• 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.

• Journal of Distribution Science
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• v.18 no.6
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• pp.25-35
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• 2020

Purpose:Travel agencies have use digital tools in order to shift the paradigm in how business is conducted. Online travel agencies provide the same services as a normal travel agency, including hotels, transportation, guided tours, reservations, and related services, but using an "online platform. Travelers planning a trip can use a lot of forms to collect information and have access to a larger amount of information, so the factors that influence the user's behavioral intention are very important. This research has the conducted to find what factors lead to the attitudes of consumers in using OTA using the UTAUT model. Research design, data and methodology: The object of this study were respondents of a google survey using convenient sample extraction method, chosen among consumers who gathered information, or purchased a product. A total of 217 of the 235 questionnaires Google survey answered were used in the final analysis, excluding insincere responses. Using PSS v.21 and AMOS v.21, frequency analysis, feasibility and reliability analysis, path analysis was performed. Results: UTAUT affects OTA use satisfaction and trust, and OTA satisfaction and trust affect behavior intention. Conclusions: Research was conducted using the UTAUT model to explore factors that affect the attitudes of users of online travel agencies (OTA).

• Journal of the Korean Society for Aviation and Aeronautics
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• v.32 no.1
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• pp.49-60
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• 2024

This study used the Unified Theory of Acceptance and Use of Technology(UTAUT) model to find factors that influence consumer acceptance intention toward Vertiport, a physical ground support technology required to implement AAM services. The analysis showed that among the four independent variables, Vertiport's social influence and facilitating conditions have a significant impact on future Vertiport usage behavior. At this point, the public has not yet had actual experience with Vertiport, so there is a limitation of considering it as a future concept based on speculation and measuring acceptance by actual behaviors related to its use (inquiries, information gathering, interest, etc.). Research on acceptance and attitudes toward new transportation methods should be further activated and developed along with future service development. Through the results of this study, we aim to understand the initial public acceptance of Vertiport as a ground-based infrastructure in the AAM field (or UAM) and propose strategic implications for the direction of service development.

• 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.

• 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.

• Asia-Pacific Journal of Business
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• v.9 no.4
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• pp.181-199
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• 2018

The purpose of this study is to verify the extended technology readiness and acceptance model according to the characteristics of technology for the continuous use motive of SNS users. In particular, we conducted a comparative study on the differences in technology readiness and acceptance model between countries through the empirical analysis of the users of SNS in Korea and China with different technological and cultural environments. The results of this study are as follows; First, Positive technology readiness index has a positive effect on performance expectancy, effort expectancy, social influence, and facilitating conditions, which are variables of UTAUT. Positive technology readiness also has a positive effect on Enjoyment, which is added in this study. Second, negative technology readiness index has negative effect on performance expectancy and social influence, which are variables of UTAUT. In addition, negative technology readiness index has not a significant effect on enjoyment, which was added in this study. Finally, the relationship between technology readiness index, motivation for technology acceptance, and continuously intention to use has a partially different influence on the Korean and Chinese users. Based on the results of this study, this study suggested academic implications and practical implications.

• Journal of Information Technology Applications and Management
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• v.27 no.1
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• pp.75-95
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• 2020

Smart Factory is the decisive factor of the Fourth Industrial Revolution and is a key field for national competitiveness. Until now, most smart factory research has focused on policy and technology. In order to spread more technology, it is necessary to study what factors influence the adoption of smart factory technology in the enterprise. Nevertheless, little research has been done. In this study, based on the UTAUT (Unified Theory of Acceptance and Use of Technology), which has been proved through many years of research, I have studied the factors that influence the acceptance of smart factory technology. As a result of research, performance expectancy, social influence, and facilitating conditions of UTAUT model had a positive(+) effect on behavior intention. Their relationship of influence was in the order of performance expectancy (β = .459)> facilitating conditions (β = .212)> social influence (β = .210). However, it was found that the effort expectancy did not affect the behavior intention, and the impact of the newly perceived risk on the behavior intention to use was not confirmed. The main reason is that the acceptance of smart factory technology is not a matter of personal interest but a matter of organizational choice. Trust, on the other hand, was found to be partially mediated between performance expectancy, facilitating conditions, social influence and behavior intention. For many years, many researchers have validated the UTAUT, which has been validated through various empirical studies. It is academically meaningful to begin the study of factors affecting the acceptance of smart factory technology in terms of the UTAUT. In practice, it is necessary to provide SME employees with more information related to the introduction of smart factories, to provide advanced services related to the establishment of smart factories, and to establish a standardized model for each industry.

• 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 Information Technology Applications and Management
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• v.26 no.6
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• pp.29-46
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• 2019

This study analyzed the factors influencing the technology acceptance of the general public in the drones and ARs, one of the key technologies of the industry 4.0. The theoretical basis was the extended unified theory of acceptance and use of technology model(UTAUT2), which uses performance expectancy, effort expectancy, social influence, facilitating conditions, and hedonic motivation as factors common to both services. The price value factor was excluded considering that most ARs were free, and the perceived risk factors, including privacy, which were not in UTAUT2, were included because they are important factors for ICT technology acceptance. The hypothesis was tested by structure equation model. Social influence and hedonic motivation had a positive(+) effect on intention to use technology. On the other hand, in the case of effort expectancy, neither the AR nor the drone had a significant influence on intention to use technology. Furthermore, performance expectancy had a positive(+) effect on intention to use in AR, but no significant influence was found out in drones. On the contrary, in the case of the facilitating conditions, the influence of the drones was positive (+), but the relation of AR was not investigated. The perceived risk was tested for the negative (-) influence of use intention of AR, but no significant relationship was found out for the drones. Among the significant influencing factors, hedonic motivation was the most powerful factor in AR and drones. Theoretical and practical implications are presented based on these results.

• 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.