• The Research Journal of the Costume Culture
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• v.31 no.4
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• pp.489-503
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• 2023

This study utilized the unified theory of acceptance and use of technology 2 (UTAUT2) to examine usage intentions associated with virtual fitting services. Six independent variables were examined: performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, and habit. The study collected responses from 445 participants who had utilized virtual fitting services. Regarding factors related to usage intentions associated with these services, performance expectancy and social influence were found to significantly influence the usage intentions associated with photo-based virtual fitting services. Furthermore, performance expectancy, social influence, and habit significantly influenced the usage intention of avatar-based virtual fitting services. This suggests that higher levels of performance expectancy and social influence positively impact the usage intentions associated with both types of virtual fitting services, while habit influences only avatar-based virtual fitting services. Moreover, the findings confirm that effort expectancy, facilitating conditions, and hedonic motivation from UTAUT2 do not significantly influence usage intentions associated with virtual fitting services. By analyzing factors influencing potential customers' virtual fitting service usage intentions, this study can suggest effective strategies to increase usage intentions for companies providing virtual fitting services. Additionally, these findings can be utilized in the formulation of virtual fitting service marketing strategies.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.95-102
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• 2023

This study was to identify the factors affecting nurses' use intention of digital healthcare and the moderating effect of clinical career based on the UTAUT model. The items were composed by performance expectancy 3 items, facilitation condition 3tiems, and perceived risk 3 items. CFA was performed to verify the construct validity. As a results, average variance extracted (AVE) was .5 or higher, and construct reliability (CR) was .7 or higher. Model fit was confirmed as CMIN/df=1.797, GFI=.955, CFI=.979, TLI=.968, IFI=.979, and RMSEA=.063. The internal reliability was .93 for performance expectancy, .84 for facilitating conditions, and .64 for perceived risk. Performance expectancy, facilitating condition, and perceived risk had a significant effect on use intention, and clinical career showed a moderating effect(t=-2.159, p=.032). Therefore, in order to enhance the use intention of digital health care, performance expectancy, and facilitating conditions should be raised and perceived risk should be reduced.

• Journal of Korea Game Society
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• v.21 no.3
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• pp.67-78
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• 2021

The subjects of this study are Chinese players who have participated in public welfare games. SPSS24.0 and AMOS24.0 were used to analyze the data, including reliability analysis, validity analysis, correlation analysis, structural equation model verification and so on. The hypothesis results show that Trust-Aware is the most important motivation dimension that affects players' participation in public welfare games. Under the dimension of Performance Expectancy, the main influencing factors are players' needs for self-realization and concern for vulnerable groups. Perceived Risk and Social Influence are the motivational factors that influence players' participation in public welfare games.

• The Journal of Information Systems
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• v.26 no.1
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• pp.143-169
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• 2017

Purpose With the increase of the elderly population, the growth of its information system related market is increasing. However, empirical studies for the usage of elderly people's smartphones are still limited. This study aims to investigate the factors that affect the seniors' smartphone usage behaviors. Design/Methodology/Approach First, a preliminary study was conducted with targeting seniors who have visited Gwangju Senior Technology Center(GSTC) in order to understand the factors that affect the intention of utilizing smartphones. Next, based on the preliminary study results and literature reviews including the UTAUT model, performance expectancy, effort expectancy and social influence were considered for the major factors affecting the usage of elderly people's smartphones. Also, the moderate effects of personal innovativeness and usage function were discussed. A questionnaire survey of 181 seniors visiting GSTC was analyzed to empirically test the research model. Findings By the empirical tests, the performance expectancy and the effort expectancy of the seniors had significant impacts on their smartphone usage behavior. While the moderating effect of personal innovativeness was not significant, the moderating effect of the usage function was significant in the relationship between performance expectancy and the smartphone usage behavior. The results of this study are expected to provide guidelines to excavate the technical development and the niche market targeting the elderly people.

• Journal of Convergence for Information Technology
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• v.7 no.4
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• pp.53-60
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• 2017

The purpose of this study was to identify the factors affecting intention and attitude of artificial intelligence technology(AI) of university students in healthcare using UTAUT model. Participants were 278 college students and the data were collected through self-reported questionnaire from May 15 to June 14, 2016. The collected data were analyzed using PASW Statistics/AMOS 22.0. The results were as follows. The effect of expectation factor, social influence, usefulness of work, anxiety factor had a significant effect on use of AI technology Intention. Factor of expectation effect, social influence, usefulness of work, anxiety factor had a significant effect on use of AI technology. As a result of verifying the significance of the indirect effect, it can be seen that the direct effect of the anxiety factor on the attitude factor is partially mediated by the use intention factor and the intention to use was partially mediated in the direct effect of the usefulness factor of the task on the attitude factor. This result means that it is important to increase the expectation factors, social effects, and perceived usefulness through accurate information based on facts and to reduce vague anxiety in order to increase the positive intention and attitude of university students' use of AI technology.

