• Korean small business review
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• v.42 no.4
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• pp.251-283
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• 2020

The purpose of this study is to provide assistance to the establishment of related policies to improve the level of acceptance and use of smart factories for SMEs in Korea. To this end, the Unified Technology Acceptance Model (UTAUT) was extended to select additional factors that could affect the intention to accept technology, and to demonstrate this. To achieve the research objective, a questionnaire composed of 7-point Likert scales was prepared, and a survey was conducted for manufacturing-related companies. A total of 136 questionnaires were used for statistical processing. As a result of the hypothesis test, performance expectation and social influence had a positive (+) positive effect on voluntary use, but effort expectation and promotion conditions did not have a significant effect. As an extension factor, the network effect and organizational characteristics had a positive (+) effect, and the innovation resistance had a negative effect (-), but the perceived risk had no significant effect. When the size of the company is large, the perceived risk and innovation resistance are low, and the level of influencing factors for veterinary intentions, veterinary intentions, and veterinary behaviors are excluded. Through this study, factors that could have a positive and negative effect on the adoption (reduction) of smart factory-related technologies were identified and factors to be improved and factors to be reduced were suggested. As a result, this study suggests that smart factory-related technologies should be accepted.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.293-299
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• 2022

The purpose of study is to relieve the users' anxiety caused by the simplification of the easy money transfer service. With the development of technology, financial services are being simplified, but on the contrary, the chasm occurs. The study was conducted in two rounds. First, based on UTAUT, the perception of the service and the willingness to accept the technology were investigated through a questionnaire. Second, after presenting the tracking function of the remittance situation derived through the heuristic method, in-depth interviews were conducted on reliability and intention to continue using it. As the result, it was found that the clear feedback had a positive effect on relieving users' anxiety. It is expected that studies approaching the chasm from the point of view of design will be actively conducted.

• Journal of the Korea Society of Computer and Information
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• v.23 no.8
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• pp.59-66
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• 2018

In this paper we purposes to analyze the motivation of mobile payment adopters. In this study, with unified theory of acceptance and use of technology (UTAUT) model as the basis of research, we set up a structural equation model based on gender, age, experience and voluntary, collected data in the form of a questionnaire survey and analyzed drivers that affected mobile payers. In this study, The necessity of this paper is that the group of Korean students belongs to a special group with nearly 70,000 people. The penetration rate of mobile payment in China is 77%, ranking first in the world, but after the young people came to Korea. There are many obstacles and inconveniences when using mobile payment. We have proposed special subjects for special populations. the survey data were analyzed using SPSS22.0 and AMOS22.0 statistical software and the proposed model was modified. The results show that consumers' mobile payment is mainly motivated by social influence and performance expectancy. These results are of theoretical value and offer a new direction and implications to mobile payment developers. Besides, they also provide useful information and guidance for enterprises to aim at the market of Chinese oversea students in South Korea.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.3
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• pp.1-10
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• 2018

Wearable Technology is going to be the biggest buzzword and the next generation of digital revolution in the near future. Wearables have changed the focus of the healthcare industry to prevention programs in order to encourage individuals to be more active and to take the responsibility of their own health. Although, the intention of consumers to use wellness wearables has been growing rapidly, the number of individuals who refuses continued use of such devices increases day-by-day. Diffusion and innovation of new technology could be more efficiently gained by consumer's adoption. So, it is extremely important for providers and designers to understand the impact of positive and negative factors on consumers' intention to use wellness wearables. Moreover, a unified framework is required for better understanding of individuals' behavioral intention for using wellness wearables. Thus, the goal of this study is to identify the potential factors that influence consumers' willingness to use wellness wearables as well as proposing a unified framework based on Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and Value-based Adoption Model (VAM) with two extra factors, perceived trust and perceived health increase. The findings of this article improves the theoretical understanding of the engaged factors in the proposed research model of the study.

• Journal of Information Technology Applications and Management
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• v.21 no.2
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• pp.49-79
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• 2014

The adoption of technology has always been of interest to academicians and practitioners of the field of Management Information System. This is so because without proper and adequate adoption, technology-no matter how beneficial or advanced it may be-will be of little value to users. Numerous researches, such as the researches of the Technology Acceptance Model (TAM) or the Unified Theory of Acceptance and Use of Technology (UTAUT), had been conducted to understand the human nature in association with the adoption or rejection of technologies that have bombarded the users. The coming of smart technologies (i.e., smart phones and devices), however, seems to have fundamentally changed the environment for adoption. The ubiquity combined with mobility of technology, especially when it comes to mobile apps, seem to make the old PC era of two-stage-pre and post-adoption models obsolete. A new model of adoption that identifies the determinants of technology acceptance and continuance is needed for the smart age. To this end, this paper undertakes an empirical study, by analyzing 229 users of Social Networking Service (SNS) mobile apps, to identify the role of user experience on the multi-stage adoption of technology, and provides results that User Experience (UX) plays the crucial role of bridging the separate stages of pre and post adoption of technologies. The paper concludes by providing practical implications of the new model as it relates to mobile apps and technologies, and recommendations for further studies to get a better understanding of technology adoption in the smart age.

