Browsing by Author "Matimbwa, Hadija"

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Assessment of Current Post-Harvest Handling Techniques for Mango and Avocado in Mbeya Region, Tanzania: Challenges and Opportunities for Improvement
(Elsevier, 2025-07-31) Mng’ong’o, Marco E.; Matimbwa, Hadija; Komanya, Absalom; Maro, Lilian; Mshora Abubakar M
Mango (Mangifera indica) and avocado (Persea americana) are valuable fruits in Tanzania, known for their nutritional and economic importance. However, their perishability leads to significant post-harvest losses, especially for smallholder farmers in Mbeya. The limited knowledge about post-harvest handling identifies a research gap. This study assessed practices and challenges among mango and avocado farmers to improve handling techniques. A survey of 150 smallholder farmers in Kyela and Rungwe districts (August–September 2024) examined harvesting, storage, transportation, and post-harvest challenges. Data analysis revealed that 64 % of farmers use traditional harvesting methods that lead to mechanical damage. While 68.8 % manually hand-harvest, others rely on tree shaking (8.3 %) and sticks or stones (18.8 %), further increasing fruit damage. Storage at ambient temperature (46 %) fails to extend shelf-life, causing rapid quality deterioration. Trans portation by motorcycle (44 %) and head carrying (34 %) exposes fruits to damage. Key challenges included fruit drop (36 %), rotting before harvest (28 %), and insect infestation (24 %). Only 23.4 % of farmers had reliable market access, highlighting a major constraint. Education level influenced challenges, with lower-educated farmers facing more rotting and pest issues. Findings indicate current post-harvest practices are inadequate, leading to major losses. Simple, cost-effective technologies like edible coatings and training on improved har vesting, storage, and transportation are necessary. Investment in affordable cold storage and better transport infrastructure is crucial. This study provides actionable insights for policymakers and stakeholders to enhance mango and avocado value chains in Tanzania
Assessment of Current Post-Harvest Handling Techniques for Mango and Avocado in Mbeya Region, Tanzania: Challenges and Opportunities for Improvement
(Elsevier, 2025-07-31) Mng’ong’o, Marco E.; Matimbwa, Hadija; Komanya, Absalom; Maro, Lilian; Mshora, Abubakar M.
Mango (Mangifera indica) and avocado (Persea americana) are valuable fruits in Tanzania, known for their nutritional and economic importance. However, their perishability leads to significant post-harvest losses, especially for smallholder farmers in Mbeya. The limited knowledge about post-harvest handling identifies a research gap. This study assessed practices and challenges among mango and avocado farmers to improve handling techniques. A survey of 150 smallholder farmers in Kyela and Rungwe districts (August–September 2024) examined harvesting, storage, transportation, and post-harvest challenges. Data analysis revealed that 64 % of farmers use traditional harvesting methods that lead to mechanical damage. While 68.8 % manually hand-harvest, others rely on tree shaking (8.3 %) and sticks or stones (18.8 %), further increasing fruit damage. Storage at ambient temperature (46 %) fails to extend shelf-life, causing rapid quality deterioration. Trans portation by motorcycle (44 %) and head carrying (34 %) exposes fruits to damage. Key challenges included fruit drop (36 %), rotting before harvest (28 %), and insect infestation (24 %). Only 23.4 % of farmers had reliable market access, highlighting a major constraint. Education level influenced challenges, with lower-educated farmers facing more rotting and pest issues. Findings indicate current post-harvest practices are inadequate, leading to major losses. Simple, cost-effective technologies like edible coatings and training on improved har vesting, storage, and transportation are necessary. Investment in affordable cold storage and better transport infrastructure is crucial. This study provides actionable insights for policymakers and stakeholders to enhance mango and avocado value chains in Tanzania
Enhancing Organizational Performance through Human Resource Incentives: Insights from TANESCO Dodoma, Tanzania
(Mbeya University of science and Technology, 2025-03-01) Mwinuka, Thomas; Matimbwa, Hadija; Kamala, Mugisha
Human resource incentives are crucial for enhancing organisational performance by boosting employee motivation, satisfaction, and performance. A study at TANESCO Dodoma analysed the effects of financial incentives, staff training, and employee recognition using a quantitative methodology and explanatory cross-sectional design. This research provided insights into the immediate effect of these incentives on organisational performance and the overall effectiveness of the employees at TANESCO Dodoma. A study was conducted with 187 employees from TANESCO Dodoma, selected through simple random sampling to ensure representativeness. Data was collected through structured questionnaires to assess employee perceptions and attitudes on the incentives and analysed using multiple linear regression techniques, yielding significant findings. The results indicated a significant positive relationship between various incentives and organisational performance. Specifically, the findings indicate that staff training is the most significant factor in improving performance, with a p-value of p < 0.001. Financial incentives follow closely, showing a notable impact with a p-value of p = 0.01. While staff recognition also plays an important role, its effect is comparatively smaller, with a p-value of p = 0.022. The study highlights the crucial role of human resource incentives at TANESCO Dodoma in driving organisational performance. This study provides context-specific evidence on the contribution of human resource incentives, particularly in a Tanzanian public sector setting, which has received limited attention in prior research. The study recommends optimising financial incentives to boost employee motivation and performance, expanding training programs to enhance skills, and implementing recognition practices to reward exceptional contributions. These strategies emphasise the need for continuous investment in human resources to support sustainable growth and success
Examination Seating Optimization Using Graph Coloring and Combinatorial Design
(ELSEVIER, 2026) Kibona, Isack E.; January, Jeremiah; Matimbwa, Hadija; Nchia, Edwin; Matungwa, William; Vuai, Said A.H.
