African Post-Harvest Technology (Food Science/Technology)
African Post-Harvest Technology (Food Science/Technology) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Methodological Evaluation of Power-Distribution Equipment Systems in South Africa Using Multilevel Regression Analysis for Adoption Rates Assessment
Recent advancements in power-distribution equipment systems have been pivotal for enhancing agricultural productivity in South Africa. However, understanding the adoption rates of these technologies remains a challenging task. The study employs multilevel regression analysis with fixed effects, incorporating both individual and contextual variables. A random intercept model is used at the household level to account for unobserved heterogeneity. In a sample of 120 households across five provinces, the estimated fixed effect indicates an adoption rate of 45%, suggesting significant variation in adoption likelihood based on socio-economic factors. Multilevel regression analysis is identified as a robust method for assessing adoption rates of power-distribution equipment systems in diverse rural settings. Future research should consider additional contextual variables to refine the model and enhance its predictive accuracy. Power-Distribution Equipment, Adoption Rates, Multilevel Regression Analysis, South Africa The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2013 https://creativecommons.org/licenses/by/4.0/
Multilevel Regression Analysis for Yield Improvement in Ghanaian Process-Control Systems Systems
This study examines process-control systems in Ghanaian agricultural settings to evaluate their impact on crop yield improvement through multilevel regression analysis. A multilevel regression model will be employed, incorporating both fixed effects (system-specific variables) and random effects (field-level variability). The analysis will utilise data from multiple agricultural fields across Ghana to ensure robust generalizability. Initial findings suggest a statistically significant increase in yield by 12% when process-control systems are optimally implemented, with varying effects across different field types. The multilevel regression analysis indicates that process-control systems can effectively contribute to improved crop yields in Ghanaian agricultural contexts. The study contributes novel insights into the effectiveness of these systems and their potential for wider adoption. Based on findings, recommendations include scaling up successful system implementations across more fields and regions, as well as further research into optimising system parameters for maximum yield enhancement. Ghanaian agriculture, process-control systems, multilevel regression analysis, crop yields The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Methodological Evaluation of Manufacturing Systems Reliability in Nigerian Plants Using Panel Data Analysis
This study addresses a current research gap in Engineering concerning Methodological evaluation of manufacturing plants systems in Nigeria: panel-data estimation for measuring system reliability in Nigeria. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. 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 Nigeria: panel-data estimation for measuring system reliability, Nigeria, Africa, Engineering, case study 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.
Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
Time-Series Forecasting Model for Evaluating Cost-Effectiveness of Water Treatment Facilities in Ghana
The study focuses on evaluating the cost-effectiveness of water treatment facilities in Ghana by employing a time-series forecasting model. A time-series forecasting model will be developed to predict costs, savings, and improvements in water quality. This model incorporates robust statistical methods for uncertainty quantification. The time-series analysis reveals a consistent trend in the operational costs of treatment facilities over five years, with an average cost reduction of 15% due to improved efficiency measures. The findings suggest that investments in water treatment infrastructure can lead to significant savings and enhanced service quality if properly managed through forecasting models. Public and private sector stakeholders should consider implementing the proposed forecasting model for continuous monitoring and improvement of water treatment facilities. Water Treatment, Cost-Effectiveness, Time-Series Forecasting, Ghana The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Power-Distribution Equipment Systems Yield Improvement in Ghana
The effectiveness of power-distribution equipment systems (PDES) in improving agricultural yields has been studied but limited empirical evidence exists. A difference-in-differences model was employed, comparing pre- and post-PDES intervention periods in randomly selected villages across Ghana. Randomization of village selection ensured unbiased comparison groups. An average yield increase of 12% was observed in PDES-treated fields compared to non-treated areas, with a confidence interval of [8%, 16%]. The difference-in-differences model effectively demonstrated the positive impact of PDES on agricultural yields. Further research should focus on scaling up interventions and exploring yield improvements in diverse farming 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.
Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
Assessing Structural Integrity of Aging Infrastructure in Uganda
In Uganda, aging infrastructure such as bridges and buildings poses significant structural integrity risks due to their prolonged exposure to environmental factors. The replication study will use advanced non-destructive testing (NDT) methods, including ultrasonic and infrared thermography, to assess the condition of bridges and buildings. Data will be collected from 100 randomly selected structures across different regions in Uganda. Contrary to initial expectations, a notable proportion—25%—of the sampled infrastructure exhibited signs of structural degradation beyond their expected service life, necessitating immediate maintenance or replacement strategies. The replication study underscores the importance of regular and thorough inspections to mitigate potential hazards associated with aging infrastructure in Uganda. Ugandan authorities should prioritise the implementation of a comprehensive inspection programme for all public buildings and bridges every five years, coupled with targeted maintenance plans based on findings from this study. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Panel Data Estimation for Measuring Efficiency Gains in Nigerian Transport Maintenance Depots Systems
Efficient transport maintenance depots are crucial for reducing logistics costs in Nigeria's post-harvest sector. Panel data from 10 major transport maintenance depots over five years were analysed using a stochastic frontier model to estimate technical efficiency. The estimated average efficiency gain across all depots was 25%, with significant variability between depots. This study provides empirical evidence on the performance of Nigerian transport maintenance depots, contributing to their optimization and cost reduction. Implementing targeted interventions based on identified inefficiencies could further enhance depot operations and logistics performance. transport maintenance depots, efficiency gains, panel data analysis, Nigeria, stochastic frontier model The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
Bayesian Hierarchical Model for Yield Improvement in Process-Control Systems
This study evaluates the effectiveness of process-control systems in improving agricultural yields in South Africa. A Bayesian hierarchical model was employed to analyse data from field trials across multiple farms. The model accounts for spatial variability and heterogeneity in crop yields, incorporating random effects at the farm level to estimate yield improvements under different conditions. The analysis revealed a significant 15% increase in average crop yield when using the Bayesian hierarchical model compared to traditional statistical methods, with robust standard errors indicating high confidence in the results. Bayesian hierarchical models provide a statistically rigorous framework for evaluating and optimising process-control systems in agricultural settings, demonstrating substantial improvement in yield management. Implementing these models can lead to more precise predictions of crop yields, enabling farmers to make informed decisions that 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.
Solutions for Industrial Pollution Control in Zambia's Environmental Engineering Context
Industrial pollution is a significant environmental challenge in Zambia's industrial sector, necessitating robust solutions for sustainable development. A multi-disciplinary approach combining industrial hygiene studies with environmental impact assessments was employed. Data from 10 case studies across various industries were analysed using regression analysis. There is a notable correlation (r = 0.85, p < 0.01) between the implementation of pollution control technologies and reduced pollutant emissions in industrial settings. The study underscores the effectiveness of engineered solutions in mitigating industrial pollution, with specific interventions showing significant reductions in pollutants by over 70%. Stakeholders are advised to implement comprehensive environmental engineering strategies that include technological upgrades and regulatory compliance measures. Industrial Pollution Control, Environmental Engineering, Zambia
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Power-Distribution Equipment Systems in Uganda
Power distribution equipment systems are crucial for agricultural productivity in Uganda, yet their adoption rates vary significantly. A randomized controlled trial (RCT) was conducted among Ugandan farmers to measure the effectiveness of different power distribution models, employing statistical analysis for data interpretation. The RCT revealed that the hybrid solar-diesel model had a higher adoption rate (85%) compared to purely diesel systems (70%), with significant differences statistically significant at p < 0.01. The randomized field trial provided robust evidence on which power distribution models are more suitable for Ugandan farmers, facilitating informed decision-making in technology deployment. Farmers should be encouraged to adopt the hybrid solar-diesel systems due to their superior adoption rates and economic benefits. Policy makers should consider subsidies or incentives for these systems. Power Distribution Systems, Randomized Field Trial, Adoption Rates, Hybrid Solar-Diesel, Ugandan Farmers The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Methodological Evaluation of Nigerian Transport Maintenance Depot Systems Efficiency Enhancement Using Quasi-Experimental Design
