• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.177-192
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• 2021

The Development Assistance Committee of the Organization for Economic Cooperation and Development discusses the reorganization of the five evaluation criteria of the Public Development Assistance Committee, which are used internationally, and the five evaluation criteria including adequacy, efficiency, effectiveness, impact, and sustainability when assessing public development assistance in 1991. This study is to derive alternatives by applying the evaluation criteria of the Development Assistance Committee of the Organization for Economic Cooperation and Development in the evaluation of the inclusive business program being implemented in Nepal since 2019. As a result of the study, the adequacy of Nepal's inclusive business program was consistent with continuous employment and job creation for vulnerable groups such as disabled and orphan women. Efficiency can be said to be efficient in that processes such as work order and work confirmation are made with an electronic management tool, and delivery of the result is transmitted online, saving time and cost compared to other industries. The effectiveness of this project can be said to be an effective program in that it provides high-quality jobs such as providing specialized computer graphics education for the vulnerable, such as disabled and orphan women in Nepal, and hiring graduates as employees. Sustainability is the point that KOICA's inclusive business program has enabled vulnerable groups in the existing fields of agriculture and manufacturing to engage in the computer graphics industry, and the scalability of movies, characters, education businesses, and role models in other countries.However, considering that the scale of public development assistance will continue to increase in the future, it is necessary to establish a systematic monitoring system and a recirculation system so that the project between the donor and recipient countries can continue.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.145-165
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• 2023

Recommendation system plays a significant role on relieving difficulties of selecting information among rapidly increasing amount of information caused by the development of the Internet and on efficiently displaying information that fits individual personal interest. In particular, without the help of recommendation system, E-commerce and OTT companies cannot overcome the long-tail phenomenon, a phenomenon in which only popular products are consumed, as the number of products and contents are rapidly increasing. Therefore, the research on recommendation systems is being actively conducted to overcome the phenomenon and to provide information or contents that are aligned with users' individual interests, in order to induce customers to consume various products or contents. Usually, collaborative filtering which utilizes users' historical behavioral data shows better performance than contents-based filtering which utilizes users' preferred contents. However, collaborative filtering can suffer from cold-start problem which occurs when there is lack of users' historical behavioral data. In this paper, hybrid music recommendation system, which can solve cold-start problem, is proposed based on the playlist data of Melon music streaming service that is given by Kakao Arena for music playlist continuation competition. The goal of this research is to use music tracks, that are included in the playlists, and metadata of music tracks and playlists in order to predict other music tracks when the half or whole of the tracks are masked. Therefore, two different recommendation procedures were conducted depending on the two different situations. When music tracks are included in the playlist, LightFM is used in order to utilize the music track list of the playlists and metadata of each music tracks. Then, the result of Item2Vec model, which uses vector embeddings of music tracks, tags and titles for recommendation, is combined with the result of LightFM model to create final recommendation list. When there are no music tracks available in the playlists but only playlists' tags and titles are available, recommendation was made by finding similar playlists based on playlists vectors which was made by the aggregation of FastText pre-trained embedding vectors of tags and titles of each playlists. As a result, not only cold-start problem can be resolved, but also achieved better performance than ALS, BPR and Item2Vec by using the metadata of both music tracks and playlists. In addition, it was found that the LightFM model, which uses only artist information as an item feature, shows the best performance compared to other LightFM models which use other item features of music tracks.

• Journal of Service Research and Studies
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• v.13 no.1
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• pp.48-62
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• 2023

