• Journal of Information Technology Services
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• v.18 no.5
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• pp.133-153
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• 2019

The application of mindfulness is increasing in corporation for business innovation. However, the influence of mindfulness has not been confirmed for employee in detail. Mindfulness is the awareness that arises from paying attention in the present. We often experience uncertainty abounds about what the information technology is, how well it works in the process of using information technology. According to the definition of mindfulness, mindfulness can deepen employee's thoughts and understanding of information technology and will provide a clue to the solution of the issue. This study focusses on impact of mindfulness on IT usage behavior, particularly on IT continuance usage. Research question of this study is whether mindfulness impact perceived factors related to IT continuance usage. The study of relationship between IT and mindfulness will have meaningful results because both IT and Mindfulness are aimed at corporate innovation. Based on most recent theory in IT continuance usage, called by Decomposed Expectation-Disconfirmation Model, we established hypotheses and examined the impact of mindfulness on perceived factors in process of IT continuance usage. For empirical analysis, we collected 303 employee samples and conducted Structural Equation Modeling for path analysis. We showed that mindfulness has a positive impact on perceived usefulness, usability and usefulness confirmation, usability confirmation. We also confirmed that antecedent of satisfaction is perceived usefulness, perceived usability and usefulness confirmation, usability confirmation, and satisfaction is the cause of IT continuance usage. We suggested academic and practical implication based on empirical analysis results. In academic perspective, we found the role of mindfulness in process of IT continuance usage. From practical point of view, we suggest to use of mindfulness program for IT continuance usage in corporation.

• Journal of Fashion Business
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• v.22 no.6
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• pp.83-93
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• 2018

The purpose of this research is to investigate the characteristics of big data-based fashion shopping (BDFS) application, perceived usefulness, and expectation confirmation that influence the continuous usage intention of BDFS application users based on the expectation-confirmation model. A survey was conducted with female consumers in their 20s, who are living in Seoul and Incheon area and have used BDFS applications, A total of 182 responses were used for the data analysis. Five hypotheses were proposed, and regression analyses were conducted to test those hypotheses. The results indicated that the users' perceived usefulness increased with the increase of accuracy and personalization characteristics of the app and the expectation confirmation. The result suggested that it is essential to provide accurate information for users to feel useful and to develop the personalized offerings and services which can be the biggest strength of the big-data based mobile fashion store. It was also found that continuous usage intention increases with increased perceived usefulness and expectation confirmation. This result suggests that expectations can play a critical role in perceiving the usefulness of BDFS applications and the user's expectation confirmation also significantly affected the users' continuous usage intention.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.9
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• pp.75-91
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• 2022

This study assesses the Internet banking adoption tendency by existing bank customers of Bangladesh. Currently, almost all the leading banks in the country have implemented Internet banking platforms. However, the active user count remains relatively low and there hasn't been any conclusive research on the drivers and inhibitors of Internet banking. This study evaluates the reasons and quantitatively establishes the factors leading to the adoption and usage continuance of internet banking by existing bank customers. Responses from 460 bank account holders were collected via online questionnaires using a purposive sampling approach, and a core conceptual framework based on Technology Acceptance Model (TAM) and Technology Readiness Index (TRI) was used. The study concluded that internet banking adoption is significantly impacted by the ease of use, customer service, and technology familiarity. Similarly, customer satisfaction is affected by the perceived value and the perceived risk. Through regression analysis, it was found that usage continuance is 89% explained by adoption and customer satisfaction. Multi-group moderation showed significant impact by groups divided based on usage frequency, income level, and age. Perceived risk weakened the impact of perceived value and technology familiarity on usage adoption. Additionally, perceived risk reduced the impact of consumer satisfaction and usage continuance.

• Journal of information and communication convergence engineering
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• v.19 no.3
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• pp.142-147
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• 2021

In this paper, we propose an intelligent research fund management system that applies artificial intelligence technology to an integrated research fund management system. By defining research fund management rules as work rules, a detection model learned using deep learning is designed, through which the disapproval status is presented for each research fund usage history. The disapproval detection system of the RCMS implemented in this study predicts whether the newly registered usage details are recognized or disapproved using an artificial intelligence model designed based on the use of an 8.87 million research fund registered in the RCMS. In addition, the item-detail recommendation system described herein presents the usage details according to the usage history item newly registered by the artificial intelligence model through a correlation between the research cost usage details and the item itself. The accuracy of the recommendation was shown to be 97.21%.

