• Science of Emotion and Sensibility
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• v.27 no.2
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• pp.69-80
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• 2024

The COVID-19 pandemic highlighted the importance of remote education, yet the adoption rate of AI in the educational sector remains relatively low, and studies into learners' familiarity with using AI learning robots are scarce. In response, this study analyzes the factors influencing users' familiarity with AI learning robots in a smart learning environment tailored to the untact era. To this end, social big data analysis was used to examine changes in public perception and the frequency of mentions of smart learning and AI learning robots. The results showed that positive perceptions of smart learning significantly outweigh negative ones, reflecting the convenience and improved accessibility that technology brings to education. However, there is also a considerable negative perception attached to smartphone use, which is interpreted as reflecting concerns that smartphones may disrupt learning and bring other negative aspects of technology dependence. These results indicate mixed social concerns and expectations regarding the educational use of smart learning and AI technologies. The effective introduction and use of AI learning robots, especially in smart learning environments, necessitate considering these social perceptions. This study provides foundational data for the effective implementation and use of AI learning robots in smart learning environments and suggests the need for approaches that primarily consider users' familiarity and social perceptions in the development of educational technologies.

• The Korean Journal of Franchise Management
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• v.12 no.4
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• pp.41-54
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• 2021

Purpose: Delivery food orders are on the rise due to the COVID 19 pandemic. Many customers are ordering food through delivery apps rather than visiting restaurants to eat out. Delivery application platforms are growing due to the development of O2O. Most of the people who provide gig worker for delivery applications are rider. Rider provides labor on their own terms and have more work flexibility and autonomy than ordinary workers. Trust can be transferred from a well-known entity to an unknown entity. From the customer's point of view of using the delivery application, trust can be seen through the third-party trust of the delivery application platform-rider-customer. Therefore, this study intends to investigate the effect on delivery application trust and rider trust through the well-known characteristics of delivery applications. Research design, data, and methodology: This study was conducted on Korean consumers over 20 years of age who have ordered food through a delivery application for the past month. After educating 5 investigators about the purpose of this study, 60 copies of the survey were conducted per person. During the investigation period, from September 2 to September 26, 2021, 322 copies were collected over 25 days. Among the collected questionnaires, 37 were excluded from insincere or partially unanswered, and 285 were used for analysis. In addition, the collected data were analyzed using SPSS 25.0 and AMOS 25.0. Result: As a result of the study, convenience, price, and variety of restaurants were found to have a significant positive (+) effect on app trust, but design did not have a significant effect on app trust. Also, it was found that convenience had a significant positive (+) effect on trust in rider, but design, price, and variety of restaurants did not have a significant effect. App trust was found to have a significant positive (+) effect on rider trust and intention to use, and it was found to have a significant positive (+) effect on rider trust and intention to use. Conclusions: First, this study established a structural framework between delivery application characteristics-delivery-app trust-rider trust-intention to use. Second, in this study, it was found that customer trust in well-known delivery applications was transferred to less-known rider trust. Third, the delivery application should increase the convenience of use. Fourth, delivery application should set the delivery fee appropriately. Fifth, delivery application must continuously train the rider.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.684-693
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• 2021

Purpose: The purpose is to establish a safe facility environment from abnormal voltages such as lightning by developing a smart land resistance measuring device that can acquire real-time land resistance data using Arduino. Method: This paper studied design models and application cases by developing a land resistance acquisition and analysis system with Arduino and a power line communication (PLC) system. Some sites in the wind power generation complex in Gyeongsangnam-do were selected as test beds, and real-time land resistance data applied with new technologies were obtained. The electrode arrangement adopted a smart electrode arrangement using a combination of a Wenner four electrode arrangement and a Schlumberger electrode arrangement. Result: First, the characteristic of this technology is that the depth of smart multi-electrodes is organized differently to reduce the error range of the acquired data even in the stratigraphic structure with specificity between floors. Second, IT convergence technology was applied to enable real-time transmission and reception of information on land resistance data acquired from smart ground electrodes through the Internet of Things. Finally, it is possible to establish a regular management system and analyze big data accumulated in the server to check the trend of changes in various elements, and to model the optimal ground algorithm and ground system design for the IT convergence environment. Conclusion: This technology will reduce surge damage caused by lightning on urban infrastructure underlying the 4th industrial era and design an optimized ground system model to protect the safety and life of users. It is also expected to secure intellectual property rights of pure domestic technology to create jobs and revitalize our industry, which has been stagnant as a pandemic in the post-COVID-19 era.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.54 no.6
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• pp.880-889
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• 2021

The home meal replacement (HMR) market has attracted significant attention due to COVID-19 pandemic and products that utilize the combination of different processed ingredients are now being developed. In this study, Broughton's ribbed ark Scapharca broughtonii was soaked in seasoned soy sauce with the incorporation of mustard leaf Brassica juncea (M-BRA), which is known to have a unique texture as well as excellent functional properties such as antioxidation, to develop a regional specialty product. The optimal conditions for manufacturing M-BRA from the seasoned soy sauce (the sauce to be added [X₁] and the soaking time [X₂]), were examined using response surface methodology (RSM) to analyze the significance of the salinity (Y₁), amino-N content (Y₂), and overall acceptance (Y₃). The coefficient of determination (R²) between X₁-X₂ and Y₁-Y₃ were close to 1, thereby confirming the suitability of the RSM model. The optimal conditions were seasoned soy sauce addition of 140% and soaking time of 156 min. The M-BRA manufactured under these conditions exhibited superior overall acceptance compared to seasoned commercial soy sauce, which was used as a control. We expect that the market for M-BRA manufactured by combining marine and agricultural materials will expand owing to superior overall acceptance compared with commercial products.

