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This study examines Korean users’ attitudes and emotions toward Melon and Spotify, which lead the music streaming market. We used Text Mining, Semantic Network Analysis, TF-IDF, Centrality, CONCOR, and Word2Vec analysis. As a result of the study, MelOn was used in a user’s daily life. Based on Melon’s advantages of providing various contents, the advantage is judged to have considerable competitiveness beyond the limits of the streaming app. However, the MelOn users had negative emotions such as anger, repulsion, and pressure. On the contrary, in the case of Spotify, users were highly interested in the music content. In particular, interest in foreign music was high, and users were also interested in stock investment. In addition, positive emotions such as interest and pleasure were higher than MelOn users, which could be interpreted as providing attractive services to Korean users. While previous studies have mainly focused on technical or personal factors, this study focuses on consumer reactions (online reviews) according to corporate strategies, and this point is the differentiation from others.

Scooters are a popular way to get around on your own in many places, such as Taiwan, India, Thailand, etc., because they are easy to move around in, small, and cheaper to buy than cars. On the other hand, traditional scooters that run on fossil fuels put some pollution into the air and add to problems like global warming and air pollution. Switching from scooters that run on fossil fuels to electric scooters can help clean up the air in cities with much pollution. To promote the use of electric scooters, it’s important to know how consumers feel about them. The current study investigates consumers’ purchase intentions for electric scooters. Based on the questionnaire survey results (n = 567), we found that consumers’ environmental concerns, price consciousness, and perceived subjective norms are associated with electric scooter purchase intention. Consumers with price consciousness may choose fossil-fuel-powered scooters because they consider electric-powered scooters more costly, although environmentally friendly. The study gives researchers and practitioners a glimpse into consumers’ environmental concerns and subjective norms for a sustainable product.

This paper aims to analyse the factors influencing the implementation of smart factories and their performance after implementation, using the grounded theory analysis method based on interview data. The research subjects were 21 companies that were selected by the Smart Manufacturing Innovation Promotion Group under the SME Technology Information Promotion Agency in 2020-2021 as the best case smart factory implementation companies, and introduced the intermediate stage 1 or above. A total of 87 concepts were generated as a result of the analysis. We were able to classify them into 16 detailed categories, and finally derived six broad categories. These six categories are “motivation for adoption”, “adoption context”, “adoption level”, “technology adoption”, “usage effect” and “management effect”. As a result of the overall structure analysis, it was found that the adoption level of smart factory is determined by the adoption motivation, the IT technology experience affects the adoption level, the adoption level determines the usage and usage satisfaction, internal and external training affects the usage and usage satisfaction, and the performance or results obtained by the usage and usage are reduced defect rate, improved delivery rate and improved productivity. This study was able to derive detailed variables of environmental factors and technical characteristics that affect the adoption of smart factories, and explore the effects on the usage effects and management effects according to the level of adoption. Through this study, it is possible to suggest the direction of adoption according to the characteristics of SMEs that want to adopt smart factories.

The present research aims to examine whether learning from the supervisor influences readiness for change with the mediating impact of planfulness. Drawing upon the theory of planned behavior, it is hypothesized that learning from the supervisor positively impacts planfulness ability in individuals, which in turn enhances the readiness for change. Through using convenience sampling, the sample of 451 was collected from employees working full-time in the manufacturing and I.T. service organizations in India. Structural equation modeling and regression analysis indicate that learning from the supervisor is positively associated with readiness for change and planfulness. Additionally, planfulness fully mediated the relationship between learning from the supervisor and readiness to change. The findings of the present research highlight that continuous support and learning from the supervisor enhances the planfulness ability of the individual and consequently enhances individual readiness for change. The current research is pioneering in testing the hypothetical model associating learning from the supervisor, planfulness, and readiness for change.

