• Journal of Venture Innovation
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• v.6 no.4
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• pp.63-81
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• 2023

The purpose of this study was to utilize the Photovoice qualitative research method targeting university students. Through this method, we aimed to understand the perceptions of environmental issues, environmental barriers, and eco-friendly behaviors among university students. By employing the Photovoice methodology, we sought to share the perspectives of university students on eco-friendly behaviors, explore the motivations and manifestations of these behaviors, and reflect on their significance. The ultimate goal was to provide practical suggestions for fostering eco-friendly behaviors through an in-depth examination of the visual narratives and reflections of university students. Under the overarching theme of the environment, participants were given the opportunity to individually select and explore three specific sub-themes: 'My Concept of the Environment,' 'Environmental Barriers in My Life,' and 'My Eco-friendly Behaviors.' Participants engaged in the process of capturing photographs from their daily lives related to each theme, expressing their thoughts and perspectives through the selected images. Subsequently, they shared and discussed their insights, actively listening to the opinions of others in the group. The results of this study revealed several key findings. Firstly, participants assigned meaning to the photographs they selected by directly capturing aspects related to the environment, such as 'waste,' 'discomfort,' 'fine dust=environmental pollution,' and 'indifference.' Secondly, participants attributed meaning to the selected photographs related to environmental barriers, associating them with concepts like 'invisibility,' 'apathy,' 'social stigma,' 'inefficiency,' and 'compulsion.' Lastly, participants ascribed significance to photographs selected in the context of eco-friendly behaviors, with themes like 'recycling,' 'energy conservation,' 'reuse,' and 'reducing the use of disposable items.' Based on these research findings, the confirmation of the V-A-B (Values-Attitudes-Behavior) model was established. It was observed that consumers structure a hierarchical relationship between their personal values, attitudes, and behaviors. The study also identified clear impediments in consumers' daily lives hindering the practice of eco-friendly behaviors. In light of this, the research highlighted the need for strategies to address the discomfort or inconvenience associated with implementing environmentally friendly consumer behaviors. The implications of the study suggest that interventions or solutions are necessary to alleviate barriers and promote a more seamless integration of eco-friendly practices into consumers' daily routines.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.157-172
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• 2023

The recent Fourth Industrial Revolution is accelerating changes due to digital transformation. According to this trend, the existing start-up paradigm is changing, and new business models based on new technologies and creative ideas are emerging. In addition, the diversity of mentoring relationships and environments such as online mentoring, reverse mentoring, group mentoring, and multiple mentoring is also increasing. However, most mentors in their 50s and 60s, who are mainly active in the start-up field, have been able to help mentees a lot based on their own experience and expertise, but they are having difficulty responding to the changing environment due to a lack of understanding and experience of new technologies and environments. To cope with these changes well, mentors must constantly study, acquire and apply the latest technologies to improve their understanding of new technologies and the environment. In addition, it is necessary to have an understanding and respect for the diversity of mentoring relationships and environments, and to maximize the effectiveness of mentoring by actively utilizing them. Therefore, mentors should recognize that they directly affect the growth and development of mentees, constantly acquire new knowledge and skills to maintain and develop expertise, and actively deliver their knowledge and experiences to mentees. Therefore, in this study, was tried to empirically analyze the relationship between mentoring's influence on mentor's job satisfaction through mentor's personal learning and self-efficacy. The results of the empirical analysis were as follows. Among the functions of mentoring, career function and role modeling were found to have a positive effect on both personal learning and self-efficacy, which are parameters, and job satisfaction, which is a dependent variable. On the other hand, psychological and social functions have a positive effect on personal learning, but they do not have an effect on self-efficacy and job satisfaction. In addition, as a result of analyzing the mediating effect, all mediating effects were confirmed for career functions, and only the mediating effect of self-efficacy was confirmed for role modeling. Through this study, mentoring is an important factor in promoting job satisfaction, personal learning and self-efficacy, and this study can be said to be academically and practically meaningful in that it confirmed personal learning and self-efficacy as factors that increase mentor's job satisfaction, and the focus of mentoring research was shifted from mentee to mentor to study the impact of mentoring on mentors.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.1-16
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• 2023

