• The Journal of the Korea Contents Association
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• v.14 no.9
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• pp.538-555
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• 2014

Systematic studies have been rarely conducted on the acceptance of big data technology despite the technology drawing much attention from academia, industry and general public. With big data technology still being in the infant stage in Korea, a study model was constructed in this paper by integrating the innovation diffusion theory and the task technology fit theory with this technology acceptance model (TAM) as the central framework to make big data technology more readily acceptable in the country, and the aim of making big data technology readily acceptable was expanded as the moderator variable of the TAM. The results of this study showed that "subjective norm" and "task technology fit" showed the most significant effect as the exogenous variables of the TAM. In addition, the "innovative characteristic of the organization" was the significant exogenous variable affecting the intention to accept big data technology to those "technology utilizers" that try to come up with new services or products that are technology-based; however, "subjective norm" was the rather significant factor affecting those simple "technology users". Finally, a significant difference was seen in the verification of mediation effect.

• Journal of the Korean Regional Science Association
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• v.36 no.1
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• pp.51-67
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• 2020

The purpose of this study is to estimate the housing area per capita for verifying if the public Big Data, of the building ledger and resident registration ledger, can be used as well as the National Census and Housing Survey. The Mankiw and Weil (MW) model was constructed by extracting samples of general detached houses and flat houses from the public big data, and compared with the result from traditional survey method. Then, the MW models of 25 municipalities in Seoul was established. As a result, it can be confirmed that it is possible to establish MW models comparable to regular surveys using public big data, and to establish a model for each basic localities which was difficult to use as a regular survey method. Public Big Data has the advantage of expanding the knowledge frontier, but there are some limitations because it uses data generated for other original purposes. Also, the difficult process of accessing personal information is a burden to carry out analysis. It is expected that continuing research should be needed on how public Big Data would be processed to complement or replace traditional statistical surveys.

• Review of KIISC
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• v.33 no.5
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• pp.39-46
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• 2023

4차 산업혁명과 더불어 빅데이터의 활용이 보편화되었고, 최근 생성형 AI를 기점으로 인류의 정보 활용은 매년 그 최대치를 갱신하고 있다. 이 과정에서 의도치 않은 개인정보 노출 및 프라이버시 침해 사례들이 발생하고 있다. 동형암호는 정보 활용과 보호가 동시에 필요한 이 시점에서 주목할만한 기술이다. 최근에는 국내·외 다양한 분야에서 동형암호 기술의 적용사례가 등장하고 있으며, 이는 동형암호 기술이 상용화 단계에 이르렀음을 보여 준다. 본 고에서는 동형암호 활용사례를 중심으로 동형암호 기술 동향을 살펴보고자 한다.

• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.35-45
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• 2021

The e-commerce industry using mobile or web is growing rapidly, and the emergence of various platform services is causing innovative changes in the e-commerce industry. This study aims to identify the attachment types of e-commerce users and to demonstrate the relationship between the PPerceived Usefulness, and Perceived Ease of Use by TAM. In order to empirically verify the research model of this study, a survey was conducted on ordinary people with experience using e-commerce and path analysis was conducted by using PLS to analyze its Internal consistency, Confirmatory factor analysis, Discriminant validity and Goodness-of-fit verification. As a result, a significant relationship between Perceived Stability, Perceived Usefulness, and Perceived Ease of Use was identified, could verify the association with the TAM and Acceptance Intention.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.127-129
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• 2015

A meta-analysis is a statistical integration method that delivers an opportunity to overview the entire result of integrating and analyzing many quantitative research results. This study will find meaningful independent variables for criterion variables that affect influencing on purchase intention in social network service, on the basis of the results of a meta-analysis. We reviewed a total of 29 studies related on purchase intention in social network service published in Korean journals between 2000 and 2015, where a cause and effect relationship is established between variables that are specified in the conceptual model of this study. Thus, we present the theoretical and practical implications of these results and discuss the differences between these results through a comparative analysis with previous studies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.2
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• pp.408-414
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• 2016

This study will find meaningful independent variables for criterion variables that affect influencing on purchase intention in social network service, on the basis of the results of a meta-analysis. We reviewed a total of 29 studies related purchase intention in social network service published in Korea journals between 2005 and 2015, where a cause and effect relationship is established between variables that are specified in the conceptual model of this study. The result of the meta-analysis might be summarized that the highest effect size (r = .455) is the path from the satisfaction to the purchase intention. The second biggest effect size (r = .398) was found in the path between the word of mouth to the purchase intention. Next, the effect size (r = .386) in the path from the trust to the purchase intention showed very lower. Finally, the result of the meta analysis can be concluded that lower effect size (r = .342) Further, the predictive variables of this study have power of explanation about 22%-12% or more. Based on these findings, several theoretical and practical implications were suggested and discussed.

