• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.4
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• pp.1-18
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• 2015

This paper proposes relational capability as a main driver of constructing inter-organizational collaboration networks. Based on social network theory and relational view literature, three components of relational capability are constructed and implemented by an agent-based model. The components include organizational capability, structural capability, and trust between a partner and a focal firm. These three components are updated by two micro mechanisms: structural mechanism and relational mechanism. Structural mechanism is a feedback loop in which the relational capability increases structural capability and vice versa. Relational mechanism is a learning-by-doing process in which a focal firm experiences success or failure of collaboration and the experience increases or decreases cumulative trust in a partner firm. Result of agent-based simulation shows that a collaboration network emerges through interactions of firm's relational capabilities and the characteristics of emerged networks vary with the contribution of structural capability and trust to relational capability. Specifically, in case structural capability contributes more to relational capability, the average degree centrality and collaboration proportion increases as time passes and enters into an equilibrium state. In that case, almost every firms participated in the network collaborates each other so that the emerged network becomes highly cohesive. In case trust contributes more to relational capability, the results are reversed. In an equilibrium state, the balance of contribution between structural capability and trust makes an emerged network larger and maximizes average degree centrality of the network.

• Journal of the Speleological Society of Korea
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• no.88
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• pp.38-44
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• 2008

This study aims to identify the efficiency by applying diverse index to the positions of vertex in the network among the network analysis methods in order to identify the relational location features of caves. The first consideration was about the relational location features according to the linking degree and centrality of cave. The second consideration was about the structural equivalence between caves or between caves and the surrounding tourists attractions. A variety of index examined in this study is very efficient for identifying the positions of caves in the network. Furthermore, the relational location features in consideration of surrounding tourists attractions identified the availability of more objective and quantitative expression. In particular, when there are other caves around a cave, it is also very useful to identify the structural equivalence or comparison with other caves.

• Journal of Korean Society of Rural Planning
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• v.11 no.3 s.28
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• pp.29-42
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• 2005

This study aimed to apply a methodological approach, 'social network analysis' to a case study for the understanding of relational structure among stakeholders related to green tourism development. By doing so, this study argued that it is important to identify stakeholder's network structure to help green tourism planners develop collaborative relationship among stakeholders. This study identified the stakeholders regarding a community-based festival development in the southern area of Korea, and investigated two types of networks among them: decision-making power relational and intimate network. Interviewer-administrated survey and in-depth interview were employed for data collection. The data was analyzed by SPSS (version 10.0) and Net-MinerII (version 2.5.0), and by constant comparison method. The result revealed that low different groups of the stakeholders were separated in the intimate networt and that the festival organizational body was not connected with other stakeholders in the decision-making power relational network. The existence of separated groups and weak relationship among the stakeholders appeared to relate to age-group differences, and different views on the festival between the stakeholders.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.10
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• pp.77-85
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• 1993

In this paper, we present a method to solve a convexly combined fuzzy relational equation with generalized connectives. For this, we propose a neural network whose structure represents the fuzzy relational equation. Then we derive a learning algorithm by using the concept of back-propagation learning. Since the proposed method can be used for a general form of fuzzy relational equations, such fuzzy max-min or min-max relational equations can be treated as its special cases. Moreover, the relational structure adopted in the proposed neurocomputational approach can work in a highly parallel manner so that real-time applications of fuzzy sets are possibles as in fuzzy logic controllers, knowledge-based systems, and pattern recognition systems.

• Asia-Pacific Journal of Business
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• v.10 no.4
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• pp.49-63
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• 2019

The export regulation of semiconductor core materials, which began with the recent revision of the export management regulations of Japan, raises the need for a new cooperation network. A hierarchical management network that was effective in the fast-follower system requires organic cooperation between the public sector and industry through a multilateral network that emphasizes horizontal co-operation among innovation actors. This study focused on the relational capital that exists among members of a business association such as an association that has been relatively marginalized from previous studies. In addition, this study aimed to analyze the effect of network activity characteristics such as industry-university linkage and informal exchange on technological innovation. Through this, I would like to draw implications for enhancing the effectiveness of the government's R & D support and innovation performance of R & D companies. Based on the results of the SMEs R & D survey, this study found that relational capital, informal exchange had a positive effect on technological innovation performance. However, if the relational capital exceeds a certain level, it is analyzed that there is a negative effect due to group think and lock-in effect. This means that informal exchange channels should be expanded for innovation and enhancement, and relational capital should be managed in consideration of the negative effects that may occur when certain levels are exceeded.

