• Journal of Digital Convergence
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• v.12 no.1
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• pp.287-294
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• 2014

Cloud computing is a new method of computing and managing organizational information technology resources strategically. From the user perspective, it involves computing environment for accessing applications remotely, storing data, and supporting cooperative works. For the cloud computing to be effective in an organization, it should be accepted by individual users. In this paper we propose a research model, extending and modifying UTAUT model. We also test the validity of the model using the questionnaire from a sample of cloud computing services users.

• The Journal of Economics, Marketing and Management
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• v.11 no.6
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• pp.43-55
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• 2023

Purpose: The purpose of this study was to identify the relationship between smart factory utilization and continued use intention between UTAUT, dynamic capabilities of smart factory construction companies and present the company's strategic direction. Research design, data, and methodology: In this study, a structured research model was derived to confirm the relationship between UTAUT, dynamic capabilities, smart factory utilization and continued use intention and the difference according to Technology perception. For analysis a total of 223 valid questionnaires from e-commerce users were used. Confirmatory factor analysis, correlation analysis, and structural equations were conducted to verify. Results: Both UTAUT, dynamic capabilities had a significant effect on smart factory utilization as well as continued use intention. It was found that the relationship between UTAUT, dynamic capabilities, smart factory utilization, and continued use intention. differed depending on the technology perception. Conclusions: Organizational members utilize the smart factory in anticipation of effects such as work performance and various improvements. Smart factory data will be used continuously when it is useful for business processes and operations. It is necessary to establish strategies and provide training to improve the technical level and capabilities of organizational members. Through this, a strategy is needed that can be continuously used by utilizing the information obtained through smart factory to improve work efficiency, productivity and efficiency increase is needed

• The Journal of Information Systems
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• v.24 no.2
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• pp.23-52
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• 2015

Purpose This study aims to understand the role of digital knowledge in accepting the green technology. This study combined digital option theory with the second version of the Unified Theory of Acceptance and Use of Technology (UTAUT2). Contrary to other studies in which the UTAUT2 is used to explain IT adoption behavior, we look at the relationship between IT and the UTAUT2 from a new angle, incorporating an important aspect of IT, that is, digitized knowledge richness, as a determinant of the UTAUT2. Design/methodology/approach Grounded in the UTAUT2, a content analysis was conducted to investigate novel constructs dedicated to explaining green technology adoption. In this study, an amended version of the UTAUT2 specific to green technology is offered that better explains the green technology adoption behavior of consumers. Using the items identified by content analysis, we developed a questionnaire with 36 survey items. We measured all the items on a seven-point Likert-type scale. We randomly selected 402 survey respondents from a set of panel data. After a pilot study, we analyzed the main survey data by using PLS 2.0M3 and SPSS 20.0, and employed structural equation modeling to test the hypotheses. Findings The results suggest that the UTAUT2 was found to be extendable to technologies other than conventional IT. Social influence is more significant than conventional utilitarian and hedonic-based constructs such as those utilized in the UTAUT and UTAUT2 in explaining adoption behavior in the context of green technologies. The hypothesized connection between digitized knowledge richness and adoption intention was supported by the results of studies on the role of IT in formation of attitudes toward eco-friendly production. The results also indicate that digital knowledge can also encourage people to try green technology when they learn that their peers are already using the technology successfully.

• Journal of Distribution Science
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• v.18 no.3
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• pp.53-65
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• 2020

Purpose: This study tests the suitability of a new technology acceptance model for a mobile payment system by checking how statistically significant the change is from the UTAUT (Unified Theory of Acceptance and Use of Technology) and UTAUT 2 models. Research, Data, and Methodology: We surveyed 250 students at Incheon University who are using the mobile payment system. The analysis was conducted on 243 valid questionnaires. The survey was conducted for one month in October 2018. The collected data were analyzed using SPSS and hierarchical regression analysis was applied. Results: Using hierarchical regression analysis, this study confirmed whether the newly added hedonic motivation, switching cost, and perceived risk variables in the UTAUT2 model are good explanatory variables. Mobile payment usage experience was found to have a moderating effect on mobile payment reuse intention. According to the analysis, the UTAUT2 model brought about more influential change than the variables of the UTAUT model. Conclusions: This study found that consumers' psychological factors added in the UTAUT2 model greatly influenced the reuse intention for mobile payment. As an implication of this study, mobile payment providers need to develop strategies that could meet hedonic motivation, switching cost and perceived risk for their customers.

• Journal of Korean Society for Quality Management
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• v.50 no.3
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• pp.491-502
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• 2022

Purpose: The purpose of this study is to find factors affecting the acceptance intention of autonomous mobility service by applying the unified technology acceptance theory(UTAUT). Methods: The measurement items for each component of this study were modified to meet the purpose of the study by referring to previous studies related to mobility based on UTAUT, which has secured validity and reliability in many studies. The collected data through the online survey were analyzed using hierarchical regression analysis. Results: It was found that performance expectation, effort expectation, social influence, and facilitation conditions for autonomous mobility service had a positive effect on acceptance intention. Also, in this relationship, it was confirmed that driving experience moderated the relationship between performance expectation and acceptance intention, and between effort expectation and acceptance intention. Conclusion: Understanding the public's acceptance of autonomous mobility services, and suggesting strategic implications for the direction of service development to companies that are pushing to enter the autonomous mobility service market.

