Identification and Evaluation Methods of Expert Knowledge Based on Social Network Analysis

This study aims to construct a theoretical framework to analyze the elements of the network structure and the relationship system within the seafood supply chain. The scope of the investigation is to evaluate how these elements influence the flow of products and the efficiency of the seafood supply chain and why these social interactions can create value and enhance competitive advantage. The model combines the resource- and knowledge-based view and the social network analysis applied to seafood supply chains. To demonstrate the application of the model, two theoretical examples and a real case study of the Mercado del Mar in Guadalajara, Mexico, are used. Primary data are obtained from semi-structured interviews, social network analysis metrics, and qualitative analysis. Findings are based on the analysis of theoretical examples and must be considered with caution. Nevertheless, the observations in the examples and case study provide new arguments to the relationship between the pattern of interrelationship and the efficiency of a supply chain. This study emphasizes the necessity of combining quantitative and qualitative analyses to understand and explain real-life supply networks.

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

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.694-697.3522 ◽

2013 ◽

Vol 694-697 ◽

pp. 3522-3525 ◽

Cited By ~ 1

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.

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Use of Social Network Analysis for Tax Control in Spain

Revista Hacienda Pública Española ◽

10.7866/hpe-rpe.21.4.5 ◽

2021 ◽

Vol 239 (4) ◽

pp. 159-197

Author(s):

Ignacio González ◽

◽

Alfonso Mateos ◽

Keyword(s):

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Best Practices ◽

Expert Knowledge ◽

Lessons Learned ◽

Research Strategies ◽

Comprehensive Overview ◽

Net Worth ◽

Experienced User

The Spanish Tax Agency is an experienced user of big data and has now deployed social network analysis (SNA) tools. SNA tools have led to a qualitative leap in such wide-ranging areas as tax collection, enforcement, control of ultra-high-net-worth individuals, and money laundering. This paper presents a comprehensive overview of the different lines of research, strategies and results of nine projects over the last five years, including the lessons learned. We present the best practices in pattern discovery, the tools developed for the control of big fortunes and the strategy developed to create a bridge between expert knowledge and SNA technologies. We highlight the results of investigating interposed entities used to channel personal remuneration, complex corporate structures, and opaque companies.

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