• Asian Journal of Innovation and Policy
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• v.12 no.1
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• pp.054-074
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• 2023

With the advent of the '4th Industrial Revolution', digitalization using AI (Artificial Intelligence), big data, IoT (Internet of Things), cloud computing and mobile is accelerating across all industries and global companies have fundamentally reorganized customer experiences, business models, and operations centering on digital transformation. Business innovation drives productivity improvement, process simplification, price, competitiveness and sustainable expansion. Whether digital transformation will be necessary for the current industrial environment is no longer important, and how quickly companies achieve digitalization has emerged as the utmost crucial element in industrial continuity. As non-face-to-face and remote technologies have begun in earnest, and accelerated in the pharmaceutical industry. They are looking for ways to provide value, generate profits, improve efficiency, and sustain the future. Compared to other industries, the pharmaceutical-related sectors have shown high interest in digital transformation especially to reduce costs and meet the challenge of delivering products during the pandemic environment.

• Journal of Digital Convergence
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• v.21 no.2
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• pp.27-32
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• 2023

This study is about a marketability analysis and commercialization methodology analysis system using big data, and a marketability analysis and commercialization methodology analysis system that can analyze the marketability of the product based on a content channel capable of viral marketing. The marketability analysis and commercialization methodology analysis system using big data according to this study analyzes the marketability of the products to be analyzed by analyzing the marketing content provided on the content channel, so it has the advantage of determining more accurate viral marketing effects on the products to be analyzed.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.9
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• pp.327-337
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• 2022

The purpose of this study is to determine the direction and significance of variables influencing small and medium enterprises (SMEs) decisions regarding accounting policy in Vietnam. Research data was collected through a survey of 296 subjects, including chief accountants, accountants, managers, and lecturers with practical experience in accounting work at enterprises. With the help of specialized software SPSS, determining the impact of factors on the choice of accounting policy of enterprises is done through a multivariate regression model with control tools Cronbach's alpha determination, EFA factor analysis, and Pearson correlation analysis. Research results show that there are seven factors affecting the choice of accounting policy in Vietnamese SMEs; in which, the factors information technology, legal environment, information demand, manager's awareness, and accounting qualification have a positive impact; and two factors are tax pressure, and financial leverage have a negative impact on accounting policy choice. These results are consistent with most of the previously published studies. However, in contrast to many previous studies, our research shows that accounting's psychological factor does not affect the accounting policy choice. This is consistent with the characteristics of SMEs in Vietnam because the role of accountants is not appreciated in the business.

• Advanced Industrial SCIence
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• v.2 no.1
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• pp.15-20
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• 2023

The purpose of this study is to analyze the changes and importance of welfare policies in Chungcheong Province using big data analysis technology in the era of the Fourth Industrial Revolution, and to propose stable welfare policies for all generations, including the socially underprivileged. Chungcheong-do policy-related big data is coded in Python, and stable government policies are proposed based on the results of visualization analysis. As a result of the study, the keywords of Chungcheong-do government policy were confirmed in the order of region, society, government and support, education, and women, and welfare policy should be strengthened with a focus on improving local health policy and social welfare. For future research direction, it will be necessary to compare overseas cases and make policy proposals on the stable impact of national welfare policies.

• Informatization Policy
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• v.23 no.4
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• pp.3-23
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• 2016

Since Turing (1950) proposed the development of a machine or system that could think and communicate with humans, many engineers and scientists have made endless efforts to create machines and systems that can replace humans. This effort made the field of artificial intelligence. Recently, as many people have been interested in the 4th Industrial Revolution, research on artificial intelligence technology has been actively carried out not only in the university laboratories but also in the companies as the core technology for realizing the 4th Industrial Revolution. As the artificial intelligence technology has been penetrated deeply into our lives, it is true that our lives have become much easier and more comfortable than in the past, but on the other hand, we have begun to have various negative effects. In this study, we review the social changes caused by artificial intelligence in terms of intelligent products and services. By analyzing positive effects and dysfunctions in various cases of daily life and work environment, we try to identify main policy issues.

