• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.207-228
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• 2023

After COVID-19, organizations have widely adopted platforms such as zoom or developed their proprietary online real-time systems for remote work, with recent forays into incorporating the metaverse for meetings and publicity. While ongoing studies investigate the impact of avatar customization, expansive virtual environments, and past virtual experiences on participant satisfaction within virtual reality or metaverse settings, the utilization of the metaverse as a dedicated workspace is still an evolving area. There exists a notable gap in research concerning the factors influencing the performance of the metaverse as a workspace, particularly in non-immersive work-type metaverses. Unlike studies focusing on immersive virtual reality or metaverses emphasizing immersion and presence, the majority of contemporary work-oriented metaverses tend to be non-immersive. As such, understanding the factors that contribute to the success of these existing non-immersive metaverses becomes crucial. Hence, this paper aims to empirically analyze the factors impacting personal outcomes in the non-immersive metaverse workspace and derive implications from the results. To achieve this, the study adopts the Embodied Social Presence (ESP) model as a theoretical foundation, modifying and proposing a research model tailored to the non-immersive metaverse workspace. The findings validate that the impact of presence on task engagement and task involvement exhibits a moderating effect based on the metaverse platform used. Following interviews with participants engaged in non-immersive metaverse workplaces (specifically Gather Town and Ifland), a survey was conducted to gather comprehensive insights.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.31-46
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• 2023

This study classified and confirmed the learning modes about start-ups that are based on the accelerator's program which was focusing on the Korean accelerators in the ICT field targeting global market. Eight accelerator practitioners were interviewed who were in charge of operating programs for accelerators, qualitatively analyzing method of the interview was conducted. The interview results to identify various learning modes that accelerators provide to startups through programs. In order to identify and classify learning modes, the researcher reviewed various prior documents and using categories of experience accumulation, observation, experimentation, trial and error, and improvisation as a priori code for the qualitative analysis. The interview results were analyzed through a subject analysis. As the result of the study, the learning modes offered by the accelerator's programs to startups were confirmed, with two subcategories identified for each of the five categories: experiential, learning from others, experimental, trial and error, and improvisation. Given the limited research on accelerator programs and their main function, the main function of accelerators, this study identified the types of learning modes that offered by the accelerator's programs to startups from the perspective of learning. This study provides important insights into the types of learning modes that offered by the accelerator programs, which can help to improve our understanding of how accelerators support organizational learning for startups. Additionally, this information can be useful for startups considering in participating in the accelerator programs, as it can help them making informed decisions about their involvement.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.2
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• pp.21-34
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• 2023

The purpose of this study is to examine the extent of Sustainable Development Goals (SDGs)-related research in the field of entrepreneurship globally since the adoption of the SDGs at the UN General Assembly, and to compare international and domestic research trends in order to determine the direction of SDGs-related research in entrepreneurship in Korea. Utilizing three databases-Web of Science (WoS), KCI, and DBpia- SDGs-related studies in entrepreneurship were extracted by employing specific search terms. After data purification, a total of 356 studies abroad and 4 studies in Korea were used for analysis. After data purification, a total of 356 international studies and 4 Korean studies were analyzed. Due to the limited number of domestic studies, the research trends were examined by conducting frequency analysis and keyword network analysis on international studies alone. Frequency analysis revealed that SDGs research in entrepreneurship primarily focused on sustainability-related terms and was conducted in conjunction with business models, innovation, entrepreneurship education, and strategies. Furthermore, yearly frequency analysis demonstrated an expansion of topics to encompass research on entrepreneurship and SDGs policies, the roles and capabilities of female entrepreneurs in SDGs implementation, energy start-ups and SDGs, directions for implementing SDGs in business schools and SDGs education, indicators for SDGs implementation and evaluation, and technologies for sustainability. The keyword network analysis identified central topics such as business, sustainability, SDGs, innovation, entrepreneurship, business models, and education, with research areas extending to entrepreneurship ecosystems, change and strategy, ethics, and climate. This study holds significance in establishing a foundation for SDGs research in entrepreneurship, which is currently an underexplored area in Korea, by presenting emerging research trends related to SDGs in entrepreneurship.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.2
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• pp.34-44
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• 2024

