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Volume 15, Issue 1, March 2025 |
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A COMPARISON BETWEEN TWO ROMANIAN DEVELOPMENT REGIONS FROM A SMART CITY PERSPECTIVE Alexandra GONTEAN Babes-Bolyai University, Cluj-Napoca Romania Vlad-Tudor TRINCĂ Babes-Bolyai University, Cluj-Napoca Romania DOI: https://doi.org/10.24818/beman/2025.15.1-01 |
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Smart city initiatives are becoming more visible nowadays in Eastern Europe, due to the rapid steps taken in terms of digitalization during the pandemic and the funding opportunities available. The comparison of two Romanian development regions will be the main focus of this study, which will highlight the fact that there are no notable differences between the two development regions while demonstrating that a number of factors influence the degree of smart city project implementation within the communities. Both interested parties and academics studying the smart city framework may find value in the study's findings. |
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2. SHAPING HIGHER EDUCATION: THE RISE OF ENTREPRENEURIAL UNIVERSITIES Florina-Sanda TRIPA
University of Oradea, Oradea Romania Daniel BADULESCU
University of Oradea, Oradea Romania Alina BADULESCU
University of Oradea, Oradea Romania Simona-Aurelia BODOG
University of Oradea, Oradea Romania DOI:
https://doi.org/10.24818/beman/2025.15.1-02 |
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Entrepreneurial universities play a crucial role in existing economic landscape, stimulating innovation, entrepreneurial initiative and economic development. These institutions extend their traditional mission of teaching and research by integrating an entrepreneurial perspective, promoting the commercialization of research and supporting start- ups. The concept of the entrepreneurial university has evolved significantly, now including actions and initiatives that support innovation and knowledge transfer to industry and communities. Factors such as visionary leadership, institutional culture, support networks and collaborations with business and public authorities are essential for the development of these universities. For regional development, knowledge transfer and commercialization of the academic research’s outcomes, the incubators and support for new firms are also important activities promoted by these universities. While facing challenges such as funding constraints and bureaucratic hurdles, entrepreneurial universities have significant opportunities to innovate and collaborate with industry partners. Their impact on regional development is evident by creating jobs, stimulating innovation and improving the local entrepreneurial ecosystem, thus contributing to economic growth and human capital development.
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3. ETHICAL DIMENSIONS OF HUMAN RESOURCES AUDITING IN THE DIGITAL ERA Alice STEFANESCU Bucharest University of Economic Studies, Bucharest Romania Daria MARIN Bucharest University of Economic Studies, Bucharest Romania
DOI: https://doi.org/10.24818/beman/2025.15.1-03 |
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Digital human resources (HR) auditing reshapes organizational practices, enhancing efficiency and fostering innovation through advanced technologies such as artificial intelligence (AI), blockchain, and predictive analytics. However, these tools also pose significant ethical challenges, including data confidentiality, algorithmic bias, and the complexity of international regulatory frameworks. This article examines these ethical dilemmas, emphasizing the impact of digital transformation on organizational culture and providing recommendations for the ethical use of technologies in HR auditing. By prioritizing transparency, security, and diversity, organizations can balance digital benefits with respect for employees' rights and values, establishing digital HR auditing as a cornerstone of sustainable corporate governance. |
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Mirela POPA Babes-Bolyai University, Cluj-Napoca
Romania Anuța BUIGA Babes-Bolyai University, Cluj-Napoca
Romania Lavinia BECEA Babes-Bolyai University, Cluj-Napoca
Romania DOI: https://doi.org/10.24818/beman/2025.15.1-04 |
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This study aims to examine the effects of FDI (foreign direct investment) on sustainable economic growth in 73 countries and to analyze the impact of FDI on inequalities between countries. The economic growth of a country is measured by the real gross domestic product per capita (GDPpc). The inequalities between countries are measured by the Sustainable Development Goals score, respectively the SDG10 score (reduced inequalities) and the SDG8 score (decent work and economic growth). The study shows that the statistically significant impact of exogenous variables on GDPpc or SDG10 score, differs from one group of countries to another, as follows: (1) in small countries (the size of the population), purchasing power index of exports (PPexp) negatively affects GDPpc, while productive capacities index and FDI inward positively affect GDPpc; (2) in large countries, PPexp (negatively) and GDP growth (positively) affect SDG10; (3) in developed countries, PPexp negatively affects GDPpc; (4) in developing countries Gross Fixed Capital Formation Inward (positively) and GDP growth (negatively) affect GDPpc. FDI inward and Gross Fixed Capital inward have negative impact on SDG10, while FDI outward and Gross Fixed Capital outward positively affect SDG10, only in developing countries; (5) in high-income countries, FDI positively affects GDPpc; (6) GDP growth has a positive and statistically significant impact on SDG10 only in upper-middle countries. The multiple regression coefficients that highlight the impact of exogenous variables on SDG8, do not highlight differences between high-income, upper-middle-income and lower-middle-income countries. |
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Ioana-Marcela PĂCURARU Bucharest University of Economic Studies, Bucharest Romania Ciprian-Sorin CHIRVASE Bucharest University of Economic Studies, Bucharest Romania Ştefan-Ioan TIRITEU Bucharest University of Economic Studies, Bucharest Romania
DOI: https://doi.org/10.24818/beman/2025.15.1-05 |
