With the faster pace of China’s opening to the outside world, the contacts between Chinese enterprises and Portuguese speaking countries are becoming more and more frequent. Under this trend, how to further improve the quality of Portuguese classroom teaching is related to the development of students, enterprises and the long-term development of the whole country. This paper mainly focuses on the two aspects of “the main problems existing in Portuguese classroom teaching” and “the improvement countermeasures of Portuguese classroom teaching”. Combined with the current situation of Portuguese teaching, this paper puts forward targeted reform measures, in order to further optimize the Portuguese teaching system, with “student development”, “enterprise development” and take “national development” as the ultimate goal to cultivate a large number of high-quality Portuguese talents to the society.

This paper analyzes the relevance of social accounting information for managing financial institutions, using Banca Transilvania Financial Group (BTFG) as a case study. It explores how social accounting data can enhance decision-making processes within these institutions. Social information from BTFG’s annual integrated reports was used to construct a social balance sheet, and financial data was collected to calculate economic value added (EVA) and social value added (SVA). Research question include: Does social accounting represent a lever for substantiating the managerial decision in financial institutions? Results show that SVA is a valuable indicator for financial institution managers, reflecting the institution’s contributions to social well-being, environmental impact, and community support. Policy implications suggest regulatory bodies should mandate the inclusion of social accounting metrics in financial reporting standards to encourage socially responsible practices, enhance transparency, and incentivize institutions achieving high SVA. This paper contributes to the literature by demonstrating the practical application of social accounting in financial institutions and highlighting the importance of SVA as a managerial tool. It aligns with existing research on integrating corporate social responsibility (CSR) metrics into financial decision-making, enhancing the understanding of combining social and economic indicators for comprehensive performance assessment The abstract covers motivation, methodology, results, policy implications, and contributions to the literature.

Work can be demanding, imposing challenges that can be detrimental to the job performance of employees. Efforts are therefore underway to develop practices and initiatives that may improve job performance and well-being. These include interventions based on mindfulness, inclusive leadership and work engagement. In the present study, authors have presented an association of inclusive leadership and mindfulness towards job performance through employee work engagement among secondary teachers in the context of Hong Kong. The sample size of 263 teachers working from three secondary schools in Sha Tin, Hong Kong has been incorporated in this study. A structured questionnaire designed on a 5-point Likert scale has been used based on purposive sampling by analysis of IBM SPSS 27 and Smart PLS version 4.0.9 by applying a structural equation modelling approach (SEM). The results indicated a strong positive influence on employee work engagement and job performance. Moreover, the bootstrap investigation showed that mindfulness and inclusive leadership were significantly associated with employees’ work engagement in the presence of mediators’ work engagement. This study adds to the very scarce literature on inclusive leadership and mindfulness. In addition, this research is the first study to test the mindfulness skill, inclusive leadership and job performance relationship. Furthermore, this is the first study to explore the concept of mindfulness and inclusive leadership in the Hong Kong context. Moreover, the findings of this research can be beneficial for future theory development on mindfulness skill and inclusive leadership in cross-cultural contexts.

The purpose of this study is to analyze how the entrepreneurial mindset, social context, and entrepreneurial ambitions of university students in the United Arab Emirates (UAE) have progressed over time in terms of starting their businesses. The research aims to investigate the evolution of the entrepreneurship mindset, considering the implementation of educational and governmental policies over the past decade to promote entrepreneurship among UAE university graduates. To collect primary data and evaluate the impact of the studied variables on the dependent variable “entrepreneurial ambitions,” a self-created questionnaire was used. The results reveal a positive correlation between personal context variables and entrepreneurial ambitions, as well as between personality traits and entrepreneurial ambitions. Furthermore, the study demonstrates the constructive effect of education, government policies, and capital availability on fostering entrepreneurial ambitions in the UAE.

The telecommunications services market faces essential challenges in an increasingly flexible and customer-adaptable environment. Research has highlighted that the monopolization of the spectrum by one operator reduces competition and negatively impacts users and the general dynamics of the sector. This article aims to present a proposal to predict the number of users, the level of traffic, and the operators’ income in the telecommunications market using artificial intelligence. Deep Learning (DL) is implemented through a Long-Short Term Memory (LSTM) as a prediction technique. The database used corresponds to the users, revenues, and traffic of 15 network operators obtained from the Communications Regulation Commission of the Republic of Colombia. The ability of LSTMs to handle temporal sequences, long-term dependencies, adaptability to changes, and complex data management makes them an excellent strategy for predicting and forecasting the telecom market. Various works involve LSTM and telecommunications. However, many questions remain in prediction. Various strategies can be proposed, and continued research should focus on providing cognitive engines to address further challenges. MATLAB is used for the design and subsequent implementation. The low Root Mean Squared Error (RMSE) values and the acceptable levels of Mean Absolute Percentage Error (MAPE), especially in an environment characterized by high variability in the number of users, support the conclusion that the implemented model exhibits excellent performance in terms of precision in the prediction process in both open-loop and closed-loop.

Floods have always been an unavoidable natural disaster globally. Due to that, many efforts have been taken in order to alleviate the effect, especially in protecting the victims from losing their lives as well as their belongings. This study focuses on ensuring a smooth allocation process for flood victims to the relief centres considering the nature of their location, near the river, inland, and coastal. The finding indicated that a few implications have been highlighted for disaster management, such as changes in flood victim allocation patterns, classification of prone areas based on three areas, identification of most disaster areas, and others. Thus, to enhance the efficiency of allocation and to avoid any bad incidents happening during the flood occurrence, the allocation of flood victims is proposed to be started at a more critical area like the river area and followed by other areas. The finding also indicated that the proposed allocation procedure yielded a slightly lower average travel distance than the existing practice. These findings could also provide valuable information for disaster management in implementing a more efficient allocation procedure during a disaster.