In this paper, we propose a novel method for ranking items such as countries, individuals, or firms based on two indices. This approach is particularly useful when constructing a composite indicator that combines both dimensions is not feasible. The proposed ranking approach involves an iterative scheme where the Voronoi algorithm is applied in a two-dimensional space at each step. To provide empirical evidence that our approach works satisfactorily, we applied the Voronoi-based iterative scheme to rank 34 European countries based on two dimensions: the Human Development Index (HDI) and the Happiness Index (HI). The correlation coefficient between the rankings based on HDI and HI is lower than the correlation coefficients between the Voronoi-based ranking and HDI, as well as between the Voronoi-based ranking and HI. These results suggest that the new method is capable of better capturing the information from both original indices.
Two in One: A New Tool to Combine Two Rankings Based on the Voronoi Diagram / Mariani, Francesca; Ciommi, Mariateresa; Recchioni, Maria Cristina. - In: SOCIAL INDICATORS RESEARCH. - ISSN 0303-8300. - (2023). [Epub ahead of print] [10.1007/s11205-023-03192-9]
Two in One: A New Tool to Combine Two Rankings Based on the Voronoi Diagram
Mariani, Francesca;Ciommi, Mariateresa
;Recchioni, Maria Cristina
2023-01-01
Abstract
In this paper, we propose a novel method for ranking items such as countries, individuals, or firms based on two indices. This approach is particularly useful when constructing a composite indicator that combines both dimensions is not feasible. The proposed ranking approach involves an iterative scheme where the Voronoi algorithm is applied in a two-dimensional space at each step. To provide empirical evidence that our approach works satisfactorily, we applied the Voronoi-based iterative scheme to rank 34 European countries based on two dimensions: the Human Development Index (HDI) and the Happiness Index (HI). The correlation coefficient between the rankings based on HDI and HI is lower than the correlation coefficients between the Voronoi-based ranking and HDI, as well as between the Voronoi-based ranking and HI. These results suggest that the new method is capable of better capturing the information from both original indices.File | Dimensione | Formato | |
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