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Efficiency Measurement and Influencing Factors Analysis of Urban Commercial Banks: An Empirical Study Based on SBM-DDF and Tobit Model
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Xiaotian XU
Science Technology and Industry | 2025, 25(12) : 152 - 157
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Science Technology and Industry | 2025, 25(12): 152-157
Industrial Development
Efficiency Measurement and Influencing Factors Analysis of Urban Commercial Banks: An Empirical Study Based on SBM-DDF and Tobit Model
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Xiaotian XU
Affiliations
  • Southwest University of Science and Technology, Mianyang 621000, Sichuan, China
Published: 2025-06-25
Outline
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Through the study of the panel data of 17 listed city commercial banks in the five years from 2017 to 2022, the DEA-SBM-DDF model was used to measure their efficiency. The results show that the operational efficiency of urban commercial banks is generally high, but it shows a downward trend, and there are great differences in the management level among banks, and the operational efficiency of Bank of Beijing is the highest. Finally, the Tobit model was used to analyze the influencing factors affecting the operational efficiency of urban commercial banks, and the results show that the scale of Internet payment, asset scale and non-interest income non-performing loan ratio have a significant impact on the operational efficiency of urban commercial banks. The analysis results also have a certain reference role for other commercial banks’ goal setting, performance evaluation and job candidates’ selection of target commercial banks.

efficiency  /  DEA-SBM-DDF method  /  Tobit model  /  city commercial bank
Xiaotian XU. Efficiency Measurement and Influencing Factors Analysis of Urban Commercial Banks: An Empirical Study Based on SBM-DDF and Tobit Model[J]. Science Technology and Industry, 2025 , 25 (12) : 152 -157 .
Year 2025 volume 25 Issue 12
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Article Info
  • Receive Date:2025-01-02
  • Online Date:2025-12-17
  • Published:2025-06-25
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  • Received:2025-01-02
Affiliations
    Southwest University of Science and Technology, Mianyang 621000, Sichuan, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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