There is a growing residential type to be one-person householes, but alternative and consideration for them is short. Especially, one-person households's crime prevention is not considered. So, In this study, one-person households resident's inside and surroundings of residential's fear of crime and a part of weakness for crime were investigated by types of houses and sex. For the result, One-room resident's fear of crime is the highest at inside, surroundings, fear of crime compare to other type of residents and more than 2 households and the apartment's resident has less fear of crime at inside and surroundings than other types residents. Also, female has more fear of crime than male at inside, but outside's is resemblance between them.
The objectives of this study were to classify the types of elderly households and to compare the characteristics of their dietary lifestyle. Panel data surveyed by Korea Rural Economic Institute (KREI) for Food Purchase Attitudes over three years (2019 - 2021) were utilized for the analysis. Through a factor analysis, five common factors were extracted out of 19 basic variables related to dietary style, which indicate two kinds of consumer competency index (safe diet, traditional diet) and three kinds of purchase frequency (healthy food, meat & fish, fresh seafood). Applying the cluster analysis method, by using socioeconomic variables along the five common factors, elderly households aged 60 or older were grouped into four types. As a result, Type 1 elderly households accounted for 50.8%, Type 2 for 16.2%, Type 3 for 27.8%, and Type 4 for 5.2% out of all 870 elderly households. Type 1 is characterized as a low-income vulnerable class with a poor diet, Type 2 as a middle-income class with a healthy food-oriented diet, whereas Type 3 was classified as a middle-income class with a meat-oriented diet, and Type 4 as a high-income class with diverse dietary culture. It is necessary to expand the agri-food voucher pilot project to the entire country and also increase the monthly subsidy for the Type 1 elderly households. Implementing community kitchen projects for elderly single-person households, promoting senior internships by providing incentives to companies that employ retirees, the provision of education by local governments on a safe and balanced diet for Types 2 and 3, and the promotion of an elderly-friendly social environment are also recommended.
This study aimed to quantify the impact of crossbreeding at farm level, in mixed farm systems in Gujarat. Households with crossbred cattle did not differ from households without crossbreds in terms of farm resources, crop gross margins and off-farm income. The use of crossbred animals did increase livestock gross margins by 64% and household income by 22%. The three agro-ecological zones included in this study differed considerably according to farm system and household income. However, in all three zones, households with crossbreds had higher livestock gross margins than households without crossbreds. There was no real difference in work load and labour division between households with and without crossbreds. There was also no difference in the use of bullocks for draught purposes between the two types of households. In particular buffaloes are being replaced by crossbred cattle. There was a large variation in farm income, largely because of land area. The milk offake per average cow and the number of buffaloes also related positively to farm income in both types of households. Crossbreeding has proved technically and financially viable in different Gujarat mixed farming systems. It can be concluded that crossbreeding is an important development option for landless farmers.
The purpose of this study was to examine low-income households' financial problems and the demand for financial counseling. For these purposes, a survey of 500 low-income households was conducted by an on-line survey company. The results were as follows. First, four types of low-income households classified by income and job criteria were: the not-working poorest (16.2%), the working poor (27.0%), the not-working low-income (13.8%), and the working low-income (43.4%). Also, seven areas of financial problems were found through factor analysis. They included difficulty of survival, insufficient funds for special expenditures, defaults on financial obligation, decrease of income, increase of debts, emotional anguish, and difficulty in meeting living expenditures. 61.6% of respondents requested financial counseling, and 44.5% of them preferred internet counseling to counseling by phone or in-person, while 49.5% desired access to public counseling organizations. The five types of financial counseling content for low-income households that were found through factor analysis were financial planning, credit management, asset management/investment, public support, and use of credit cards. The low-income householders demanded financial planning counseling and pubic support counseling more than the other types of financial counseling. Logistic regression analysis revealed that the demand for financial counseling participation was significantly influenced by age and income. The demand for financial counseling content was age, income, and types of financial problems. Therefore, general financial counseling programs for low-income households should be expanded. Furthermore, those counseling programs can be useful if they not only include credit management but also financial planning, economic support information and savings.
The purposes of this study are to identify the factors affecting asset and debt choice behavior of rural households as well as to examine the differences in asset and debt choice behavior between rural and urban households. The data are taken from Korean Household Panel Study conducted in 1996 by Daewoo Economic Research Institute. Among 2,833, a final sample of 2,625 -537 rural and 2,088 urban sample- is used in this study. The results show that, the asset and debt choice behavior of rural households is totally different from that of urban households. The ratio of rural households holding all types of financial assets and sales credit is less than that of urban households while the ratio of holding real asset and loan is greater in rural than urban households. The most influential variable on the ownership of asset and debt is the age of household head. And there exist interrelationships between ownership of different assets and debts.
Because of rapid aging, housing stability of elderly household is becoming an important social problem. The population of the elderly people was 11.3% and that of the elderly household was 23.2%, about 407 million, in 2010. Yet, social policies for elderly people are focusing on the household who takes care of the elderly people, not on the elderly headed households. These policies fail to reflect the reality. Housing satisfaction of the elderly household is different based on the tenure type and the satisfaction can be further affected by the types of elderly household within the same tenure group. Thus, strengthening the policies for the elderly headed households as well as differentiating the policies based on the types of household is required in order to meet the needs of the elderly households. For the elderly household living in a rent house in a city, a housing voucher is needed and for the low income elders who own their houses, housing renovation is required. Public housing affects only the residential satisfaction of single elderly households, not for all elderly households probably because public housing does not meet the demand of the elderly households appropriately. Since the elderly households wanting to move is noticeably small, a policy that provides proper facilities within the elders' neighborhood is most necessary. Also, in order to lessen the burden of housing expenses of the elders with low income, a public housing policy, in which 2-3 people living together in one public housing, needs to be examined.