Due to imbalances in supply and demand within the labor market, start-ups have emerged as crucial players in the generation of high-quality employment opportunities, particularly in stagnant job markets. In response to this trend, governments are allocating substantial financial and human resources to initiatives that support start-up development. This has led to an increasing rate of engagement in start-up ventures across diverse age groups, not limited to younger individuals. Start-ups are enterprises focused on the commercialization of innovative ideas with the aim of achieving profitability in the marketplace. Research concerning the successful market integration of new products and the attainment of sustainable growth is pivotal. Such research is instrumental not only for the success of start-ups but also for realizing the broader social functions and contributions that these enterprises can offer. Previous research has often examined new product market-entry strategies, often referred to as new product marketing, particularly for large companies and SMEs. However, there is a gap in studies focusing on prototype marketing strategies specific to start-ups. Thus, this study aims to examine the impact of Pre-announcing marketing strategies on the market attention garnered by start-ups with low recognition and limited infrastructure, and how such attention contributes to their sustainable growth. Specifically, the study aims to uncover the causal relationship between information attributes like relevance, vividness, and novelty in building customer relationships, and their impact on purchase intentions influenced by performance expectations and hedonic motivations. In terms of Pre-announcing information attributes, relevance, vividness, and novelty positively influence performance expectations and hedonic motivations as outlined in the extended Unified Theory of Acceptance and Use of Technology (UTAUT2). These factors, in turn, positively impact the purchase intention for pre-announced new products from start-ups. These findings are expected to provide both theory and practical insights into the factors influencing market entry through the use of Pre-announcing marketing strategies for start-up new products.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.2
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• pp.65-80
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• 2022

Despite the uncertainty and risky factors of startups, the special and critical role of accelerators in carrying out professional nurturing and investment for them is becoming increasingly significant in the startup social-system. However, academic research on investment determinants that have a profound impact on the survival of accelerators is lacking, and there are only a few empirical studies on the classification and importance of factors, and they do not enjoy the benefits of theoretical studies. This study proposes a business model innovation framework based on the business model innovation theory that reflects the nature and properties of startups that are investment targets of accelerators and derives 12 investment decision factors. The framework defines that the target, direction, and performable force of startup innovation are a business model, strategy, and dynamic capability. Besides, the framework analyzes the investment decision factors of the existing accelerators based on the business model innovation framework to verify the suitability and sufficiency of the composition. As a result of the analysis, first, most of the items were faithfully composed from a static point of view of business model innovation, but it was found that the factors related to the core activities to evaluate the activity and customer relationship were insufficient. Second, from the strategic point of view, the necessity of developing factors that can encompass the definition and content of core resources, which are internal strategic factors, was raised. Third, from the dynamic point of view, it was found that many of the investment determinants of accelerators were concentrated on the lower level of dynamic competencies. This can be judged as a result of reflecting the characteristics of a startup that needs to develop a solution with few resources and a small number of team members. In addition, the roles and interrelationships between each factor are not clear, thus it was found as a limiting point for startups to view and evaluate the direction and process in which startups dynamically innovate their business models. This study is considerably differentiated in that it provides a business model innovation framework and offers a theoretical basis for investment determinants by deriving the investment determinants of accelerators based on the framework and design the foundation for subsequent research. The business model innovation framework presented in this study has great implications in that it contributes to the achievement of startups, accelerators, and startup support organizations.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.133-150
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• 2022

The purpose of this study was to develop a female entrepreneurial competency model. For the purpose, two Focus Group Interviews (FGI) were conducted with seven outstanding female entrepreneurs, and three expert reviews were conducted. In addition, in order to verify the validity of the provisional female entrepreneur competency model derived from the FGI and competency modeling expert review, the female entrepreneur competency model was finally confirmed through a survey of 442 female entrepreneurs. The results were as follows. First, a female entrepreneur competency model consisting of 6 competency groups and 25 competencies of entrepreneurship, emotion, business management, relationship management, strategic management, and multitasking, and 75 behavioral indicators describing each competency was developed. Second, sensibility and multitasking are competencies that reflect the characteristics of female entrepreneurs. In particular, 'social sense', which is the ability to be considerate of others in the emotional competency group and the ability to respond well to subtle nuances, and the multitasking competency group's unique strengths are women's ability to perform various tasks at the same time. The 'work-family control ability' of a female entrepreneur who maintains a balance between 'multi-tasking' and work and family is a representative competency of only female entrepreneurs. Third, the developed female entrepreneurship competency model is meaningful in that it not only increases female entrepreneurial competency so that prospective female entrepreneurs can successfully run a business through entrepreneurship education, but it also makes it easy for existing female entrepreneurs to reflect and improve their competencies. If we provide appropriate training programs to female entrepreneurs based on their competency, it will be possible to effectively enhance the entrepreneurial competency, which is the key to strengthening the competitiveness of female entrepreneurs. The female entrepreneur competency model developed through this study can provide a basis for future research on competency diagnosis and education needs analysis.

