Low levels of financial literacy cause people to have lower savings rates, higher transaction costs, larger debts and the loans acquisition with higher interest rates, therefore it becomes relevant to analyze the determinants of financial literacy. The aim of this research is to identify whether there is an association between the financial literacy level and sociodemographic characteristics. The Mexican Petroleum Company (Pemex) employees is the population analyzed. Pemex is the state-owned oil and natural gas producer, transporter, refiner and marketer in Mexico. A non-probabilistic convenience sampling was performed and 404 responses were obtained. The analysis of data was carried out with the Bayesian method. The results show that there is an association between Pemex employees’ level of financial literacy and their level of education, income, age and type of retirement saving. No association was found between their level of financial literacy and gender, marital status and whether or not they have children.

The development of artificial intelligence (AI) and 5G network technology has changed the production and lifestyle of people. AI also has promoted the transformation of talent training mode under the integration of college industry and education. In the context of the current transformation of education, AI and 5G networks are increasingly used in the education industry. This paper optimizes and upgrades the training mode of skilled talents in higher vocational colleges by using its advanced methods and technologies of information display. This means is helpful to analyze and solve a series of objective problems such as the single training form of the current talent training mode. This paper utilizes the principles and laws of industry university research (IUR) collaboration for reference to construct and optimize the talent training mode based on the analysis of the requirements of talent training and the role of each subject in talent training. Then, the ecological talent training environment can be realized. In the analysis of talent training mode under the cooperation of production and education, the correlation coefficients of network construction, environment construction, scientific research funds, scientific research level, and policy support were 0.618, 0.576, 0.493, 0.785, and 0.451, respectively. This showed that the scientific research level had the greatest impact on talent training in the talent training mode of IUR collaboration, while policy support had less impact on talent training compared with other factors. The combination of AI and 5G network technology with the talent training mode of IUR cooperation can effectively analyze the influencing factors and problems of the talent training mode. The hybrid method is of great significance to the talent training strategy and fitting degree.

This study aims to analyse the impact of Brexit on London’s housing market, exploring socio-economic and regional disparities. By examining property transaction data from 2012 to 2022, the research seeks to understand how Brexit has influenced real housing prices across different boroughs of London. The methodology involves aggregating transaction data from the Her Majesty (HM) Price Paid database and normalizing prices using the Consumer Price Index (CPI) to obtain real price variations. These data were segmented into three distinct periods: pre-Brexit (2012–2016), post-plebiscite Brexit (2016–2019), and post-implementation Brexit (2020–2022). Spatial analysis was conducted using the software Quantum Geographic Information System (QGIS), transforming point data (postcodes) into polygonal data (wards) for better visualization and comparison. The findings reveal significant socio-economic impacts, with traditionally affluent areas such as Westminster, Kensington, and Chelsea experiencing notable declines in real housing prices. Conversely, certain outer boroughs like Newham and Barnet showed resilience, with positive real price variations despite decreased sales. This geographical disparity underscores the uneven distribution of Brexit’s economic consequences, highlighting the critical role of localized economic policies and development projects in mitigating adverse effects. The results confirm existing literature on the polarization and regional inequalities exacerbated by Brexit while providing new insights into the complex interplay of local and global factors affecting housing markets. The findings emphasize the need for targeted policy interventions to address the diverse challenges posed by Brexit, ensuring both affluent and disadvantaged areas receive adequate support. This research is crucial for informing public policy, urban planning, and housing market strategies in a post-Brexit context, promoting equitable and sustainable development across London.

Balancing broad learning outcomes in graduate programs with detailed classroom learning outcomes is increasingly crucial in education systems. This study employs a qualitative paradigm through a case study method to address the gap between learning outcomes at the graduate program level and those at the course level. Using the ESSENTIA CURRICULUM framework—a curriculum design methodology derived from software engineering practices—we propose an innovative and adaptable approach for aligning program-wide and course-specific learning outcomes. The ESSENTIA CURRICULUM, named for its focus on the “essence of the curriculum”, is applied to the ICT for Research course within the M.Sc. program in University Teaching at the University of Nariño. This framework fosters a consistent educational journey centered on learning achievements and demonstrates its effectiveness through a comprehensive self-assessment process and stakeholder feedback. The implications of this research are twofold: it highlights the potential of adopting interdisciplinary methodologies for curriculum design and provides a scalable and alternative strategy for harmonizing learning outcomes across diverse educational contexts. By bridging principles from software engineering into education, this novel approach offers new avenues for improving curriculum coherence and applicability.

This paper focuses on examining the relationship among organizational factor, work-related factor, psychological factor, personal factor and the commitment of oil palm smallholders toward Malaysian Sustainable Palm Oil (MSPO) certification. The study employed a descriptive research methodology and a structured survey instrument to gather data from oil palm smallholders (n = 441) through simple random sampling technique. Data analysis was conducted using SPSS and partial least square structural equation modeling (PLS-SEM) to test the proposed relationship. The findings reveal that organizational factors significantly impact the affective (β = 0.345, p < 0.05), normative (β = 0.424, p < 0.05), and continuance commitment (β = 0.339, p < 0.05) of oil palm smallholders. Additionally, work-related factors show a substantial effect on these same dimensions of commitment; affective (β = 0.277, p < 0.05), normative (β = 0.263, p < 0.05), and continuance (β = 0.413, p < 0.05). Psychological factors significantly impact the affective (β = 0.216, p < 0.05) and normative commitment (β = 0.146, p < 0.05), with no statistically significant influence on continuance commitment. Conversely, personal factors exhibit limited influence, affecting only continuance commitment (β = 0.104, p < 0.05) to a minor degree, with no statistically significant impact on affective and normative commitment. The present research is among the few empirical findings that have examined the oil palm smallholders' commitment towards MSPO certification. By emphasizing the role of organizational and work-related factors, the study offers valuable insights for stakeholders within the oil palm sector, highlighting areas to enhance smallholder commitment toward sustainability standards. Consequently, this study contributes a unique perspective to the existing body of literature on sustainable practices in the oil palm industry.

Water-based, waterfront tourism has always played an important role in the development of the tourism sector, water has been and still is an important attraction and contributes to regional development. In Hungary, Lake Balaton is the primary destination for waterfront tourism, offering a wide range of opportunities in this sector. Water-based, waterfront tourism is mainly concentrated in the high summer season, but there is an increasing range of opportunities in both the low and high season. In our research, we investigated the development of cruise tourism in Lake Balaton in the off-season, in the months of September-October 2023, by conducting in-depth interviews and questionnaire research. Our research has confirmed that this service is also in demand outside the high season. In the autumn, cruises add a special value to the experience, they can help to reduce seasonal fluctuations in tourism by offering attractive activities and also increase income for local businesses during the off-season.