Measuring Bank Performance: From Static Black Box to Dynamic Network Models

Fukuyama, Hirofumi; Weber, William

doi:10.1007/978-1-4899-7705-2_10

Cited by 1 publication

(1 citation statement)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some scholars tried to study the black boxes that open bank efficiency evaluations. For example, some scholars use CAMELS to establish input indicators [22,23]; after Tone (2009) proposed network DEA [24], some scholars tried to evaluate the internal complex system of a bank with that method [25,26]. However, the CAMELS indicators still cannot solve the problem of whether input and output have a production relationship and how many indicators are appropriate.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Bank Innovation Efficiency with Data Envelopment Analysis: From the Perspective of Uncovering the Black Box between Input and Output

Zhong

Wang

2021

Mathematics

View full text Add to dashboard Cite

The evaluation of corporation operation efficiency (especially innovation efficiency) has been always a hot topic. The currently popular evaluation methods are data envelopment analysis (DEA) and its improved methods. However, these methods have the following problems: the production process is regarded as a black box, and the actual production relationship between input and output is not analyzed. To solve these problems: (1) the black box theory and production function theory are introduced to uncover the black box of input and output; (2) regression models are used to alleviate the multicollinearity problem of inputs, and the most appropriate model of production relationship is selected; and (3) the results of the production function are compared with the results of the efficiency evaluation from multiple perspectives. Taking rural commercial banks in China as examples to evaluate their innovation efficiency, this article shows the following: (1) with the black box theory and production function theory, the staff, equipment, and intermediate business cost are suitable as innovation input variables, and intermediate business income is suitable as an innovation output variable; (2) the main challenges faced by rural commercial banks are reducing the reliance on human capital investment, strengthening technological innovation, and improving the efficiency of intermediate business cost management, which is hard to reveal with traditional DEA. The method proposed in this article provides an applicable reference for improving DEA method analysis.

show abstract