Browsing by Author "Kadigi, Michael L."

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Econometric analysis of consumers’ preference heterogeneity for yoghurt and ice cream products in Tanzania: A latent class model and mixed logit mode
(Heliyon, 2024-11-22) Kadigi, Michael L.; Philip, Damas; Mlay, Gilead I.; Mdoe, Ntengua S.
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, so cioeconomic 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 attri butes is essential for increasing market share and effectively segmenting markets. These findings would be useful incorporated into strategic planning to enhance the competitiveness and sus tainability of Tanzania’s dairy industry.
Internal control systems and the revenue collection performance among Local Government Authorities (LGA) in Tanzania
(Journal of Policy and Development Studies, 2025-02-17) Hyera, Dennis W.; Kadigi, Michael L.; Ndyetabula, Daniel W.
This study examines the influence of internal control systems on revenue collection performance in selected Local Government Authorities (LGAs) in Tanzania. Weak internal controls contribute to inefficiencies, fraud, and inconsistent financial reporting, posing challenges to revenue collection. The study evaluates the influence of internal control mechanisms in three LGAs, Mbeya, Mwanza, and Manyara, categorised as high, medium, and low performers by the Controller and Auditor General (CAG). A cross-sectional survey design was employed, collecting data from 400 revenue officers across the three LGAs. The study applied Two-Stage Least Squares (2SLS) regression, using external audit frequency as an instrument to address endogeneity concerns. Structured questionnaires facilitated standardised data collection. Findings reveal that solid internal controls significantly improve revenue collection. Accurate financial records (β = 0.045, p < 0.01), timely reporting (β = 0.226, p < 0.01), and effective monitoring (β = 0.152, p < 0.01) enhance revenue efficiency. However, fraud incidents negatively impact revenue growth (β = -0.042, p < 0.1). Internal audits strongly influence revenue increments (β = 0.241, p < 0.01), highlighting their crucial role. To enhance revenue performance, LGAs should strengthen internal audits, improve the accuracy of financial records, implement fraud prevention measures, and optimise reporting timelines. Policymakers should establish standardised internal control frameworks, invest in technology, and engage Public-Private Partnerships (PPPs), local communities, civil society organisations, and NGOs to enhance external oversight, promote citizen participation, and reinforce trust. Additionally, conducting regular policy reviews will improve accountability and efficiency in revenue collection processes.