• Management & Information Systems Review
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• v.39 no.3
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• pp.17-35
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• 2020

The purpose of this study is to develop business models for current situational scenarios reflecting customer needs emphasize the need for implementing a logistics cooperation system by analyzing big data to strengthen SCM competitiveness capacities. For healthcare SCM competitiveness needed for the logistics cooperation usage intent, they were divided into product quality, price leadership, hand-over speed, and process flexibility for examination. The wordcloud results that analyzed major considerations to realize work efficiency between medical institutes, words like unexpected situations, information sharing, delivery, real-time, delivery, convenience, etc. were mentioned frequently. It can be analyzed as expressing the need to construct a system that can immediately respond to emergency situations on the weekends. Furthermore, in addition to pursuing communication and convenience, the importance of real-time information sharing that can share to the efficiency of inventory management were evident. Accordingly, it is judged that it is necessary to aim for a business model that can enhance visibility of the logistics pipeline in real-time using big data analysis on site. By analyzing the effects of the adaptability of a supply chain network for healthcare SCM competitiveness, it was revealed that obtaining competitive capacities is possible through the implementation of logistics cooperation. Stronger partnerships such as logistics cooperation will lead to SCM competitive capacities. It will be necessary to strengthen SCM competitiveness by searching for a strategic approach among companies in a direction that can promote mutual partnerships among companies using the joint logistics system of medical institutes. In particular, it will be necessary to search for ways to utilize HCSM through big data analysis according to the construction of a logistics cooperation system.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.85-93
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• 2021

The government is pursuing plans to create new e-government services. In terms of improving business procedures, dBrain (finance), e-people (personnel), and Onnara (electronic payment and business management) have achieved considerable results, and are currently making efforts to improve existing administrative services using newly emerged ICT. Among them, this paper attempted to study whether self-learning-based intelligent administrative services are efficient in the work process of public officials promoting actual work and affect their continued use. Based on individual perceptions and attitudes toward advanced ICTs such as AI, big data, and blockchain, public officials' influences on administrative services were identified and verified using UTAUT variables. They believe that the establishment and introduction of innovative administrative services can be used more efficiently, and they have high expectations for the use and provision of services as ICT develops. In the future, a model will be also applied to citizens

• Information Systems Review
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• v.25 no.3
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• pp.199-220
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• 2023

Projects to deploy and diffuse smart factories in South Korea are aimed at enhancing national manufacturing competitiveness. However, a significant portion of deployed companies remain at the basic stage and struggle to utilize smart factories regularly. Existing studies have primarily focused on the technical aspects of smart factories, using data analytics and case studies, leading to a gap in empirical research on continuous use and upgrade intentions. This study identifies key factors influencing smart factory usage and user satisfaction, drawing on the Information Systems Success Model (ISSM) and previous research. It empirically examines the impact of these factors on continuous use intention, management performance, and advancement acceptance intention through smart factory usage and user satisfaction. A structural equation model is employed to validate the research hypotheses, using survey data from 287 small and medium-sized manufacturing enterprises (SMEs) that have adopted smart factories. Results demonstrate that system quality, information quality, service quality, and government support significantly affect smart factory usage, while service quality and government support influence user satisfaction. Furthermore, smart factory usage and user satisfaction have positive effects on management performance, continuous use intention, and subsequently advancement acceptance intention. This study provides novel insights by demonstrating the specific impact mechanisms of smart factory user satisfaction on the business and the intentions of manufacturing SMEs regarding continuous use and advancement acceptance, leveraging the ISSM.

• The Journal of Bigdata
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• v.5 no.2
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• pp.201-213
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• 2020

Despite empirical research that the response to human risk is significantly influenced affective factors, the role of affective factors has been unexplored in information privacy research. This study aims to explore the privacy behaviors of location-based service (LBS) users from an affective point of view. Specifically, the study explored the relationship between three types of privacy threats (collection, hacking, secondary use), two affects (worry, anger), and a coping behavior (continuous use intentions). The structured survey was conducted with 552 users. In order to analyze the effect of the combination of perception of particular privacy threats and particular affects on the intention of continuous use, association rules, one of the data mining techniques, was employed. As a result, there was a difference in the intention to use according to the combination of the perception of risk and affect responses, and the most significant influence on the intention is when the second use of personal information was combined with anger. This study has significant theoretical contribution in that it includes affective factors in the research of information privacy users, complementing the biases of existing cognition-oriented approaches and providing a comprehensive understanding of privacy response behavior.