Filippo Ferrarini, Silvia Muzzioli, Bernard De Baets
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Therefore, the purpose of this paper is to measure regional competitiveness using the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) by considering different distance measures and two levels of analysis to provide a comparative and comprehensive measurement of regional competitiveness in Europe.</p><!--/ Abstract__block -->\n<h3>Design/methodology/approach</h3>\n<p>The authors apply TOPSIS based on three different distance measures (the Manhattan, the Euclidean and the Mahalanobis distance measures) to the regions of the EU Regional Competitiveness Index (RCI) 2019, which is taken as the frame of reference.</p><!--/ Abstract__block -->\n<h3>Findings</h3>\n<p>The authors replicate the RCI by using TOPSIS with a less preferred choice of distance measure, indicating TOPSIS as a valuable method for policymakers in the analysis of regional competitiveness. The authors argue in favour of the Mahalanobis distance measure as the best of the three, as it considers correlations among macro-economic indicators.</p><!--/ Abstract__block -->\n<h3>Originality/value</h3>\n<p>This study aims to make three contributions. Firstly, by replicating the RCI by means of TOPSIS with a less preferred choice of distance measure, the paper provides a benchmark for future research on regional competitiveness. Secondly, by suggesting the use of TOPSIS with the use of the Mahalanobis distance measure, the authors show how to measure regional competitiveness by taking into account correlations among pillars. Thirdly, the authors argue in favour of considering clusters of regions when measuring regional competitiveness.</p><!--/ Abstract__block -->","PeriodicalId":46521,"journal":{"name":"Competitiveness Review","volume":"15 1","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A TOPSIS analysis of regional competitiveness at European level\",\"authors\":\"Filippo Ferrarini, Silvia Muzzioli, Bernard De Baets\",\"doi\":\"10.1108/cr-01-2024-0005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3>Purpose</h3>\\n<p>The measurement of regional competitiveness is becoming essential for policymakers to address territorial disparities, while considering the issue of correlations among indicators. Therefore, the purpose of this paper is to measure regional competitiveness using the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) by considering different distance measures and two levels of analysis to provide a comparative and comprehensive measurement of regional competitiveness in Europe.</p><!--/ Abstract__block -->\\n<h3>Design/methodology/approach</h3>\\n<p>The authors apply TOPSIS based on three different distance measures (the Manhattan, the Euclidean and the Mahalanobis distance measures) to the regions of the EU Regional Competitiveness Index (RCI) 2019, which is taken as the frame of reference.</p><!--/ Abstract__block -->\\n<h3>Findings</h3>\\n<p>The authors replicate the RCI by using TOPSIS with a less preferred choice of distance measure, indicating TOPSIS as a valuable method for policymakers in the analysis of regional competitiveness. 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A TOPSIS analysis of regional competitiveness at European level
Purpose
The measurement of regional competitiveness is becoming essential for policymakers to address territorial disparities, while considering the issue of correlations among indicators. Therefore, the purpose of this paper is to measure regional competitiveness using the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) by considering different distance measures and two levels of analysis to provide a comparative and comprehensive measurement of regional competitiveness in Europe.
Design/methodology/approach
The authors apply TOPSIS based on three different distance measures (the Manhattan, the Euclidean and the Mahalanobis distance measures) to the regions of the EU Regional Competitiveness Index (RCI) 2019, which is taken as the frame of reference.
Findings
The authors replicate the RCI by using TOPSIS with a less preferred choice of distance measure, indicating TOPSIS as a valuable method for policymakers in the analysis of regional competitiveness. The authors argue in favour of the Mahalanobis distance measure as the best of the three, as it considers correlations among macro-economic indicators.
Originality/value
This study aims to make three contributions. Firstly, by replicating the RCI by means of TOPSIS with a less preferred choice of distance measure, the paper provides a benchmark for future research on regional competitiveness. Secondly, by suggesting the use of TOPSIS with the use of the Mahalanobis distance measure, the authors show how to measure regional competitiveness by taking into account correlations among pillars. Thirdly, the authors argue in favour of considering clusters of regions when measuring regional competitiveness.
期刊介绍:
The following list indicates the key issues in the Competitiveness Review. We invite papers on these and related topics. Special issues of the Review will collect papers on specific topics selected by the editors. Definition/conceptual framework of competitiveness Competitiveness diagnostics and rankings Competitiveness and economic outcomes Specific dimensions of competitiveness Competitiveness and endowments Competitiveness and economic development Location and business strategy International business and the role of MNCs Innovation and innovative capacity Clusters and cluster initiatives Institutions for competitiveness Public policy (e.g., innovation, cluster development, regional development) The Competitiveness Review aims to publish high quality papers directed at scholars, government institutions, businesses and practitioners. It appears in collaboration with key academic and professional groups in the field of competitiveness analysis and policy, including the Microeconomics of Competitiveness (MOC) network and The Competitiveness Institute (TCI) practitioner network for competitiveness, clusters and innovation.