• The Journal of Society for e-Business Studies
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• v.13 no.2
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• pp.117-147
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• 2008

Developing various ubiquitous computing services (U-services) is being propelled throughout the industry. As U-services are being penetrated into our daily life, research on the factors influencing the acceptance of U-services is highly needed. In this line of study, we examined previous literatures about information technology acceptance and UTAUT model, and applied UTAUT model to U-service acceptance. To characterize the U-services into our research model, we newly introduced 'context based personalization' factor. Since the respondents could not directly experience the U-services yet, we adopted scenario-based questionnaire. For this, we deliberately developed U-service scenario. And then this U-service scenario is verified using capability-based assessment method. Using data collected from 251 respondents, this study found that 'context based personalization' factor was positively and significantly related to the acceptance of U-service as well as UTAUT model's 4 factors such as performance expectancy, effort expectancy, social influence and facilitating conditions.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1717-1726
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• 2018

This study is for looking into Factors affecting the Intention of using about Fitness Tracker based on IoT by Flow Theory and UTAUT Model. The independent variables of the IoT-based fitness tracker have been selected as Challenge, Skill Factors used in the Flow experience theory and selected the personal characteristics of health perception, enjoyment, Social Influence, and Facilitating Conditions. In addition UTAUT theory was used as parameter of Performance Expectancy and Effort Expectancy and intention of Use behavior was selected as a dependent variable. For verifying research hypothesis, This study collected 126 surveys data and carried out a statistical analysis by Smart PLS. The result shows that new Flow Experience and Personal Characteristic Factors with key variables in the UTAUT Model affect significantly to Intention of using about Fitness Wearable environment based IoT.

• Journal of Fashion Business
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• v.24 no.6
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• pp.1-17
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• 2020

This study investigated the perceptions, attitudes, and behaviors of potential consumers toward using 3D printers to create their personal clothes. An online survey and a series of Welch's t-tests and ANOVA were conducted to investigate the differences in demographic characteristics, prior experiences in 3D printing, and levels of need for uniqueness among the sub-groups. A multiple linear regression analysis was performed to test the relationships among variables of the modified Unified Theory of Acceptance and Use of Technology (UTAUT). There were significant differences in gender and prior experiences regarding the UTAUT of personal 3D printing. The need for uniqueness has a positive effect on consumers' intention to use 3D printing technology for designing personal clothes and perception of the price of the 3D printer used to create individual clothes is important. Positive relationships were found between UTAUT variables as well as the use and purchase intentions. This study analyzed the potential for popularization of 3D printing technology to create fashion items and explore consumer willingness to embrace and use personal fashion designs. The results of this study are expected to assist consumers, designers, retailers and marketers, and experts in 3D printing technology by providing insight into consumer awareness and acceptance of personalized 3D-printed fashion and products.

• Journal of Service Research and Studies
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• v.13 no.2
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• pp.99-113
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• 2023

In a customer-based industry, customer retention is the competitiveness of a company, and improving customer retention improves the competitiveness of the company. Therefore, accurate prediction and management of potential dormant customers is paramount to increasing the competitiveness of the enterprise. In particular, there are numerous competitors in the domestic card industry, and the government is introducing an automatic closing system for dormant card management. As a result of these social changes, the card industry must focus on better predicting and managing potential dormant cards, and better predicting dormant customers is emerging as an important challenge. In this study, the Recurrent Neural Network (RNN) methodology was used to predict potential dormant customers in the card industry, and in particular, Long-Short Term Memory (LSTM) was used to efficiently learn data for a long time. In addition, to redefine the variables needed to predict dormant customers in the card industry, Unified Theory of Technology (UTAUT), an integrated technology acceptance theory, was applied to redefine and group the variables used in the model. As a result, stable model accuracy and F-1 score were obtained, and Hit-Ratio proved that models using LSTM can produce stable results compared to other algorithms. It was also found that there was no moderating effect of demographic information that could occur in UTAUT, which was pointed out in previous studies. Therefore, among variable selection models using UTAUT, dormant customer prediction models using LSTM are proven to have non-biased stable results. This study revealed that there may be academic contributions to the prediction of dormant customers using LSTM algorithms that can learn well from previously untried time series data. In addition, it is a good example to show that it is possible to respond to customers who are preemptively dormant in terms of customer management because it is predicted at a time difference with the actual dormant capture, and it is expected to contribute greatly to the industry.

