Classification of countries based on development indices by using K-means and grey relational analysis
Abstract Clustering countries based on their development profile is important, as it helps in the efficient allocation and use of resources for institutions like the World Bank, IMF and many others. However, measuring the status of development in each country is challenging, as development encompass...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Basel, Sayel [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer Nature B.V. 2021 |
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| Übergeordnetes Werk: |
Enthalten in: GeoJournal - Springer Netherlands, 1977, 87(2021), 5 vom: 26. Juli, Seite 3915-3933 |
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| Übergeordnetes Werk: |
volume:87 ; year:2021 ; number:5 ; day:26 ; month:07 ; pages:3915-3933 |
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| DOI / URN: |
10.1007/s10708-021-10479-2 |
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| 520 | |a Abstract Clustering countries based on their development profile is important, as it helps in the efficient allocation and use of resources for institutions like the World Bank, IMF and many others. However, measuring the status of development in each country is challenging, as development encompasses several facets such as economic, social, environmental and institutional aspects. These dimensions should be captured and aggregated appropriately before attempting to classify countries based on development. In this context, this paper attempts to measure various dimensions of development through four indices namely, Economic Index (EI), Social Index (SI), Sustainability Index (SUI) and Institutional Index (II) for the period between 1996 through 2015 for 102 countries. And then we categorize the countries based on these development indices using the grey relational analysis and K-means clustering method. Our study classifies countries into four clusters with twelve countries in the first cluster, fifty in second, twenty-seven and thirteen countries in third and fourth clusters respectively. Having taken each of the dimensions of development independently, our results show that no cluster has performed poorly in all four aspects. | ||
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10.1007/s10708-021-10479-2 doi (DE-627)OLC2079856642 (DE-He213)s10708-021-10479-2-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn BIODIV DE-30 fid Basel, Sayel verfasserin aut Classification of countries based on development indices by using K-means and grey relational analysis 2021 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2021 Abstract Clustering countries based on their development profile is important, as it helps in the efficient allocation and use of resources for institutions like the World Bank, IMF and many others. However, measuring the status of development in each country is challenging, as development encompasses several facets such as economic, social, environmental and institutional aspects. These dimensions should be captured and aggregated appropriately before attempting to classify countries based on development. In this context, this paper attempts to measure various dimensions of development through four indices namely, Economic Index (EI), Social Index (SI), Sustainability Index (SUI) and Institutional Index (II) for the period between 1996 through 2015 for 102 countries. And then we categorize the countries based on these development indices using the grey relational analysis and K-means clustering method. Our study classifies countries into four clusters with twelve countries in the first cluster, fifty in second, twenty-seven and thirteen countries in third and fourth clusters respectively. Having taken each of the dimensions of development independently, our results show that no cluster has performed poorly in all four aspects. Development K-means clustering Grey relational analysis Principal component analysis Gopakumar, K. U. aut Rao, R. Prabhakara aut Enthalten in GeoJournal Springer Netherlands, 1977 87(2021), 5 vom: 26. Juli, Seite 3915-3933 (DE-627)13044555X (DE-600)715360-0 (DE-576)015981851 0343-2521 nnns volume:87 year:2021 number:5 day:26 month:07 pages:3915-3933 https://doi.org/10.1007/s10708-021-10479-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-GEO SSG-OPC-GGO GBV_ILN_70 GBV_ILN_267 AR 87 2021 5 26 07 3915-3933 |
