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论文编号：	14122
作者编号：	2320200455
上传时间：	2023/6/12 14:25:00
中文题目：	疫苗制造企业数字化转型过程中的供应链关键数据识别研究——以A企业为例
英文题目：	Research on Key Data Identification of Supply Chain in the Digital Transformation Process of Vaccine Manufacturing Enterprises: A Case Study of Enterprise A
指导老师：	樊振佳
中文关键字：	疫苗供应链；数字化转型；关键数据识别
英文关键字：	Vaccine supply chain; Digital transformation; Key data identification
中文摘要：	近年来，随着疫情在全球的大爆发，国内外多家企业和科研机构便争分夺秒地开始了疫苗的研发工作，疫苗制造企业“疫”外走红，整个疫苗产业的供应链进入了一个新的发展阶段。在数字化转型时代浪潮的驱动下，由于传统供应链无法满足现有业务发展的要求，大部分疫苗生产企业其实已经发现数字化转型势在必行。但是由于缺乏在数字化转型过程中的专业指导，企业仍旧有很多亟待解决的问题，包括具体要从哪个部分开始数字化转型、在数字化转型过程中如何筛选识别出需要重点关注的关键数据等等问题。 本文通过文献资料研究法、专家访谈法和模型分析法，以疫苗制造企业在数字化转型过程中的供应链关键数据识别问题作为本次研究的突破口，通过分析A疫苗制造企业在当前供应链数字化转型过程中面临的问题和原因，系统归纳梳理出A疫苗制造企业供应链在全链条产生的可供提取和进行管理的22类数据管理要素，并结合AHP-DEMATEL 方法和 HOQ方法，运用定性定量的管理理论与工具，转换得出各种数据管理要素的相对重要度，进而筛选识别出对于疫苗企业供应链数字化转型有重要意义的关键数据并给出数据差异化管理建议：1.重点关注相对重要度占到前70%的关键数据要素，最大限度地投入资金、精力以及人力成本进行数字化转型管理，从而使这类数据可以作为企业管理决策的有效支持，提升企业整体管理决策的科学性和适用性；2.在确保对这部分关键数据管理要素进行有效数字化管理的基础上，将剩余的资金和精力主要用于中间20%数据要素的管理；3.如果市面上出现性价比较高的数字化转型数据管理的产品与服务、或者在供应链数字化转型的实施项目工期紧张时，可以暂时延后对相对重要度占最后10%的数据管理要素的管理。 本研究一方面构建了疫苗制造企业供应链在数字化转型过程中的关键数据识别框架，填补了相关领域的研究空白，同时也帮助疫苗制造企业对供应链数字化转型进行科学决策和方案制定，进而实现数据驱动的智能决策，有利于提升疫苗制造企业在供应链数字化转型方面的管理效率，帮助企业利用有限的资源获取更大的收益。
英文摘要：	In recent years, with the global outbreak of the epidemic, many companies and research institutions at home and abroad have been scrambling to start the research and development of new vaccines. Vaccine manufacturing enterprises become popular outside the epidemic, and the supply chain of the entire vaccine industry has entered a new stage of development. Driven by the wave of the digital transformation era, most vaccine manufacturers have actually found that digital transformation is imperative, as the traditional supply chain cannot meet the requirements of existing business development. However, due to the lack of professional guidance in the digital transformation process, companies still have many pressing issues to be solved, including the specific part of the digital transformation to start from, how to filter and identify the key data to focus on in the digital transformation process, and other issues. This paper uses literature research, expert interviews, and model analysis methods to identify key data in the supply chain of vaccine manufacturing enterprises during the digital transformation process as the breakthrough point for this study. By analyzing the difficulties and reasons faced by vaccine manufacturing enterprises in the current supply chain digital transformation process, Systematically summarize and sort out 22 types of data management elements that can be extracted and managed throughout the supply chain of A vaccine manufacturing enterprise, and combine AHP-DEMATEL method and HOQ method to convert the relative importance of various data management elements using qualitative and quantitative management theories and tools, Then screen and identify the key data that are important for the digital transformation of the enterprise supply chain and provide data management suggestions: 1. Focus on the key data elements that account for the top 70% of the relative importance, and maximize the investment of funds, energy, and labor costs for digital transformation management, so that such data can be used as effective support for enterprise management decisions, improving the scientificity and applicability of overall enterprise management decisions; 2. On the basis of ensuring effective digital management of these data management elements, the remaining funds and energy are mainly used for the management of the intermediate 20% data elements; If there are cost-effective digital transformation data management products and services, or when the implementation project for supply chain digital transformation is under tight schedule, the management of data management elements that account for the last 10% of the relative importance can be temporarily postponed. On the one hand, this study has constructed a framework for identifying key data in the supply chain of vaccine manufacturing enterprises during the digital transformation process, filling the research gaps in relevant fields. At the same time, it has also helped vaccine manufacturing enterprises make scientific decisions and plan formulation for the digital transformation of the supply chain, thereby realizing data-driven intelligent decision-making, which is conducive to improving the management efficiency of vaccine manufacturing enterprises in the digital transformation of the supply chain, helping enterprises utilize limited resources to achieve greater benefits.
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