Innovation performance evaluation for high-tech companies using a dynamic network data envelopment analysis approach

2020 ◽  
Author(s):  
Anyu Yu ◽  
Yu Shi ◽  
Jianxin You ◽  
Joe Zhu
Keyword(s):  
Performance Evaluation ◽  
Data Envelopment Analysis ◽  
Dynamic Network ◽  
Innovation Performance ◽  
Analysis Approach ◽  
High Tech ◽  
Network Data ◽  
Data Envelopment ◽  
Network Data Envelopment Analysis

scholarly journals The Sustainability Performance of Chinese Banks: A New Network Data Envelopment Analysis Approach and Panel Regression

2019 ◽  
Vol 11 (6) ◽  
pp. 1622 ◽  
Author(s):  
Yantuan Yu ◽  
Jianhuan Huang ◽  
Yanmin Shao
Keyword(s):  
Data Envelopment Analysis ◽  
Scale Effects ◽  
Estimation Method ◽  
Dynamic Network ◽  
Generalized Least Squares ◽  
Foreign Banks ◽  
Network Data ◽  
Significant Heterogeneity ◽  
Data Envelopment ◽  
Network Data Envelopment Analysis

This paper develops a new network data envelopment analysis (DEA) model that simultaneously integrates the non-convex metafrontier and undesirable outputs and which is super efficient at performing dynamic network slacks-based measures. The model is employed to discuss the efficiency of 36 commercial banks in China during the years 2010–2014. The efficiency of these banks shows significant heterogeneity and the efficiency of most foreign banks has much room for improvement. Regarding both the non-convex metafrontier and the group frontier, state-owned banks perform the best, followed by joint-stock banks, with foreign banks performing the worst; the same is true for the technology gap ratios. The empirical results produced by the feasible generalized least squares estimation method indicate that liquidity and scale effects exert positive impacts on bank efficiency. An alternative estimation method confirmed that the conclusions were robust.

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