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10.1007/s10708-021-10479-2 doi (DE-627)OLC2079856642 (DE-He213)s10708-021-10479-2-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn BIODIV DE-30 fid Basel, Sayel verfasserin aut Classification of countries based on development indices by using K-means and grey relational analysis 2021 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2021 Abstract Clustering countries based on their development profile is important, as it helps in the efficient allocation and use of resources for institutions like the World Bank, IMF and many others. However, measuring the status of development in each country is challenging, as development encompasses several facets such as economic, social, environmental and institutional aspects. These dimensions should be captured and aggregated appropriately before attempting to classify countries based on development. In this context, this paper attempts to measure various dimensions of development through four indices namely, Economic Index (EI), Social Index (SI), Sustainability Index (SUI) and Institutional Index (II) for the period between 1996 through 2015 for 102 countries. And then we categorize the countries based on these development indices using the grey relational analysis and K-means clustering method. Our study classifies countries into four clusters with twelve countries in the first cluster, fifty in second, twenty-seven and thirteen countries in third and fourth clusters respectively. Having taken each of the dimensions of development independently, our results show that no cluster has performed poorly in all four aspects. Development K-means clustering Grey relational analysis Principal component analysis Gopakumar, K. U. aut Rao, R. Prabhakara aut Enthalten in GeoJournal Springer Netherlands, 1977 87(2021), 5 vom: 26. Juli, Seite 3915-3933 (DE-627)13044555X (DE-600)715360-0 (DE-576)015981851 0343-2521 nnns volume:87 year:2021 number:5 day:26 month:07 pages:3915-3933 https://doi.org/10.1007/s10708-021-10479-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-GEO SSG-OPC-GGO GBV_ILN_70 GBV_ILN_267 AR 87 2021 5 26 07 3915-3933 |
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10.1007/s10708-021-10479-2 doi (DE-627)OLC2079856642 (DE-He213)s10708-021-10479-2-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn BIODIV DE-30 fid Basel, Sayel verfasserin aut Classification of countries based on development indices by using K-means and grey relational analysis 2021 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2021 Abstract Clustering countries based on their development profile is important, as it helps in the efficient allocation and use of resources for institutions like the World Bank, IMF and many others. However, measuring the status of development in each country is challenging, as development encompasses several facets such as economic, social, environmental and institutional aspects. These dimensions should be captured and aggregated appropriately before attempting to classify countries based on development. In this context, this paper attempts to measure various dimensions of development through four indices namely, Economic Index (EI), Social Index (SI), Sustainability Index (SUI) and Institutional Index (II) for the period between 1996 through 2015 for 102 countries. And then we categorize the countries based on these development indices using the grey relational analysis and K-means clustering method. Our study classifies countries into four clusters with twelve countries in the first cluster, fifty in second, twenty-seven and thirteen countries in third and fourth clusters respectively. Having taken each of the dimensions of development independently, our results show that no cluster has performed poorly in all four aspects. Development K-means clustering Grey relational analysis Principal component analysis Gopakumar, K. U. aut Rao, R. Prabhakara aut Enthalten in GeoJournal Springer Netherlands, 1977 87(2021), 5 vom: 26. Juli, Seite 3915-3933 (DE-627)13044555X (DE-600)715360-0 (DE-576)015981851 0343-2521 nnns volume:87 year:2021 number:5 day:26 month:07 pages:3915-3933 https://doi.org/10.1007/s10708-021-10479-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-GEO SSG-OPC-GGO GBV_ILN_70 GBV_ILN_267 AR 87 2021 5 26 07 3915-3933 |
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10.1007/s10708-021-10479-2 doi (DE-627)OLC2079856642 (DE-He213)s10708-021-10479-2-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn BIODIV DE-30 fid Basel, Sayel verfasserin aut Classification of countries based on development indices by using K-means and grey relational analysis 2021 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2021 Abstract Clustering countries based on their development profile is important, as it helps in the efficient allocation and use of resources for institutions like the World Bank, IMF and many others. However, measuring the status of development in each country is challenging, as development encompasses several facets such as economic, social, environmental and institutional aspects. These dimensions should be captured and aggregated appropriately before attempting to classify countries based on development. In this context, this paper attempts to measure various dimensions of development through four indices namely, Economic Index (EI), Social Index (SI), Sustainability Index (SUI) and Institutional Index (II) for the period between 1996 through 2015 for 102 countries. And then we categorize the countries based on these development indices using the grey relational analysis and K-means clustering method. Our study classifies countries into four clusters with twelve countries in the first cluster, fifty in second, twenty-seven and thirteen countries in third and fourth clusters respectively. Having taken each of the dimensions of development independently, our results show that no cluster has performed poorly in all four aspects. Development K-means clustering Grey relational analysis Principal component analysis Gopakumar, K. U. aut Rao, R. Prabhakara aut Enthalten in GeoJournal Springer Netherlands, 1977 87(2021), 5 vom: 26. Juli, Seite 3915-3933 (DE-627)13044555X (DE-600)715360-0 (DE-576)015981851 0343-2521 nnns volume:87 year:2021 number:5 day:26 month:07 pages:3915-3933 https://doi.org/10.1007/s10708-021-10479-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-GEO SSG-OPC-GGO GBV_ILN_70 GBV_ILN_267 AR 87 2021 5 26 07 3915-3933 |