This study examined the effects of eating alone, meal type, and dietary lifestyles on healthy eating capability of one-person households. We analyzed the mediation effects of weekly frequencies of each meal type taken by one-person households between eating habits such as eating alone and dietary lifestyles of one-person households and healthy eating capability. We also analyzed data from the 2019 Food Consumption Behavior Survey using a sample of 688 one-person households. Factor analysis, latent profile analysis, structural equation model analysis was conducted; direct and indirect effects of independent variables were tested using bootstrap method. The major results were as follows. Frequency of eating alone was about 10 times a week on average; one-person households had home-made meals about 12 times a week, for restaurant meals, 4 times, for delivered/take-out food, 0.39 times, and for other types, 0.44 times. Weekly frequencies of eating alone and meal types taken by one-person households were significantly different among the different socio-demographic groups. Dietary lifestyle was classified into four classes: traditional, health ignorant, food lifestyle ignorant, and balanced. Eating alone and dietary lifestyle had a significant effect on weekly frequency of each meal type. Frequencies of eating alone, balanced dietary lifestyle, and taking home-made meals had a positive direct effect on healthy eating capability, and frequency of taking delivered or take-out food and food consumption ignorant lifestyle had a negative direct effect. Eating alone, balanced and traditional dietary lifestyles had a positive indirect effect through the meal type; however, watching Mug-bang had a negative indirect effect.
The purpose of the study was to examine the characteristics and economic status of deficit households. The data for this study were from The Household Income and Expenditure Survey in 2000, 2005, and 2010 conducted by the National Statistics Office (NSO). Deficit households were defined by those who had expenditures higher than their income. Among total households, the proportion of deficit households was 26.84% in 2000, 28.14% in 2005, and 27.15% in 2010. The average propensity to consume was 132.1 in 2005, which was higher than those in 2000 and 2010. Deficit households were classified into five types using cluster analysis: 1)overall-overconsumption group(33.07%), 2)basic needs group(26.33%), 3)transportation expenditure-dominated group(6.73%), 4)education expenditure-dominated group(27.63%), 5)health care expenditure-dominated group(6.24%). The overall-overconsumption group was the largest group of total households and the portion of this group among total households decreased by 4.97%p from 2005 to 2010. However, the education expenditure-dominated group increased by approximately 7.6%p over the period. It was also found that households in 2000 and 2010 were more likely to be in all five groups than households in 2005. Other major determinants of households with deficit were gender, age, number of family members, education level, dual income, home ownership, vehicle ownership, and income class.
In South Korea, social, the number of single-person households has rapidly increased because of financial factors. Since single-person households have characteristics differentiated from general households, many enterprises pay attention to them that appear as important consumers. This study conducted a survey with consumers in their 20s to 50s in single-person households, nationwide who had an experience of purchasing HMR. The results of this study can be summarized as follows: First, of the benefits pursued in dietary life, the pursuit of nutrition a negative (-) impact on RTH type and did not have any impacts on the RTE and RTC types. The pursuit of taste had a positive (+) impact only on the RTE type while it did not have any impact on the RTH and RTC types. The pursuit of convenience had positive (+) impacts on all RTH, RTE and RTC types, while the pursuit of price sought did not have any impact on all types. Second, of the preferences by each HMR type, preferences for the RTH and RTC types had positive (+) impacts on purchase intention while preference for the RTE type did not have any impact on purchase intention. Third, of the benefits pursued in dietary life, the pursuits of taste and convenience had positive (+) impacts on purchase intention while the pursuits of nutrition and price did not have any significant impacts on purchase intention. In addition, of the benefits pursued in dietary life, the pursuit of convenience had a significant impact on purchase intention mediated by preference by each HMR type. As a result, taste of HMR and the aspects of convenience act as factors inducing purchases, and products in the various forms of taste and convenience in order to appeal consumers who pursue taste and convenience.
The purpose of the study was to investigate the characteristics and economic status of deficit households compared to surplus households. Data from The Household Income and Expenditure Survey 2005 by NSO and 50, 207 salary/wage earners' households were used for the analysis. The statistical methods used were GLM, logit, and cluster analyses. The analysis results showed that 25.3 percent of the households were deficit households. Approximately half of the lowest 20% income group were deficit households. Income deficit households earned 1, 273 thousand less than that of surplus households, whereas consumption of deficit households was 1, 006 thousand more than that of surplus households. The average propensity of consumption of deficit households was 142.1. According to the logit analysis, factors contributing to the probability of belonging to a deficit household included income level, household size, age and educational level, occupation, homeownership, car ownership, and wife's employment status. Deficit households were classified into 5 types: 1) health care expenditure-dominated group, 2) housing expenditure-dominated group, 3) education expenditure-dominated group, 4) money transfer-dominated group, and 5) overall-overconsumption group. The overall-overconsumption group was the largest group of all at 58.5%. It was found that for all five groups, the changes in household size, income group, home ownership, and occupation of the individual were variables that influenced the probability of belonging to a certain group.
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