• The Journal of Information Systems
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• v.30 no.3
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• pp.159-175
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• 2021

Purpose The purpose of this study was to find the effect of the determinants on the Big data utilization in industry. The determinants of Big data utilization were deduced by reviewing theoretical background and discussions on Big data related researches. Research model and proposed hypothesis were constructed from TOE framework and UTAUT model. Design/methodology/approach The research was conducted to collect a sample data from the experts involved in the Big data projects in industry. In addition, interviews and online survey were performed to get sample data. Exploratory factor analysis was conducted to verify the grouping of these questionnaire items and confirmatory factor analysis was done to verify the validity and reliability of the measurement model. Finally, research hypothesis was verified and theoretical and practical implications were proposed for further studies. Findings The results show that the technical factor have a significant effect on the expectancy factor and the behavioral factor. The organizational factor have a significant effect on the behavioral factor. In addition, the expectancy factor was significant on the behavioral factor and the intention-to-use of Big data system.

• Journal of Information Science Theory and Practice
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• v.9 no.1
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• pp.54-67
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• 2021

This paper presents the ISRI (Information Systems Research Indicators) Web tool, publicly and freely available at isri.sciencesphere.org. Targeting Information Systems (IS) researchers, it compiles and organizes IS adoption and use theories/models, constructs, and indicators (measuring variables) available in the scientific literature. Aiming to support the IS theory development process, the purpose of ISRI is to gather and systematize information on research indicators to help researchers and practitioners' work. The tool currently covers eleven theories/models: DeLone and McLean's IS Success Model (D&M ISS); Diffusion of Innovations Theory (DOI); Motivational Model (MM); Social Cognitive Theory (SCT); Task-Technology Fit (TTF); Technology Acceptance Model (TAM); Technology-Organization-Environment Framework (TOE); Theory of Planned Behavior (TPB); Decomposed Theory of Planned Behavior (DTPB); Theory of Reasoned Action (TRA); and Unified Theory of Acceptance and Use of Technology (UTAUT). It also includes currently over 400 constructs, nearly 2,500 indicators, and about 60 application contexts related to the models. For the creation of the tool's database, nearly 580 references were used.

• Journal of Distribution Science
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• v.15 no.5
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• pp.53-64
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• 2017

Purpose - This study focuses on use intention of mobile travel Apps by Chinese tourists visiting Korea based on UTAUT model, ISS model and ITM model. And the corresponding market promotion schemes are proposed for operators of mobile travel Apps by the research results. Research design, data, and methodology - After collecting 326 respondents in China with cross-sectional questionnaires, this study begins the empirical research with users of mobile travel Apps, and analyzes data with IBM SPSS 23.0 and IBM AMOS 23.0. Results - The results of this study include the following aspects: firstly, the System quality and Information quality are accepted for hypotheses of Satisfaction and Performance expectancy. Secondly, the Personal Propensity to Trust and Firm Reputation are accepted for Initial Trust hypothesis, and the hypotheses of Firm Reputation and Initial Trust are accepted for Use Intention. Thirdly, the Performance expectancy, Effort expectancy, Social influence are accepted for Use Intention hypothesis. Conclusions - With the increase of tourists visiting Korea, it can be predicted that the needs visiting Korea will be increased persistently for Chinese - this trend brings about the increase of the Chinese travel. First, information quality greatly influences satisfaction and performance expectancy. The research result shows that, the higher the mobile traveling App's information quality is, the higher the satisfaction and performance expectancy will be. Therefore, operators of mobile traveling App should have in-depth investigations towards users, to know the latter's real demand to the information quality and then provide corresponding services. Second, performance expectancy and effort expectancy greatly influence users' intention. Therefore, mobile traveling App operators should improve Apps' convenience and efficiency and, in doing so, find an effective method for market expansion. Third, social influence greatly affects users' intention. The result shows that mobile traveling App operators should pay attention to the influence of mass media and friends' recommendation on users, thereby it is necessary to improve advertisement activities. Fourth, initial trust also influences users' intention. The result shows that initial trust is a key element inducing users to generate use intention. Therefore, mobile traveling Apps operators should make efforts to catch elements that influence users' initial trust.

• The Journal of Industrial Distribution & Business
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• v.10 no.3
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• pp.59-72
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• 2019

Purpose - Blockchain technology, which has the characteristics of credibility, security, integrity and decentralization, has brought innovation to internet platforms that mediate peer to peer transactions, as well as changes to the contents distribution services. Blockchain-based copyright distribution platforms can solve problems which have been articulated on prior internet social networks: increased market dominance of platform business because of centralization with no reward to creators who upload on platforms, and lack of fairness, such as unfair profit distribution between the copyright holder and businesses. With this background, the current research confirmed the factors that affect the intention of usage and behaviors, targeting potential users of blockchain-based copyright distribution platforms. Research design, data, and methodology - Centered around the UTAUT2 Model, the research model was designed with 'Perceived Security' added as Construct, and 'Age' and 'Knowledge Level' added as moderating variables. For data, 607 responses were collected by an online survey, and 601 responses were included in the final analysis. We analyzed the research model and sample by using SPSS 23.0 and AMOS 23.0 on the collected responses. Results - First, results of research on whether Constructs make positive effects on Intention of use is: social influence, facilitating conditions, habit, and perceived security had positive effects on intention of use, and performance expectancy, effort expectancy, hedonic motivation, and economic value did not. Second, results of the research on whether facilitating condition, habit, and intention of use made an impact on using behaviors, it was shown that only habit and intention of use made positive effects. Third, in two groups divided by age above or under 40, group effort expectancy, intention of use, habit, and intention of use had controlling effects, and facilitating condition, intention of use, perceived security, and intention of use had effects in both groups. Conclusions - The research shows that no matter how great a blockchain-based platform is, if advantages of blockchain are not proved in various industries and utilized in real life like the internet, blockchain-based distribution systems will develop slowly. Rather than a short-term inducement emphasizing technology, there is a need for a strategic approach that can foster the environment.

• 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.