{"title":"几种宗教虔诚度度量的特征","authors":"Ronald B. Larson, Chris Heimrich","doi":"10.2139/ssrn.2624397","DOIUrl":null,"url":null,"abstract":"Incorporating religiosity variables into macro- and micro-marketing studies can add to the insights produced. This research used data from a national survey of 725 adults, fielded in January 2015, to illustrate how religiosity measures differ. Responses to 34 survey questions were used to construct six factor-based religiosity measures. Six linear regressions tried to predict the religiosity factors with demographics, a social desirability bias measure, and a political preference indicator as independent variables. While some independent variables were significant, the six religiosity and spirituality factors (Intrinsic Motivation, Extrinsic-Social, Extrinsic-Personal, Tentativeness Quest, Complexity Quest, and Doubt Quest) contained considerable information that was not explained by the regressions.","PeriodicalId":203673,"journal":{"name":"PSN: Other Political Behavior: Race","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Characteristics of Several Religiosity Measures\",\"authors\":\"Ronald B. Larson, Chris Heimrich\",\"doi\":\"10.2139/ssrn.2624397\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Incorporating religiosity variables into macro- and micro-marketing studies can add to the insights produced. This research used data from a national survey of 725 adults, fielded in January 2015, to illustrate how religiosity measures differ. Responses to 34 survey questions were used to construct six factor-based religiosity measures. Six linear regressions tried to predict the religiosity factors with demographics, a social desirability bias measure, and a political preference indicator as independent variables. While some independent variables were significant, the six religiosity and spirituality factors (Intrinsic Motivation, Extrinsic-Social, Extrinsic-Personal, Tentativeness Quest, Complexity Quest, and Doubt Quest) contained considerable information that was not explained by the regressions.\",\"PeriodicalId\":203673,\"journal\":{\"name\":\"PSN: Other Political Behavior: Race\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"PSN: Other Political Behavior: Race\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.2624397\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"PSN: Other Political Behavior: Race","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2624397","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Incorporating religiosity variables into macro- and micro-marketing studies can add to the insights produced. This research used data from a national survey of 725 adults, fielded in January 2015, to illustrate how religiosity measures differ. Responses to 34 survey questions were used to construct six factor-based religiosity measures. Six linear regressions tried to predict the religiosity factors with demographics, a social desirability bias measure, and a political preference indicator as independent variables. While some independent variables were significant, the six religiosity and spirituality factors (Intrinsic Motivation, Extrinsic-Social, Extrinsic-Personal, Tentativeness Quest, Complexity Quest, and Doubt Quest) contained considerable information that was not explained by the regressions.