{"title":"组织心理学中的模糊集定性比较分析(fsQCA):理论概述、研究指南和使用R软件的一步一步教程。","authors":"Nicola Cangialosi","doi":"10.1017/SJP.2023.21","DOIUrl":null,"url":null,"abstract":"<p><p>Fuzzy set qualitative comparative analysis (fsQCA) is a method for assessing the effects of configurations of variables leading to an outcome. The recent growth of interest in this technique in organizational psychology is proving this method to be an important tool for addressing new and decisive research hypotheses. However, the effectiveness of fsQCA is dictated not only by its general principles, but also by how well these are understood and applied in the research community. Consequently, a guide that covers the fundamental ideas and tenets of the approach is required to aid the research community in its comprehension and practical application. The current study seeks to offer an understanding of FsQCA by providing: (a) A complete description of the method highlighting some of the most important theoretical-methodological aspects; (b) a perspective on the most used guidelines and recommendations, and (c) step-by-step instructions on how to carry out FsQCA in R using the QCA package. Data from 120 employees and supervisors derived from a company based in central Italy were used o best to illustrate how to carry out fsQCA. Codes for conducting the analyses from the QCA package for R accompany the tutorial and can be adapted to a new dataset.</p>","PeriodicalId":54309,"journal":{"name":"Spanish Journal of Psychology","volume":"26 ","pages":"e21"},"PeriodicalIF":2.9000,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fuzzy-Set Qualitative Comparative Analysis (fsQCA) in Organizational Psychology: Theoretical Overview, Research Guidelines, and A Step-By-Step Tutorial Using R Software.\",\"authors\":\"Nicola Cangialosi\",\"doi\":\"10.1017/SJP.2023.21\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Fuzzy set qualitative comparative analysis (fsQCA) is a method for assessing the effects of configurations of variables leading to an outcome. The recent growth of interest in this technique in organizational psychology is proving this method to be an important tool for addressing new and decisive research hypotheses. However, the effectiveness of fsQCA is dictated not only by its general principles, but also by how well these are understood and applied in the research community. Consequently, a guide that covers the fundamental ideas and tenets of the approach is required to aid the research community in its comprehension and practical application. The current study seeks to offer an understanding of FsQCA by providing: (a) A complete description of the method highlighting some of the most important theoretical-methodological aspects; (b) a perspective on the most used guidelines and recommendations, and (c) step-by-step instructions on how to carry out FsQCA in R using the QCA package. Data from 120 employees and supervisors derived from a company based in central Italy were used o best to illustrate how to carry out fsQCA. Codes for conducting the analyses from the QCA package for R accompany the tutorial and can be adapted to a new dataset.</p>\",\"PeriodicalId\":54309,\"journal\":{\"name\":\"Spanish Journal of Psychology\",\"volume\":\"26 \",\"pages\":\"e21\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2023-07-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Spanish Journal of Psychology\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1017/SJP.2023.21\",\"RegionNum\":4,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Spanish Journal of Psychology","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1017/SJP.2023.21","RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY","Score":null,"Total":0}
Fuzzy-Set Qualitative Comparative Analysis (fsQCA) in Organizational Psychology: Theoretical Overview, Research Guidelines, and A Step-By-Step Tutorial Using R Software.
Fuzzy set qualitative comparative analysis (fsQCA) is a method for assessing the effects of configurations of variables leading to an outcome. The recent growth of interest in this technique in organizational psychology is proving this method to be an important tool for addressing new and decisive research hypotheses. However, the effectiveness of fsQCA is dictated not only by its general principles, but also by how well these are understood and applied in the research community. Consequently, a guide that covers the fundamental ideas and tenets of the approach is required to aid the research community in its comprehension and practical application. The current study seeks to offer an understanding of FsQCA by providing: (a) A complete description of the method highlighting some of the most important theoretical-methodological aspects; (b) a perspective on the most used guidelines and recommendations, and (c) step-by-step instructions on how to carry out FsQCA in R using the QCA package. Data from 120 employees and supervisors derived from a company based in central Italy were used o best to illustrate how to carry out fsQCA. Codes for conducting the analyses from the QCA package for R accompany the tutorial and can be adapted to a new dataset.
期刊介绍:
The Spanish Journal of Psychology is published with the aim of promoting the international dissemination of relevant empirical research and theoretical and methodological proposals in the various areas of specialization within psychology.
The first Spanish journal with an international scope published entirely in English.