Digital transformation is a significant phenomenon that affects almost every business sector, particularly the telecommunications industry, which is closely intertwined with information technology. This study is grounded in McLuhan’s concept of technological determinism and Martin Heidegger’s philosophy of technology, which asserts that media and technology shape human thoughts and interactions, benefiting individuals, society, and culture alike. The primary objective of this research is to investigate the environmental factors that influence digital transformation and to assess its impact on the strategic renewal of a company. This research employs exploratory qualitative methods, collecting in-depth information through interviews with the respondents from Indonesia’s leading telecommunications operator who can provide comprehensive and contextual insights into digital transformation. The findings reveal specific environmental factors that drive digital transformation. The major identified components of strategic renewal include advancements in information technology, the role of human resources, and interactions with external parties, including customers and partners.

The cars industry has undergone significant technological advancements, with data analytics and artificial intelligence (AI) reshaping its operations. This study aims to examine the revolutionary influence of artificial intelligence and data analytics on the cars sector, particularly in terms of supporting sustainable business practices and enhancing profitability. Technology-organization-environment model and the triple bottom line technique were both used in this study to estimate the influence of technological factors, organizational factors, and environmental factors on social, environmental (planet), and economic. The data for this research was collected through a structured questionnaire containing closed questions. A total of 327 participants responded to the questionnaire from different professionals in the cars sector. The study was conducted in the cars industry, where the problem of the study revolved around addressing artificial intelligence in its various aspects and how it can affect sustainable business practices and firms’ profitability. The study highlights that the cars industry sector can be transformed significantly by using AI and data analytics within the TOE framework and with a focus on triple bottom line (TBL) outputs. However, in order to fully benefit from these advantages, new technologies need to be implemented while maintaining moral and legal standards and continuously developing them. This approach has the potential to guide the cars industry towards a future that is environmentally friendly, economically feasible, and socially responsible. The paper’s primary contribution is to assist professionals in the industry in strategically utilizing Artificial Intelligence and data analytics to advance and transform the industry.

Relational database models offer a pathway for the storage, standardization, and analysis of factors influencing national sports development. While existing research delves into the factors linked with sporting success, there remains an unexplored avenue for the design of databases that seamlessly integrate quantitative analyses of these factors. This study aims to design a relational database to store and analyse quantitative sport development data by employing information technology tools. The database design was carried out in three phases: (i) exploratory study for context analysis, identification, and delimitation of the data scope; (ii) data extraction from primary sources and cataloguing; (iii) database design to allow an integrated analysis of different dimensions and production of quantitative indicators. An entity-relationship diagram and an entity-relationship model were built to organize and store information relating to sports, organizations, people, investments, venues, facilities, materials, events, and sports results, enabling the sharing of data across tables and avoiding redundancies. This strategy demonstrated potential for future knowledge advancement by including the establishment of perpetual data updates through coding and web scraping. This, in turn, empowers the continuous evaluation and vigilance of organizational performance metrics and sports development policies, aligning seamlessly with the journal’s focus on cutting-edge methodologies in the realm of digital technology.

The high unemployment rate among university graduates is prompting universities to enhance the business skills of their students. This research aims to holistically explain the role of university support and entrepreneurial resilience in increasing students’ business innovation capabilities. To analyze phenomena and relationships between variables, a quantitative approach using partial least square structural equation modeling (PLS-SEM) was used. This research sample involved 165 student entrepreneurs who are members of the student entrepreneur community in Indonesia. Knowledge management does not significantly impact increasing business innovation capabilities. However, perceived university support and entrepreneurial resilience have been shown to significantly impact business innovation capabilities and strengthen the influence of knowledge management activities on increasing business innovation capabilities. Universities must create policies supporting extracurricular entrepreneurship programs, focusing on building entrepreneurial resilience. This can be achieved through workshops and business incubator initiatives involving partnerships with industry and the entrepreneurial community. This research provides a new perspective in analyzing higher education entrepreneurship education through a more in-depth explanation of the extracurricular activities of the student business community to build business innovation capabilities based on knowledge, institutional, and trait theory perspectives.

The study aims to explain the relationship between the effectiveness of a business and its management through the analysis of working capital. The findings prove the complementary relationship. The analysis of working capital will always have a significant impact on the effectiveness of business management. The main objective of any corporation is to be effective in business, which can be achieved by analyzing the working capital. The result shows that analysis of working capital based on factors like operational efficiency, the company’s earnings and profitability, cash management, corporate receivable management, and corporate inventory management creates room for improvement and effectiveness in business management. Firms might enhance finances for business expansion by lowering their working capital requirements. It has also been revealed that there is a considerable difference in industries across time. It was observed that there is a high association between working capital efficiency and firm profitability. A highly efficient corporation is less vulnerable to liquidity risk and is also self-sufficient in terms of external finance. Numerous studies have been done to regulate the true rapport between working capital investments and their impact on financial presentation. It demonstrates that effective investment in working capital management may boost profitability and business value. The relationship between accounting and finance was explained by measuring working capital management in demand to illustrate the status of profitability. It was suggested that accountants take a more professional approach to updating their accounting and finance skills in their organization through effective working capital management.

In the modern economy, non-financial reporting has become an essential tool for evaluating the social performance of companies. This article explores the importance of non-financial reporting as a central element in assessing sustainable performance, focusing on analyzing sustainability reports published by 20 companies listed on the Bucharest Stock Exchange (BVB). The study examines how these companies approach environmental, social, and governance (ESG) aspects in their reports and what is the relationship between these aspects and financial reporting indicators. Through the statistical analysis of the non-financial reports published by companies participating in the study with the help of the Pearson coefficient and the regression equations, the correlation between the financial and non-financial indicators is determined in order to validate the research hypotheses. The results indicate increased attention to transparency and social responsibility, highlighting the correlation between sound reporting practices and cooperative performance by combining social and environmental aspects with financial information. The research also highlights the challenges encountered in the reporting process and the level of compliance with international sustainability standards.