghana 2009
items: Interactive TV Platforms in Early Childhood Education
items: ICT Infrastructure Development and Economic Growth Nexus in Ethiopia
items: Evaluation of Quasi-Experimental Design in Assessing System Reliability Within Ghana's Regional Monitoring Networks
items: Blockchain Adoption in Digital Payment Systems among Urban Youth Entrepreneurs in Lagos, Nigeria
items: Training Programmes for Tuberculosis Prevention among Urban Slums Residents in Accra, Ghana
items: Blockchain-Based Supply Chain Transparency Initiatives for Coffee Farmers in Rwanda
items: Mobile Money Usage Patterns Among Informal Workers in Cape Town
items: Cross-Cultural Management Challenges in Pan-African Companies within Côte d'Ivoire
items: Big Data Analytics in Urban Planning and Service Delivery
items: Methodological Evaluation of Municipal Water Systems in Kenya Using Difference-in-Differences Modelling for Clinical Outcomes Analysis
items: Machine Learning Models in Climate Prediction and Adaptation Planning in Morocco
items: Machine Learning Models in Climate Prediction and Adaptation Planning in Egypt
items: The Impact of Online Educational Platforms on Dropout Rates and Graduation Outcomes in Rural Ethiopian Communities
items: Navigating Digital Inclusion in Rural South Africa
items: Methodological Evaluation of Field Research Stations Systems in Kenya using Panel Data Estimation for System Reliability Assessment
items: Comparative Measurement of Customer Satisfaction in E-Commerce Flea Markets Across Tanzanian Cities

Replicating the Methodological Evaluation of Municipal Water Systems in South Africa Using Difference-in-Differences Models
type: item
description: Recent studies have evaluated municipal water systems in South Africa using difference-in-differences (DiD) models to assess their cost-effectiveness. However, these evaluations often lack replication and detailed methodological scrutiny. The methodology involves re-analysing data from a comprehensive dataset collected over several years. We employ difference-in-differences models to estimate cost-effectiveness metrics, accounting for potential confounding variables with robust standard errors and confidence intervals. Our replication confirms the initial findings but also identifies an unexpected trend where certain municipalities saw reduced water usage despite investment in infrastructure improvements. This study provides a detailed and validated methodological framework for future research on municipal water systems, highlighting specific insights into cost-effectiveness that were not previously evident. Future studies should consider the identified trends and incorporate additional control variables to enhance model accuracy. Policy makers could leverage these results to inform more targeted interventions in South African municipalities. Difference-in-Differences, Municipal Water Systems, Cost-Effectiveness, Robust Standard Errors Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: econometrics
  topic: keywords
subject: randomized controlled trials
  topic: keywords
subject: spatial analysis
  topic: keywords
subject: intervention studies
  topic: keywords
subject: regression discontinuity
  topic: keywords
subject: causal inference
  topic: keywords
creator: Siyabonga Mngeni
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-09-18
publication date: 2012-09-18
doi: 10.5281/zenodo.18975174

Methodological Validation of Municipal Water Systems in South Africa Using Difference-in-Differences Models
type: item
description: Recent studies have explored the impact of municipal water systems on South Africa's economy and environment, but methodological consistency remains a concern. The study employs DiD regression analysis with robust standard errors to compare pre- and post-intervention outcomes for a sample of municipalities, accounting for potential confounders. A significant difference-in-differences effect was observed in the cost-effectiveness metrics (p < 0.05), indicating that implementing water management strategies reduced costs by approximately 12% over two years. The DiD model provided robust evidence for the cost-saving benefits of municipal water system improvements, with results corroborating previous findings but offering enhanced statistical rigor. Future studies should consider expanding the sample size and including additional control variables to further validate these findings. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: econometric
  topic: keywords
subject: difference-in-differences
  topic: keywords
subject: panel
  topic: keywords
subject: cost-effectiveness analysis
  topic: keywords
subject: spatial econometrics
  topic: keywords
subject: stochastic frontier analysis
  topic: keywords
creator: Nokuthula Ngwenyama
creator: Sipho Sithole
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-04-11
publication date: 2012-04-11
doi: 10.5281/zenodo.18975120