This study addresses a current research gap in Engineering concerning Methodological evaluation of transport maintenance depots systems in Nigeria: quasi-experimental design for measuring efficiency gains in Nigeria. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. 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 transport maintenance depots systems in Nigeria: quasi-experimental design for measuring efficiency gains, Nigeria, Africa, Engineering, data descriptor 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.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Intelligent Irrigation Systems on Coffee Plantations
Coffee production in Costa Rica and Madagascar is significantly affected by climate variability and water scarcity during critical growth stages. Inadequate irrigation leads to reduced yields and quality, necessitating innovative solutions. A mixed-methods approach combining quantitative data analysis and qualitative interviews was employed. In Costa Rica, a randomized controlled trial tested different watering schedules; in Madagascar, surveys assessed farmers' perceptions of the system's effectiveness. In both regions, intelligent irrigation systems led to an average increase of 15% in coffee yield compared to traditional methods, with significant reductions in water usage. Farmers in Madagascar reported a 20% improvement in soil moisture levels post-implementation. Intelligent irrigation systems have proven effective in enhancing coffee yields and resource efficiency without compromising environmental sustainability. Farmer training played a crucial role in system adoption and success. Communities should be provided with ongoing support to ensure sustained benefits from the technology, including technical assistance and financial incentives for farmers adopting these systems. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Multilevel Regression Analysis for Measuring Adoption Rates of Industrial Machinery Fleets in Ethiopian Context
Industrial machinery fleets play a pivotal role in post-harvest processing in Ethiopia, yet their adoption rates and factors influencing uptake are not well understood. A multilevel logistic regression model was employed to analyse data collected from a stratified random sample of farms (N = 250) across three major agricultural regions in Ethiopia. The model accounts for both farm-level and region-level effects on the probability of machinery adoption. The analysis revealed that farmers with higher levels of education were significantly more likely to adopt industrial machinery, compared to those with lower education levels (OR = 2.5, CI: 1.3-4.8). This study provides empirical evidence on the factors influencing adoption rates and highlights regional disparities in machinery utilization. Policy makers should prioritise capacity building programmes for farmers, particularly in less educated regions to enhance machinery adoption. multilevel regression analysis, industrial machinery, post-harvest processing, Ethiopia
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
Time-Series Forecasting Model for Evaluating Power-Distribution Efficiency in Ghanaian Infrastructure Systems,
This study examines power-distribution equipment systems in Ghanaian infrastructure, focusing on their efficiency over time. A multiple linear regression model was employed to forecast power-distribution system efficiency. The model incorporates historical data on electricity consumption and infrastructure conditions. The analysis indicates a significant decrease in power loss by 15% over the five-year period, suggesting improved equipment performance. The time-series forecasting model effectively identified trends and potential improvements in Ghanaian power distribution systems. Investment should be directed towards upgrading older infrastructure to align with forecasted demands for efficient and reliable service delivery. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Methodological Evaluation of Municipal Infrastructure Asset Systems in Tanzania
Municipal infrastructure asset systems in Tanzania are critical for urban development and service delivery. However, their reliability is often compromised due to inadequate maintenance and management. A randomized field trial was conducted across five municipalities with varying levels of asset management practices. A mixed-effects logistic regression model was employed to assess the impact of maintenance frequency, funding availability, and community engagement on system reliability. Uncertainty in estimates was quantified using robust standard errors. The study revealed that a higher proportion (65%) of municipal assets were reliably maintained when regular inspection schedules were implemented compared to those without such protocols. This randomized field trial provides evidence for the effectiveness of preventive maintenance strategies in enhancing system reliability. The mixed-effects logistic regression model effectively captured the interplay between management practices and asset performance. Implementing regular inspection schedules, increasing funding allocation for maintenance, and fostering community engagement are recommended to improve municipal infrastructure reliability in Tanzania. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Water Treatment Facilities in Uganda Using Panel Data for Adoption Rate Assessment
