• Korean System Dynamics Review
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• v.13 no.2
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• pp.73-91
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• 2012

This study aims to comprehensively understand the dynamics between the factors related to service quality, satisfaction and reuse intention. The contents of the study are as follows. First, it draws the limitations of the existing studies by reviewing the literature related to the relationships between service quality, satisfaction and reuse intention. Second, it highlights the characteristics of System Dynamics as a means of overcoming their shortcomings as well as examining the dynamic mechanism of the relevant factors. Third, it explores the feedback loops of the relevant key variables and the feedback structure of the system. Lastly, it concludes with the suggestions and implications of the key research findings. This study is expected to emphasize the importance of the feedback mechanism operating around the service quality, satisfaction, and reuse intention. Further, the causal loop diagram developed can be a basic material for the diverse levels of governments as well as service providers to refer to for improving the service quality of Community Social Service Investment Program.

• Korean Journal of Social Welfare
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• v.64 no.4
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• pp.137-161
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• 2012

The importance of voucher service evaluation is increasing with the expansion of voucher, but the previous studies on performance evaluation could not reflect the characteristics of voucher. But there is no study on the factors affecting voucher performance. Thus, this study focuses on the empirical analysis of voucher program performance and analysed the factors affecting voucher satisfaction. Data used in this study is collected form 70 social service agencies that deliver voucher service and 1445 service users in Community-Development voucher service in Community Service Investment Program. The methods applied in this study are Hierarchial Linear Model(HLM) using service user variables(level 1) and service agency variables(level 2). These variables are extracted from the previous studies on performance of social welfare service and voucher service. The findings show that user's satisfaction is influenced by level 1 variables such as sex, need and also influenced by level 2 variables of service type and area* organization type. On these analysis, this study gives policy implication.

• Journal of Convergence for Information Technology
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• v.8 no.2
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• pp.163-169
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• 2018

The purpose of this study is to analyze educational needs and perception of job performance in the community service investment program service providers. Data were collected from 619 service providers and was analyzed by t-test. In the case of the director, there was a significant difference in 10 professional qualification areas, 2 business management areas, 4 customer management areas, and 4 service development and marketing areas. In the case of the practitioners, there was a significant difference in 3 professional qualification areas, 2 business management areas, 2 customer management areas, and 5 service development and marketing areas. In the case of the therapist, there was a significant difference in all 35 areas. These findings offer theoretical background and practical implications for the education direction of community service investment program service providers.

• Korean Journal of Social Welfare Studies
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• v.42 no.1
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• pp.151-177
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• 2011

With the expansion of Voucher program, academic and practical concerns of performance evaluation of voucher service has been more emphasized. Accordingly, client satisfaction survey are expanding these days, but the study of client satisfaction as a performance indicator aimed at service client has not been yet conducted systematically. The purpose of this study is to develop Satisfaction Index, targeting at client of community-development voucher program in Community Service Investment Project conducted by the Ministry of Health and Welfare. Data were collected from 1800 client of community-development voucher program. This study summarized theoretically many kinds of satisfaction measurement and composed the Satisfaction Index reflecting characteristics of Voucher. By the item analysis and reliability analysis, the element satisfaction was identified as homogeneous items. General satisfaction were obtained using element satisfaction and overall satisfaction, it was found to be valid through the evaluation of convergent and discriminant validity as a tool for satisfaction. This study suggest using the '1step weighted approach' than '2step weighted approach' having weakness of complex overlapping manner.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.107-129
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• 2022

It is important to preempt new technology because the technology competition is getting much tougher. Stakeholders conduct exploration activities continuously for new technology preoccupancy at the right time. Gartner's Hype Cycle has significant implications for stakeholders. The Hype Cycle is a expectation graph for new technologies which is combining the technology life cycle (S-curve) with the Hype Level. Stakeholders such as R&D investor, CTO(Chef of Technology Officer) and technical personnel are very interested in Gartner's Hype Cycle for new technologies. Because high expectation for new technologies can bring opportunities to maintain investment by securing the legitimacy of R&D investment. However, contrary to the high interest of the industry, the preceding researches faced with limitations aspect of empirical method and source data(news, academic papers, search traffic, patent etc.). In this study, we focused on two research questions. The first research question was 'Is there a difference in the characteristics of the network structure at each stage of the hype cycle?'. To confirm the first research question, the structural characteristics of each stage were confirmed through the component cohesion size. The second research question is 'Is there a pattern of diffusion at each stage of the hype cycle?'. This research question was to be solved through centralization index and network density. The centralization index is a concept of variance, and a higher centralization index means that a small number of nodes are centered in the network. Concentration of a small number of nodes means a star network structure. In the network structure, the star network structure is a centralized structure and shows better diffusion performance than a decentralized network (circle structure). Because the nodes which are the center of information transfer can judge useful information and deliver it to other nodes the fastest. So we confirmed the out-degree centralization index and in-degree centralization index for each stage. For this purpose, we confirmed the structural features of the community and the expectation diffusion patterns using Social Network Serice(SNS) data in 'Gartner Hype Cycle for Artificial Intelligence, 2021'. Twitter data for 30 technologies (excluding four technologies) listed in 'Gartner Hype Cycle for Artificial Intelligence, 2021' were analyzed. Analysis was performed using R program (4.1.1 ver) and Cyram Netminer. From October 31, 2021 to November 9, 2021, 6,766 tweets were searched through the Twitter API, and converting the relationship user's tweet(Source) and user's retweets (Target). As a result, 4,124 edgelists were analyzed. As a reult of the study, we confirmed the structural features and diffusion patterns through analyze the component cohesion size and degree centralization and density. Through this study, we confirmed that the groups of each stage increased number of components as time passed and the density decreased. Also 'Innovation Trigger' which is a group interested in new technologies as a early adopter in the innovation diffusion theory had high out-degree centralization index and the others had higher in-degree centralization index than out-degree. It can be inferred that 'Innovation Trigger' group has the biggest influence, and the diffusion will gradually slow down from the subsequent groups. In this study, network analysis was conducted using social network service data unlike methods of the precedent researches. This is significant in that it provided an idea to expand the method of analysis when analyzing Gartner's hype cycle in the future. In addition, the fact that the innovation diffusion theory was applied to the Gartner's hype cycle's stage in artificial intelligence can be evaluated positively because the Gartner hype cycle has been repeatedly discussed as a theoretical weakness. Also it is expected that this study will provide a new perspective on decision-making on technology investment to stakeholdes.