• Information Systems Review
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• v.20 no.2
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• pp.39-62
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• 2018

Thanks to the growth of computing power and the recent development of data analytics, researchers have started to work on the data produced by users through the Internet or social media. This study is in line with these recent research trends and attempts to adopt data analytical techniques. We focus on the impact of "internal marketing" factors on firm performance, which is typically studied through survey methodologies. We looked into the job review platform Jobplanet (www.jobplanet.co.kr), which is a website where employees and former employees anonymously review companies and their management. With web crawling processes, we collected over 40K data points and performed morphological analysis to classify employees' reviews for internal marketing data. We then implemented econometric analysis to see the relationship between internal marketing and market capitalization. Contrary to the findings of extant survey studies, internal marketing is positively related to a firm's market capitalization only within a limited area. In most of the areas, the relationships are negative. Particularly, female-friendly environment and human resource development (HRD) are the areas exhibiting positive relations with market capitalization in the manufacturing industry. In the service industry, most of the areas, such as employ welfare and work-life balance, are negatively related with market capitalization. When firm size is small (or the history is short), female-friendly environment positively affect firm performance. On the contrary, when firm size is big (or the history is long), most of the internal marketing factors are either negative or insignificant. We explain the theoretical contributions and managerial implications with these results.

• Journal of Nutrition and Health
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• v.57 no.3
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• pp.320-335
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• 2024

Purpose: This study examined the impact of adolescents' dietary behavior on their quality of life using the nutrition quotient for adolescents (NQ-A) for some high school students in Seoul. Methods: The subjects were 176 high school students living in Seoul. The NQ-A was used to assess the dietary quality, and the quality of life was assessed by categorizing it into life satisfaction, environment, health, participation and safety, leisure activities, and emotional factors using survey questions validated through previous studies. Results: The NQ score of the survey subjects was 49.30 points. Based on the NQ scores, 7.4%, 46.6%, and 46.0% of participants were categorized as the 'high', 'medium', and 'low' groups, respectively. The total NQ score and balance, diversity, and practice factor scores were positively correlated with life satisfaction, environment, health, participation and safety, and leisure activities among the quality of life subscales. Regression analysis showed that the total NQ score was positively associated with life satisfaction, health, leisure activities, and emotions; the moderation factor was negatively associated with life satisfaction and health. The balance factor was positively associated with the environmental factor. The practice factor was positively associated with health, leisure activities, and emotions, and the environment factor was negatively associated with emotions. Conclusion: These results show that adolescents' quality of life is closely related to their diet, so it is necessary to maintain a balanced and varied food intake and desirable eating behaviors to improve adolescents' quality of life. Furthermore, adolescents' quality of life is influenced by other factors. Therefore, further research is needed to assess the quality of life, including dietary factors, as well as physical, emotional, psychological, and social development.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.123-138
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• 2017