• Knowledge Management Research
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• v.14 no.1
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• pp.21-37
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• 2013

Due to the development of social networks and smartphones, many different kinds of issues have emerged in business and society. By reflecting these trends, social network sites have appeared and they are recognized as the new concept of sites. The major feature of the social network sites is that the social relationship had been taken to the online space. Social network sites support the formation of a network and offer users the relationship between users offline as well as online. Based on the features mentioned above, users enjoy the benefits using social network sites. These social network sites in the enterprise can be used to form relationships with customers. This study identified the influencing factors as relational benefits and social influence on relationship commitment in social network sites. In addition, we analyzed that how the relationship commitment between users affects user loyalty after their using social network sites. We presented empirical results by utilizing structural equation model with 244 respondents and the significant implications for the academy and the practice with discussions.

• Journal of the Speleological Society of Korea
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• no.86
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• pp.8-15
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• 2008

This study is about the efficiency of graph theory that can be applied as the research analysis method in order to identify the relational location features of the caves favored as the ecological tourists attraction. Creating network with traffic nodes and surrounding tourists attractions in a certain space including the caves as the tourists attraction and structural analysis on the overall network using various kinds of index will be very useful method to identify the relational location features and benefits from linking the caves as the tourists attractions. In particular, it can be applied to set the spatial scope in the tourism development plan including the caves as the tourists attractions.

• World Technopolis Review
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• v.5 no.1
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• pp.47-60
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• 2016

In today's digital non-linear global business environment, innovation initiatives are influenced by inter-organizational, political, economic, environmental, technological systems, as well as by decisions made individually by key actors in these systems. Network-based structures emerge from social linkages and collaborations among various actors, creating innovation ecosystems, complex adaptive systems in which entities co-create value. A shared vision of value co-creation allows people operating individually to arrive together at the same future. Yet, relationships are difficult to see, continually changing and challenging to manage. The Innovation Ecosystem Transformation Framework construct includes three core components to make innovation relationships visible and articulate networks of relational capital for the wellbeing, sustainability and business success of innovation ecosystems: data-driven visualizations, storytelling and shared vision. Access to data facilitates building evidence-based visualizations using relational data. This has dramatically altered the way leaders can use data-driven analysis to develop insights and provide ongoing feedback needed to orchestrate relational capital and build shared vision for high quality decisions about innovation. Enabled by a shared vision, relational capital can guide decisions that catalyze, support and sustain an ecosystemic milieu conducive to innovation for business growth.

• Journal of Korea Multimedia Society
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• v.12 no.7
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• pp.1022-1031
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• 2009

In this paper, we propose a researcher modeling technique based on ontology and construct social network for researchers using diverse relational properties. User ontology schema is created by extending the existing HR-XML model for a researcher model. User ontology schema and instance are created by OWL. We compose social network model for efficient cooperation between researchers using static relational properties such as educational background and dynamic relational properties such as co-authors and co-workers, etc. Closeness has direction because researcher network is differently configured by the researchers. We define inferencing rules using SWRL and inference ontology rules using racer inference machine to compose direct relationships between researchers. The proposed model for researchers can be applied to the cooperation model for researchers by retrieving common expert group dynamically.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.1
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• pp.75-84
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• 2021

For analyzing big data, the social network is increasingly being utilized through relational data, which means the connection characteristics between entities such as people and objects. When the relational data does not exist directly, a social network can be configured by calculating relational data such as attribute similarity from attribute data of entities and using it as links. In this paper, the composition method of the social network using the attribute similarity between entities as a connection relationship, and the clustering method using subgroups for the configured social network are suggested, and the clustering effectiveness of the clustering results is evaluated. The analysis results can vary depending on the type and characteristics of the data to be analyzed, the type of attribute similarity selected, and the criterion value. In addition, the clustering effectiveness may not be consistent depending on the its evaluation method. Therefore, selections and experiments are necessary for better analysis results. Since the analysis results may be different depending on the type and characteristics of the analysis target, options for clustering, etc., there is a limitation. In addition, for performance evaluation of clustering, a study is needed to compare the method of this paper with the conventional method such as k-means.