• The Journal of Society for e-Business Studies
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• v.18 no.4
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• pp.215-240
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• 2013

This research has reviewed the major composition concepts and the positive research results in the selected studies which were theoretically based on IDT (Innovation Diffusion Theory), IRM (Model of Innovation Resistance), TAM(Technology Acceptance Model), and IAPA(Information Asset Protection Activity) in order to improve the theoretical explanation of major characterized factors influencing on the introduction of MST (Mobile Security Technology). The characterized factors for the adaptation of MST and 17 hypotheses on the MST study models in order to test the effects on the intention to use are empirically verified by utilizing the analysis method of structure equation model. As a result of a study, First, the most influential characterized factors of IRM are shown as compatibility, complexity, relative advantage, information asset protection in order. Second, the characterized factors affecting intention to use are shown as relative advantage, compatibility, innovation resistance, performance expectancy. The results of this study are relevantly significant to establish the theoretical foundation of the study on the adaptation of MST and The verification of the characterized factors provide strategic implication for the introduction of MST and policy direction which alleviates informational gap between new MST and previous Security Technology to diffusion agency.

• Journal of Information Technology Services
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• v.14 no.1
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• pp.263-276
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• 2015

As a social being, people can cooperate and control one another through the power of reputation, which is a critical opinion of someone given by others. Nevertheless, there have been obstacles in clarifying the identity of traditional types of reputation, for they are mostly words of mouth passed among members of a society. However, due to dramatic technological advancement and widespread use of the Internet and social media, now we can clearly see and analyze written reputations, which used to be passed only from mouth to mouth. Against this background, this study examines whether a negativity bias-a notion that an event of a more negative nature has a greater effect on one's psychological state than a positive event-applies to spread of reputation online, and examines related factors and effects. To this end, reputation-related online comments left by social media users during the election period of Korea's 6th provincial election on 4 June 2014 were analyzed. For the analysis, a Bass diffusion model was used, which is based on the innovation diffusion theory. The analysis results confirmed that, at online forum, negative reputations spread more quickly and more widely than positive ones, had a greater impact, and mass media such as online news outlets had a significant influence on spread of reputation online.

• 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.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.2
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• pp.97-116
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• 2004

Recently, e portion of on-line stock brokerage has been rapidly increased to be more than 50%, on the basis of contracted money. The usage of wCTS(Web Based Cyber Trading Systems) has now got into the steady state over the initial diffusion stage, which means wCTS has got more-than-half customer base in on-line service. Therefore, brokerage service providers have their competitive strategic focus on customer retention through the enhancement of customer loyalty. This study provides framework and survey results on explanation of wCTS user's loyalty, what and how factors affect wCTS user's loyalty. We adopt the results of early studies on information technology acceptance and diffusion such as TAM(Technology Acceptance Model) and IDT(Innovation Diffusion Theory). We also referred loyalty theory of marketing area and studios on CTS usage. We categorized explanation factors as three groups characteristics of users, characteristics of system, social environment. And we assumed that these three factors could affect the loyalty through two parameters : customer satisfaction and trust to the system. This study firstly shows that the ease of use and usefulness, the major factors of TAM. can also be applied to the loyalty of wCTS with resulting that the usefulness is more important than the ease of use In wCTS. Secondly, it shows that the innovative and risk-sensitive user has the lower degree of loyalty. Thirdly, it shows that the satisfaction and trust impact the loyalty simultaneously, the trust particularly impacts more strongly than the loyalty, due to the characteristics of monetary transaction in wCTS. This study provides meaningful results to the other on-line EC service fields as a first empirical research regarding the loyalty to wCTS which is a typical on-line EC service.

• Journal of Korean Society of Rural Planning
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• v.26 no.3
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• pp.115-126
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• 2020

This study designed an extended technology acceptance model incorporating and combining TPB, TAM, UTAUT, and IDT, which are known to be useful in explaining technology acceptance intention, to analyze antecedents affecting smart farm acceptance intention from the perspective of policy handlers. In the model of this study, nine independent variables were set, including subjective norm, perceived behavioral control, attitude, perceived usefulness, performance expectation, effort expectation, social impact, promotion condition, and fitness. The effect of these variables on farm acceptance intention was analyzed. The study found that four factors, including perceived behavioral control, perceived usefulness, social impact, and fitness, had positive effects on the acceptance intention of smart farms. Of these, perceived usefulness had the highest impact. In conclusion, all the TPB, TAM, UTAUT, and IDT applied to the research hypothesis to explain the smart farm acceptance intention included on or more variables with significant effects. In other words, these theories were evaluated as useful to explain the acceptance intention of smart farms.

