• Journal of Distribution Science
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• v.9 no.3
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• pp.83-94
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• 2011

Most domestic companies, with the exclusion of major firms, are reluctant to implement a supply chain management (SCM) network into their operations. Most small- and medium-sized enterprises are not even aware of SCM. Due to the inherent total-systems efficiency of SCM, it coordinates domestic manufacturers, subcontractors, distributors, and physical distributors and cuts down on cost of inventory control, as well as demand management. Furthermore, a lack of SCM causes a decrease in competitiveness for domestic companies. The reason lies in the fundamentality of SCM, which is the characteristic of information sharing, process innovation throughout SCM, and the vast range of problems the SCM management tool is able to address. This study suggests the contemplation and reformation of the current SCM situation by analyzing the SCM strategic plan, discourses and logical discussions on the topic, and a successful case for adapting SCM; hence, the study plans to productively "process" SCM. First, it is necessary to contemplate the theoretical background of SCM before discussing how to successfully process SCM. I will describe the concept and background of SCM in Chapter 2, with a definition of SCM, types of SCM promotional activities, fields of SCM, necessity of applying SCM, and the effects of SCM. All of the defects in currently processing SCM will be introduced in Chapter 3. Discussion items include the following: the Bullwhip Effect; the breakdown in supply chain and sales networks due to e-business; the issue that even though the key to a successful SCM is cooperation between the production and distribution company, during the process of SCM, the companies, many times, put their profits first, resulting in a possible defect in demands estimation. Furthermore, the problems of processing SCM in a domestic distribution-production company concern Information Technology; for example, the new system introduced to the company is not compatible with the pre-existing document architecture. Second, for effective management, distribution and production companies should cooperate and enhance their partnership in the aspect of the corporation; however, in reality, this seldom occurs. Third, in the aspect of the work process, introducing SCM could provoke corporations during the integration of the distribution-production process. Fourth, to increase the achievement of the SCM strategy process, they need to set up a cross-functional team; however, many times, business partners lack the cooperation and business-information sharing tools necessary to effect the transition to SCM. Chapter 4 will address an SCM strategic plan and a case study of LG Electronics. The purpose of the strategic plan, strategic plans for types of business, adopting SCM in a distribution company, and the global supply chain process of LG Electronics will be introduced. The conclusion of the study is located in Chapter 5, which addresses the issue of the fierce competition that companies currently face in the global market environment and their increased investment in SCM, in order to better cope with short product life cycle and high customer expectations. The SCM management system has evolved through the adaptation of improved information, communication, and transportation technologies; now, it demands the utilization of various strategic resources. The introduction of SCM provides benefits to the management of a network of interconnected businesses by securing customer loyalty with cost and time savings, derived through the consolidation of many distribution systems; additionally, SCM helps enterprises form a wide range of marketing strategies. Thus, we could conclude that not only the distributors but all types of businesses should adopt the systems approach to supply chain strategies. SCM deals with the basic stream of distribution and increases the value of a company by replacing physical distribution with information. By the company obtaining and sharing ready information, it is able to create customer satisfaction at the end point of delivery to the consumer.

• Trans-
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• v.9
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• pp.17-36
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• 2020

This study is aimed at discussing the possibility of content production, utilization and expansion, focusing on the exhibition case of Danwon Art Museum run by Ansan Cultural Foundation. In 1991, the Ministry of Culture, Sports and Tourism named Ansan as the City of Danwon since it is believed to be the hometown of Danwon Kim Hong-do (1745~?), a painter of the late Joseon Dynasty and a well-known master of genre painting. As a result, Ansan is making various efforts to utilize Danwon Kim Hong-do for its unique resource through internal and external business such as the creation of Danwon Sculpture Park, the operation of Danwon Art Museum, and the planning of Danwon Kim Hong-do Festival. However, the biggest problem with Ansan is that there are not many collections of Kim Hong-do. Ansan has owned a total of six works as of May this year: a deer and a boy, flowers and a bird, A view of clouds on the water, Daegwallyeong, Yeodongbin, A way to Singwangsa. Accordingly, Danwon Contents Center has set up a vision to systematically collect, preserve, and display various visual and artistic materials related to Kim Hong-do, offering high-quality information based on digital data. In other words, it is a complex cultural information agency of One-Source Multi-Use, which combines the functions of libraries, archives and art galleries so that visitors' desire is satisfied. It reflects the contemporary trend of overcoming the limitations of the ancient paintings and satisfying the role and function of the art museum. From the opening of the Danwon Contents Hall, the original work of Kim Hong-do has been interpreted and produced as media contents or recreated as a new form of art by modern artists. Exhibition using technologies such as touch screen and 'deep zoom' helps visitors to heighten their experience of the archives and get inside the world of the genius painter.

