• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.40-51
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• 2011

The key issues of recommendation systems provide the contents satisfying the interests of users for the huge amounts of contents over internet. The existing recommendation system use the algorithms considering the users' profiles and context information to enhance the exactness of a recommendation. However, the existing recommendation system can't satisfy the requirements of service providers because the business models of service providers is not considered. In this paper, we propose the mobile recommendation system using the composite contexts and the recommendation weights applying the business model of service providers. The proposed system retrieves the contents of the contents providers using composite context information and apply the recommendation weights to recommend the suitable contents for the business models of service providers. Therefore, we provide the contents satisfying the consumption value of users and the business models of service providers to mobile users.

• KSCI Review
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• v.9 no.2
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• pp.9-18
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• 2002

To establish and operate adequate business model is core procedure to survive from severe competitive environment and can create payoff through BM. Whether company have or maintain competitive advantage. It depends on how to position company in the value system. In this study. like to achieve integration and rebuilding of value chain through B2E relationship and affiliation which could not achieved because of limit of manpower, cost, time. After analysis of B2E model. affiliated program, propose Affiliated B2E model. Proposed model has mutual supplemented function module which compensate mutual profit between parent company and employee company.

• Spatial Information Research
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• v.20 no.2
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• pp.81-92
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• 2012

Recently, it is very important to create economic value as well as develop core algorithms and technologies in the field of R&D. Various R&D projects make an effort to do the technology commercialization of their results and, as part of efforts, many studies on business model(BM) are conducted to create economic benefits in using the developed technology. However, it is difficult to use the general business model methodologies, which are usually utilized for companies, to the government's research due to different processes and characteristics between them. And for the practical application of business models, it needs to systematize conceptual business models in technical perspective through technical architecture analysis. In this study, a business model development process and a technical architecture analysis for national R&D project is developed for the technology commercialization. In addition, the process is applied to Korean Land Spatialization Program (KLSP) organized by Ministry of Land, Transport and Maritime Affairs to verify the feasibility of its practical application.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.339-347
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• 2021

This study aims to forecast the exchange rate by a combination of different models as proposed by Poon and Granger (2003). For this purpose, we include three univariate time series models, i.e., ARIMA, Naïve, Exponential smoothing, and one multivariate model, i.e., NARDL. This is the first of its kind endeavor to combine univariate models along with NARDL to the best of our knowledge. Utilizing monthly data from January 2011 to December 2020, we predict the Pakistani Rupee against the US dollar by a combination of different forecasting techniques. The observations from M1 2020 to M12 2020 are held back for in-sample forecasting. The models are then assessed through equal weightage and var-cor methods. Our results suggest that NARDL outperforms all individual time series models in terms of forecasting the exchange rate. Similarly, the combination of NARDL and Naïve model again outperformed all of the individual as well as combined models with the lowest MAPE value of 0.612 suggesting that the Pakistani Rupee exchange rate against the US Dollar is dependent upon the macro-economic fundamentals and recent observations of the time series. Further evidence shows that the combination of models plays a vital role in forecasting, as stated by Poon and Granger (2003).

• Journal of Distribution Science
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• v.22 no.8
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• pp.65-76
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• 2024

Purpose: The study aims to recognize the relationship between big data analytics capabilities, big data analytics process, and perceived business performance from supply chain management to total customer satisfaction. Research design, data and methodology: The study followed a quantitative approach with a descriptive design. The data was collected from leading e-commerce companies in India using a structured questionnaire, and the data was coded and decoded using MS Excel, SPSS, and R language. It was further tested using Cronbach's alpha, KMO, and Bartlett's test for reliability and internal consistency. Results: The results showed that the big data analytics process acts as a robust mediator between big data analytics capabilities and perceived business performance. The 'direct, indirect and total effect of the model' and 'PLS-SEM model' showed that the big data analytics process directly impacts business performance. Conclusions: A complete indirect relationship exists between big data analytics capabilities and perceived business performance through the big data analytics process. The research contributesto e-commerce companies' understanding of the importance of big data analytics capabilities and processes.

• Journal of Korea Spatial Information System Society
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• v.11 no.4
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• pp.9-18
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• 2009

R&D businesses lead by a government of each countries are recognized as important businesses that may affect the destinies of the nation. However, the process of developing a new business has not been so favorable as the process was primarily managed by engineers who concentrate on research development. The problem was solved by applying a business model regarding outcomes of a developed research. Yet it is difficult to apply the business model methods that are commonly used for enterprises to government's research businesses due to their unique research development characteristics. Therefore, it is developed a business model methodology for national R&D project in this study. In addition, the methodology applies to a sub-project of Korean Land Spatialization Program(KLSP) organized by Ministry of Land, Transport and Maritime Affairs to verify the possibility of practical application.

• The Journal of Industrial Distribution & Business
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• v.10 no.10
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• pp.67-79
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• 2019

