The poverty becomes a serious problem because of the impact it causes. The factors that affect poverty are economic growth, low education, the limitation of natural resources, the limitation of employment opportunities, capital, and family burdens. All of these factors constitute a vicious circle in the problem of poverty. The problems studied are lag-1 investment, lag-2 investment, employment opportunities, and provincial minimum wages and their effects on the poverty rates in Riau Province, Indonesia. The fundamental problem faced by Riau Province today is the high level of poverty amidst government policies that have not met the expectations. The purpose of this study is to analyze government policies in order to reduce the poverty. The research method used was an explanatory study or hypothesis testing study that aims to explain and test hypotheses for the relationship among variables. The relationship described is a causal (cause-effect) relationship. The data were arranged in the form of time series during 1997-2018. The research model was formulated as a linear function based on the Nerlove's Partial Adjustment Model approach and was recursively analyzed using linear regression through the Ordinary Least Square (OLS) method. The findings of this research model are lag-1 investment, lag-2 investment, employment opportunities, and provincial minimum wages have a significant effect on the poverty rate in Riau Province.

The indicators of success in macro development can be measured from the economic growth, which is reflected in changes in the Gross Regional Domestic Product (GRDP). The factors which affect the economic growth are very complex. This study analyzes the economic growth and the factors that affect Sumatra island. The data used is panel data with descriptive analysis techniques and multiple linear regression. Based on the research results: Education, economic openness, road infrastructure, and investment have a positive and significant effect on economic growth and poverty and unemployment have a negative and significant effect on economic growth. Besides, the results of panel data explained that the openness of the economy to economic growth is very low, while the highest is education.

The aim of this research is to analyze the impact of coffee industry on economic growth of Vietnam. This research has used historic data for coffee production, consumption, exports, and coffee stock for Vietnam, thus this research has followed a quantitative design. The data in this research has been collected from the time period ranging from 1990 to 2018. There are several techniques that were applied in E-views such as descriptive statistics, bounds test, and autoregressive distributed lag model. The results of ARDL model indicate that in the short run coffee industry has an influence on the economic growth in Vietnam. It can be stated that for the short-run the null hypothesis is rejected stating that domestic consumption, exportable consumption, gross opening stock, and total coffee production have impacts over the gross domestic product (GDP) of Vietnam. The results of Bounds test show there is a significant impact of coffee industry on the economic growth of Vietnam in the long run as well.

One of the main goals of every individual or household is to achieve financial well-being. Previous research has shown that various factors influence financial well-being. This research aims to develop an integrated family financial welfare model by examining various factors that affect it. This study uses data of 1,158 households taken using an online survey. The data is analyzed using a structural equation model. The results show that financial experience, financial knowledge, financial status, and marital status directly affect financial well-being. Financial behavior significantly mediates the influence of financial behavior, financial knowledge, and locus of control on financial well-being. Furthermore, marital status strengthens the effect of financial knowledge on financial well-being, but it does not strengthen the effect of financial experience on financial well-being. This study suggests that the Government and financial authorities need to improve further the effectiveness of financial literacy and financial inclusion programs and campaign for a more frugal life among households to avoid financial difficulties.

The status process and the multiplicity occur in the economic environment in the Republic of Iraq within the organization of work for companies and change towards the best new types of special operations through accounting and administrative methods to reduce costs. The paper opted the decision on the use of outsourcing and defined comprehensive evaluation criteria for the effectiveness of outsourcing - the outsourcing factor (Fout), which takes into average values obtained for the estimates of relative parameters to be interpreted on the Harrington scale translated into a ten-point system. The authors rely data analyses of business processes based on a sample from one of the industrial companies operating in the Republic of Iraq, which is the State Company For Implementation (SCI), in the Republic of Iraq, in the demonstrated the need to transfer it to full outsourcing & partial outsourcing and actually execution. This has a positive impact on the company's main financial and economic indicators and increase their competitiveness in the market, which has been the focus of many research studies. The study itself brings a unique method in theory and practice, which can be used by other companies, to deduce the implications of business organization to decision makers who are seeking for the best types of new special operations, which contributes to raising its competitiveness in the market.

The aim of this research was to evaluate the impact of decentralization and electronic participatory budgeting on managerial performance. Additionally, the study sought to investigate the management accounting system's role in strengthening the effect of decentralization and electronic participatory budgeting on managerial performance. This quantitative research involved 30 regional units, using primary data collected through questionnaires of 108 fund management officials. The findings of this study demonstrated that decentralization and electronic participatory budgeting both have a positive and significant effect on managerial performance. Furthermore, the management accounting system was found to act as a moderator between decentralization and performance, but not between electronic participatory budgeting and performance.

