scholarly journals Research on Enterprise Competitive Information Management Based on Co-Occurrence Analysis

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Peng Wu ◽  
Ran Feng
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Multidimensional Scaling ◽  
Scaling Analysis ◽  
New Methods ◽  
Information Research ◽  
Data Source ◽  
Link Data ◽  
Better Than

Link data source lack has seriously hampered the research development of competitive information for enterprises based on co-link analysis in recent years, and exploring application and innovation of the new method of URL co-occurrence analysis in enterprises competitive information research is very important to make up for current inadequacy. And exploration on problems such as whether Jaccard handling needs to be conducted on collected data and how the effect is to conduct information research in different methods for data in different handling ways is meaningful to theoretical perfection of competitive information research of enterprises. Non-Jaccard data and Jaccard data are compared with examples of Chinese representative banks based on new methods of URL co-occurrence analysis, and competitive information research of enterprises is conducted in the multidimensional scaling method and social network analysis method; and comprehensive exploration and analysis are conducted from multiperspectives such as gradient grading analysis, recognition of main competitors, and competitive landscape analysis of fine grit. Innovative research competitive information for enterprises based on URL co-occurrence analysis in this thesis effectively makes up for current inadequacy due to link data source lack, and it expands new spaces for competitive information research of enterprises; it is also in research in this thesis that analysis result based on non-Jaccard data is far better than analysis result based on Jaccard data when multidimensional scaling analysis is conducted; analysis result based on non-Jaccard data and analysis result based on Jaccard data uncover competitive information of related enterprises when social network analysis is conducted, and above conclusions in this thesis are all verified and analyzed through example data.

scholarly journals “CLIQUES”: ACADEMIC RELATIONSHIPS AMONG HIGHER EDUCATION STUDENTS

2021 ◽  
Vol 15 (1) ◽  
pp. 72-89
Author(s):  
Geraldo Magela Rodrigues de Vasconcelos ◽  
Ester Sarah Liandro ◽  
Velcimiro Inácio Maia ◽  
Gustavo Melo Silva
Keyword(s):  
Higher Education ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Business Administration ◽  
Education Students ◽  
Research Technique ◽  
The Social ◽  
Formation Of Groups ◽  
Better Than

This work has investigated the academic relationships of five classes, 185 students, from an Undergraduate Business Administration course. The Social Network Analysis (SNA) research technique has been used. The results show that homophilia is predominant in the formation of groups. Only in one class does performance have a greater influence. The “cliques” were more clearly defined in only one class. The analysis of the results also indicates that students with social brokerage roles perform better than their peers.

Measuring teamwork and team performance in collaborative work environments

2017 ◽  
Vol 5 (2) ◽  
pp. 196-205 ◽  
Author(s):  
Kylie Goodell King
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Collaborative Work ◽  
Dispersion Models ◽  
Global Marketplace ◽  
Content Type ◽  
New Methods ◽  
And Performance ◽  
Future Evaluation

Purpose Tasks in today’s global marketplace are becoming increasingly reliant on the work of teams. As creativity and innovation are frequently required for organizational success, work teams are becoming more and more prominent within all types of organizations. With the rise of organizational teams, the purpose of this paper is to develop appropriate tools to measure how well these teams work together and how well they perform required tasks. Design/methodology/approach This paper outlines a measure of teamwork, a transactive memory system (TMS), and proposes new methods for using TMSs to measure team structures, processes, and performance. These new methods include dispersion models and social network analysis. Findings Dispersion models and social network analysis hold promise for the future evaluation of TMS and other team constructs. Originality/value This paper provides a summary of two novel approaches to the measurement of TMS and other team constructs.

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