• Journal of Korean Society of Rural Planning
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• v.23 no.3
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• pp.147-161
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• 2017

Climate changes from global warming and reduction in agricultural land result in volatility of prices of agricultural products, causing a imbalance of food market in Korea. It is necessary to develop a transnational food industry cooperation system among Korea, China and Russia that directly or indirectly affect food industry in terms of the whole industrial network. This study analyzes the value chain and linkage in the agriculture, forestry and fisheries industries in three nations. The unit structure and the industrial patterns of three nations were derived using the World Input-output Table (WIOT) from 2004 to 2014 every five years. This paper is expected to contribute to develop food security cooperation in the northern part of the Korean peninsula and to promote the mutual growth of food industry through industry linkage and cooperation.

• Journal of Korea Technology Innovation Society
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• v.11 no.2
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• pp.145-170
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• 2008

The existence of network is indeed the single most important factor that brings about new business phenomena in the new digital economy, especially in the IT industry. Network effect refers to a phenomenon that the increase in size of the network leads to increased network value and user utility. It determines the competitive structure of an industry and the performances of industry competitors (Shapiro and Varian, 1999). The phenomenon of increasing returns and winner-take-all enjoyed by the early winner in the competition can be attributed to the existence of positive feedback which increases the value of network and induces more users into join the network (Arthur, 1996; Shapiro and Varian, 1999; Song and Lee, 2003). This research attempts to shed light on the topic of innovation and competitive strategy of network-based industries. We analyze the case of the Korean mobile communications industry, in which a shift in technological paradigm from 2G to 3G brought new changes to the competitive structure of the industry. The Korean mobile communications industry makes an ideal case for analysis since it is an industry whose value is inherently dependent upon its user network. It is characterized by the typical increasing returns, in which a monopolizing player is enjoying firstmover's network effects. Because of the existence of network in the mobile communications industry, latecomers' disruptive innovations could not outcompete the incumbent's sustaining innovations. The contribution of this research lies in laying a groundwork for future studies by introducing a numerical simulation model to analyze the complexity theory and network effect.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.1-10
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• 2013

The value added network service industry has played and important role in the telecommunication service industry and in the economic development of Korea. This study uses input-output analysis to investigate the role of value added network service sector in the Korean national economy for the period 2000, 2005, 2009, focusing on four topics in its application: production inducing effects, value-added inducing effect, employment-inducing effects by demand-driven model and supply shortage effect by supply-driven model, inflation impacts by the Leontief price model, finally analysing inter-industry linkage effects. The results of this study are as follows: production inducing effects analysis 2000 0.5253won to 2009 1.31314won, value-added inducing effects 0.25112won to 0.5337won employment inducing effects from 0.09749 to 0.21025 people grew, the supply shortage effect from 1.29003 to 2.12048won, price impact of Leontief price model was increased from 0.0022% to 0.00258%. Finally, inter-industry linkage effects, appeared to have the characteristics of final demand raw industrial.

• Asia pacific journal of information systems
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• v.9 no.3
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• pp.93-110
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• 1999

The previous studies regarding the stock returns have advocated that industry effects exist over entire industry. As the industry categories are more rigid, the demand for predicting the industry sectors is rapidly increasing. The advances in Artificial Intelligence and Neural Networks suggest the feasibility of a valuable computational model for stock returns prediction. We propose a sector-factor model for predicting the return on industry stock index using neural networks. As a substitute for the traditional models, neural network model may be more accurate and effective alternative when the dynamics between the underlying industry features are not well known or when the industry specific asset pricing equation cannot be solved analytically. To assess the potential value of neural network model, we simulate the resulting network and show that the proposed model can be used successfully for banks and general construction industry. For comparison, we estimate models using traditional statistical method of multiple regression. To illustrate the practical relevance of neural network model, we apply it to the predictions of two industry stock indexes from 1980 to 1995.

