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.

In the dynamic contemporary business landscape, the convergence of technology, finance, and management plays a pivotal role in organizational success. This research explores the multifaceted realm of strategic integration, emphasizing the intricate balance between these domains. The background sets the stage, elucidating the historical evolution and growing relevance of this integration. Various research methodologies, including case studies, surveys, interviews, and data analysis, are used to investigate practical aspects. The study delves into the role of technology, emphasizing digital transformation, innovation, and IT infrastructure. It dissects financial management, focusing on decision-making, risk management, and capital allocation. Additionally, management and leadership are discussed, with an emphasis on change management, strategic leadership, and skill development. Challenges, such as cultural disparities and regulatory complexities, are scrutinized, alongside opportunities like improved decision-making and enhanced productivity. Real-world case studies illustrate success stories and lessons learned. The paper concludes with findings, implications for businesses and management, and practical recommendations for navigating this convergence. This research contributes valuable insights into performance and competitiveness, facilitating a better understanding of key performance metrics and positioning strategies in the digital age.

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.

The study explores improving opportunities of forecasting accuracy from the traditional method through advanced forecasting techniques. This enables companies to optimize inventory management, production planning, and reducing the travelling time thorough vehicle route optimization. The article introduced a holistic framework by deploying advanced demand forecasting techniques i.e., AutoRegressive Integrated Moving Average (ARIMA) and Recurrent Neural Network-Long Short-Term Memory (RNN-LSTM) models, and the Vehicle Routing Problem with Time Windows (VRPTW) approach. The actual milk demand data came from the company and two forecasting models, ARIMA and RNN-LSTM, have been deployed using Python Jupyter notebook and compared them in terms of various precision measures. VRPTW established not only the optimal routes for a fleet of six vehicles but also tactical scheduling which contributes to a streamlined and agile raw milk collection process, ensuring a harmonious and resource-efficient operation. The proposed approach succeeded on dropping about 16% of total travel time and capable of making predictions with approximately 2% increased accuracy than before.

Most countries have adopted a more liberal policy to socialize public relations under the influence of neoliberalism and lobbying by economic elites to strengthen the role of market mechanisms and citizens’ entrepreneurial activity. The nature, scale, sequence, and strategy of economic and social reforms in each country have their specifics. Today multi-vector and large-scale changes are taking place in social and labor policy, and they do not always have an internal logic. The study assesses prospects for the development of the labor market in the context of global transformations. Within the framework of this study, the collected information was processed gradually. Data processing was modified during the study phase. At the first stage, data processing results were used to determine total and non-farm self-employment for two groups of countries with developing economies and estimate the scale of vulnerable employment. At the second stage, indicators were identified that characterize various categories of economically active population that belong to the precariat. At the third stage, the authors analyzed data on non-standard forms of employment. The authors assumed that these forms have a right to exist and will be implemented more often. There is an imbalance between standard and non-standard forms of employment. Further research should consider the transformation of labor from material and intangible dominants to creativity.

This study investigates the significance of data analytics in digital marketing for sustainable business growth. Data analytics has become an indispensable instrument in the world of digital marketing, offering organisations the means to achieve sustainable growth while minimising their environmental impact. We gathered data from 273 marketing and business consultants, chosen for their expertise in digital channels and data analytics, using a survey research design. The questionnaire, which was validated through expert review and pilot testing, assessed the relationship between data analytics utilization and its impact on competitive advantage and business optimization. We conducted statistical analyses, including descriptive and inferential statistics, using SPSS version 25.0. Findings reveal a significant correlation between data analytics adoption in digital marketing and sustainable business competitive advantage, as well as a notable impact on business optimization. Recommendations emphasise the strategic importance of customer segmentation and predictive analytics in leveraging data analytics for targeted marketing campaigns and proactive adjustments to market trends. This study underscores the indispensability of data analytics in the evolving digital marketing landscape, offering actionable insights for businesses seeking sustainable growth and competitive advantage.