• Geophysics and Geophysical Exploration
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• v.8 no.1
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• pp.67-72
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• 2005

To investigate the feasibility of a new concept of storing Liquefied Natural Gas (LNG) in a lined hard rock cavern, and to develop essential technologies for constructing underground LNG storage facilities, a small pilot plant storing liquid nitrogen (LN2) has been constructed at the Korea Institute of Geoscience and Mineral Resources (KIGAM). The LN2 stored in the cavern will subject the host rock around the cavern to very low temperatures, which is expected to cause the development of an ice ring and the change of ground condition around the storage cavern. To investigate and monitor changes in ground conditions at this pilot plant site, geophysical, hydrogeological, and rock mechanical investigations were carried out. In particular, geophysical methods including borehole radar and three-dimensional (3D) resistivity surveys were used to identify and monitor the development of an ice ring, and other possible changes in ground conditions resulting from the very low temperature of LN2 in the storage tank. We acquired 3D resistivity data before and after storing the LN2, and the results were compared. From the 3D images obtained during the three phases of the resistivity monitoring survey, we delineated zones of distinct resistivity changes that are closely related to the storage of LN2. In these results, we observed a decrease in resistivity at the eastern part of the storage cavern. Comparing the hydrogeological data and Joint patterns around the storage cavern, we interpret this change in resistivity to result from changes in the groundwater flow pattern. Freezing of the host rock by the very low temperature of LN2 causes a drastic change in the hydrogeological conditions and groundwater flow patterns in this pilot plant.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.4
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• pp.115-133
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• 2021

This study examines the concept and related technologies of the 4th industrial revolution that has been mixed so far and examines the socio-economic changes and influences resulting from it, and the cases of responding to the 4th industrial revolution in major countries. Based on this, by deriving SWOT factors and calculating the importance of each factor for Korean venture companies to prepare for the forth industrial revolution, it was intended to help the government and policymakers in suggesting directions for establishing related policies. Furthermore, the purpose of this study was to suggest a direction for securing global competitiveness to Korean venture entrepreneurs and to help with basic and systematic analysis for further academic in-depth research. For this study, a total of 21 items derived through extensive literature research and data research to understand what are the necessary competency factors for internal and external environmental changes in order for Korean venture companies to have global competitiveness in the era of the 4th Industrial Revolution. After reviewing SWOT factors by three expert groups and confirming them through Delphi survey, the importance of each item was analyzed by using AHP, a systematic decision-making technique. As a result of the analysis, it was shown that Strength(48%), Opportunity(25%), Threat(16%), Weakness(11%) were considered important in order. In terms of sub-items, 'quick and flexible commercialization capability', 'platform/big data/non-face-to-face service activation', and 'ICT infrastructure and it's utilization' were shown to be of the comparatively high importance. On the other hand, in the lower three items, 'macro-economic stability and social infrastructure', 'difficulty in entering overseas markets due to global protectionism', and 'absolutely inferior in foreign investment' were found to have low priority. As a result of the correlation verification by item to see differences in opinions by industry, academia, and policy expert groups, there was no significant difference of opinion, as industry and academic experts showed a high correlation and industry experts and policy experts showed a moderate correlation. The correlation between the academic and policy experts was not statistically significant (p<0.01), so it was analyzed that there was a difference of opinion on importance. This was due to the fact that policy experts highly valued 'quick and flexible commercialization', which are strengths, and 'excellent educational system and high-quality manpower' and 'creation of new markets' which are opportunity items, while academic experts placed great importance on 'support part of government policy', which are strengths. The implication of this study is that in order for Korean venture companies to secure competitiveness in the field of the 4th industrial revolution, it is necessary to have a policy that preferentially supports the relevant items of strengths and opportunity factors. The difference in the details of strength factors and opportunity factors, which shows a high level of variability, suggests that it is necessary to actively review it and reflect it in the policy.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.2
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• pp.49-58
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• 2019

