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论文编号：	15737
作者编号：	2320224013
上传时间：	2025/12/9 17:29:54
中文题目：	L公司矿区无人驾驶业务的商业模式 优化研究
英文题目：	The business model of L Company''s unmanned mining operation optimization research
指导老师：	李颖
中文关键字：	无人驾驶；商业画布；层次分析法；模糊综合评价；商业模式创新
英文关键字：	autonomous driving；business canvas；Analytic Hierarchy Process；fuzzy comprehensive evaluation；business model innovation
中文摘要：	当前社会科技飞速发展，无人驾驶技术的发展是科技进步的重要一环，目前无人驾驶技术已发展到商业化落地的关键时期，如何保持一个公司商业模式的有效性，已经可以决定公司是否能够在激烈的市场中具备竞争力。本研究将以L公司为案例，综合运用商业画布、AHP层次分析法和模糊综合评价法等理论工具，对L公司的商业模式进行评价，并针对其核心矛盾对L公司的商业模式进行优化。 本研究从整体矿区无人驾驶行业出发，通过PESTEL、波特五力模型对L公司的外部环境进行分析，通过VRIO框架等理论对L公司内部环境进行分析，由此识别L公司的核心资源能力。在内外环境的分析基础上，研究开始构建商业模式评价体系，评价体系包含5个一级指标和15个二级指标；之后笔者通过专家问卷调查确定各指标权重及通过大众问卷调查进行L公司商业模式打分。经过收集结果并分析可得，L公司商业模式综合得分为3.642分（满分5分），其中“价值主张有效性”和“核心资源与流程支撑度”指标得分较高，但“盈利与成本控制能力”指标得分较低。 针对问卷分析结果，研究开始对L公司商业模式进行优化，确定了从技术供应商向运营服务商的战略转型方案，为提高盈利模式，设计初装费+运营服务费+数据增值服务费的混合盈利模式，并论述了通过合资运营优化客户关系、通过产品化、标准化优化成本结构等方案。最后通过新旧商业模式的对比，清晰展现了优化后商业模式的优点及改良所在。 本研究不仅为L公司提供了具体的商业模式优化方案，也为同类技术驱动型企业的商业模式优化提供了理论分析框架和实践参考，对推动无人驾驶行业的商业化进程具有重要的理论与实践意义。 关键词：无人驾驶；商业画布；层次分析法；模糊综合评价；商业模式创新
英文摘要：	With the rapid development of social technology, autonomous driving is an important part. Currently, autonomous driving technology has reached a critical period of commercialization. How to maintain the effectiveness of a company's business model can determine whether the company can be competitive in the fierce market. This study will take L company as a case, comprehensively use business canvas, AHP analytic hierarchy process and fuzzy comprehensive evaluation method and other theoretical tools to evaluate the business model of L company, and optimize the business model of L company based on its core contradictions. This study starts from the overall mining area unmanned driving industry, analyzes the external environment of L company through PESTEL and Porter's Five Forces model, and analyzes the internal environment of L company through VRIO framework and other theories, thereby identifying the core resource capabilities of L company. Based on the analysis of internal and external environments, the study begins to construct a business model evaluation system, which includes 5 primary indicators and 15 secondary indicators. Then, the author determines the weight of each indicator through expert questionnaire survey and scores the business model of L company through public questionnaire survey. After collecting and analyzing the results, it can be concluded that the comprehensive score of L company's business model is 3.642 points (out of 5 points), with higher scores for "value proposition effectiveness" and "core resource and process support degree" indicators, but lower scores for "profit and cost control ability" indicator. Based on the results of the questionnaire analysis, the research began to optimize the business model of L Company. It identified a strategic transformation plan from a technology supplier to an operational service provider. To improve the profit model, a hybrid profit model consisting of initial installation fees, operational service fees, and data value-added service fees was designed. The research also discussed plans to optimize customer relationships through joint venture operations and optimize cost structures through productization and standardization. Finally, by comparing the old and new business models, the advantages and improvements of the optimized business model were clearly demonstrated. This study not only provides a specific business model optimization plan for L company, but also provides a theoretical analysis framework and practical reference for the business model optimization of similar technology-driven enterprises. It has important theoretical and practical significance for promoting the commercialization process of the autonomous driving industry. Key words: autonomous driving；business canvas；Analytic Hierarchy Process；fuzzy comprehensive evaluation；business model innovation
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