这篇研究旨在利用主成分分析和Logistic模型来进行金融上市公司财务预警分析。财务预警分析是评估公司财务健康状况并预测可能的财务困境的重要工具。本研究通过PCA分析来降维,提取出最具代表性的财务指标,然后利用Logistic回归模型来预测公司是否会陷入财务困境。用79家金融业上市公司2021年数据进行检验,得出建模组总体预测准确率为71.67%,检验组总体预测准确率为82%。通过这种方法,研究旨在为金融上市公司提供有效的财务预警机制,帮助企业管理层及时发现潜在的财务风险,同时完善了对目前金融业上市公司财务预警模型的相关研究,帮助投资者、管理者和监管机构更好地评估和管理财务风险。The aim of this study is to conduct financial early warning analysis of financial listed companies using Principal Component Analysis and Logistic Modelling. Financial early warning analysis is an important tool for assessing the financial health of a company and predicting possible financial distress. In this study, PCA analysis is used to reduce the dimensionality and extract the most representative financial indicators, and then Logistic regression model is used to predict whether the company will be in financial distress. Tests using 2021 data from 79 listed companies in the financial sector yielded an overall prediction accuracy of 71.67% for the modelling group and 82% for the test group. Through this method, the study aims to provide listed financial companies with an effective financial early warning mechanism to help corporate management identify potential financial risks in a timely manner, and at the same time, it improves the relevant research on the current financial early warning models of listed companies in the financial industry to help investors, managers, and regulators better assess and manage financial risks.
好特卖是一家主打“超低折扣”的品牌零售集合连锁店,开辟了零售折扣店的全新赛道。本研究实施了产学研相结合的研究路径,充分发挥了学术界、产业界与实际市场之间的互动作用。通过开展市场调研,积累丰富的数据资料,旨在研究好特卖学生消费意愿及推广模式,全面分析影响学生购买意愿的各种因素,并在此基础上提出具有针对性的建议。通过大量的问卷调查以及二元Logistic回归分析,得到影响好特卖学生消费意愿的12种因素,同时得出好特卖应充分了解学生群体的消费需求,丰富商品种类,提供优质的购物体验;在商品品质得以保证的基础上,可以适当提高性价比,以满足学生的消费预算的结论。在此基础上,本研究从宣传和商品两个角度提出了相关适合好特卖的营销宣传建议。HotMaxx is a brand retail collection chain featuring “ultra-low discount”, opening up a new track of retail discount stores. This research implements the research path of combining industry, university and research, and gives full play to the interactive role between academia, industry and the actual market. Through conducting market research and accumulating rich data, it aims to study the students’ consumption intention and promotion mode for HotMaxx, comprehensively analyze various factors affecting students’ purchase intention, and put forward targeted suggestions on this basis. Through a large number of questionnaire survey and binary Logistic regression analysis, 12 factors affect the students’ consumption intention for HotMaxx. At the same time, it is concluded that HotMaxx should fully understand the consumption needs of students, enrich the types of goods, and provide high-quality shopping experience;on the basis of ensuring the quality of goods, the cost performance can be appropriately improved to meet the students’ consumption budget. On this basis, this research puts forward relevant marketing suggestions sui
文章以江苏省为例,基于二元 logistic模型探究了AI 生成式对话产品使用意愿的影响因素。通过对用户的认知、使用情况、影响因素等方面进行调查,分析了用户未来继续使用 AI 生成式对话产品的意愿。研究发现,用户的使用满意度和周围人的使用程度对其使用意愿有显著的正向影响,说明 AI 产品的用户体验和社会传播效应对其未来发展具有重要作用。同时,用户的年龄和职业对使用意愿的影响不显著。通过对模型的回归分析,为 AI 生成式对话产品的迭代优化和推广提出了建议,未来应通过提升技术精度和用户满意度,扩大产品的用户群体。