• Journal of the Korea Society of Computer and Information
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• v.29 no.7
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• pp.53-71
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• 2024

Generative Artificial Intelligence (AI) has become the focus of societal attention due to its wide range of applications and profound impact. This paper constructs a comprehensive theoretical model based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), integrating variables such as Personal Innovativeness and Perceived Risk to study the key factors influencing enterprises' adoption of Generative AI. We employed Structural Equation Modeling (SEM) to verify the hypothesized paths and used the Bootstrapping method to test the mediating effect of Behavioral Intention. Additionally, we explored the moderating effect of Perceived Risk through Hierarchical Regression Analysis. The results indicate that Performance Expectancy, Effort Expectancy, Social Influence, Price Value, and Personal Innovativeness have significant positive impacts on Behavioral Intention. Behavioral Intention plays a significant mediating role between these factors and Use Behavior, while Perceived Risk negatively moderates the relationship between Behavioral Intention and Use Behavior. This study provides theoretical and empirical support for how enterprises can effectively adopt Generative AI, offering important practical implications.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.3
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• pp.153-168
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• 2019

Augmented Reality(AR) has been one of the important technologies of the 4th industrial revolution. Consumer acceptance of new technologies is substantial issue for market expansion, but there have been few empirical studies on factors that affect the acceptance or use intention of AR. In this study, we have explored and analyzed the factors influencing technology acceptance based on the extended unified theory of acceptance and use of technology(UTAUT2) model in the AR business and have discussed it with comparison with existing research based on this analysis. The results of this study suggest that the main variables of the existing UTAUT1 model had significant positive effect on the intention to use, such as performance expectancy, effort expectancy, facilitating conditions and hedonic motivation, habits of UTAUT2. In addition, perceived risk introduced in this study had a negative effect on intention to use. Furthermore, the impact between these two factors have been effort expectancy(${\beta}=.294$)>habits(${\beta}=.268$)>hedonic motivation(${\beta}=.266$)>performance expectancy,(${\beta}=.263$)>facilitating conditions(${\beta}=.233$)>perceived risk(${\beta}=-.094$). The impact of social influence did not have a significant effect on intention to use. The intention to use was analyzed to have a significant positive effect on the actual use and recommendation intention. On the other hand, the hypothesis that the age and gender has played a moderating role between independent variables and the intention of use were investigated. Age was found out to play a role as a moderator between social influence, facilitating conditions, hedonic motivation, habits and intention to use. In the same way, gender has been shown to play a moderating role between facilitating conditions, perceived risk and intention to use. Academic and practical implications are suggested based on the results of this study.

• Knowledge Management Research
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• v.23 no.4
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• pp.251-273
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• 2022

Metaverse is one of the most frequently used words recently, with digitalization accelerated by the COVID-19 pandemic that started in 2019 and the development of information and communication technology. It is expected to bring a new revolution in our life as a whole in user experience. In particular, as telecommuting was adopted in the business area, interest in virtual office services such as digital video conferencing and remote offices, which are similar to the metaverse, has also increased. In this study, a study on the intention to use the metaverse service used in the work environment was applied to the Unified Theory of Acceptance and Use of Technology 2(UTAUT2). External variables for metaverse characteristics, such as self-presentation, telepresence, and technostress, were analyzed and discussed. In this study, PC-based Gather.town and VR-based Facebook Horizon, currently the most well-known and considered usable in work environments, were introduced to potential users and conducted a survey. This study has academic implications in that the research has examined the factors that affect the technology acceptance intention of users who want to apply the metaverse as a work environment based on the UTAUT2 model, unlike previous studies that have been mainly researched on the general metaverse. In practice, it may be helpful to suggest factors that should be considered when firms adopt the metaverse for business purposes.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.7
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• pp.177-186
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• 2012

Social Network Service is a web-based service that allows the people to construct relationship among users with same interest and supports various activities such as managing personal relations and sharing information or contents. The objective of this study is analysing the influence of the innovativeness on the use intention in SNS based on the UTAUT model. This study establishes a theoretical model that includes four independent variables(performance expectancy, effort expendancy, social influence, innovativeness) and two moderating variables(gender and innovativeness). The empirical results obtained in a sample of 403 university students are followings; 1) The use intention is positively influenced by the performance expectancy, effort expendancy, social influence and innovativeness. The effort expectancy is the strongest predictor of the use intention 2) The gender has a moderating effect whileas the innovativeness has no moderating effect. For men, the stronger the effect of performance expectancy on the use intention and for women, the stronger the effect of social influence on the use intention.

• 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.