• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.53-60
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• 2022

YouTube realistically shows fake news and biased content based on facts that have not been verified due to low entry barriers and ambiguity in video regulation standards. Therefore, this study aims to analyze the influence of the media and YouTube on individual behavior and their relationship. Data from YouTube and Twitter are randomly imported with selenium, beautiful soup, and Twitter APIs to classify the 31 most frequently mentioned keywords. Based on 31 keywords classified, data were collected from YouTube, Twitter, and Naver News, and positive, negative, and neutral emotions were classified and quantified with NLTK's Natural Language Toolkit (NLTK) Vader model and used as analysis data. As a result of analyzing the correlation of data, it was confirmed that the higher the negative value of news, the more positive content on YouTube, and the positive index of YouTube content is proportional to the positive and negative values on Twitter. As a result of this study, YouTube is not consistent with the emotion index shown in the news due to its secondary processing and affected characteristics. In other words, processed YouTube content intuitively affects Twitter's positive and negative figures, which are channels of communication. The results of this study analyzed that YouTube plays a role in assisting individual discrimination in the current situation where accurate judgment of information has become difficult due to the emergence of yellow media that stimulates people's interests and instincts.

• Korean Journal of Community Nutrition
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• v.20 no.3
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• pp.165-177
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• 2015

Objectives: Based on individual and environmental characteristics of low-income children, we developed a nutrition education program for school-aged children from low-income families according to effective use in social welfare centers. Methods: We conducted in-depth group interviews to assess program needs in 28 participants, 10 low-income school-aged children and 9 of their care givers, 9 social workers and 9 care-givers. Theoretical backgrounds of our program were heath belief model and social cognitive theory considering motivation, action and environment characteristics. Results: Based on the findings of this qualitative study, we developed major program themes and contents. Five selected key themes were 'balanced diet', 'processed food', 'food hygiene and safety', 'Korean healthy traditional diet', and 'family cooking' to induce changes in dietary behaviors. Main findings of in-depth group interviews included 'child's active participation', 'simple and easy to understand messages', and 'environmental constraints' such as a lack of child care at home, limited budget of social welfare centers, and less qualified educators for nutrition and health. Each lesson was constructed as a 1-hour program particularly emphasizing activity-based programs, including cooking and teamwork exercises. Program contents in each session consisted of activities that could induce outcome and value expectations, self-efficacy, perceived benefits, and barriers and cues to actions regarding diet behavior. Conclusions: We developed a nutrition education programthat is rarely available for low-income children in Korea, considering theoretical bases. Further studies are needed to validate our program.

• Journal of Distribution Science
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• v.9 no.4
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• pp.29-42
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• 2011

With the many advantages of the internet, online shopping has become one of the fastest growing types of retail businesses. However, internet-based firms are much more firmly required to retain existing customers rather than secure new ones, and to make them revisit the site by strengthening trust and loyalty, thereby improving profits and outrivaling competitors. Commitment is an essential part of successful long-term relationships between buyers and sellers. Although commitments by both parties in an exchange can provide the foundation for the development of relational social norms, disproportionate commitments can lead to opportunism by the less committed partner. Moreover, flow, which is characterized by intense concentration and enjoyment, was found to be significantly linked with exploratory use behavior, which in turn was linked to the extent of computer use. The level of flow was, itself, determined by the individual's sense of being in control, and the level of challenge perceived in maneuvering a website. Website attractiveness goes hand in hand with the attractiveness of an internet shopping mall, and it can be conceptualized as the persuasive effectiveness of a message by the use of familiarity, favor, similarity, etc. It occurs when information receivers try to achieve self-satisfaction when they actually or emotionally identify themselves with an information source. This study investigates the relationship between the perceived system characteristics of an internet shopping mall and the loyalty of online consumers, and it examines how perceived website attractiveness and flow play mediating roles between the perceived system characteristics of an internet shopping mall and the affective commitment in the context of a clothes internet shopping mall. For these purposes, a structural model comprising several variables was developed. That model was tested with an analysis of moment structure (AMOS) using data from respondents who had purchased clothing through the internet during the past three months. In this model, the perceived system characteristics of an internet shopping mall, such as familiarity, reputation, uniqueness, positive emotions, self-efficacy, and interactivity, were proposed to affect the website's attractiveness and flow, and lead to a higher affective commitment over time. Thus, the perceived website attractiveness and flow were proposed as core mediating variables between perceived system characteristics and affective commitment. The results of a reliability test using Cronbach's Alpha, and a confirmatory factor analysis warranted using unidimensionality for the measures for each construct. In addition, the nomological validity of the measures was warranted from the results of a correlation analysis. The results of empirical analyses indicated that systematic attributes resulting in website attractiveness and user's characteristics, thereby triggering customers' flow, play a crucial role in inducing customers' affective commitment, and a user's characteristics are twice as important as systematic attributes in this study. Moreover, familiarity, reputation, and uniqueness all have a significant effect on website attractiveness, and the research showed that uniqueness took the first place, and that familiarity and reputation followed in order of magnitude. The fact that reputation was not the most important factor that affects the attractiveness of an internet shopping mall, with uniqueness or familiarity having a greater impact, suggests much deeper implications. Finally, positive emotion, self-efficacy, and interactivity all have a significant effect on customers' flow. In particular, the fact that positive emotion, compared to self-efficacy or interactivity, has much more impact on flow is very suggestive.