• Journal of Information Technology Applications and Management
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• v.21 no.4_spc
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• pp.463-483
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• 2014

Data are dramatically increased and big data technology is spotlighted innovative technology among the latest information technologies. Organizations are interested in adoption of big data system to analyze various data format and to identify new business opportunity. The purpose of this study is to build a unified model for a system adoption through analysis of impact that affects behavioral intention and usage behavior of using big data. This study in addition to Technology-Organization-Environment (TOE), that is used the introduction of organizational studies, and Diffusion of Innovation (DOI) have implemented an extended unified model including the unified theory of acceptance and use of technology (UTAUT) that is usually used in personal level adoption study. The hypothesis was set up after implementing research model, and then got 411 effective survey data to target the member of organizations. As a result, all models (UTAUT, TOE, DOI) are affect to behavioral intention and usage behavior. It is verified that the suggested unified model was appropriate.

• The Journal of Bigdata
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• v.2 no.2
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• pp.47-56
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• 2017

The UTAUT was presented as a comprehensive of eight existing theories to improve the limit of Technology Acceptance Model (TAM), and it has been also utilizing in various fields related to acceptance and diffusion of new technology. In this study, we analyzed factors utilized in UTAUT through meta-analysis, and confirms the consistency of the model. We presented the principal factors and the additional factors. Moreover, we presented differences and suggestions through comparative analysis with previous researches. The meta-analysis showed that satisfaction, hedonic motivation, attitude, perceived enjoyment showed a important factors as additional factors. Based on this result, we presented an extended UTAUT model. In the case of Korea studies, it was found that increasing the degree of behavior intention is the most important factor leading to use behavior. The results of this research will be able to support researchers who research the acceptance and diffusion of new technologies, and companies trying to launch new products.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.129-143
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• 2020

The purpose of this study is to explain users' wearable healthcare device adoption using performance expectancy, effort expectancy, facilitating condition, hedonic motivation and price value of UTAUT2, and to identify the causal relationship between intention to use wearable healthcare device and innovativeness. The research model proposed in this study is based on UTAUT2(Extended Unified Theory of Acceptance and Use of Technology). In specific, performance expectancy, effort expectancy, facilitating condition, hedonic motivation and price value of UTAUT2 and innovativeness are adopted in our research model. To validate the research model, we carry out the analysis of the survey data using Smart PLS 3.0 to test the hypotheses. According to the empirical analysis results, this study confirms that Innovativeness have significant effects on the performance expectancy, effort expectancy, Facilitating condition, Hedonic motivation, and price Value of wearable healthcare devices. It also finds that the performance expectancy, effort expectancy, Facilitating condition, hedonic motivation, and price value affects the intention to use wearable healthcare devices.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.4
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• pp.54-63
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• 2018

Airlines are promoting self-service based technology by introducing mobile check-in, Kiosk and self-back drop systems, which will help customer satisfaction and efficiency. This study is about the usage intension to use Technology-based Airline Self-Service, the purpose of this study is to examine the key variables affecting Unified Theory of Acceptance (UTAUT2) in using Technology-based Airline Self-Service. According to the results of the ANOVA, there was a significant difference among the groups according to the experience of the self-service device. And analysis results using Structural Equation Model(SEM) was suggested that the performance expectation and hedonic motive of UTAUT2 model were found to have significant influence on initial trust. Also, initial trust affects the intention to use. There are some moderating effects on the structural equation by groups according to the experience of the self-service device. This research has significance in that it can help establish a marketing strategy of airlines to expand the self-service based on the airline technology.

• The Journal of Information Systems
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• v.28 no.3
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• pp.159-202
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• 2019

Purpose The purpose of this study is to explain users' wearable healthcare device adoption using performance expectancy, effort expectancy, the hedonic motivation and price value of UTAUT2, and to identify the causal relationship between intention to use wearable healthcare device and innovation resistance formed by perceived risks. Design/methodology/approach The research model proposed in this study is based on UTAUT2(Extended Unified Theory of Acceptance and Use of Technology) and MIR(Model of Innovation Resistance). In specific, performance expectancy, effort expectancy, hedonic motivation and price value of UTAUT2 and innovation resistance formed by perceived risks of MIR are adopted in our research model. To validate the research model, we carry out the analysis of the survey data using Smart PLS 3.0 to test the hypotheses. Findings According to the empirical analysis results, this study confirms that the performance expectancy, effort expectancy, hedonic motivation, and price value have significant effects on the intention to use wearable healthcare devices. It also finds that perceived risk affects innovation resistance and in turn, innovation resistance affects the intention to use wearable healthcare devices.