• Journal of Service Research and Studies
• /
• v.13 no.3
• /
• pp.147-159
• /
• 2023

This study is a study to develop a model for measurement and processing of experience data, which is emerging as a core value in quality management of medical services. In the theoretical background, a literature study was conducted on the importance of experience in medical service, measurement and processing of experience data, and realization of patient-centeredness. Based on these literature and theoretical background research results, operational definitions were performed for the following four research variables, and statistical tests were conducted. Hypothesis 1 is the effect of measuring experience data from the perspective of three factors on persona modeling, Hypothesis 2 is the effect of persona modeling on service blueprint visualization, Hypothesis 3 is the effect of service blueprint visualization on realization of patient-centeredness, and Hypothesis 4 is persona modeling This is the effect that modeling has on the realization of patient-centeredness. After data-based testing of factor analysis, reliability analysis, and correlation analysis, all four hypotheses were adopted as a result of verification using regression analysis. In conclusion, in an era where it is difficult to recognize the value of having only good medical staff and medical equipment in hospitals, it was possible to grasp the meaning that what kind of medical service experience is continuously obtained is more important to patients than the effectiveness of medical staff and medical equipment. In the era of the service economy, the core of hospital service competitiveness is providing attractive experiences, which is the real strength of hospitals, so the measurement and processing of experience data, which is the subject of this study, will have an important meaning in realizing patient-centeredness and realizing smart hospitals.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• 2006.11a
• /
• pp.548-553
• /
• 2006

Activity-based productivity data can be used as an significant reference in many areas of project management such as performance evaluation and project planning. However, the existence of various factors influencing construction productivity makes it difficult to collect and analyze the productivity data. In the most of the domestic construction sites, there is no systematic method to collect and analyze the productivity data along with information on influencing factors; it is common to heavily rely on experience and intuition of field managers when dealing with construction productivity data. Therefore it is necessary to develop a management system for collecting and utilizing the productivity data as well as the factors influencing construction productivity. The main objective of this research is to define the construction productivity and its influencing factors at the activity level. In addition, methodologies on how to analyze the productivity data and to estimate productivity of future projects are proposed.

• Journal of Internet of Things and Convergence
• /
• v.8 no.2
• /
• pp.49-54
• /
• 2022

Immersive contents is content that provides a realistic experience by maximizing the user's five senses, and includes virtual reality, augmented reality, and mixed reality. In order to provide a sense of reality to users in immersive content, it is necessary to provide realistic visual images, hearing, and touch. However, due to the rapid change in the environment for developing immersive content, experts in training human resources are having difficulties in designing the curriculum. In this study, we propose a series of educational courses that use drones to acquire and process real-world measurement data and apply the derived data to VR, AR, and MR to help experts in training immersive content develop talent. The design of training process composes through demand survey and analysis of companies, students, and local communities. This study can be a useful resource for education experts who want to train immersive contents manpower.

• Journal of Intelligence and Information Systems
• /
• v.26 no.3
• /
• pp.1-36
• /
• 2020

This study is to reveal the acceptance factors of the Market Sentiment Index (MSI) created by reflecting the investor sentiment extracted by processing unstructured big data. The research model was established by exploring exogenous variables based on the rational behavior theory and applying the Technology Acceptance Model (TAM). The acceptance of MSI provided to investors in the stock market was found to be influenced by the exogenous variables presented in this study. The results of causal analysis are as follows. First, self-efficacy, investment opportunities, Innovativeness, and perceived cost significantly affect perceived ease of use. Second, Diversity of services and perceived benefits have a statistically significant impact on perceived usefulness. Third, Perceived ease of use and perceived usefulness have a statistically significant effect on attitude to use. Fourth, Attitude to use statistically significantly influences the intention to use, and the investment opportunities as an independent variable affects the intention to use. Fifth, the intention to use statistically significantly affects the final dependent variable, the intention to use continuously. The mediating effect between the independent and dependent variables of the research model is as follows. First, The indirect effect on the causal route from diversity of services to continuous use intention was 0.1491, which was statistically significant at the significance level of 1%. Second, The indirect effect on the causal route from perceived benefit to continuous use intention was 0.1281, which was statistically significant at the significance level of 1%. The results of the multi-group analysis are as follows. First, for groups with and without stock investment experience, multi-group analysis was not possible because the measurement uniformity between the two groups was not secured. Second, the analysis result of the difference in the effect of independent variables of male and female groups on the intention to use continuously, where measurement uniformity was secured between the two groups, In the causal route from usage attitude to usage intention, women are higher than men. And in the causal route from use intention to continuous use intention, males were very high and showed statistically significant difference at significance level 5%.

• Korea journal of population studies
• /
• v.29 no.1
• /
• pp.185-207
• /
• 2006

Predominant explanations of the persistence of sex segregation ill occupations link job choices to profoundly gendered responses to childbearing and other family demands, arguing that women are more likely to seek jobs which are in some sense compatible with motherhood, either because they are family friendly (flexible, low intensity work) or because they are easy to exit and re-enter. In this paper, I examine the effect of occupational sex segregation on job exits into the labor market among women, with a special attention to the role of childbearing and child rearing. I use data from detailed employment histories gathered from the National Longitudinal Survey of Youth (NLSY) in continuous time event history models. My results indicate that women in female dominated jobs are less likely to exit their jobs than women in other types of occupations. Further this relationship is not shaped by motherhood. While mothers or pregnant women are more likely to leave work, mothers in female-dominated occupations are slightly less likely to leave employment than mothers in other occupations. These results are not consistent with the ideas that women's choice of female-dominated occupations expresses a gendered identity and women strategically seek jobs which accommodate maternal roles. Taken together, my findings do not provide support to the idea that women choose female-dominated occupations because they are easier to integrate with motherhood (except for the pregnancy period).