This study examines the interaction between foreign direct investment (FDI), idiosyncratic risk, sectoral GDP, economic activity, and economic growth in ASEAN countries using structural equation modeling (SEM) performed using AMOS software. The analysis uses data from the ASEAN Statistics Database 2023 to distinguish the significant direct and indirect impacts of FDI on idiosyncratic risks, sectoral GDP, economic activity and aggregate economic growth can. ASEAN, which includes ten Southeast Asian countries, has experienced rapid economic growth and increasing integration in recent decades, making it an interesting area to study these relationships. The study covers a comprehensive period to capture trends and differences among ASEAN member states. Applying SEM with AMOS allows a detailed examination of complex relationships between important economic variables. The results show a clear link between FDI inflows, idiosyncratic risks, industry GDP performance, economic activity, and overall economic growth. More specifically, FDI inflows have a notable direct influence on idiosyncratic risks, which then impact GDP growth by sector, and the level of economic activity and ultimately contribute to economic growth trends. economy more broadly in ASEAN countries. These findings highlight the importance of understanding and effectively managing the dynamics between FDI and various economic indicators to promote sustainable economic development across ASEAN. This information can inform policymakers, investors, and stakeholders in developing targeted strategies and policies that maximize the benefits of FDI while minimizing related risks to promote strong and inclusive economic growth in the region. This study highlights the multifaceted relationships in the ASEAN economic context, emphasizing the need for strategic interventions and policy frameworks to exploit the potential of foreign investment directed at ASEAN, to the Sustainable Development Goals and long-term economic prosperity in the region.

The present study, developed under a quantitative approach, explanatory scope and causal correlational design, aims to determine the influence of invisible learning on the research competence of high school students in two private schools in the city of Lima, Peru, whose educational models seek to develop autonomous learning and research through discovery learning and experimentation. Two questionnaires were applied to 120 students of the VII cycle of basic education, one to measure the perception regarding invisible learning with 20 items and the other to measure investigative competencies with 21 items; both instruments underwent the corresponding validity and reliability tests before their application. Among the main findings, descriptive results were obtained at a medium level for both variables, the correlations found were significant and moderate, and as for influence, the coefficient of determination R² yielded a value of 0.13, suggesting that 13% of investigative competence is predicted by invisible learning. These results show that autonomy, the use of digital technologies, metacognition and other aspects that are part of invisible learning prepare students to solve problems of varying complexity, allowing them to face the challenges of contemporary knowledge in an innovative and effective manner.

Mobile banking has become very important in today’s life as technological advancements have led bank clients to use banking services. Clients’ attitudes toward mobile banking services are based on their expectations is the background of this research. So, the main objective is to observe the purposeful conduct in mind of clients to adopt mobile banking services. This study also examines the influence of six variables on financial services clients’ desire to utilize mobile banking services, including perceived benefits, perceived ease of use, trust, security, perceived privacy, and technology expertise. Consequently, the goal of this study is to find out the crucial and deciding factors that may influence clients’ willingness to use mobile banking features in Bangladesh as a developing country. The sample shaped for this research is 310 respondents from Bangladesh a developing country. For analytical purposes, SEM has been used to test hypotheses. The results show that in Bangladesh, factors like perceived value, security, and technological aptitude greatly determine whether a customer will utilize mobile banking. Financial institutions have proven to be successful in serving clients through mobile phones. Clients have made good use of mobile banking only to save money, cost, and labor. The research suggests that mobile banking operations must be timely and accurate, the transaction process must be short, interactivity, convenience of usage, and so on. The findings have important implications for bank regulatory authority, management, bankers, and executives who wish to increase mobile banking usage to secure their long-term profitability.

The article is devoted to formulation of theoretical principles and practical recommendations regarding organization and planning of the investigation of criminal offenses in the field of economic activity, which are committed with the participation (assistance) of law enforcement officers. The methodology for the article is chosen taking into account the purpose and tasks, object and subject matter of the study. The research results were obtained with the help of the following methods: dialectical; formal and logical; formal and legal; comparative and legal; historical and legal, complex analysis; analysis and synthesis; axiomatic; system and structural method. The obtained results of the study indicated that organization and planning of the investigation of criminal acts under consideration is a purposeful activity of the authorized bodies, which is carried out under the guidance of the investigator, detective of the pre-trial investigation body. These activities require systematic, comprehensive approach and must take into account a wide range of circumstances that can affect the process and results of the investigation: the nature of the criminal offense, access to the necessary financial, human and technical resources; the competence of the investigator, the detective; terms and deadlines for investigation and presenting materials to the court, establishing effective cooperation between competent authorities. The study highlights the peculiarities of the organization and planning of the investigation of criminal offenses in economic activities, when law enforcement officers are involved, and suggests directions for improving the effectiveness of their implementation.

Optimizing Storage Location Assignment (SLA) is essential for improving warehouse operations, reducing operational costs, travel distances and picking times. The effectiveness of the optimization process should be evaluated. This study introduces a novel, generalized objective function tailored to optimize SLA through integration with a Genetic Algorithm. The method incorporates key parameters such as item order frequency, storage grouping, and proximity of items frequently ordered together. Using simulation tools, this research models a picker-to-part system in a warehouse environment characterized by complex storage constraints, varying item demands and family-grouping criteria. The study explores four scenarios with distinct parameter weightings to analyze their impact on SLA. Contrary to other research that focuses on frequency-based assignment, this article presents a novel framework for designing SLA using key parameters. The study proves that it is advantageous to deviate from a frequency-based assignment, as considering other key parameters to determine the layout can lead to more favorable operations. The findings reveal that adjusting the parameter weightings enables effective SLA customization based on warehouse operational characteristics. Scenario-based analyses demonstrated significant reductions in travel distances during order picking tasks, particularly in scenarios prioritizing ordered-together proximity and group storage. Visual layouts and picking route evaluations highlighted the benefits of balancing frequency-based arrangements with grouping strategies. The study validates the utility of a tailored generalized objective function for SLA optimization. Scenario-based evaluations underscore the importance of fine-tuning SLA strategies to align with specific operational demands, paving the way for more efficient order picking and overall warehouse management.

The application of optimization algorithms is crucial for analyzing oil and gas company portfolio and supporting decision-making. The paper investigates the process of optimizing a portfolio of oil and gas projects under economic uncertainty. The literature review explores the advantages of applying various optimizers to models that consider the mean and semi-standard deviations of stochastic multi-year cash flows and revenues. The methods and results of three different optimization algorithms are discussed: ranking and cutting algorithms, linear (Simplex) and evolutionary (genetic) algorithms. Functions of several key performance indicators were used to test these algorithms. The results confirmed that multi-objective optimization algorithms that examine various key performance indicators are used for efficient optimization in oil and gas companies. This paper proposes a multi-criteria optimization model for investment portfolios of oil and gas projects. The model considers the specific features of these projects and is based on the Markowitz portfolio theory and methodological recommendations for project assessment. An example of its practical application to oil and gas projects is also provided.