While plastic waste has become a more frequent occurrence on the rural landscape in sub-Saharan Africa, studies on the management of plastic waste have focused largely on urban and peri-urban areas, ignoring forest-adjacent communities. This study analyzed the socio-economic characteristics, plastic waste management practices and challenges among households in five communities bordering Gambari Forest Reserve, Oyo State, Nigeria: Idi Ayunre, Onipe, Onigambari, Ibusogboro and Olonde. The study employed a multistage sampling procedure to select 120 households, and data were collected using a structured questionnaire through interviews. Data were analyzed using descriptive statistics and Pearson product moment correlation. Results indicated that the majority of the sample was women (55.8%) and married respondents (83.3%), with most respondents being between 41 and 50 years old and having at least secondary education. Most respondents engaged in waste management practices such as encouraging children not to litter (73.3%) and reporting dumping to community leaders (73.3%), but formal recycling and use of reusable alternatives were moderate, with 56.7% of respondents classified in the low-practice group. The most common challenges were lack of designated collection points (57.5%), limited access to recycling facilities (40.0%) and inadequate knowledge of proper disposal methods (40.0%), with 63.3% of respondents falling into the highconstraint category. There was a positive correlation between challenges faced and methods adopted for plastic waste management (r = 0.421, p = 0.000). The results suggest that infrastructural and awareness gaps, rather than unwillingness, are the main drivers of ineffective plastic waste management in these communities.

This study examined the relationship between digitalisation and the performance of microfinance institutions, using Kyebando SACCO as a case study. The study was guided by three objectives: to assess the level of digitalisation adopted by Kyebando SACCO, to establish the level of organisational performance, and to determine the statistical relationship between the two variables. A descriptive cross-sectional and correlational design was adopted, targeting a population of 150 staff and members, from which a sample of 110 respondents was drawn using Krejcie and Morgan's (1970) table and stratified random sampling.
Data were collected using a structured, five-point Likert-scale questionnaire and analysed using SPSS through descriptive
statistics, Pearson correlation, and simple linear regression. The findings revealed a high level of digitalisation (M = 3.83) and
a high level of overall performance (M = 3.69) at Kyebando SACCO, with a strong, positive, and statistically significant
correlation between digitalisation and performance (r = 0.612, p < 0.01). Regression analysis showed that digitalisation
significantly predicts performance (β = 0.573, p < 0.01), explaining 37.5% of the variance in performance (R² = 0.375). The
study concludes that digitalisation is a key driver of SACCO performance and recommends increased investment in secure
digital infrastructure, digital literacy training, and a phased digitalisation roadmap linked to measurable performance targets.

This study examined the relationship between total quality management (TQM) practices and operational performance
in the utility pole treatment industry, using Uganda Electricity Distribution Company Limited (UEDCL) as the case.
The utility pole treatment segment occupies a critical position within Uganda's electricity distribution value chain, since the durability of treated wooden poles directly determines network reliability, the frequency of unplanned outages, and the lifecycle cost of distribution infrastructure. Despite substantial investment in preservative treatment plants and quality inspection regimes, UEDCL has continued to record pole rejection rates, premature pole failures, and treatment cycle delays that suggest an incomplete institutionalisation of quality management. Guided by a positivist philosophy and a cross sectional survey design, the study collected quantitative data from 132 respondents drawn from treatment plant operations, quality assurance, procurement, engineering, and supervisory cadres, selected through stratified random sampling from a target population of 198. A structured questionnaire anchored on a fivepoint Likert scale measured four TQM dimensions, namely top management commitment, process management, employee involvement and training, and customer focus, alongside operational performance measured through quality conformance, cost efficiency, delivery reliability, and flexibility. Data were analysed using descriptive statistics, Pearson product-moment correlation, and multiple linear regression in SPSS version 26. Findings revealed that process management recorded the highest mean score while employee involvement recorded the lowest. All four TQM dimensions were significantly and positively correlated with operational performance, with process management showing the strongest association (r = 0.712, p < 0.01), followed by top management commitment (r = 0.658, p < 0.01), customer focus (r = 0.591, p < 0.01), and employee involvement (r = 0.544, p < 0.01). The regression model was significant (F = 47.83, p < 0.001) and explained 59.7 per cent of the variance in operational performance, with process management (β = 0.362, p < 0.001) and top management commitment (β = 0.284, p < 0.001) emerging as the strongest predictors. The study concludes that TQM is a substantive determinant of operational performance in pole treatment operations and recommends that UEDCL institutionalise statistical process control at the retort and posttreatment stages, strengthen preservative retention verification, and invest in structured operator competency development.