Analysis of Economic Efficiency and Influencing Factors of Commercial Banks based on Information Mining
DOI:
https://doi.org/10.54691/bcpbm.v17i.410Keywords:
Information Mining; Commercial Banks; Economic Efficiency; Influencing Factors.Abstract
In the field of commercial banks with a huge amount of data, in order to achieve long-term development, we must attach great importance to the application of professional data processing technology. With the gradual opening of the financial market, foreign banks, especially international multinational banks with strong comprehensive strength, have entered the Chinese financial market one after another, which will undoubtedly bring great impact and challenges to Chinese commercial banks. Information mining, as a professional data processing technology, has been widely used in the field of huge data in recent years. The application of information mining in commercial banks can effectively improve the data processing ability and competitiveness of commercial banks. Strengthening the application of information mining is the inevitable choice for commercial banks to develop in the future. Based on information mining, this paper analyzes the economic efficiency and influencing factors of commercial banks. The efficiency of commercial banks is a core part of national commercial banks' pursuit of progress and competition in the global economy. This paper analyzes and studies the efficiency and influencing factors of national commercial banks.
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References
Pan X, Zhang J, Li C, et al. Analysis of China's regional wind power generation efficiency and its influencing factors [J]. Energy & Environment, 2019, 30(2):254-271.
Alalwan A A, Dwivedi Y K, Rana N P. Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust [J]. International Journal of Information Management, 2017, 37(3):99-110.
Jaabi S, Fatty A. Measuring Efficiency of Commercial Banks in The Gambia[J]. The Social Science Journal, 2018, 5(11):631-651.
Sh A, Msd B, Rs B. Assessing energy efficiency of Indian paper industry and influencing factors: A slack-based firm-level analysis[J]. Energy Economics, 2019, 81:454-464.
Gao X, Chen J, Huai N. Mining heterogeneous information networks [J]. Information Processing & Management, 2019, 55(3): 844-857.
Lee H, Choi K, Yoo D, et al. Recommending valuable ideas in an open innovation community A text mining approach to information overload problem[J]. Industrial management & data systems, 2018, 118 (4): 683-699.
Mirtsch M, J Kinne, Blind K. Exploring the Adoption of the International Information Security Management System Standard ISO/IEC 27001: A Web Mining-Based Analysis[J]. IEEE Transactions on Engineering Management, 2020, PP (99):1-14.
Martin N, Fischer D A, Kerpedzhiev G D, et al. Opportunities and Challenges for Process Mining in Organizations: Results of a Delphi Study[J]. Business & Information Systems Engineering, 2021, 63 (10): 1-17.






