• The Journal of the Korea Contents Association
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• v.14 no.9
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• pp.538-555
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• 2014

Systematic studies have been rarely conducted on the acceptance of big data technology despite the technology drawing much attention from academia, industry and general public. With big data technology still being in the infant stage in Korea, a study model was constructed in this paper by integrating the innovation diffusion theory and the task technology fit theory with this technology acceptance model (TAM) as the central framework to make big data technology more readily acceptable in the country, and the aim of making big data technology readily acceptable was expanded as the moderator variable of the TAM. The results of this study showed that "subjective norm" and "task technology fit" showed the most significant effect as the exogenous variables of the TAM. In addition, the "innovative characteristic of the organization" was the significant exogenous variable affecting the intention to accept big data technology to those "technology utilizers" that try to come up with new services or products that are technology-based; however, "subjective norm" was the rather significant factor affecting those simple "technology users". Finally, a significant difference was seen in the verification of mediation effect.

• Journal of Digital Convergence
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• v.12 no.2
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• pp.577-586
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• 2014

As SNS has increased its influence on the society as a whole, companies also have started to consider how to take advantage of the new service paying specific attention to its characteristics of immediacy, sharability and interactivity. This study aims to circumstantiate the relationship between a task support tool of SNS and task-media fit, user characteristics and performance by focusing on its usage in work field. To address this issue, a Task-Technology Fit model is used to propose a research model considering the characteristics of SNS as a social element, information technology as well as its user characteristics. The outcome shows that job characteristics, virtual competence and media characteristics have a significant influence on task-media fit, whereas virtual competence and SNS characteristics variables have a significant influence on SNS usage. Besides, task-media fit has a significant influence on SNS usage and work performance while SNS usage has a significant influence on work performance. The study suggests that strategic use of SNS helps improve work performance and these individual characteristics should be considered in planning of SNS utilizing strategy.

• Journal of Fashion Business
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• v.16 no.4
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• pp.46-63
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• 2012

This research purposed to the conceptual model with integrates the expanded task technology fit theory(TTF) and technical acceptance model(TAM) for the effect of the motivational factor of the consumer characteristics in the used the fashion mobile commerce. To fulfill the study objectives, a total of 432 questionnaires were conducted to the customers with first-hand experience with merchandise in mobile commerce. The judgement sampling method was employed on sample population ages from 20s to 30s over two month period. Based on the results of the above-mentioned path analysis, The result showed that First, the utilization experience was adopted as the have the notes effect in the and information acquisition fit, support fit, quality fit, perceived ease of use. and the innovativeness was adopted as the have the notes effect in the information support fit, perceived trust, perceived ease of use. and the self-efficacy was adopted as the have the notes effect in the and information quality fit, perceived usefulness, perceived ease of use. Second, the information acquisition fit, support fit were adopted as the have the notes effect in the perceived trust, perceived usefulness, perceived ease of use. and the information quality fit was adopted as the have the notes effect in the perceived trust, perceived usefulness. Third, the appeared similar effect which considers from all relationships such as perceived trust, perceived usefulness, perceived ease of use, acceptance attitude and purchase intention.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.631-635
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• 2015

Construction managers use scheduling methods to improve the outcome of their project. In spite of the many obvious advantages of the critical path method (CPM), its use in construction has been limited. Understanding the reasons why CPM is not used as extensively as expected could improve its level of acceptance in the construction industry. The link between construction scheduling methods and the capabilities of the scheduling staff has been an on-going concern in the construction industry. This study proposes a staffing-technology fit model to understand why CPM is not used as extensively as expected in construction scheduling. A staffing-technology fit model that aims to measure the extent to which a construction scheduling method matches the staff's experience, know-how and capabilities. The model that is proposed is an answer to the lack of proper instruments for evaluating the extent to which scheduling methods are used in the industry.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.2
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• pp.644-654
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• 2013

It is required for enterprises to construct the proper information management system in order to cope with the volatile business situations. The mobile office system is introduced from the needs to provide organization members smart information and mobility. By setting the model, hence, we intend to scrutinize the impact of the task-technology fit model and organizational characteristics of the mobile office system on the job performance. As a result, system quality, information quality and mobility are revealed to affect positively the task-technology fitness and the fitness also affects the job performance positively. Organization characteristics affects the job performance positively through the task-technology fitness, too. Therefore the organization which plans to introduce the mobile office system should consider the task-technology fitness and exert organizational-level efforts to adopt and use the mobile office system in the workplace.