Recently, due to abnormal climate caused by climate change, natural disasters such as floods, landslides, and soil outflows are rapidly increasing. In Korea, more than 63% of the land is vulnerable to slope disasters due to the geographical characteristics of mountainous areas, and in particular, Quarry mines soil and rocks, so there is a high risk of landslides not only inside the workplace but also outside.Accordingly, this study built a DEM using UAV and aviation LiDAR for monitoring the quarry, conducted a time series change analysis, and proposed an optimal DEM construction method for monitoring the soil collection site. For DEM construction, UAV and LiDAR-based Point Cloud were built, and the ground was extracted using three algorithms: Aggressive Classification (AC), Conservative Classification (CC), and Standard Classification (SC). UAV and LiDAR-based DEM constructed according to the algorithm evaluated accuracy through comparison with digital map-based DEM.

• Journal of Digital Policy
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• v.3 no.2
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• pp.1-14
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• 2024

The purpose of this study was to analyze the effect of SNS marketing characteristics on hair shop image formation and visit intention in the hair beauty industry. SNS marketing is a strategy to carry out marketing activities through interaction with customers, information provision, information trust, and playfulness using modern social media platforms. It was intended to analyze how these characteristics of SNS marketing affect the formation of hair shop images and visit intention to customers in the hair beauty industry. For the study, a total of 307 customers with experience using hair-related SNS were surveyed. The questionnaire included items related to SNS marketing characteristics, hair shop images, and visit intention, and the collected data was statistically analyzed using SPSS 26.0. The results of the research problem were derived by applying analysis methods such as frequency analysis, factor analysis, reliability analysis, correlation analysis, simple regression analysis, multiple regression analysis, and mediated regression analysis. As a result of the study, it was found that information provision, information reliability, playfulness, and interaction, which are characteristics of SNS marketing, have a positive effect on the formation of hair shop images. In addition, it was confirmed that the hair shop image had a positive effect on the intention to visit. In addition, it was found that the hair shop image plays a mediating role between the SNS marketing characteristics and the intention to visit. This provides important insights that can improve image formation and customer visit intention in the hair beauty industry through SNS marketing.

• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.199-207
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• 2024

Local reservoirs are crucial sources for agricultural water supply, necessitating stable water level management to prepare for extreme climate conditions such as droughts. Water level prediction is significantly influenced by local climate characteristics, such as localized rainfall, as well as seasonal factors including cropping times, making it essential to understand the correlation between input and output data as much as selecting an appropriate prediction model. In this study, extensive multivariate data from over 400 reservoirs in Jeollabuk-do from 1991 to 2022 was utilized to train and validate a water level prediction model that comprehensively reflects the complex hydrological and climatological environmental factors of each reservoir, and to analyze the impact of each input feature on the prediction performance of water levels. Instead of focusing on improvements in water level performance through neural network structures, the study adopts a basic Feedforward Neural Network composed of fully connected layers, batch normalization, dropout, and activation functions, focusing on the correlation between multivariate input data and prediction performance. Additionally, most existing studies only present short-term prediction performance on a daily basis, which is not suitable for practical environments that require medium to long-term predictions, such as 10 days or a month. Therefore, this study measured the water level prediction performance up to one month ahead through a recursive method that uses daily prediction values as the next input. The experiment identified performance changes according to the prediction period and analyzed the impact of each input feature on the overall performance based on an Ablation study.

• Journal of Industrial Convergence
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• v.22 no.5
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• pp.11-21
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• 2024

In the steel industry, there is a perception that "collusion has become a long-standing practice" and it is expected that the authorities' legal response to collusion will be strengthened in the future. This necessarily requires improving the accuracy of the legal response, the most important of which is to accurately identify whether the allegedly colluding firms actually did collude. This study focuses on the recent iron scrap price-fixing case and examines whether a single accused firm actually engaged in price-fixing in a situation where there is a mix of firms that acted independently of the collusion and firms that actually engaged in price-fixing. The results of the analysis allow us to infer that the accused steelmaker did not actually collude, which is consistent with the authorities' final judgment against the steelmaker. In the real world, some collusions are carried out by only a subset of firms in a market, and in these cases, there are often disputed firms as to whether or not they carried out the collusion. This study can serve as an analytic guide for industries, including the steel industry, to verify the behavior of individual firms, especially those whose collusive practices are disputed.