• Journal of Gifted/Talented Education
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• v.26 no.1
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• pp.77-99
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• 2016

The purpose of this study was to examine the effect of GI-STEAM program on leadership, creative personality, and learning flow of elementary Gifted Students. GI-STEAM program was the convergence model of Group Investigation that belongs to Co-learning and STEAM framework of learning criterion. The participants were 16 gifted students in a Korean elementary school located in Gyeong-gi province. The experimental design was one group pretest-posttest design. After a pretest on leadership, creative personality, and learning flow was conducted, classes were carried out as GI-STEAM program for the gifted student and a post-test was conducted. The study results of the class that was conducted twelve times for two weeks are as follows. First, Individual area of leadership is meaningfully developed in statistics after GI-STEAM program. The sub-domains of leadership, such as the communication, organization management, society commitment and teamwork showed a statistically significant improvement. Second, the domain of creative personality didn't show meaningful difference after GI-STEAM program. However, the aesthetic in the sub-domains of the creative personality showed a statistically significant improvement. Third, learning flow was meaningfully developed in statistics after GI-STEAM program. The sub-domains of the leadership, such as the balance between challenge and ability, integration with behavior and consciousness, concrete feedback and Autotelic experience showed a statistically significant improvement. In conclusion, GI-STEAM is an effective program for improving ability of communication, aesthetic sensibility, which are core competency of 'creative-convergence' gifted students. For this reason, it is highly considered that various programs applying GI-STEAM should be developed.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.2
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• pp.89-102
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• 2018

With the development of mobile technology, asset management on the Internet have also developed a lot. Drawing on Technology Acceptance Model, this study examines YUEBAO deployment to model consumers' purchase intention to use financial products offered online. In this study, we hypothesized that the characteristics of online asset management product will affect the purchase intention through perceived usefulness and conduct empirical analysis on Chinese consumers. In the study model, the independent variables were considered to include individual involvement, experience, product protection, corporate credibility, convenience, mobility, and familiarity. In addition, the parameters constitute the usefulness, and the dependent variable is the purchase. The results are as follows. First, YUEBAO's complementarity, corporate credibility, convenience, and familiarity have a significant influence on YUEBAO's usefulness. Second, The YUEBAO's usefulness has a noticeable effect on the purchase intention. To perceive the high usefulness, the practicality strategy of enhancing the protection property, corporate reliability, convenience and familiarity of the online asset management product is needed. The study of consumer purchase behavior and consumer purchase intention of online wealth management products is very valuable for academic and practical work.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.593-600
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• 2006

Joint opening of jointed concrete pavement is caused by change in temperature and humidity of adjoined slab. The magnitude of joint opening influences on the load-transfer-efficiency and the behavior of sealant. If temperature or humidity decreases, joint opening increases. Generally maximum joint opening of a given joint is predicted by using AASHTO equation. While different magnitudes of joint opening at the individual joints have been observed in a given pavement section, AASHTO equation is limited to predict average joint opening in a given pavement section. Therefore the AASHTO equation may underestimate maximum joint for the half of joint in a given pavement section. Joints showing larger opening than the designed may experience early joint sealant failure, early faulting. Also unexpected spalling may be followed due to invasion of fine aggregate into the joints after sealant pop-off. In this study, the variation of the joint opening in a given pavement section was investigated based on the LTPP SMP data. Factors affecting on the variation are explored. Finally a probabilistic joint opening model is developed. This model can account for the reliability of the magnitude of joint opening so that the designer can select the ratio of underestimated joint opening.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.3
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• pp.119-133
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• 2022