• Journal of Digital Convergence
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• v.18 no.5
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• pp.75-87
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• 2020

The present study determined new value that can be created through the convergence between artificial intelligence technology (AIT) and all industries by deriving and thoroughly analyzing major issues related to artificial intelligence (AI). This study analyzes domestic articles related to AI using topic modeling method based on LDA algorithm. Keywords were extracted from 3,889 articles of eleven metropolitan newspapers, eight business newspapers and major broadcasting companies; articles were selected by searching for the keyword "artificial intelligence". Keywords were extracted by optimizing the relevance parameter λ to improve the measure of pointwise mutual information (PMI), which shows the association among the keywords of each topic, and topic names were inferred from keywords based on valid evidence. The extracted topics widely showed changes occurring throughout society, economy, industries, culture, and the support policy and vision of the government.

• Journal of Korean Society of Transportation
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• v.9 no.2
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• pp.57-74
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• 1991

Deregulation privatization regionalism and globalization are the specific examples of the recent trends in the world air transport market. As encouraged by the international trends and the domestic policy of promoting market mechanism Korean has been driving a two-airline policy since 1989. But due to the absence of experience and philosophy about the airline co-mpetition both Korean government and the two airlines have been criticized for failing to set fair-competition rules and for struggling to secure air service rights regardless of national interest. Therefore this study shows the costs and benefits of a two-airline policy in a small count-ry reviews the empirical studies about the cost structure of American and Canadian airlines and analyzes the economic consequences of allocating air service rights between two airlines. The policy recommendations are (1) removing government restrictions and expanding ai-rport facilities to develop the domestic market (2) retaining the two-airline policy in the in-ternational market (3) increasing traffic density rather than expanding network for the small airline (4) improving comparative advantage through a global alliance and a technological innovation for the big airline and (5) building an official committee for co-ordinating the two airlines' interests.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.79-90
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• 2024

This study focused on user trust in ChatGPT, a generative AI technology, and explored the factors that affect usage status and intention to continue using, and whether the influence of trust varies depending on the purpose. For this purpose, the survey was conducted targeting people in their 20s and 30s who use ChatGPT the most. The statistical analysis deploying IBM SPSS 27 and SmartPLS 4.0. A structural equation model was formulated on the foundation of Bhattacherjee's Expectation-Confirmation Model (ECM), employing path analysis and Multi-Group Analysis (MGA) for hypothesis validation. The main findings are as follows: Firstly, ChatGPT is mainly used for specific needs or objectives rather than as a daily tool. The majority of users are cognizant of its hallucination effects; however, this did not hinder its use. Secondly, the hypothesis testing indicated that independent variables such as expectation- confirmation, perceived usefulness, and user satisfaction all exert a positive influence on the dependent variable, the intention for continuance intention. Thirdly, the influence of trust varied depending on the user's purpose in utilizing ChatGPT. trust was significant when ChatGPT is used for information retrieval but not for creative purposes. This study will be used to solve reliability problems in the process of introducing generative AI in society and companies in the future and to establish policies and derive improvement measures for successful employment.

• Information Systems Review
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• v.26 no.1
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• pp.19-56
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• 2024

This study is empirical research to enhance understanding of AI (artificial intelligence) training data project in South Korea. It primarily focuses on the various concerns regarding data quality from policy-executing institutions, data construction companies, and organizations utilizing AI training data to develop the most reliable algorithm for society. For academic contribution, this study suggests a theoretical foundation and research model for understanding AI training data quality and its antecedents, as well as the unique data and ethical aspects of AI. For this purpose, this study proposes a research model with important antecedents related to AI training data quality, such as data attribute factors, data building environmental factors, and data type-related factors. The study collects 393 sample data from actual practitioners and personnel from companies building artificial intelligence training data and companies developing artificial intelligence services. Data analysis was conducted through Fuzzy Set Qualitative Comparative Analysis (fsQCA) and Artificial Neural Network analysis (ANN), presenting academic and practical implications related to the quality of AI training data.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.299-308
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• 2021

This study aimed at identifying the significant effects and effectiveness of patients with mild dementia when using personalized reminiscence therapy digital services using AI voice technology. In the process of interpreting the results of stakeholder interviews, the design idea of personal customization using voice AI technology was derived, and prototypes were created and usability tests were conducted in the first and second rounds. The main results are as follows: Since reminiscence therapy itself is highly influenced by personal experience and can receive customized care guides based on treatment status and results through customized treatment programs, the concept of personalization can improve the quality of treatment than existing treatment methods. However, it is expected that the usability of the service will further increase if we study micro-interactions that can prevent errors and increase usability, as issues that may arise due to the forgetting cognitive characteristics of mild dementia patients are observed.