• The Journal of the Korea Contents Association
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• v.16 no.9
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• pp.127-135
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• 2016

We identified a competition network which has never been studied before and investigated the relationship between centrality of participants in singing competition and their winning percentage within the competition network. We collected competition data from 'Immortal Songs: Singing the Legend', which is a Korean television music competition program, and constructed a competition network. We calculated centrality and winning percentage and analyzed their relationship using correlation analysis, regression analysis, and visualization. There are four main findings in this research. First, a competition network is a scale-free network whose degree distribution follows a power law. Second, there is a logarithmic relationship between the count of competition and closeness. Third, winning percentage converges to approximately 60% for players who have participated in more than 20 competitions. Lastly, a strength of opponents affects approximately 23% of winning percentage for players with less than 20 competitions. The academic significance of this study is that we pioneered the definition of the competition network and applied social network analysis method. Another significant contribution of this paper is that we found explicit patterns between the centrality and winning percentage, suggesting ways to improve social relationship in competition network and to increase winning percentage.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.18-24
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• 2022

State highway agencies (SHAs) typically apply a competitive procurement procedure to select contractors for their design-bid-build projects. Since the level of competition affects construction bid prices and project outcomes, the Federal Highway Agency (FHWA) suggests SHAs seek ways to improve competition among contractors continuously. However, they rarely conduct an empirical assessment of the current competition level necessary to identify room for improvement. Besides the number of bidders on a project, other factors such as winning or losing rates among the contractors in previous projects can also indicate the degree of competition; only a few contractors may have won the majority of the projects in a specific region. However, few studies have investigated such factors. This paper proposes a network analysis-based approach to evaluating contractor competition levels of highway projects using historical bid tabulation data. The proposed method provides insights into overall competition levels, the determination of competitive contractors, and winning rate distribution among contractors.

• Journal of Navigation and Port Research
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• v.38 no.3
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• pp.307-315
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• 2014

This paper aims to empirically examine how shipping companies can effectively acquire knowledge from their strategic alliance partners. This paper adopts cooperative network embeddedness mechanism, such as network density and tie closeness, as a channel through which to acquire more knowledge for shipping participants within a strategic alliance network. This study also examines the moderating role of competition between alliance partners in reinforcing the effectiveness of the cooperative relationships on the knowledge acquisition. Based on the literature, hypotheses to predict the aforementioned associations between cooperative network embeddedness and knowledge acquisition and the moderating role of competition in facilitating that association are established. A quantitative research method using survey data conducted in the Korean shipping industry was employed in order to empirically test the presented hypotheses. The results show that if players in a shipping alliance network are embedded in a dense network and have close relationships with their alliance partners, this helps to facilitate a greater degree of knowledge acquisition from the partners; and the impact of network density on the knowledge acquisition would be intensified with the higher level of competition between shipping companies.

• Journal of the Korea Safety Management & Science
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• v.17 no.3
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• pp.265-272
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• 2015

The competition between companies for prior occupation of the market is becoming fierce. In this highly competitive situation, it is important for companies to differentiate themselves if they are going to have a chance at success. And the competition to create the best solution method possible is higher than ever. Increased competition is forcing companies to lower costs and improve efficiency. A supply chain management(SCM) has become one of the most important solution methods of competitive advantage. This study has developed a simulator for the supply chain network problem. The simulator is designed to simulate the conditions of an actual supply chain network considering uncertainties. The simulator developed using commercial simulation tool ARENA and the results of computational experiments for a simple example were given and discussed to validate the developed simulator. Further research is needed, but using the simulator could become a useful tool for decision making in the supply chain network area.

• Journal of the Korean Operations Research and Management Science Society
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• v.35 no.4
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• pp.55-79
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• 2010

This study deals with a model for platform competition in a two-sided market. We suppose there are both direct and indirect network externalities between suppliers and users of each platform. Moreover, we suppose that both users and suppliers are distributed in their relative affinity for each platform type. That is, each user [supplier] has his/her own preferential position toward each platform, and users [suppliers] are horizontally differentiated over [0, 1]. And for analytical tractability, some parameters like direct and indirect network externalities are the same across the markets. Given the parameters and the pricing profile, users and suppliers conduct subscription game, where participants select the platform that gives them the highest payoffs. This game proceeds according to a replicator dynamics of the evolutionary game, which is simplified by properly defining gains from participant's strategy in the subscription game. We find that depending on the strength of these network effects, there might either be multiple stable equilibria, at which users and suppliers distribute across both platforms, or one unstable interior equilibrium corresponding to the market tipping in favor of either platform. In both cases, we also consider the pricing power of competing platform providers under the framework of the Stackelberg game. In particular, our study examines the possible effects of the type of competition between platform providers, which may constrain the equilibrium selection in the subscription game.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.1
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• pp.111-124
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• 1999

