• Land and Housing Review
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• v.15 no.2
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• pp.107-124
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• 2024

Based on Muan-gun, Jeollanam-do, this study explores how to mitigate the disappearance of rual areas. The study surveyed 95 young farmers in Muan-gun to assess their farming practices and the challenges they face. We further employ factor analysis and cluster analysis classify young farmers in Muan-gun, facilitating the identification of tailored policies or initiatives aimed at fostering and supporting young farmers. The results are summarized as follows. First, Muan County does not have any ordinances or original projects specifically designed to support young farmers. Second, the succession rate of farmland among young farmers in Muan County is 41.1%, which is comparable to the national rate of 43.7%. This indicates that approximately 40% of young farmers in Korea have inherited farmland, a critical foundation for agricultural activities. Third, despite accumulating farming experience, young farmers have not seen any improvement in local living conditions, and rather their difficulties have intensified. Fourth, this study conducted a factor analysis using 21 variables, resulting in the selection of seven common factors for cluster analysis. Consequently, young farmers in Muan County were categorized into three groups. The multinomial logit analysis revealed that the typology of young farmers is influenced by indicators such as cultivated area, farming experience, demand for smart farms, farm income, and farming type (rice cultivation or other). Therefore, to attract young farmers and prevent the decline of rural areas, policy efforts should focus on minimizing entry barriers to farming infrastructure, such as access to farmland, and improving local settlement conditions.

• 한국노년학
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• v.36 no.4
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• pp.1037-1058
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• 2016

This study aims to investigate the female caregivers'experiences of aggression by nursing home residents, and to identify the policy strategies for violence prevention referred by the female caregivers. A total of 121 female caregivers with more than 6 months of working experiences had participated in this study. Of these, 56.2% had experienced verbal aggression, 51.2% physical aggression, and 27.3% sexual aggression, which reveals that client violence toward caregivers in nursing homes was at an alarming level. Although, physical and verbal violences were mostly caused unintentionally, about a half of the sexual aggression were caused deliberately. Aggression occurred the most when caregivers were providing the following services: changing the diapers or clothes, giving a bath, and serving meals. It was found that 'hitting' was the most common form of physical aggression and it was 'swearing' and 'touching or physical contacting' in the case of verbal and sexual aggression, respectively. Though there was a difference depending on the type of aggression, the most frequent reactions against client violence were to start a conversation or calm down the nursing home residents, and to leave the scene or ignore the incident. This means that the caregivers are coping very passively through resolving the aggressions by themselves, or overlooking the situation. The most frequently recommended strategy to prevent resident aggression was to provide educational programs on violence prevention to nursing home residents and caregivers(42.7%). Compared to the previous studies, this study indicates some differentiated strategies to prevent violence in nursing homes, which include hiring male caregivers, assuring directors to pay closer attention toward caregivers, using refined language between caregivers and residents, and keeping caregivers to wear appropriate clothes. Based on the study results, some policy recommendations on the prevention of client violence in nursing homes were suggested.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.3
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• pp.13-29
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• 2021

The purpose of this study was to analyze the spatial distribution and location factors of startups by generation (young and middle-aged) in Seoul. To this end, a research model was established that included factors of industry, population, and startup institutions by generation in 424 administrative districts using the Seoul Business Enterprise Survey(2018), which includes data on the age group of entrepreneurs. As an analysis method, descriptive statistics were conducted to confirm the frequency, average and standard deviation of startups by generation and major variables in the administrative districts of Seoul, and spatial distribution and characteristics of startups by generation were analyzed through global and local spatial autocorrelation analysis. In particular, the spatial distribution of startups in Seoul was confirmed in-depth by categorizing and analyzing startups by major industries. Afterwards, an appropriate spatial regression analysis model was selected through the Lagrange test, and based on this, the location factors affecting startups by generation were analyzed. The main results derived from the research results are as follows. First, there was a significant difference in the spatial distribution of young and middle-aged startups. The young people started to startups in the belt-shaped area that connects Seocho·Gangnam-Yongsan-Mapo-Gangseo, while middle-aged people were relatively active in the southeastern region represented by Seocho, Gangnam, Songpa, and Gangdong. Second, startups by generation in Seoul showed various spatial distributions according to the type of business. In the knowledge high-tech industries(ICT, professional services) in common, Seocho, Gangnam, Mapo, Guro, and Geumcheon were the centers, and the manufacturing industry was focused on existing clusters. On the other hand, in the case of the life service industry, young people were active in startups near universities and cultural centers, while middle-aged people were concentrated on new towns. Third, there was a difference in factors that influenced the startup location of each generation in Seoul. For young people, high-tech industries, universities, cultural capital, and densely populated areas were significant factors for startup, and for middle-aged people, professional service areas, low average age, and the level of concentration of start-up support institutions had a significant influence on startup. Also, these location factors had different influences for each industry. The implications suggested through the study are as follows. First, it is necessary to support systematic startups considering the characteristics of each region, industry, and generation in Seoul. As there are significant differences in startup regions and industries by generation, it is necessary to strengthen a customized startup support system that takes into account these regional and industrial characteristics. Second, in terms of research methods, a follow-up study is needed that comprehensively considers culture and finance at the large districts(Gu) level through data accumulation.