• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.81-88
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• 2021

Convertible bonds are financial products that contain the nature of both bonds and shares, which are generally issued by companies with lower credit ratings to increase liquidity. Conversion bonds rely on qualitative judgment in the past, although decision-making on whether and when to exercise the right to convert is the most important issue. Therefore, this paper proposes to apply artificial neural network techniques to scientifically determine the exercise of conversion rights. We distinguish between a total of 1,800 learning data published in the past and 200 predictive experimental data and build an artificial neural network learning model. As a result, the parity performance in most groups was excellent, achieving an average excess of about 10% or more. In particular, groups 3-6 recorded an average excess of about 20% and group 6 recorded an average excess of about 37%. This paper is meaningful in that it focused on solving decision problems by converging and applying machine learning techniques, a representative technology of the fourth industry, to the financial sector.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.5
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• pp.356-364
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• 2019

The Ministry of Science and ICT recently announced its policy direction that involves charging the economic value of radio spectrum for promoting its efficient usage. According to the policy, there will be much efforts to estimate the economic values of various usages of radio spectrum. In this study, the economic value of radio spectrum is estimated for trunked radio system(TRS) by employing the least cost alternative methodology. The proposed methodology estimates the value of radio spectrum according to the cost of an alternative that can be employed for providing the same service. The value of radio spectrum for TRS was determined on the basis of the cost associated with the provision of TRS through the LTE network, wherein the value of radio spectrum for TRS comprises the LTE network cost, capital expenditure for the LTE service, subsidy for the LTE handset, and compensation cost for migration. Results obtained from this study can aid in calculating the economic values of radio spectra for other services and applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2631-2649
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• 2021

Device-to-Device (D2D) communication is one of the enabling technologies for 5G networks that support proximity-based service (ProSe) for wireless network communications. This paper proposes a power control algorithm based on the Nash equilibrium and game theory to eliminate the interference between the cellular user device and D2D links. This leadsto reliable connectivity with minimal power consumption in wireless communication. The power control in D2D is modeled as a non-cooperative game. Each device is allowed to independently select and transmit its power to maximize (or minimize) user utility. The aim is to guide user devices to converge with the Nash equilibrium by establishing connectivity with network resources. The proposed algorithm with pricing factors is used for power consumption and reduces overall interference of D2Ds communication. The proposed algorithm is evaluated in terms of the energy efficiency of the average power consumption, the number of D2D communication, and the number of iterations. Besides, the algorithm has a relatively fast convergence with the Nash Equilibrium rate. It guarantees that the user devices can achieve their required Quality of Service (QoS) by adjusting the residual cost coefficient and residual energy factor. Simulation results show that the power control shows a significant reduction in power consumption that has been achieved by approximately 20% compared with algorithms in [11].

• Journal of Korea Technology Innovation Society
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• v.22 no.2
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• pp.220-241
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• 2019

In order to provide theoretical guidance to research in platform strategy, we build the conceptual framework based on the organizational ecology and analyze symbiotic/competitive relationship between platform entities. Platform owner and service provider (i.e. complementors) make symbiotic relationship, where platform owner provide service provider user-base and platform resources such as marketing tools and platform technology, and service provider provide platform owner services which users utilize. In addition to symbiotic relationships, platform owner has competitive relationship with other platform owners, and service provider builds competitive relationship with other service providers. In these relationships, the strategy of platform owner affects service provider and service provider builds a strategy for their own survival and success. This type of interaction makes competitive dynamics in platform. However, previous platform literature focuses on strategies to enhance network effect from the perspective of platform owner. Thus, there is little attention on interaction among the service providers. Using the framework based on community ecology of organizational ecology, we analyze interaction and strategy between platform owner and service provider in the viewpoint of platform openness strategy and platform pricing strategy. This research contributes to the literature of platform strategy by providing a theoretical framework based on organizational ecology to deeply understand the dynamics of platform.

• Journal of Korean Society of Transportation
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• v.17 no.3
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• pp.61-70
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• 1999

The Purpose of this study is to test whether Braess Paradox (BP) can be revealed in a real world network. Fer the study, Namsan 2nd tunnel case is chosen, which was shut down for 3 years for repair works. The revelation of BP is determined by analyzing network-wise traffic impacts followed by the tunnel closure. The analysis is conducted using a network simulation model called SECOMM developed for the congestion management of the Seoul metropolitan area. Also, the existence of BP is further identified by a before-after traffic survey result of the major arterials nearby the Namsan 2nd tunnel. The model estimation expected that the closure of Namsan 2nd tunnel improve the network-wise average traffic speed from 21.95km/h to 22.21km/h when the travel demand in the study area and congestion Pricing scheme on Namsan 1st & 3rd tunnels remain unchanged. In addition, the real world monitoring results of the corridors surrounding Namsan 2nd tunnel show that the average speed increases from 29.53km/h to 30.37km/h after the closure. These findings clearly identify the BP Phenomenon is revealed in this case.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.2
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• pp.115-123
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• 2018

This study is empirically intended to put forward the modeling and process improvement measures for the SCM capability in small venture firms. The findings are summarized as follows. There were strategic alliance, technological development and centralization in the modeling of strategic planning for supply chain, not the least of which is strategic alliance, followed by centralization and technological development. There were routing scheduling, network integration and third party logistics outsourcing in decision making, not the least of which was network integration. There were customer service management, productivity management and quality management in management control, not the least of which was quality management. And there were order management choice, pricing demand, shipment delivery and customer management in transaction support system, not the least of which was order management choice. As for the above-mentioned findings, to maximize the SCM capability and operate the optimized process in small venture firms, the existing strategic alliances can optimize the quality management and stabilize the transaction support system through the network sharing and integration from the perspective of relevant organizational members' capability and process improvement. And the strategic linkage between firms can maximize the integrated capability of information system beyond the simple exchange relation between electronic data, achieving a differentiated competitive advantage. Consequently, the systematization and centralization for the maximization of SCM capability, including the infrastructure construction based on the system compatibility and reliability for information integration, should be preceded before the modeling of the integrated capability for optimum supply chain and the best process management in the smart era.

