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This review provides a comprehensive, step-by-step guide to the application of partial least squares structural equation modeling (PLS-SEM) for novice researchers. This is a conceptual and literature-based review that focuses on best practices and PLS-SEM literature. It highlights the rationale for using PLS-SEM, sample size, software tools, and essential metrics in PLS-SEM analysis. Drawing on best practices and recent literature, the review offers a framework for conducting and reporting PLS-SEM analysis. The review presents essential such as outer loadings, Cronbach’s alpha coefficients, average variance extracted (AVE), composite reliability, cross-loadings, Heterotrait-Monotrait ratio of correlations (HTMT), the Fornell-Larcker criterion, variance inflation factor (VIF), and redundancy analysis. Moreover, for more consistent results, the paper emphasizes on researchers to employ 10,000 bootstrap subsamples and Bias-corrected and accelerated (BCa) bootstrap in assessing the structural model. Insights regarding path coefficients, p-values, R-square (R2), f-square (f2), and Q-square (Q2),  are also presented. Furthermore, the review underscores the trade-off between predictive power and model fit when applying PLS-SEM. The presented practical insights alert novice researchers in avoiding common pitfalls and enhance the methodological rigor of empirical research that utilizes PLS-SEM. This step-by-step guide supports early-career researchers and contributes to the ongoing debates on improving methodological clarity and transparency.

In Southern Africa, the human immunodeficiency virus constitutes a significant public health challenge, characterised by elevated rates of new infections in rural populations. Conversely, biomedical interventions have facilitated advancement. The incorporation of Indigenous Knowledge Systems into Human Immunodeficiency Virus preventive techniques is still little investigated. This systematic analysis assesses the incorporation of Indigenous Knowledge Systems into community-based HIV prevention strategies in Southern Africa. This systematic review complied with the PRISMA principles. A search was performed across various electronic databases, including PubMed, Google Scholar, and CINAHL, for papers published from 01 January 2015 to 31 June 2025. A total of 51,972 studies were discovered, of which 14 matched the inclusion criteria and were evaluated. The analysis revealed that incorporating Indigenous Knowledge Systems into community-based HIV prevention programs in Southern Africa improved cultural relevance, community involvement, and trust in health initiatives. Traditional healers significantly contributed to counselling, education, and the increase of HIV testing in rural regions, leading to enhanced service accessibility and diminished stigma. Notwithstanding these advantages, several projects nevertheless lacked official policy support and organised collaborations between conventional and biological health sectors.

This article explores the perceptions of teachers about their role to implement the national school nutrition programme in the Harry Gwala District KwaZulu-Natal. This article originated from my Ph.D. study in which a qualitative research design with a sample of teachers was used, and nutrition coordinators who play a primary role in the school nutrition programme. Data was collected through individual interviews and document analysis. The study findings indicated that teachers perceived their role to interact with learners during feeding time as necessary in order to achieve the main objectives of the programme. The findings secondly indicated that teachers have a perception that their monitoring and supervision role ensured that there is a great need to check food stuff delivered by service providers as the key to ensure smooth running of the school nutrition programme, the findings thirdly emphasis that, teachers perceived as their role to ensure that all learners at school benefit from the programme. The findings also heighted that teachers were demotivated by unavailability of feeding equipment in their role to implement the school nutrition programme. The study also assert that school teachers had a perception that smooth running of the school nutrition programme depends on their proper management and administration of the programme. The study also find that teachers perceived safety and security on school nutrition programme as the most challenging aspect on their role to implement the programme. It was also discovered that the duty to that the service providers, Volunteer Food Handlers are not paid on time is also perceived as a barrier to programme implementation. Teachers have a perception that food for learners should be prepared and served under hygienic conditions even if the infrastructure if poorly developed. This study has a meaningful contribution to the entire implementation of the national school nutrition programme, and also fill the gap on how teachers perceive their role in the implementation of the school nutrition programme.