Purpose - The purpose of this study was to explore the model that supports the recipient country by using the ODA (Official Development Assistance) project and at the same time fits the global start-up/employment support of donor country with CSV business model. Specifically, we wanted to examine the feasibility of the project based on the existing ODA projects. Research design, data, and methodology - As the methodology, case studies and interview were conducted as well as literature studies. The case analysis is based on a press release of the entire KOICA's ODA project, which has been implemented for one year, based on 2017. After consideration, the actual results and future feasibility were analyzed. The interviews were conducted on senior Korean officials and Indian officials involved in Vietnam's ODA project. Results - As a result, some of the project cases applied and analyzed according to the model of this study were judged to be highly potential. Based on the results of this analysis, as the model derived from this study pursues, the global business model is developed under the CSV (Creating Shared Value) strategy through ODA projects to support recipient countries and global start-up/employment support of donor country. The possibility of simultaneously pursuing this model based on CSV business model was also confirmed. Conclusions - In the past, free aid agencies like KOICA focused solely on supporting recipient countries, but in terms of sustainability, they could discover the potential of supporting the global start-up/employment of the donor country using CSV business model in ODA project. In this study, we tried to find the theoretical background and potential possibilities in some ODA projects based on CSV business model. As a result of the analysis of KOICA ODA projects in 2017 and interviews, some ODA projects could be used to improve the economic development of the recipient country as well as the global start-up/employment of the donor country. Therefore, it is necessary for the ministries of the government to promote ODA projects to understand the framework that achieves these two objectives simultaneously and to promote ODA projects based on various strategic considerations.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.59-71
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• 2014

System trading is becoming more popular among Korean traders recently. System traders use automatic order systems based on the system generated buy and sell signals. These signals are generated from the predetermined entry and exit rules that were coded by system traders. Most researches on system trading have focused on designing profitable entry and exit rules using technical indicators. However, market conditions, strategy characteristics, and money management also have influences on the profitability of the system trading. Unexpected price deviations from the predetermined trading rules can incur large losses to system traders. Therefore, most professional traders use strategy portfolios rather than only one strategy. Building a good strategy portfolio is important because trading performance depends on strategy portfolios. Despite of the importance of designing strategy portfolio, rule of thumb methods have been used to select trading strategies. In this study, we propose a SVM-based strategy portfolio management system. SVM were introduced by Vapnik and is known to be effective for data mining area. It can build good portfolios within a very short period of time. Since SVM minimizes structural risks, it is best suitable for the futures trading market in which prices do not move exactly the same as the past. Our system trading strategies include moving-average cross system, MACD cross system, trend-following system, buy dips and sell rallies system, DMI system, Keltner channel system, Bollinger Bands system, and Fibonacci system. These strategies are well known and frequently being used by many professional traders. We program these strategies for generating automated system signals for entry and exit. We propose SVM-based strategies selection system and portfolio construction and order routing system. Strategies selection system is a portfolio training system. It generates training data and makes SVM model using optimal portfolio. We make $m{\times}n$ data matrix by dividing KOSPI 200 index futures data with a same period. Optimal strategy portfolio is derived from analyzing each strategy performance. SVM model is generated based on this data and optimal strategy portfolio. We use 80% of the data for training and the remaining 20% is used for testing the strategy. For training, we select two strategies which show the highest profit in the next day. Selection method 1 selects two strategies and method 2 selects maximum two strategies which show profit more than 0.1 point. We use one-against-all method which has fast processing time. We analyse the daily data of KOSPI 200 index futures contracts from January 1990 to November 2011. Price change rates for 50 days are used as SVM input data. The training period is from January 1990 to March 2007 and the test period is from March 2007 to November 2011. We suggest three benchmark strategies portfolio. BM1 holds two contracts of KOSPI 200 index futures for testing period. BM2 is constructed as two strategies which show the largest cumulative profit during 30 days before testing starts. BM3 has two strategies which show best profits during testing period. Trading cost include brokerage commission cost and slippage cost. The proposed strategy portfolio management system shows profit more than double of the benchmark portfolios. BM1 shows 103.44 point profit, BM2 shows 488.61 point profit, and BM3 shows 502.41 point profit after deducting trading cost. The best benchmark is the portfolio of the two best profit strategies during the test period. The proposed system 1 shows 706.22 point profit and proposed system 2 shows 768.95 point profit after deducting trading cost. The equity curves for the entire period show stable pattern. With higher profit, this suggests a good trading direction for system traders. We can make more stable and more profitable portfolios if we add money management module to the system.

• Journal of Information Science Theory and Practice
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• v.12 no.3
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• pp.36-48
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• 2024

The information retrieval (IR) process often encounters a challenge known as query-document vocabulary mismatch, where user queries do not align with document content, impacting search effectiveness. Automatic query expansion (AQE) techniques aim to mitigate this issue by augmenting user queries with related terms or synonyms. Word embedding, particularly Word2Vec, has gained prominence for AQE due to its ability to represent words as real-number vectors. However, AQE methods typically expand individual query terms, potentially leading to query drift if not carefully selected. To address this, researchers propose utilizing median vectors derived from deep median networks to capture query similarity comprehensively. Integrating median vectors into candidate term generation and combining them with the BM25 probabilistic model and two IR strategies (EQE1 and V2Q) yields promising results, outperforming baseline methods in experimental settings.

• Journal of Distribution Science
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• v.20 no.11
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• pp.79-88
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• 2022

Purpose: The purpose of this study was to determine the effect of agricultural exports and imports on economic growth in Bangladesh and propose an upgraded and customized model of the supply chain for agribusiness growth in Bangladesh to achieve plain sailing and systematic operation and financial gains at home and abroad. Research design, data, and methodology: All data in the research have been collected from secondary sources. Gross domestic product was used as the dependent variable and exports and imports of agricultural products were used as independent variables. Pairwise Granger causality was utilized to see the impact of the variable responsible for the economic growth in Bangladesh and the causal relationship between the variables analyzed was measured using Johansen co-integration test. Results: From the empirical analysis, the researchers observed that agricultural commodity imports and exports have a unidirectional impact on economic growth in Bangladesh and a long-run causal link with economic growth in Bangladesh. The suggested supply chain model of agribusiness aids in achieving smooth operations, systematic management, and monetary gains both domestically and internationally. Conclusions: This paper contributes to the development of a more effective and profitable agribusiness supply chain in Bangladesh systematically through their theoretical and practical implications.