• Journal of Navigation and Port Research
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• v.46 no.2
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• pp.134-144
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• 2022

The development and operation of autonomous ships are spotlighted as a next-generation technology that will provide newbenefits for the maritime business during the fourth industrial revolution. To expand the adoption of autonomous ships, the much more interest of the nation and the industries will have to be changed to actual adoption in shipping companies. For this, it is judged that research to identify the factors impacting the adoption intention of autonomous ships should be preceded. However, most studies on autonomous ships have focused on developing the technology, revising the law, establishing policies, and managing human resources, with few studies on influencing factors in the adoption of autonomous ships. A model, to identify the factors that impact the intention to the adoption of autonomous ships, based on the theory of diffusion of innovation and the TOE framework was developed. The suggested model was verified through empirical analysis targeting the shipping companies and the marine industries in Korea. As the result of this study, it was found that top management support, financial slack, and competitive intensity significantly impacted the intention to adopt autonomous ships. Additionally, it was revealed that the overall awareness of autonomous ships among Korean shipping companies is poor.

• Journal of Distribution Science
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• v.21 no.8
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• pp.83-96
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• 2023

Purpose: This study examined the relationship between the factors (Credibility, Usability) and user Innovativeness of the ChatGPT on TRA (Theory of Reasoned Action; Subjective Norm, Attitude) and Switching Intention. TRA and Innovation Diffusion Theory (IDT) were used. Research design, data and methodology: From April 26 to 27, 2023, an online panel survey agency was commissioned to conduct a survey of GhatGPT users in their 20s and 40s in Korea, and a total of 210 people were used for the final analysis. Verification of the research model was performed using SPSS and AMOS. Results: First, ChatGPT factors (Credibility, Usability) were found to have positive effects on TRA (Subjective Norm, Attitude). Second, ChatGPT user Innovativeness was found to have a positive effect on TRA (Subjective Norm, Attitude). Third, ChatGPT users' TRA (Subjective Norm, Attitude) were found to have positive effects on Switching Intention. Conclusions: These results mean that the superior Usability and Credibility of ChatGPT and the Innovativeness of users have a significant effect on the Switching Intention from existing Portal Service (Naver, Google, Daum, etc.) to ChatGPT. Generative AI such as ChatGPT should strive to develop various services such as improving the convenience of functions so that innovative users can use them easily and conveniently in order to provide services that meet expectations.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.817-828
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• 2021

This article aims to examine the intention to use Islamic microfinance by women entrepreneurs in Malaysia. Microfinance plays a significant role in developing the modern economy in the world by alleviating poverty, creating employment, and empowering women in society. The framework was built on Innovation and Diffusion Theory and Planned Behaviour Theory. The present study has adopted a quantitative research method, which focused on cross-sectional research design to address this problem. Primary data was collected and processed by using a 5-point Likert scale. For this research, a total of 178 questionnaires were distributed among women owners of micro-enterprises in Malaysia by using area collection sampling. To analyze the data, the SmartPLS 3 software package was used. This study developed seven hypotheses, all which have been supported both directly, indirectly, and mediated. This result will be beneficial in assisting policymakers, academics and future researchers who must consider the supported variables. Thus, the study contributes to developing a unique framework to assist women-owned micro-enterprise to success. It will be beneficial for practitioners to enhance women micro-enterprise success rate as well. Indeed, all of the grounded methods have implications both in theory and their main application for the business in SMEs.

• The Journal of Korean Association of Computer Education
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• v.8 no.5
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• pp.63-72
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• 2005

The purpose of this study is finding factors affecting the decision of Web-based learning system (Edunet) use and searching for ways to diffuse Edunet use. Based on the diffusion of innovations theory and the results of the previous studies about web-based instruction, seven predictors influencing the decision of Edunet use were extracted. Seven variables as the followings; (1) perceived attributes of innovation (Relative Advantage, Compatibility, Complexity) (2) Innovativeness (3) Self-efficacy (4) Subjective Norm (5) Support. The participants were 315, 5-6th grade elementary school students, and the questionnaire was 20-item with 7-point Likert scales. To analyze the collected data and test the hypothesis, binary logistic regression was employed. The result indicated that the fitness of regression model including seven decision factors was proved. In addition, two factors, subjective norm and support, were identified as the important decision factors of Edunet use.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.140-141
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• 2017

Big data analysis, in the large amount of data stored as the data warehouse which it refers the process of discovering meaningful new correlations, patterns, trends and creating new values. Thus, Big data analysis is an effective analysis of various big data that exist all over the world such as social big data, machine to machine (M2M) sensor data, and corporate customer relationship management data. In the big data era, it has become more important to effectively analyze not only structured data that is well organized in the database, but also unstructured big data such as the internet, social network services, and explosively generated web documents, e-mails, and social data in mobile environments. By the way, a meta analysis refers to a statistical literature synthesis method from the quantitative results of many known empirical studies. We reviewed a total of 750 samples among 50 studies published on the topic related as IDT between 2000 and 2017 in Korea.