In the 21st century, brand communication has been significantly transformed through the interaction of users and artificial intelligence (AI), who co-create and recreate texts in digital environments. This evolution challenges traditional disciplines and roles, opening new perspectives for textual production on multiple platforms. The study examines the current state and application of the textual component in brand communication, exploring its disciplinary foundations, rhetorical traces, and research methodologies. To this end, a content analysis of 97 relevant publications from 2000 to 2024 was conducted, selected for their impact on the field of brand communication and following the guidelines established in the PRISMA statement. The results identified three sources of textual creation: Organization, users and algorithms. In addition, persuasion and sentiment take precedence at the rhetorical level, while data mining stands out in message analysis. In conclusion, the advertising text, which previously prevailed in brand communication with corporate authorship, formal prefiguration and a closed entity, now expands in a media and networked context. This text originates from a multiplicity of human and automated sources, overlapping rhetorical phases and fluid textualities. The shift implies a transition from unidirectional communication, characterized by repeated impacts, to multidirectional communication with spiraling trajectories and iterative adjustments. This challenges the boundaries of genres and formats, merging the persuasiveness of rhetoric and the imagination of storytelling. This situation demands commercial policies that integrate new professionals and roles, in partnership with the educational sector, and that address copyright with AI and users.

The application of optimization algorithms is crucial for analyzing oil and gas company portfolio and supporting decision-making. The paper investigates the process of optimizing a portfolio of oil and gas projects under economic uncertainty. The literature review explores the advantages of applying various optimizers to models that consider the mean and semi-standard deviations of stochastic multi-year cash flows and revenues. The methods and results of three different optimization algorithms are discussed: ranking and cutting algorithms, linear (Simplex) and evolutionary (genetic) algorithms. Functions of several key performance indicators were used to test these algorithms. The results confirmed that multi-objective optimization algorithms that examine various key performance indicators are used for efficient optimization in oil and gas companies. This paper proposes a multi-criteria optimization model for investment portfolios of oil and gas projects. The model considers the specific features of these projects and is based on the Markowitz portfolio theory and methodological recommendations for project assessment. An example of its practical application to oil and gas projects is also provided.

In the context of globalization and urbanization, rural development faces many challenges, such as population loss and uneven distribution of resources. This paper analyzes the similarities and differences in sustainable rural development strategies between China and Europe through a comparative perspective. China has optimized land use by relying on land policy innovations, such as the household contract responsibility system and the “separation of three rights”, as well as the construction of small towns; while Europe focuses on private ownership and market mechanisms, and supports agricultural and rural development through the Common Agricultural Policy (CAP). Using literature review, comparative research and policy analysis, the study shows that the policy innovations in China and Europe, each with its own focus, have been effective in promoting agricultural output and rural social development. Particularly noteworthy is that the “three rights” policy has increased agricultural productivity through the liberalization of management rights, while the European CAP has contributed to the diversification of the rural economy and environmental protection through continuous reforms. This study emphasizes that through policy innovation and international cooperation, combining the strengths of China and Europe, it is possible to provide a new model of sustainable development for the global countryside. Specifically, through the establishment of Sino-European R&D centers for agricultural science and technology, exchange of talents, and cooperation in green infrastructure development, technology transfer and application can be accelerated, cultural exchange and understanding can be promoted, and the sustainable development agenda for global rural areas can be jointly advanced.

This paper uses existing studies to explore how Artificial Intelligence (AI) advancements enhance recruitment, retention, and the effective management of a diverse workforce in South Africa. The extensive literature review revealed key themes used to contextualize the study. This study uses a meta-narrative approach to literature to review, critique and express what the literature says about the role of AI in talent recruitment, retention and diversity mapping within South Africa. An unobtrusive research technique, documentary analysis, is used to analyze literature. The findings reveal that South Africa’s Human Resource Management (HRM) landscape, marked by a combination of approaches, provides an opportunity to cultivate alternative methods attuned to contextual conditions in the global South. Consequently, adopting AI in recruiting, retaining, and managing a diverse workforce demands a critical examination of the colonial/apartheid past, integrating contemporary realities to explore the potential infusion of contextually relevant AI innovations in managing South Africa’s workforce.

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.

The internationalization of higher education began to take shape during the period of the Republic of China. This trend manifested in various forms and encompassed a rich array of activities, including the construction of teaching staffs, the exchange of international students, and the presence of overseas scholars giving lectures in China. Between 1899 and 1945, Japanese institutions sent nearly 200 academic overseas students to China. With the establishment and improvement of the internal system of universities in the Republic of China, these students were able to study and interact with Chinese scholars. The forms of communication were diverse, the content was rich, and the channels were smooth, making the process lively and interesting with distinct characteristics of the era. Consequently, this group became both participants and witnesses in the internationalization process of universities in the Republic of China. However, the full-scale Anti-Japanese War disrupted the internationalization of universities, causing it to deviate from its normal trajectory. Some Japanese academic overseas students who had previously studied in China became instruments of Japanese imperialism’s cultural invasion and educational colonization. These students played a significant role in promoting the “alternative internationalization” of universities in the Republic of China. In short, examining the involvement of Japanese academic overseas students providing us a unique insight into the general situation and processes of internationalization at universities in the Republic of China during different historical periods.

This study examines the determinants of inflation in Tunisia from 1998 to 2023, with a particular focus on the role of fiscal policy. The study analyzes the long-run and short-run relationships between inflation and key macroeconomic variables, including government expenditure, government revenue, money supply, balance of trade, and budget deficits using ARDL model. The empirical findings reveal that budget deficits have a significant and positive impact on inflation, underscoring the critical role of fiscal imbalances in driving price instability. In contrast, government expenditure, government revenue, money supply, and balance of trade do not exhibit statistically significant long-term effects on inflation. The results highlight the importance of fiscal discipline and effective coordination between fiscal and monetary policies to achieve price stability. These findings provide valuable insights for policymakers in Tunisia and other developing economies facing similar inflationary pressures, emphasizing the need for prudent fiscal management and structural reforms to mitigate inflation volatility and ensure macroeconomic stability.