Title: Drivers of green finance development: a nonlinear fsQCA-ANN analysis

Authors: Quanling Cai; Weidong Chen; Mingxing Wang; Kaisheng Di

Addresses: Department of Management and Economics, Tianjin University, Tianjin, China; College of Politics and Public Administration, Qinghai Minzu University, Xining, Qinghai Province, China ' Department of Management and Economics, Tianjin University, Tianjin, China ' College of Finance and Economics, Qinghai University, Xining, Qinghai Province, China ' Department of Management and Economics, Tianjin University, Tianjin, China; College of Politics and Public Administration, Qinghai Minzu University, Xining, Qinghai Province, China; Department of Party Committee, Party School of the Qinghai Provincial Committee of CPC, Xining, Qinghai Province, China

Abstract: Based on the TOE framework and analysing 31 Chinese provinces, this study uses fsQCA and ANN to explore key drivers of green finance. Findings indicate that green finance policies, environmental investments, financial regulation, and the digital economy significantly foster green finance development with varied pathways across regions. Public environmental awareness, technological innovation, and digital inclusive finance are also crucial. The study reveals a nonlinear development model for green finance, shaped by complex factor interactions, offering theoretical support for policymakers to design effective green finance strategies in complex economic contexts to achieve sustainable development goals.

Keywords: green finance; nonlinear analysis; fuzzy-set qualitative comparative analysis; fsQCA; artificial neural networks; ANN.

DOI: 10.1504/IJGW.2025.145679

International Journal of Global Warming, 2025 Vol.36 No.1, pp.86 - 105

Received: 02 Oct 2024
Accepted: 30 Oct 2024
Published online: 14 Apr 2025 *

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