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.
Highlights
Economic theory has exposed the importance of technology and knowledge in economic development and human welfare (Tchamyou, 2017; Dodgson & Gann, 2018)
We provide the results of the composite indicators (CI) using the unweighted average as an aggregation method, which is the aggregation method proposed by the European Innovation Scoreboard (EIS)
Model 1 yields higher values for all countries than the rest of the models since it assigns weights to each of the sub-indicators, which provide an optimal overall score in the case of each country. This is a fairly adaptable model when selecting optimal weights, as it only has to meet two restrictions: restriction (1a), which standardizes the weights, and restriction (1 b), which indicates that the CI is an increasing function of the subindicators, so an improvement in one of the sub-indicators will always result in an improvement in the final CI score
Summary
Economic theory has exposed the importance of technology and knowledge in economic development and human welfare (Tchamyou, 2017; Dodgson & Gann, 2018). A historical analysis of the processes of transformation of the productive system allows us to identify the growing importance of the concept of “knowledge” as a driving force in development processes (Karahan, 2012). The concept of “KnowledgeBased Economy” (KBE) was initially introduced by Machlup (1962) and made.
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