• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.539-544
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• 2023

In this study, several important aspects were studied in producing video advertisements based on the lifestyle and SNS status of Generation Z. Generation Z highly values participation and interaction due to the nature of SNS, so SNS advertisements should be produced in a way that induces active interaction with viewers and accepts feedback. Here's a summary of the main parts. It prefers various content formats of Generation Z that consume information. Advertisements should be produced in various formats such as text, images, and videos, and should have flexibility suitable for various platforms. Because each SNS platform has its own characteristics due to platform specialization, this study suggests that advertisements analyze the characteristics of the platform and use the appropriate content strategy for the optimized platform. As an emphasis on value proposition, we propose an advertising format setting to focus on what value the product or brand provides. It is important to clearly emphasize the advantages and intrinsic value of a product or service in video advertising, and in conclusion, we propose to focus on the case of increasing interest by adopting modern and trendy design of storytelling as an attractive and unique design method of aesthetic design and visual effects. Considering these factors comprehensively, the research value of this paper will be able to establish an effective SNS marketing strategy by producing video advertisements that match the lifestyle and SNS usage characteristics of Generation Z.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.325-345
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• 2023

In the rapidly evolving domain of e-commerce, our study presents a cohesive approach to enhance customer satisfaction prediction from online reviews, aligning methodological innovation with practical insights. We integrate the RFE-SHAP feature selection with LDA topic modeling to streamline predictive analytics in e-commerce. This integration facilitates the identification of key features-specifically, narrowing down from an initial set of 28 to an optimal subset of 14 features for the Random Forest algorithm. Our approach strategically mitigates the common issue of overfitting in models with an excess of features, leading to an improved accuracy rate of 84% in our Random Forest model. Central to our analysis is the understanding that certain aspects in review content, such as quality, fit, and durability, play a pivotal role in influencing customer satisfaction, especially in the clothing sector. We delve into explaining how each of these selected features impacts customer satisfaction, providing a comprehensive view of the elements most appreciated by customers. Our research makes significant contributions in two key areas. First, it enhances predictive modeling within the realm of e-commerce analytics by introducing a streamlined, feature-centric approach. This refinement in methodology not only bolsters the accuracy of customer satisfaction predictions but also sets a new standard for handling feature selection in predictive models. Second, the study provides actionable insights for e-commerce platforms, especially those in the clothing sector. By highlighting which aspects of customer reviews-like quality, fit, and durability-most influence satisfaction, we offer a strategic direction for businesses to tailor their products and services.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.6
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• pp.71-88
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• 2022

The purpose of this study is to develop the competencies to help micro entrepreneurs who have experienced failure to successfully re-challenge. To this end, relevant literature published from 1977 to 2022 was analyzed, behavioral event interviews (BEI) were conducted with 7 successful micro entrepreneurs, and focus group interviews (FGI) were conducted three times by inviting competency development and HRD experts. Based on these research activities, the draft about competencies for micro entrepreneurs who had have failure was derived. And then inviting 12 experts in related field for Delphi Analysis, the final competency model that helps micro entrepreneurs successfully recover were developed as follows : Competency Groups(small business owners, recovery from failure), 8 detailed competencies(seize business opportunities, business planning, business differentiation, operation management, market exploration, research and development of products and services, positive self-regulation, overcoming and coping with failure experiences), 22 competency factors, and 72 behavioral indicators. This study has an academic significance in that it developed the competencies required for micro entrepreneurs recovering from failure. In addition, the results of this study can be used to develop a competency-based education program for micro entrepreneurs and to select suitable candidates for support programs.

• Journal of the Korean Regional Science Association
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• v.40 no.1
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• pp.37-51
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• 2024

To respond to local extinction, South Korea, under the leadership of the Ministry of the Interior and Safety, identified depopulated areas in 2021 and launched the Local Extinction Response Fund in 2022. However, due to its early stage of implementation, analyzing the characteristics and changes of policy response to local extinction at the central government level remains a challenge. In contrast, Japan, facing similar issues of local extinction as South Korea, has established a robust central government-led response system based on the Regional Revitalization Act and the Comprehensive Strategy and Basic Policy on Community-Population-Job Creation. Hence, this study examines Japan's policy responses to local extinction by analyzing the first and second periods of the Comprehensive Strategy and Basic Policy on Community-Population-Job Creation. For the analysis, topic modeling was employed to enhance text analysis efficiency and accuracy, complemented by expert interviews for validation. The results revealed that the first-period strategy's topics encompassed economy and society, start-up, local government, living condition, service, and industry. Meanwhile, the second-period strategy's topics included resource, the New Normal, woman, digital transformation, industry, region, public-private partnership, and population. The analysis highlights that the policy target, policy direction, and environmental change significantly influenced these policy shifts.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.3
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• pp.100-107
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• 2024

Currently, in Korea, due to the rapid aging and deterioration of facilities, the minimum Maintenance Level and Performance Level' of facilities are required by the 'Facility Safety Act' or 'Infrastructure Management Act'. Since infrastructure assets have a long lifespan and the pattern of deterioration over time is complex, it is very difficult to maintain infrastructure as 'minimum maintenance state' or 'minimum performance state' by the current way of management. 'Asset Management' shall be performed not only by a technical perspective, but also by an accounting perspective such as cost and asset value. However, due to lack of awareness of 'asset management' among stakeholder, only technical perspective management is being carried out in practice. In order to effectively manage infrastructure assets, complex consideration of various asset value factors such as budget and service as well as safety and durability are required. In this paper, we presented a theory to evaluate and quantify the road network value for efficient asset management of the road network. We also presented a method of simulation to apply the theory presented in this paper. Through simulation and the results derived from this study, it is possible to specify the budget for the future national asset management, and to optimize the strategy for the management of old road facilities.