As seen in the recent K-pop craze, the size and influence of the Korean music industry is growing even bigger. At least 6,000 songs are released a year in the Korean music market, but not many can be said to have been successful. Many studies and attempts are being made to identify the factors that make the hit music. Commercial factors such as media exposure and promotion as well as the quality of music play an important role in the commercial success of music. Recently, there have been many marketing campaigns using Internet memes in the pop music industry, and Internet memes are activities or trends that spread in various forms, such as images and videos, as cultural units that spread among people. Depending on the Internet environment and the characteristics of digital communication, contents are expanded and reproduced in the form of various memes, which causes a greater response to consumers. Previously, the phenomenon of Internet memes has occurred naturally, but artists who are aware of the marketing effects have recently used it as an element of marketing. In this paper, the mediated effect of Internet memes in relation to the success factors of popular music was analyzed, and a prediction model reflecting them was proposed. As a result of the analysis, the factors with the mediated effect of 'cover effect' and 'challenge effect' were the same. Among the internal success factors, there were mediated effects in "Singer Recognition," the genres of "POP, Dance, Ballad, Trot and Electronica," and among the external success factors, mediated effects in "Planning Company Capacity," "The Number of Music Broadcasting Programs," and "The Number of News Articles." Predictive models reflecting cover effects and challenge effects showed F1-score at 0.6889 and 0.7692, respectively. This study is meaningful in that it has collected and analyzed actual chart data and presented commercial directions that can be used in practice, and found that there are many success factors of popular music and the mediating effects of Internet memes.

• Land and Housing Review
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• v.14 no.2
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• pp.19-34
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• 2023

The proportion of single-person households has been steadily increasing, and the young account for the highest proportion at 35.9% among all single-person households. However, research on young single-person households has been relatively recent. Research on single-person households has mostly focused on all single-person households or elderly single-person households, and comparative research between different age groups is lacking. Therefore, this study categorizes all single-person households into young, middle-aged, and elderly groups to investigate the differences in the factors that affect their residential satisfaction and to analyze how these residential environment factors affect life satisfaction through the mediating effect of residential satisfaction. The 2020 Seoul Survey Urban Policy Index Survey data were analyzed using a structural equation model to investigate the impact of each factor. First, a finding is that various residential environment factors directly affect residential satisfaction and life satisfaction. Next, it was found that residential satisfaction directly affects life satisfaction in the models of young and middle-aged single-person households. Through this, it was confirmed that there are differences in residential environment factors that affect residential satisfaction and that residential satisfaction plays an important mediating role. Finally, it was found that the factors that affect the residential and life satisfaction of young single-person households are more diverse compared to other age groups. This study provides policy implications that age group differences should be considered first in order to improve the residential and life satisfaction of single-person households. In particular, for young single-person households, it is necessary to consider more diverse alternatives to improve their residential and life satisfaction.

• Journal of Nutrition and Health
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• v.56 no.6
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• pp.602-614
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• 2023

Purpose: The balance between synthesis and degradation of proteins plays a critical role in the maintenance of skeletal muscle mass. Mitochondrial dysfunction has been closely associated with skeletal muscle atrophy caused by aging, cancer, and chemotherapy. Polygalacin D is a saponin derivative isolated from Platycodon grandiflorum (Jacq.) A. DC. This study aimed to investigate the effects of polygalacin D on myoblast differentiation and muscle atrophy in association with mitochondrial function in in vitro and in zebrafish models in vivo. Methods: C2C12 myoblasts were cultured in differentiation media containing different concentrations of polygalacin D, followed by the immunostaining of the myotubes with myosin heavy chain (MHC). The mRNA expression of markers related to myogenesis, muscle atrophy, and mitochondrial function was determined by real-time quantitative reverse transcription polymerase chain reaction. Wild type AB^* zebrafish (Danio rerio) embryos were treated with 5-fluorouracil, leucovorin, and irinotecan (FOLFIRI) with or without polygalacin D, and immunostained to detect slow and fast types of muscle fibers. The Tg(Xla.Eef1a1:mitoEGFP) zebrafish expressing mitochondria-targeted green fluorescent protein was used to monitor mitochondrial morphology. Results: The exposure of C2C12 myotubes to 0.1 ng/mL of polygalacin D increased the formation of MHC-positive multinucleated myotubes (≥ 8 nuclei) compared with the control. Polygalacin D significantly increased the expression of MHC isoforms (Myh1, Myh2, Myh4, and Myh7) involved in myoblast differentiation while it decreased the expression of atrophic markers including muscle RING-finger protein-1 (MuRF1), mothers against decapentaplegic homolog (Smad)2, and Smad3. In addition, polygalacin D promoted peroxisome proliferator-activated receptor-gamma coactivator (Pgc1α) expression and reduced the level of mitochondrial fission regulators such as dynamin-1-like protein (Drp1) and mitochondrial fission 1 (Fis1). In a zebrafish model of FOLFIRI-induced muscle atrophy, polygalacin D improved not only mitochondrial dysfunction but also slow and fast muscle fiber atrophy. Conclusion: These results demonstrated that polygalacin D promotes myogenesis and alleviates chemotherapy-induced muscle atrophy by improving mitochondrial function. Thus, polygalacin D could be useful as nutrition support to prevent and ameliorate muscle wasting and weakness.

