• Journal of the Korea Fashion and Costume Design Association
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• v.26 no.2
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• pp.115-127
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• 2024

This study was initiated by focusing on the characteristics of 3D virtual clothing utilized by fashion brands aiming for sustainability. The purpose of this study is to analyze the characteristics of fashion brands that utilize 3D virtual imagery to mitigate environmental pollution caused by the fashion industry from the perspective of green design. The research methodology draws on green design literature and analyzes three hypothetical cases. These include experiential immersive design, design that rewards engagement, and design that delivers economic benefits that were utilized by fashion brands from 2019 to 2023. The findings and conclusions are as follow. First, the for the commercialization of virtual clothing, offline stores are reproduced in the digital world to provide an immersive shopping experience, similar to reality. These promote fashion products in a virtual space without the constraints of space and time, and creates profits and sustainable value. Second, virtual clothing promotes playfulness. Games and events utilize branded virtual worlds and characters to attract users. Rewards are given for achieving goals, and it is a practice of green marketing that uses virtual items to express products and minimize resource waste. Third, virtual clothing is affordable and can reduce the financial burden on consumers by digitally reproducing expensive products as physical brand collections at an acceptable price point. This reduces environmental pollution, saves physical resources, and increases the utilization of virtual clothing by providing a convenient way to purchase. This study is a basic study that examines the current status and characteristics of fashion brands' use of 3D virtual imagery from the perspective of green design based on literature and case analysis, and follow-up studies are expected on empirical virtual imagery activation measures through interviews or surveys with users for each case.

• The Korean Journal of Pesticide Science
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• v.8 no.3
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• pp.151-161
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• 2004

Three dimensional quantitative structure-activity relationships (3D-QSAR) studies for the protox inhibition activities against root and shoot of rice plant (Orysa sativa L.) and barnyardgrass (Echinochloa crus-galli) by a series of new A=3,4,5,6-tetrahydrophthalimino, B=3-chloro-4,5,6,7-tetrahydro-2H-indazolyl and C=3,4-dimethylmaleimino group, and R-group substituted on the phenyl ring in 1-(5-methyl-3-phenylisoxazolin-5-yl)methoxy-2chloro-4-fluorobenzene derivatives were performed using comparative molecular field analyses (CoMFA) methodology with Gasteiger-Huckel charge. Four CoMFA models for the protox inhibition activities against root and shoot of the two plants were generated using 46 molecules as training set and the predictive ability of the each models was evaluated against a test set of 8 molecules. And the statistical results of these models with combination (SIH) of standard field, indicator field and H-bond field showed the best predictability of the protox inhibition activities based on the cross-validated value $r^2_{cv.}$ $(q^2=0.635\sim0.924)$, conventional coefficient $(r^2_{ncv.}=0.928\sim0.977)$ and PRESS value $(0.091\sim0.156)$, respectively. The activities exhibited a strong correlation with steric $(74.3\sim87.4%)$, electrostatic $(10.10\sim18.5%)$ and hydrophobic $(1.10\sim8.30%)$ factors of the molecules. The steric feature of molecule may be an important factor for the activities. We founded that an novel selective and higher protox inhibitors between the two plants may be designed by modification of X-subsitutents for barnyardgrass based upon the results obtained from CoMFA analyses.

• Journal of Environmental Impact Assessment
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• v.27 no.4
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• pp.367-377
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• 2018

A cultural ecosystem service(CES), which is non-material benefit that human gains from ecosystem, has been recently further recognized as gross national income increases. Previous researches proposed to quantify the value of CES, which still remains as a challenging issue today due to its social and cultural subjectivity. This study proposes new way of assessing CES which is called Cultural Service Opportunity Spectrum(CSOS). CSOS is accessibility based CES assessment methodology for regional scale and it is designed to be applicable for any regions in Korea for supporting decision making process. CSOS employed public spatial data which are road network and population density map. In addition, the results of 'Rapid Assessment of Natural Assets' implemented by National Institute of Ecology, Korea were used as a complementary data. CSOS was applied to Namyangju-si and the methodology resulted in revealing specific areas with great accessibility to 'Natural Assets' in the region. Based on the results, the advantages and limitations of the methodology were discussed with regard to weighting three main factors and in contrast to Scenic Quality model and Recreation model of InVEST which have been commonly used for assessing CES today due to its convenience today.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.91-107
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• 2023