• Journal of Navigation and Port Research
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• v.48 no.3
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• pp.146-154
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• 2024

The ship management industry in South Korea has been growing steadily, leading the government to implement policies to support its development in response to changing environmental conditions. These policies aim to improve the competitiveness of South Korea's ship management industry by recognizing the importance of skilled professionals in determining its success. Plans and policies have been put in place to cultivate these professionals, but ship management companies are currently facing a serious shortage of manpower. To enhance the industry's competitiveness, it is essential to attract and retain competent ship management professionals. Therefore, this study investigates the reasons for turnover among these professionals. The research results identified four factors contributing to turnover: Work Environment, Economic Compensation and Welfare Benefits, Self-Development, and Promotion and Career Advancement. Subsequent multiple regression analysis based on these factors revealed the need to strengthen economic rewards and benefits in order to reduce turnover rates among ship management professionals. This study provides foundational data for the development of stable human resource management policies for the future of the ship management industry.

• Journal of Cadastre & Land InformatiX
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• v.54 no.1
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• pp.49-61
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• 2024

South Korea faces a declining population and rural areas vanishing due to urbanization. Infrastructure, especially medical facilities, may not be sustainable for a long-term. This may impact vulnerable groups like children, teens, and the elderly, worsened by an aging population and low birth rates. Gangwon-do, notably Chuncheon-si, suffers from rural depopulation and poor healthcare self-sufficiency. In this paper, using 2SFCA(Two-Step Floating Catchment Area), we analyze healthcare access in Chuncheon-si, identifying gaps and vulnerable areas. LISA analysis helps map medical vulnerability, considering patient demand and supply. The Gini coefficient assesses spatial inequality. We propose distributing healthcare services and personnel based on age and region. The aim is to identify locations for additional hospitals catering to the elders, Infants, Children, and Adolescents,considering spatial accessibility.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.207-212
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• 2024

The importance of hydrogen fuel cells continues to be emphasized, and there is a growing demand for education and training in this field. Among various educational environments, metaverse education is opening a new era of change in the global education industry, especially to adapt to remote learning. The most significant change that the metaverse has brought to education is the shift from one-way, instructor-centered, and static teaching approaches to multi-directional and dynamic ones. It is expected that the metaverse can be effectively utilized in hydrogen fuel cell engineer education, not only enhancing the effectiveness of education by enabling learning and training anytime, anywhere but also reducing costs associated with engineering education.In this research, inspired by these ideas, we are designing a fuel cell education platform. We have created a platform that combines theoretical and practical training using the metaverse. Key aspects of this research include the development of educational training content to increase learner engagement, the configuration of user interfaces for improved usability, the creation of environments for interacting with objects in the virtual world, and support for convergence services in the form of digital twins.

• Information Systems Review
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• v.25 no.1
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• pp.27-46
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• 2023

Research on restaurant recommender systems has been proposed due to the development of the food service industry and the increasing demand for restaurants. Existing restaurant recommendation studies extracted consumer preference information through quantitative information or online review sensitivity analysis, but there is a limitation that it cannot reflect consumer semantic preference information. In addition, there is a lack of recommendation research that reflects the detailed attributes of restaurants. To solve this problem, this study proposed a model that can learn the interaction between consumer preferences and restaurant attributes by applying deep learning techniques. First, the convolutional neural network was applied to online reviews to extract semantic preference information from consumers, and embedded techniques were applied to restaurant information to extract detailed attributes of restaurants. Finally, the interaction between consumer preference and restaurant attributes was learned through the element-wise products to predict the consumer preference rating. Experiments using an online review of Yelp.com to evaluate the performance of the proposed model in this study confirmed that the proposed model in this study showed excellent recommendation performance. By proposing a customized restaurant recommendation system using big data from the restaurant industry, this study expects to provide various academic and practical implications.

• Information Systems Review
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• v.25 no.1
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• pp.129-143
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• 2023

In the era of big data, the field of artificial intelligence is showing remarkable growth, and in particular, the image classification learning methods by deep learning are becoming an important area. Various studies have been actively conducted to further improve the performance of CNNs, which have been widely used in image classification, among which a representative method is the Convolutional Recurrent Neural Network (CRNN) algorithm. The CRNN algorithm consists of a combination of CNN for image classification and RNNs for recognizing time series elements. However, since the inputs used in the RNN area of CRNN are the flatten values extracted by applying the convolution and pooling technique to the image, pixel values in the same phase in the image appear in different order. And this makes it difficult to properly learn the sequence of arrangements in the image intended by the RNN. Therefore, this study aims to improve image classification performance by proposing a novel hybrid method of CNN and RNN applying the concepts of encoder and decoder. In this study, the effectiveness of the new hybrid method was verified through various experiments. This study has academic implications in that it broadens the applicability of encoder and decoder concepts, and the proposed method has advantages in terms of model learning time and infrastructure construction costs as it does not significantly increase complexity compared to conventional hybrid methods. In addition, this study has practical implications in that it presents the possibility of improving the quality of services provided in various fields that require accurate image classification.