• 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.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.4
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• pp.103-113
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• 2024

This study applies the UTAUT theory to examine the intention to use online shopping mall chatbot services and to elucidate the mediating effect of anthropomorphism in their relationship. For this purpose, a sample of students from A University in Gyeongnam was surveyed online using Google Docs from the first to the second week of May 2024, and after excluding 5 insincere respondents, 245 were used for the final analysis. The key findings are as follows. First, among the UTAUT factors for online shopping mall chatbot services, performance expectancy, effort expectancy, facilitating conditions, and social influence were found to have a significant positive impact on anthropomorphism. The relative impact appeared in the order of performance expectancy, social influence, facilitating conditions, and effort expectancy. Second, anthropomorphism in online shopping mall chatbot services had a significant positive impact on usage intention. Third, the UTAUT factors of performance expectancy, effort expectancy, facilitating conditions, and social influence had a significant positive impact on usage intention, with the relative impact appearing in the order of facilitating conditions, social influence, performance expectancy, and effort expectancy. Fourth, the mediating effect of anthropomorphism was confirmed in the relationship between UTAUT factors and usage intention for online shopping mall chatbot services. This study is limited to students from A University in Gyeongnam, which may restrict the generalizability of the results. Future research should select a broader sample considering regional and demographic diversity and use diverse data collection methods to enhance the reliability and validity of the data.

• 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.

• International Journal of Contents
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• v.18 no.2
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• pp.58-67
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• 2022

As the Internet rapidly evolves, online learning has emerged as the third largest scenario in the field of education. Online education, different from the two traditional learning scenarios of the school and society, is characterized with broader learning types and higher freedom. In today's post-pandemic era, art education, which relies on face-to-face teaching, is of particular significance to expand online education methods. Based on the UTAUT model, this paper posits seven hypotheses about the willingness to continue learning in online art education. After collecting valid data through a questionnaire, a detailed empirical analysis was conducted via SPSS and AMOS. The results of empirical analysis show that less than half of the respondents had experienced the online art education, mirroring that this is a market worth developing. Based on the findings, learning habit does not significantly impact art learners' willingness to continue learning online. This result and other verified hypotheses are detailed in the discussion part of this paper. This study proves that UTAUT can better explain user behavior than the traditional information system model prior to the improvement, and also has strong explanatory power in the field of art education. The conclusion also posits some operational suggestions from the perspective of practitioners in this field, thereby providing a theoretical basis for art education practitioners.

• 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.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.711-720
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• 2020

This research aims to analyze the factors affecting the acceptance of social commerce, including performance expectancy, effort expectancy, social support, facilitating conditions, hedonic motivation, habitability, price saving orientation, and privacy concerns using the Unified Theory of Acceptance and Use of Technology (UTAUT2). UTAUT2 has been examined and modified in various contexts. The research model studies the acceptance and use of technology in the context of customers. This study adopts a quantitative method using the partial least squares regression (PLS) approach involving 244 respondents. The respondents are users of social commerce in Indonesia. The result of this research indicates that social influence, facilitating conditions, hedonic motivation, habit, price value orientation, and privacy concerns have a significant effect on behavioral intention. On the other hand, performance expectancy and effort expectancy does not affect behavioral intention. Furthermore, price value has a significant effect on social commerce user behavior. Lastly, facilitating conditions and habits does not affect social commerce user behavior. This research contributes to the development of theory by examining an additional variable, which is privacy concern. This study is significant since social media and social commerce have grown exponentially nowadays. Implications of the results for the development of the theory (UTAUT2) and practice are discussed in the article.