SNA Based Expert Knowledge Map Design for Ship-Block Scheduling Decision-Making

2013 ◽  
Vol 694-697 ◽  
pp. 3522-3525 ◽  
Author(s):  
Yong Wen Huang ◽  
Zu Hua Jiang ◽  
Li Jun Liu
Keyword(s):  
Decision Making ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Block Scheduling ◽  
Expert Knowledge ◽  
Knowledge Map ◽  
Map Building ◽  
Map Design ◽  
Reliable Basis

To organize the experts rationally and facilitate the sharing of expert knowledge, an expert knowledge map framework based on social network analysis (SNA) for ship-block scheduling is proposed. The function of expert knowledge map is analyzed, and the approaches of SNA based knowledge map building are introduced. Then, the network structure was analyzed quantitatively to find the factors that hold back the spreading and innovating of knowledge by SNA. The result indicates that SNA can offer the reliable basis on how to take strong measures to organize the experts, which can improve the expert knowledge map’s structure and the effectiveness of knowledge navigation and sharing.

Computing an effective decision making group of a society using social network analysis

2013 ◽  
Vol 28 (3) ◽  
pp. 577-587 ◽  
Author(s):  
Donghyun Kim ◽  
Deying Li ◽  
Omid Asgari ◽  
Yingshu Li ◽  
Alade O. Tokuta ◽  
...  
Keyword(s):  
Decision Making ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Effective Decision ◽  
Effective Decision Making

Social Network Analysis

2021 ◽  
pp. 155-184
Author(s):  
Yuh-Wen Chen
Keyword(s):  
Decision Making ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Multiple Criteria Decision Making ◽  
Multiple Objective ◽  
Self Organizing Map ◽  
Social Communities ◽  
The Social ◽  
Long Time

Social network analysis (SNA) is an attractive problem for a long time when social communities were popular since 2010. Scholars like to explore the meaning behind the numerous interactions generated at these social media sites. The primary and essential issue of SNA is to monitor, estimate, and engage the potential influencers who are most relevant and active to network. If we can analyze the social network this way, business enterprises could use minimal efforts to sustain the activity of influential users, improve sales, and enhance their reputations. In this chapter, a research framework based on multiple-criteria decision making (MCDM) is proposed. The authors will show how scholars could use dynamic self-organizing map (SOM) based on multiple-objective evolving algorithm (MOEA) and static weighted influence non-linear gauge system (WINGS) to analyze a social network. Finally, comparisons are made between the innovative approaches and the methods in tradition.

Ties that Bother - Ties that Matter

2017 ◽  
Vol 133 (1) ◽  
pp. 29-45
Author(s):  
Renáta Hosnedlová
Keyword(s):  
Decision Making ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Structural Characteristics ◽  
Third Parties ◽  
Decision Making Process

The aim of this article is to show that it is necessary to consider the negative, latent and lost ties, and those with the quality “zero” when studying the formation, change and reaffirmation of residential intentions and decisions. We use the case of Ukrainian immigrants residing in Spain, where we focus on the negative ties and the effects of relational strain among third parties, applying the approach of qualitative social network analysis. We pinpoint the compositional and structural characteristics of negative ties that are significant concerning decision-making process and constructing collecting data tools.

scholarly journals The Effect Of The Relationships Between Affiliated Firms On Direction Of Income Shifting Within Business Groups

2014 ◽  
Vol 30 (3) ◽  
pp. 817 ◽  
Author(s):  
Kyung Jin Park ◽  
Joohyun Lim ◽  
Ki Young Kim
Keyword(s):  
Decision Making ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Ownership Structure ◽  
Business Group ◽  
The Other ◽  
Centrality Measures ◽  
Income Shifting ◽  
Tax Burden

<p>In this study, we examined how income shifting performs among affiliates in a business group to maximize the benefits of the entire business group in terms of minimizing the tax burden, with a particular focus on the direction of income shifting between affiliates within the business group. We find that tax-related decision-making for the entire business group is affected by the relationships between the affiliated firms, that is, the ownership structure of the whole business group. To analyze the ownership structure, we use centrality measures in a social network analysis. The results show that affiliates with the higher outdegree-centrality; that is, firms investing more shareholdings in other affiliates have a tendency to perform more income shifting. On the other hand, the affiliates with high indegree-centrality, that is, firms which are owned by other affiliates, were revealed to be given the income shifting from other affiliated firms to minimize the tax burden of the entire business group.</p>

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