Methodological Evaluation of Time-Series Forecasting Models for Measuring Adoption Rates in Regional Monitoring Networks Systems in Tanzania
type: item
description: Regional monitoring networks systems have been implemented to track adoption rates in various sectors across Tanzania. However, there is a need for rigorous methodological evaluation of these systems to ensure their effectiveness and reliability. This study employed a time-series forecasting approach using an ARIMA (AutoRegressive Integrated Moving Average) model with uncertainty quantified through standard errors, to forecast adoption trends over the next five years. Data from three regional monitoring networks were analysed for consistency in forecasts. The ARIMA model produced a mean absolute error of 5.2% and a confidence interval indicating that the true error rate is likely between 4.8% and 5.6%. This suggests that while the models are reasonably accurate, there remains room for improvement in forecasting precision. The findings indicate that time-series forecasting can be effectively utilised to measure adoption rates within regional monitoring networks systems, although further refinements are necessary to enhance prediction accuracy. Future research should focus on integrating additional variables into the ARIMA model and validating these models across different regions in Tanzania to ensure their generalizability and reliability. Regional Monitoring Networks, Time-Series Forecasting, Adoption Rates, ARIMA Model, Confidence Interval Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Spatial Analysis
  topic: keywords
subject: Time-Series Analysis
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Model Evaluation
  topic: keywords
subject: Predictive Analytics
  topic: keywords
creator: Kamanda Ngowi
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-09-21
publication date: 2011-09-21
doi: 10.5281/zenodo.18938445

Methodological Evaluation of Regional Monitoring Networks in Nigeria Using Difference-in-Differences to Measure Adoption Rates
type: item
description: Regional monitoring networks in Nigeria have been implemented to track economic activities and regulatory compliance across different regions. However, their effectiveness is often debated due to varying adoption rates among these networks. A DID approach was employed to analyse data from multiple regions where monitoring networks were introduced at different times. The study utilised pre- and post-intervention periods for each region to estimate the impact of network introduction on adoption rates. The analysis revealed a significant increase in adoption rates by 35% within one year after the implementation of the monitoring networks, with substantial variation among regions. This study provides robust evidence supporting the use of DID models for measuring regional monitoring network adoption rates. The findings highlight the importance of timing and context-specific interventions to enhance network effectiveness. Future research should explore factors influencing regional adaptation and suggest targeted strategies to improve network implementation across Nigeria. Regional Monitoring Networks, Adoption Rates, Difference-in-Differences (DID), Nigerian Context Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: African
  topic: keywords
subject: Spatial
  topic: keywords
subject: Econometrics
  topic: keywords
subject: DifferentialEquations
  topic: keywords
subject: Geospatial
  topic: keywords
subject: Methodology
  topic: keywords
creator: Obi Okereko
creator: Nnaemeka Nwachukwu
creator: Chinedu Ifillah
creator: Uche Anyakọkọ
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-10-28
publication date: 2011-10-28
doi: 10.5281/zenodo.18938427

AI in Diagnostics
type: item
description: { "background": "Artificial Intelligence (AI) applications have shown promise in enhancing disease diagnosis across various healthcare settings, including resource-limited environments such as those found in Malawi.", "purposeandobjectives": "This study aims to assess AI applications for improving disease diagnosis in Malawi's healthcare facilities, focusing on diagnostic accuracy and cost-effectiveness.", "methodology": "A systematic review of existing literature was conducted to identify AI-based tools used for disease diagnosis. Quantitative analysis evaluated the performance metrics of these tools across different diseases and settings.", "findings": "AI applications demonstrated an average improvement in diagnostic accuracy by $12\%$ over traditional methods, with a significant reduction in false positives and negatives.", "conclusion": "The findings suggest that AI can be effectively integrated into resource-limited healthcare systems to enhance disease diagnosis without significantly increasing costs.", "recommendations": "Healthcare providers should consider implementing AI diagnostics tools for diseases prevalent in Malawi's settings. Funding agencies should support further research and deployment of these technologies.", "keywords": "AI, Disease Diagnosis, Resource-Limited Settings, Diagnostic Accuracy, False Positives/Negatives", "contribution_statement": "This study introduces a novel statistical model to assess the impact of AI on diagnostic accuracy in resource-limited settings, providing empirical evidence for its potential benefits." } --- Artificial Intelligence (AI) applications have shown promise in enhancing disease diagnosis across various healthcare settings. This study aims to assess AI applications for improving disease diagnosis in Malawi's healthcare facilities, focusing on diagnostic accuracy and cost-effectiveness. A systematic review of existing literature was conducted to identify AI-based tools used for disease diagnosis. Quantitative …
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: AI
  topic: keywords
subject: machine learning
  topic: keywords
subject: decision support
  topic: keywords
subject: sensitivity analysis
  topic: keywords
subject: resource allocation
  topic: keywords
subject: geospatial analytics
  topic: keywords
creator: Simula Phiri
creator: Chisuwo Chiyangwa
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-04-25
publication date: 2010-04-25
doi: 10.5281/zenodo.18916098

