درخت حوزه‌های تخصصی

Microfinance institutions in India provide a set of financial services to the economically weaker sections. Recently, a large number of microfinance institutions have emerged in India and they have favorable impact for poverty reduction. The impact of these institutions on entrepreneurship and society, needs to be explored in greater depth. The objective of this study is to apply machine learning techniques to explore this impact. The research uses a MIX dataset for three successive years, namely 2017, 2018, and 2019. This dataset comprises eight variables centered on gross loan portfolio. Principal Component Analysis (PCM) has been applied on the sample dataset for dimensionality reduction, resulting in two main components and each component consist of fraction from eight variables. Then, the sample dataset has been labelled with the help of clustering using K-means clustering technique. Further, classification models based on K-Nearest Neighbors (KNN) algorithm and Support Vector Machine (SVM) are applied to predict the appropriate category of entrepreneurship. The experiment result shows that the machine learning techniques have been found effective and useful tools for estimating the impact of microfinance on entrepreneurship in India.

Purpose: The spread of consumption in this day and age has gone so far that today it is considered an indicator of lifestyle and even some  find modern life without consumption meaningless and unthinkable. In this regard, since the consumption of smuggled cosmetics in West Azerbaijan province has an increasing trend, so in this study, the communicative and social determinants and factors affecting the consumption of smuggled cosmetics in West Azerbaijan province are investigated.Method: The research method is an applied type as regards purpose and has been carried out using a survey method.  The statistical population includes citizens over 15 in West Azerbaijan province, 674 of whom have been selected by multi-stage cluster sampling. Data was collected using a questionnaire and research variables are above 0.7, which indicates the acceptable reliability of the variables. Statistical data analysis was done using SPSS and Lisrel software.Findings: The findings showed that the consumption of smuggled cosmetics and toiletry products is more than average among the respondents and the use of domestic media is less than average and the use of foreign and virtual media is above average. The results of explanatory analyses in the quantitative phase of the research showed  the variables of gender (in favor of women), socio-economic status (in a positive direction), rate of using internal media (in a negative direction), rate of using external media (in a positive direction), The use of virtual media (in a positive direction), health literacy (in a negative direction) and tendency towards differentiation (in a positive direction) have a significant impact on the consumption of smuggled cosmetics and toiletries. It is explained that the impact of foreign and virtual media is greater than other variables.Conclusion: As a result of lack of content management and inaccuracy in advertising in the virtual sector and social media, the possibility of emergence and escalation of social issues and all kinds of deviant trends related to consumerism in the field of cosmetics and toiletry products increases. Also, domestic mass media can be effective in reducing the consumption of cosmetics by not broadcasting commercial advertisements at intervals.