Constructing Knowledge Economy Composite Indicators using an MCA-DEA approach

Autor: José Manuel Guaita Martínez, Mónica de Castro Pardo, José M. Martín, María del Sol Ostos Rey
Přispěvatelé: Guaita Martínez, José Manuel, Martín Martín, José María, Ostos Rey, María Del Sol, Castro Pardo, Mónica de
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Ekonomska Istraživanja, Vol 34, Iss 1, Pp 331-351 (2021)
Re-Unir. Archivo Institucional de la Universidad Internacional de La Rioja
instname
Economic research-Ekonomska istraživanja
Volume 34
Issue 1
Digibug. Repositorio Institucional de la Universidad de Granada
Digibug: Repositorio Institucional de la Universidad de Granada
Universidad de Granada (UGR)
ISSN: 1331-677X
1848-9664
Popis: 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.
Databáze: OpenAIRE