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论文编号：	15594
作者编号：	2320233763
上传时间：	2025/12/7 9:51:10
中文题目：	M公司面向初创AI硬科技企业的估值体系研究
英文题目：	Research on the Valuation System for Start-up AI Hard-tech Company in M Co., Ltd.
指导老师：	薛红志副教授
中文关键字：	初创企业；AI硬科技；估值体系；风险投资
英文关键字：	Startup Company; AI Hard Technology; Valuation System; Venture Capital
中文摘要：	随着以人工智能（AI）技术为核心的新一轮科技革命和产业变革的迅猛发展，创业投资（Venture Capital，VC）机构都纷纷瞄上了蕴含巨大社会财富、可以推动经济社会高质量发展的硬科技赛道。但与一般企业不同的是，处于初创期的AI硬科技企业往往具有高研发壁垒、大规模资金预算、投资回报周期长、不可预测商业模式、可比财务数据稀缺的特殊性特征，使得传统的估值模型或手段方法，如现金流折现估值法、市盈率法等，在应用于初创AI硬科技企业时变得束手无策。鉴于此，聚焦国内投资机构M公司面临的估值管理痛点，从理清理论线索（概述估值相关理论）、分析现状及存在问题、完善初创AI硬科技企业估值这三个方面对问题展开阐述，并力求为M公司提供一整套科学性、系统性、全方位的估值体系，帮助投资机构有效地掌握、评判、识别、评估并实现这些新投资机会的价值。 本文首先回顾了初创企业估值的相关理论与文献，明确了AI硬科技企业的估值特点；其次分析了M公司当前估值实践中存在的问题，包括技术资产评估不足、生命周期匹配度低等；在此基础上，构建了包含技术资产维度、生命周期维度和管理适配维度的“三维动态估值体系”，并设计了相应的评估流程和指标权重；最后通过案例应用验证了该体系的实际效用，结果表明新体系能有效提升投资决策效率、改善投资组合质量。本研究为风险投资机构对初创AI硬科技企业的估值提供了可操作的管理工具，具有较强的实践价值。 本研究的创新之处在于，跳出了传统估值所关注“模型”的局限，从企业管理的更高维度构建了一套适用于初创企业的综合性价值评估“体系”，强调流程、标准、工具与组织管理的有机结合。研究成果不仅对M公司的投资管理实践具有直接的指导意义，也为整个创业投资行业科学评估初创AI硬科技企业的价值提供了有益的参考与借鉴。
英文摘要：	With the rapid development of the new round of technological revolution and industrial transformation centered on artificial intelligence (AI) technology, venture capitalists (VC) have all focused on the tracks that contain huge social wealth and can promote the high-quality development of the economy and society. However, unlike ordinary companies, AI hard technology companies in the initial stage often have special characteristics such as high R&D barriers, large-scale capital budget, long investment return cycle, unpredictable business model, and scarce comparable financial data, making traditional valuation models or methods, such as discounted cash flow valuation method and price-to-earnings ratio method, ineffective when applied to the AI hard technology field. This poses a huge challenge to the valuation of early-stage AI hard technology startups. In view of this, focusing on domestic investment institutions M, the work difficulties and pain points faced by M in this regard are elaborated. The problem is discussed from three parts: clarifying theoretical clues (summarizing valuation-related theories), analyzing current characteristics (analyzing current conditions), and constructing a valuation system for AI startup hard technology companies. The aim is to provide a set of scientific, systematic, and comprehensive methodological system for companies to effectively master, evaluate, identify, assess, and realize the value of these new investments. This thesis first reviews the relevant literature on the value of start-ups and describes the characteristics of AI hard technology companies at the start-up stage. Then, it analyzes and summarizes the reasons why the value of start-ups cannot be reasonably evaluated by M's existing system, which are the lightness of technological assets and the matching of the cycle. Thus, a "three-dimensional dynamic system" consisting of "the dimension of entrepreneurial companies, the dimension of technology and life cycle, and the dimension of management applicability" is proposed, along with the corresponding method process and weight design method. Finally, examples are given to illustrate that the new system can more effectively improve investment efficiency and promote investment returns. Therefore, this new system provides decision-making suggestions for risk investors on the effective evaluation and assessment of the value of start-up companies. This research can help VC management institutions conduct management-oriented evaluation and valuation activities for the value of hard technology start-ups at their current development stage. Thus, it has important practical and reference guiding significance. From the perspective of M, the research results can also further supplement and improve its management system practice achievements, and from an industry perspective, it can be a beneficial reference and inspiration for scientifically valuing start-up technology companies in the initial stage.
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