• Journal of Digital Convergence
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• v.17 no.9
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• pp.115-126
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• 2019

This study is a survey of people who are return to farming on the intention of accepting ICT convergence technology in agriculture. The research targets were 218 people based on convenience and judgment sampling methods, and the exploratory factor analysis and multiple return analysis were performed with SPSS 22.0. As a result, the independent variables such as performance expectation, effort expectation, and social influence had a positive effect on the acceptance intention of ICT convergence technology in agriculture. In addition, the moderating effects of innovation resistance on these influence relationships were also verified. The limitations of this study are the lack of verification of perception changes and the inability to control variables. As a result of this research, the results of the UTAUT in other fields were confirmed in this study. It is hoped that this study will further facilitate the research of agriculture in ICT convergence technology.

• Journal of Digital Contents Society
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• v.14 no.3
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• pp.291-301
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• 2013

This study is to derive the factors that influence the acceptance of LTE smart phones. Using an extended technology acceptance model to look at the factors affecting the acceptance LTE smart phone. Variables and the LTE features on the personal characteristics variables were chosen based on the study. This study was done through a survey. Surveyed LTE smart phone's primary audience, taking into account the age of 20 were analyzed mainly. LTE smart phone's acceptance factors affecting individual innovation, speed, price factors. When formulating marketing strategies in the future, based on the results of this study, elements that can stimulate innovation and speed, not just an individual's stability, if we estimate that we can derive a more meaningful and effective marketing results.

• Information Systems Review
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• v.23 no.3
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• pp.97-125
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• 2021

Blockchain is a core technology to solve personal information leakage and data management issues, which are limitations of existing Genomic Sequencing services. Due to continuous cost reduction and deregulation, the market size of Genomic Sequencing has been increasing, also the potential of services is expected to increase when Blockchain's security and connectivity are combined. We created our research model by combining the Technology Acceptance Model (TAM) and the Innovation Resistance Theory also analyzed the factors affecting the acceptance intention and innovation resistance of the Blockchain Based Genomic Sequencing Information Platform. A survey was conducted on 150 potential users of Blockchain and Genomic Sequencing services. The analysis was conducted by setting the four Blockchain variables: Security, transparency, availability, and diversity). Also, we set the Perceived Usefulness, Perceived risk, and Perceived Complexity for Technology Acceptance and Innovation Resistance variables and analyzed the effect of the characteristics of the Blockchain on acceptance intention and innovation resistance through these variables. Through this analysis, key variables that need to be considered important to reduce resistance and increase acceptance intention could be identified. This study presents innovation factors that should be considered in companies preparing a new Blockchain Based Genomic Sequencing Information Platform.

• Journal of The Korean Association of Information Education
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• v.18 no.4
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• pp.509-520
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• 2014

This study investigated the structural relationships among factors on intention to use mobile learning and suggests practical strategies to enhance learners' behavior intention in secondary school. In this study, we hypothesized that mobile computing self-efficacy, personal innovativeness, and social influence had positive effects on perceived usefulness and perceived ease of use, which ultimately had positive effects on intention to use mobile learning. In order to examine structural relationship among variables, we surveyed 289 high school students in spring semester of 2014. After collecting data, we examined causal relationship among variables using Structural Equation Modeling. The results of this study are as follows: First, mobile computing self-efficacy and personal innovativeness significantly affected perceived ease of use. Second, mobile computing self-efficacy, social influence, and perceived ease of use significantly affected perceived usefulness. Lastly, perceived usefulness and perceived ease of use significantly affected intention to use mobile learning of high school students.

• Journal of Digital Convergence
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• v.18 no.2
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• pp.57-71
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• 2020

The purpose of this study is to extend Davis's Technology Acceptance Model(TAM) to verify the intention of use fintech factors in which usefulness, easiness, accessibility, affordability, innovation, and uncertainty for middle-aged and older adult. Data was derived from the 2017 Driving and Mobility Survey of Older Adult Korean, which was collected from 457 middle-aged and older adult aged 55 and over in Seoul and Gyeonggi-do Province. Then, structural equation was used to verify the fintech technology acceptance factors of the middle-aged and older adult. The results showed that fintech technology acceptance factors of middle-aged and older adult were verified as usefulness, easiness, innovation, and uncertainty. Namely, the higher usefulness, easiness and innovation resulted in higher the intention to use fintech. Also, the lower the uncertainty resulted in higher the intention to use fintech. This study has implication for fintech, a representative technology of the Aging-Friendly Finance Industry, to identify the technology acceptance factors by expanding the Technology Acceptance Model(TAM) for middle-aged and older adult.

• 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 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.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2013.10a
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• pp.233-246
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• 2013

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2489-2497
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• 2009

The objective of this research is to get the lesson of the policy by searching the factors of technology acceptance focused on u-Health system. For the purpose of this research, this study presented the concept of u-Health and literature review associated with technology acceptance. Also, this research analyzed the factors affecting 'acceptance of u-Health system'. As a result of the analysis, the first factor affecting acceptance of u-health system is 'self-efficacy' and the second factor is 'connecting'. These results showed characteristics of the innovative aspects and the 'anytime and anywhere' in the ubiquitous concept. Therefore, considering these factors when developing with the priority of u-health system will be able to increase the likelihood of business revenue.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.219-226
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• 2012

A study herein is carried out for acceptance procedure of innovative products in the aspect which usage intention is formed by usefulness expectation and rejection factors for innovative products during acceptance procedure of users when information technology innovative products are launched in the market. Empirical study was carried out for non-smart phone users within mobile phone users. As a result of study, firstly, usefulness expectation of users for information technology innovative products is positively (+) affecting to usage intention, while usefulness expectation was shown to be negatively (-) affecting to rejection. Secondly, social factors were found which positively (+) affect to usefulness expectation for innovative products, and satisfaction for conventional products negatively (-) affects to usefulness expectation. Thirdly, there were satisfaction and consuming effort for conventional products from consumers for the factors which affects to innovative products rejection of consumers. Based on the result of study herein, there is a specific strategy needed for information technology innovative products although consumers have expectation usefulness for the products as well as rejection which brings out to remove the intention to use the products.