• Journal of Korea Trade
• /
• v.26 no.7
• /
• pp.59-76
• /
• 2022

Purpose - As ahigher-order ability, improvisational capability is often employed to help a firm cope with unexpected or unanticipated issues. In light of the severe global business challenges and turbulent environmental changes, this study aimed to explore whether home-based network ties could shape the influence of improvisational capability on international entrepreneurship, alongside investigating the boundary conditions of competitive turbulence in their moderating effects. Design/methodology - The sample for the international entrepreneurship sector was obtained from the Industry and Information Technology Department of Jiangsu. In September 2021, the questionnaires were sent to the targeted ventures and required the top managers to complete the survey by email or telephone. The final research sample comprised 113 international new ventures. To test the hypotheses, moderated hierarchical regression analysis was conducted. Findings - Our empirical results suggested that (1) unlike some previous literature, a positive effect of improvisational capability on the performance of international new ventures was not found; (2) home country-based networks (both political ties and business ties) are contingent factors that may partially stimulate the value creation of improvisational capability; and (3) in a highly competitive environment, the moderating role of business ties at home may become much stronger, however, the contingent role of political ties at home was not found. Originality/value - This study mainly concentrates on the two important types of home country-based networks, political and business ties at home, that may help international new ventures access strategic resources necessary for supporting the performance implications of improvisational capability. Thus, it extends the existing improvisational theory to encompass international entrepreneurship.

• Women's Health Nursing
• /
• v.28 no.1
• /
• pp.56-64
• /
• 2022

Purpose: This study aimed to investigate the effects of health-promoting behaviors (HPB), marital intimacy, and parenting stress on the quality of life (QoL) of low-income women with young children in Korea, an underserved group. Methods: This cross-sectional survey employed a descriptive correlational design. Using convenience sampling, 123 low-income women with children younger than 6 years were recruited from 14 health and community centers in Jeonju, Korea, from June 2020 to May 2021. Participants completed a questionnaire on QoL, HPB, marital intimacy, and parenting stress. Data were analyzed using descriptive statistics, independent t-test, analysis of variance, Pearson correlation, and hierarchical regression analysis. Results: Participants, who were on average 37.41±3.65 years old and had 1 to 2 children (n=98, 79.7%), reported a mid-level (3.14 out of 1-5) of QoL. Marital intimacy (β=.38, p<.001) was the most influential factor on the QoL of low-income women with young children. In descending order, HPB (β=.35, p<.001) and non- employment status (β=-.21, p=.003) had a significant influence on QoL (F=15.64, p<.001), and the overall explanatory power was 49.0%. Conclusion: Considering the mid-level QoL of low-income women with young children, programs aimed at improving the QoL of low-income women need to promote marital intimacy and maintain HPB, while considering their employment status. Strategies that include couple counseling, health care to encourage healthy lifestyles, and reemployment education are needed.

• Journal of Digital Convergence
• /
• v.20 no.3
• /
• pp.497-505
• /
• 2022

This study aimed to investigate the effect of Grit and positive psychological capital on job engagement in general hospital nurses. Participants were 159 nurses working at General Hospital in Gangwondo Province and data were collected from April 9 to 21, 2020. Data were analyzed by t-test, one-way ANOVA, Pearson's correlation coefficient, and hierarchical multiple regression using SPSS version 24.0. Job engagement was correlated with perseverance efforts and positive psychological capital. The factors influencing job engagement were self-efficacy (β=.23, p=.029) and optimism (β=.28, p=.001) with 41.8% explanatory power (F=12.34, p<.001). Therefore, in order to improve job enthusiasm, further study is necessary to develop and apply the positive psychological capital improvement program and identify its effect.

• The Korean Journal of Franchise Management
• /
• v.7 no.1
• /
• pp.21-29
• /
• 2016

Purpose - The primary purpose of this study is to employ effective marketing methods using market segmentation of coffee shops by determining how motivations to visit coffee shops have different impacts on demographic profile of visitors and characteristics of coffee shop visits, so as to draw out a better understanding of customers of coffee market. Research design, data, and methodology - Data were collected using surveys of self-administered questionnaires toward coffee shop users in Daejeon, Korea. A number of samples used in data analysis were 253 excluding unusable responses. The data were analyzed through frequency, reliability, and factor analysis using SPSS 20.0. Factor analysis was conducted through the principal component analysis and varimax rotation method to derive factors of one or more eigen values. In addition, the cluster analysis, multivariate ANOVA, and cross-tab analysis were used for the market segmentation based on the types of motivation for coffee shop visits. The process of the cluster analysis is as follows. Four clusters were derived through hierarchical clustering, and k-means cluster analysis was then carried out using mean value of the four clusters as the initial seed value. Result - The factor analysis delineated four dimensions of motivation to visit coffee shops: ostentation motivation, hedonic motivation, esthetic motivation, utility motivation. The cluster analysis yielded four clusters: utility and esthetic seekers, hedonic seekers, utility seekers, ostentation seekers. In order to further specify the profile of four clusters, each cluster was cross tabulated with socio-demographics and characteristics of coffee shop visits. Four clusters are significantly different from each other by four types of motivations for coffee shop visits. Conclusions - This study has empirically examined the difference in demographic profile of visitors and characteristics of coffee shop visits by motivation to visit coffee shops. There are significant differences according to age, education background, marital status, occupation and monthly income. In addition, coffee shops use pattern characterization in frequency of visits to coffee shops, relationships with companion, purpose of visit, information sources, brand type, average expense per visit, important elements of selection attribute were significantly different depending on motivations for coffee shop visits.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.3D
• /
• pp.347-356
• /
• 2009