The purpose of this study was to investigate the impact of investment fund attributes such as fund product characteristics, returns on fund investment (ROI), internal controls, and after service on fund investor behavior based on investment information technology. In addition, we also examined how customers reinvest through emotional immersion, company trust and company satisfaction of investment firms in the context of fund investment. First, empirical results show that fund product characteristics, returns on fund investment, and financial firms’ internal controls and after service act as signals to fund investors to shape their reinvestment intentions. Second, while investors are generally perceived to be interested only in investment returns, this study also shows that they consider both fund product characteristics and fund investment returns, which are core attributes of funds, as well as financial firms’ internal control and after service, which are non-core attributes. Third, we find that company trust is an important factor in investors’ reinvestment intentions, showing that investors are more likely to reinvest in a fund if they perceive the financial firm to be trustworthy and reliable. Finally, these findings emphasize that investors consider not only tangible aspects of fund products, such as fund product characteristics and returns on fund investment, but also intangible factors, such as financial firms’ internal control and after service, and trustworthiness. Taken together, another implication is that the more advanced the investment information technology of financial firms, the more trust, satisfaction, immersion, and reinvestment intentions of investors will increase.

In this study, we investigate the changes and realities of the content production process focusing on Image generation AI revolutions such as Stable Diffusion, Midjourney, and DELL-E, and examine the current status of related department operations at universities and Find out the status of the current curriculum. Through this, we suggest the need to produce AI-adaptive content talent through re-establishing the capabilities of content-related departments in art universities and quickly introducing curriculum. This is because it can be input into the efficient AI content development system currently being applied in industrial fields, and it is necessary to cultivate talent who can perform managerial and technical roles using various AI systems in the future. In conclusion, we will prepare cornerstone research to establish the university’s status as a source of talent that can lead the content industry beyond the AI content production era, and focus on convergence capabilities and experience with the goal of producing convergence talent to cultivate AI adaptive content talent, suggests the direction of curriculum application for value creation.

This study tried to identify factors affecting online activity before and after the COVID-19 pandemic. To this end, the effects of consumer innovativeness, self-esteem, and need for cognition on the activity of online media such as Internet and social media were investigated, and whether privacy concerns had a moderating effect. For this study, survey data from 2019(before the outbreak of COVID-19) to 2021(after the outbreak of COVID-19) of the ’Korea Media Panel Survey’ surveyed by the Korea Information Society Development Institute was used for analysis. The research results that affect Internet activity are as follows. Before the outback of COVID-19, it was found that hedonic innovativeness and social innovativeness had a positive effect and cognitive innovativeness had a negative effect on increasing Internet activity. There was no moderating effect on privacy concerns. The period after the outbreak of COVID-19, need for cognition was found to have a positive effect on increasing social media activity. In addition, the moderating effect of privacy concerns was found in the relationship between need for cognition and Internet activity. There was no privacy concern effect before the outbreak of COVID-19, and the privacy concern effect appeared on functional innovation and need for cognition after the outbreak of COVID-19. This study aims to present various implications for companies to understand the characteristics of online consumers using the Internet and social media after the pandemic.

In the field of animation, as technology advances, production technology, production methods, and production culture are also steadily developing. The demand for content is increasing rapidly around the OTT platform, and the demand for animation content and diversity is increasing. With these market changes, animation creation ability is becoming a more important animation education goal. There is also a need to innovate educational methods to provide students with the skills and knowledge required in the modern animation business. This paper investigated the composition of the educational curriculum of domestic and foreign animation universities education. It examines artificial intelligence (AI) technology that can be used in animation creation and explores the design and direction of the university animation curriculum using it. AI technology has already proven its potential in various areas, and it is integrated into the animation curriculum to present various development potentials. Using AI technology, students can focus on practical and essential animation education by preventing technical difficulties in animation creation, increase their experience in animation production, and experiment with planning and producing various contents. It is proposed to design an educational curriculum that further strengthens animation creation and production capabilities by forming smart animation classes to foster talents who can lead the future animation industry in a new direction.

Due to technological advancements, the data industry is growing, leading to a demand for data professionals in the market. Job seekers interested in data-related positions include not only those with relevant majors but also non-majors. Therefore, this study aims to identify effective educational methods for non-majors lacking data knowledge and skills to develop both data and business competencies. This research focuses on 28 trainees who participated in the “Data Youth Campus” program conducted by K-institution. The program spanned 10 weeks and was structured into three phases: fundamentals, practical training, and projects, systematically enhancing trainees' capabilities. The effectiveness of the curriculum and trainee management was verified by measuring and analyzing improvement of competencies and satisfaction with the program. This study offers valuable insights for the design and implementation of data education programs tailored to non-majors.