• Journal of Venture Innovation
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• v.3 no.2
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• pp.147-175
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• 2020

This study analyzed the effects that digital experience factors influence on purchase intention and the purchase. The study targeted an online shopping mall with a strong digital experience value among industries. The research model was derived by adding variables to independent and mediating variables according to the industry context of online shopping which is based on the theoretical background and previous studies. Product variety, price efficiency, convenience and conversation were used by terms of digital marketing mix as independent variables. Personalization has been very important factor in online shopping malls, and therefore added as a independent variable. Flow has been added as a mediating variable. Purchase and purchase intention has been used as dependent variables. For empirical testing of established research models and generalization of research results, research was conducted on online shopping malls where digital experiences are important. To do this, a survey was conducted for existing users of online shopping malls. In hypothesis testing, the hypothesis was established that product diversity, price efficiency, convenience, conversation and personalization influenced the intention to purchase online shopping. In particular, the product diversity and conversation variable were tested as the most influential factors on purchase intention. For price efficiency and personalization there were no statistically significant effect. Flow has been shown to be a partial mediator between Product variety and purchase intention in online shopping. In particular, in the case of personalization, it was tested to have a significant influence on purchase intention only when there was a flow experience called pleasure and immersion. This is because the flow experience of pleasure and immersion has played a full mediating role and significantly has affected the purchase intention, because the consumers themselves have to carry out the overall purchase journey without human help due to the nature of online. In the digital experience economy, since consumers are mostly digital consumers, where communication and sharing are the basics, they have been conducting digital word-of-mouth communication and sharing naturally before purchasing. Based on these results, theoretical and practical implications were suggested.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.2
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• pp.35-52
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• 2023

Recently, as the non-face-to-face environment has developed due to COVID-19 and environmental pollution, the importance of online digital healthcare is increasing, and venture start-ups and activities such as health care, telemedicine, and digital treatments are also actively underway. This study conducted the impact on the acceptability of digital healthcare smartwatches with an integrated approach of the expanded integrated technology acceptance model (UTAUT2) and the behavioral inference model (BRT). The most advanced integrated technology acceptance model for innovative technology acceptance research was used to identify major factors such as utility expectations, social effects, convenience, price barriers, lack of alternatives, and behavioral intentions. For the study, about 410 responses from ordinary people in their teens to 60s across the country were collected, and based on this, the hypothesis was verified using structural equations after testing reliability and validity of the data. SPSS 23 and AMOS 23 were used for research analysis. Studies have shown that personal innovation has a significant impact on the reasons for acceptance (use value, social impact, convenience of use), attitude, and non-use (price barriers, lack of alternatives, and barriers to use). These results are the same as the results of previous studies that confirmed the influence of the main value of innovative ICT on user acceptance intention. In addition, the reason for acceptance had a significant effect on attitude, but the effect of the reason for non-acceptance was not significant. It can be analyzed that consumers are interested in new ICT products and new services, but purchase them more carefully and selectively. This study has evolved from the acceptance analysis of general-purpose consumer innovation technology to the acceptance analysis of consumer value in smartwatch digital healthcare, which is a new and important area in the future. Industrially, it can contribute to the product's purchase and marketing. It is hoped that this study will contribute to increasing research in the digital healthcare sector, which will play an important role in our lives in the future, and that it will develop into in-depth factors that are more suitable for consumer value through integrated approach models and integrated analysis of consumer acceptance and non-acceptance.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.21-35
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• 2023

