MSDO / MDSO: A TECHNIQUE FOR REDUCING THE NUMBER OF CAUSAL CONDITIONS IN QUALITATIVE COMPARATIVE ANALYSIS
DOI:
https://doi.org/10.14210/alcance.v29n1(Jan/Abr).p2-19Keywords:
Crisp Set QCA. Comparative Qualitative Analysis. Causal Conditions Reduction.Abstract
Objective: this paper aims to exemplify and analyze each of the operational steps of the MSDO / MDSO technique in order to reduce the systemic complexity in the use of the csQCA method, with the support of the MDSO / MSDO web application. Methodological Design: Comparative analysis: more different cases with equal results and more similar cases with different results (MDSO / MSDO). An application of the technique was carried out to identify the causal conditions that explain the differences in innovative performance in 26 innovation networks in Brazil and Spain. Results From the twenty causal conditions analyzed, which were grouped into four categories (clusters) called Structural, Human, Financial and Organizational Resources, eight causal conditions explaining the difference in performance were identified. Methodological implications: Considering that one of the main problems in social research, including recent innovation studies, is the size of systemic complexity. The difficulty of reducing systemic complexity has been manifested repeatedly when researchers in the field of Administration and Innovation have used case analysis with binary data, called Crisp Set Comparative Qualitative Analyzes - csQCA. The MSDO / MDSO analysis (more different cases with equal results and more similar cases with different results) contributed to minimize this problem Originality: the technique has been less used in Brazil. The four stages of application of the technique are detailed demonstrated and analyzed.References
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