• The Korean Journal of Franchise Management
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• v.13 no.2
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• pp.1-15
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• 2022

Purpose: The globalization of the Korean restaurant franchise industry differs from the business performance of enhancing the brand image and customers' intention to revisit depending on the degree of localization marketing. Therefore, it is necessary to consider the extent to which the localization marketing activities of overseas Korean restaurant franchise companies affect the customer's perception. This study aims to investigate the effects of localization marketing (Localized Menu, Localized Price, Localized Service Experience, Localized Promotion, Localized Physical Environment) of Korean restaurant franchise companies on customer revisit intention. Research design, data, and methodology: For this study, 150 questionnaires using local Korean restaurants in Beijing, China, were analyzed using SPSS Ver.21 and AMOS Ver.22. Result: It was confirmed that the localized menu, localized service experience, and localized physical environment all affect the intention to revisit customers. Based on these verification results, if overseas franchises fully recognize localization marketing, which is an important factor for local business success, and establish localization strategies, they can gain an edge in competition with local Korean restaurants or restaurant franchises founded by locals. There may be a higher probability that However, it was found that localization price and localization promotion had no mediating effect of brand image between revisit intention and revisit intention. It was found that it had no effect on the degree of inquiry and had a negative effect. Conclusions: Due to the impact of the COVID-19 pandemic, there have been many changes in the domestic and overseas food service industry over the past two years. Therefore, in future research, it is necessary to study the localization of overseas Korean restaurant franchise companies that are more multidimensionally subdivided. Various measures of customized localization marketing for optimal regional characteristics should be developed and applied to enhance customer revisiting and brand image of Korean restaurant franchise companies entering overseas. In the future, this study will be meaningful data for the establishment of localization marketing (Localized Menu, Localized Price, Localized Service Experience, Localized Promotion, Localized Physical Environment) strategies for Korean restaurant franchise companies that consider overseas expansion or have already entered.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.3
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• pp.119-133
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• 2022

The COVID-19 pandemic is rapidly changing the behavior of members of society. Typically, the strong contagious power of the virus minimizes interaction between people in the real world, and they keep interaction activities to a minimum through online activities. Recently, as people demand online activities that enhance a sense of reality, the metaverse, which strengthens the 3D technology-centered sense of presence capability, is being chosen by people. The purpose of this study is to suggest a strategic direction for the establishment of the metaverse business model of startups by presenting factors for users' use and gratification of the metaverse. In detail, this study proposes the motivation for using the metaverse by reflecting the uses and gratification theory, and suggests a method to strengthen the motivation for the metaverse by reflecting the presences provided by the metaverse plotform and individual characteristics (normtive interpersonal influence). We surveyed people over 20 years of age who experienced metaverse and obtained 314 samples. In addition, we conducted the main effect analysis using the structural equation model and the moderating effect analysis using Process 3.1. As a result of hypothesis testing, we confirmed that metaverse presence (telepresence, social presence) has a positive effect on intention to continuous use by increasing metaverse's use and satisfaction factors (information, enjoyment, social interactivity). In addition, we found that individuals' normative interpersonal influence moderated the positive relationship between uses and gratification factors(enjoyment and social interactivity) intention to continuous use. Our study suggests strategies for establishing a user-centered business model for companies related to the metaverse.

• The Journal of KAIRB
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• v.3 no.1
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• pp.11-18
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• 2021

Purpose: The purpose of this study is to investigate a satisfaction survey of untact education and platforms that can be used for untact education to provide recommendations on future development of Education of Persons Conducting Clinical Trials. Methods: Online survey was distributed among students who have taken Untact Education of Persons Conducting Clinical Trials. The result was separated according to topic and descriptive statistics was used for analysis. The satisfaction survey used 10-point scale. Results: Of the 1,720 students who received the survey, 1,347 (78.3%) responded to the lecture satisfaction survey. The satisfaction level for broadcasting program (Kakao TV), an untact educational platform for the education of clinical trial workers at Kyung Hee University Medical Center, was relatively high with 8.09±1.99 points. Average score respondents recommending Kyung Hee University Untact Education of Persons Conducting Clinical Trials was 8.03±1.83 and customer recommendation score (Net Promotor Score) was 27.1%. Satisfaction level of the preferred training time was divided into weekday-morning (8-11 AM) (8.16±1.75), weekday-afternoon (12-4 PM) (7.73±2.07), weekday-evening (5-9 PM) (7.78±2.22), and weekend-morning (9-11 AM) real-time untact education (8.48±1.76) and analyzed. There was a noticeable difference between weekend-morning and weekday-afternoon (p<0.0001) and weekend-morning and weekday-evening (p=0.0001) real-time untact education. When asked about conducting education after COVID-19 pandemic ends, 79.2% (1,012 of 1,279) of the respondents answered that they prefer real-time untact education while 20.8 % (266 of 1,279) preferred face-to-face education. Conclusion: Online education, without time and space constraint, is expected to be the mainstream market in Korea for Education of Persons Conducting Clinical. Kyung Hee University Untact Education of Persons Conducting Clinical has achieved above average satisfaction using Kakao TV. Kyung Hee University Real-time Untact Education of Persons Conducting Clinical Net Promotor Score is 27.1%, which is above industry average, communication with trainees should be considered to improve Net Promotor Score.

