The Republic of Moldova is a state with a small, but dynamic economy and which, with the help of competitiveness in the IT industry, is looking for a place on the economic market in the Eastern European region. The research approaches this topic from an economic, historical, but also geopolitical point of view. This analysis of economic data and figures from the last period, combined with government policies and that of the National Bank of Moldova, means that in the near future the software economic area of Moldova will become an important regional player in this part of Europe.

Despite the apparent agreement today on the concept of sustainability, the means to achieve it holistically are still controversial. “Just sustainability” concept has recently gained traction, casting doubt on whether sustainability can be attained under capitalism. On the social level, many recent urban studies have been concerned with the concept of social justice and the distribution of resources and wealth as a means to achieving socially equitable sustainability. In this regard, a few questions are brought up: can social sustainability be achieved under capitalism? Are Islamic built environments a viable alternative? Many contemporary studies have described Islamic built environments as sustainable and strived for defining their sustainability criteria. However, they mostly focused on the built environment’s physical environmental aspects without relating them to the socio-economic spheres. Using the concepts of power and rights as key analytical tools, the paper examines a few capitalist utopian reform approaches and compares them in terms of their ability to achieve just sustainability with Islamic built environments. Several examples from primary Islamic history books will be used to examine Islamic built environments. It is concluded that Islamic built environments have attained the just sustainability that contemporary reform approaches sought to accomplish.

In rural areas, land use activities around primary arterial roads influence the road section’s traffic characteristics. Regulations dictate the design of primary arterial roads to accommodate high speeds. Hence, there is a mix of traffic between high-speed vehicles and vulnerable road users (pedestrians, bicycles, and motorcycles) around the land. As a result, researchers have identified several arterial roads in Indonesia as accident-prone areas. Therefore, to improve the road user’s safety on primary arterial roads, it is necessary to develop models of the influence of various factors on road traffic accidents. This research uses binary logistic regression analysis. The independent variables are carelessness, disorderliness, high speed, horizontal alignment, road width, clear zone, road shoulder width, signs, markings, and land use. Meanwhile, the dependent variable is the frequency of accidents, where the frequency of accidents consists of multi-accident vehicles (MAV) and single-accident vehicles (SAV). This study collects data for a traffic accident prediction model based on collision frequency in accident-prone areas. The results, road shoulder width, and road sign factor all have an impact on the frequency of traffic accidents. According to a realistic risk analysis, MAV and SAV have no risk difference. After validation, this model shows a confidence level of 92%. This demonstrates that the model generates estimations that accurately reflect reality and are applicable to a wider population. This research has the potential to assist engineers in improving road safety on primary arterial roads. In addition, the model can help the government measure the impact of implemented policies and engage the public in traffic accident prevention efforts.

This study investigates how financial literacy affects the financial health of Saudi Arabian banking industry workers in Saudi Arabia. The study uses a sample of 183 individuals and a comprehensive framework that includes components like financial behaviour, risk management, financial planning, financial knowledge, financial confidence, financial communication, and overall financial pleasure. The study finds strong positive correlations between many aspects of financial well-being and financial literacy through correlation and regression analysis. Notably, risk management, financial behaviour, overall financial contentment, and financial confidence are all positively impacted by financial literacy. The results underscore the multifaceted character of financial well-being and underscore the critical function of financial literacy in moulding favourable financial consequences. Furthermore, the study pinpoints particular domains in which focused financial literacy initiatives might be executed to augment the general financial welfare of banking industry staff members. The study sheds light on the relationship between financial literacy and well-being in a particular occupational context, which is significant information for both the academic and practical domains. The banking industry needs customized financial education programs because of the social and management ramifications. These programs will help the community’s overall financial health in addition to providing benefits to individual employees. In its conclusion, the study makes recommendations for other research directions, such as longitudinal studies and examinations of the function of digital financial literacy in the changing banking environment.

Nowadays, customer service in telecommunications companies is often characterized by long waiting times and impersonal responses, leading to customer dissatisfaction, increased complaints, and higher operational costs. This study aims to optimize the customer service process through the implementation of a Generative AI Voicebot, developed using the SCRUMBAN methodology, which comprises seven phases: Objectives, To-Do Tasks, Analysis, Development, Testing, Deployment, and Completion. An experimental design was used with an experimental group and a control group, selecting a representative sample of 30 customer service processes for each evaluated indicator. The results showed a 34.72% reduction in the average time to resolve issues, a 33.12% decrease in service cancellation rates, and a 97% increase in customer satisfaction. The implications of this research suggest that the use of Generative AI In Voicebots can transform support strategies in service companies. In conclusion, the implementation of the Generative AI Voicebot has proven effective in significantly reducing resolution time and markedly increasing customer satisfaction. Future research is recommended to further explore the SCRUMBAN methodology and extend the use of Generative AI Voicebots in various business contexts.