• Korean journal of communication and information
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• v.68
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• pp.7-33
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• 2014

Using data from an online survey in Korea, this study examines factors affecting college students' intention to use wearable device based on an extended Unified Theory of Acceptance and Use Technology (UTAUT) (UTAUT2 Model). The results of the regression analysis suggest that performance expectancy, social influence, and facilitating conditions from original UTAUT are statistically significant variables to explain college students' intention to use wearable device. Also, the results of the data analysis reveal that added factors from UTAUT2 like hedonic motivation and price value are influential factors to explain intention to use wearable device. In addition, this study suggests that future studies need to test the UTAUT2 model in the context of new information and communication technologies.

• 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.

• 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.2
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• pp.108-115
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• 2018

This study was undertaken to explore the determinants affecting behavioral intention to adopt airport self-service. Based on the theoretical model incorporating the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Technology Acceptance Model (TAM), in this study, a revised and extended model was proposed in order to better explain Airport Self-service adoption. Moreover, the aim was to determine the mediating effect of hedonic motivation on Airport Self-service adoption. The proposed model was empirically tested using survey data provided by 323 respondents and was analyzed using a multiple regression analysis.

• Journal of Fashion Business
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• v.19 no.2
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• pp.69-84
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• 2015

The objective of this study is to investigate the intention to adopt smart wear, based on extended UTAUT model. We examined the effects of performance expectancy (PE), effort expectancy (EE), hedonic motivation (HE), social influence (SI), facilitating conditions (FC), and price value (PV) on the intended adoption of smart watch and smart shoes, respectively. In addition, moderating effects of gender, age, and innovation resistance were examined. An online survey was conducted, comprised of 2030 consumers who were aware of smart watch or smart shoes. In total, 393 responses were analyzed. About 50.4% were male, and 44.8% were in their 20's. An exploratory factor analysis generated five factors - PE & HM, EE, SI, FC, and PV- which were employed as independent variables in the multiple regression models. PE & HM, PV, and SI influenced on the intention to use both smart devices. FC showed the significant effect only on the intention to adopt the smart watch. In terms of gender differences, SI and PV were the important predictors of the intention to adopt the smart watch in the female group only. With respect to age difference, SI was very effective in explaining the intention of individuals in their 30's to adopt smart wear. Among the low innovation resistance group, SI was significant predictor, while PE & HE and PV were significant among the high resistance group. The findings provide useful information about the possibility of the adoption of smart wear, and new insight into market segmentation.

• 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 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 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.

• Knowledge Management Research
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• v.16 no.4
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• pp.191-213
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• 2015

With the advancement of virtual reality technology, virtual reality contents and devices are being competitively released. This research deals with an early stage adoption model of a motion-sensing input device which enhances the user experience of these virtual reality contents and devices. In contrast to the previous research on the adoption or resistance of innovative products, this work compares and analyzes the antecedents in MIR(Model of Innovation Resistance) of resistance-perspective as well as those in UTAUT2(Extended Unified Theory of Acceptance and Use of Technology) and IDT(Innovation Diffusion Theory) of adoption-perspective, and suggests a resistance-incorporated adoption model from a new viewpoint. The analysis of questionnaire data indicates the following results: Performance expectancy, effort expectancy, price value, hedonic motivation in UTAUT2 and visibility in IDT have a significant negative influence on innovation resistance. Compatibility in IDT and MIR exerts a positive influence on perceived value. Social influence and hedonic motivation in UTAUT2 positively relates to perceived value. Higher innovation resistance results in lower perceived value, with innovation resistance and perceived value negatively and positively affecting intention to use, respectively.

• Fashion & Textile Research Journal
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• v.24 no.5
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• pp.577-592
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• 2022

This study aims to confirm which factors related to technology acceptance affect generation MZ's use of luxury fashion platforms. For this purpose, Internet self-efficacy and technology readiness were added as new exogenous and moderating variables using extended UTAUT. Then, performance expectancy, effort expectancy, social influence, and facilitating condition as a factor of UTAUT were set as mediating factors. Response data were collected through questionnaires for generation MZ with experience in using luxury fashion platforms, and a factor analysis, reliability analysis, correlation analysis, and path analysis were conducted using the SPSS and AMOS statistical programs. According to the results, the Internet self-efficacy of generation MZ significantly affected on performance expectancy, effort expectancy, social influence, and facilitating conditions on the luxury fashion platform. Moreover, performance expectancy and social influence had a significant effect on the use intention of luxury fashion platforms, but effort expectancy and facilitating condition did not have a significant effect on use intention and use behavior. Additionally, as the moderating effect of technology readiness affects only the relationship between social influence and behavioral intention, it was confirmed that social influence is an important variable with the characteristics of MZ consumers. Therefore, it is deemed necessary to recognize the importance of social influence when trying to use new technologies targeting generation MZ in the fashion industry.