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Artificial Intelligence (AI) has emerged as a transformative technology in healthcare, significantly advancing personalised medicine. By leveraging vast amounts of data, AI enhances early disease detection, tailors treatments to individual patients, and optimises medical resource management. Despite these advantages, the integration of AI in healthcare presents challenges, including concerns over data privacy, acceptance among healthcare professionals, and the need for comprehensive regulatory frameworks. Therefore, this study investigates the impact of AI on personalised medicine, assessing its benefits, limitations, and real-world applications. It explores AI’s role in diagnostics, personalised treatment strategies, and the optimisation of medical workflows, while critically examining ethical and legal challenges. The study also underscores the necessity of robust regulations to ensure responsible and ethical AI deployment in healthcare. A systematic documentary analysis of scientific articles, case studies, and healthcare organisation reports forms the basis of this research. Case studies from hospitals and companies that have successfully implemented AI are analysed to evaluate its impact on diagnostic accuracy, treatment efficiency, and medical costs. The findings are correlated with existing literature to provide a comprehensive perspective on current and future trends in AI-driven personalised medicine. The results of this study show that AI has demonstrated significant improvements in diagnostic precision, reduced the time required for disease identification, and enhanced the effectiveness of personalised treatment plans. Studies indicate that AI-driven approaches contribute to cost reductions by minimising late-stage treatments and enabling more efficient allocation of medical resources. However, critical challenges such as algorithm transparency, bias mitigation, and patient data security continue to hinder widespread AI adoption in healthcare. |
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6. BUILDING INTERNAL INNOVATION CAPACITY IN LARGE ENTERPRISES: A STRATEGIC IMPERATIVE Alexandra POPESCU-ZORICA Bucharest University of Economic Studies, Bucharest Romania
DOI: https://doi.org/10.24818/beman/2025.15.1-06 |
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This paper explores the necessity for large enterprises to develop robust internal innovation capabilities as a strategic imperative for sustaining long-term competitiveness. While 83% of global companies prioritize innovation, only 3% demonstrate high innovation readiness, highlighting a gap between ambition and execution. The study employs a literature review and case study analysis to examine the structural and cultural barriers that hinder corporate innovation, including risk aversion, hierarchical decision-making, and a focus on operational efficiency over exploration. The research further evaluates leading innovation governance models, including Deschamps & Nelson’s governance structures and Brouwer’s hierarchical, market-driven, and hybrid models, as well as practical innovation frameworks such as the Ambidextrous Organization Model and Doblin’s Ten Types of Innovation. The findings suggest that companies must move beyond incremental improvements and acquisitions by implementing adaptive governance structures, cross-functional collaboration, and long-term strategic foresight. The paper identifies a set of best practices for developing innovation capacity, including the integration of intrapreneurship programs, AI-driven innovation, open innovation partnerships, and agile methodologies. The research concludes that organizations achieving a balance between governance structure, innovation frameworks, and strategic adaptability outperform competitors in growth and resilience. Recommendations include establishing leadership commitment, aligning innovation efforts with corporate strategy, and fostering a culture of experimentation to drive long-term business success. |
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Genevieve BAKAM Tshwane University of Technology, Pretoria South Africa
Khumbulani MPOFU Tshwane University of Technology, Pretoria South Africa
Charles MBOHWA Tshwane University of Technology, Pretoria South Africa
DOI: https://doi.org/10.24818/beman/2025.15.1-07 |
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In addition to digital transformation, businesses have reviewed their business strategies and decision-making techniques to develop a competitive advantage in the transport manufacturing sector. It happens that innovative business approaches face some limitations compromising business survival in the long term. This study investigates the importance of adopting a reference model for business analytics-based decision-making processes in rail transport manufacturing companies. This study follows a qualitative research design using secondary data published in various annual reports to define the thematic analysis around descriptive, prescriptive, and predictive analytics for enhanced business analytics-based decision-making solutions. Results indicate that improved business decisions should be based on the combination of company strategies, technology innovation and business analytics techniques for goals alignment, innovative solutions and data visualisation. Additionally, descriptive, prescriptive, and predictive analytics are generated in a predefined format to suit business, socioeconomic and environmental requirements like product localisation, company equity, financial support of black businesses, skills development, local community empowerment, and environmental protection. Business analytics-based decisions enable cost control, differentiated business decisions for competitive advantage, and strategy upgrades in addition to customer satisfaction, profitability growth and long-term sustainability. The proposed reference model shows the link between company strategies, data analysis, and technology impact in generating enhanced analytics powering the decision-making process in transport manufacturing to ensure the revitalisation of future transport in South Africa. Recommendations highlight that the South African government should improve technology infrastructure and skills development to limit resistance to digital transformation enabling business analytics. |