Empirical results.

Based on 2010–2019 Chinese logistics listed companies as research samples, the paper used the binary Logit model measuring degree of financing constraints. The Kernel density function and Markov chain model are used to forecast China listed companies financing logistics dynamic constraints and business performance growth. Furthermore the stock of knowledge was chosen as a threshold variable to explore the impact of financing constraints on corporate performance growth of listed logistics enterprises. We find that the degree of financing constraints of logistics enterprises in our country has not been significantly eased. Corporate performance has not changed significantly and there are no obvious spatial gap and polarization with the passage of time. The impact of financing constraints on the corporate performance growth of logistics enterprises in China has a double threshold effect of knowledge stock, and has an inhibitory effect that first increases and then decreases. This is because in the short term, the investment of knowledge stock by enterprises can crowd out more corporate liquidity, and in the long run, it is related to the conversion rate of the knowledge stock itself. Because of the uneven regional distribution of resources and differences in the degree of economic development, there is a growing disincentive effect in central China as the stock of knowledge accumulates.

本研究以2010—2019年中国物流行业上市公司为研究样本，采用二元Logit模型测度企业融资约束程度；借助核密度函数与马尔可夫链模型，对中国物流行业上市公司的融资约束动态特征与企业绩效增长开展预测分析，并选取知识存量作为门槛变量，探究融资约束对物流行业上市公司绩效增长的影响效应。研究结果表明，我国物流企业的融资约束程度未得到显著缓解，企业绩效整体无明显变动，随时间推移亦未显现显著空间差距与极化现象。我国物流企业融资约束对绩效增长的影响存在基于知识存量的双重门槛效应，且呈现先增强后减弱的抑制作用。究其根源，短期内企业对知识存量的投入会挤占更多企业流动性；长期来看则与知识存量自身的转化效率密切相关。受资源区域分布不均与经济发展水平差异影响，随着知识存量积累，华中地区的抑制效应呈现逐步增强的态势。