{"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}
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.