In Tanzania, a growing upper and middle classes, particularly among urbanites, exhibit distinct preferences for higher-quality processed foods, including dairy products. This study examines variations in consumer preferences and their willingness to pay for yogurt and ice cream, which serve as stand-ins for processed milk products. The analysis is based on a discrete choice experiment involving 400 participants in Dar es Salaam. A random parameter logit model was utilized to account for preference heterogeneity, while latent class models (LCMs) were applied to uncover the underlying factors driving these differences in preferences. Our findings reveal three distinct consumer classes: processed milk sceptics (who prefer unprocessed dairy products), processed milk advocates (who prefer processed products), and neutral consumers (indifferent between processed and unprocessed milk). Preferences are influenced by product attributes, socioeconomic characteristics, and attitudes towards processed foods. The results indicate that Tanzanian consumers place the greatest value on sensory attributes, packaging, and the product's origin (local versus imported). This research offers fresh perspectives on the intricate preferences of dairy consumers in Tanzania, a topic that has been relatively underexplored. The findings suggest that producers and marketers must adapt to the dynamic market by balancing intrinsic and extrinsic factors against price. Understanding consumers' socioeconomic and product attributes is essential for increasing market share and effectively segmenting markets. These findings would be useful incorporated into strategic planning to enhance the competitiveness and sustainability of Tanzania's dairy industry.

Tanzania has been taking various measures to drop the Under-Five Mortality Rate (UFMR), but the pace to meet national and global UFMR targets has been slow. Nevertheless, the decline for the past years has continued to be low as compared to the Sustainable Development Goals (SDGs) target which is set at 25 deaths/1000 live births by 2030. The lack of statistical modeling-based forecast values of UFMR results into setting targets that are not SMART towards the realization of national and international goals of the health sector. Thus, the current study uses both ARFIMA and ARIMA to make forecasts of UFMR in Tanzania from 2021 to 2030 by using data extracted from the World Databank - World Development Indicators (WDI). Also, an accuracy comparison between the ARFIMA and ARIMA best-fit models in forecasting UFMR was conducted. The forecasts from the best ARFIMA (1, 0.284243, 2) model indicate that by June 2026 the rate will on average be 41 deaths/1,000 live births as compared to the Tanzanian Five Year Development Plan Phase III (TFYDP-III) target of 40 deaths/1,000 live births; whereas the best fit ARIMA (1, 2, 0) model forecasts depict that the rate will be 40.1 deaths/1,000 live births as compared to the TFYDP-III target. In relation to the UN SDGs target of 25 deaths/1,000 live births by 2030, the ARFIMA (1, 0.284243, 2) model forecast values indicate that by 2030, Tanzania will experience a decrease in UFMR to 35.2 deaths/1,000 live births. The ARIMA (1, 2, 0) forecast values indicate that by 2030, Tanzania will experience a decrease in UFMR to 32.9 deaths/1,000 live births. The results of using RMSE and MAPE forecasting model accuracy measures reveal that the ARFIMA (1, 0.284243, 2) model performs better than ARIMA (1, 2, 0) in forecasting UFMR.

Knowledge, attitude, and practice (KAP) of farmers in post-harvest management (PHM) are essential for reducing food waste. However, their enhancement also depends on the training programs. Previous studies on the linkage between training programs and farmers’ KAP have been conducted with less emphasis on hermetic storage technology (HST) for PHM. This study aimed to assess the effect of training on KAP and, hence, the adoption of HSTs among smallholder farmers. The underlying theory of change of the study assumes that awareness and access to post-harvest technologies have effects on adoption rates, hence improving food security and income. A quasi-experimental matched-pair cluster randomization design was used to establish a cause-and-effect relationship between an independent and dependent variable. Maize farmer groups totalling 637 farmers were randomly selected and followed the experimental design of the “Evidence-based Scaling of Improved On-Farm Storage among Smallholders in Tanzania” intervention from Kilosa and Kondoa districts of Tanzania, whereas the treatment group farmers received training and free five hermetic storage bags each, while the control group farmers did not. However, this study documented the demographic profiles of farmers in association with KAP on HST using a pre-designed structured questionnaire and used ordinary least squares regression to explore this relationship. We find evidence consistent with a positive and significant relationship between training, KAP, and adoption. The results suggest that the KAP score and adoption were high for farmers who received training as an intervention for PHM using hermetic bags. Overall, the results are consistent with the theory that there is an effect between training and KAP and, thus, the adoption of HST. The study recommends placing emphasis on farmer’s training programs regarding PHM, thus increasing their knowledge, attitude, and practices, and hence their adoption, to enhance food loss control.

The study utilized data from the adoption pathway survey and utility maximization theory to examine the impacts of adopting multiple sustainable agricultural practices (SAPs) on food security, nutrition, and poverty among smallholder maize farmers in the Morogoro region of Tanzania. The SAPs considered include manure, crop rotation, intercropping, crop residuals, and improved maize varieties. Using the endogenous treatment effect model, data collected from 470 farming households in Kilosa and Mvomero districts through a multi-stage sampling procedure were analyzed. Prior to data analysis, weak instrument and zero first-stage tests were employed to test the robustness and validity of the selected instruments, with results deemed satisfactory. The empirical findings indicate that the application of improved maize varieties, crop residual, and crop rotation had positive and significant impacts on the household’s food security and nutrition. Notably, the usage of improved maize varieties alone demonstrated positive and significant impacts on the poverty indicators, suggesting its potential to alleviate poverty among smallholder farmers. The study recommends the development of agricultural productivity enhancement programmes. These programmes should feature a precise targeting strategy aimed at food-insecure households and poor farming households, with the goal of eradicating hunger and nutrition deficiencies within these vulnerable groups. Furthermore, the poverty-alleviating impacts of SAPs, such as the application of improved maize varieties, are expected to grow with increased adoption. Consequently, it is crucial to prioritize significant investments in agriculture. Strengthening and improving maize seed systems becomes imperative, aiming to guarantee the availability and affordability of enhanced maize varieties for smallholder farmers in Tanzania. This step will facilitate wider adoption and contribute to poverty reduction among farming communities.

Local government authorities (LGAs) face significant challenges in revenue collection due to inadequate internal controls, leading to inefficiencies, fraud, and inconsistent reporting. This study investigates the effect of internal control systems on revenue collection performance within selected LGAs in Tanzania, namely Mbeya, Mwanza, and Manyara. Using a cross-sectional survey design, data were collected from 400 respondents across the three councils. Two Stage Least Square regressions were employed with the frequency of external audits as the instrument to control for endogeneity. The findings indicate that while certain internal control measures, such as financial record accuracy and internal audits, positively influence revenue effectiveness and reliability, challenges such as fraud and delayed reporting adversely affect revenue growth and operational efficiency. LGAs should enhance internal audit functions, improve financial record accuracy, strengthen fraud prevention, optimize reporting timelines, and enhance monitoring mechanisms through investment in technology and staff training. Policymakers should develop a standardized framework for internal controls, invest in technology infrastructure, encourage Public-Private Partnerships (PPP), and regularly review policies to ensure effective revenue collection in LGAs.