• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.36 no.4
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• pp.105-112
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• 2018

This study aims to apply 3D scanning technology to the field of landscape planning design. Through this, 3D scans were conducted on Soswaewon Garden and Seongrakwon Gardens to find directions for traditional landscape planning and designs. The results as follows. First, the actual measurement of the traditional garden through a 3D scan confirmed that a precise three-dimensional modeling of ${\pm}3-5mm$ error was constructed through the merging of coordinate values based on point data acquired at each observation point and postprocessing. Second, as a result of the 3D survey, the Soswaewon Garden obtained survey data on Jewoldang House, Gwangpunggak Pavilion, the surrounding wall, stone axis, and Aeyangdan wall, while the Seongnakwon Garden obtained survey data on the topography, rocks and waterways around the Yeongbyeokji pond area. The above data have the advantage of being able to monitor the changing appearance of the garden. Third, spatial information developed through 3D scans could be developed with a three-dimensional drawing preparation and inspection tool that included precise real-world data, and this process ensured the economic feasibility of time and manpower in the actual survey and investigation of landscaping space. In addition, modelling with a three-dimensional 1:1 scale is expected to be highly efficient in that reliable spatial data can be maintained and reprocessed to a specific size depending on the size of the design. In addition, from a long-term perspective, the deployment of 3D scan data is easy to predict and simulate changes in traditional landscaping space over time.

• Management & Information Systems Review
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• v.37 no.4
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• pp.41-62
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• 2018

As the volume of unstructured data increases through various social media, Internet news articles, and blogs, the importance of text analysis and the studies are increasing. Since text analysis is mostly performed on a specific domain or topic, the importance of constructing and applying a domain-specific dictionary has been increased. The quality of dictionary has a direct impact on the results of the unstructured data analysis and it is much more important since it present a perspective of analysis. In the literature, most studies on text analysis has emphasized the importance of dictionaries to acquire clean and high quality results. However, unfortunately, a rigorous verification of the effects of dictionaries has not been studied, even if it is already known as the most essential factor of text analysis. In this paper, we generate three dictionaries in various ways from 39,800 news articles and analyze and verify the effect each dictionary on the accuracy of document classification by defining the concept of Intrinsic Rate. 1) A batch construction method which is building a dictionary based on the frequency of terms in the entire documents 2) A method of extracting the terms by category and integrating the terms 3) A method of extracting the features according to each category and integrating them. We compared accuracy of three artificial neural network-based document classifiers to evaluate the quality of dictionaries. As a result of the experiment, the accuracy tend to increase when the "Intrinsic Rate" is high and we found the possibility to improve accuracy of document classification by increasing the intrinsic rate of the dictionary.

• The Korean Journal of Franchise Management
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• v.12 no.1
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• pp.21-34
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• 2021

Purpose: This study examines the structural relationship between perceived quality, relationship quality, and revisit intention in the context of coffee shop. In this model, perceived quality consists of product, service, and experience quality, and relationship quality consists of satisfaction, trust, and commitment, and performance consists of revisit intention. More specially, this study identifies whether perceived quality plays a mediating role in the relationship between perceived quality and relationship quality and the direct/indirect effects of perceive quality on intention to revisit. Research design, data and methodology: The survey was conducted from September 1 to 30, 2019. The data were collected from 320 respondents and analyzed using structural equation modeling (SEM) with AMOS program. Results: The findings are as follows. First, quality perception of coffee specialty stores had a statistically positive effect on relationship quality, indicating supports H1. Therefore, customers can know that they are aware of the quality of coffee specialty stores, including quality of service and experience as well as products, and that they form relationship quality with coffee specialty stores. Second, relationship quality between coffee shops and customers had a significant positive effect on performance. Thus, H2 was supported. The results show that if the coffee shop does not consider relationship quality as important, customer loyalty decreases, the number of customers decreases, and the number of customers who switch to another coffee shop increases, which can lead to a threat to the coffee shop. Third, in the case of hypothesis H3, it was found that there was a partial mediating effect of satisfaction and trust between quality perception and reuse intention of coffee specialty stores, so hypothesis H3 was partially supported. As commitment appears to have no mediating effect, it can be said that customers who use coffee shops are not only difficult to maintain as regular customers of a particular coffee shop, but also have ample room to move to other coffee shops. Conclusions: Although many scholars point out the importance of service quality, few studies were conducted in the context of the Korean food service industry (including coffee shops). From this perspective, this study tested several hypotheses that the quality (product, service, experience) perceived by customers can have a positive effect on relationship quality and performance (re-visit intention), either directly or indirectly. The findings of this study demonstrate that if the manager of a coffee shop understands the characteristics of quality perceived by customers and the role of relationship quality, the effect of quality perceptions on customers can be maximized in order to maintain the relationship with customers.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.609-625
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• 2021

