Open AccessThe Organization Model of Big Data Innovation Alliance: A Multi-Case Study from the Perspective of Virtual Clusters
Author(s) -
Tianzhu Li,
Xiaomei Wang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1624/3/032035
Subject(s) - alliance , generality , big data , perspective (graphical) , knowledge management , economies of agglomeration , business , data science , industrial organization , computer science , data mining , management , engineering , artificial intelligence , political science , economics , chemical engineering , law
The Big Data Innovation Alliance can be understood as a cross-industry and cross-region spatial agglomeration phenomenon based on Big Data. From the two aspects of constituent elements and organizational characteristics, the Big Data Innovation Alliance is found to be a learning organization with a flat management structure. A multi-case study method is used to empirically test the virtual cluster characteristics of the big data innovation alliance organization model using four typical cases, and to analyze its generality and specificity based on the research variables. Several policy implications have been obtained for the big data innovation alliance organization model.