Chapter 3 The Two QCAs
From a Small-N to a Large-N Set Theoretic Approach
Bibliographic Data
| ID | 20034809 |
|---|---|
| Authors | Thomas Greckhamer (0000-0002-5766-556X), Vilmos F Misangyi (0000-0001-5025-885X), Peer C Fiss |
| Year | 2013 |
| Pages | 49-75 |
| Publication date | 2013-01-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | CHAPTER |
| Venue | Configurational Theory and Methods in Organizational Research (SOURCE_BOOK) |
| Publisher | Emerald Group Publishing Limited (PUBLISHER) |
| DOI | 10.1108/s0733-558x(2013)0000038007 |
| OpenAlex | W2506533400 |
| ISBN | 9781781907788 |
| Language | EN |
| Citations received | 91 |
| References cited | 31 |
Although QCA was originally developed specifically for small-N settings, recent studies have shown its potential for large-N organization studies. In this chapter, we provide guidance to prospective researchers with the goal of opening up QCA’s potential for widespread use in organization studies involving large-N settings, both as an alternative and as a complement to conventional regression analyses. We compare small-N and large-N QCA with respect to theoretical assumptions and objectives, processes and decisions involved in building the causal model, selecting the sample, as well as analyzing the data and interpreting the results. Finally, we discuss the prospects for large-N configurational analysis in organization studies and related fields going forward
Biology · Data science · Econometrics · Economics · Machine learning · Management science · Qualitative comparative analysis · Computer Science · Innovation and Knowledge Management · Mathematics · Qualitative Comparative Analysis Research
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| Unique citing works | 91 |
|---|---|
| Citations per year | 7,58 |
| Citation span | 2014 - 2026 (13) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 88 |