Identifying single necessary conditions with NCA and fsQCA

被引:295
作者
Dul, Jan [1 ,2 ]
机构
[1] Erasmus Univ, Rotterdam Sch Management, NL-3000 DR Rotterdam, Netherlands
[2] Burgemeester Oudlaan 50, NL-3062 PA Rotterdam, Netherlands
关键词
Necessity; Critical success factor; Constraint; Bottleneck; fsQCA; NCA;
D O I
10.1016/j.jbusres.2015.10.134
中图分类号
F [经济];
学科分类号
02 ;
摘要
Single necessary (but not sufficient) conditions are critically important for business theory and practice. Without them, the outcomes cannot occur, and other conditions cannot compensate for this absence. Currently two analytical approaches are available for identifying single necessary conditions: Necessary Condition Analysis (NCA), which was recently developed, and fuzzy-set qualitative comparative analysis (fsQCA), which is a more established approach. FsQCA normally focuses on sufficient but not necessary configurations, but can also identify necessary but not sufficient conditions. This study uses NCA to analyze two examples of empirical datasets published in the journal of Business Research that use fsQCA to identify single necessary conditions. A comparison of the results of NCA and fsQCA shows that NCA can identify more necessary conditions than fsQCA and can specify the level of the condition that is required for a given level of the outcome. (c) 2015 Elsevier Inc. All rights reserved.
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页码:1516 / 1523
页数:8
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