This study examines how formal and informal institutional pressures influence public sector financial reporting quality in Ghana. Despite ongoing public financial management reforms, challenges such as weak enforcement of standards, inconsistent disclosures, and limited transparency continue to undermine reporting quality. Existing research has largely emphasised technical and administrative determinants, with limited attention to the role of institutional pressures in shaping reporting behaviour. Grounded in Institutional Theory, the study adopts a quantitative approach and collects data from 344 senior finance officers across ministries, departments, and agencies in Ghana. Structural Equation Modelling (SEM) is employed to analyse the relationships between regulatory environment, government structure, societal expectations, stakeholder expectations, and financial reporting quality. The results indicate that government structure and societal expectations significantly enhance financial reporting quality, while the regulatory environment and stakeholder expectations have no significant direct effects. The study contributes to institutional theory by demonstrating that formal and informal pressures exert unequal influence in a developing-country public sector context. It also extends public sector accounting literature by providing large-sample empirical evidence from Ghana. The findings suggest that improving reporting quality requires strengthening governance structures, enhancing civic accountability mechanisms, and improving enforcement capacity.

This study examines the long-run relationship between foreign direct investment (FDI) inflows and institutional quality within the Arab Maghreb Union (AMU), focusing on Algeria, Mauritania, Morocco, and Tunisia over the period 2002–2019. Drawing on institutional theories of FDI, the analysis employs governance indicators such as political stability, control of corruption, government effectiveness, regulatory quality, and rule of law to assess their influence on investment dynamics. Using panel unit root and cointegration tests, the study confirms the existence of a stable long-term equilibrium among the variables. The Fully Modified Ordinary Least Squares (FMOLS) estimator is applied to quantify these relationships. Empirical results indicate that control of corruption, political stability, and regulatory quality exert significant positive effects on FDI inflows, even after accounting for macroeconomic controls. Conversely, government effectiveness and rule of law show no statistically significant impact in the presence of the macroeconomic control variables. These findings underscore the critical role of institutional quality in shaping the investment climate of AMU economies. Policy implications suggest that targeted reforms such as strengthening anti-corruption frameworks, enhancing political stability, and improving regulatory governance can bolster institutional credibility, mitigate investment risk, and attract sustainable FDI to the region.  

The central theme of John Maynard Keynes’s The General Theory of Employment, Interest and Money (henceforth, The General Theory) is that uncertainty governs economic activity. Because people lack the information needed to make informed decisions and pursue their best interests, they can only act in ways they believe will best serve them or fall back on convention. However, the conventions households rely on may lead to deficient or excessive demand for commodities. As businesses respond to demand deficiencies or excesses, production and employment may also become unstable. When demand is modestly deficient or excessive, contractions and expansions will be mild, as in the trade cycle. However, if demand is extremely deficient or excessive, contractions and expansions could be severe, as in the Great Depression and the 2008 Financial Crisis. This paper examines how uncertainty leads to the trade cycle in Keynes’s theory, while setting aside the more severe form of instability for another occasion.

Road infrastructure is essential for socioeconomic development, market access and public service delivery. However, effective implementation requires leadership capabilities that address emerging challenges and operational constraints. This study examined the influence of problem-solving skills on road infrastructure project implementation in Kitui County, Kenya. The study was guided by Path–Goal Theory and adopted a positivist research philosophy and descriptive survey research design. The target population comprised 600 employees involved in planning, procurement, supervision, technical implementation and administration of road infrastructure projects within the Kitui County Department of Public Works and Infrastructure. Proportionate stratified random sampling was used to select 240 respondents. Data were collected using structured questionnaires and analysed using the Statistical Package for the Social Sciences (SPSS) Version 26. Descriptive statistics, Pearson’s correlation and simple linear regression were employed. Of the 240 questionnaires distributed, 175 were returned, representing a response rate of 72.9%. The findings revealed a positive and statistically significant relationship between problem-solving skills and road infrastructure project implementation (r = 0.640, p < 0.001). Regression results further indicated that problem-solving skills significantly predicted project implementation (β = 0.640, B = 0.707, p < 0.001), explaining 41.0% of the variation in implementation outcomes (R² = 0.410). The study concludes that problem-solving skills are important for addressing implementation challenges and improving road infrastructure project outcomes. It recommends that the County Government of Kitui strengthen leadership development through training in problem identification, analytical decision-making, adaptive responses and innovative problem-solving to support timely project completion, efficient resource utilization and compliance with required quality standards.

