• 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 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.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.630-646
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• 2022

This study examines online art platforms as a new type of informational technology and seeks to verify the impact of the user's perceived value and acceptance of new technologies on the behavioral intention about art platforms. For this, it was conducted to survey 489 users of the online art platform. Several emotional value, functional value, social value, and value for money were selected as perceived value variables, and performance expectancy, effort expectancy, and facilitating conditions were set as variables of new technology adaptation. As evident in the correlation with perceived values, emotional value and social value have a significant impact on all parameters of new technology adaptation, while functional values and value for money only affect facilitating conditions and behavioral intention, respectively. Furthermore, the impact of acceptance of new technologies confirms that performance expectancy and facilitating conditions affect behavioral intention. This study demonstrates the perceived value of online art platform users and the acceptance of new technologies. Therefore, it is expected that platform providers will be able to use it as primary data to understand and reflect user requirements.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.5
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• pp.3143-3149
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• 2013

Background: Breast cancer is the most common type of cancer among women in Turkey and around the world. Treatment adversely affects women's physical, psychological, and social conditions. The purpose of this study was to identify the experiences of Turkish women with breast cancer and the facilitating coping factors when they receive chemotherapy. Methods: A phenomenological approach was used to explain the experiences and facilitating factors of breast cancer patients during the treatment period. Data were collected through individual semi-structured interviews. The sample comprised 11 women with breast cancer receiving treatment. Results: At the end of the interviews conducted with women with breast cancer, two main themes were identified: adjustment and facilitating coping factors. The adjustment main theme had two sub-themes: strains and coping. Women with breast cancer suffer physical and psychological strains as well as stress related to social and health systems. While coping with these situations, they receive social support, turn to spirituality and make new senses of their lives. The facilitating coping factors main theme had four sub-themes: social support, disease-related factors, treatment-related factors and relationships with nurses. It has been determined that women receiving good social support, having undergone preventive breast surgery and/or getting attention and affection from nurses can cope with breast cancer more easily. Conclusions: Women with breast cancer have difficulty in all areas of their lives in the course of the disease and during the treatment process. Therefore, nurses should provide holistic care, teaching patients how to cope with the new situation and supporting them spiritually. Since family support is very important in Turkish culture, patients' relatives should be informed and supported at every stage of the treatment.

• 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.

• The Journal of Bigdata
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• v.9 no.1
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• pp.169-186
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• 2024

This study aims to analyze the acceptance factors for expanding the adoption of AI by SMEs and draw practical and policy implications. To this, we conducted an empirical analysis of AI acceptance factors among 315 SMEs in various industries such as manufacturing, service, and information and communication sectors located in Korea. Based on the UTAUT, we examined the influence of decision-making reliability, perceived awareness, policy support, education and training, perceived cost, perceived risk, and system complexity, and found that decision-making reliability positively affects performance expectancy and social influence, perceived awareness positively affects performance expectancy and effort expectancy, policy support positively affects social influence and facilitating conditions, and education and training positively affects effort expectancy and facilitating conditions. Perceived cost had a negative effect on social influence and facilitating conditions, and perceived risk had a negative effect on performance expectancy and social influence. System complexity had a negative effect on effort expectancy but no effect on facilitating conditions. These results are expected to be widely utilized as basic research for the diffusion of AI in industry and provide practical and policy implications for promoting the adoption of AI in SMEs.

• 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.

• Korean Journal of Organic Agriculture
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• v.28 no.2
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• pp.119-138
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• 2020

The purpose of this study was to examine the intention of consumer acceptance of technology in agricultural production by applying the unified theory of acceptance and use of technology (UTAUT) to smart farm. In particular, this study analyzed the intention to accept the technology of agricultural students, farmers, start-up farmers, returning farmers, and returnees in the general manufacturing industry and high-tech industries, and in agricultural sectors corresponding to primary industries. The results showed that performance expectancy, social influence, facilitating conditions, IT development level, and reliability had a significant influence on the intention to use smart farm technology. However, effort expectancy and price value were rejected because no significant impact on use intention was tested. In addition, the influences of the variables showing their influence were reliability (β=.569) > IT development level (β=.252) > social influence (β=.235) > performance expectancy (β=.182) > facilitating conditions (β=.134).

• 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.

• The Journal of Information Systems
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• v.19 no.4
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• pp.111-136
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• 2010

This study examined the difference in the usage of internet banking users between Korea and China. This model tests various theoretical research hypotheses relating to internet banking, The Unified Theory of Acceptance and Use of Technology(UTAUT). The factors influencing on the use intention of Internet banking have been classified as performance expectancy, effort expectancy, social influence and facilitating conditions. The proposed model was empirically tested using data collected from a survey of internet banking users in Korea and China. The model is used by SPSS 15.0 and AMOS 7.0 for analysis on the sample collected from 272 respondents. The result of hypothesis testing are as follows. First, performance expectancy and social influence positively influence use intention of internet banking user both Korea and China. Second, facilitating conditions only positively influence on the usage of internet banking users in Korea. On the other side, effort expectancy do not influence the use intention of internet banking users in both two countries. The results of study will provide practical implications on the internet banking in Korea and China.