Digitalization has recently gained significant relevance in the education field. The focus has been on its use and application, as well as on training teachers and students to become responsible, competent, and ethical users of technology. This is connected to the creation of policies and programs that promote online learning and interaction from basic to higher education. In this context, this study aims to analyze the scientific production related to digital citizenship through a bibliometric mapping of publications indexed in the Web of Science database. The goal is to identify the main research trends in this field. The results show a growth in the number of publications since 2016, mainly focusing on topics such as digital citizenship media, digital competences, higher education, teachers, students, adolescents, adults, competence, digital literacy, and citizenship education. The presence of a significant number of journals related to the field of education denotes a close relationship between this field and the topic of study. Also, it is revealing a higher concentration of research production in the United States and Europe, with Latin America being absent from this scenario. The study identifies an intellectual structure of the discipline, particularly regarding the most relevant authors, journals, and descriptors. These results are important for understanding the research practices inherent to the field, which projects digital citizenship as an emerging topic. The study concludes by proposing lines of interest for further research on the topic in education and other fields, as well as acknowledging the limitations found in the present article.

The successful execution of large-scale infrastructure projects is essential for economic growth and societal development, but these projects are too often beset with financial risks. The main financial risks related to infrastructure projects, including cost overrun, funding uncertainty, currency fluctuation, and regulatory change are examined in this research. The study identifies and assesses the magnitude and frequency of these risks by combining surveys and analysis of financial reports. The findings show that current risk management strategies, including hedging, contingency funds, and public-private partnerships, are often unsuitable to respond to the specific needs of financial uncertainties. The research suggests the need for an all-encompassing financial risk management framework that relies on real-time data analysis and a cocktail of risk assessment tools. Additionally, the development of strategic tailored approaches to address financial risk recovery depends on proactive stakeholder engagement. This research complements the existing literature on risk management in infrastructure projects by highlighting the financial dimensions of risk management and suggesting future research on advanced financial tools and technologies. Ultimately, large-scale infrastructure project sustainability and success contribute to economic stability and societal well-being can only be achieved through effective financial risk management.

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 business life cycle is examined through a comprehensive literature review in this academic study. Our initial approach involves searching for relevant articles on firm life cycle and strategy using the Web of Science and Scopus databases. We conduct bibliometric analyses to identify key contributors and recurring keywords. Subsequently, we select twenty-seven research papers to explore the Theory Development, Characteristics, Context, and Methodology (TCCM) framework for firm life cycle and strategy. Our analysis summarizes corresponding business strategies for each stage, including the use of Initial Management Control Systems (MCS) in the introduction phase. As companies grow, a high inventory-to-sales ratio may hinder effectiveness, but it proves beneficial in the growth and revival stages. Mature companies excel in green process innovation and engage more in Corporate Social Responsibility (CSR) activities. In the decline stage, firms use cost efficiencies, asset retrenchment, and core activity focus for recovery, signaling commitment to a successful turnaround. However, there is a research gap in exploring appropriate global strategies for various life cycle stages, providing an opportunity for additional articles to thoroughly investigate this relationship and assess multinational enterprises’ success trajectories throughout their life cycles.

The main purpose of this paper was to examine the impact of generative artificial intelligence (AI) on employee well-being and work dynamics. Using qualitative methodology, three semi-structured interviews were conducted to investigate the implications of generative AI on employee outcomes such as efficiency, job satisfaction, ethical considerations, and work-life balance. The findings highlighted the potential benefits and risks associated with generative AI implementation in the workplace. The study contributed to the literature by adopting a qualitative approach, allowing in-depth exploration of individual experiences with generative AI in the workplace. The study discussed the implications for employers, employees, and society.

Immeasurable basic and applied information has been evolved on all important floricultural crops through large-scale worldwide research on interdisciplinary aspects. The quantum and quality of work done on Chrysanthemum, among all other ornamentals, are par excellence. Conscientious attempt has been made to collect the whole multidisciplinary experimental results achieved world over. Despite remarkable achievements in knowledge and technology, a major part of present experimental research on chrysanthemum is largely a routine repeat of work. Assessment of past and present work is now significant for preparing target-oriented future research resolutions. This will help to secure the favored results within a justifiable period.