This paper presents an optimization approach for exam seating in universities with limited infrastructure, based on a mixed-course allocation model. Students in different courses share rooms while maintaining spatial separation to improve academic integrity. The model incorporates a theoretical probability of interaction, which decreases as the number of mixed courses in a room increases. Using real data with 5175 students, the proposed model significantly improves upon the traditional method. Although the traditional approach required 35 rooms with a total capacity of 7269, the proposed model utilized only 12 large rooms, leaving 23 rooms unused and saving about 2475 seats. The unused space within the occupied rooms was minimal (approximately 29 seats), indicating near-optimal utilization. The invigilation requirement was reduced from at least 70 to 36, achieving nearly 50% savings. Small- enrollment and carryover courses are efficiently integrated and sorted. The model is formulated using graph coloring and combinatorial optimization, supported by a simple allocation algorithm
Influence of User Characteristics on the Effectiveness of LGAs’ Human Resource Information System in Tanzania
(G-CARD, 2023) Matimbwa, Hadija; Olatokun, Wole
The implementation of the Human Resource Information System (HRIS) in Local Government Authorities (LGAs) in Tanzania aimed at addressing shortcomings of methods in managing employee’s information. The shortcomings primarily involved outdated data concerning civil servants. This study explored how user characteristics impact the effectiveness of HRIS in Tanzanian LGAs, specifically focusing on information timeliness, completeness and accuracy. The study covered Mwanza, Arusha, Dodoma, Morogoro, Iringa and Kagera Regions. A questionnaire and an interview guide were used for data collection from 213 participants sampled form 249 HR stakeholders. A total of 201 respondents participated in the study. An ordered logistic regression model was employed for data analysis. The findings revealed that user characteristics such as IT skills, commitment and experience have an influence on the HRIS effectiveness. Therefore, it is crucial to prioritize IT skills training to foster commitment among HRIS staff and promote knowledge sharing among in order to ensure successful implementation of HRI within the LGAs.
Technological Determinants of Human Resource Information System Effectiveness in Tanzania
(Journal of Policy and Development Studies (JPDS), 2024-11-29) Mugisha, Kamala; Matimbwa, Hadija
Organizations are increasingly moving from traditional paper files to digital filing systems to gain a competitive edge and improve access to human resources and HR-related information. This digitalization process not only makes data more accessible but also enhances its utilization for HR decision-making. As a result, HR-related information becomes more comprehensive, accurate, and up-to date. This study specifically investigates the impact of technological factors on the effectiveness of human resource information systems (HRIS) within local government authorities (LGAs) in Tanzania. The research utilized a combination of descriptive and inferential statistics, including ordered logistic regression analysis, to examine the impact of technological characteristics on the effectiveness of Human Resource Information Systems (HRIS). The findings revealed that factors such as compatibility, complexity, usefulness, and reliability play a crucial role in determining the timeliness, comprehensiveness, and accuracy of data retrieval within HRIS. The study offers valuable insights for improving human resource management practices in LGAs) through the adoption of computerized HRIS. The discussed approach enhances decision-making and improves access to information, contributing to the achievement of organizational goals. It also emphasizes the importance of regularly updating systems to keep pace with changing technological landscapes.
Unveiling the Potential of Artificial Intelligence in Human Resource Management: A Systematic Review of Adoption Strategies, Challenges, and Future Directions
(Open Access Review Article, 2025-04-23) Mohamed,Halima H.; Matimbwa, Hadija; Banzi,Jamal
Artificial intelligence (AI) has emerged as a transformative force in human resource management (HRM), as it improves efficiency, decision-making processes, and employee experience while offering an unprecedented opportunity to create value for consumers, employees, and organizations. Despite its transformative potential, recent studies reveal a disconnect between expectations and the benefits of implementing AI. This systematic review examines the current state of AI in HRM, identifying key adoption strategies, challenges, and organizational prerequisites for successful integration. It provides a comprehensive, objective understanding of the organizational resources necessary to enhance AI capabilities in HRM, enabling organizations to fully benefit from them. Using CiteSpace for bibliometric analysis, the study traces the evolution of AI in HRM from algorithmic advancements to practical applications. Our findings highlight that successful AI adoption requires more than just technological investment; it demands leadership commitment, workforce upskilling, cultural adaptability, and cross-functional collaboration. We also discuss theoretical contributions such as refining AI-HRM frameworks and practical implications, including strategies for mitigating implementation risks. Finally, this study provides actionable insights for HR professionals, policymakers, and researchers seeking to harness AI’s full potential while addressing adoption barriers. By bridging the gap between expectations and reality, our work lays the foundation for future research on AI-driven HRM innovation