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). [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.
2023
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/320871
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 1
social impact