Multilevel Regression Analysis of Process-Control Systems in Tanzanian Agricultural Yield Improvement Context

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Autori principali: Mwakwere, Ali, Ngowi, Kamasi, Mvibwa, Zawadi, Makanda, Engelbert
Natura: Recurso digital
Lingua:inglese
Pubblicazione: Zenodo 2005
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author Mwakwere, Ali
Ngowi, Kamasi
Mvibwa, Zawadi
Makanda, Engelbert
author_facet Mwakwere, Ali
Ngowi, Kamasi
Mvibwa, Zawadi
Makanda, Engelbert
contents <p>Process-control systems are pivotal in enhancing agricultural yields by optimising resource allocation and management practices. A multilevel regression model was employed to analyse data from multiple sites in Tanzania, accounting for both contextual and individual-level variables affecting yield outcomes. The analysis revealed a significant positive effect of process-control systems on agricultural yields (β = +0.35, p < 0.01), with substantial variability explained by site-specific conditions (R² = 0.45). Process-control systems show promise in Tanzania for yield improvement but require tailored implementation considering local contexts. Further research should focus on integrating these systems into existing agricultural support structures to maximise benefits across diverse landscapes. Agricultural Yield, Process-Control Systems, Multilevel Regression Analysis, Tanzanian Agriculture The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_18814428
institution Zenodo
language eng
publishDate 2005
publisher Zenodo
record_format zenodo
spellingShingle Multilevel Regression Analysis of Process-Control Systems in Tanzanian Agricultural Yield Improvement Context
Mwakwere, Ali
Ngowi, Kamasi
Mvibwa, Zawadi
Makanda, Engelbert
African geography
multilevel regression
process control
resource allocation
agricultural yield
econometrics
statistical methods
<p>Process-control systems are pivotal in enhancing agricultural yields by optimising resource allocation and management practices. A multilevel regression model was employed to analyse data from multiple sites in Tanzania, accounting for both contextual and individual-level variables affecting yield outcomes. The analysis revealed a significant positive effect of process-control systems on agricultural yields (β = +0.35, p < 0.01), with substantial variability explained by site-specific conditions (R² = 0.45). Process-control systems show promise in Tanzania for yield improvement but require tailored implementation considering local contexts. Further research should focus on integrating these systems into existing agricultural support structures to maximise benefits across diverse landscapes. Agricultural Yield, Process-Control Systems, Multilevel Regression Analysis, Tanzanian Agriculture The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.</p>
title Multilevel Regression Analysis of Process-Control Systems in Tanzanian Agricultural Yield Improvement Context
topic African geography
multilevel regression
process control
resource allocation
agricultural yield
econometrics
statistical methods
url https://doi.org/10.5281/zenodo.18814428