Amidst an upsurge in the quantity of delinquent loans, the financial industry is experiencing a fundamental transformation in the approaches utilised for debt recovery. The debt collection process is presently undergoing automation and improvement through the utilisation of Artificial Intelligence (AI), an emergent technology that holds the potential to revolutionise this sector. By leveraging machine learning, natural language processing, and predictive analytics, automated debt recovery systems analyse vast quantities of data, generate forecasts regarding the likelihood of recovery, and streamline operational processes. Debt collection systems powered by AI are anticipated to be compliant, precise, and effective. On the other hand, conventional approaches are linked to increasing expenditures and inefficiencies in operations. These solutions facilitate efficient resource allocation, customised communication, and rapid data analysis, all while minimising the need for human intervention. Significant progress has been made in data analytics, predictive modelling, and decision-making through the application of artificial intelligence (AI) in debt recovery; this has the potential to revolutionize the financial sector’s approach to debt management. The findings of the research underscore the criticality of artificial intelligence (AI) in attaining efficacy and precision, in addition to the imperative of a data-centric framework to fundamentally reshape approaches to debt collection. In conclusion, artificial intelligence possesses the capacity to profoundly transform the existing approaches utilized in debt management, thereby guaranteeing financial institutions’ sustained profitability and efficacy. The application of machine learning methodologies, including predictive modelling and logistic regression, signifies the potential of the system.

The research is focused on the evolution of the enterprises, in the field of specialized professional services, medium-period, enterprises that implemented projects financed within Regional Operational Program (ROP) during the 2007–2013 financial programming period. The analysis of the economic performance of the micro-enterprises corresponds to general objectives, but there can be outlined connections between these performances and other economic indicators that were not considered or followed through the financing program. The study case is focused on the development of micro-enterprises in the services area, in the Central Region, Romania (one of the eight development regions in Romania). The scientific approach for this article was based on a regressive statistical analysis. The analysis included the economic parameters for the enterprises selected, comparing the economic efficiency of these enterprises, during implementation with the economic efficiency after the implementation of the projects, during medium periods, including the sustainability period. The purpose of the research was to analyse the economic efficiency of the selected micro-enterprises, after finalizing the projects’ implementation. The authors intend to point out the need for a managerial instrument based on the economic efficiency of companies that are benefiting from non-reimbursable funds. This instrument should be taken into consideration in planning regional development at the national level, regarding the conditions and results expected. Although the authors used regressive statistical analysis the purpose was to prove that there is a need for additional managerial instruments when the financial allocations are being designed at the regional level. This study follows the interest of the authors in proving that the efficiency of non-reimbursable funds should be analysed distinctively on the activity sectors.

Technological management has promoted distinctive characteristics in the socio-productive development of the regions. Its usefulness in entrepreneurial activity is studied to design the architecture of a technological observatory as an intelligent system for entrepreneurship in Latin America. Using a descriptive-explanatory method, data obtained from the application of two instruments directed to 18 experts in information and communication technologies and 174 entrepreneurs distributed 92 in Lima-Peru and 82 in Santiago de Cali-Colombia are processed. The findings show informational and training barriers and a weak or non-existent technological platform for effective entrepreneurial development. Added to the low development of plans and alliances mediated by technologies, whose experience supports public policies that strengthen entrepreneurship as an emerging economy. The architecture supports the functional and operational aspects of the system. Its scalability in other regions dynamizes the services-processes required prior to the detection of needs directed towards the projection of sustainable entrepreneurship.

The intensification of urbanization worldwide, particularly in China, has led to significant challenges in maintaining sustainable urban environments, primarily due to the Urban Heat Island (UHI) effect. This effect exacerbates urban thermal stress, leading to increased energy consumption, poor air quality, and heightened health risks. In response, urban green spaces are recognized for their role in ameliorating urban heat and enhancing environmental resilience. This paper has studied the microclimate regulation effects of three representative classical gardens in Suzhou—the Humble Administrator’s Garden, the Lingering Garden and the Canglang Pavilion. It aims to explore the specific impacts of water bodies, vegetation and architectural features on the air temperature and relative humidity within the gardens. With the help of Geographic Information System (GIS) technology and the Inverse Distance Weighted (IDW) spatial interpolation method, this study has analyzed the microclimate regulation mechanisms in the designs of these traditional gardens. The results show that water bodies and lush vegetation have significant effects on reducing temperature and increasing humidity, while the architectural structures and rocks have affected the distribution and retention of heat to some extent. These findings not only enrich our understanding of the role of the design principles of classical gardens in climate adaptability but also provide important theoretical basis and practical guidance for the design of modern urban parks and the planning of sustainable urban environments. In addition, the study highlights GIS-based spatial interpolation as a valuable tool for visualizing and optimizing thermal comfort in urban landscapes, providing insights for developing resilient urban green spaces.