定性比较分析
创业
前因(行为心理学)
答辩人
样品(材料)
集合(抽象数据类型)
模糊集
计量经济学
计算机科学
模糊逻辑
定性研究
社会学
经济
心理学
社会心理学
社会科学
政治学
人工智能
机器学习
色谱法
法学
化学
程序设计语言
财务
作者
Evan J. Douglas,Dean A. Shepherd,Catherine Prentice
标识
DOI:10.1016/j.jbusvent.2019.105970
摘要
Entrepreneurship theory has largely been developed and tested using symmetrical correlational methods, effectively describing the sample-average respondent and subsuming individual differences. Such methods necessarily limit investigation of asymmetries that are evident in entrepreneurship, and provide only a single explanation that belies the multiple pathways to entrepreneurship observed in practice. This paper employs a case-based approach—fuzzy-set Qualitative Comparative Analysis (fsQCA)—to identify configurations of antecedent attributes of individuals in groups within samples, thereby revealing asymmetries and multiple entrepreneurial pathways that are otherwise hidden in the data. We explain the application of fsQCA to reveal these common issues in entrepreneurship; demonstrate how fsQCA complements correlational methods and offers finer-grained understanding of individual entrepreneurial behavior; and offer a comprehensive research agenda to build new entrepreneurship theory.
科研通智能强力驱动
Strongly Powered by AbleSci AI