There have been studies on the satisfaction, preference, and post occupancy evaluation of urban parks in order to reflect users' preferences and activities, suggesting directions for future park planning and management. Despite using questionnaires that are proven to be affective to get users' opinions directly, there haven been limitations in understanding the latest changes in park use through questionnaires. This study seeks to address the possibility of utilizing the thirdgeneration SNS data, Instagram and Google, to compare behavior patterns and trends in park activities. Instagram keywords and photos representing user's feelings with a specific park name were collected. We also examined reviews, peak time, and popular time zones regarding selected parks through Google. This study tries to analyze users' behaviors, emerging activities, and satisfaction using SNS data. The findings are as follows. People using park near residential areas tend to enjoy programs being operated in indoor facilities and to like to use picnic places. In an adjacent park of commercial areas, eating in the park and extended areas beyond the park boundaries is found to be one of the popular park activities. Programs using open spaces and indoor facilities were active as well. Han River Park as a detached park type offers a popular venue for excercises and scenery appreciation. We also identified companionship characteristics of different park types from texts and photos, and extracted keywords of feelings and reviews about parks posted in $3^{rd}$ generation SNS. SNS data can provide basis to grasp behavioral patterns and satisfaction factors, and changes of park activities in real time. SNS data also can be used to set future directions in park planning and management in accordance with new technologies and policies.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.1-23
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• 2019

Big data refers to data that is difficult to store, manage, and analyze by existing software. As the lifestyle changes of consumers increase the size and types of needs that consumers desire, they are investing a lot of time and money to understand the needs of consumers. Companies in various industries utilize Big Data to improve their products and services to meet their needs, analyze unstructured data, and respond to real-time responses to products and services. The financial industry operates a decision support system that uses financial data to develop financial products and manage customer risks. The use of big data by financial institutions can effectively create added value of the value chain, and it is possible to develop a more advanced customer relationship management strategy. Financial institutions can utilize the purchase data and unstructured data generated by the credit card, and it becomes possible to confirm and satisfy the customer's desire. CRM has a granular process that can be measured in real time as it grows with information knowledge systems. With the development of information service and CRM, the platform has change and it has become possible to meet consumer needs in various environments. Recently, as the needs of consumers have diversified, more companies are providing systematic marketing services using data mining and advanced CRM (Customer Relationship Management) techniques. KB Kookmin Card, which started as a credit card business in 1980, introduced early stabilization of processes and computer systems, and actively participated in introducing new technologies and systems. In 2011, the bank and credit card companies separated, leading the 'Hye-dam Card' and 'One Card' markets, which were deviated from the existing concept. In 2017, the total use of domestic credit cards and check cards grew by 5.6% year-on-year to 886 trillion won. In 2018, we received a long-term rating of AA + as a result of our credit card evaluation. We confirmed that our credit rating was at the top of the list through effective marketing strategies and services. At present, Kookmin Card emphasizes strategies to meet the individual needs of customers and to maximize the lifetime value of consumers by utilizing payment data of customers. KB Kookmin Card combines internal and external big data and conducts marketing in real time or builds a system for monitoring. KB Kookmin Card has built a marketing system that detects realtime behavior using big data such as visiting the homepage and purchasing history by using the customer card information. It is designed to enable customers to capture action events in real time and execute marketing by utilizing the stores, locations, amounts, usage pattern, etc. of the card transactions. We have created more than 280 different scenarios based on the customer's life cycle and are conducting marketing plans to accommodate various customer groups in real time. We operate a smart offering system, which is a highly efficient marketing management system that detects customers' card usage, customer behavior, and location information in real time, and provides further refinement services by combining with various apps. This study aims to identify the traditional CRM to the current CRM strategy through the process of changing the CRM strategy. Finally, I will confirm the current CRM strategy through KB Kookmin card's big data utilization strategy and marketing activities and propose a marketing plan for KB Kookmin card's future CRM strategy. KB Kookmin Card should invest in securing ICT technology and human resources, which are becoming more sophisticated for the success and continuous growth of smart offering system. It is necessary to establish a strategy for securing profit from a long-term perspective and systematically proceed. Especially, in the current situation where privacy violation and personal information leakage issues are being addressed, efforts should be made to induce customers' recognition of marketing using customer information and to form corporate image emphasizing security.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.2
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• pp.59-75
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• 2019

