• 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.

• Journal of Information Technology Applications and Management
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• v.18 no.2
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• pp.61-89
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• 2011

Blog is a new global phenomenon, but many research papers about organizational blog have not been shown. In this study the influencing factors of the organizational blog usage are empirically investigated, and several guidelines are suggested to IT professionals who involves the design and implementation of the organizational blog. The research model consists of seven independent variables, one dependent variable, and two moderating variables. The following variables are established as the independent variables; information, interface, service, communication, enjoy, performance expectation, and social influence. Two dimensions such as need and orientation are suggested for the moderating variables, and the actual usage is adopted as a dependent variable. As a result of multiple regression analysis using a stepwise method, the independent variables except for interface and communication affect the actual usage of organizational blogs. The moderating effects for need and orientation are partially supported. The implications of this study are as the followings; (1) The empirical factors affecting the usage of organizational blogs are empirically investigated, (2) The affecting factors vary according to the type of organizational blogs, and (3) Some guidelines are suggested for organizational blog's design.

• Journal of Distribution Science
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• v.17 no.7
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• pp.15-25
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• 2019

Purpose - e-Commerce is now one of the alternatives in shopping. Ease of Use and convenience aspects are the main supporting reasons that e-commerce is a trend for most people today. This study examines the relationship between the theory of technology to consumer behavior in using e-commerce applications. Research design, data, and methodology - The number of samples in this study was 600 samples from four major e-commerce made in Indonesia. The research method of this study Structural Equation Model (SEM) with AMOS and SPSS applications as analysis tools. Results - The results of this study state that most hypotheses support prior research and grand theory. On the other hand, the components of technology acceptance theory are mostly able to moderate variable consumer behavior in the digital era. Conclusions - The combination of essential elements of technology theory are oriented to the fundamental aspects of human beings as social beings. The most important thing for the development of the e-commerce industry to develop and be sustainable is the obligation to increase consumer confidence. The combination of components of technology theory and CCT can be a comprehensive marketing strategy and innovation to competitive advantage in the future.

• The Journal of Information Systems
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• v.26 no.4
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• pp.303-325
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• 2017

Purpose The purpose of this study is to forage for the factors for explaining the adoption behavior of the mobile convenient payment system based on the Personality Trait, Unified Theory of Acceptance and Use of Technology, and Regulatory focus. Design/methodology/approach This study made a design of the research model by integrating the factors of Unified Theory of Acceptance and Use of Technology with the factors of Big five personality traits on the basis of Samrt device environment. In addition, this study, did empirical analysis of the structural equation model by PLS(Partial Least Squares) in order to find out the relationship of personal factors and mobile convenient payment system's features. Findings According to the empirical analysis result, this study confirmed that the acceptance of mobile convenient payment systems is influence by personality traits and factors based on Unified Theory of Acceptance and Use of Technology and trust. In addition, this study find out that the behavior of an adoption of mobile convenient payment systems according to the type of regulatory focus.

• Journal of Information Technology Applications and Management
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• v.19 no.3
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• pp.31-47
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• 2012

As the dependence on information is increasing, the protection of personal information (PI) becomes a critical issue for the organizations, causing not only financial loss but also negative impacts on corporate images and reputations. To date, academic research in this area is scarce. This study analyzes the factors affecting the establishment and/or implementation of Personal Information Management System (PIMS) and provides direction for the practice. In this study, we assume that PIMS is one of the new technology adopted by organizations, and Unified Theory of Acceptance and Use of Technology (UTAUT) model is selected as a base model for the study. Using structural equation modeling technique, both measurement and structural models are validated, and hypotheses are tested. Major findings of the study include (1) the major driver of the organizations attempting to adopt PIMS seems to be the improvement of the business outcomes, (2) organizational capability and resource are important in the establishment of PIMS, and (3) the perceived difficulty of the establishment of PIMS is not affecting the intention to adopt PIMS. Since the importance of personal information security is high, establishment of PIMS is becoming one of the critical issues in the organizations. The establishment of PIMS should be encouraged to strengthen the competitiveness of businesses and to enhance the security level of the entire nation. It is expected that this study may contribute to developing plans and policies for establishment of PIMS in practice, and to providing a foundation for further research in this area.