Mwajuma Muya, Bahati Ilembo and Mackfallen Anasel
This paper examines factors affecting the delivery care (DC) and postnatal care (PNC) services utilization in Tanzania using the predictive accuracy of the binary logit model by…
Abstract
Purpose
This paper examines factors affecting the delivery care (DC) and postnatal care (PNC) services utilization in Tanzania using the predictive accuracy of the binary logit model by including DC as among the predictors of PNC utilization.
Design/methodology/approach
The study used secondary data from the Tanzania Demographic and Health Survey and Malaria Indicator Survey (2022) based on a sample of 13,266 women aged 15–49. Binary logit was used to analyze the association between independent variables and each binary dependent variable, followed by a stepwise likelihood ratio test for binary logistic regression analysis to select the most important predictors associated with DC and PNC. Odds ratios were used to predict the likelihood of the occurrence of significant explanatory variables in explaining the outcomes.
Findings
The results showed that the type of place of residence, wealth index, region, highest educational level, husband/partner’s level of education and respondent’s occupation were significant predictors of DC utilization. In contrast, the woman’s age, region, highest educational level, wealth index, DC and husband/partner’s educational level were significant predictors of PNC utilization. Public health interventions are needed to promote and increase the utilization of delivery and postal care services. The targets should be poor women and those residing in rural or remote areas.
Originality/value
Including DC as a predictor variable (which was not used before) in PNC utilization improved the predictive power of the model and the robustness of the results.
Details
Keywords
Joseph Lwaho and Bahati Ilembo
This paper was set to develop a model for forecasting maize production in Tanzania using the autoregressive integrated moving average (ARIMA) approach. The aim is to forecast…
Abstract
Purpose
This paper was set to develop a model for forecasting maize production in Tanzania using the autoregressive integrated moving average (ARIMA) approach. The aim is to forecast future production of maize for the next 10 years to help identify the population at risk of food insecurity and quantify the anticipated maize shortage.
Design/methodology/approach
Annual historical data on maize production (hg/ha) from 1961 to 2021 obtained from the FAOSTAT database were used. The ARIMA method is a robust framework for forecasting time-series data with non-seasonal components. The model was selected based on the Akaike Information Criteria corrected (AICc) minimum values and maximum log-likelihood. Model adequacy was checked using plots of residuals and the Ljung-Box test.
Findings
The results suggest that ARIMA (1,1,1) is the most suitable model to forecast maize production in Tanzania. The selected model proved efficient in forecasting maize production in the coming years and is recommended for application.
Originality/value
The study used partially processed secondary data to fit for Time series analysis using ARIMA (1,1,1) and hence reliable and conclusive results.
Details
Keywords
Bakari Maligwa Mohamed, Geraldine Arbogast Rasheli and Leonada Rafael Mwagike
The purpose of this study was to identify and assess the regulatory and institutional constraints in managing procurement records in Tanzania’s procuring entities.
Abstract
Purpose
The purpose of this study was to identify and assess the regulatory and institutional constraints in managing procurement records in Tanzania’s procuring entities.
Design/methodology/approach
This study used a mixed study design. There were explorative case study and questionnaire survey study methods used sequentially. In total, 15 procuring entities were used for exploratory case study, while 200 respondents were administered with questionnaires. A 75 per cent response rate was realised.
Findings
Results indicated that management and care of procurement records is constrained by regulatory and institutional constraints. The identified and assessed constraints were inter alia: incapacity of institutional actors, inadequate regulatory and institutional arrangements, inadequacy of storage space, equipment and facilities and insufficiency of security and safety measures.
Research limitations/implications
This research focussed on the procuring entities found in Dar es Salaam, which accounts for 40.72 per cent of the total procuring entities in Tanzania. Based on this, the generalisation of research findings can be sought in that particular context.
Practical implications
Findings imply that procurement records management and care is highly influenced by the constraining factors that hinder efficient records keeping in most procuring entities in Tanzania.
Social implications
Majority of procurement management units and user departments’ staff were found to possess inadequate knowledge, skills and competences in management and care of procurement records. The procuring entities should ensure that procurement staffs are trained in records and archives management practices.
Originality/value
This study contributes towards adding knowledge to the existing body of knowledge on the procurement records and archives management systems.