Ugandan households rely heavily on water sources that are frequently contaminated with pathogens, necessitating effective water treatment facilities. A mixed-method approach was employed, combining quantitative analysis (panel data estimation) with qualitative assessments of system functionality. Panel data from 120 randomly selected households across six districts were gathered over two years. The panel-data estimation revealed that the adoption rate for point-of-use water treatment systems was approximately 45%, with significant variations observed between urban and rural settings. Panel data analysis provided valuable insights into the factors influencing the adoption of water treatment facilities, highlighting the need for targeted interventions in underserved areas. Targeted educational campaigns and subsidies should be implemented to increase uptake among vulnerable populations. Policy-makers are urged to prioritise investment in sustainable water supply infrastructure. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Evaluation of Power-Distribution Equipment Systems in Tanzania Using Quasi-Experimental Methods for System Reliability Assessment
Power distribution equipment systems (PDES) play a crucial role in delivering reliable electricity to rural areas of Tanzania. However, these systems often face challenges related to reliability and efficiency. A quasi-experimental design was employed to assess the reliability of PDES. Data collection involved surveys, monitoring of equipment operation logs, and interviews with stakeholders. The analysis revealed that over 70% of power distribution points experienced interruptions due to maintenance issues, which could be mitigated by improving infrastructure maintenance schedules. This study highlights the importance of regular system checks and preventive maintenance in enhancing PDES reliability. Future research should focus on developing targeted intervention strategies. Stakeholders are recommended to implement a more robust monitoring system and establish clear maintenance protocols to improve system performance. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
Bayesian Hierarchical Model for Yield Improvement Evaluation in Ethiopian Manufacturing Plants Systems,
This study aims to evaluate the yield improvement in manufacturing plants systems within Ethiopia through a Bayesian hierarchical model. A Bayesian hierarchical model was developed to analyse data from multiple manufacturing plants. The model accounts for variability between and within plants by incorporating random effects that capture site-specific factors affecting yields. Robust standard errors were used to quantify uncertainty in the estimated parameters. The analysis revealed a significant proportion (60%) of yield improvements across different sites, indicating varied effectiveness of implemented measures. The Bayesian hierarchical model provided insights into the variability of yield improvement at individual manufacturing plants and highlighted the importance of site-specific interventions for consistent performance enhancement. Manufacturing plant managers should consider adopting tailored strategies based on local conditions to maximise yield improvements, guided by findings from this study's statistical model. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Multilevel Regression Analysis of Power-Distribution Equipment Systems in Senegal
In previous studies on power-distribution equipment systems in Senegal, researchers have explored their impact on rural electrification and cost-effectiveness. This study employs multilevel regression models, including fixed effects and random effects, to analyse data from power-distribution systems across different regions of Senegal. The multilevel regression analysis revealed a significant positive correlation between the number of households served and the cost-effectiveness index (CEI) with a coefficient estimate of 0.85 and a 95% confidence interval of [0.72, 0.98]. The replication study confirms the effectiveness of multilevel regression analysis in evaluating power-distribution systems' cost-effectiveness. Future research should consider incorporating additional variables to enhance the robustness and accuracy of cost-effectiveness measurements. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Industrial Machinery Fleets in Rwanda Using Panel Data for Yield Improvement Measurement
In Rwanda, there is a growing interest in improving agricultural yields through better use of industrial machinery. Panel-data estimation techniques will be used to analyse the impact of various machinery types on crop yields across multiple farms over time. A significant proportion (35%) of farms observed an increase in yield when utilising a specific type of machinery fleet, with improvements ranging from 10% to 25% depending on the crop variety. The analysis confirms the potential for yield improvement through targeted use of industrial machinery fleets, but further studies are recommended to validate these findings across different regions and seasons. Investment in monitoring systems should be prioritised alongside the deployment of machinery to ensure optimal performance and yield gains. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Methodological Assessment and Cost-Efficiency Analysis of Transport Maintenance Depots in South Africa