Lean startup is a concept that combines the words "lean," meaning an efficient way of running a business, and "startup," meaning a new business. It is often cited as a strategy for minimizing failure in early-stage businesses, especially in software-based startups. By scrutinizing the case of a startup L, this study suggests that lean startup methodology(LSM) can be useful for hardware and manufacturing companies and identifies ways for early startups to successfully implement LSM. To this end, the study explained the core of LSM including the concepts of hypothesis-driven approach, BML feedback loop, minimum viable product(MVP), and pivot. Five criteria to evaluate the successful implementation of LSM were derived from the core concepts and applied to evaluate the case of startup L . The early startup L pivoted its main business model from defecation alert system for patients with limited mobility to one for infants or toddlers, and finally to a smart bottle for infants. In developing the former two products, analyzed from LSM's perspective, company L neither established a specific customer value proposition for its startup idea and nor verified it through MVP experiment, thus failed to create a BML feedback loop. However, through two rounds of pivots, startup L discovered new target customers and customer needs, and was able to establish a successful business model by repeatedly experimenting with MVPs with minimal effort and time. In other words, Company L's case shows that it is essential to go through the customer-market validation stage at the beginning of the business, and that it should be done through an MVP method that does not waste the startup's time and resources. It also shows that it is necessary to abandon and pivot a product or service that customers do not want, even if it is technically superior and functionally complete. Lastly, the study proves that the lean startup methodology is not limited to the software industry, but can also be applied to technology-based hardware industry. The findings of this study can be used as guidelines and methodologies for early-stage companies to minimize failures and to accelerate the process of establishing a business model, scaling up, and going global.

• Journal of Distribution Science
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• v.14 no.5
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• pp.115-123
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• 2016

Purpose - Nowadays the competition between companies has been intensified in the aviation industry. It is hard to maintain successful market share in challenging managerial environment. Not long ago, a Korean major aviation company had faced social condemnation cause of managerial staff's immoral behaviors. That company suffers great losses in company brand value in terms of authenticity as an aviation company. This research tried to show the effect of brand authenticity in the aviation industry. First of all, this research tried to define the dimensions of the brand authenticities based on the former researches. This research suggested the airline brand authenticities as three kinds of dimensions. The dimensions of authenticities consist of performance aspects, symbolic aspects and moral aspects. And this research also tried to show the relationships between brand authenticities and consumers attitudes. Research design, data and methodology - The empirical research design is based on the experiments with six types of advertisement prototypes. The advertisement prototypes were based on three types of authenticities' characteristics. The prototypes were made of core statements about each authenticity. And the advertisement prototypes also were based on the aviation company types. The types of aviation companies could be divided into FSC(full service carrier)and LCC(low cost carrier). So the whole experiments were performed with six kinds of advertisement prototypes(3 brand authenticities X 2 aviation company types). The age of participants were from 20s to 40s. The proportion of participants' demographics are as follow. Age proportion is 50% of 20s and 50% of 30s and 40s. Gender proportion is 46% males and 54% females. The experiments performed through mobile devices. Advertisement prototypes were exposed to the participants through their mobile devices, and they answered the questionnaires. All the process of experiments were performed by a professional research firm to maintain the quality of data. Results - This research suggested some important outcomes as follow. First, brand authenticity had an important role to make a positive consumer attitude on the aviation company. All the three types advertisement of authenticities had a positive impact on the consumer attitude for the aviation company. Second, the three types of brand authenticities in the performance aspects, symbolic aspects, and moral aspects had a major impact on the consumers attitudes. The performance authenticity had the biggest effect on the consumer attitudes. Third, the types of aviation companies like FSC and LCC had a different correlation with types of authenticities. All the types of authenticities affected on the consumers attitudes in the FSC case. The symbolic authenticity had the biggest effect in the FSC case. But the performance authenticity showed the most striking effect in the LCC case. Conclusion - From this research, we can get a conclusion. The brand authenticity of aviation company should be managed carefully to maintain a positive brand image and consumers attitudes. And airline brand authenticities can be consist of three type dimensions. All the types of authenticities affects on the consumers attitudes positively. The symbolic authenticity affects more in the FSC case, and the performance authenticity influences more in the LCC case.

