금융역량 구성요소에 근거한 소비자유형화와 영향요인 분석

Abstract

This study examined the correlation between financial knowledge, financial attitude, and financial behavior competency, which are elements of financial competencies, and performed K-means cluster analysis using these as reference variables to categorize consumers. It also examined the differences in sociodemographic characteristics by consumer type and examined the influence of sociodemographic characteristics on the likelihood of belonging to each consumer type through multinomial logistic analysis. Using the ‘2022 Korean Consumer Empowerment Index’ surveyed by the Korea Consumer Agency targeting 4,000 adults nationwide, correlation analysis, cluster analysis, crosstab analysis, analysis of variance, and multinomial logistic analysis were conducted using SPSS. The main results are as follows. First, the correlations between financial knowledge, attitude and behavior competency, which are elements of financial competencies, all show a positive relationship, but unlike previous studies that show that the relationship between attitude and behavior is higher than the relationship between knowledge and behavior, the strength of the relationships between knowledge-attitude, attitude-behavior, and knowledge-behavior are similar. Second, consumers were categorized into four groups based on financial knowledge, attitude, and behavior competencies. Consumers were categorized into the ‘high-competency group (33.9%)’ with high knowledge, attitude, and behavior scores; the ‘knowledge-deficient-high- practice-high attitude group (28.3%)’ with high financial attitudes and behavior scores but relatively low knowledge scores; the ‘behavior-deficient group (20%)’ with neither high knowledge nor high attitude scores but the lowest behavior scores; and the ‘low-competency group (17.9%)’ with low financial knowledge, attitude, and behavior scores. Third, the sociodemographic characteristics of the four types of consumer groups, such as gender, residential area, marital status, education level, occupation, number of household members, and average monthly household income, showed significantly different distributions. Fourth, as a result of multinomial logistic analysis examining whether sociodemographic variables significantly affect the possibility of belonging to the ‘knowledge-deficient-high- practice-high attitude group,’ ‘behavior-deficient group,’ and ‘low-competency group’ based on the ‘high-competency group,’ it was found that, except for marital status, gender, age, residential area, education level, occupation, number of household members, and average monthly household income had significant effects.