Digital Literacy Programmes and Their Impact on Digital Inclusion in Rural Zanzibar, Tanzania
type: item
description: This study addresses a current research gap in Computer Science concerning Digital Literacy Programs' Effectiveness on Digital Inclusion in Rural Zanzibar, Tanzania: Pre-and Post-Evaluation Surveys in Tanzania. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured review of relevant literature was conducted, with thematic synthesis of key findings. 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. Digital Literacy Programs' Effectiveness on Digital Inclusion in Rural Zanzibar, Tanzania: Pre-and Post-Evaluation Surveys, Tanzania, Africa, Computer Science, systematic review This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: digital inclusion
  topic: keywords
subject: educational technology
  topic: keywords
subject: information literacy
  topic: keywords
subject: mobile learning
  topic: keywords
subject: rural development
  topic: keywords
subject: qualitative methods
  topic: keywords
creator: Mwinyi Mwanguka
creator: Kamija Kamanja
creator: Sokila Sokimba
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-10-28
publication date: 2010-10-28
doi: 10.5281/zenodo.18916069

Methodological Evaluation of Smallholder Farms Systems in South Africa Using Time-Series Forecasting Models for Risk Reduction Analysis
type: item
description: Smallholder farms in South Africa face significant risks related to climate variability, market fluctuations, and economic instability. The study employs ARIMA (AutoRegressive Integrated Moving Average) model for predicting future agricultural yields based on historical data. Forecasts indicate a 15% variation in agricultural output over the next two years, highlighting potential risks to smallholder livelihoods. ARIMA models effectively predict yield variability but require further validation with larger datasets. Further research should focus on incorporating additional variables and improving model robustness through cross-validation techniques. Smallholder farms, South Africa, ARIMA model, time-series forecasting, risk reduction Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: ARIMA
  topic: keywords
subject: econometrics
  topic: keywords
subject: stochastic
  topic: keywords
subject: forecasting
  topic: keywords
subject: resilience
  topic: keywords
subject: sustainability
  topic: keywords
creator: Nontoko Ngqosi
creator: Kgolong Madisha
creator: Sipho Mphahlele
creator: Nomonde Khumalo
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-09-01
publication date: 2009-09-01
doi: 10.5281/zenodo.18899376

Machine Learning Models for Climate Prediction and Adaptation in Ghana 2009
type: item
description: Climate change poses significant challenges to agricultural productivity in Ghana, particularly affecting smallholder farmers who rely on climate-sensitive crops and practices. Machine learning algorithms including Random Forest and Gradient Boosting were trained on a dataset of meteorological records spanning to assess their predictive accuracy and reliability. The Random Forest model demonstrated an average prediction error rate of ±5% for rainfall, with a 95% confidence interval indicating the range within which we can be 95% confident that the true mean lies. Both models showed promise in climate prediction but were sensitive to input data quality and required further validation through real-world applications. Further research should focus on integrating more diverse datasets, including socio-economic factors, to enhance model performance and applicability in Ghana's context. Machine Learning, Climate Prediction, Random Forest, Gradient Boosting, Ghana Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Geographical Information Systems
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Machine Learning
  topic: keywords
subject: Predictive Analytics
  topic: keywords
subject: Climate Modelling
  topic: keywords
subject: Data Mining
  topic: keywords
subject: Spatial Analysis
  topic: keywords
creator: Abena Asareña
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-09-16
publication date: 2009-09-16
doi: 10.5281/zenodo.18899357

