The study of metaphor has a long history, and it has gradually been taken seriously from the very beginning of Aristotle of ancient Greek. In 1980, American scholars George Lakoff and Mark Johnson published the book Metaphor We Lived By jointly, from which metaphor began to be known as a way of cognition. The differences in languages and cultures, together with the complicated working mechanism of metaphor, post a great challenge in translating metaphor in literary work. This paper analyzes example sentences taken from Chinese classical works. By comparing these sentences with their English translations, we can have a glimpse of the translation strategies often used in rendering metaphor.

Extensive reading has enjoyed the increasing popularity from L2 educators as a potentially effective form of L2 reading instruction. However, many researchers tend to ignore the importance of selection of material. The paper is an attempt to explore the appropriate criteria of qualified graded readers, which can be helpful for English teachers and learners in ER program.

This study conducts a systematic literature review to analyze the integration of artificial intelligence (AI) within business excellence frameworks. An analysis of the findings in the reviewed articles yielded five major themes: AI technologies and intelligent systems; impact of AI on business operations, strategies, and models; AI-driven decision-making in infrastructure and policy contexts; new forms of innovation and competitiveness; and the impact of AI on organizational performance and value creation in infrastructure projects. The findings provide a comprehensive understanding of how AI can be integrated into organizational excellence emerged frameworks to address challenges in infrastructure governance, and sustainable development. Key questions addressed include: how AI affects consumer behavior and marketing strategies. What AI’s capabilities for businesses, especially marketing and digital strategies? How can organizations address the drivers and barriers to help make better use of AI in these business operations? Should organizations even do anything with these insights? These questions and more will be tackled throughout this discussion. This paper attempts to derive a comprehensive conceptual framework from several fields of human resources, operational excellence, and digital transformation, that can help guide organizations and policymakers in embedding AI into infrastructure and development initiatives. This framework will help practitioners navigate the complexities of AI integration, ensuring profitability and sustainable growth in a highly competitive landscape. By bridging the gap between AI technologies and development-related policy initiatives, this research contributes to the advancement of infrastructure governance, public management, and sustainable development.

While some conflict can serve as a more sophisticated stimulus to student achievement, significant or unresolved conflict can delay or even frustrate even the best-planned curriculum. The aim of our study is to get a clear picture of the conflicts with whom and to what extent the international students studying on our campuses have conflicts that affect their performance, and how they can manage them. In our study, based on a questionnaire survey (n = 480), we revealed that the international students at our university have the most conflicts with other foreign students, and the least with Hungarians, including their teachers. On the other hand, we found that according to the Thomas-Kilmann Conflict Instrument, they solve their problems by the Compromising and Accommodating style. The results obtained by detailed socio-demographic aspects show significant differences, mainly between gender, age, and country groups. Knowledge of the revealed facts and connections can offer conscious and careful solutions to understand and reduce tensions, and this can improve the understanding and management of conflict in the classroom, in collaborative projects, and even in non-teaching environments on campuses.

Artificial Intelligence (AI) has become a pivotal force in transforming the retail industry, particularly in the online shopping environment. This study investigates the impact of various AI applications—such as personalized recommendations, chatbots, predictive analytics, and social media engagement—on consumer buying behaviors. Employing a quantitative research design, data was collected from 760 respondents through a structured online survey. The snowball sampling technique facilitated the recruitment of participants, focusing on diverse demographics and their interactions with AI technologies in online retail. The findings reveal that AI-driven personalization significantly enhances consumer purchase intentions and satisfaction. Multiple regression analysis shows that AI personalization (β = 0.35, p < 0.001) has the most substantial impact on purchase intention, followed by chatbot effectiveness (β = 0.25, p < 0.001), predictive analytics (β = 0.20, p < 0.001), and social media engagement (β = 0.15, p < 0.01). Similarly, AI personalization (β = 0.30, p < 0.001), predictive analytics (β = 0.25, p < 0.001), and chatbot effectiveness (β = 0.20, p < 0.001) significantly influence consumer satisfaction. The hierarchical regression analysis underscores the importance of ethical considerations, showing that ethical and transparent use of AI increases consumer trust and engagement. Model 1 explains 45% of the variance in consumer behavior (R² = 0.45, F = 154.75, p < 0.001), while Model 2, incorporating ethical concerns, explains an additional 10% (R² = 0.55, F = 98.25, p < 0.001). This study highlights the necessity for retailers to leverage AI technologies ethically and effectively to gain a competitive edge, improve customer satisfaction, and drive long-term success. Future research should explore the long-term impacts of AI on consumer behavior and the integration of emerging technologies such as augmented reality and the Internet of Things (IoT) in retail.

The contraction of manufacturing economic activity in Latin American countries has been affected by the health crisis in the last few years. This phenomenon has negatively impacted the Latin American countries’ economies. In order to evaluate the impact of the manufacturing economy, this research integrates the impact of Foreign Direct Investment (FDI) on the growth of the Ecuadorian manufacturing sector, from 1981 to 2019, considering the role of the state through public spending using cointegration. The results are not consistent considering the empirical framework used; thus, FDI has a negative and significant influence on the manufacturing sector. Also, the manufacturing sector has a strong relationship with FDI in the short run and a less significant one in the long run. The results presented in this research suggest promoting domestic and FDI in the manufacturing sector, not only towards overexploited and monopolized sectors such as mining and telecommunications.