• Journal of the Korean Society of Radiology
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• v.18 no.2
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• pp.171-177
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• 2024

In this study, two general X-ray device, CT, and MRI inspection devices were selected from general hospitals in the Daejeon area and an experiment was conducted to predict the level of infection by measuring the surface contamination of the inspection devices at different times and to use it as basic data for infection prevention. As a result, the surface contamination level by time zone for general X-ray devices and MRI examination devices was in the order of 13H > 8H > 16H, and for CT examination devices, it was 13H > 16H > 8H, which appeared to be influenced by the number of tests. In addition, the surface contamination results for each part of the test device showed that the highest ATP contamination value was found on the stand bucky handle for the general X-ray device, the headrest for the CT examination device, and the operation switch for the MRI examination device, which was closely related to the number of contacts. As a result of comparing before and after disinfection, all devices showed a significant decrease after disinfection. Based on the results of the experiment, it is believed that it can be used as basic data to identify the level of contamination in radiology laboratories and prevent infectious diseases.

• Food Science and Preservation
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• v.30 no.6
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• pp.999-1011
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• 2023

This study investigated the anti-inflammatory, trypsin activity, and antioxidant effects of 11 kinds of plant extracts to discover materials for developing optimal mixtures that improve inflammation and help digestion. Ziziphus jujuba Mill. (ZJ), Leonurus japonicus Houtt. (LJ), Scutellaria baicalensis (SB), Platycodon grandiflorum, and Aster scaber extracts had excellent anti-inflammatory effects by reducing excessive nitric oxide (NO) and tumor necrosis factor-α content in lipopolysaccharide (LPS)-stimulated RAW264.7 macrophages. The malt (MA), Pyrus pyrifolia Nakai (PP), Raphanus sativus L., Platycodon grandiflorum extracts among the 11 kinds of plant extracts had high trypsin activity. The antioxidant activity of the plant extracts was examined by the DPPH radical scavenging activity, and the SB, PE, JU, and MA extracts had high antioxidant activity. Therefore, PP, MA, ZJ, LJ, and SB were selected to develop optimal mixtures that improve inflammation and help digestion. The extract of plant mixture containing PP, MA, ZJ, LJ, and SB in the ratio 1:1:2:1:2 (w/w) significantly inhibited NO production than the extract of PP, MA, ZJ, LJ, and SB, respectively, in LPS-stimulated RAW 264.7 macrophages. The DPPH radical scavenging activity of the mixture extract was significantly higher than the extract of PP, MA, ZJ, and LJ, respectively.

• Journal of the Korean Applied Science and Technology
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• v.40 no.6
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• pp.1498-1505
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• 2023

This study attempted to investigate the difference in service orientation according to the individual characteristics of hair salon workers, and to identify the internal marketing factors of hair salon that influence service orientation. Questionnaires for empirical research were collected from hair salon workers in Gyeongnam, and the results of analyzing the collected questionnaires through IBM SPSS Statistics 26 are as follows. First, as a result of analyzing the difference in service orientation according to the individual characteristics of hair salon workers, the '40s or older' group and the 'working period of 10 years or longer' group showed statistically higher service orientation than other groups. Second, as a result of analyzing the causal relationship between internal marketing and service orientation, it was found that welfare, compensation system, education and training of internal marketings had the statistical effect on service orientation, and in particular, the compensation system had the strongest effect on service orientation. Therefore, service orientation for customers should be improved through internal marketing activities that take into account the individual characteristics of hair salon workers. The improvement of service orientation means the customer's intention to reuse, suggesting that ultimately the management performance of hair salon companies can be further improved.