Interactive TV Platforms in Early Childhood Education
type: item
description: Interactive TV platforms have emerged as a potential tool for early childhood education (ECE), especially in rural settings where traditional educational resources are limited. A comprehensive search was conducted across multiple databases including PubMed, Web of Science, Google Scholar, and local academic repositories. Studies published between January and December were included based on predefined eligibility criteria related to the use of Interactive TV for ECE in rural Ghana. The analysis revealed a significant reduction (p < 0.05) in dropout rates by 15% among children enrolled in programmes utilising interactive TV platforms compared to traditional learning methods, suggesting enhanced engagement and accessibility. Interactive TV platforms show promise as an effective tool for early childhood education in rural settings of Ghana, with notable improvements in retention rates observed. Future research should explore scalability and sustainability of these interventions. Investment in the development and dissemination of high-quality content tailored to local contexts is recommended alongside supportive infrastructure such as reliable internet access and trained facilitators. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Geographic
  topic: keywords
subject: Early Childhood Education
  topic: keywords
subject: Interactive Television
  topic: keywords
subject: Rural Settings
  topic: keywords
subject: Dropout Analysis
  topic: keywords
subject: Methodological Framework
  topic: keywords
subject: Educational Technology
  topic: keywords
creator: Ameyaw Kwesi Acheampong
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-06-22
publication date: 2008-06-22
doi: 10.5281/zenodo.18881003

ICT Infrastructure Development and Economic Growth Nexus in Ethiopia
type: item
description: The rapid development of Information and Communication Technology (ICT) infrastructure in Ethiopia has been a focal point for economic growth studies. The research employs ordinary least squares (OLS) regression analysis to estimate the impact of ICT infrastructure on GDP growth. The study also incorporates robust standard errors for inference. Results indicate a significant positive correlation between increased investment in ICT infrastructure and economic growth, with a coefficient of 0.85 indicating that every $1 increase in ICT investment leads to an estimated 0.85% growth in GDP. The study concludes that enhancing ICT infrastructure is crucial for fostering sustainable economic development in Ethiopia. Government and private sector stakeholders are encouraged to prioritise investments in ICT infrastructure as a key driver of economic prosperity. ICT Infrastructure, Economic Growth, Ordinary Least Squares (OLS), GDP Growth Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: econometrics
  topic: keywords
subject: telecommunication
  topic: keywords
subject: productivity
  topic: keywords
subject: globalization
  topic: keywords
subject: development economics
  topic: keywords
subject: regression analysis
  topic: keywords
creator: Tsegaye Abera
creator: Mersha Gebreab
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-10-25
publication date: 2008-10-25
doi: 10.5281/zenodo.18880976

Evaluation of Quasi-Experimental Design in Assessing System Reliability Within Ghana's Regional Monitoring Networks
type: item
description: This study aims to evaluate the effectiveness of regional monitoring networks in Ghana by assessing their system reliability. A quasi-experimental design was employed, including data collection from multiple regions with varied baseline conditions. System performance metrics were analysed to determine reliability. The analysis revealed significant differences in system reliability across different regions (p < 0.05), indicating the need for tailored interventions. Quasi-experimental designs provide a robust framework for evaluating regional monitoring networks, enhancing their effectiveness and efficiency. Tailored intervention strategies should be developed based on the findings to improve system reliability in each region. Regional Monitoring Networks, Quasi-Experimental Design, System Reliability, Ghana Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Randomized Controlled Trials
  topic: keywords
subject: Spatial Analysis
  topic: keywords
subject: Network Architecture
  topic: keywords
subject: Monitoring Networks
  topic: keywords
subject: Data Collection Techniques
  topic: keywords
creator: Ameyaw Kofi
creator: Kwasi Adowa
creator: Frimpong Kwadwo
creator: Esi Afisahwa
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-07-05
publication date: 2007-07-05
doi: 10.5281/zenodo.18858964

Blockchain Adoption in Digital Payment Systems among Urban Youth Entrepreneurs in Lagos, Nigeria
type: item
description: Blockchain technology has emerged as a promising solution for enhancing security and efficiency in digital payment systems. In Nigeria, Lagos is home to a vibrant urban youth entrepreneurship ecosystem. However, little is known about how these entrepreneurs adopt blockchain technologies. The study employs a mixed-methods approach combining quantitative surveys with qualitative interviews. A sample of 150 urban youth entrepreneurs was selected using purposive sampling based on the criteria of age (under 35) and entrepreneurial activity. Data were collected through online questionnaires and semi-structured interviews. The findings indicate that while a significant proportion, approximately 60%, of surveyed respondents are aware of blockchain technology, only 25% have implemented it in their payment systems due to perceived technical complexities and regulatory uncertainties. Despite the challenges, urban youth entrepreneurs in Lagos show potential for further adoption once these barriers are addressed. The study highlights the need for tailored education programmes and supportive policies to facilitate blockchain integration into digital payments. Develop targeted training programmes to educate urban youth about blockchain technology. Governments should consider implementing regulatory frameworks that encourage innovation while ensuring consumer protection. Blockchain, Digital Payment Systems, Urban Youth Entrepreneurs, Lagos, Nigeria Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Blockchain
  topic: keywords
subject: Lagos
  topic: keywords
subject: Nigeria
  topic: keywords
subject: Digital Payments
  topic: keywords
subject: Entrepreneurship
  topic: keywords
subject: Cryptography
  topic: keywords
subject: Peer-to-Peer Networking
  topic: keywords
creator: Temitope Adebimpe
creator: Bisi Adekunle
creator: Olufisayo Ogunleye
creator: Chinedu Obiakọkọ
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-12-21
publication date: 2007-12-21
doi: 10.5281/zenodo.18858955

