• Korean Journal of Organic Agriculture
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• v.28 no.3
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• pp.315-334
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• 2020

This study was conducted to analyze factors affecting acceptance of smart farm technology. Smart farm technology is rapidly being introduced to agriculture in accordance with the progress of the 4th Industrial Revolution, but research on this is still little. Therefore, in this study, based on the unified theory of acceptance and use of technology (UTAUT), a research model reflecting the characteristics of smart farm technology was constructed. To test this, empirical analysis was performed. A survey was conducted for students in smart farm technology education and adult male and female farmers who are currently planning to operate smart farms. Valid 204 sample were used for analysis. The hypothesis test was based on multiple regression analysis using SPSS 24 statistical package. For the mediating effect and moderating effect, Process Macro 3.4 based on the regression equation was used. The results of testing the hypothesis are as follows. First, in the causal hypothesis test, it was shown that performance expectancy, social influence and price value have a significant positive effect on the intention to use smart farm technology. On the other hand, effort expectancy, facilitating conditions were not tested for a significant influence on the use of smart farm technology. As a result of analyzing the mediating effect of trust, it was found that trust plays a mediating role between performance expectancy, effort expectancy, social influence, facilitating conditions, price value and intention to use smart farm technology. In particular, the effort expectancy has not been tested for a direct significant effect on intention to use smart farm technology, but it has been shown to have an impact through trust. Trust was found to be a full mediating between the effort expectancy and the intention to use the smart farm technology. The current IT level of prospective users has been shown to play a moderating role between performance expectancy, facilitating conditions and intention to use smart farm technology. In particular, the IT level was found to strengthen the relationship between performance expectancy and intention to use smart farm technology. Based on the results of these studies, academic and practical implications were suggested.

• Fashion & Textile Research Journal
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• v.25 no.3
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• pp.291-303
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• 2023

The purpose of this study is to investigate the impact of technical acceptance factors of Chinese MZ generation consumers' use of online fashion platforms on behavioral intentions and usage behavior, and to determine whether satisfaction plays an additional role in the relationship between behavioral intentions and usage behavior. The research results can be summarized as follows. First, among the technology acceptance factors that influence Generation MZ consumers when they use online fashion platforms, it was found that performance expectancy, effort expectancy, facilitating conditions, hedonic motivation, price value, habit, and content quality significantly influence the behavioral intention to use online fashion platforms. Second, the facilitating conditions and the platform usage intention of Chinese Generation MZ consumers directly and significantly influence the usage behavior on online fashion platforms. In contrast, it was confirmed that habit does not significantly influence actual usage behavior. Third, this study confirmed the moderating effect of satisfaction on the relationship between behavioral intention and usage behavior on online fashion platforms. This research, which proposes a research model explaining the usage intention and behavior of online fashion platforms based on UTAUT2, integrating not only the organizational aspect but also the consumer aspect to empirically verify the usage intention and the final usage behavior from the general consumer's perspective, has academic significance.

• Journal of Distribution Science
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• v.21 no.7
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• pp.117-129
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• 2023

Purpose: With the number of COVID-19 cases declining and generational differences among how people use mobile apps, including health service apps, the goal of this research is to identify and analyze the factors that affect people's attitudes when using the Halodoc health service app during the third year of the pandemic. Research design, data, and methodology: This study proposes a quantitative analysis method based on PLS-SEM modeling. This study has used a questionnaire survey to collect randomized data from 268 Halodoc users from generations Y and Z in Jakarta. Results: Both the Y and Z generations believe there is a significant usefulness factor in the attitude toward using the application. The start of the pandemic period demonstrates that the urgency of using health service applications is no longer determined by performance expectations, effort, or social panic, but rather by these applications' usability. Conclusions: Even though a health service application is no longer considered an urgent service or a priority need, attitudes, and behaviors in using it emphasize the aspect of long-term benefits. These findings supplement other considerations and understandings in application of the Unified Theory of Acceptance and Use of Technology (UTAUT) model in explaining attitudes and intention behaviors.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.21-39
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• 2021

The acceptance of smartphone applications in the learning field is one of the most significant challenges for higher education institutions in Saudi Arabia. These institutions serve large and varied sectors of society and have a tremendous impact on the knowledge gained by student segments at various ages. M-learning is of great importance because it provides access to learning through a wide range of mobile networks and allows students to learn at any time and in any place. There is a lack of quality requirements for M-learning applications in Saudi societies partly because of mandates for high levels of privacy and gender segregation in education (Garg, 2013; Sarrab et al., 2014). According to the Saudi Arabian education ministry policy, gender segregation in education reflects the country's religious and traditional values (Ministry of Education, 2013, No. 155). The opportunity of many applications would help the Saudi target audience more easily accept M-learning applications and expand their knowledge while maintaining government policy related to religious values and gender segregation in the educational environment. In addition, students can share information through the online framework without breaking religious restrictions. This study uses a quantitative perspective to focus on defining the technical aspects and learning requirements for distributing knowledge among students within the digital environment. Additionally, the framework of the unified theory of acceptance and use of technology (UTAUT) is used to modify new constructs, called application quality requirements, that consist of quality requirements for systems, information, and interfaces.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.993-1001
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• 2021

