• Information Systems Review
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• v.23 no.4
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• pp.1-22
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• 2021

In the newly encountered economy caused by the Corona virus Disease-19, remote transaction becomes a new normal that disrupt traditional economic order. In the middle of the disruption, mobile tech is placed and remote finance on mobile is highly noticed and considered as an infra-tech to support the new ecology, In mobile finance. remote payment is becoming the most common service and personal identification on it is critical to operate the new service. There are various means of remotely identifying a person. Recently the use of biometric information is increasing. In this study, a correlation analysis was conducted on factors that effects to biometrics usage and the intention to use in remote personal identification. Variables for critical factor in the remote identification were classified into 4 groups such as Performance expectancy, Effort expectancy, Social influence, and Security. The empirical analysis based on the Unified Theory of Acceptance and Use of Technology (UTAUT) was conducted. The relationship between variables and the intention to use is also analyzed. In the study, stepwise regression analysis was conducted four times in which variables were adjusted in individual stage. As a result, the analysis suggests that performance expectancy, effort expectancy, social influence, security have positive effects for intention to use. Additionally, effort expectancy and security have moderating effects to intention to use depends on biometric authentication experience. The analysis has shown positive effect of variables grouped on the intention to use them. It also suggests that the intention to use biometric authentication will quickly grow. This study is expected to make a contribution to utilize and improve the use of biometric information in mobile payment.

• Korean Journal of Culture and Social Issue
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• v.14 no.1_spc
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• pp.111-134
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• 2008

In this article, a fairly extensive literature review was conducted to depict the current status of academic motivation and its developmental trend among Korean adolescents. The focal factors were perceived competence and autonomy which have been considered as major determinants of academic motivation. Theoretical frameworks adopted were self-efficacy theory, expectancy-value theory, and self-determination theory. Empirical studies conducted in Korean educational settings during the past decade were the target of the literature review. Results of the literature analysis revealed that, in general, there was a decreasing tendency in perceived competence from elementary to middle school which followed by a slight increase after entering high school. Similar trend revealed in the development of autonomous motivation, in that middle and high school students' intrinsic motivation levels were lower than that of the elementary groups. The amotivational tendency was increased as the grade level proceeded toward high school, which requires attention from educators. Discussion was followed in an attempt to provide plausible interpretations for this undesirable current status of Korean adolescents' academic motivation and to suggest implications for possible remedial actions both in pedagogical perspectives and students' well-being.

• The Mathematical Education
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• v.46 no.3
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• pp.263-272
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• 2007

Mathematics Teaching Efficacy Beliefs Inventory (MTEBI) was translated into Korean and conducted among Korean pre-service mathematics teachers. The Korean-translated MTEBI consists of two subscales with 16 items. Personal Mathematics Teaching Efficacy (PMTE) subscale has 10 items and Mathematics Teaching Outcome Expectancy (MTOE) subscale has 6 items. The purpose of this study is to investigate the internal reliability and the construct validity of the Korean-translated MTEBI. The Cronbach alpha coefficient of Korean-translated MTEBI and its two subscales are respectively .87, .83, and .74 which imply that the instrument is reliable. The construct validity was achieved by performing factor analysis. Principal component solution with varimax rotation for the Korean-translated MTEBI was used in factor analysis and thus the best fit simple structure was obtained by two factors which correspond to the self-efficacy dimension and the outcome expectancy dimension of Bandura's self-efficacy theory.

• Asia pacific journal of information systems
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• v.18 no.3
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• pp.45-65
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• 2008

