Original scientific paper
https://doi.org/10.1080/1331677X.2020.1782765
Constructing Knowledge Economy Composite Indicators using an MCA-DEA approach.
José Manuel Guaita Martínez
José María Martín Martín
María Sol Ostos Rey
Mónica de Castro Pardo
Abstract
Composite indicators are a remarkably useful tool in policy analysis and public communication for assessing phenomena, such as
Knowledge-Based Economy (KBE), that cannot be expressed by
means of a simple indicator. The objective of this study is to propose and compare three MCA-DEA models from a “Benefit of
Doubt” (BoD) approach in order to build KBE Composite
Indicators. To show the effectiveness of the models, this paper
proposes a case study of 36 European countries to assess the
degree of development of KBE. The results revealed differences
with respect to the optimal weights assigned to the sub-indicators, the discriminating power, the operability, and the participatory nature of the models. Model 1 yielded high scores for every
country and low discriminating power. Model 2 favored the most
efficient countries in terms of KBE and allows for the incorporation of expert knowledge, thereby giving flexibility to the process. Model 3 made it possible to construct composite indicators
from an optimal balance approach and yielded low results overall.
These results demonstrate the necessity to analyze the different
choices for measuring KBE in order to determine which indicator
is more suitable for each context.
Keywords
Knowledge economy; management; composite indicators; innovation; GP; BoD.
Hrčak ID:
301167
URI
Publication date:
31.12.2021.
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