EconPapers    
Economics at your fingertips  
 

Analysis of Global Innovation Index by structural qualitative association

Kun-Huang Huarng and Tiffany Hui-Kuang Yu

Technological Forecasting and Social Change, 2022, vol. 182, issue C

Abstract: The Global Innovation Index (GII) is a popular index for measuring country's innovation competitiveness. Hence, this study intends to analyze the whole relationships of the GII. The GII structure consists of multiple layers of variables. In a research structure, when there are more variables and more layers, the number of relationships can grow very huge. This study uses both fuzzy set qualitative comparative analysis and structural qualitative association as the research methods and proposes a systematic approach to screen out the insignificant relationships. This study uses GII 2020 as the data and concludes two relationships for Positive GII and two for Negative GII. When all antecedents but Market Sophistication are Positive, the GII tends to be Positive. On the other hand, when all antecedents but Market Sophistication are Negative, the GII tends to be Negative. This study then provides new ranking of the countries based on the empirical results. Though the new ranking for a specific country may be different from the original one, the top countries in the original ranking remain on the top on the new ranking and the bottom countries remain in the bottom.

Keywords: Fuzzy set qualitative comparative analysis (fsQCA); Structural qualitative association; Thresholds (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162522003742
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:182:y:2022:i:c:s0040162522003742

DOI: 10.1016/j.techfore.2022.121850

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:tefoso:v:182:y:2022:i:c:s0040162522003742