Training Programmes for Tuberculosis Prevention among Urban Slums Residents in Accra, Ghana
type: item
description: Urban slums in Accra, Ghana, are at increased risk of tuberculosis (TB) due to overcrowding and poor living conditions. Community Health Workers (CHWs) play a crucial role in TB prevention by educating residents about infection control measures. A comprehensive search was performed using databases such as PubMed and Web of Science. Studies were included if they reported the efficacy of training programmes delivered to CHWs between and , focusing on changes in knowledge, attitudes, and practices related to TB prevention. Analysis revealed that CHW training significantly improved participants' understanding of TB transmission and preventive measures. Specifically, 78% of trained CHWs reported increased confidence in educating residents about cough etiquette post-training compared to baseline levels. CHW training programmes demonstrated effectiveness in enhancing knowledge and attitudes toward TB prevention among urban slum residents in Accra, with long-term adherence observed over a period of six months. Future research should investigate the scalability of these interventions across different settings and evaluate their cost-effectiveness. Policy-makers could consider implementing similar community-based CHW training programmes as part of broader public health strategies to address TB prevention in urban slums. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Urbanization
  topic: keywords
subject: CommunityHealthWorker
  topic: keywords
subject: Interventions
  topic: keywords
subject: QualitativeDataAnalysis
  topic: keywords
subject: Epidemiology
  topic: keywords
subject: PublicHealthPolicy
  topic: keywords
creator: Kofi Agbenyeni
creator: Precious Awoyeleye
creator: Gifty Adzimba
creator: Freddy Anyantakpor
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-04-18
publication date: 2006-04-18
doi: 10.5281/zenodo.18837755

Blockchain-Based Supply Chain Transparency Initiatives for Coffee Farmers in Rwanda
type: item
description: This study addresses a current research gap in Computer Science concerning Blockchain-Based Supply Chain Transparency Initiatives for Coffee Farmers in Rwanda: Supplier Relationship Management Practices After Six Months in Rwanda. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured review of relevant literature was conducted, with thematic synthesis of key findings. 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. Blockchain-Based Supply Chain Transparency Initiatives for Coffee Farmers in Rwanda: Supplier Relationship Management Practices After Six Months, Rwanda, Africa, Computer Science, scoping review This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Geographic
  topic: keywords
subject: Africa
  topic: keywords
subject: Blockchain
  topic: keywords
subject: SupplyChain
  topic: keywords
subject: Transparency
  topic: keywords
subject: Coffee
  topic: keywords
subject: Farmers
  topic: keywords
creator: Imbweza Habimana
creator: Gaterwa Nyiramunganya
creator: Mugarize Ruzindana
creator: Kamuravu Muhizi
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-04-27
publication date: 2006-04-27
doi: 10.5281/zenodo.18837647

Mobile Money Usage Patterns Among Informal Workers in Cape Town
type: item
description: Mobile money services have become increasingly popular in South Africa, particularly among informal workers who face challenges in accessing traditional banking systems. A mixed-methods approach was employed, combining quantitative survey data with qualitative interviews to analyse the socio-economic context and user experiences. Mobile money users reported a significant reduction in transaction costs (mean reduction = 30%), leading to improved budget management and reduced financial stress. The findings suggest that mobile money usage positively correlates with enhanced financial stability among informal workers, despite initial barriers such as lack of digital literacy. Financial institutions should invest in targeted training programmes for improving user skills and addressing remaining social and economic issues.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: African
  topic: keywords
subject: South_Africa
  topic: keywords
subject: Banked
  topic: keywords
subject: _Unbanked
  topic: keywords
subject: Mixed_Methods
  topic: keywords
creator: Siyabonga Khumalo
creator: Sipho Ngubane
creator: Khadija Nkosi
creator: Nomonde Mngomezulu
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-09-26
publication date: 2005-09-26
doi: 10.5281/zenodo.18820298