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Abstract Clustering countries based on their development profile is important, as it helps in the efficient allocation and use of resources for institutions like the World Bank, IMF and many others. However, measuring the status of development in each country is challenging, as development encompasses several facets such as economic, social, environmental and institutional aspects. These dimensions should be captured and aggregated appropriately before attempting to classify countries based on development. In this context, this paper attempts to measure various dimensions of development through four indices namely, Economic Index (EI), Social Index (SI), Sustainability Index (SUI) and Institutional Index (II) for the period between 1996 through 2015 for 102 countries. And then we categorize the countries based on these development indices using the grey relational analysis and K-means clustering method. Our study classifies countries into four clusters with twelve countries in the first cluster, fifty in second, twenty-seven and thirteen countries in third and fourth clusters respectively. Having taken each of the dimensions of development independently, our results show that no cluster has performed poorly in all four aspects. © The Author(s), under exclusive licence to Springer Nature B.V. 2021 |
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Abstract Clustering countries based on their development profile is important, as it helps in the efficient allocation and use of resources for institutions like the World Bank, IMF and many others. However, measuring the status of development in each country is challenging, as development encompasses several facets such as economic, social, environmental and institutional aspects. These dimensions should be captured and aggregated appropriately before attempting to classify countries based on development. In this context, this paper attempts to measure various dimensions of development through four indices namely, Economic Index (EI), Social Index (SI), Sustainability Index (SUI) and Institutional Index (II) for the period between 1996 through 2015 for 102 countries. And then we categorize the countries based on these development indices using the grey relational analysis and K-means clustering method. Our study classifies countries into four clusters with twelve countries in the first cluster, fifty in second, twenty-seven and thirteen countries in third and fourth clusters respectively. Having taken each of the dimensions of development independently, our results show that no cluster has performed poorly in all four aspects. © The Author(s), under exclusive licence to Springer Nature B.V. 2021 |
| abstract_unstemmed |
Abstract Clustering countries based on their development profile is important, as it helps in the efficient allocation and use of resources for institutions like the World Bank, IMF and many others. However, measuring the status of development in each country is challenging, as development encompasses several facets such as economic, social, environmental and institutional aspects. These dimensions should be captured and aggregated appropriately before attempting to classify countries based on development. In this context, this paper attempts to measure various dimensions of development through four indices namely, Economic Index (EI), Social Index (SI), Sustainability Index (SUI) and Institutional Index (II) for the period between 1996 through 2015 for 102 countries. And then we categorize the countries based on these development indices using the grey relational analysis and K-means clustering method. Our study classifies countries into four clusters with twelve countries in the first cluster, fifty in second, twenty-seven and thirteen countries in third and fourth clusters respectively. Having taken each of the dimensions of development independently, our results show that no cluster has performed poorly in all four aspects. © The Author(s), under exclusive licence to Springer Nature B.V. 2021 |
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Classification of countries based on development indices by using K-means and grey relational analysis |
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Gopakumar, K. U. Rao, R. Prabhakara |
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