RT Journal Article
T1 Constructing Knowledge Economy Composite Indicators using an MCA-DEA approach
A1 Guaita Martínez, José Manuel
A1 Martín Martín, José María
A1 Ostos Rey, María Sol
A1 De Castro Pardo, Mónica
AB Composite indicators are a remarkably useful tool in policy ana- lysis 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 pro- pose 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-indica- tors, the discriminating power, the operability, and the participa- tory 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 incorpor- ation of expert knowledge, thereby giving flexibility to the pro- cess. 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.
PB Taylor & Francis
SN 1331-677X
YR 2020
FD 2020
LK https://hdl.handle.net/20.500.14352/97101
UL https://hdl.handle.net/20.500.14352/97101
LA eng
NO José Manuel Guaita Martínez, José María Martín Martín, María Sol Ostos Rey & Mónica de Castro Pardo (2021) Constructing Knowledge Economy Composite Indicators using an MCA-DEA approach., Economic Research-Ekonomska Istraživanja, 34:1, 331-351, DOI: 10.1080/1331677X.2020.1782765
DS Docta Complutense
RD 29 jul 2025