This study aims to determine the factors influencing student performance using the teaching and learning process through e-learning based on the unified theory of acceptance and use technology (UTAUT). This study also sets out to propose additional variables to expand the UTAUT model to be more suitable to use in higher education. This research conducted a literature review, expert interviews, and a self-administered survey involving 200 students at tertiary institutions in Riau province, Indonesia. The questionnaire data were analyzed using SmartPLS 2. This study shows that UTAUT constructs, namely, social influence, facility conditions, and effort expectancy have a significant influence on student behavior and performance, while the performance expectancy variable shows no significant effect. The additional variables, including lecturer characteristics, external motivation, and organizational structure, directly affect student performance. However, concerning student behavior, motivation and environment are the only variables with a significant effect. The results of this study suggest the behavior deteminant such as lecturer characteristics, motivation and environment, and organizational structure improve student performance. This study investigates factors affecting the performance of university students through the learning employing e-learning by developing the UTAUT constructs to include the lecturer characteristics, motivation and environment, and organizational structure in improving student performance.

• Asia-Pacific Journal of Business
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• v.12 no.3
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• pp.1-36
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• 2021

Purpose - This empirical study, aims to identify the determinants of adoption and acceptance of mobile payment as to understand why it is successful in some countries in Sub-Saharan Africa but failing in others. A comparative study of a successful mobile payment service and a purported failed one was done as to have some insights to the factors affecting acceptance of the technology. Design/methodology/approach - The strength of three notable theories: theory of diffusion of innovation (DOI), the extended unified theory of user acceptance of information technology (UTAUT2) and self-efficacy theory were use. The self-efficacy of government support inclusion as, a moderating variable in the form of infrastructure, securing transaction and price value revealed the relevance of government in the success of mobile payment service. By means of a field survey of 705 subjects in two separate regions of Africa (East and West), the data was collected and use to test the research model. Findings - The study result shows the importance of the moderating factor of government support to the success of mobile payment of any nation. The result also shows the importance of the perception of relative advantage, compatibility, complexity, social influence as already revealed by other studies. Research implications or Originality - Mobile payment success in some part of Sub-Saharan Africa is well known but also suggested to fail in some Sub-Saharan African countries. Buttressing the need for understanding of the factors affecting mobile payment acceptance. This article empirically examined the factors influencing the success of mobile payment, and we implicated that if the implementation of mobile payment is to be successful for mobile commerce in any nation, adoption, acceptance and use by its citizen is imperative.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.25-33
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• 2020

In this paper, the purpose is to verify the impact of performance expectations, effort expectations, social impact, individual innovation and perceived value on the intent of use and the behavior of use. Used Unified Theory of Acceptance and Use of Technology (UTAUT) to verify the applicability of this model in China, and established the research model by adding two new variables to UTAUT according to the situation of the Chinese market. To achieve this goal, 345 questionnaires were collected for experienced music creators using artificial intelligence nuggets in China by means of Internet research. The collected data were analyzed through frequency analysis, factor analysis, reliability analysis, and structural equation analysis through SPSS V. 22.0 and AMOS V 22.0. The verification of the hypotheses presented in the research model identified the decisive influence factors on the use of artificial intelligence music acceptance by Chinese users. The study is innovative in that it attempts to verify the applicability of UTAUT in the Chinese context. In the construction of the user acceptance model of AI music, three influencing factors will have an effect on users' intentions, and according to the degree of effect, from largest to smallest, they are respectively Perceived Innovativeness, Performance Expectancy and Effort Expectancy. This paper will also provide some management advices, i.e. improving the utility and usability of AI music, encouraging users with individual innovativeness, developing competitive and attractive pricing policies, increasing publicity, and prioritizing word-of-mouth advertising.

• 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 Technology Innovation
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• v.27 no.4
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• pp.111-144
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• 2019

As virtual assistants rapidly diffused into the market, the voice shopping market is expected to expand. The purpose of this study is to identify the factors that determine the consumers' intention to adopt voice shopping by using the unified theory of acceptance and use of technology(UTAUT). In this study, we set variables that influence the intention to adoption of voice shopping with performance expectation and effort expectations as the variables of UTAUT and playfulness expectations as an extended variable. In addition, we also include four voice secretary attributes such as response accuracy, compatibility, social presence, and safety in our research model to investigate the source of motivation of voice shopping adoption. The result of this analysis shows that variables such as performance expectation, effort expectation, and amusement expectation have a positive effect on the intention to adoption of voice shopping. With respect to the four voice shopping attributes, compatibility had a positive effect on performance expectancy, effort expectancy, and playfulness expectancy. Social presence has a positive effect on playfulness expectancy. Safety has a positive effect on effort expectancy and playfulness expectancy. On the other hand, response accuracy is not significant for performance expectancy, effort expectancy, and playfulness expectancy. This study reveals the determinants of intention to adopt the new purchasing method called voice shopping, and suggests the important factors for the innovation of commerce business.

• 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.