This study was carried out to explore the 4th Industrial Revolution technology from the perspective of the landscape industry to provide the basic data necessary to increase the virtuous circle value. The 4th Industrial Revolution, the characteristics of the landscape industry and urban regeneration were considered and the methodology was established and studied including the technical classification system suitable for systematic research, which was selected as a framework. First, the 4th Industrial Revolution technology based on digital data was selected, which could be utilized to increase the value of the virtuous circle for the landscape industry. From 'Element Technology Level', and 'Core Technology' such as the Internet of Things, Cloud Computing, Big Data, Artificial Intelligence, Robot, 'Peripheral Technology', Virtual or Augmented Reality, Drones, 3D 4D Printing, and 3D Scanning were highlighted as the 4th Industrial Revolution technology. It has been shown that it is possible to increase the value of the virtuous circle when applied at the 'Trend Level', in particular to the landscape industry. The 'System Level' was analyzed as a general-purpose technology, and based on the platform, the level of element technology(computers, and smart devices) was systematically interconnected, and illuminated with the 4th Industrial Revolution technology based on digital data. The application of the 'Trend Level' specific to the landscape industry has been shown to be an effective technology for increasing the virtuous circle values. It is possible to realize all synergistic effects and implementation of the proposed method at the trend level applying the element technology level. Smart gardens, smart parks, etc. have been analyzed to the level they should pursue. It was judged that Smart City, Smart Home, Smart Farm, and Precision Agriculture, Smart Tourism, and Smart Health Care could be highly linked through the collaboration among technologies in adjacent areas at the Trend Level. Additionally, various utilization measures of related technology applied at the Trend Level were highlighted in the process of urban regeneration, public service space creation, maintenance, and public service. In other words, with the realization of ubiquitous computing, Hyper-Connectivity, Hyper-Reality, Hyper-Intelligence, and Hyper-Convergence were proposed, reflecting the basic characteristics of digital technology in the landscape industry can be achieved. It was analyzed that the landscaping industry was effectively accommodating and coordinating with the needs of new characters, education and consulting, as well as existing tasks, even when participating in urban regeneration projects. In particular, it has been shown that the overall landscapig area is effective in increasing the virtuous circle value when it systems the related technology at the trend level by linking maintenance with strategic bridgehead. This is because the industrial structure is effective in distributing data and information produced from various channels. Subsequent research, such as demonstrating the fusion of the 4th Industrial Revolution technology based on the use of digital data in creation, maintenance, and service of actual landscape space is necessary.

• Food Science and Industry
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• v.51 no.4
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• pp.278-301
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• 2018

Although more than 80% of living organisms are found in marine ecosystems, only less than 10% of marine resources have been utilized for human food consumptions and other usages. It is well known that marine resources (fish, shellfish and algae) have exceptional nutritional properties; however, their functional characteristic has not been completely discovered. It is believed that metabolites (organic compounds, proteins, peptides, lipids, minerals, etc.) play an important role to show its biological properties. Marine proteins and peptides are considered to be future drugs due to their excellent biological activities with a fewer adverse side effect. Marine peptides show several biological activities, including antimicrobial, antioxidant, anti-inflammatory, anti-cancer, anti-viral, anti-tumor, anti-diabetic, anti-hypertensive, anti-coagulant, immunomodulatory, appetite suppressing and neuroprotective effects. Therefore, the pharmaceutical, nutraceutical, and cosmeceutical companies have been paid attention to the marine peptides to commercialize into products. This current review mainly focused on the above mentioned biological activities of marine peptides and protein hydrolysates as a functional food and pharmaceutical applications. To commercialize these materials in industrial level required large quantity in high-purity level, and it is complicated to produce huge quantity from the marine resources due to insufficient raw materials, unavailability of raw materials through a year, hinder the growth with geographical variations, and availability of compounds in extreme small quantities. The best solution for these issues is to introduce new modern technologies such as artificial intelligence robots, drones, submersibles and automated raw material harvesting vessels in farming industries instead of man power, which will lead to 4th industrial revolution.