• Journal of Information Technology Services
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• v.17 no.4
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• pp.1-19
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• 2018

Effective internal communication is known to have a positive impact on business performance, but there is a lack of research on the effects of online channels for workplace communication. This study using regression analysis examines how task-technology fit, information richness, self-efficacy, perceived ease of use, and perceived usefulness related to online communication channels affect not only the satisfaction with the tools but also the effectiveness of them. Additionally, we verify how the organizational culture of online and offline communication shows the control effect. As a result, all five variables were positively correlated with internal communication channels satisfaction, and we found that the organizational culture of online and offline communication controls the relationship between online communication channels satisfaction and effectiveness.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3992-4005
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• 2018

In our current information-based society in which knowledge is a fundamental asset to production, the capability to utilize information and produce knowledge with the use of information technology (IT) has become essential to learning. Massive Open Online Courses (MOOCs) have recently been introduced in light of such changes and are recognized as an alternative to open education. MOOCs' capabilities are being acknowledged in lifelong education in terms of reeducation and knowledge sharing, and also in terms of improving teaching quality, and improving university students' levels of creativity and integrated thinking by supporting high-level content and teaching. Therefore, this study presents an extended research model that combines information system (IS) continuance and task-technology fit models. Our study researches previous literature, revealing factors of continuous use after accepting MOOCs from the learner's perspective, and analyzes the model empirically. The ideal environment for MOOCs learners is evaluated, and a strategic approach to the successful settlement and diffusion of MOOCs is presented based on this study's findings.

• Journal of Distribution Science
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• v.18 no.1
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• pp.107-121
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• 2020

Purpose: Shared mobility services are the most notable in the shared economy; however, they have yet to be activated in Korea due to various regulations and conflicts amongst stakeholders. Nevertheless, shared mobility has become an irresistible trend of the times, as it can cause a great deal of economic and environmental benefits. In this vein, the purpose of this study is to contribute to the revitalization of shared mobility services in Korea and to provide service providers with implications for developing consumer-oriented marketing strategies. Research design, data and methodology: Based on the reasons that the users do not use shared mobility service, the factors influencing the behaviors of shared mobility users are structured and analyzed in a reliable, technical and procedural manner. To this end, the theory of reasoned action (TRA) of Ajzen and Fisbbein, the initial trust model (ITM), task technology fit (TTF) and switching cost (SC) are adopted. A total of 202 questionnaires were collected from the respondents who were aware of shared mobility. Then statistical processing of the collected data used SmartPLS(v.3.2.8), a PLS-SEM (Partial Least Squares Structural Equation Modeling) analysis program. The steps of the analysis are as follows. First, a PLS-Algorithm analysis was performed to evaluate the measurement model, and a Bootstraping and Blindfolding analysis was performed to evaluate the structural model and verify the hypotheses. Second, a multi-group analysis (PLS-MGA) was conducted to further analyze the differences depending on whether or not users experienced shared mobility service. Results: The results showed that initial trusts model (ITM) and task technology fit (TTF) have positive effects on users' behaviors through the mediation of the intention to use. As opposed to the assumption, switching costs did not have negative moderating effects in relation to the intention to use and users' behaviors. The influence of IT self-efficacy was significant, depending on the prior experience to use shared mobility services. Conclusions: This study will contribute to the revitalization of domestic shared mobility services and the formulation of service providers' marketing strategies. In future studies, there is a need to explore, reconstruct, and validate factors other than the impact factors of the shared mobility services used in this research model.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.6
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• pp.61-69
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• 2016

The purpose of this study is to examine the factors influencing usage intention of social network service (SNS) in social enterprise. This model tests various theoretical research hypotheses relating the social enterprise, task-technology fit (TTF), technology acceptance model (TAM), and usage intention of SNS. The data were gathered from 84 questionnaire respondents. Smart partial least square (PLS) 2.0 have been utilized for deriving the study results. The result of hypothesis testing are as follows. First, TTF positively influence perceived usefulness, perceived ease of use, and usage intention of SNS. Second, perceived usefulness positively influence usage intention of SNS. But perceived ease of use does not influence usage intention of SNS. This study will provide theoretical and practical implications of TTF and usage intention of SNS in social enterprise.