This paper is described clustering analysis of traffic characteristics-based highway classification in order to deviate from methodologies of existing highway functional classification. This research focuses on comparing the clustering techniques performance based on the total within-group errors and deriving the optimal number of cluster. This research analyzed statistical clustering method (Hierarchical Ward's minimum-variance method, Nonhierarchical K-means method) and Kohonen self-organizing maps clustering method for highway characteristic classification. The outcomes of cluster techniques compared for the number of samples and traffic characteristics from subsets derived by the optimal number of cluster. As a comprehensive result, the k-means method is superior result to other methods less than 12. For a cluster of more than 20, Kohonen self-organizing maps is the best result in the cluster method. The main contribution of this research is expected to use important the basic road attribution information that produced the highway characteristic classification.

• Korean Journal of Social Welfare Studies
• /
• v.41 no.4
• /
• pp.135-160
• /
• 2010

This study was designed to analyze, by using a hierarchical logistic regression analysis method, how difficulties in business start-ups and personal characteristics independently determine the utilization of micro-enterprise support services. The services were categorized into eight areas: capital, technical service, psychological service, item feasibility and business plan, site selection and interior service, marketing, finance and accounting, employment service. This study found that difficulties in business start-ups were a significant factor in six areas. Personal characteristics were a significant factor in four areas, when difficulties in start-ups were controlled. Among the personal characteristics, higher possibility of service utilization was anticipated in people with start-ups experience than people without experience, and in women than men. This results point out that service strategies should be targeted for people with difficulties in order to improve the accessibility of micro-enterprises support services. The results also indicate that the strategies should be considered for people with no start-ups experience, low academic ability, and female entrepreneurs who are vulnerable.

• Journal of Industrial Convergence
• /
• v.22 no.4
• /
• pp.65-73
• /
• 2024

The purpose of this study was to identify the effect of job resources of hospital workers on presenteeism and to verify the mediating effect of job embeddedness based on this. Participants included 301 hospital workers form hospitals located in B city. Date was collected form July 10 to August 10, 2023. The collected data were analyzed by frequency analysis, descriptive statistics, Pearson's correlation coefficient, Baron and Kenny's three-step hierarchical regression and Sovel's test method using the SPSS 26.0 program. In this study, it was found that there was a correlation between job resources, job embeddedness and presenteeism of hospital workers, job resources and job embeddedness influenced negatively on presenteeism, and it was confirmed that job embeddedness partially mediated in the relationship between job resources and presenteeism. Based on this, in order to reduce presenteeism of hospital workers. it was suggested to improve job integrity by providing sufficient job resources institutionally an administratively and providing continuous educational opportunities.

• Journal of Industrial Convergence
• /
• v.22 no.4
• /
• pp.49-55
• /
• 2024

This study is a descriptive research study to determine the mediating effect of anxiety in the relationship between patient care communication and patient satisfaction among hospitalized patients. Data was collected using self-administered questionnaires from October to December 2021. The collected data were analyzed using descriptive statistics, Pearson's correlation coefficient, and hierarchical multiple regression using the SPSS 24.0 program, and the effectiveness of the mediation effect was tested using the Sobel test. As a result of the study, there was a positive correlation between patient care communication and patient satisfaction, and a negative correlation between patient care communication and anxiety. And there was also a negative correlation between patient satisfaction and anxiety. In the relationship between patient care communication and patient satisfaction, anxiety had a partial mediating effect (z=2.93, p<.001), with an explanatory power of 38.4%. In order to improve patient satisfaction based on the results of this study, it is necessary to develop a program that can improve nurses' patient care communication capabilities and reduce patients' anxiety.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.1
• /
• pp.111-119
• /
• 2024

In this paper, we propose a big data platform that can collect information from various sources collected at ocean. Currently operating ocean-related big data platforms are focused on storing and sharing created data, and each data provider is responsible for data collection and preprocessing. There are high costs and inefficiencies in collecting and integrating data in a marine environment using communication networks that are poor compared to those on land, making it difficult to implement related infrastructure. In particular, in fields that require real-time data collection and analysis, such as weather information, radar and sensor data, a number of issues must be considered compared to land-based systems, such as data security, characteristics of organizations and ships, and data collection costs, in addition to communication network issues. First, this paper defines these problems and presents solutions. In order to design a big data platform that reflects this, we first propose a data source, hierarchical MEC, and data flow structure, and then present an overall platform structure that integrates them all.

• The Journal of the Acoustical Society of Korea
• /
• v.27 no.3
• /
• pp.111-118
• /
• 2008

In this paper, we propose a new automatic taxonomy generation algorithm for the audio genre classification. The proposed algorithm automatically generates hierarchical taxonomy based on the estimated classification accuracy at all possible nodes. The estimation of classification accuracy in the proposed algorithm is conducted by applying the training data to classifier using k-fold cross validation. Subsequent classification accuracy is then to be tested at every node which consists of two clusters by applying one-versus-one support vector machine. In order to assess the performance of the proposed algorithm, we extracted various features which represent characteristics such as timbre, rhythm, pitch and so on. Then, we investigated classification performance using the proposed algorithm and previous flat classifiers. The classification accuracy reaches to 89 percent with proposed scheme, which is 5 to 25 percent higher than the previous flat classification methods. Using low-dimensional feature vectors, in particular, it is 10 to 25 percent higher than previous algorithms for classification experiments.