{"title":"国民总收入、足球工作者与国家队成绩的logistic回归分析","authors":"Peter Omondi-Ochieng","doi":"10.1108/TPM-04-2015-0018","DOIUrl":null,"url":null,"abstract":"Purpose – This study aims to examine the association between national economic prosperity (measured by per capita gross national income – GNI) and the acquisition of football workers (indicated by number of amateur footballers, football officials and professional footballers) and predict football performances (specified by qualifications at continental football championships) based on per capita GNI and football workers. Design/methodology/approach – Archival data of 203 national football teams were utilized based on continental football championship records before 2014. Binary logistic regression analysis was used to build various models to ascertain their predictive values. Economically prosperous nations are those with a per capita GNI of more than US$10,000, and unprosperous nations are those with per capita GNI of less than US$10,000. Findings – The analysis indicated that per capita GNI was significantly and positively associated with the acquisition of football workers – but not predictive of footb...","PeriodicalId":46084,"journal":{"name":"Team Performance Management","volume":null,"pages":null},"PeriodicalIF":1.6000,"publicationDate":"2015-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/TPM-04-2015-0018","citationCount":"13","resultStr":"{\"title\":\"Gross national income, football workers and national football team performances: A logistic regression analysis\",\"authors\":\"Peter Omondi-Ochieng\",\"doi\":\"10.1108/TPM-04-2015-0018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Purpose – This study aims to examine the association between national economic prosperity (measured by per capita gross national income – GNI) and the acquisition of football workers (indicated by number of amateur footballers, football officials and professional footballers) and predict football performances (specified by qualifications at continental football championships) based on per capita GNI and football workers. Design/methodology/approach – Archival data of 203 national football teams were utilized based on continental football championship records before 2014. Binary logistic regression analysis was used to build various models to ascertain their predictive values. Economically prosperous nations are those with a per capita GNI of more than US$10,000, and unprosperous nations are those with per capita GNI of less than US$10,000. Findings – The analysis indicated that per capita GNI was significantly and positively associated with the acquisition of football workers – but not predictive of footb...\",\"PeriodicalId\":46084,\"journal\":{\"name\":\"Team Performance Management\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2015-09-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1108/TPM-04-2015-0018\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Team Performance Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/TPM-04-2015-0018\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MANAGEMENT\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Team Performance Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/TPM-04-2015-0018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MANAGEMENT","Score":null,"Total":0}
Gross national income, football workers and national football team performances: A logistic regression analysis
Purpose – This study aims to examine the association between national economic prosperity (measured by per capita gross national income – GNI) and the acquisition of football workers (indicated by number of amateur footballers, football officials and professional footballers) and predict football performances (specified by qualifications at continental football championships) based on per capita GNI and football workers. Design/methodology/approach – Archival data of 203 national football teams were utilized based on continental football championship records before 2014. Binary logistic regression analysis was used to build various models to ascertain their predictive values. Economically prosperous nations are those with a per capita GNI of more than US$10,000, and unprosperous nations are those with per capita GNI of less than US$10,000. Findings – The analysis indicated that per capita GNI was significantly and positively associated with the acquisition of football workers – but not predictive of footb...
期刊介绍:
This international journal contributes to the successful implementation and development of work teams and team-based organizations by providing a forum for sharing experience and learning to stimulate thought and transfer of ideas. It seeks to bridge the gap between research and practice by publishing articles where the claims are evidence-based and the conclusions have practical value. Effective teams form the heart of every successful organization. But team management is one of the hardest challenges faced by managers.