Statistical Analysis Of Factors Affecting Purchase Intention Of New Energy Vehicles

In the current society,the problem of environmental pollution is severe and the energy crisis is intensifying.Under the background of the new era of "lucid waters and lush mountains are invaluable assets",green environmental protection,energy saving and emission reduction concepts are becoming more and more important.Therefore,new energy vehicles have received widespread attention.However,as an emerging product,new energy vehicles still face some problems,resulting in their low proportion in the national automobile market and the embarrassing situation of poor recognition.Therefore,exploring the key factors affecting consumers' willingness to purchase and enhancing consumers' recognition of new energy vehicles are of great significance for promoting the rapid development of new energy automobile industry.Based on relevant literatures at home and abroad,this paper collects data by means of questionnaires,and uses the data to make an empirical analysis of the basic characteristics of the respondents and the factors affecting purchase intention.Chapter one mainly introduces the research background and research significance of the thesis,summarizes the relevant research literature and results at home and abroad,and clarifies the research methods and research ideas of the thesis.Chapter two briefly describes the factors and models used in the paper,such as factor analysis,path analysis and multivariate Logistic regression.Chapter three refers to the relevant literature and the predecessor design classic scale to conduct questionnaire design,conduct questionnaire reliability and validity analysis for pre-investigation data,and modify the questionnaire to carry on formal investigation.Chapter four analyzes the obtained 314 valid questionnaires.Firstly,the basic characteristics of the respondents are analyzed,and using the contingency table to perform the independent chi-square test by the SPSS23.0 software.Secondly,the system clustering method is used to cluster the samples surveyed to obtain three classes.Thirdly,we analyze the 22 factors that affect consumers' willingness to purchase,and use the principal component method to extract six common factors,confirmatory factor analysis is performed using Amos software.Finally,we establish a multivariate Logistic regression model to forecast the prospects of new energy vehicles.Chapter five is conclusions and recommendations.There is a significant relationship between the gender,age,occupation,annual family income,driver's license of the respondent and the willingness to purchase.The extracted six common factors have different degrees of influence on the willingness to purchase.Safety and comfort have the most significant impact,followed by green environmental protection,cost advantages and supporting services.By analyzing the coefficients of the multivariate logistic regression model,we find that safety and comfort have the greatest impact on the prospects of new energy vehicles,followed by green environmental protection,cost advantages and high efficiency and convenient.Finally,according to the analysis results,some reasonable proposals are put forward for the development of new energy vehicles.