The COVID-19 pandemic is rapidly changing the behavior of members of society. Typically, the strong contagious power of the virus minimizes interaction between people in the real world, and they keep interaction activities to a minimum through online activities. Recently, as people demand online activities that enhance a sense of reality, the metaverse, which strengthens the 3D technology-centered sense of presence capability, is being chosen by people. The purpose of this study is to suggest a strategic direction for the establishment of the metaverse business model of startups by presenting factors for users' use and gratification of the metaverse. In detail, this study proposes the motivation for using the metaverse by reflecting the uses and gratification theory, and suggests a method to strengthen the motivation for the metaverse by reflecting the presences provided by the metaverse plotform and individual characteristics (normtive interpersonal influence). We surveyed people over 20 years of age who experienced metaverse and obtained 314 samples. In addition, we conducted the main effect analysis using the structural equation model and the moderating effect analysis using Process 3.1. As a result of hypothesis testing, we confirmed that metaverse presence (telepresence, social presence) has a positive effect on intention to continuous use by increasing metaverse's use and satisfaction factors (information, enjoyment, social interactivity). In addition, we found that individuals' normative interpersonal influence moderated the positive relationship between uses and gratification factors(enjoyment and social interactivity) intention to continuous use. Our study suggests strategies for establishing a user-centered business model for companies related to the metaverse.

• Information Systems Review
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• v.22 no.1
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• pp.33-57
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• 2020

Although cryptocurrency which can promote innovation in the blockchain ecosystem is published for many useful purposes, in Korea, cryptocurrency is recognized only as a means of investment for the profit. The fact emphasizes only the speculative nature of the cryptocurrency, so investor negates the fundamental purpose of cryptocurrency and hinders innovation in the blockchain ecosystem. The purpose of this study is to investigate the cause of cryptocurrency perception and speculative behavior of domestic cryptocurrency investors from an academic perspective. We use a model that reflects the traditional considerations and cryptocurrency's characteristics in investment. Using the model, we can explain the cause of misperception of cryptocurrency through the theory of bounded rationality. In building the research model, we use variables of venture and angel investor's consideration used in investment decisions and collect the keywords from indexes of whitepaper to reflect the properties of cryptocurrency. This study mentions that, due to the imitations presented by Simon, individuals are forced to perceive cryptocurrency as a means of speculation and to make irrational decisions that impair ecosystem health. We analyze whether there is a significant difference in rationality in decision made by the sample under limited knowledge and imperfect information constraints. As a result, imperfect information constraints led investors to consider only irrational criteria in decision making. From this result, this study suggests that information asymmetry needs to be relaxed so that investment can be pursued together with rational investment and development of blockchain ecosystem. In addition, the industry can capture strategic insights for successful financing through ICO by enabling better understanding of investor decision-making.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.5
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• pp.53-68
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• 2014

This study is aimed at analyzing the factors that affect the behaviors of employee's investment, such as a decision making process in a variety of views and proving the extent of how those factors influence on their investment. The basic assumption is that the preceding factors that can be determined by the personal investment propensity, a psychological factor asserted by Behavior Financial Theory and financial-economic and social environment. This study uses Hershey's Investment Behavior Model(2007) as the main analysis tool to explain the investment behavior of individuals and deals with personal investment inclination in the psychological perspective of overconfidence, self-control and the risk tolerance propensity and add the financial and economic factors in terms of financial literacy and economic distress. Also the new preceding social environmental factors like social interaction and the effect of reference group are added to make this research to be more precise. This study analyze the adjustment effect of professional invest-consulting service that affect the fluctuation influence between the individual variables(those factors) and subordination variable(the level of investment satisfaction). The study reveals that overconfidence and self-control in direct ways have a positive effect on the level of investment satisfaction in terms of investment behavior and economic distress has a negative effect on the level of investment satisfaction. The adjustment effect provided by financial experts in investment consulting service is affirmed as the critical factor that increase the influence between self-control and the level of investment satisfaction. To conclude, the research reveals that the psychological factors are the main criteria when the workers as employees have to make investment decisions. To make investors be reasonable, a systematic financial education system provided by experts is needed from the early adolescent stages and financial companies should develop the relevant services of consulting service department as a key financial sector and financial investment products and consulting program and marketing tool pertinent to investors ages, vocational traits and their inclinations.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.