Peru is a country open to the world economy and to national and foreign investments; therefore, economic activities of an industrial, commercial and service nature in general are developed. It also has a wide variety of natural resources, which is why the state has chosen to apply differentiated treatment in the tax field to certain types of business activities by granting certain “benefits” and “incentives”. However, due to a lack of knowledge about tax legislation, they are not used adequately. In this context, the objective was to analyze the level of knowledge of the legislation, tax and its impact on the development of their operations in formal business aquaculture in the ring circumlacustrine of the region in 2021. It was developed under a descriptive correlational design with a sample of 80 circumlacustrine ring aquaculture companies. The results indicated that there is a low level of knowledge about tax legislation on the part of the owners of aquaculture companies, which negatively affects the development of their formal operations in the circumlacustrine ring of the Puno region. As a consequence, it has a negative impact on the formalization of companies since they do not know about the benefits and tax incentives and even less about the tax regimes to which they are subject as taxpayers; therefore, aquaculture companies are in the informality category in a high percentage.

Over the course of many years, the Mekong Delta region has experienced relatively low and inconsistent levels of business attraction and low quality of the enterprise environment compared to other regions in Vietnam. To delve into whether this discrepancy reflects a negative perception of the business environment in the area, this study employs a dataset comprising the aggregate Provincial Competitiveness Index (PCI) and nine of its component scores, alongside other significant control variables, to analyze business attraction trends spanning from 2010 to 2020. It based on the modeling analysis for the panel data that includes Pool-OLS, FEM and REM models. The findings indicate that PCI serves as an important indicator influencing the quality of the business environment and plays a role in determining the location preferences of businesses. It is observed that public investment has exerted an impact on enticing new businesses to the region throughout this period. These research outcomes carry several policy implications, suggesting that public policy interventions can positively shape the business environment, consequently bolstering the appeal of business investments in the region.

This article explores the role of informatization in the integration and development of the cultural and tourism industry, and proposes corresponding analysis and strategies. Firstly, informatization improves the quality and efficiency of cultural and tourism products and services by enhancing the design and production process and personalizing and customizing the services. Secondly, informatization expands the boundaries of cultural and tourism products and markets by utilizing the internet and mobile applications to extend the spatial and temporal boundaries, and leveraging data analysis and intelligent technologies to broaden the scope and scale. Lastly, informatization enhances the management and operational level of the cultural and tourism industry, improving efficiency and decision-making through the use of advanced technologies such as big data and artificial intelligence.

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.

The impact of the coronavirus outbreak was seen all over the world in all sectors. In the case of Bangladesh, it was not free of threats. Like all other sectors, the economic, social, and educational sectors were under serious threat. This study examined the effects of COVID-19 on the lives of Bangladeshi students, with a particular focus on their idealized portrayals of plans, daily routines, social interactions, and mental well-being. This research also investigated the influence of COVID-19 on education, social life, and other sectors and how the government was dealing with this unprecedented situation and these elevation challenges. A mixed-methods approach was adopted for this research. A total of 90 students from Bangladeshi higher educational institutions were taken as a sample size using the random sampling method. SPSS software was used for data analysis. The study’s quantitative results showed that Bangladeshi students faced challenges related to teaching, learning, and social distancing during the COVID-19 pandemic. Additionally, the study revealed that the pandemic adversely affected higher education in Bangladesh. Rebels and concerned citizens from all parts of the state must work together to move forward. COVID-19 has had a natural effect on education and almost every other field. The need for social distancing has pushed the education system to change because of social distancing. Many educational institutions worldwide have shuttered their campuses and relocated their teaching and learning online.

The purpose of this research is to estimate the differences in sales levels between businesses owned by individuals who self-identify as Indigenous (IE) and those who do not (NIE), as well as between males (ME) and females (WE), and how this intersection may affect their sales levels. To accomplish this, an Analysis of Variance (ANOVA) is used to compare the means between the groups analyzed, and Tukey’s Honestly Significant Differences (HSD) is used to determine the magnitude and direction of these differences. The results of the study show that indigenous-owned businesses have sales that are 26% lower than the general average, while women-owned businesses have sales that are 70.6% lower in the same comparison. In addition, businesses run by indigenous women have sales that are 93.5% lower on average. These findings suggest that the challenges faced by entrepreneurs reflect the structural inequalities observed in other areas of society and highlight the need for public and private policies focused on reducing these gaps.