The Research on the Manufacturing Enterprise Organizational Innovation Path Performance Estimated Based on Pls Path Model
DOI: 10.23977/aetp.2019.31017 | Downloads: 16 | Views: 1841
Wang Peng 1
1 School of Economics and Management, Dalian University, No.10, Xuefu Avenue, Economic & Technical Development Zone, Dalian, Liaoning, China
Corresponding AuthorWang Peng
In order to estimate enterprises organizational innovation path performance levels scientifically and efficiently, this thesis conclude three different organizational innovation path based on enterprise organizational innovation path operation reality character: radical organizational innovation path, mild organizational innovation path, conservative organizational innovation path. Then according to the different organizational innovation path performance set the theatrical model and relate research hypothesis. And based on the above discussion, this thesis constructs enterprise organizational innovation path performance estimated model based on PLS path model, then give concrete estimated and evaluated process, and use the PLS-SEM method to vivificate the theatrical model. The final answer shows: the enterprises organizational innovation path performance estimate model based on PLS path model fit for the single dimension precondition have optimal convergence effect and explain ability, and high level of the fitting, we can also know the radical organizational innovation path performance effect degree is the highest, the mild organizational innovation path performance effect degree is the second, and the conservative organizational innovation path performance effect degree is the lowest.
KEYWORDSPls path model, Sem (structure equation model), Organizational innovation path performance, Organizational innovation performance
CITE THIS PAPER
Wang Peng, The Research on the Manufacturing Enterprise Organizational Innovation Path Performance Estimated Based on Pls Path Model. Advances in Educational Technology and Psychology (2019) 3: 117-120. DOI: http://dx.doi.org/10.23977/aetp.2019.31017.
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