Namibia’s farming sector faces recurrent drought, water scarcity and uneven access to agricultural services. This structured narrative review examines the relevance of Big Data to commercial and small-scale farming through the pathway from data collection to usable decisions. It draws on research and institutional reports on remote sensing, precision agriculture, analytics, advisory services and data governance. Search dates, executed queries, selection counts and source-level appraisal records remain unverified; systematic coverage is not claimed. The synthesis distinguishes Namibia-specific documentation, findings from African settings whose comparability requires assessment, and potential local uses inferred from international research. Namibian sources establish sector context but do not substantiate measured farming benefits attributable to Big Data. African literature informs adoption and access considerations, while international reviews describe technical applications and implementation requirements. Candidate uses include crop and pasture monitoring, irrigation support, livestock information, forecasting and drought preparedness. The review’s contribution is a Namibia-focused interpretation of where data-to-decision pathways may fail, particularly when farmers cannot afford or act on advice. Proposed responses identify advisory services, farmer organisations, public data custodians and technology providers as potential actors, subject to local validation, affordability and accountable governance. These are recommendations for testing, not demonstrated effects. Locally evaluated changes in decisions, resource use, productivity, resilience and income are needed before impact claims can be made.

The fluctuation of firm value of companies listed in Nairobi Securities Exchange (NSE) has been a consequence of a number of determinants. Carbon emission disclosure has been a subject of concern by many stakeholders since the advent of global warming aspect worldwide. On this basis this study investigated the effect of carbon emission disclosure on firm value of listed companies in the NSE and further, interrogated the moderating role of corporate characteristics (firm size, leverage and profitability) on this relationship. The inquiry focuses on listed companies in the NSE for the period 2022 to 2024. Anchored on the stakeholder, legitimacy and resource-based-view theories, the study combined explanatory longitudinal and ex-post-facto research designs. From a population of 64 listed companies by December 2024, an initial sample of 54 companies was purposively selected. The final response rate was 43 (80%) firms that entered the final analysis. The study was anchored on the stakeholder theory, legitimacy theory and resource-based view theory. Secondary data obtained from the sampled company annual integrated reports and/or sustainability report for the 3 year period was described using descriptive statistics and analyzed using hierarchical regression methods in SPSS version 27. From the study findings it is revealed that carbon emission disclosure has a statistically significant negative effect on firm value. While corporate characteristics of firm size and leverage were found not to significantly influence the relationship, profitability was found to moderate the relationship between carbon emission disclosure and firm value. The negative interaction with profitability does not however support the argument that firms can buffer profitability through carbon disclosure. There is a need for enhanced assurance and comparability in carbon disclosure by regulators. Firms should also endeavor to link carbon disclosure to credible transition plans and financially responsible decarbonization strategies.

The implementation of Artificial Intelligence (AI) in the oil and gas sector is increasingly expanding as an effort to improve operational efficiency and support employees’ work activities. However, the successful adoption of AI depends not only on the availability of technology but also on employees’ level of acceptance and ability to utilize it effectively. This study aims to analyze the impact of AI Acceptance on employee productivity at PT Seashore and identify the factors that cause AI acceptance to have not yet resulted in optimal productivity improvements. This study employs a qualitative approach using a case study method through semi-structured interviews with three AI-using employees and four key informants. Data were analyzed thematically based on the Technology Acceptance Model (TAM) perspective using Open Code. The findings indicate that AI Acceptance has a good impact on productivity, particularly in administrative, repetitive, and structured tasks, by saving time and improving efficiency. However, this impact remains suboptimal due to limitations in prompting, inaccuracies and hallucinations, the need for verification and rework, the risk of overreliance, limited technical understanding, task suitability, and constraints related to AI access and governance.