Since the stock market is driven by the expectation of traders, studies have been conducted to predict stock price movements through analysis of various sources of text data. In order to predict stock price movements, research has been conducted not only on the relationship between text data and fluctuations in stock prices, but also on the trading stocks based on news articles and social media responses. Studies that predict the movements of stock prices have also applied classification algorithms with constructing term-document matrix in the same way as other text mining approaches. Because the document contains a lot of words, it is better to select words that contribute more for building a term-document matrix. Based on the frequency of words, words that show too little frequency or importance are removed. It also selects words according to their contribution by measuring the degree to which a word contributes to correctly classifying a document. The basic idea of constructing a term-document matrix was to collect all the documents to be analyzed and to select and use the words that have an influence on the classification. In this study, we analyze the documents for each individual item and select the words that are irrelevant for all categories as neutral words. We extract the words around the selected neutral word and use it to generate the term-document matrix. The neutral word itself starts with the idea that the stock movement is less related to the existence of the neutral words, and that the surrounding words of the neutral word are more likely to affect the stock price movements. And apply it to the algorithm that classifies the stock price fluctuations with the generated term-document matrix. In this study, we firstly removed stop words and selected neutral words for each stock. And we used a method to exclude words that are included in news articles for other stocks among the selected words. Through the online news portal, we collected four months of news articles on the top 10 market cap stocks. We split the news articles into 3 month news data as training data and apply the remaining one month news articles to the model to predict the stock price movements of the next day. We used SVM, Boosting and Random Forest for building models and predicting the movements of stock prices. The stock market opened for four months (2016/02/01 ~ 2016/05/31) for a total of 80 days, using the initial 60 days as a training set and the remaining 20 days as a test set. The proposed word - based algorithm in this study showed better classification performance than the word selection method based on sparsity. This study predicted stock price volatility by collecting and analyzing news articles of the top 10 stocks in market cap. We used the term - document matrix based classification model to estimate the stock price fluctuations and compared the performance of the existing sparse - based word extraction method and the suggested method of removing words from the term - document matrix. The suggested method differs from the word extraction method in that it uses not only the news articles for the corresponding stock but also other news items to determine the words to extract. In other words, it removed not only the words that appeared in all the increase and decrease but also the words that appeared common in the news for other stocks. When the prediction accuracy was compared, the suggested method showed higher accuracy. The limitation of this study is that the stock price prediction was set up to classify the rise and fall, and the experiment was conducted only for the top ten stocks. The 10 stocks used in the experiment do not represent the entire stock market. In addition, it is difficult to show the investment performance because stock price fluctuation and profit rate may be different. Therefore, it is necessary to study the research using more stocks and the yield prediction through trading simulation.

• Cartoon and Animation Studies
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• s.37
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• pp.361-392
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• 2014

Regarding works that express objects realistically in painting, Gustave Courbet advocated realism in the mid-19th century, France, resisting the then academist style of painting, and works in realist style were produced in earnest by painters such as H. Daumier or Jean F. Millet, who went along with him. Later, realism has expanded into the realm of general literature, including fine art, which has had profound impacts on works of art and literary works. In comics, too, in the same historical context as a form of painting, realistic comics began to be produced by painters or cartoonists at the time. These realism comics are those dealing with stories based on facts, and in terms of contents, objective description and representation of the social realities of the times is one of the most important objectives, but it could not be concluded that in their visual aspect, that is, that of expressing the objects, they were realistic. In the meantime, a graphic novel was born, which was the intermediate form between comics and novels around the United States and Europe since the 1980s. Graphic novels appeared in forms and styles with strong literary and artistic values in the comics market in the U.S. which was full of the superhero genre (comics around heroes), and their major characteristics are very realistic expressions in terms of contents and visual aspect. They are complex and delicate and even have artistic, literary values as if readers read a fiction or literary work of which its narrative structures or pictures are produced with graphics. The characteristics of realistic expressions shown in graphic novels are very different from the previous works of comics. It is noteworthy that they began to be acknowledged as works of art like painting or illustration, thanks to their features of strongly individual auteurist painting style, a fairly high degree of completion of the works, and creative and experimental expression techniques or methods, instead of following the fashion of the times. In recent years, in South Korea, Hollywood blockbuster films have been released one after another and become box office hits, there are increasing interest and demand for the original graphic novels. Accordingly, many original graphic novels have been translated and started to be sold, and keeping pace with this global flow of fashion, some writers in Korea began to produce works of graphic novels. However, to look into the domestic works produced claiming to be graphic novels, there are various opinions on their format and authenticity. In this sense, this study focused on Ga-ya Kwon's Namhansanseong, one the representative works of Korean style graphic novels, and in particular, it attempted to analyze their characteristics and commonalities focusing on the visual aspect of realistic expressions of objects. It is expected that there would be an opportunity to seek for ways so that Korean style graphic novel can be further developed as a genre of comics, with competitiveness by looking back on the identity and present state of domestic graphic novels and developing and applying Korea's original subject matters differentiated from those of graphic novels in the U.S., Europe or Japan through this study. In addition, it is desired that they will be a new energizer for the stagnant domestic comics market.