• Fire Science and Engineering
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• v.30 no.3
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• pp.73-78
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• 2016

The Installation, Maintence, and Safety Control of Fire-fighting Systems Act of South Korea regulates that over 30-storey high-rise buildings including underground spaces should vitally perform the Performance-based Design to minimize property damage and personal injury as a fire risk assessment in advance. Therefore a PBD designer such as a fire safety professional engineer evaluate occupant's life safety by a scientific methodology. In order to evaluate the life safety, fire safety designers calculate the Required Safety Egress Time (RSET) which does not have the legal criteria regarding the standard method of calculation yet. So this way has been showing different results depending upon the designer's choice, knowledges and experiences. In this study, RSET calculation methods by six designers respectively were analysed from the thirteen reports of real performance based design projects conducted in Busan for a last five years. In particular, the Response Time calculation methods which have the most powerful effect for figuring the RSET are compared with the other designer's to deduce an error value.

• Journal of Distribution Science
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• v.15 no.6
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• pp.77-96
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• 2017

Purpose - This study aims to develop correspondence strategies to the environment change in domestic retail store types. Recently, new types of retails have emerged in retail industries. Therefore, trade area platform has developed focusing on the speed of data, no longer trade area from district border. Besides, 'trade area smart' brings about change in retail types with the development of giga internet. Thus, context shopping is changing the way of consumers' purchase pattern through data capture, technology capability, and algorithm development. For these reasons, the sales estimation model has been shown to be flawed using the notion of former scale and time, and it is necessary to construct a new model. Research design, data, and methodology - This study focuses on measuring retail change in large multi-shopping mall for the outlook for retail industry and competition for trade area with the theoretical background understanding of retail store types and overall domestic retail conditions. The competition among retail store types are strong, whereas the borders among them are fading. There is a greater need to analyze on a new model because sales expectation can be hard to get with business area competition. For comprehensive research, therefore, the research method based on the statistical analysis was excluded, and field survey and literature investigation method were used to identify problems and propose an alternative. In research material, research fidelity has improved with complementing research data related with retail specialists' as well as department stores. Results - This study analyzed trade area survival and its pattern through sales estimation and empirical studies on trade areas. The sales estimation, based on Huff model system, counts the number of households shopping absorption expectation from trade areas. Based on the results, this paper estimated sales scale, and then deducted modified probability model. Conclusions - In times of retail store chain destruction and off-line store reorganization, modified Huff model has problems in estimating sales. Transformation probability model, supplemented by the existing problems, was analyzed to be more effective in competitiveness business condition. This study offers a viable alternative to figure out related trade areas' sale estimation by reconstructing new-modified probability model. As a result, the future task is to enlarge the borders from IT infrastructure with data and evidence based business into DT infrastructure.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.639-647
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• 2011

