Thanks to the ongoing expansion of internet access and, most recently, the movement restrictions that were put in place globally to stop COVID-19 spread, many small and medium enterprises (SMEs) are prepared to use social media platforms to market their products as a way to improve their business performance in emerging economies. Businesses at all levels that use social media marketing (SMM) see a considerable increase in their output. This study’s objective is to identify the factors that significantly help Ugandan SMEs implement SMM techniques to enhance their commercial performance. Here, statistical models are utilized to analyze how the age and gender of SMEs owners as moderating variables affect the adoption and performance of SMEs in Uganda. A theoretical model that is based on the Technology Acceptance Model (TAM) and Innovation Diffusion Theory (IDT) theories has been put out as part of a specific conceptual framework. The following indicators are used to evaluate the performance of SMEs: sales, customer engagement, awareness of customers’ needs, low operation costs, and brand modification by staff. Empirical model validation has been performed using 152 business units (observation units) corresponding to the number of respondents (units of analysis), and the ensuing analyses have been done using structural equation modelling (SEM). The results indicate that compatibility and perceived ease of use have a positive impact on SMEs to adopt SMM, while perceived usefulness has a negative impact on SMEs to adopt SMM. Age and gender as moderating variables all have a positive moderating effect. With limited studies available on the subject, this research contributes to already existing literature by combining two components of the TAM model and one component of the IDT to explain the impact of SMM on SMEs when moderated by both age and gender in a developing economy.

Two approaches to parameter estimation for a mixture of two univariate Gaussian distributions are numerically compared. The proposed method (PM) is based on decomposing a continuous function into its odd and even components and estimating them as polynomials, the other is the usual maximum likelihood (ML) method via the expected maximisation (EM) algorithm. An overlapped mixture of two univariate Gaussian distributions is simulated. The PM and ML are used to re-estimate the known mixture model parameters and the measure of performance is the absolute percentage error. The PM produces comparable results to those of to the ML approach. Given that the PM produces good estimates, and knowing that the ML always converges given good initial guess values (IGVs), it is thus recommended that the PM be used symbiotically with the ML to provide IGVs for the EM algorithm.

This analysis focused on the impact of participatory budgeting (PB) procedures and budget implementation on financial sustainability (FS) in local governments in Uganda, specifically budget approval. The analysis employed direct correlations within a structural equation modeling (SEM) framework and assessed the moderating effect of employee age groups. Confirmatory factor analysis confirmed the instrument’s validity and reliability, and the structural model demonstrated an excellent fit: CFI = 0.986, TLI = 1.000, RMSEA = 0.000, SRMR = 0.015. The results show that PB procedures have a strong impact on financial sustainability, and that most reliable indicators are budget implementation. Although some age groups showed considerable path changes, age only had a small and inconsistent moderating influence on PB–FS correlations, according to multigroup SEM moderation analysis. The results indicate that institutional capacity, accountability and transparency has a greater influence on the effectiveness of PB than personnel demographics. The study provides practical recommendations on the design of context-sensitive PB systems, and also adds empirical evidence to the debate on local public financial management reforms in emerging countries. In order to improve the sustainable fiscal performance, the recommendations are: strengthening the surveillance framework, strengthening technical capacities in budgeting procedures, and increasing the capacity-building initiatives.