• Korean small business review
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• v.42 no.4
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• pp.251-283
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• 2020

The purpose of this study is to provide assistance to the establishment of related policies to improve the level of acceptance and use of smart factories for SMEs in Korea. To this end, the Unified Technology Acceptance Model (UTAUT) was extended to select additional factors that could affect the intention to accept technology, and to demonstrate this. To achieve the research objective, a questionnaire composed of 7-point Likert scales was prepared, and a survey was conducted for manufacturing-related companies. A total of 136 questionnaires were used for statistical processing. As a result of the hypothesis test, performance expectation and social influence had a positive (+) positive effect on voluntary use, but effort expectation and promotion conditions did not have a significant effect. As an extension factor, the network effect and organizational characteristics had a positive (+) effect, and the innovation resistance had a negative effect (-), but the perceived risk had no significant effect. When the size of the company is large, the perceived risk and innovation resistance are low, and the level of influencing factors for veterinary intentions, veterinary intentions, and veterinary behaviors are excluded. Through this study, factors that could have a positive and negative effect on the adoption (reduction) of smart factory-related technologies were identified and factors to be improved and factors to be reduced were suggested. As a result, this study suggests that smart factory-related technologies should be accepted.

• Journal of Korea Entertainment Industry Association
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• v.15 no.5
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• pp.115-128
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• 2021

The purpose of this study is to examine the importance and satisfaction perceived in the purchase of goods and the use of a court in badminton club members. The results will be used for basic data to increase club members and present the methods to activate badminton. The survey on goods, price, programs, facilities, staff, and publicity was conducted. The IPA matrix was applied for data processing. The following conclusions were drawn. First, as a result of analyzing the ranking of importance and satisfaction, the first place of importance was coach's professionalism of staff factors, followed by safety of facility factors and program contents and effects of program factors. The first place of satisfaction was cleanliness and management of facility factors, followed by coach's professionalism of staff factors and staff's kindness of staff factors. Second, as a result of the IPA matrix of importance and satisfaction, Quadrant I included appropriateness of training time and program contents and effect of program factors, parking size and cleanliness and management of facility factors, coach's professionalism and staff's service attitude of staff factors, and customer service and complaint resolution of publicity factors. Quadrant II showed appropriateness of price, value for money, and discount policy of price factors and materials and design of goods factors. Quadrant III included excellent customer service of goods of goods factors, various program construction of program factors, court location and accessibility, and various convenient facilities of facility factors, and various publicity and event programs, website construction, and various publicity strategies of publicity factors. Quadrant IV showed brand value of goods, awareness, and brand specialty of goods of goods factors.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.289-297
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• 2022

The purpose of this study was to investigate the perception of dental students based on their experiences of online classes after taking non-face-to-face education courses for all the school semesters in 2020. For the research method, an online survey was conducted on A survey was conducted on 161 dental students enrolled in A University. The analytical method was conducted through frequency analysis, correlation analysis, and multiple regression analysis. The survey analysis findings showed that the satisfaction of dental students' about the non-face-to-face education course was above 4.2, and the detailed items were in the order of the appropriateness of the attendance processing method, satisfaction with recorded video lectures, and the assessment method of the course grade. In the case of the factors that affect the satisfaction of non-face-to-face education courses, the learning system and assessment method were statistically significant. The online class type that is most preferred by the students is recorded video lectures, and the highest number of participants chose 21~30 minutes as the appropriate time for the class content. It is considered that the application of the online system will continue to be used together with face-to-face education courses in the education site and various university-level efforts like systematic support are required to achieve effective learning achievements. This study only investigated the non-face-to-face education operation conditions of A University, so it cannot be generalized to all universities, but it can be used as basic data to provide education curriculum design and supportive measures for the compatibility of face-to-face and non-face-to-face courses.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.75-83
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• 2021

This study presented the analysis results and implications by identifying the structural relationship between the image of food tourism products, the long-term orientation of attachment, and the behavioral intention. The convenience sampling method of the non-probability sampling method was used, and the survey was conducted non-face-to-face due to COVID-19. This study was conducted for customers who live in Jeollabuk-do and Jeollanam-do and have experienced local traditional food. As for the survey method, the main researcher's acquaintances and related experts were consulted and utilized to select the survey subjects, and the survey was conducted by sending/returning them by mail or e-mail. Statistical processing was analyzed using SPSS 25.0 and AMOS 25.0 statistical packages. As a result of the verification, the relationship between the image and attachment of food tourism, the relationship between the long-term orientation in the attachment of traditional food, and the behavioral intention in the attachment of traditional food are significant. A significant positive (+) relationship was formed in the relationship of hypothesis setting according to the research purpose of the relationship.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.877-884
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• 2022

This study was attempted to investigate the effects of psychological safety and physical self-concept on ego-resilience of nursing students. This data collected from September to November 2021 through a structured questionnaire from 166 nursing students at M University in Jeolla Southern Province. For data processing, descriptive statistics, t-test, ANOVA, Scheffe test, Pearson's correlation analysis, and multiple regression analysis were performed using the SPSS 23.0 program. As a result of this study, there were significant positive correlations in the self-resilience of nursing students with psychological stability and physical self-concept(r=.480, p<.001, r=.426, p<.001). The factors affecting the ego-resilience of nursing students were psychological safety(β=0.352, p<.001) and physical self-concept (β=0.236, p<.001), and the explanatory power was 26%. As a result of this study, it is necessary to increase psychological safety and physical self-concept in order to increase the ego-resilience of nursing students. It is necessary to develop and apply guide programs that enhances psychological stability for nursing students, and to provide education and facilities so that they can have a healthy body and mind, not only academics.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.407-418
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• 2023