• Journal of Korea Society of Digital Industry and Information Management
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• v.20 no.2
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• pp.141-157
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• 2024

This study examines the impact of cryptocurrency value characteristics on cryptocurrency investment intention. Stock craze and information provided through various media, including YouTube, play an essential role in helping investors recognize the value of cryptocurrency and develop positive investment intentions. In this study, we applied the Value-Based Adoption Model (VAM) to verify the relationship between cryptocurrency value characteristics and investment intention. We surveyed 500 cryptocurrency investors to assess network externalities, awareness, compatibility, cost benefits (fees), technicality, security, perceived value, and investment intentions. SEM (Structural Equation Modeling) using AMOS 26.0 was used for data analysis. Results show that network externalities, awareness, compatibility, cost benefits (fees), security, and perceived value significantly impact investment intention. This study provides insights that help investors accurately perceive cryptocurrencies and develop strategies to increase investment intentions. It also contributes to improving investors' decision-making ability. This comprehensive approach will foster the growth of the cryptocurrency market and strengthen investor confidence.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2150-2156
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• 2013

This study attempts to identify how the value network of mobile industry has evolved in the value creating process. The longitudinal case study on SK Telecom was conducted by measuring the SK Telecom's investment structure during from 1999 to 2008. Results show that the convergence services based on the advanced mobile networks changed the revenue structure, and enabled SK Telecom to reposition as a media company. For the value creation, SK Telecom's value network has flexibly adapted to convergence environment through dynamic asset reconfiguration.

• Journal of the Korean Society of Industry Convergence
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• v.5 no.2
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• pp.103-110
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• 2002

An artificial neural network is applied to the prediction of compressive strength, slump value of concrete. Standard mixed tables arc trained and estimated, and the results are compared with those of experiments. To consider the varieties of material properties, the standard mixed tables of two companies of Ready Mixed Concrete are used. And they are trained with the neural network. In this paper, standard back propagation network is used. For the arrangement on the approval of prediction of compressive strength and slump value, the standard compressive strength of 210, $240kgf/cm^2$ and target slump value of 12, 15cm are used because the amount of production of that range arc the most at ordinary companies. In results, in the prediction of compressive strength and slump value, the predicted values are converged well to those of standard mixed tables at the target error of 0.10, 0.05, 0.001 regardless of two companies.

• Journal of the Economic Geographical Society of Korea
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• v.19 no.3
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• pp.491-511
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• 2016

This paper attempts to understand the nature and dynamics of global value chains in the auto industry using the OECD TiVA 2015 edition on the bilateral foreign value added in exports over the period 1995-2011 and employing the techniques of social network analysis such as the computation of network measures and visualization of value added trade flows. It is shown that there has been a tendency towards increasing production fragmentation both within and across regions. The automotive value-added network is found to have small-world properties with a hierarchical, clustered and dense structure. The differences among the US, Germany and China as major suppliers of foreign value added in global automotive value chains are remarkably revealed. Although the fragmentation of production has been developed on a global scale, a dichotomous tension between center and periphery and domestic and foreign capital lies behind it.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.41-47
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• 2012

MANET has vulnerable structure on security owing to structural characteristics as follows. MANET consisted of moving nodes is that every nodes have to perform function of router. Every node has to provide reliable routing service in cooperation each other. These properties are caused by expose to various attacks. But, it is difficult that position of environment intrusion detection system is established, information is collected, and particularly attack is detected because of moving of nodes in MANET environment. It is not easy that important profile is constructed also. In this paper, conformal predictor - support vector machine(CP-SVM) based intrusion detection technique was proposed in order to do more accurate and efficient intrusion detection. In this study, IDS-agents calculate p value from collected packet and transmit to cluster head, and then other all cluster head have same value and detect abnormal behavior using the value. Cluster form of hierarchical structure was used to reduce consumption of nodes also. Effectiveness of proposed method was confirmed through experiment.

• Knowledge Management Research
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• v.22 no.4
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• pp.1-26
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• 2021

Measuring the intangible asset has been vigorously studied for its importance. Especially, the value of character in media industry is difficult to quantitatively evaluate in spite of the industry's rapid growth. Recently, the Social Network Analysis (i.e., SNA) has been actively applied to understand human usage patterns in a media field. By using SNA methodology, this study attempts to investigate how the character network characteristics of media works are linked to human search behaviors. Our analysis reveals the positive correlation and causality between character network centralities and character search data. This result implies that the character network can be used as a clue for the valuation of character assets.