This study employs a mixed-methods approach to explore the financial ramifications and perceived hurdles of adopting international accounting guidelines on asset value reduction in small and medium-sized enterprises (SMEs) in Barranquilla, Colombia, over a recent multi-year timeframe. Through scrutiny of fiscal data and thorough dialogues with SME leaders and finance professionals, the investigation unveils significant industry-specific variations in the monetary impact of embracing these global standards. Manufacturing SMEs are found to shoulder a weightier burden compared to their counterparts in the service sector. The research underscores the pivotal role of perceived standard intricacy in molding the financial outcomes for SMEs, even when accounting for factors such as acquaintance with the guidelines and professional tenure. These discoveries augment our comprehension of global accounting standard adoption in emerging economies and accentuate the necessity for bespoke support mechanisms to assist SMEs in traversing the complexities of implementing these international norms. The insights gleaned from this inquiry can guide policymakers and accounting authorities in crafting sector-specific directives and resources. Such targeted assistance can aid SMEs in harmonizing with worldwide accounting practices while curtailing potential adverse effects on their fiscal performance.

The study sheds light on how service quality aspects affect customer satisfaction in the Saudi banking sector’s particular socio-cultural setting. Thus, the study examines the role of service quality dimensions on customer satisfaction in the banking industry of Saudi Arabia. The study examined how reliability, assurance, empathy, tangibility, and responsiveness affect customer satisfaction in the Saudi Arabian banking market using 250 bank clients. 250 Saudi bank customers completed a standardised questionnaire. These were normal bank customers with proper bank accounts. IBM SPSS correlational and multiple regression analysis investigated variable connections. The study found a significant favourable influence of reliability on customer satisfaction. However, assurance was not significant. Empathy had a significant impact on customer satisfaction. Tangibility shown a significant impact on customer satisfaction. Responsiveness was not significant. The study emphasises on reliability, empathy, and physical service delivery to boost banking customer happiness. The study found 3 of 5 service quality factors to be significant predictors. Service empathy, tangibility, and reliability greatly impacted customer satisfaction. Managers in Saudi banking should prioritize reliability, empathy, and tangibility to boost customer satisfaction. To keep customers happy, managers should monitor these service quality dimensions and adjust strategies based on feedback. Technology can improve service quality by streamlining processes and personalizing experiences.

Credit policies for clean and renewable energy businesses play a crucial role in supporting carbon neutrality efforts to combat climate change. Clustering the credit capacity of these companies to prioritize lending is essential given the limited capital available. Support Vector Machine (SVM) and Artificial Neural Network (ANN) are two robust machine learning algorithms for addressing complex clustering problems. Additionally, hyperparameter selection within these models is effectively enhanced through the support of a robust heuristic optimization algorithm, Particle Swarm Optimization (PSO). To leverage the strength of these advanced machine learning techniques, this paper aims to develop SVM and ANN models, optimized with the PSO, for the clustering problem of green credit capacity in the renewable energy industry. The results show low Mean Square Error (MSE) values for both models, indicating high clustering accuracy. The credit capabilities of wind energy, clean fuel, and biomass pellet companies are illustrated in quadrant charts, providing stakeholders with a clear view to adjust their credit strategies. This helps ensure the efficient operation of banking green credit policies.

Corporate social responsibility (CSR) is an important concept of modern economic theory. In the last few decades, it has become an increasingly popular marketing tool used by companies. Consumers too want to see more CSR activities, especially those focused on environmental protection. The petroleum industry produces both toxic and non-toxic waste at almost all stages of production. While petroleum companies satisfy market demand, they also want to meet consumers’ moral and ethical demands. In this light, CSR has become vital for the development of industry. This paper looks at CSR in the petroleum industry, and its effect on customer satisfaction and subsequently toward the customer repurchase intention in Malaysia. The starting point of this paper is the Stakeholder Theory. It then examines CSR endeavors within the oil and gas sector and its link to customer repurchase intentions. It also looks at the established hypotheses between the activities of CSR (Economic Responsibility, Legal Responsibility, Ethical Responsibility, Philanthropic Responsibility), customer satisfaction and repurchase intention. This paper aims to learn about the customer’s sense of fulfilment with the CSR activities, and what could be the reaction base on the customer’s expectation.

The current study aims to determine the post COVID-19 adoption rates, the variation of the adoption by regions, and the effects of communication technologies on higher education with focus on students’ engagement and faculty satisfaction. The present research uses the convergent parallel design which is a form of mixed-methods research design. First, the study searched for 18 relevant articles using key search terms including “post-COVID-19 education”, “e-learning tools”, “communication technologies” and “higher education”. The qualitative analysis, however, shows that the technological strategies have to be in line with the preparedness of the people, the need to address challenges such as the lack of face-to-face contact and how technologies such as augmented reality and simulation-based learning can be used. Quantitative analysis shows that teleconferencing tools (β = 0.45, p < 0.001) and cloud computing (β = 0.38, p < 0.003) have positive impact on engagement and satisfaction. The one-way ANOVA results show that there is a difference in the adoption rates across the regions while the MCAs score for communication challenges is 60%. From the descriptive statistics it can be seen that there is a very high adoption rate of cloud computing (Mean = 89.7%, Standard Deviation = 3.1%) and teleconferencing tools (Mean = 84.9%, Standard Deviation = 4.5%). The Structural Equation Modeling (SEM) shows the domino effect of teleconferencing on engagement (β = 0.60, p < 0.001), satisfaction (β = 0.75, p < 0.002) and collaboration efficiency (β = 0.55, p < 0.001). Thus, the current study establishes the fact that there is a need to provide equal opportunities and technology which is adaptable to improve the students’ engagement and satisfaction in various learning institutions.

Urbanization process affects global socio-economic development. Originally tied to modernization and industrialization, current urbanization policy is focused on productivity, economic activities, and environmental sustainability. This study examines impact of urbanization in various regions of Kazakhstan, focusing on environmental, social, labor, industrial, and economic indicators. The study aims to assess how different indicators influence urbanization trends in Kazakhstan, particularly regarding environmental emissions and pollution. It delves into regional development patterns and identifies key contributing factors. The research methodology is based on classical economic theories of urbanization and modern interpretations emphasizing sustainability and socio-economic impacts and includes two stages. Shannon entropy measures diversity and uncertainty in urbanization indicators, while cluster analysis identifies regional patterns. Data from 2010 to 2022 for 17 regions forms the basis of analysis. Regions are categorized into groups based on urbanization levels leaders, challenged, stable, and outliers. This classification reveals disparities in urban development and its impacts. Findings stress the importance of integrating environmental and social considerations into urban planning and policies. Targeted interventions based on regional characteristics and urbanization levels are recommended to enhance sustainability and socio-economic outcomes. Tailored urban policies accommodating specific regional needs are crucial. Effective management and policy-making demand a nuanced understanding of these impacts, emphasizing region-specific strategies over a uniform approach.