• Atmosphere
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• v.31 no.5
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• pp.593-606
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• 2021

The Korea Meteorological Administration/National Institute of Meteorological Sciences (KMA/NIMS) has monitored atmospheric CO₂ at Anmyeondo (AMY) World Meteorological Organization (WMO) Global Atmosphere Watch Programme (GAW) regional station since 1999, and expanded its observations at Jeju Gosan Suwolbong station (JGS) in the South and at Ulleungdo-Dokdo stations in the East (ULD and DOK) since 2012. Due to a recent WMO CO₂ scale update and a new filter (NIMS) to select baseline levels at each station, the 22 years of CO₂ data are recalculated. After correction for the new CO₂ scale, we confirmed that those corrected records are reasonable within the compatibility goal (±0.1 ppm of CO₂) between KMA/NIMS and National Oceanic and Atmosphereic Administration (NOAA) flask-air measurements with the new scale. With the new NIMS filter, CO₂ baseline levels are now more representative of the large-scale background compared to previous values, which contained large CO₂ enhancements. Atmospheric CO₂ observed in South Korea is 4 to 8 ppm greater than the global average while the amplitude of seasonal variation is similar (10~13 ppm) to the amplitude averaged over a comparable latitude zone (30°N-60°N). Variations in CO₂ growth rate are also similar, increasing and decreasing similar to global values, as it reflects the net balance between terrestrial respiration and photosynthesis. In 2020, atmospheric CO₂ continued increasing despite the COVID-19 pandemic. Even though fossil emission was reduced (around -7% globally), we still emitted large amounts of anthropogenic CO₂. Overall, since CO₂ has large natural variations and its source was derived from not only fossil fuel but also biomass burning, the small fossil emission reduction could not affect the atmospheric level directly.

• The Journal of Bigdata
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• v.6 no.2
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• pp.17-28
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• 2021

Current development of technologies related to 4^th industrial revolution and the pandemic of COVID-19 lead the rapid expansion of e-marketplace. The level of competition among several companies gets increased by introducing different strategies. To cope with the current change in the market and satisfy the customers who request the better delivery service, the new concept, fulfillment, has been introduced. It makes the leadtime of process from order picking to delivery reduced and the efficiency improved. Still, the efficiency of operation in fulfillment centers constrains the service level of the entire delivery process. In order to solve this problem, several different approaches for demand forecasting and coordinating supplies using Bigdata, IoT and AI, which there exists the trivial limitations. Because it requires the most lead time for operation and leads the inefficiency the process from picking to packing the ordered items, the logistics service providers should try to automate this procedure. In this research, it has been proposed to develop the efficient plans to automate the process to move the ordered items from the location where it stores to stage for packing using AGV and AMR. The efficiency of automated devices depends on the number of items and total number of devices based on the demand. Therefore, the result of simulation based on several different scenarios has been analyzed. From the result of simulation, it is possible to identify the several factors which should be concerned for introducing the automated devices in the fulfillment centers. Also, it can be referred to make the optimal decisions based on the efficiency metrics.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.75-91
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• 2023

As the business-to-customer (B2C) online market expands after the COVID-19 pandemic, the logistics industry has been constructing automated warehouses to handle multi-product, low-volume logistics. When constructing a logistics automation warehouse, it is crucial to validate that the facility's performance and operational logic are designed to meet the required throughput of the automated warehouse from the system design phase. This study proposes simulation-based validation and optimal alternatives for an H logistics automation warehouse in Iksan, Jeollabuk-do. Firstly, we focused on the box supply and packing processes, which are related to the release process, among the entire logistic processes. Then, we analyzed the potential bottlenecks in the target process and designed and implemented a discrete-event simulation model based on the analysis results. The simulation experiments showed that the facility parameters and operational logic identified in the system design phase did not satisfy the performance requirements of the entire automated warehouse. Additional experiments were conducted to suggest alternatives to meet the system performance requirements by changing the facility parameters and operational logic. We expect that the proposed study will be utilized in the future, not only in the system design phase but also in the system construction phase, for verification purposes to ensure that the construction proceeds according to the design.