Expectations surrounding generative AI technology and its profound ramifications are sweeping across various industrial domains. Given the anticipated pivotal role of the startup ecosystem in the utilization and advancement of generative AI technology, it is imperative to cultivate a deeper comprehension of the present state and distinctive attributes characterizing venture capital (VC) investments within this domain. The current investigation delves into South Korea's landscape of VC investment deals and prognosticates the projected VC investments by juxtaposing these against the United States, the frontrunner in the generative AI industry and its associated ecosystem. For analytical purposes, a compilation of 286 investment deals originating from 117 U.S. generative AI startups spanning the period from 2008 to 2023, as well as 144 investment deals from 42 South Korean generative AI startups covering the years 2011 to 2023, was amassed to construct new datasets. The outcomes of this endeavor reveal an upward trajectory in the count of VC investment deals within both the U.S. and South Korea during recent years. Predominantly, these deals have been concentrated within the early-stage investment realm. Noteworthy disparities between the two nations have also come to light. Specifically, in the U.S., in contrast to South Korea, the quantum of recent VC deals has escalated, marking an augmentation ranging from 285% to 488% in the corresponding developmental stage. While the interval between disparate investment stages demonstrated a slight elongation in South Korea relative to the U.S., this discrepancy did not achieve statistical significance. Furthermore, the proportion of VC investments channeled into generative AI enterprises, relative to the aggregate number of deals, exhibited a higher quotient in South Korea compared to the U.S. Upon a comprehensive sectoral breakdown of generative AI, it was discerned that within the U.S., 59.2% of total deals were concentrated in the text and model sectors, whereas in South Korea, 61.9% of deals centered around the video, image, and chat sectors. Through forecasting, the anticipated VC investments in South Korea from 2023 to 2029 were derived via four distinct models, culminating in an estimated average requirement of 3.4 trillion Korean won (ranging from at least 2.408 trillion won to a maximum of 5.919 trillion won). This research bears pragmatic significance as it methodically dissects VC investments within the generative AI domain across both the U.S. and South Korea, culminating in the presentation of an estimated VC investment projection for the latter. Furthermore, its academic significance lies in laying the groundwork for prospective scholarly inquiries by dissecting the current landscape of generative AI VC investments, a sphere that has hitherto remained void of rigorous academic investigation supported by empirical data. Additionally, the study introduces two innovative methodologies for the prediction of VC investment sums. Upon broader integration, application, and refinement of these methodologies within diverse academic explorations, they stand poised to enhance the prognosticative capacity pertaining to VC investment costs.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.131-148
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• 2023

The purpose of this study is to investigate the effects of entrepreneurial environment and entrepreneurial competency on entrepreneurial intention by setting degree of self-determination as a moderating variable for pre-entrepreneur of agriculture industry. The entrepreneurial environment was divided into perceived support and perceived barriers, and the sub-variables of entrepreneurial competence were set as creativity, problem solving, communication, marketing, and business plan. 253 questionnaires were used for empirical analysis. The results of the analysis using SPSS v25.0 and Process macro v4.2 are as follows. First, the perceived support and perceived barriers of the entrepreneurial environment have a significant effect on entrepreneurial intention. Creativity, problem solving, marketing and business plan of entrepreneurial competency have a significant effect on entrepreneurial intention, but the effect of communication was non-significant. Second, the degree of self-determination did not moderate the relationship between perceived support, barriers and entrepreneurial intention. This means that the level of self-determination may not have a significant effect on the relationship between entrepreneurial environment and entrepreneurial intention. Third, the degree of self-determination was found to moderate the relationship between creativity, problem solving, communication, marketing and business plan of entrepreneurial competency and entrepreneurial intention. Specifically, as the degree of self-determination increases, the size of the influence of creativity, problem solving, marketing, and business plan on entrepreneurial intention plays a role of strengthening in a positive direction. On the other hand, as the degree of self-determination increases, the degree of self-determination, which weakens the relationship between communication and entrepreneurial intention. Future research will require exploration of other factors that can explain entrepreneurial environment and entrepreneurial capacity, and follow-up studies are needed to analyze the moderated mediating effects through conditional process models that include new mediating and moderating variables.