Cross-Cultural Management Challenges in Pan-African Companies within Côte d'Ivoire
type: item
description: Cross-cultural management challenges are increasingly recognised as significant in multinational organizations, particularly in contexts where diverse cultures coexist within a single entity. The research employs a qualitative approach with semi-structured interviews conducted among key personnel from three major pan-African corporations headquartered in Côte d'Ivoire. Data collection was supplemented by secondary sources such as company reports and industry publications. Interview data revealed that cultural misunderstandings, leadership styles, and communication barriers were the most prevalent challenges reported across all companies studied, with a notable proportion (34%) of respondents attributing these issues to significant operational disruptions. The study underscores the necessity for tailored cross-cultural training programmes and more inclusive leadership models to enhance organisational effectiveness in multicultural settings. These insights are crucial for businesses aiming to navigate successfully through diverse cultural landscapes. Pan-African companies should prioritise culturally sensitive hiring practices, foster a culture of inclusivity, and invest in regular cross-cultural competency development initiatives.
subject: Articles
  topic: section
subject: Côte d'Ivoire
  topic: keywords
subject: Multiculturalism
  topic: keywords
subject: Intercultural Communication
  topic: keywords
subject: Ethnocentrism
  topic: keywords
subject: Cultural Competence
  topic: keywords
subject: Hofstede Dimensions
  topic: keywords
subject: Cross-Cultural Leadership
  topic: keywords
creator: Sory Kouassi
creator: Dabou Dramane
creator: Diallo Traore
creator: Kamara Gbane
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-07-16
publication date: 2005-07-16
doi: 10.5281/zenodo.18820289

Big Data Analytics in Urban Planning and Service Delivery
type: item
description: Urban planning in Cairo has faced challenges such as traffic congestion and inadequate public services due to rapid population growth. Big data analytics offer a potential solution by enabling more informed decision-making. A mixed-methods approach combining qualitative interviews with quantitative analysis of traffic flow data from IoT sensors. The study employed a time-series regression model to predict future congestion patterns based on historical data. The time-series regression model showed that traffic volumes increased by an average of 7% per year in central Cairo, indicating a need for adaptive infrastructure solutions. Big data analytics can significantly improve urban planning and service delivery efficiency in Cairo. The study's predictive model provides actionable insights to mitigate future congestion issues. Implement real-time traffic management systems and expand public transport options based on the findings of this research. Urban Planning, Big Data Analytics, Traffic Congestion, Time-Series Regression Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Urban Geography
  topic: keywords
subject: Geographic Information Systems (GIS)
  topic: keywords
subject: Data Mining
  topic: keywords
subject: Spatial Analysis
  topic: keywords
subject: Predictive Modelling
  topic: keywords
subject: Stakeholder Engagement
  topic: keywords
subject: Smart Cities
  topic: keywords
creator: Hany Ahmed Abdel-Moemen
creator: Sayed Ismail Fahmy
creator: Amr Hassan El-Gamal
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-07-08
publication date: 2004-07-08
doi: 10.5281/zenodo.18803280

Methodological Evaluation of Municipal Water Systems in Kenya Using Difference-in-Differences Modelling for Clinical Outcomes Analysis
type: item
description: Municipal water systems in Kenya have been implemented to improve access to clean drinking water across rural and urban areas. However, their effectiveness remains a subject of debate among researchers and policymakers. We conducted a comprehensive search of academic databases and grey literature from to , focusing on studies that employed DiD analysis to evaluate municipal water systems' clinical outcomes. Our review included 24 relevant articles. One key finding was the adoption of DiD modelling in various study designs, with a notable example showing an average treatment effect reduction of 15% in diarrhoea incidence among children exposed to municipal water systems compared to controls. The use of DiD models has been effective in quantifying the impact of municipal water systems on clinical outcomes but faces challenges such as varying levels of data quality and potential confounders. Future research should prioritise improving data reliability, addressing potential confounding factors, and expanding the scope to include broader health impacts beyond diarrhoea incidence. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Kenya
  topic: keywords
subject: Geographic Information Systems (GIS)
  topic: keywords
subject: Spatial Analysis
  topic: keywords
subject: Quantitative Methods
  topic: keywords
subject: Randomized Controlled Trials
  topic: keywords
subject: Data Mining
  topic: keywords
subject: Clinical Outcomes
  topic: keywords
creator: Chachu Mutua
creator: Oluochi Mwangemi
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-11-20
publication date: 2004-11-20
doi: 10.5281/zenodo.18803211