This evapaper is toluate the forecasting performance of three neural network(NN) approaches against ARIMA model using the famous time series analysis competition data. The first NN approach is to analyze the second Makridakis (M2) Competition Data using Multilayer Perceptron (MLP) that has been the most popular NN model in time series analysis. Since it is recently known that MLP suffers from bias/variance dilemma, two approaches are suggested in this study. The second approach adopts Cascade Correlation Network (CCN) that was suggested by Fahlman & Lebiere as an alternative to MLP. In the third approach, a time series is separated into two series using Noise Filtering Network (NFN) that utilizes autoassociative memory function of neural network. The forecasts in the decomposition analysis are the sum of two prediction values obtained from modeling each decomposed series, respectively. Among the three NN approaches, Decomposition Analysis shows the best forecasting performance on the M2 Competition Data, and is expected to be a promising tool in analyzing socio-economic time series data because it reduces the effect of noise or outliers that is an impediment to modeling the time series generating process.

• ETRI Journal
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• v.30 no.4
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• pp.587-596
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• 2008

Facility-based competition (FBC) in the telecommunications market is considered to have lower static efficiency in the short term and higher dynamic efficiency in the long term. Under service-based competition (SBC), the entrant can reduce its setup costs by leasing network facilities from the incumbent, which makes the entrant viable, pushes the market price down and promotes static efficiency. This paper attempts to measure static efficiency by comparing the profits of the incumbent and entrant in terms of consumer surplus and social welfare under each competition type by extending the Stackelberg model. The results, assuming a linear demand function and variation in regulatory level, show that FBC results in higher social welfare than SBC on the whole. However, SBC accompanied by strong regulation is also shown to have the potential to be superior over FBC. It is also revealed that FBC exhibits a higher producer surplus (particularly, the incumbent's producer surplus) and is, therefore, more desirable in terms of dynamic efficiency. When the entrant's cost is high in FBC, social welfare is shown to be lowered, implying that cost competitiveness is a necessary condition for social welfare.

• ETRI Journal
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• v.36 no.4
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• pp.572-580
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• 2014

Mobile operators in saturated markets increasingly favor mobile network sharing (MNS) over facility-based competition. Previous research examining MNS primarily focused on its positive effects, while the negative effects were largely overlooked. This study proposes a decision-making model using an analytic hierarchy process technique to evaluate decision-making criteria among various types of MNS policies. The decision-making model was applied to Wireless Broadband services in Korea to determine the relative importance of both positive and negative evaluation criteria and preference among multiple types of MNS policies. Positive evaluation criteria (that is, efficiency) were far greater in importance than negative evaluation criteria (that is, competition harm). The preference for adopting MNS among five alternative approaches was also revealed. The study findings offer immediate policy insights in Korea and provide a decision-making framework for policy makers in other countries to utilize.

• Journal of Information Technology Applications and Management
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• v.9 no.2
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• pp.1-16
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• 2002

Recently, neural network methods have been studied to find out more valuable information in data bases. But the supervised learning methods of neural networks have an overfitting problem, which leads to errors of target patterns. And the unsupervised learning methods can distort important information in the process of regularizing data. Thus they can't efficiently classify data, To solve the problems, this paper introduces a hybrid neural networks HACAB(Hybrid Algorithm combining a Competition learning model And BP Algorithm) combining a competition learning model and 8P algorithm. HACAB is designed for cases which there is no target patterns. HACAB makes target patterns by adopting a competition learning model and classifies input patterns using the target patterns by BP algorithm. HACAB is evaluated with random input patterns and Iris data In cases of no target patterns, HACAB can classify data more effectively than BP algorithm does.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.105-113
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• 2017

Network externality can be defined as the effect that one user of a good or service has on the value of that product to other people. When a network externality is present, the value of a product or service is dependent on the number of others using it. There exist asymmetries in network externalities between the online and traditional offline marketing channels. Technological capabilities such as interactivity and real-time communications enable the creation of virtual communities. These user communities generate significant direct as well as indirect network externalities by creating added value through user ratings, reviews and feedback, which contributes to eliminate consumers' concern for buying products without the experience of 'touch and feel'. The offline channel offers much less scope for such community building, and consequently, almost no possibility for the creation of network externality. In this study, we analyze the effect of network externality on the competition between online and conventional offline marketing channels using game theory. To do this, we first set up a two-period game model to represent the competition between online and offline marketing channels under network externalities. Numerical analysis of the Nash equilibrium solutions of the game showed that the pricing strategies of online and offline channels heavily depend not only on the strength of network externality but on the relative efficiency of online channel. When the relative efficiency of online channel is high, the online channel can greatly benefit by the network externality. On the other hand, if the relative efficiency of online channel is low, the online channel may not benefit at all by the network externality.