• Knowledge Management Research
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• v.22 no.2
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• pp.119-144
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• 2021

Recently, as competition in the market evolves from the competition among companies to the competition among their supply chains, companies are struggling to enhance their supply chain management (hereinafter SCM). In particular, as blockchain technology with various technical advantages is combined with SCM, a lot of domestic manufacturing and distribution companies are considering the adoption of blockchain-oriented SCM (BOSCM) services today. Thus, it is an important academic topic to examine the factors affecting the use of blockchain-oriented SCM. However, most prior studies on blockchain and SCMs have designed their research models based on Technology Acceptance Model (TAM) or the Unified Theory of Acceptance and Use of Technology (UTAUT), which are suitable for explaining individual's acceptance of information technology rather than companies'. Under this background, this study presents a novel model of blockchain-oriented SCM acceptance model based on the Technology-Organization-Environment (TOE) framework to consider companies as the unit of analysis. In addition, Value-based Adoption Model (VAM) is applied to the research model in order to consider the benefits and the sacrifices caused by a new information system comprehensively. To validate the proposed research model, a survey of 126 companies were collected. Among them, by applying PLS-SEM (Partial Least Squares Structural Equation Modeling) with data of 122 companies, the research model was verified. As a result, 'business innovation', 'tracking and tracing', 'security enhancement' and 'cost' from technology viewpoint are found to significantly affect 'perceived value', which in turn affects 'intention to use blockchain-oriented SCM'. Also, 'organization readiness' is found to affect 'intention to use' with statistical significance. However, it is found that 'complexity' and 'regulation environment' have little impact on 'perceived value' and 'intention to use', respectively. It is expected that the findings of this study contribute to preparing practical and policy alternatives for facilitating blockchain-oriented SCM adoption in Korean firms.

• Information Systems Review
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• v.7 no.2
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• pp.163-181
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• 2005

In this paper, we report case analysis on entob.com which is one of the leading domestic players in MRO e-marketplace. Critical success factors of achieving early liquidity and right ownerships are addressed for successful e-marketplace launching. Change management issues, required to encourage suppliers participation and to overcome adoption barriers from buyer firms, are suggested and illustrated for the successful implementation of the MRO e-marketplace. The business model architectures enabling to create e-intermediary value to both the suppliers and buyers are detailed. Finally, benefits of buyer firms captured through e-procurement business process streamlining and material cost savings are reported as the successful application stories. The findings suggest practical managerial insights for MRO e-marketplace implementation and further research.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.3
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• pp.611-619
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• 2017

This paper intends to develop unit water production cost (UWPC) between alternative water resources including desalination, freshwater reservoirs, single-purpose dams, underground dams, and two indirect water in-take technologies - riverbank filtration and aquifer storage and recovery (ASR). The UWPCs of water supply schemes including each alternative are determined based on project cost, and operation and maintenance estimation models, which were developed based on real project cost data. The sensitivity analysis of UWPCs reveals that ASR is the lowest cost option in producing drinkable water among the alternatives, followed by riverbank filtration and underground dam. It is expected that economics related to the finding plays a critical role in supporting water resources planning and budget allocation for central and local water authority in Korea.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.1
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• pp.73-83
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• 2007

Network modeling of irrigation system that links irrigation facilities with stream is necessary to establish complicated rural water management system and to manage agricultural water effectively. This study attempted a network modeling for an agricultural water district called "ANGO" located in Anseongcheon watershed by connecting ArcHydro Model developed to control geographical information data in the field of water resources and AWDS(Agricultural Water Demand & Supply Estimation System) developed by KRC (Korea Rural Community & Agriculture Corporation). Network modeling was embodied by build topology between spatial objects of total 70 agricultural irrigation facilities (24 reservoirs, 18 pumping stations, 28 weirs) and stream network using ArcHydro Model. In addition, new menus were added in ArcGIS system for query and visualization of text-based AWDS outputs such as irrigation facilities information, water demand and supply analysis.

• Korean Journal of Construction Engineering and Management
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• v.8 no.5
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• pp.161-172
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• 2007

By prosperous condition of construction economy in the early 90s in Korea, the government needed a lot of the qualified professional engineers (PE) to manage the construction site. In order to meet the high demand of P.E., Government has established the admitted engineer systems(AES) in 1995 that give the authority of principal engineers to the admitted engineers who do not take the written examination but have equivalent working experience. Since 2000, professional $engineer^{\circ}{\phi}s$ shortage has been resolved. however, the opposite situation, which is serious over-supply of construction engineers has occurred. Thus, Government announced that would abolish the admitted engineer systems as recognized the existent admitted engineers(about 1,000,000 persons) from 2007. However, Professional Engineers Institution has strongly insisted that Government should not recognize existent admitted engineers. From this point of view, it is critical to make the supply-demand forecast systems as a derivative approach of System Dynamics also, that is useful in comparing the argument between Government and Professional Engineers Institution. This paper describes about principal $engineer^{\circ}{\phi}s$ supply change by admitted engineer system abrogation and suggests the idea to regulate the supply and demand with the improvement of the regal system.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.121-129
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• 2021

