In Central and Eastern European countries, the labour shortage is becoming increasingly pronounced, posing a challenge for the economy. Labour shortages limit the potential national income as many positions remain unfilled, which could lead to a slowdown in economic growth. To address this issue, various solutions need to be explored. This research aims to analyze solutions for alleviating labour shortages, with particular emphasis on measures that encourage workforce participation. One strategy is introducing training and retraining programs that help workers develop skills and adapt to labour market demands. Another option is to promote part-time employment, which may be especially attractive to groups unable or unwilling to work full-time. Enhancing population mobility could also be crucial in addressing labour shortages, particularly in bridging regional disparities. Integrating certain inactive groups, such as retirees, homemakers, students, people with disabilities, and those with low education levels experiencing generational poverty, into the labour market could also yield significant benefits. The study employs quantitative analysis methods and includes a survey that examines citizens’ perspectives on the effectiveness of measures aimed at increasing labour market participation and their economic impact on the Slovak economy. The survey data were collected in 2023 in the region of Rožňava and its surrounding areas.
Credit risk assessment is one of the most important aspects of financial decision-making processes. This study presents a systematic review of the literature on the application of Artificial Intelligence (AI) and Machine Learning (ML) techniques in credit risk assessment, offering insights into methodologies, outcomes, and prevalent analysis techniques. Covering studies from diverse regions and countries, the review focuses on AI/ML-based credit risk assessment from consumer and corporate perspectives. Employing the PRISMA framework, Antecedents, Decisions, and Outcomes (ADO) framework and stringent inclusion criteria, the review analyses geographic focus, methodologies, results, and analytical techniques. It examines a wide array of datasets and approaches, from traditional statistical methods to advanced AI/ML and deep learning techniques, emphasizing their impact on improving lending practices and ensuring fairness for borrowers. The discussion section critically evaluates the contributions and limitations of existing research papers, providing novel insights and comprehensive coverage. This review highlights the international scope of research in this field, with contributions from various countries providing diverse perspectives. This systematic review enhances understanding of the evolving landscape of credit risk assessment and offers valuable insights into the application, challenges, and opportunities of AI and ML in this critical financial domain. By comparing findings with existing survey papers, this review identifies novel insights and contributions, making it a valuable resource for researchers, practitioners, and policymakers in the financial industry.
The purpose of this study is to investigate different factors associated with remote online home-based learning (thereafter named OHL), including technical system quality, perceived quality of contents, perceived ease of use, and perceived usefulness in relation to the satisfaction of undergraduate students following the post-COVID-19 pandemic in Malaysia. Additionally, the mediating roles of attitude are also investigated. Two hundred questionnaires were distributed using judgmental sampling method and 156 completed responses were collected. The data were subsequently analyzed using PLS-SEM. The findings imply that the OHL system is an effective method although it is challenging to operate. In terms of perceived technical system quality, OHL is currently more gratifying for students; however, some have reported that the quality of the content delivered via the remote system is still unsatisfactory. Moreover, the study found that attitude is a significant determinant of undergraduates’ satisfaction with OHL. This study contributes to the advancement of current knowledge by inspecting the factors of the Undergraduate Level OHL System using the mediating roles of attitude. In terms of underpinning theories, Technology Acceptance Model and Information System Model were employed as the guiding principles of the current study.
A smart city focuses on enhancing and interconnecting facilities and services through digital technology to offer convenient services for both people and businesses. The basic infrastructure of smart cities consists of modern technologies such as the Internet of Things (IoT), cloud computing and artificial intelligence. These urban areas utilize different networks, such as the Internet and IoT, to share real-time information, improving convenience for the inhabitants. However, the reliance of smart cities on modern technologies exposes them to a range of organized, diverse, and sophisticated cyber threats. Therefore, prioritizing cybersecurity awareness and implementing appropriate measures and solutions are essential to protect the privacy and security of citizens. This study aims to identify cyber threats and their impact on smart cities, as well as the methods and measures required for key areas such as smart government, smart healthcare, smart mobility, smart environment, smart economy, smart living, and smart people. Furthermore, this study seeks to evaluate previous research in this field, establish necessary policies to mitigate these threats, and propose an appropriate model for the infrastructure associated with IT networks in smart cities.
Buru Regency is the primary hub for producing eucalyptus oil, a highly valued commodity in the region. The oil extracted from the eucalyptus epidemic plant possesses antiseptic, antibacterial, and antifungal characteristics. Amidst the Covid-19 pandemic, numerous industries require it as a fundamental component of pharmaceuticals. An essential factor in the eucalyptus oil production process is the presence of eucalyptus leaves. Therefore, leaf-sorting workers, including women, are required to ensure this availability. However, in reality, the daily lives of eucalyptus leaf massagers are characterized by challenging economic conditions and a socio-economic environment that lags behind workers in other sectors. This study aims to examine and investigate the roles and work patterns of employed women and the strategies they employ to ensure the consistent flow of household income. The research employed a qualitative methodology with a phenomenological approach. A total of 24 informants were purposefully selected based on their involvement in achieving the research objectives. The results indicate that the COVID-19 pandemic has altered the circumstances of women who collect leaves and rely heavily on eucalyptus trees as a natural resource. Physical adaptation strategies are the preferred methods used to fulfill household requirements. Implementing physical adaptations does not deter women leaf-sorters from continuing their work. Their commitment to meeting their basic needs significantly motivates them to persist in their role as leaf sorters. The income of women engaged in sorting eucalyptus leaves in their households during the COVID-19 pandemic.
The global COVID-19 crisis has precipitated an economic downturn in many countries, subsequently raising concerns about the potential challenges faced by marginalized populations, such as refugees, in accessing essential healthcare, hygiene facilities, and critical health information and safety guidelines within the context of Jordan. Consequently, it is of paramount importance to investigate and evaluate the specific economic hurdles related to COVID-19 that refugees are encountering. This inquiry will serve as a valuable foundation for shaping public health interventions aimed at containing the virus’s spread and guiding policymakers on strategies to enhance the well-being of refugees in Jordan. This paper offers a comprehensive examination of Syrian refugees in Jordan, including an analysis of the policies implemented by Jordan concerning Syrian refugees in the context of the COVID-19 pandemic. Moreover, the report assesses whether international assistance, both through bilateral and multilateral channels, can mitigate the impact of COVID-19 on Jordan’s capacity to continue hosting Syrian refugees. It also delves into the economic consequences of COVID-19, covering aspects such as poverty, education, the health sector budget, healthcare accessibility, essential needs, livelihoods, the labor market, and food security among Syrian refugees in Jordan.
Copyright © by EnPress Publisher. All rights reserved.