Tuberculosis (TB) is still a major public health concern in many regions of the world, including Indonesia's West Java Provinces. Accurate TB risk factor prediction can enhance overall TB control efforts by directing focused therapies. In this study, utilizing a combination of Negative Binomial Mixed Models (NBMMs) and Feed-Forward Neural Networks (FFNNs), we offer a unique method for the predictive modeling of TB risk variables. A variety of sociodemographic, behavioral, and environmental factors that are known to be linked to TB are included in the dataset utilized in this investigation. To correct for overdispersion and include both fixed and random effects in the model, we first fitted an NBMM major problem in epidemiological investigations is modeling count data with overdispersion, and the NBMM component of the model offers a versatile and effective framework for doing so. Following that, we include an FFNN component in the model, which helps us to detect relevant predictive features and alter the model's weights accordingly. Backpropagation methods are used by the FFNN to adjust model parameters and enhance accuracy. The resulting Negative Binomial Mixed Model Neural Network (NBMMNN) model has a high accuracy value of up to 0.944. Our research suggests that the NBMMNN model outperforms conventional models that are frequently used to predict TB risk factors. By contrast to simpler models, the NBMMNN model can capture complicated and nonlinear interactions between predictors and outcomes. Additionally, the inclusion of random variables in the model enables us to take into account potential sources of variability in the data as well as unmeasured confounding. This work emphasizes the opportunity to enhance TB risk prediction and control efforts by integrating NBMMs with FFNNs. In West Java Provinces and other comparable contexts, the NBMMNN model might be a helpful tool for identifying and resolving TB risk factors, guiding targeted interventions, and enhancing overall TB control efforts.

This study investigates the effect of perceived risks, i.e., financial risk, product risk, and convenience risk, as well as the COVID-19 pandemic situation on online shopping behavior among Malaysians. This study uses convenience sampling techniques and comprises 185 respondents who have experience buying online. In addition, the study setting was non-contrived, and data was gathered using a closed-ended questionnaire through an online survey. Descriptive analysis was conducted using SPSS version 25.0 software and SmartPLS version 3.2.8 to test the proposed hypotheses. This study found that perceived risk factors such as financial, product, and convenience risk did not influence online shopping behavior. In contrast, the COVID-19 pandemic positively influences online shopping behavior among consumers. It showed a new development in the theory of online shopping behavior, where users continue to make purchases despite being aware that there may be various risks due to the spread of COVID-19. The role of the ministry, business owners, and consumer associations needs to be given attention to form a sustainable electronic commerce system and protect the rights of consumers. This research can help consumers understand their rights.

The development of technology and smart mobile devices such as phones and tablets has changed the behavior of tourists when booking tourism services. Based on the technology acceptance model, this study aims to explore the factors influencing the intention to use mobile applications for accommodation booking among GENZ in Vietnam. The analysis of 218 users revealed that four factors influence the behavior of using mobile applications for booking: performance expectancy, effort expectancy, social influence, and hedonic motivation. In addition to identifying the factors affecting usage intention, this study also proposes implications to assist developers and providers in improving their applications and developing suitable product strategies for the future.

In a confirmatory study, researchers are expected to employ the covariance-based structural equation modeling (CB-SEM). One of the key presumptions when utilizing CB-SEM is that the data is multivariate normal. Nevertheless, a perfect normal distribution is rarely observed in real-life data. To resolve this, the unweighted least square (ULS) is designed to specifically deal with non-normal data in SEM. However, ULS often yields improper solutions like negative, or boundary estimates of unique variances since it considers measurement errors in observed variables. The disturbance in SEM is reflected in unique variance, which is random error due to unreliability or measurement error and reliable variation in the item that indicates unknown latent causes. Consequently, this can generate bias in indicator loadings estimates. As an action to disentangle this issue, the present study proposes the implementation of regularization parameters by adding small positive values to the variance-covariance matrix. The ratio of bias to variance in a model can be improved to obtain the best estimation performance. Pro-Active Monte Carlo simulation was used to produce multivariate non-normal data with designated sample sizes and population characteristics. The data were analyzed using R Programming Environment by employing “psych”, “MASS”, “foreign”, “mvrnonnorm”, “purr”, and “semTools” packages with 1000 replications to produce multivariate non-normal data. Next, the “lavaan” package was used for SEM and regularized SEM analyses. The outcome of this study proves the capability of regularized ULS to improve parameter estimation.