The rapid growth of the Internet has increased the amount of transmission of personally identifiable information. At the same time, with new Internet related technologies, organizations are trying to collect and access more personal information than before, which in turn makes individuals concern more about their information privacy. For their successful businesses, organizations have tried to alleviate these concerns in two ways: (1) by offering privacy policies that promise certain level of privacy protection; (2) by offering benefits such as financial gains or convenience. In this paper, we interpret these actions in the context of the information processing theory of motivation. This paper follows Hann et al.(2007)'s methods to analyze Internet users privacy concerns in Korea and tries to compare the findings. Our research objectives are as follows: First, we analyze privacy concern mitigation strategies in the framework of the expectancy theory of motivation. Subsequently, we show how the expectancy theory based framework is linked o the conjoint analysis. We empirically validate the predictions that the means to mitigate privacy concerns are associated with positive valences resulting in an increase in motivational score. In order to accommodate real-life contexts, we investigate these means in trade-off situation, where an organization may only be able to offer partially complete privacy protection and/or promotions and/or convenience, While privacy protection (secondary use, improper access) are associated with positive valences, we also find that financial gains can significantly increase the individuals' motivational score of a website in Korea. One important implication of this empirical analysis is that organizations may possess means to actively manage the privacy concerns of Internet users. Our findings show that privacy policies are valued by users in Korea just as in the US or Singapore. Hence, organizations can capitalize on this, by stating their privacy policy more prominently. Also organizations would better think of strategies or means that may increase online users' willingness to provide personal information. Since financial incentives also significantly increase the individuals' motivational score of website participation, we can quantify the value of website privacy protection in terms of monetary gains. We find that Korean Internet users value the total privacy protection (protection against errors, improper access, and secondary use of personal information) as worthy as KW 25,550, which is about US 28. Having done this conjoint analysis, we next adopt cluster analysis methodology. We identify two distinct segments of Korea's internet users-privacy guardians and information sellers, and convenience seekers. The immediate implication of our study is that firms with online presence must differentiate their services to serve these distinct segments to best meet the needs of segments with differing trade-offs between money and privacy concerns. Information sellers are distinguished from privacy guardians by prior experience of information provision, To the extent that businesses cannot observe an individual's prior experience, they must use indirect methods to induce segmentation by self-selection as suggested in classic economics literature of price discrimination, Businesses could use monetary rewards to attract information sellers to provide personal information. One step forward from the societal trends that emphasize the need of legal protection of information privacy, our study wants to encourage organizations and related authorities to have the viewpoints to consider both importance of privacy protection and the necessity of information trade for the growth of e-commerce.

• 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 the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.245-255
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• 2016

Consumer expectation is divided into rational and emotional components with regard to the experience of products or services. The purpose of this study is to investigate the relationship between these two types of expectations and consumer satisfaction. For the theoretical framework, we use the dual expectation theory with respect to the should-expectation and will-expectation, and verify their effects on consumer satisfaction. The findings of this study imply that under rational expectation, consumer satisfaction increases when the result of their experience exceeds their expectation and the impact is stronger when the will-expectation is satisfied. Under emotional expectation, consumer satisfaction increases when the should-expectation exceeds the result of the actual performance, but decreases when there is disaccord between the will-expectation and performance. For emotional-based expectation, the impact on consumer satisfaction is stronger for should-expectancy disconfirmation than for will-expectancy disconfirmation.

• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.101-114
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• 2021

This study aimed to analyze the degree of consumers' expectations for their performance and efforts in using overseas direct purchase, impact of overseas direct purchase on the society, and effect of price value to their intention to use overseas direct purchase in the future. In addition, the significance of overseas direct purchase on the user-perceived availability is empirically analyzed. As a result of the study, it was confirmed that performance expectancy, effort expectancy, social influence, and price value showed significantly positive effect on the intention to use overseas direct purchase in the future. With respect to the perceived availability in using overseas direct purchase, it was found out that effort expectancy and price value had significantly positive effect; however, it appeared that performance expectancy and social influence had no significant effect on the perceived availability of the users.

• Journal of Korean Society for Quality Management
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• v.50 no.3
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• pp.593-615
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• 2022

Purpose: The purpose of this study was to explore and examine the factors influencing customer satisfaction and subscription intention in order to propose useful implication regarding subscription economy model. Methods: This study adopts the extended Unified Theory of Acceptance and Use of Technology model (UTAUT2) as the theoretical framework. On the basis of literature review, this study suggested 9 related hypothesis. To examine the hypothesis proposed, the study designed surveys with 32 questions and 456 answers were collected for the analysis. The study adopted a structural equation model and path analysis, using AMOS and SPSS programs. Results: The results of this study are as follow: All hypothesis except performance expectancy and effort expectancy have significant influence on customer satisfaction. Performance expectancy and effort expectancy have no significant influence on customer satisfaction and facilitate condition is significant but negatively associated with customer satisfaction. Conclusion: Result of this study is expected to suggest data regarding subscription economy and customer satisfaction for business with subscription model. In detail the result implies that highly sophisticated curation system would create more customer satisfaction and subscription intention rather than how a subscription-based platform is easily used. Moreover, curation system of subsription-based music platform should function with high accuracy on recommendation in a creative visual form in order to gain comparative advantage while most platforms have built own curation service.

