The effective allocation of resources within police patrol departments is crucial for maintaining public safety and operational efficiency. Traditional methods often fail to account for uncertainties and variabilities in police operations, such as fluctuating crime rates and dynamic response requirements. This study introduces a fuzzy multi-state network (FMSN) model to evaluate the reliability of resource allocation in police patrol departments. The model captures the complexities and uncertainties of patrol operations using fuzzy logic, providing a nuanced assessment of system reliability. Virtual data were generated to simulate various patrol scenarios. The model’s performance was analyzed under different configurations and parameter settings. Results show that resource sharing and redundancy significantly enhance system reliability. Sensitivity analysis highlights critical factors affecting reliability, offering valuable insights for optimizing resource management strategies in police organizations. This research provides a robust framework for improving the effectiveness and efficiency of police patrol operations under conditions of uncertainty.

This study investigated the utilization of Artificial Intelligence (AI) in the Recruitment and Selection Process and its effect on the Efficiency of Human Resource Management (HRM) and on the Effectiveness of Organizational Development (OD) in Jordanian commercial banks. The research aimed to provide solutions to reduce the cost, time, and effort spent in the process of HRM and to increase OD Effectiveness. The research model was developed based on comprehensive review of existing literature on the subject. The population of this study comprised HR Managers and Employees across all commercial banks in Jordan, and a census method was employed to gather 177 responses. Data analysis was conducted using Amos and SPSS software packages. The findings show a statistically significant positive impact of AI adoption in the Recruitment and Selection Process on HR Efficiency, which in turn positively impacted OD Effectiveness. Additionally, the study indicated that the ease-of-use of AI technologies played a positive moderating role in the relationship between the Recruitment and Selection Process through AI and HR Efficiency. This study concludes that implementing AI tools in Recruitment is vital through improving HR Efficiency and Organization Effectiveness.

This article examines how financial technology determines bank performance in different EU countries. The answer to that question would allow banks to choose their development policy. The paper focuses  on the main and most popular bank services that are linked to financial technology. A SWOT analysis of FinTech is also presented to show the benefits and drawbacks of FinTech. FinTech-based services are very diverse and are provided by financial  firms and banks alike. This paper looks at the financial technology provided by banks: internet usage (internet banking), number of ATMs, credit transfers in a country, percentage of the population in a country holding a debit or credit card and whether that population has received or made a digital payment. Using the multi-criteria assessment methods of CRITIC and EDAS, the authors analysed and compared the countries of the European Union and the financial technology used in them. As a result of the application of these methods, the EU countries under consideration were ranked in terms of the use of financial technology. Subsequently, three banks from different countries with different levels of the use of financial technology were selected for the study. For these banks, financial ratios of profitability were calculated to characterise their performance. Correlation and pairwise regression analyses between the banks’ profitability ratios and financial technology were used to assess the relationship and influence between these ratios. The main conclusion of the study focuses on the extent to which financial technology influences the performance of banks in the selected countries. It is likely that further research will try to take into account the size of the country’s population when analysing all financial technologies. Researchers also needed to find out what influence financial technologies have on the such financial indicators as operational efficiency (costs), financial stability, and capital adequacy.

The covid-19 pandemic has adversely affected the sustainability of micro and small enterprises (MSEs), with a particularly pronounced impact in Central Java. Entrepreneurs who struggle to adapt to reduced consumer purchasing power and the increasing reliance on digital technology are at heightened risk of business closure. Despite these challenges, inclusivity remains a crucial element for MSEs in fostering local economic development. Accordingly, this study seeks to examine the role of inclusivity in the sustainability of MSEs that are based on digital technology. Data were collected through the use of questionnaires and focus group discussions. Respondents were digital-based MSEs entrepreneurs from five selected regions, with Central Java having the largest number of digital media users. Key informants included experts from Diponegoro University, the International Council of Small Business (ICSB), the Department of Cooperatives and Micro, Small and Medium Enterprises at the provincial and district levels, and non-governmental organizations. The collected data was analyzed using the Rapid Appraisal for Micro and Small Enterprises (Rap-MSE’s) method. To assess the sustainability status, the study utilized several dimensions, including economic, environmental, social, institutional, technological, and inclusivity factors. Both multidimensional and individual analyses indicated that the sustainability status was relatively robust. MSEs that integrated digital technology into their operations were able to withstand the challenges posed by covid-19 and adapt to the new normal. In conclusion, the inclusivity dimension in the adoption of digital technology has gained increased importance in driving local economic development.

This study explores the interactions between inflation and stock market. We carried out a bibliometric analysis with R package to highlight the worldwide research trends in the field, covering the period of three crises (financial, health crisis and war of Ukraine). Next, using monthly data for the period from 1 March 2020 to 31 August 2023 and based on a vector autoregressive model, impulse response and variance decomposition are performed to explore the dynamic relationships between inflation and Greek stock market. The results reveal the existence of high volatility in Athens’ stock market during COVID-19 pandemic, owning to a shock of the inflation. Regarding the period of Ukrainian war, the study verified the Fama’s hypothesis that there is a negative relationship between inflation and stock returns. The findings have significant implications for investors and policy makers.