It has now been more than a year since the start of the COVID-19 pandemic in Korea, which has claimed thousands of lives and changed every aspect of life. The corona pandemic not only caused physical damages but also psychological one which is a collective social stress phenomenon often termed as 'corona blue'. The purpose of this study is to examine how empathy affects anxiety and depression through risk perception and indirect trauma, which are psychological variables related to the corona pandemic as a disaster. The survey data from 214 people were analyzed with a structural equation modelling. The results shows that 53.3 % of the participants experienced anxiety and 35.7% suffered from depression, which were about 6 times higher than ones from the 2019 government data. Affective empathy had a significant effect on risk perception, and cognitive empathy had a significant effect on indirect trauma. Risk perception and indirect trauma both had a significant effect on anxiety, and anxiety had a significant impact on depression. Only cognitive empathy had a significant indirect effect on anxiety and depression. This study provides an important insight into understanding a social phenomenon of 'corona blue' from a empathic perspective.

• The Journal of Engineering Geology
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• v.33 no.2
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• pp.323-334
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• 2023

The vast volumes of data that are generated during site characterization and associated research for the disposal of high-level radioactive waste require effective data management to properly chronicle and archive this information. The Swedish Nuclear Fuel and Waste Management Company, SKB, established the SICADA database for site selection, evaluation, analysis, and modeling. The German Federal Company for Radioactive Waste Disposal, BGE, established ArbeitsDB, a database and document management system, and the ELO data system to manage data collected according to the Repository Site Selection Act. The U.K. Nuclear Waste Services established the Data Management System to manage any research and survey data pertaining to nuclear waste storage and disposal. The U.S. Department of Energy and Office of Civilian Radioactive Waste Management established the Technical Data Management System for data management and subsequent licensing procedures during site characterization surveys. The presented cases undertaken by these national agencies highlight the importance of data quality management and the scalability of data utilization to ensure effective data management. Korea should also pursue the establishment of both a data management concept for radioactive waste disposal that considers data quality management and scalability from a long-term perspective and an associated data management system.

• The Korean Journal of Franchise Management
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• v.9 no.3
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• pp.19-29
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• 2018

Purpose - Due to the increase in coffee consumption and competition, domestic coffee franchise companies are currently entering the overseas market. Therefore, coffee franchise companies are pursuing a variety of marketing strategies to meet customer needs and gain competitive advantage in overseas markets. From this perspective, overseas franchise companies need to ensure that their servicescapes meet the needs of their overseas customers. For these purposes, the study is to identify the impact servicescapes on customer satisfaction and customer loyalty focused on Global Coffee Franchise Company "C", which extended its business worldwide in Mongolia. Research design, data, and methodology - The data were collected from customers who had visited the stores of 'C' company in Ulaanbaatar, Mongolia. 435 valid questionnaires collected through online survey coded and analyzed using frequency, confirmatory factor analysis, correlations analysis, and structural equation modeling with SPSS 24 and SmartPLS 3.0. Result - Firstly, seating comfort, facility aesthetics, and cleanliness, ambient conditions among servicescapes influenced customer satisfaction. Secondly, servicescapes didn't affect the loyalty directly. Third, customer satisfaction had positive effect on loyalty. Fourthly, cleanliness which was ranked lower in Korea had a great effect on customer satisfaction in Mongolia. Fifthly, IPMA(Importance-performance map analysis) shows that the importance of servicescapes is higher for women than for men, and facility aesthetics for female and cleanliness is the most important for male. Conclusions - The results of this study show that there is a positive (+) effect on customer satisfaction in order of cleanliness, ambient conditions, aesthetics, and seating comfort. Therefore, franchise companies considering or advancing into Mongolia should consider importance in order of cleanliness, ambient conditions and aesthetics when entering Mongolia market. For example, franchise managers should select Monday as a "clean day," and all merchants should spend all of their open hours and keep their stores clean in accordance with the head office manual. In addition, franchise managers need to hire a VMD (visual merchandising) experts to build up a physical environment that will effectively highlight the space-specific display of the store so that Mongolian local customers can have a satisfactory climate and aesthetics. And, the IMPA analysis between servicescapes and customer satisfaction shows that women are more susceptible to servicescapes than men. Especially, in the case of women, the importance of esthetics is high, but the performance is low. Thus, if the aesthetics are actively improved, customer satisfaction can be effectively increased.

