• Journal of the Korea Society of Computer and Information
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• v.24 no.10
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• pp.101-116
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• 2019

In this paper, we propose a novel behavioral model that explains the use of the military battlefield management system more effectively in the non-voluntary use environment. This study intends to suggest a model based on the Unified Theory of Acceptance and Use of Technology(UTAUT), an extended TAM. Also, it introduces the concept of 'Conative IS use' as a dependent variable that can explain user's behavior more effectively in non-voluntary technology acceptance environment. In addition, we propose the major factors affecting the UTAUT components from the TOE(Technology-Organization-Environment) perspectives, and analyze their effects. In order to validate the proposed model, this study applies PLS(Partial Least Squares) to the survey collected from military personnel. The findings of our study may shed a light on improving the effectiveness of battlefield management information system.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.1
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• pp.11-21
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• 2017

Internet Banking Offers Major Advantages for Both Banks and Customers. However, Not All People have equal Access or Skills to use such Services. The Main Objective of this Study is to Understand the Fctors Influencing Internet Banking Usage we Developed a Research Model Drawing from the UTAUT and Digital Divide Research. The Model was Tested and find more than 90% of Variance of Internet Banking Usage was Explained by the Model. Results Demonstrate that the Strongest Factor Influencing the Intention to adopt Internet Banking Services is the Degree to which an Individual Believes that it is Safe to use such Services. In the Paper, all the Hypotheses Except for the Hypothesis on the Effort Expectation are Accepted with Statistical Significance.

• Journal of Service Research and Studies
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• v.13 no.2
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• pp.99-113
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• 2023

In a customer-based industry, customer retention is the competitiveness of a company, and improving customer retention improves the competitiveness of the company. Therefore, accurate prediction and management of potential dormant customers is paramount to increasing the competitiveness of the enterprise. In particular, there are numerous competitors in the domestic card industry, and the government is introducing an automatic closing system for dormant card management. As a result of these social changes, the card industry must focus on better predicting and managing potential dormant cards, and better predicting dormant customers is emerging as an important challenge. In this study, the Recurrent Neural Network (RNN) methodology was used to predict potential dormant customers in the card industry, and in particular, Long-Short Term Memory (LSTM) was used to efficiently learn data for a long time. In addition, to redefine the variables needed to predict dormant customers in the card industry, Unified Theory of Technology (UTAUT), an integrated technology acceptance theory, was applied to redefine and group the variables used in the model. As a result, stable model accuracy and F-1 score were obtained, and Hit-Ratio proved that models using LSTM can produce stable results compared to other algorithms. It was also found that there was no moderating effect of demographic information that could occur in UTAUT, which was pointed out in previous studies. Therefore, among variable selection models using UTAUT, dormant customer prediction models using LSTM are proven to have non-biased stable results. This study revealed that there may be academic contributions to the prediction of dormant customers using LSTM algorithms that can learn well from previously untried time series data. In addition, it is a good example to show that it is possible to respond to customers who are preemptively dormant in terms of customer management because it is predicted at a time difference with the actual dormant capture, and it is expected to contribute greatly to the industry.

• Korean journal of communication and information
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• v.68
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• pp.7-33
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• 2014

Using data from an online survey in Korea, this study examines factors affecting college students' intention to use wearable device based on an extended Unified Theory of Acceptance and Use Technology (UTAUT) (UTAUT2 Model). The results of the regression analysis suggest that performance expectancy, social influence, and facilitating conditions from original UTAUT are statistically significant variables to explain college students' intention to use wearable device. Also, the results of the data analysis reveal that added factors from UTAUT2 like hedonic motivation and price value are influential factors to explain intention to use wearable device. In addition, this study suggests that future studies need to test the UTAUT2 model in the context of new information and communication technologies.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.32 no.1
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• pp.49-60
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• 2024

This study used the Unified Theory of Acceptance and Use of Technology(UTAUT) model to find factors that influence consumer acceptance intention toward Vertiport, a physical ground support technology required to implement AAM services. The analysis showed that among the four independent variables, Vertiport's social influence and facilitating conditions have a significant impact on future Vertiport usage behavior. At this point, the public has not yet had actual experience with Vertiport, so there is a limitation of considering it as a future concept based on speculation and measuring acceptance by actual behaviors related to its use (inquiries, information gathering, interest, etc.). Research on acceptance and attitudes toward new transportation methods should be further activated and developed along with future service development. Through the results of this study, we aim to understand the initial public acceptance of Vertiport as a ground-based infrastructure in the AAM field (or UAM) and propose strategic implications for the direction of service development.

