The Measurement of Social Cohesion at Province Level in Poland Using Metric and Interval-Valued Data

Walesiak, Marek; Dehnel, Grażyna

doi:10.3390/su12187664

Cited by 8 publications

(5 citation statements)

References 36 publications

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“…This variant of the Hellwig method was applied to evaluate the economic efficiency of small- and medium-sized manufacturing enterprises in districts of Wielkopolska province [ 32 , 33 ], assess changes in population ageing in regions of the V4 countries [ 34 ], and measure social cohesion at the province level in Poland [ 35 ].…”

Section: The Hellwig Methods Based On Two Reference Pointsmentioning

confidence: 99%

On Some Extension of Intuitionistic Fuzzy Synthetic Measures for Two Reference Points and Entropy Weights

Roszkowska

Jefmański

Kusterka-Jefmańska

2022

Entropy

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In this paper, a novel Double Intuitionistic Fuzzy Synthetic Measure (DIFSM), based on intuitionistic fuzzy values for handling multi-criteria decision-making problems used to rank alternatives, is presented. In the studies, intuitionistic fuzzy sets (IFSs) represented uncertain, imprecise information or human judgment. The intuitionistic fuzzy sets can also reflect the approval, rejection, and hesitation of decision-makers. The degrees of satisfiability and non-satisfiability and uncertainty of each alternative with respect to a set of criteria are described by membership functions, non-membership functions, and hesitancy indexes, respectively. The aggregation algorithm DIFSM is inspired by Hellwig’s method based on two reference points: ideal point (pattern) and anti-ideal point (anti-pattern), measuring distances between the alternative and ideal point and distance between the ideal and anti-ideal point. The proposed methods take into consideration the entropy-based weights of criteria. An illustrative example is given to demonstrate the practicality and effectiveness of the proposed approach. Additionally, the comparative analysis results, using the DIFSM and the Intuitionistic Fuzzy TOPSIS-based framework, are presented.

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Section: The Hellwig Methods Based On Two Reference Pointsmentioning

confidence: 99%

On Some Extension of Intuitionistic Fuzzy Synthetic Measures for Two Reference Points and Entropy Weights

Roszkowska

Jefmański

Kusterka-Jefmańska

2022

Entropy

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“…It takes no account of economic indicators. A more detailed overview of the social cohesion concept and its measurement, including the strategic priorities of cohesion policy in the European Union, can be found in Walesiak and Dehnel [15].…”

Section: An Overview Of the Social Cohesion Conceptmentioning

confidence: 99%

“…Systematic monitoring and measurement of social cohesion require the use of adequate methods and reliable statistical data. Social cohesion can be assessed on the basis of primary data (cf., e.g., [2][3][4][5][6][7][8][9][10]) or secondary data (cf., e.g., [11][12][13][14][15][16]). Primary data about social cohesion come from sample surveys, while secondary data are provided mainly by official statistics.…”

Section: Introductionmentioning

confidence: 99%

A Measurement of Social Cohesion in Poland’s NUTS2 Regions in the Period 2010–2019 by Applying Dynamic Relative Taxonomy to Interval-Valued Data

Walesiak

Dehnel

2023

Sustainability

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Composite indicators play an important role in the analysis of socio-economic phenomena. A number of different approaches to constructing composite indicators have been proposed in the literature. Depending on the degree of compensation, they can be divided into compensatory, partially compensatory, and non-compensatory. The following article focuses on the method of relative taxonomy and its dynamic modification. While this method is typically applied to metric data, the authors propose using the dynamic approach for interval-valued data, which describes objects of interest more precisely. Metric data are of an atomic nature; i.e., an observation of each variable is expressed as one real number. In contrast, each observation of an interval-valued variable is expressed as an interval. By making use of interval-valued data, it is possible to assess objects not only at the regional level but also at a lower level of territorial aggregation, taking into account spatial variation across districts that make up each region. The study described in the article was conducted by applying relative taxonomy in its dynamic approach to interval-valued data in order to measure the level of social cohesion in Poland’s NUTS2 regions during the period 2010–2019. The target dataset was obtained by aggregating numeric data about social cohesion in districts (LAU1) at the level of regions. The lower and upper limit of the interval for each region was based on district-level data and corresponded to the 2nd and 8th decile, respectively (60% of observations), which helped to mitigate the effect of outliers. By applying dynamic relative taxonomy to interval-valued data, it was possible to graphically represent changes in the level of social cohesion that took place across 17 Poland’s NUTS2 regions between 2010 and 2019. It was found that during the reference period, the level of social cohesion in the regions systematically improved. Despite the observed variation, the distance between the regions consistently decreased over time. The level of social cohesion was found to be higher in regions that had received more EU funding to support regional development.

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“…The specific aim of the study is to provide a composite interval indicator that measures both a measure that synthesizes different indicators to measure poverty and takes into account the variability of the different results due to different choices in the construction of the same composite indicator. The use of aggregate measures based on interval data can also be found in the works (Dehnel and Walesiak 2019;Walesiak and Dehnel 2020).…”

Section: Introduction: Measuring Povertymentioning

confidence: 99%

The Analysis and the Measurement of Poverty: An Interval-Based Composite Indicator Approach

Drago

2021

Economies

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The study of poverty and its quantification is a critical yet unresolved problem in social science. This work seeks to use a new composite indicator to assess poverty as a multidimensional concept. However, subjective decisions, such as various weighting systems on the indicator’s creation, may affect its perception. In order to solve this issue, we propose to use random different composite indicators based on simulated weightings and specifications to get a comprehensive interval-based composite indicator. Our method generates robust and trustworthy measurements based on a meaningful conceptual model of poverty. Furthermore, we use some interval parameters such as the upper bound, center, and lower bound to compare the different intervals related to the different statistical units and rankings to aid in analyzing extreme situations and policy scenarios. In Sicily, Calabria, Campania, and Puglia, we identify urgent circumstances. The findings reveal a consistent indicator measurement and the shadow sector’s influence on the final measurements.

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The Measurement of Social Cohesion at Province Level in Poland Using Metric and Interval-Valued Data

Cited by 8 publications

References 36 publications

On Some Extension of Intuitionistic Fuzzy Synthetic Measures for Two Reference Points and Entropy Weights

On Some Extension of Intuitionistic Fuzzy Synthetic Measures for Two Reference Points and Entropy Weights

A Measurement of Social Cohesion in Poland’s NUTS2 Regions in the Period 2010–2019 by Applying Dynamic Relative Taxonomy to Interval-Valued Data

The Analysis and the Measurement of Poverty: An Interval-Based Composite Indicator Approach

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