• Journal of Korean Society for Quality Management
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• v.50 no.1
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• pp.43-61
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• 2022

Purpose: The purpose of this study was verifying factors that affect to intention to use AI financial services and finding a way of building an user oriented AI ecology. Methods: This study used the UTAUT (Unified Theory of Acceptance and Use of Technology) model with independent variables such as performance expectancy, effort expectancy, social influence, facilitating conditions, trust, personal innovativeness and AI understanding as moderating variable. The data was collected through online & offline survey with questionnaire from 330 financial customers. Results: As a result, the analysis suggested that the performance expectancy, social influence, facilitating conditions, personal innovativeness are statistically significant to the intention to use AI. It was also found that AI knowledge of users differently influence the intention to use through the moderating effect on the facilitating conditions. Conclusion: Performance expectancy, social influence, facilitating conditions, personal innovativeness have positive causation to the intention to use in AI financial service. On the facilitating conditions, unlike other variables, it was found that the user's intention to use was different by the level of AI understanding. It means that customers could have the strong intention to use AI even though they don't have enough pieces of knowledge on the factors. Customers seem to be of recognition that the technology has certain benefits for themselves. The facilitating factors are significantly affected by AI understanding and differently effect on the intention to use AI.

• Journal of Venture Innovation
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• v.3 no.2
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• pp.41-76
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• 2020

This study confirmed factors affecting smart factory technology acceptance through empirical analysis. It is a study on what factors have an important influence on the introduction of the smart factory, which is the core field of the 4th industry. I believe that there is academic and practical significance in the context of insufficient research on technology acceptance in the field of smart factories. This research was conducted based on the Unified Theory of Acceptance and Use of Technology (UTAUT), whose explanatory power has been proven in the study of the acceptance factors of information technology. In addition to the four independent variables of the UTAUT : Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions, Government Assistance Expectancy, which is expected to be an important factor due to the characteristics of the smart factory, was added to the independent variable. And, in order to confirm the technical factors of smart factory technology acceptance, the Task Technology Fit(TTF) was added to empirically analyze the effect on Behavioral Intention. Trust is added as a parameter because the degree of trust in new technologies is expected to have a very important effect on the acceptance of technologies. Finally, empirical verification was conducted by adding Innovation Resistance to a research variable that plays a role as a moderator, based on previous studies that innovation by new information technology can inevitably cause refusal to users. For empirical analysis, an online questionnaire of random sampling method was conducted for incumbents of domestic small and medium-sized enterprises, and 309 copies of effective responses were used for empirical analysis. Amos 23.0 and Process macro 3.4 were used for statistical analysis. For accurate statistical analysis, the validity of Research Model and Measurement Variable were secured through confirmatory factor analysis. Accurate empirical analysis was conducted through appropriate statistical procedures and correct interpretation for causality verification, mediating effect verification, and moderating effect verification. Performance Expectancy, Social Influence, Government Assistance Expectancy, and Task Technology Fit had a positive (+) effect on smart factory technology acceptance. The magnitude of influence was found in the order of Government Assistance Expectancy(β=.487) > Task Technology Fit(β=.218) > Performance Expectancy(β=.205) > Social Influence(β=.204). Both the Task Characteristics and the Technology Characteristics were confirmed to have a positive (+) effect on Task Technology Fit. It was found that Task Characteristics(β=.559) had a greater effect on Task Technology Fit than Technology Characteristics(β=.328). In the mediating effect verification on Trust, a statistically significant mediating role of Trust was not identified between each of the six independent variables and the intention to introduce a smart factory. Through the verification of the moderating effect of Innovation Resistance, it was found that Innovation Resistance plays a positive (+) moderating role between Government Assistance Expectancy, and technology acceptance intention. In other words, the greater the Innovation Resistance, the greater the influence of the Government Assistance Expectancy on the intention to adopt the smart factory than the case where there is less Innovation Resistance. Based on this, academic and practical implications were presented.