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论文编号：	16084
作者编号：	2120243840
上传时间：	2026/6/5 18:06:41
中文题目：	企业数智化对投融资期限错配的影响研究
英文题目：	Research on the Impact of Enterprise Digital and Intelligent Transformation on Maturity Mismatch
指导老师：	黄福广教授
中文关键字：	数智化转型；投融资期限错配；信息透明度；管理者过度自信；企业价值
英文关键字：	Digital and Intelligent Transformation; Investment and Financing Maturity Mismatch; Information Transparency; Managerial Overconfidence; Enterprise Value
中文摘要：	随着数字经济的快速发展，数字技术与人工智能的融合应用正在改变企业的经营模式。当前，我国数字经济核心产业增加值超过14万亿元，占GDP的比重为10.5%，市场主体超450万家，说明数智化转型已经成为企业顺应数字经济发展的必然选择。与此同时，我国金融市场体系仍有待完善，企业长期投资需求与长期资金供给不足的失衡问题突出，从而导致“短贷长投”引发的投融资期限错配问题。这种期限错配不仅会增加企业的流动性风险，甚至会造成资金链断裂进而引发财务困境，更可能通过供应链、信贷网络等途径传导至宏观层面，进一步损害金融系统的稳定性。而数智化转型为企业缓解投融资期限错配提供了新的路径，其相关作用机制与实践效果具有重要的研究价值。 基于此，本文以2007—2024年上市公司为研究样本，探究企业数智化转型对投融资期限错配的影响效应、作用机制及经济后果。实证研究发现，数智化转型能显著缓解企业投融资期限错配问题，经替换核心变量、制造业子样本回归开展稳健性检验，再采用滞后变量、工具变量、倾向得分匹配法处理内生性后，结论依旧成立。进一步开展机制分析，发现数智化转型可以通过提高信息透明度、降低管理者过度自信缓解企业期限错配，两条路径均发挥部分中介效应，同时商业信用水平在二者关系中存在正向调节效应，即商业信用水平越高，数智化转型对期限错配的缓解作用越明显。经济后果检验结果显示，数智化转型通过缓解投融资期限错配，能够有效提升企业价值。最后进行异质性分析，发现数智化转型对期限错配的缓解作用在国有企业、高新技术企业以及东中部地区企业中更为突出，而在非国有企业、非高新技术企业和西部地区企业中效果较弱或不显著。 本文的研究为企业通过数智化转型优化融资结构、缓解期限错配提供实践参考，也为政府制定差异化支持政策、推进数字基础设施建设、防范系统性金融风险提供理论支撑。
英文摘要：	Against the backdrop of the booming digital economy, the integrated application of digital technologies and artificial intelligence is reshaping the operational models of enterprises in China. Currently, the added value of the core industries of China’s digital economy has hit 14 trillion yuan, accounting for 10.5% of the national GDP, with the number of market entities exceeding 4.5 million. Thus, digital and intelligent transformation has become an inevitable choice for enterprises to embed themselves in the development landscape of the digital economy. Nevertheless, China is confronted with a complex and volatile economic environment and an underdeveloped financial market, where the striking contradiction between the inadequate supply of long-term funds and enterprises’ growing demand for long-term investment has given rise to the prevalent phenomenon of investment and financing maturity mismatch caused by "financing long-term projects with short-term loans". Such a mismatch not only aggravates enterprises’ liquidity risks, which may trigger capital chain breaks and subsequent financial distress, but also could transmit to the macroeconomic level through supply chains, credit networks and other channels, thereby jeopardizing the stability of the entire financial system. In this context, digital and intelligent transformation offers a novel pathway for enterprises to mitigate maturity mismatch, and the exploration of its underlying mechanisms and practical effects is of great academic and practical value. Based on the above analysis, this paper takes Chinese listed companies from 2007 to 2024 as the research sample to empirically examine the impact, transmission mechanisms and economic consequences of enterprises’ digital and intelligent transformation on investment and financing maturity mismatch. The empirical results show that digital and intelligent transformation can significantly alleviate the investment and financing maturity mismatch of enterprises. This conclusion remains robust after robustness tests including core variable replacement and separate regression on manufacturing sub-samples, as well as endogenous tests using lagged variables, constructing instrumental variables based on the relative differences in digital and intelligent development levels, and the Propensity Score Matching (PSM) method. Further mechanism analysis reveals that digital and intelligent transformation can curb enterprises’ maturity mismatch by improving information transparency and reducing managerial overconfidence, with both paths exerting a partial mediating effect. Meanwhile, the level of trade credit plays a positive moderating role in the relationship between digital and intelligent transformation and maturity mismatch, that is, a higher level of trade credit can strengthen the mitigating effect of digital and intelligent transformation on maturity mismatch. The test of economic consequences indicates that digital and intelligent transformation can effectively boost enterprise value by inhibiting investment and financing maturity mismatch. Finally, heterogeneity analysis shows that the mitigating effect of digital and intelligent transformation on maturity mismatch is more pronounced in state-owned enterprises, high-tech enterprises and enterprises in the eastern and central regions of China, while the effect is weak or insignificant in non-state-owned enterprises, non-high-tech enterprises and enterprises in the western region. This study enriches the relevant literature on the economic consequences of digital and intelligent transformation and the influencing factors of enterprises’ investment and financing maturity mismatch. It provides practical guidance for enterprises to optimize their financing structures and alleviate maturity mismatch through digital and intelligent transformation, and also offers theoretical references for the government to formulate differentiated support policies, improve digital and intelligent infrastructure construction, and guard against systemic financial risks.
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