PurposeThe paper sets out to understand the key issues that the various functions and optimal allocation of NGOs (non-governmental organizations) in the circular economy that provide public services depend not only on external quantities or densities but also on their internal size of human resources.Design/methodology/approachThe paper uses different data samples and models to study the influence mechanism of optimal NGO size of human resources and its differentiated effects on governance quality of entrepreneurship.FindingsThe authors find that a reduction in transaction costs and an increase in the aggregation degree of public demand lead to increased human capital and lower financial capital intensity. In addition, the authors find that NGO size of human resources has a relationship that is approximately U-shaped (or inverse U-shaped) with the governance quality of entrepreneurship.Practical implicationsThe paper discusses the implications for programs that encourage NGOs to optimally determine their internal size of human resources and further improve the governance quality of entrepreneurship in the circular economy.Originality/valueThe paper reveals the significant nonmonotonic relationship between local governance quality and NGO financial size, even after controlling for other NGO, city and provincial characteristics.

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The purposes of this paper are to analyze the financial management and influencing factors of small and medium-sized enterprises (SMEs) and explore the nonlinear relationship in enterprises’ financial market structure. The small and medium-sized enterprises in Eastern and Western China are taken as the research objects. First, the relationships between asset–liability constraints and financial management are discussed, analyzed, and explained. The development of enterprises’ financial management under the asset–liability constraints system is emphasized. Second, a self-adaptive nonlinear dynamic system is proposed based on dynamic surface control and the multi-directional and uncertain control of the financial market structure. Finally, a dynamic nonlinear panel estimation model for enterprises is constructed based on the nonlinear system. The simulation and empirical analysis results confirm that the proposed nonlinear system is useful in dynamic, uncertain control problems. The statistical results of the three primary indicators, economic variables, financial indicators, and control variables, reveal the significant regional differences of different financial market structure indicators. Model estimates based on the three key sub-indicators, the leverage ratio, return on assets, and debt interest rate, reveal the differences in financing and leverage ratio of small and medium-sized enterprises located in the eastern and western regions. SMEs in Eastern China are taken as examples; the direct financing rate and insurance proportion are negatively correlated with the leverage ratio and debt interest rate. In contrast, they are positively correlated with asset returns. In conclusion, there are noticeable differences in the financial market structure between different regions.

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