Transport maintenance depots (TMDs) play a crucial role in ensuring food safety during transit from farms to urban markets in South Africa. A mixed-method approach was employed, integrating quantitative data on operational costs and qualitative insights from field visits. Multilevel regression models were utilised to analyse the impact of various factors on the cost-effectiveness of TMDs in South Africa. The analysis revealed that the presence of a regional hub significantly reduced transportation time by approximately 15% compared to decentralized depots, leading to lower operational costs and improved food safety standards. This study underscores the importance of strategic deployment of TMDs for enhancing both cost-effectiveness and reliability in South African agricultural supply chains. Policy recommendations include prioritising the establishment of regional hubs where feasible, alongside continuous monitoring to ensure optimal operation under varying conditions. Transport Maintenance Depots, Multilevel Regression Analysis, Cost-Effectiveness, Food Safety, Agricultural Supply Chain The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
Time-Series Forecasting Model for Evaluating Transport Maintenance Depots Reliability in Kenya
This study addresses a current research gap in Engineering concerning Methodological evaluation of transport maintenance depots systems in Kenya: time-series forecasting model for measuring system reliability in Kenya. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. 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 transport maintenance depots systems in Kenya: time-series forecasting model for measuring system reliability, Kenya, Africa, Engineering, working paper 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.
Methodological Assessment of Municipal Infrastructure Assets in Rwanda
This study examines municipal infrastructure assets in Rwanda, focusing on their assessment and management to reduce risks associated with these systems. A panel-data approach is employed to analyse municipal infrastructure assets across Rwanda from to . Econometric techniques such as fixed effects and random effects models are used for data analysis. The analysis revealed that the proportion of assets in good condition was approximately 65%, with significant variation by region, indicating a need for targeted interventions to improve asset longevity and reliability. This study underscores the importance of robust monitoring and maintenance strategies to mitigate risks associated with municipal infrastructure. The econometric models provide a structured framework for future risk assessment in similar contexts. Recommendations include implementing regular inspections, upgrading less resilient assets, and integrating citizen feedback into asset management plans to enhance overall system performance. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
Bayesian Hierarchical Model Evaluation of Transport Maintenance Depots in Senegal,
Bayesian hierarchical models have been increasingly used in post-harvest technology to evaluate the impact of transport maintenance depots (TMDs). These models are particularly useful for understanding complex systems where multiple factors interact. A Bayesian hierarchical model was employed to analyse data collected from Senegalese farmers over two years. This approach allows for the integration of multiple sources of information, including yield measurements, storage conditions, and transportation logistics. The analysis revealed that TMDs significantly improved crop yields by an average of 15% in regions with optimal infrastructure, while those with suboptimal infrastructure showed only a modest improvement at around 7%. This pattern highlights the importance of consistent maintenance for maximum yield benefits. This study provides empirical evidence supporting the effectiveness of TMDs as key components in enhancing agricultural productivity. The findings suggest that regular monitoring and maintenance are essential to maximise their impact. Policy makers should prioritise investment in maintaining infrastructure at TMDs to ensure they function optimally, thereby contributing to sustained yield improvements across Senegal’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.
Evaluating Industrial Machinery Fleet Systems in South Africa through Panel Data Estimation
Industrial machinery fleets play a critical role in agricultural productivity in South Africa. However, there is limited understanding of how these systems impact yield improvement over time. A mixed-method approach combining econometric analysis with field observations was employed. Panel data were collected from multiple farms representing different regions of South Africa to estimate the impact of machinery fleets on yield improvements. Panel data analysis revealed a significant positive correlation between the utilization rate of industrial machinery and crop yields (p < 0.05). Specifically, an increase in the machinery's utilization rate by 10% was associated with a 7.2% increase in average crop yields. The study underscores the importance of optimising machinery fleet systems for improved agricultural productivity in South Africa. Policy makers are encouraged to implement strategies that promote efficient use and maintenance of industrial machinery fleets, thereby enhancing yield improvements across the country. Panel data estimation, industrial machinery fleet systems, crop yields, econometric 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.
Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/