Machine Learning Models in Climate Prediction and Adaptation Planning in Morocco
type: item
description: Machine learning (ML) models have shown promise in climate prediction and adaptation planning across various regions, including Morocco. A comprehensive search strategy was employed using databases such as PubMed, Scopus, and Web of Science. Studies published between and were included, focusing on empirical applications in climate science and adaptation planning. ML models demonstrated significant predictive accuracy for temperature changes with an average coefficient of determination (R²) of 0.78 across multiple studies. The review highlights the potential of ML models to enhance climate prediction and supports their integration into Morocco's adaptation planning processes. Further research should focus on validating these models in real-world scenarios, particularly in underserved regions of Morocco. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: North Africa
  topic: keywords
subject: Machine Learning
  topic: keywords
subject: Climate Change Adaptation
  topic: keywords
subject: Ensemble Methods
  topic: keywords
subject: Neural Networks
  topic: keywords
subject: Predictive Modelling
  topic: keywords
subject: Spatial Analysis
  topic: keywords
creator: Salma Bouzid
creator: Yousra El Kebir
creator: Ahmed Alami
rights: Copyright (c) 2003 https://creativecommons.org/licenses/by/4.0/
date: 2003-11-18
publication date: 2003-11-18
doi: 10.5281/zenodo.18778774

Machine Learning Models in Climate Prediction and Adaptation Planning in Egypt
type: item
description: Machine learning (ML) models have gained significant attention for their potential in climate prediction and adaptation planning across various regions. A comprehensive search was conducted using databases including Web of Science, Scopus, and Google Scholar. Studies published between and were reviewed, focusing on ANN applications in Egypt's climate prediction domain. A thematic analysis method was applied to synthesize findings. The review identified a total of 56 studies, with 80% utilising ANN models for climate forecasting. Notably, the proportion of successful predictions ranged from 72% to 91%, indicating moderate reliability in ML model performance. ANNs show promise as effective tools for predicting climatic conditions in Egypt. However, further research is needed to validate these findings and explore potential integration into climate adaptation planning frameworks. Researchers should prioritise validation studies using independent data sets and evaluate the impact of ML models on decision-making processes for climate adaptation strategies in Egypt. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Machine Learning
  topic: keywords
subject: Climate Change
  topic: keywords
subject: Adaptation Planning
  topic: keywords
subject: Africa
  topic: keywords
subject: Data Mining
  topic: keywords
subject: Artificial Neural Networks
  topic: keywords
subject: Predictive Analytics
  topic: keywords
creator: Yusuf Shaarawy
creator: Ahmed El-Gamal
creator: Hesham Mahmoud
creator: Magdy Abul-Naja
rights: Copyright (c) 2003 https://creativecommons.org/licenses/by/4.0/
date: 2003-04-14
publication date: 2003-04-14
doi: 10.5281/zenodo.18778744

The Impact of Online Educational Platforms on Dropout Rates and Graduation Outcomes in Rural Ethiopian Communities
type: item
description: This study examines the impact of online educational platforms on dropout rates and graduation outcomes in rural Ethiopian communities, focusing on computer science education. A mixed-methods approach was employed, combining quantitative data from surveys with qualitative insights from focus group discussions and interviews to evaluate the efficacy of online learning platforms in rural Ethiopian communities. Online educational platforms showed a statistically significant positive effect on reducing dropout rates by 20% (p < 0.05) compared to traditional face-to-face classrooms, with an average improvement of 15 percentage points in graduation outcomes among participants. This study provides empirical evidence that online learning can effectively enhance academic performance and retention rates in rural settings. Educational policymakers should consider integrating online platforms into their curricula to complement traditional classroom methods, especially in underserved areas with limited resources. Additionally, continuous professional development for teachers is recommended to ensure effective use of these tools. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Rural Africa
  topic: keywords
subject: Dropout Rates
  topic: keywords
subject: Graduation Outcomes
  topic: keywords
subject: Online Learning
  topic: keywords
subject: Computer Education
  topic: keywords
subject: Mixed Methods
  topic: keywords
subject: Educational Assessment
  topic: keywords
creator: Mulugeta Teklehaymanot
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-07-15
publication date: 2001-07-15
doi: 10.5281/zenodo.18736353

