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论文编号：	14841
作者编号：	2320224293
上传时间：	2024/12/3 20:51:13
中文题目：	社会责任投入下纺织服饰企业绩效评价研究
英文题目：	Research on Performance Evaluation of Textile and Apparel Enterprises under Corporate Social Responsibility(CSR)
指导老师：	车建国
中文关键字：	社会责任；BP神经网络；绩效评价
英文关键字：	Corporate Social Responsibility;BP Neural Network;Performance Evaluation
中文摘要：	随着我国纺织服装业从规模速度型向质量效益型的转变，以及“中国制造2025”战略的推进，行业在技术创新、产业升级、绿色发展等方面取得了显著成效，但企业社会责任的履行仍显不足。国内消费市场对产品的环保性、安全性和可持续性要求提高，促使企业加强供应链管理，确保各环节符合社会责任要求。同时，国际市场上环保标准和社会责任标准的提高，也要求中国纺织服饰企业积极适应并提升综合绩效。 国内学术界则随着经济社会问题的日益凸显，开始关注企业社会责任问题，并尝试构建适用于中国企业的社会责任绩效评价体系。有效的绩效评价是纺织服装企业可持续绿色健康发展的必要手段，也是管理者决策的重要依据。然而，传统的绩效评价方法已难以适应当前企业管理环境的变化，需要建立新的指标体系和评价方法，以全面评估企业在社会责任投入下的绩效表现。 基于利益相关者理论，结合我国纺织服装企业的实际情况，尝试构建一套科学、全面、可行的社会责任绩效评价指标体系和评价方法。通过定量分析与定性分析相结合的方法，确定了AHP-熵权综合确定绩效指标权重的方法，并创建了BP神经网络社会责任绩效评价模型，其次以国内纺织服饰上市公司企业为例，对其 2021 年至 2023年的绩效进行了评价分析,并对如何提升其绩效水平从利益相关者角度提出若干措施。旨在为纺织服装企业提供有效的量化工具和理论参考，推动企业更好地履行社会责任，实现经济效益与社会效益的双赢。 研究结论表明，构建适用于纺织服装企业的社会责任绩效评价体系，对于促进企业可持续发展、提升行业竞争力具有重要意义。未来，随着国内外环境的不断变化，社会责任绩效评价体系的不断完善和优化将成为纺织服装行业发展的重要趋势。
英文摘要：	As China's textile and apparel industry transitions from a scale-and-speed-driven model to a quality-and-efficiency-oriented one, and with the advancement of the "Made in China 2025" strategy, remarkable achievements have been made in technological innovation, industrial upgrading, and green development. However, the fulfillment of corporate social responsibility (CSR) remains inadequate. The domestic consumer market's heightened demands for environmental friendliness, safety, and sustainability in products have compelled enterprises to strengthen supply chain management, ensuring compliance with CSR requirements across all segments. Additionally, the elevation of environmental and social responsibility standards in international markets necessitates Chinese textile and apparel enterprises to actively adapt and enhance their overall performance. As economic and social issues gain increasing prominence in China, domestic academia has shifted its focus towards CSR matters and is endeavoring to establish a tailored CSR performance evaluation system for Chinese enterprises. This thesis argues that effective performance evaluation is a vital tool for the sustainable, green, and healthy development of textile and apparel enterprises, serving as a crucial basis for managerial decision-making. Nevertheless, traditional performance evaluation methods have struggled to adapt to the evolving corporate management environment, necessitating the establishment of new indicator systems and evaluation methodologies to comprehensively assess enterprises' performance under CSR investments. Drawing upon stakeholder theory and integrating the realities of China's textile and apparel enterprises, this thesis endeavors to construct a scientific, comprehensive, and feasible CSR performance evaluation index system and evaluation method. By combining quantitative and qualitative analyses, the thesis determines the AHP-Entropy Weight method for comprehensively determining the weights of performance indicators and creates a BP Neural Network-based CSR performance evaluation model. Subsequently, it evaluates and analyzes the performance of domestic listed textile and apparel companies from 2021 to 2023,And provide several suggestions from the perspective of stakeholders on how to improve its performance level. This study aims to provide textile and apparel enterprises with effective quantitative tools and theoretical references, promoting better CSR fulfillment and achieving a win-win scenario between economic and social benefits. The thesis concludes that establishing a CSR performance evaluation system tailored to textile and apparel enterprises is of great significance for promoting sustainable development and enhancing industry competitiveness. Looking ahead, with the continuous changes in domestic and international environments, the continuous improvement and optimization of the CSR performance evaluation system will emerge as a crucial trend in the development of the textile and apparel industry.
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