• Journal of Information Technology Applications and Management
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• v.23 no.2
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• pp.153-176
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• 2016

This study investigated factors affecting the use intention of podcast service users based on the unified theory of acceptance and use of technology (UTAUT). Performance expectancy, effort expectancy, social influence, facilitating condition, hedonic motivation, innovativeness, and media credibility were used as independent variables in the model. The survey data from the users of the podcast portal 'podbbang' were analyzed with Smart PLS 2.0 to test the structural equation model. The results revealed that the podcast service user's effort expectancy, facilitating condition, hedonic motivation, and media credibility have a significant influence on use intention. However, the relationship between the podcast service user's performance expectancy, social influence, innovativeness, and use intention were not identified as significant.

• The Journal of Korean Association of Computer Education
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• v.17 no.5
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• pp.35-42
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• 2014

This study utilized an analysis of teachers' use of smart devices in the class, which highlighted the impact factors, and elucidated the relationship between in fluencing factors. The Unified theory of Acceptance and Use of Technology (UTAUT) model is based on the study of extension and modification of the model proposed. For the study, a survey of 1,016 elementary school teachers in the Gangwon and Metropolitan(Seoul, Gyeonggi, Incheon) area was conducted. Was applied using the AMOS structural equation modeling analysis. The analysis examines the utilization of smart devices in class as factors affecting performance expectancy, effort expectancy of the main variables showed, Instant connectivity and Openness that has a direct impact on the performance expectations and effort expectancy.

• The Journal of Information Systems
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• v.24 no.2
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• pp.23-52
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• 2015

Purpose This study aims to understand the role of digital knowledge in accepting the green technology. This study combined digital option theory with the second version of the Unified Theory of Acceptance and Use of Technology (UTAUT2). Contrary to other studies in which the UTAUT2 is used to explain IT adoption behavior, we look at the relationship between IT and the UTAUT2 from a new angle, incorporating an important aspect of IT, that is, digitized knowledge richness, as a determinant of the UTAUT2. Design/methodology/approach Grounded in the UTAUT2, a content analysis was conducted to investigate novel constructs dedicated to explaining green technology adoption. In this study, an amended version of the UTAUT2 specific to green technology is offered that better explains the green technology adoption behavior of consumers. Using the items identified by content analysis, we developed a questionnaire with 36 survey items. We measured all the items on a seven-point Likert-type scale. We randomly selected 402 survey respondents from a set of panel data. After a pilot study, we analyzed the main survey data by using PLS 2.0M3 and SPSS 20.0, and employed structural equation modeling to test the hypotheses. Findings The results suggest that the UTAUT2 was found to be extendable to technologies other than conventional IT. Social influence is more significant than conventional utilitarian and hedonic-based constructs such as those utilized in the UTAUT and UTAUT2 in explaining adoption behavior in the context of green technologies. The hypothesized connection between digitized knowledge richness and adoption intention was supported by the results of studies on the role of IT in formation of attitudes toward eco-friendly production. The results also indicate that digital knowledge can also encourage people to try green technology when they learn that their peers are already using the technology successfully.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1717-1726
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• 2018

This study is for looking into Factors affecting the Intention of using about Fitness Tracker based on IoT by Flow Theory and UTAUT Model. The independent variables of the IoT-based fitness tracker have been selected as Challenge, Skill Factors used in the Flow experience theory and selected the personal characteristics of health perception, enjoyment, Social Influence, and Facilitating Conditions. In addition UTAUT theory was used as parameter of Performance Expectancy and Effort Expectancy and intention of Use behavior was selected as a dependent variable. For verifying research hypothesis, This study collected 126 surveys data and carried out a statistical analysis by Smart PLS. The result shows that new Flow Experience and Personal Characteristic Factors with key variables in the UTAUT Model affect significantly to Intention of using about Fitness Wearable environment based IoT.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.85-93
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• 2021

The government is pursuing plans to create new e-government services. In terms of improving business procedures, dBrain (finance), e-people (personnel), and Onnara (electronic payment and business management) have achieved considerable results, and are currently making efforts to improve existing administrative services using newly emerged ICT. Among them, this paper attempted to study whether self-learning-based intelligent administrative services are efficient in the work process of public officials promoting actual work and affect their continued use. Based on individual perceptions and attitudes toward advanced ICTs such as AI, big data, and blockchain, public officials' influences on administrative services were identified and verified using UTAUT variables. They believe that the establishment and introduction of innovative administrative services can be used more efficiently, and they have high expectations for the use and provision of services as ICT develops. In the future, a model will be also applied to citizens