• Journal of Korea Technology Innovation Society
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• v.20 no.2
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• pp.368-386
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• 2017

The purpose of this study is to present the technology value model based on profit approach and IITP practical guide for Ethernet network technology, which is the core technology of autonomous vehicles and connected cars in the hyper-connected industry. In-vehicle network, Ethernet technology, Ethernet port count, port pricing, and application data for technology assessment are sources of global market research organizations. The data on the company's COGS (Cost of Goods Sold), operating capital requirement, capital expenditure, and income statement data are used by the Bank of Korea's Business Analysis Report. According to the results of the study, the product market size was estimated to be US $470.3 billion and the technology market size was $52.1 billion over the seven years of economic life cycle of technology. The market value of the technology was estimated to be $260 million reflecting the possibility of entry into the market. In the case of the corporate management analysis report, the average value of the IITP and the top 25% were $0.7 million and $40.2 million, respectively. -27.8 million, and -73.6 million dollars respectively. This implies that government support for policy support is needed when conducting corporate R&D with high cost-to-sales ratio. The results of this study can be used as a reference for the evaluation of technology demand based ICT R&D technology in the industrial internet market in the fourth industrial revolution era.

• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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• pp.9-19
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• 2016

In finance literature, stock liquidity showing how stocks can be cashed out in the market has received rich attentions from both academicians and practitioners. The reasons are plenty. First, it is known that stock liquidity affects significantly asset pricing. Second, macroeconomic announcements influence liquidity in the stock market. Therefore, stock liquidity itself affects investors' decision and managers' decision as well. Though there exist a great deal of literature about stock liquidity in finance literature, it is quite clear that there are no studies attempting to investigate the stock liquidity issue as one of decision making problems. In finance literature, most of stock liquidity studies had dealt with limited views such as how much it influences stock price, which variables are associated with describing the stock liquidity significantly, etc. However, this paper posits that stock liquidity issue may become a serious decision-making problem, and then be handled by using data mining techniques to estimate its future extent with statistical validity. In this sense, we collected financial data set from a number of manufacturing companies listed in KRX (Korea Exchange) during the period of 2010 to 2013. The reason why we selected dataset from 2010 was to avoid the after-shocks of financial crisis that occurred in 2008. We used Fn-GuidPro system to gather total 5,700 financial data set. Stock liquidity measure was computed by the procedures proposed by Amihud (2002) which is known to show best metrics for showing relationship with daily return. We applied five data mining techniques (or classifiers) such as Bayesian network, support vector machine (SVM), decision tree, neural network, and ensemble method. Bayesian networks include GBN (General Bayesian Network), NBN (Naive BN), TAN (Tree Augmented NBN). Decision tree uses CART and C4.5. Regression result was used as a benchmarking performance. Ensemble method uses two types-integration of two classifiers, and three classifiers. Ensemble method is based on voting for the sake of integrating classifiers. Among the single classifiers, CART showed best performance with 48.2%, compared with 37.18% by regression. Among the ensemble methods, the result from integrating TAN, CART, and SVM was best with 49.25%. Through the additional analysis in individual industries, those relatively stabilized industries like electronic appliances, wholesale & retailing, woods, leather-bags-shoes showed better performance over 50%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.11C
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• pp.1178-1188
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• 2002

Local Loop Unbundling(LLU) has been understood as the way of facilitate the competition on the access and the local telephone service market. There are major benefits of stimulating the competition in the local service, avoiding access network duplication and reducing in environmental disruption. However, LLU has several disadvantages such as removing incentives for building alternative access networks, undermining existing investment in alternative access networks, introducing new substantial costs to the industry and requiring prolonged and detailed regulatory intervention. The economic effects of LLU generally will be different according to the special situation of each countries and the object of LLU. In case of EU, most of countries have already introduced and implemented LLU. But EU can't expect the economic effects on LLU emerged in the early stage of introducing it and faced with dilemma. To be realized the successful implementation of LLU, I think, it is required to be reviewed about the main issues such as the problem of regulation, the reasonable level of LLU pricing and the technical & operational problems.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.9-17
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• 2021

With the advancement of big data analysis, artificial intelligence, machine learning, etc., data analytics technology has developed to help with optimal decision-making. However, in certain areas, the lack of data restricts the use of these techniques. For example, real estate related data often have a long release cycle because of its recent release or being a non-liquid asset. In order to overcome these limitations, we studied the scalability of the existing time series through the TimeGAN model. A total of 45 time series related to weekly real estate data were collected within the period of 2012 to 2021, and a total of 15 final time series were selected by considering the correlation between the time series. As a result of data expansion through the TimeGAN model for the 15 time series, it was found that the statistical distribution between the real data and the extended data was similar through the PCA and t-SNE visualization algorithms.