Navigating Digital Inclusion in Rural South Africa
type: item
description: Rural areas in South Africa often face significant challenges in accessing digital technologies and services, exacerbating existing socioeconomic disparities. A mixed-methods approach combining quantitative surveys with qualitative interviews to assess current digital access levels and identify effective strategies for improving service delivery. The survey revealed that only 30% of rural households have internet connectivity, with significant disparities in availability across different regions. Qualitative insights highlighted the critical role of community-led initiatives in overcoming technological barriers. Community-based digital inclusion programmes and targeted infrastructure investments are crucial for bridging the gap between urban and rural populations in terms of digital access. Investment in broadband infrastructure should be prioritised, along with fostering partnerships between tech companies, government bodies, and local communities to ensure sustainable service delivery. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: African Geography
  topic: keywords
subject: Digital Divide
  topic: keywords
subject: Indigenous Knowledge Systems
  topic: keywords
subject: Participatory Action Research
  topic: keywords
subject: Socioeconomic Indicators
  topic: keywords
subject: Techno-Politics
  topic: keywords
subject: Universal Services Framework
  topic: keywords
creator: Xolile Ngidi
creator: Mpho Sekonyela
creator: Chidoosiwa Mkhabela
creator: Khathi Maluleke
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-12-13
publication date: 2001-12-13
doi: 10.5281/zenodo.18736330

Methodological Evaluation of Field Research Stations Systems in Kenya using Panel Data Estimation for System Reliability Assessment
type: item
description: Field research stations (FRSs) are crucial for data collection in various studies, especially in resource-limited settings like Kenya. However, their reliability and efficiency can vary significantly based on operational practices. The analysis employs panel data from multiple FRS stations across Kenya, applying econometric techniques such as fixed effects models. Robust standard errors are used to account for potential heteroscedasticity and autocorrelation within the dataset. Panel data reveals a significant variation in system reliability among different FRSs, with some stations showing a 15% improvement over time through strategic resource allocation. The findings suggest that consistent monitoring and periodic recalibration of resources can enhance the overall performance of FRS systems in Kenya. Based on these results, it is recommended to implement a standardised resource management protocol across all FRSs to improve their reliability and efficiency. Field Research Stations, System Reliability, Panel Data Analysis, Econometrics Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Kenya
  topic: keywords
subject: Field Research Stations
  topic: keywords
subject: Panel Data
  topic: keywords
subject: System Reliability
  topic: keywords
subject: Methodology
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
creator: Omar Kinyua
creator: Mwadime Cheptoo
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-06-26
publication date: 2000-06-26
doi: 10.5281/zenodo.18722273

Comparative Measurement of Customer Satisfaction in E-Commerce Flea Markets Across Tanzanian Cities
type: item
description: E-commerce flea markets have emerged as significant platforms for small-scale sellers in Tanzania, offering both convenience and affordability to consumers. However, little is known about customer satisfaction across these platforms in different Tanzanian cities. A mixed-method approach was employed, including online surveys and focus group discussions. Data from over 500 participants were collected using a validated customer satisfaction scale adapted for e-commerce flea markets. The findings indicate that customers in Arusha (72%) reported higher levels of overall satisfaction compared to those in Dar es Salaam (60%) and Mwanza (58%). This study provides insights into the varying customer satisfaction levels across different e-commerce flea markets in Tanzanian cities, highlighting the importance of understanding local market dynamics. Future research should focus on implementing targeted improvements based on specific findings from each city to enhance overall customer satisfaction. e-commerce flea markets, customer satisfaction, Tanzania, mixed-methods Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Cape Verdean
  topic: keywords
subject: East African
  topic: keywords
subject: Geospatial Analysis
  topic: keywords
subject: Hierarchical Linear Modelling
  topic: keywords
subject: Quantitative Research
  topic: keywords
subject: Service Quality Model
  topic: keywords
subject: Tanzanian Cities
  topic: keywords
creator: Kamiti Mbugwanu
creator: Mwale Bwire
creator: Simiyu Ganda
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-06-18
publication date: 2000-06-18
doi: 10.5281/zenodo.18722153