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论文编号：	14925
作者编号：	2320213744
上传时间：	2024/12/6 15:50:03
中文题目：	基于DEA方法的中国上市钢铁企业生产效率评价研究
英文题目：	Research on the Evaluation of Production Efficiency of Listed Steel Enterprises in China Based on DEA Method
指导老师：	车建国
中文关键字：	钢铁企业；数据包络分析；生产效率评价
英文关键字：	Iron and Steel Enterprises；Data Envelopment Analysis；Production efficiency evaluation
中文摘要：	钢铁行业作为国家发展中至关重要的基础产业之一，在国家经济发展和国防安全建设中扮演着极为重要的角色。它在现代工业化进程中承担着其他行业所不能替代的任务，具有极其重要的地位和不可替代的作用。我国的钢铁行业规模庞大，其总营业收入已经超过了3万亿人民币，占据我国GDP超2%。尽管规模庞大，整个行业的利润率却逐年下滑，这说明在市场萎缩的背景下，我国钢铁行业发展面临巨大的挑战。 为了深入理解我国钢铁行业当前所面临的一系列挑战，并在此基础上提出切实可行的解决方案和建议，本文选取了24家具有典型代表性的钢铁上市企业作为研究对象。本文通过对这些企业的财务报表数据进行详细搜集和整理，利用数据包络分析（DEA）方法，构建了一个专门针对上市钢铁企业的BCC分析模型。通过运用该模型对所选样本钢铁企业进行深入研究和分析，本文计算出了这些企业在综合技术效率、纯技术效率以及规模效率三个方面的具体数值。通过对这三个效率指标的综合分析，本文进一步进行了横向企业间的对比和纵向时间序列的对比，以揭示当前样本钢铁企业在运营过程中所存在的各种问题。 通过上述分析，本文总结出钢铁行业目前面临的主要问题。在投入端涉及固定资产投资的冗余、员工数量的过剩和三项费用的过度支出；在产出端涉及盈利能力的不足。在结合行业实际情况后，对上述问题进行了全面的分析，针对这些问题提出了相应的改进措施和建议。这些措施和建议从提升效率的角度出发，旨在提高钢铁行业的综合技术效率。通过提升企业自身的生产技术和管理能力，解决企业投入端冗余的问题，加强行业内的合作与交流，提高基础产品毛利率，提升整个行业的竞争力和盈利能力。通过在这些改进和优化，本文希望能够为钢铁行业面临的各种问题提供一个有效的解决方案，进而推动整个行业的持续健康发展。最后，文章也指出了研究过程中存在的诸多不足，例如对企业实际情况结合不够紧密，样本数据量有限，代表性不强等，这些原因可能会导致本文结论不够精确。未来将会通过引入更多非财务数据、引入绿色发展等因素对模型进行进一步改良，希望能够为钢铁行业的持续发展提供更多的理论支持和实践指导。
英文摘要：	As one of the most crucial basic industries in national development, the steel industry plays an extremely important role in the country's economic growth and national defense security construction. It undertakes tasks in the modern industrialization process that cannot be replaced by other industries, holding an extremely important status and irreplaceable role. China's steel industry is vast, with total operating revenues exceeding 3 trillion yuan, accounting for more than 2% of China's GDP. Despite its size, the industry's profit margins have been declining year by year, indicating that the development of China's steel industry faces significant challenges in the context of a shrinking market. In order to deeply understand the series of challenges currently faced by China's steel industry and to propose practical solutions and suggestions based on this, this thesis selects 24 representative listed steel companies as research subjects. By collecting and organizing detailed financial statement data from these companies, this thesis utilizes the Data Envelopment Analysis (DEA) method to construct a BCC analysis model specifically for listed steel enterprises. By applying this model to conduct in-depth research and analysis on the selected sample steel companies, this thesis calculates the specific values for these companies in three aspects: overall technical efficiency, pure technical efficiency, and scale efficiency. Through a comprehensive analysis of these three efficiency indicators, this thesis further conducts comparisons between enterprises horizontally and time series comparisons vertically to reveal the various problems existing in the operation of the current sample steel companies. Through the above analysis, this thesis summarizes the main problems currently faced by the steel industry. On the input side, it involves redundant fixed asset investment, excess employee numbers, and excessive expenditure on three major expenses; on the output side, it involves insufficient profitability. After considering the actual situation of the industry, a comprehensive analysis of the aforementioned issues was conducted, and corresponding improvement measures and suggestions were proposed for these problems. These measures and suggestions aim to improve the overall technical efficiency of the steel industry from the perspective of enhancing efficiency. By improving the production technology and management capabilities of enterprises, solving the problem of redundancy at the input end, strengthening cooperation and communication within the industry, increasing the gross profit margin of basic products, and enhancing the competitiveness and profitability of the entire industry. Through these improvements and optimizations, this thesis hopes to provide an effective solution to the various problems faced by the steel industry, thereby promoting the sustained and healthy development of the entire industry. Finally, this thesis also points out many shortcomings in the research process, such as insufficient integration with the actual situation of enterprises, limited sample data volume, and weak representativeness, which may lead to imprecise conclusions in this thesis. In the future, the model will be further improved by introducing more non-financial data and factors such as green development, hoping to provide more theoretical support and practical guidance for the sustainable development of the steel industry.
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