In this study, we try to minimize the tariff risk by constructing a hazardous cargo screening model by applying Association Rule Mining, one of the data mining techniques. For this, the risk level between supply chains is calculated using the Apriori Algorithm, which is an association analysis algorithm, using the big data of the import declaration form of the Korea Customs Service(KCS). We perform data preprocessing and association rule mining to generate a model to be used in screening the supply chain. In the preprocessing process, we extract the attributes required for rule generation from the import declaration data after the error removing process. Then, we generate the rules by using the extracted attributes as inputs to the Apriori algorithm. The generated association rule model is loaded in the KCS screening system. When the import declaration which should be checked is received, the screening system refers to the model and returns the confidence value based on the supply chain information on the import declaration data. The result will be used to determine whether to check the import case. The 5-fold cross-validation of 16.6% precision and 33.8% recall showed that import declaration data for 2 years and 6 months were divided into learning data and test data. This is a result that is about 3.4 times higher in precision and 1.5 times higher in recall than frequency-based methods. This confirms that the proposed method is an effective way to reduce tariff risks.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.10
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• pp.293-302
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• 2016

Since the electricity is produced and consumed simultaneously, predicting the electric load and securing affordable electric power are necessary for reliable electric power supply. In particular, a university campus is one of the highest power consuming institutions and tends to have a wide variation of electric load depending on time and environment. For these reasons, an accurate electric load forecasting method that can predict power consumption in real-time is required for efficient power supply and management. Even though various influencing factors of power consumption have been discovered for the educational institutions by analyzing power consumption patterns and usage cases, further studies are required for the quantitative prediction of electric load. In this paper, we build an electric load forecasting model by implementing and evaluating various machine learning algorithms. To do that, we consider three building clusters in a campus and collect their power consumption every 15 minutes for more than one year. In the preprocessing, features are represented by considering periodic characteristic of the data and principal component analysis is performed for the features. In order to train the electric load forecasting model, we employ both artificial neural network and support vector machine. We evaluate the prediction performance of each forecasting model by 5-fold cross-validation and compare the prediction result to real electric load.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.43-49
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• 2017

In recent years, the use of BIM in domestic construction has been increasing, but it is used mainly for internal and external visualization rather than for BIM design including drawings. For this reason, several studies have highlighted the lack of libraries and economic problems for BIM design. In other words, for the most economically small domestic design offices, activating the BIM design is a negative factor because it is difficult to invest the necessary manpower and cost to produce and use the required BIM library. The BIM design can be more applicable if the library can be supplied economically, easily, and quickly. In this study, BIM library business model and consideration factors that can provide BIM library service economically, easily, and quickly by considering the existing building material selection task and BIM library are presented. The proposed business model will increase the number of suppliers of BIM libraries, which are lacking in Korea, and will enable an effective BIM design at low cost and effort. If a service that reflects the business model proposed in this study is made, an integrated database that can consistently share information in the design, construction, and maintenance stages will be constructed. This can monitor the changes in material and equipment information during the life cycle of the building. The database can be used to monitor any changes in material and equipment information throughout the life cycle of a building, so that it can be used as historical data for effective design and maintenance as well as for material and equipment upgrades.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.308-320
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• 2021

An integrated sediment management approach that includes the recovery of the amount of declined sediment supply is effective as a fundamental solution to coastal erosion. During planning, it is essential to analyze the transfer mechanism of the sediments generated from estuaries (the junction between a river and sea) to assess the amount and rate of sediment discharge (from the river to sea) supplied back to the coast. Although numerical models that interpret the tidal sand bar flushing process during flooding have been studied, thus far, there has been no study focusing on the formation and development processes of tidal sand bars. Therefore, this study aims to construct wave deformation, flow regime calculation, and topographic change analysis models to assess the amount of recovered sediment discharge and reproduce the tidal sand bar formation process through numerical analysis for integrated littoral drift management. The tidal sand bar formation process was simulated, and the wave energy and duration of action concepts were implemented to predict the long-term littoral movement. The river flux and wave conditions during winter when tidal sand bars dominantly develop were considered as the external force conditions required for calculation. The initial condition of the topographic data directly after the Maeupcheon tidal sand bar flushing during flooding was set as the initial topography. Consequently, the tidal sand bar formation and development due to nearshore currents dependent on the incident wave direction were reproduced. Approximately 66 h after the initial topography, a sand bar formation was observed at the Maengbang estuary.

• The Journal of Society for e-Business Studies
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• v.23 no.2
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• pp.33-47
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• 2018

City gas pipelines are buried underground. Because of this, pipeline is hard to manage, and can be easily damaged. This research proposes a real time prediction system that helps experts can make decision about pressure anomalies. The gas pipline pressure data of Jungbu City Gas Company, which is one of the domestic city gas suppliers, time variables and environment variables are analysed. In this research, regression models that predicts pipeline pressure in minutes are proposed. Random forest, support vector regression (SVR), long-short term memory (LSTM) algorithms are used to build pressure prediction models. A comparison of pressure prediction models' preformances shows that the LSTM model was the best. LSTM model for Asan-si have root mean square error (RMSE) 0.011, mean absolute percentage error (MAPE) 0.494. LSTM model for Cheonan-si have RMSE 0.015, MAPE 0.668.