Title: Impact of digital finance development based on k-means clustering algorithm on alleviating financing constraints of IoT technology companies

Authors: Jiale Yang; Xinwei Li; Xiang Li; Chunyan He; Shuting Zhou; Jie Mei

Addresses: International School, Guangxi University, Nanning, Guangxi, China ' International School, Guangxi University, Nanning, Guangxi, China ' International School, Guangxi University, Nanning, Guangxi, China ' International School, Guangxi University, Nanning, Guangxi, China ' Southwestern University of Finance and Economics, Chengdu, Sichuan, China ' International School, Guangxi University, Nanning, Guangxi, China

Abstract: This study is developed to analyse the effect of alleviating the financing constraints of internet of things technology innovation enterprises under the development of digital finance based on the k-means clustering algorithm. Using the k-means clustering algorithm, the risk level of 'financing of IoT innovation enterprises' is classified. The Bayesian network is created according to the results of the k-means clustering algorithm. Then, the accuracy is predicted and the implementation of digital financial development effectively alleviates the financing constraints of technology innovative enterprises. In addition, the effect on digital financial development is more obvious when the enterprises are nonstate-owned technological innovation enterprises. For enterprises with lower quality of internal control, the effect is more obvious. And when the degree of market competition is low, the effect is more obvious. The research has certain reference value to further reduce the financing cost of science and technology innovation enterprises.

Keywords: IoT; k-means clustering algorithm; digital finance; financing.

DOI: 10.1504/IJCAT.2023.135586

International Journal of Computer Applications in Technology, 2023 Vol.73 No.3, pp.217 - 230

Received: 12 Apr 2023
Accepted: 22 Sep 2023
Published online: 18 Dec 2023 *

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