• International Commerce and Information Review
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• v.9 no.1
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• pp.119-148
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• 2007

The purpose of this research is to study whether environments of participating firms of electronic marketplace(e-MP) have an influence on usage factors which are supplying from e-MP and usage factors affect usage performances. Based on the existing researches we found variables and executed a empirical study of environment-usage-performance model. Through this research we suggested useful factors for the performance of trade enterprises. Usage factors of e-MP will overcome geographical limitation and acquire new sales areas and simultaneously widen the relationships of global enterprises. Those firms could be accessible into global market promptly. To enhance usages of e-MP, service quality which can satisfy both buyer and seller at the same time should be strengtened. Finally, the usage of e-trade information should also heighten through usage factors.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.10
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• pp.69-74
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• 2014

With the increasing interest of energy efficiency, several buildings and factories begin to monitor energy usages with a built-in energy management system. However, the built-in energy monitoring system does not reflect the dynamics of buildings and factories energy usage. To overcome the latter, we deploy several sensors to monitor the dynamics of buildings energy usage patterns. In this paper, we are proposing a framework of a sensor based energy monitoring system. Based on our limited experiments, we can monitor power usages by a person, device and time period. As a result, we can plan a better energy usage and improve energy efficiency by the monitored energy usage profile data.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.1
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• pp.88-93
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• 2005

Web usage mining is a research field for searching potentially useful and valuable information from web log file. Web log file is a simple list of pages that users refer. Therefore, it is not easy to analyze user's current interest field from web log file. This paper presents web usage mining method for finding users' current interest based on fuzzy categories. We consider not only how many times a user visits pages but also when he visits. We describe a user's current interest with a fuzzy interest degree to categories. Based on fuzzy categories and fuzzy interest degrees, we also propose a method to cluster users according to their interests for user modeling. For user clustering, we define a category vector space. Experiments show that our method properly reflects the time factor of users' web visiting as well as the users' visit number.

• Journal of the Korean Society of Clothing and Textiles
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• v.39 no.3
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• pp.433-445
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• 2015

This study examines factors that influence consumer behavior regarding the usage intentions and repurchasing behavior of counterfeits. Based on the Theory of Planned Behavior by Ajzen (1991), this study looks at the impact of attitude, subjective norm, perceived behavioral control, as well as the moral norm of consumers about intentions to use and repurchase counterfeits. An online survey was conducted on males and females over the age of 20 with previous experiences of purchasing counterfeits; subsequently, 209 responses were collected and analyzed. The covariance structure model was used to analyze the data in order to measure the factors that influence the usage of counterfeits and repurchasing behavior. The results show that attitude, subjective norm, and perceived behavioral control have significantly positive effects on usage intentions, while moral norm has a significantly negative effect on usage intentions. Usage intentions also have a significantly positive effect on repurchasing behavior and confirmed that usage intentions functions as the mediator. The variables that influence usage intentions are attitude, perceived behavioral control, moral norm, and subjective norm, in descending order. Consumer attitudes towards counterfeits is a major factor that influences usage intentions. Therefore, ethical problems should be emphasized to encourage a negative attitude towards counterfeits. This study identifies an important aspect to show that usage intentions toward counterfeits, and not purchasing intentions, influences repurchasing behavior. Findings are significant in that they reveal the role of the moral norm variable added to the TPB model.

• Informatization Policy
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• v.18 no.3
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• pp.50-68
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• 2011

In this paper, our goal is to examine the factors related to smartphone users' usage addiction. Based on existing literature on mobile usage behavior and addiction, we developed and tested a theoretical model and hypotheses, analyzing how variables based on the characteristics of smartphones affect smartphone usage addiction and how smartphone usage addiction affects social withdrawal. Given the literature review, a questionnaire survey was conducted; and the PLS(Partial Least Square), a kind of SEM(Structural Equation Model), was used to analyze and test the research model and hypotheses. The research results indicated that smartphone users' self-monitoring, loneliness, and smartphone characteristics affect users' usage addiction. Further, smartphone users' usage addiction affects their social withdrawal. Finally, theoretical and practical implications of these findings and directions for future research were discussed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11B
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• pp.1007-1015
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• 2003

In this Paper, we propose a method of determining the price for the elastic traffic in the current or future Internet services. First, we investigate the behavior in the consumption of bandwidth of elastic traffic in IP network. Next, we propose a new method to relate the bandwidth usage with the pricing for the elastic traffic, which is based partially or fully on the usage rate of the network bandwidth. Next, we propose an optimal charging function for elastic traffic, which is applicable to any Internet services. Finally, we will illustrate the implication of the work via simple numerical experiments.