Research and Analysis of Structural Hole and Matching Coefficient

Cai, Penghua; Zhang, Hai; Liu, Hong; Pan, Rong; Liu, Zheng; Li, Hui

doi:10.4236/jsea.2010.311127

Cited by 3 publications

(4 citation statements)

References 13 publications

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“…To further analyze the relationship involved, we conducted structural holes analysis through the UCINET. If nodes across more structural holes, they have less redundant connections, can access more non-redundant information and are used more frequently (Cai, Zhao, Liu, Pan, Liu, & Li, 2010). The paper uses the structural constraint algorithm to compute structural holes.…”

Section: Index Analysis Of the Networkmentioning

confidence: 99%

Strategic Design of the Purchase System Toward R&D Supply Chain Based on SNA

Cheng

Wen

2015

International Journal of Information Systems and Supply Chain Management

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In order to make the strategy for research and development (R&D) purchase system better serve the personalization of material requirements in R&D process, the authors propose to develop a strategy set which will satisfy the internal as well as external constraints simultaneously. Social network analysis is used to analyze the vertical and horizontal relationships among the project, department and enterprise layers. Through a case study, the authors display the regulatory relationship of participants under given organization pattern and supply chain configuration. To disclose the restricted equilibrium mechanism of participants involved, changes under different strategies are compared, which can assist enterprises to enforce the decision making and to improve the R&D purchase system ability. The authors outline some of the managerial implications arising from the research findings at the end of this paper.

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Section: Index Analysis Of the Networkmentioning

confidence: 99%

Strategic Design of the Purchase System Toward R&D Supply Chain Based on SNA

Cheng

Wen

2015

International Journal of Information Systems and Supply Chain Management

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“…Structural holes point to important seats in network, and based on Burt, they are the relationship between two non-duplicate persons (1). The major advantage of this theory is its ease of understanding and implementation (2).…”

Section: Introductionmentioning

confidence: 99%

“…Algorithms for extracting structural holes from network data are centrality measures, PageRank, hypertext induced topics search (HITS), and redundancy. Centrality measures (specially betweenness and closeness) (1). Opinion leaders are the very central nodes in a network.…”

Section: Introductionmentioning

confidence: 99%

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Extracting Structural Holes in Iran Medical Genetics Scientists’ Co-authorship Network: A Case Study of Faculty Members in Five Selected Centers

Zarei

Salari

Jafarzadeh

2018

Hormozgan medical journal

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Background: Structural holes as a considerable issue in network approach can be tracked in central indices. Objectives: This research aims to survey indices that can measure structural holes. We are looking for the most important scientific authors and their connections in the field of medical genetics to facilitate information flow in the network of medical genetics relations. Methods: First, co-authorship network of Iranian medical genetics scientists (faculty members) was extracted via searching Scopus, Web of Science, and PubMed databases, as a result of which 7451 articles were retrieved. With co-authorship techniques, the most central nodes in the network were picked as highlighted scientists. In the next phase, two other indices (i.e., hypertext induced topics search [HITS] and PageRank) were calculated with the help of Sci2 and compared to redundancy, efficiency and effective size as structural hole indices. Results: There was a significant relationship between the two groups of indices. There were few structural holes in our network because redundancy and constraint were low. Constraint index and centrality indices can be used for extracting structural holes. Conclusions: In confirmation of previous studies, the constraint index can be used as a method for extracting structural holes. Compared to the HITS algorithm, the constraint index works best in this regard. At the same time, the study of HITS and PageRank indicators showed a significant association between the figures derived from the calculation of these two indicators, and each one can be employed to find structural holes.

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Exploring the Peer Interaction Effects on Learning Achievement in a Social Learning Platform Based on Social Network Analysis

Lin

Chen

Chang³

et al. 2017

International Journal of Distance Education Technologies

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The benefits of social learning have been recognized by existing research. To explore knowledge distribution in social learning and its effects on learning achievement, we developed a social learning platform and explored students' behaviors of peer interactions by the proposed algorithms based on social network analysis. An empirical study was also conducted on a college course to investigate the correlation between peer interaction and learning achievement. The experiment results show that the students who tended to actively contribute knowledge to peers on the social learning platform had better learning achievements than the students who were used to the passive reception of knowledge. Besides, the knowledge transmitters and intermediaries performed better in learning achievement as well, and the knowledge contributors had closer interactions with their peers. The implications derived from the findings can inspire instructors/researchers to facilitate effective social learning, and provide suggestions to develop effective algorithms to analyze social interaction behaviors.

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Research and Analysis of Structural Hole and Matching Coefficient

Cited by 3 publications

References 13 publications

Strategic Design of the Purchase System Toward R&D Supply Chain Based on SNA

Strategic Design of the Purchase System Toward R&D Supply Chain Based on SNA

Extracting Structural Holes in Iran Medical Genetics Scientists’ Co-authorship Network: A Case Study of Faculty Members in Five Selected Centers

Exploring the Peer Interaction Effects on Learning Achievement in a Social Learning Platform Based on Social Network Analysis

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