• Journal of Venture Innovation
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• v.6 no.4
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• pp.153-170
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• 2023

Generative AI services, including ChatGPT, were becoming increasingly active. This study aimed to empirically analyze the factors that promoted and hindered the diffusion of such services from a consumer perspective. Accordingly, a research model was developed based on the Value-based Adoption Model (VAM) framework, addressing both benefit and sacrifice factors. Benefits identified included usefulness and enjoyment, while sacrifices were security and hallucination. The study analyzed how these factors affected the intention to use generative AI services. A survey was conducted among college students for empirical analysis, and 200 valid responses were analyzed. The analysis utilized structural equation modeling with AMOS 24. The empirical results showed that usefulness and enjoyment had a significant positive impact on perceived value, while security and hallucination had a significant negative impact. The order of influence on perceived value was usefulness, hallucination, security, and then enjoyment. Perceived value had a significant positive impact on usage intention. Moreover, perceived value was found to mediate the relationship between usefulness, enjoyment, security, hallucination, and the intention to use generative AI services. These findings expanded the research horizon academically by validating the effectiveness of generative AI services based on existing models and demonstrated the continued importance of usefulness in a practical context.

• Journal of Drive and Control
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• v.20 no.4
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• pp.115-122
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• 2023

This study utilized a discrete element method (DEM) simulation, as one of the virtual field trials, to predict the impact of tillage depth on the rotary blade shaft during rotavator tilling. The virtual field for the simulation was generated according to soil properties observed in an actual field. Following the generation of particles for the virtual field, a sequence of calibration steps followed to align the mechanical properties more closely with those of real soil. Calibration was conducted with a focus on bulk density and shear torque, resulting in calibration errors of just 0.02% for bulk density and 0.52% for shear torque. The prediction of the load on a rotary tiller's blade shaft involved a three-pronged approach, considering shaft torque, draft force, and vertical force. In terms of shaft torque, the values exhibited significant increases of 42.34% and 36.91% for every 5-centimeter increment in tillage depth. Similarly, the vertical force saw substantial growth by 40.41% and 36.08% for every 5-centimeter increment. In contrast, the variation in draft force based on tillage depth was comparatively lower at 18.49% and 0.96%, indicating that the effect of tillage depth on draft force was less pronounced than its impact on shaft torque and vertical force. From a perspective of agricultural machinery research, this study provides valuable insights into the DEM soil modeling process, accounting for changes in soil properties with varying tillage depths. These findings are expected to be instrumental in future agricultural machinery design studies.

• Journal of Korea Water Resources Association
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• v.56 no.spc1
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• pp.1007-1014
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• 2023

Two-dimensional flow analysis, a fundamental component of hydrodynamics, plays a pivotal role in numerically simulating fluid behavior in rivers and waterways. This modeling approach heavily relies on parameters such as eddy viscosity and roughness coefficient to accurately represent flow characteristics. Therefore, combination of appropriate parameters is very important to accurately simulate flow characteristics. In this study, an automation algorithm was developed and applied to find the optimal combination of parameters. Previously, when applying a two-dimensional flow analysis model, former researchers usually depend on the empirical approach, which causes many difficulties in finding optimal variable values. Using the experimental data, we tracked errors according to the combination of various parameters and applied the algorithm that can determine the optimal combination of parameters with the Python language. The automation algorithm can easily determine the most accurate combination by comparing the flow velocity error values among the two-dimensional flow analysis results among the combinations of 121 (11×11) parameters. In the perspective of utilizing automation algorithm, there is an expected high utility in promptly and straightforwardly determining the optimal combination of parameters with the smallest error.

• Information Systems Review
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• v.25 no.3
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• pp.99-120
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• 2023

Courier services users' experience of violating privacy affects psychology and behavior of protecting personal privacy. Depending on what privacy infringement experience (PIE) of courier services users, learning about perceived privacy infringement incidents is made, recognition is formed, affection is formed, and behavior is appeared. This paradigm of changing in privacy psychologies of courier services users has an important impact on predicting responses of privacy protective action (PPA). In this study, a theoretical research framework are developed to explain the privacy protective action (PPA) of courier services users by applying attitude theory. Based on this framework, the relationships among past privacy infringement experience (PIE), perceived privacy risk (PPR), privacy concerns (i.e., concerns in unlicensed secondary use (CIUSU), concerns in information error (CIE), concerns in improper access (CIA), and concern in information collection (CIC), and privacy protective action (PPA) are analyzed. In this study, the proposed research model was surveyed by people with experience in using courier services and was analyzed for finding relationships among research variables using structured an equation modeling software, SMART-PLS. The empirical results show the causal relationships among PIE, PPR, privacy concerns (CIUSU, CIE, CIA, and CIC), and PPA. The results of this study provide useful theoretical implications for privacy management research in courier services, and practical implications for the development of courier services business model.