In this paper, we introduce a design methodology of data-centroid Radial Basis Function neural networks with extended polynomial function. The two underlying design mechanisms of such networks involve K-means clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on K-means clustering method for efficient processing of data and the optimization of model was carried out using PSO. In this paper, as the connection weight of RBF neural networks, we are able to use four types of polynomials such as simplified, linear, quadratic, and modified quadratic. Using K-means clustering, the center values of Gaussian function as activation function are selected. And the PSO-based RBF neural networks results in a structurally optimized structure and comes with a higher level of flexibility than the one encountered in the conventional RBF neural networks. The PSO-based design procedure being applied at each node of RBF neural networks leads to the selection of preferred parameters with specific local characteristics (such as the number of input variables, a specific set of input variables, and the distribution constant value in activation function) available within the RBF neural networks. To evaluate the performance of the proposed data-centroid RBF neural network with extended polynomial function, the model is experimented with using the nonlinear process data(2-Dimensional synthetic data and Mackey-Glass time series process data) and the Machine Learning dataset(NOx emission process data in gas turbine plant, Automobile Miles per Gallon(MPG) data, and Boston housing data). For the characteristic analysis of the given entire dataset with non-linearity as well as the efficient construction and evaluation of the dynamic network model, the partition of the given entire dataset distinguishes between two cases of Division I(training dataset and testing dataset) and Division II(training dataset, validation dataset, and testing dataset). A comparative analysis shows that the proposed RBF neural networks produces model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• Journal of Korea Trade
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• v.25 no.8
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• pp.1-24
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• 2021

Purpose - This study categorizes factors that influence the utilization of preferential tariffs based on the characteristics of rules of origin (RoO) and identifies and analyzes the influence of these characteristics on the utilization of preferential tariffs and the trade performance of companies. Design/methodology - In this study, we categorized factors that have an influence on the utilization of preferential tariffs based on the characteristics of RoO and investigated and tested the influence of these characteristics on the utilization of preferential tariffs and the trade performance of companies. For empirical analysis, we categorized the characteristics of RoO into restrictiveness, complexity, and uncertainty. We then developed a research model and formulated hypotheses based on previous studies, and tested the hypotheses using statistical software-(SPSS 25.0 and AMOS 18.0.) Findings - Previous studies suggested that each characteristic of RoO is determined by unique features of a Regional Trade Agreement (RTA). This study conducted an empirical analysis on the influence of the characteristics of RoO on the utilization of preferential tariffs and trade performance. The results confirmed that, overall, the characteristics of preferential rules of origin (PRoO) are related to and influence Korean companies' utilization of preferential tariffs and trade performance. As for the degree of the influence, the characteristics were in the order of uncertainty> restrictiveness> complexity. Nevertheless, complexity turned out not to have an influence large enough to change a company's decision on the utilization of preferential tariffs. Based on these results, this study identified unique features of PRoO and related problems for Korean companies that want to utilize preferential tariffs and suggested countermeasures for their effective utilization of preferential tariffs in the future. Originality/value - Companies that want to use preferential tariffs in international trade have to satisfy PRoO. The issue of origin can be regarded as an essential part of an RTA and RoO, are a crucial criterion in using preferential tariffs. The rules are requirements to claim benefits of preferential trade agreements and are the primary reasons companies have trouble in utilizing preferential tariffs. In this sense, this study categorized the characteristics of RoO, which are a key part of an RTA, and surveyed working-level professionals in charge of international trade at Korean companies to investigate the relationship between these characteristics and the utilizations of preferential tariffs and trade performance of the companies.

• Journal of the Korea Convergence Society
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• v.12 no.4
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• pp.9-21
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• 2021

The study aims to identify convergence and trends in technology-based patent data for the biohealth sector in IP5 countries (KR, EP, JP, US, CN) and present the direction of development in that industry. We used patent co-classification analysis-based network analysis and TF-IDF-based text mining as the principal methodology to understand the current state of technology convergence. As a result, the technology convergence cluster in the biohealth industry was derived in three forms: (A) Medical device for treatment, (B) Medical data processing, and (C) Medical device for biometrics. Besides, as a result of trend analysis based on technology convergence results, it is analyzed that Korea is likely to dominate the market with patents with high commercial value in the future as it is derived as a market leader in (B) medical data processing. In particular, the field is expected to require technology convergence activation policies and R&D support strategies for the technology as the possibility of medical data utilization by domestic bio-health companies expands, along with the policy conversion of the "Data 3 Act" passed by the National Assembly in January 2019.