• The Journal of Industrial Distribution & Business
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• v.12 no.1
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• pp.15-30
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• 2021

Purpose: Year of 2020, COVID-19 has been changing the people's everyday life to ways never been thought of before all over the world. The IT and electronic industry, the methods of supplying goods and services have been changed from contact to un-tact environments based on un-tact systems very rapidly. COVID-19 has been striking the tourism and the travel industry, especially the airline and hotel industry of which services are provided by human. For the passenger service of airliner, automation has been propelled and un-tact style of service has become mainstreams except cabin service since 2000's. For passenger transportation, due to traffic regulations and exclusions etc., switching to new ways is not easy. However, under the new environment made by COVID-19, kiosk check-in, web check-in and mobile check-in has become more important. In this study, the characteristics of airline customers using mobile goods are investigated to find ways to raise the rate of utilizing mobile check-in and to increase the efficiency of boarding process. Research design, data, and methodology: Considering the COVID-19 environment, survey was done by online research company. The research model is designed to integrate the user characteristics and usage/purchase motive and technology acceptance theory. Especially considering infectious diseases prevention, concern of safety is adopted as one of the usage motive variable. Results: Extraversion or conscientiousness characteristics prefers counter check-in(contact service), while openness characteristics prefers mobile check-in(un-tact service). Concern of safety for infectious disease shows strong non-preference on counter check-in. Conclusions: Regarding service type regardless of type of the industry, automation and un-tact have been mainstreams due to high costs of labor, efficiency and standardization issue, etc., and COVID-19 has given impetus to them. For airliner, un-tact service including boarding process service has been more and more important. To raise the rate of un-tact service use, the characteristics of the user should be analyzed first. The study results indicate that for extraversion or conscientiousness, some kinds of methods to induce them to use un-tact service more are needed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1539-1545
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• 2020

With the advent of the ubiquitous era due to the development of science and technology in the modern society, interest in data generated in the IoT environment has increased socially. However, the existing IoT platform has difficulties in processing inquiry requests that require large amounts of throughput, such as statistical processing of large amounts of data. Accordingly, in this paper, we propose an IoT platform that can flexibly accommodate requirements for inquiry requests and improve inquiry performance. The platform proposed in this paper showed a performance improvement of about 1200 times in terms of average response time by introducing a separate read database. By separating the object model into a command side and a query side, the complexity of the object is reduced to meet the various demands on the platform. It was made to allow quick acceptance of the matter.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1238-1247
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• 2022

The e-commerce market is growing faster as demand for non-face-to-face shopping increases due to COVID-19. These changes lead to the expansion of various opportunities for consumers, but companies are required to understand consumer characteristics and reflect them in their sales strategies so that they can be competitive in the market. This study examined how the perceived ease and utility of consumers affect the intention to use the platform according to the technology acceptance model (TAM). As a result, it was confirmed that the price competitiveness, awareness, and ease of use of the platform had a significant effect on the utility. In addition, it was confirmed that there was no moderating effect of user characteristics on the effect of ease of use on the platform intention. These results present important implications for a company's sales strategy, and in future studies, it is necessary to expand the study in consideration of more diverse variables.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.217-225
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• 2023

The willingness of online music users to pay is the key to the protection of music copyright and the sustainable development of the industry. This paper aims to study the influencing factors of online music users' willingness to pay based on exploratory analysis. Based on the theory of customer perceived value, the unified theory of technology acceptance and use, and the theory of fan enthusiasm, the research model is constructed. Validate the obtained 583 valid data. Through analysis, I got that perceived value, interpersonal influence, fan enthusiasm, and personal payment awareness directly affect online music users' willingness to pay; practical value and hedonic value have a positive impact on perceived value, and the impact of economic cost and compilation cost has not reached a significant level; Online word-of-mouth negatively moderates the impact of perceived value on users' willingness to pay for music. Music platforms can formulate operating policies based on this.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.2
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• pp.127-137
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• 2010

A Widget platform is acknowledged to be a next generation intelligent platform that is well suited to Web 2.0 and mobile convergence environments. With prospects of growth, examining users' perceptions of current widgets can be a valuable source of information in setting directions for Widget's future development. This study identifies user interface factors that affect widget usability and investigates a strategic approach to promoting the use of widgets by analyzing user's "intention to use" in connection with the identified interface factors. The experimental results show the consistency, intuition, minimal action, and personalization have a positive(+) effect on perceived ease of use and that personalization and design have a causal effect on perceived enjoyment. Inaddition, perceived ease of use has an influence on perceived enjoyment that, inturn, has a direct influence on intention to use. On the other hand, the hypothesis that perceived ease of use has a direct effect on intention to use was rejected.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.3
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• pp.203-211
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• 2023

A Markov chain Monte Carlo (MCMC) simulation is proposed for probabilistic full waveform inversion (FWI) in a layered half-space. Dynamic responses on the half-space surface are estimated using the thin-layer method when a harmonic vertical force is applied. Subsequently, a posterior probability distribution function and the corresponding objective function are formulated to minimize the difference between estimations and observed data as well as that of model parameters from prior information. Based on the gradient of the objective function, a proposal distribution and an acceptance probability for MCMC samples are proposed. The proposed MCMC simulation is applied to several layered half-space examples. It is demonstrated that the proposed MCMC simulation for probabilistic FWI can estimate probabilistic material properties such as the shear-wave velocities of a layered half-space.

• 한국노년학
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• v.39 no.1
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• pp.109-125
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• 2019

This study examined factors that prevent older adults from using computers and/or smartphones for their health information search and health management. This study conducted face-to-face survey of a total of 240 older adults aged over 65. Based on the responses of open-ended questions, this study conducted semantic network analysis. The results showed that low level of perceived usefulness(PU) (e.g., information I want to find, detailed information, and trustworthiness) and perceived ease of use(PEOU) (e.g., how to search for information, how to install applications, and visibility) are main factors that prevent older adults from using computers and/or smartphones for their health information search and health management. Furthermore, based on the results of semantic network analysis, further hierarchical regression analysis confirmed that PU and PEOU were positively associated with intention to use mobile application. Thus, the results imply that increasing older adults' PU and PEOU can promote their intention to use mobile application.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.371-382
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• 2024

This study explored the factors affecting the intention to use ChatGPT for adult men and women. The results are summarized and presented based on the hypothesis as follows. First, perceived ease of use had a positive effect on perceived usefulness. Second, information reliability did not have a significant effect on perceived usefulness. Third, information quickness had a positive effect on perceived usefulness. Fourth, perceived ease of use had a positive effect on user satisfaction. Fifth, perceived usefulness had a positive effect on user satisfaction. Sixth, information reliability did not have a significant effect on user satisfaction. Seventh, information quickness had a positive effect on user satisfaction. Eighth, user satisfaction had a positive effect on the intention to use.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.87-99
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• 2024

This study aims to identify the competencies required for webtoon artists to survive in the future era of AI commercialization. It explores the current and future use of AI in webtoons, and predicts the role of artists in the future webtoon industry. The study finds that AI will replace human workers in some areas, but human empathy-related fields can be sustained. Artist roles like story projectors, Visual directors, and AI editors were identified as potential models for the changing role of artists. To address terminology ambiguity, a three-step AI categorization mechanical type AI, humanoid type AI, and transcendent type AI was proposed for a more realistic separation of AI capabilities. The researcher suggested these findings as guidelines for developing skills in emerging artists or re-skilling existing ones, emphasizing collaboration with AI for mutual growth rather than a negative acceptance of new technology.

• 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.