• Korean Journal of Environment and Ecology
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• v.35 no.4
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• pp.316-335
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• 2021

This study reviewed the change of theory of ecological niche(concepts and definitions) over time to provide a theoretical basis for habitat-related studies of animals and plants. Accordingly, it analyzed and summarized the major discussion trends of ecological niche worldwide in each period from the 1900s to the present. Countries advanced in ecological studies, such as the EU and the USA, have conducted theoretical and empirical studies on the ecological niche since the early 1990s. The concept of the ecological niche was introduced in the early 1900s, developed in the mid-1900s, and advanced from the mid-1900s to the late 1900s. Since the 2000s, the advanced concept has diversified with new developments in technologies and research methods. The factors suggested by theoretical and empirical studies in defining the ecological niche of a species include 1) population dynamics of the target species, 2) all biotic conditions to sustain a population (food relationship and material flow in the food chain), 3) all non-biotic conditions to sustain a population (physical environmental conditions), 4) all direct and indirect interactions between these environmental factors, and 5) response and adaptation mechanisms that include the migratory ability of the target species or genetic diversity and adaptability to change. Unlike such international advancement, there have not been sufficient theoretical, philosophical, and empirical studies of ecological niche in Korea. The concepts and definitions by Greennell, Elton, and Hutchinson were selectively and partially borrowed for empirical studies without full description. Considering that the theory of ecological niche becomes the foundation for habitat-based species conservation and restoration, it is necessary to seek diversification and advancement of theoretical and empirical research and research methods and technological development. It will provide an important foundation for the academic advancement of ecology and for establishing and implementing policies to preserve and restore ecology and biodiversity effectively and successfully in Korea.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.157-173
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• 2021

With the development of information technology, the amount of available information increases daily. However, having access to so much information makes it difficult for users to easily find the information they seek. Users want a visualized system that reduces information retrieval and learning time, saving them from personally reading and judging all available information. As a result, recommendation systems are an increasingly important technologies that are essential to the business. Collaborative filtering is used in various fields with excellent performance because recommendations are made based on similar user interests and preferences. However, limitations do exist. Sparsity occurs when user-item preference information is insufficient, and is the main limitation of collaborative filtering. The evaluation value of the user item matrix may be distorted by the data depending on the popularity of the product, or there may be new users who have not yet evaluated the value. The lack of historical data to identify consumer preferences is referred to as data sparsity, and various methods have been studied to address these problems. However, most attempts to solve the sparsity problem are not optimal because they can only be applied when additional data such as users' personal information, social networks, or characteristics of items are included. Another problem is that real-world score data are mostly biased to high scores, resulting in severe imbalances. One cause of this imbalance distribution is the purchasing bias, in which only users with high product ratings purchase products, so those with low ratings are less likely to purchase products and thus do not leave negative product reviews. Due to these characteristics, unlike most users' actual preferences, reviews by users who purchase products are more likely to be positive. Therefore, the actual rating data is over-learned in many classes with high incidence due to its biased characteristics, distorting the market. Applying collaborative filtering to these imbalanced data leads to poor recommendation performance due to excessive learning of biased classes. Traditional oversampling techniques to address this problem are likely to cause overfitting because they repeat the same data, which acts as noise in learning, reducing recommendation performance. In addition, pre-processing methods for most existing data imbalance problems are designed and used for binary classes. Binary class imbalance techniques are difficult to apply to multi-class problems because they cannot model multi-class problems, such as objects at cross-class boundaries or objects overlapping multiple classes. To solve this problem, research has been conducted to convert and apply multi-class problems to binary class problems. However, simplification of multi-class problems can cause potential classification errors when combined with the results of classifiers learned from other sub-problems, resulting in loss of important information about relationships beyond the selected items. Therefore, it is necessary to develop more effective methods to address multi-class imbalance problems. We propose a collaborative filtering model using CGAN to generate realistic virtual data to populate the empty user-item matrix. Conditional vector y identify distributions for minority classes and generate data reflecting their characteristics. Collaborative filtering then maximizes the performance of the recommendation system via hyperparameter tuning. This process should improve the accuracy of the model by addressing the sparsity problem of collaborative filtering implementations while mitigating data imbalances arising from real data. Our model has superior recommendation performance over existing oversampling techniques and existing real-world data with data sparsity. SMOTE, Borderline SMOTE, SVM-SMOTE, ADASYN, and GAN were used as comparative models and we demonstrate the highest prediction accuracy on the RMSE and MAE evaluation scales. Through this study, oversampling based on deep learning will be able to further refine the performance of recommendation systems using actual data and be used to build business recommendation systems.