The Multi-Object Goal Visual Navigation(MultiOn) is a visual navigation task in which an agent must visit to multiple object goals in an unknown indoor environment in a given order. Existing models for the MultiOn task suffer from the limitation that they cannot utilize an integrated view of multimodal context because use only a unimodal context map. To overcome this limitation, in this paper, we propose a novel deep neural network-based agent model for MultiOn task. The proposed model, MCFMO, uses a multimodal context map, containing visual appearance features, semantic features of environmental objects, and goal object features. Moreover, the proposed model effectively fuses these three heterogeneous features into a global multimodal context map by using a point-wise convolutional neural network module. Lastly, the proposed model adopts an auxiliary task learning module to predict the observation status, goal direction and the goal distance, which can guide to learn the navigational policy efficiently. Conducting various quantitative and qualitative experiments using the Habitat-Matterport3D simulation environment and scene dataset, we demonstrate the superiority of the proposed model.

• Journal of the Korea Society for Simulation
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• v.32 no.1
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• pp.35-44
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• 2023

In recent, there are many research cases that analyze trends or research trends with text analysis. When collecting documents by searching for keywords in abbreviations for data analysis, it is necessary to disambiguate abbreviations. In many studies, documents are classified by hand-work reading the data one by one to find the data necessary for the study. Most of the studies to disambiguate abbreviations are studies that clarify the meaning of words and use supervised learning. The previous method to disambiguate abbreviation is not suitable for classification studies of documents looking for research data from abbreviation search documents, and related studies are also insufficient. This paper proposes a method of semi-automatically classifying documents collected by abbreviations by going topic modeling with Non-Negative Matrix Factorization, an unsupervised learning method, in the data pre-processing step. To verify the proposed method, papers were collected from academic DB with the abbreviation 'MSA'. The proposed method found 316 papers related to Micro Services Architecture in 1,401 papers. The document classification accuracy of the proposed method was measured at 92.36%. It is expected that the proposed method can reduce the researcher's time and cost due to hand work.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.105-135
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• 2022

As COVID-19 has led to a surge in e-commerce Buy Now Pay Later(BNPL) has become preferred choice among millennials. In Korea Coupang followed by Naver Pay offers a deferred payment, aiming to create customer lock-in effect, save credit card processing fee and lay the groundwork for entering into new financial services. However the literature related to the influential factors of customers' usage intention toward a deferred payment is scarce. For the study, a multi-group analysis was carried out to find differences between Naver shopping and Coupang. The results revealed that the important factors that affect a deferred payment adoption were compatibility, impulsive buying tendency in Naver shopping, whereas compatibility, relative advantage, additional value in Coupang(listed in order of most important). In addition, impulsive buying tendency had a positive effect on adoption intention in Naver shopping and on perceived risk in Coupang. The results imply that Naver shopping need to focus on managing delinquency while Coupang should provide sufficient information on how late fees and credit rating downgrade work and try not to make a deferred payment option stand out. In order to increase adoption rate it is recommendable to narrow down target segment of a deferred payment and expand it to a specialized vertical such as travel.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.89-95
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• 2024

Nowadays, the competitiveness of a company depends on the ability of all organizational members to share and utilize the organizational knowledge accumulated by the organization. As if to prove this, the world is now focusing on ChetGPT service using generative AI technology based on LLM (Large Language Model). However, it is still difficult to apply the ChetGPT service to work because there are many hallucinogenic problems. To solve this problem, sLLM (Lightweight Large Language Model) technology is being proposed as an alternative. In order to construct sLLM, corporate data is essential. Corporate data is the organization's ERP data and the company's office document knowledge data preserved by the organization. ERP Data can be used by directly connecting to sLLM, but office documents are stored in file format and must be converted to data format to be used by connecting to sLLM. In addition, there are too many technical limitations to utilize office documents stored in file format as organizational knowledge information. This study proposes a method of storing office documents in DB format rather than file format, allowing companies to utilize already accumulated office documents as an organizational knowledge system, and providing office documents in data form to the company's SLLM. We aim to contribute to improving corporate competitiveness by combining AI technology.

• KIPS Transactions on Software and Data Engineering
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• v.13 no.1
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• pp.1-16
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• 2024

Over recent years, 6 Sigma has become a key methodology in manufacturing for quality improvement and cost reduction. However, challenges have arisen due to the difficulty in analyzing large-scale data generated by smart factories and its traditional, formal application. To address these limitations, a big data-based 6 Sigma approach has been developed, integrating the strengths of 6 Sigma and big data analysis, including statistical verification, mathematical optimization, interpretability, and machine learning. Despite its potential, the practical impact of this big data-based 6 Sigma on manufacturing processes and management performance has not been adequately verified, leading to its limited reliability and underutilization in practice. This study investigates the efficiency impact of DX SS, a big data-based 6 Sigma, on manufacturing processes, and identifies key success policies for its effective introduction and implementation in enterprises. The study highlights the importance of involving all executives and employees and researching key success policies, as demonstrated by cases where methodology implementation failed due to incorrect policies. This research aims to assist manufacturing companies in achieving successful outcomes by actively adopting and utilizing the methodologies presented.