住房满意度影响因素研究

Maimu Yang
{"title":"住房满意度影响因素研究","authors":"Maimu Yang","doi":"10.61173/p3g1ht41","DOIUrl":null,"url":null,"abstract":"This article analyzes the impact of housing satisfaction from multiple perspectives. And there are no missing values in the data. Factor analysis is used to reduce the dimensionality of variables, integrating multiple factors into five factors for easy analysis. The meanings of the factors are clear, namely: living conditions, family situation, regional economy, experience situation, and social employment quality. The factor is processed using binomial logistic regression, and the prediction effect is relatively satisfactory. Analysis of the parameters shows that the better the current living conditions, the higher the regional economy, the higher the quality of social employment, and the higher the probability of housing satisfaction. By comparing the full variable binomial logistic regression, it was found that the older the model parameters, the better their age and employment status, the larger their per capita living area, and the lower their education level. Unmarried individuals are more likely to be satisfied with their houses, which is consistent with basic knowledge.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"23 5","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on the Influencing Factors of Housing Satisfaction\",\"authors\":\"Maimu Yang\",\"doi\":\"10.61173/p3g1ht41\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article analyzes the impact of housing satisfaction from multiple perspectives. And there are no missing values in the data. Factor analysis is used to reduce the dimensionality of variables, integrating multiple factors into five factors for easy analysis. The meanings of the factors are clear, namely: living conditions, family situation, regional economy, experience situation, and social employment quality. The factor is processed using binomial logistic regression, and the prediction effect is relatively satisfactory. Analysis of the parameters shows that the better the current living conditions, the higher the regional economy, the higher the quality of social employment, and the higher the probability of housing satisfaction. By comparing the full variable binomial logistic regression, it was found that the older the model parameters, the better their age and employment status, the larger their per capita living area, and the lower their education level. Unmarried individuals are more likely to be satisfied with their houses, which is consistent with basic knowledge.\",\"PeriodicalId\":438278,\"journal\":{\"name\":\"Science and Technology of Engineering, Chemistry and Environmental Protection\",\"volume\":\"23 5\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Science and Technology of Engineering, Chemistry and Environmental Protection\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.61173/p3g1ht41\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science and Technology of Engineering, Chemistry and Environmental Protection","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.61173/p3g1ht41","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文从多个角度分析了住房满意度的影响。数据中没有缺失值。采用因子分析法降低变量的维度,将多个因子整合为五个因子,便于分析。各因子的含义明确,即:居住条件、家庭状况、地区经济、经历状况和社会就业质量。采用二项逻辑回归对因子进行处理,预测效果较为理想。参数分析表明,当前居住条件越好,地区经济越高,社会就业质量越高,住房满意度概率越高。通过比较全变量二项Logistic回归发现,模型参数年龄越大,年龄和就业状况越好,人均居住面积越大,受教育程度越低。未婚者更容易对自己的住房感到满意,这与基本常识是一致的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on the Influencing Factors of Housing Satisfaction
This article analyzes the impact of housing satisfaction from multiple perspectives. And there are no missing values in the data. Factor analysis is used to reduce the dimensionality of variables, integrating multiple factors into five factors for easy analysis. The meanings of the factors are clear, namely: living conditions, family situation, regional economy, experience situation, and social employment quality. The factor is processed using binomial logistic regression, and the prediction effect is relatively satisfactory. Analysis of the parameters shows that the better the current living conditions, the higher the regional economy, the higher the quality of social employment, and the higher the probability of housing satisfaction. By comparing the full variable binomial logistic regression, it was found that the older the model parameters, the better their age and employment status, the larger their per capita living area, and the lower their education level. Unmarried individuals are more likely to be satisfied with their houses, which is consistent with basic knowledge.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信