Exploratory Analysis of Urban Sustainability by Applying a Strategy-Based Tailor-Made Weighting Method

Abstract

The Hungarian cities are rarely analyzed in current urban studies, especially in terms of urban sustainability. The present study aimed at analyzing the Hungarian county seats by comparing them through economic, social, and environmental indicators, which cover a broad spectrum of urban sustainability by applying independent indicators. Altogether 30 variables have been involved from 2014 and 2018–2019 to reveal the regional pattern of urban sustainability among the Hungarian county seats by applying the strategy-based tailor-made (SBTM) weighting methodology. It takes into consideration the different emphases regarding local aspects and main issues of sustainability through the analysis of integrated settlement development strategies, which is a unique method compared to current approaches. After the evaluation of the results, it can be stated that the east–west axis was revealed regarding weighted and unweighted sustainability indices; furthermore, a highly heterogeneous spatial trend can be drawn with regard to the relative changes in urban sustainability performance without clearly defined regional clusters. This analysis can fill the current literature gap by analyzing the Hungarian context and elaborating an easy-to-use weighting methodology based on the cities’ development strategies which contribute to improving the variety of planning and decision-making tools in the field of urban development.

A systematic literature review: Setting a basis for smart and sustainable city performance measurement

“…Most studies adopted an expert‐led approach, where meetings, panels, or workshops were organized, and surveys were conducted. In this context, the Delphi method (Chan & Lee, 2019; Liu et al, 2018; Mohsin et al, 2020; Wey & Peng, 2021), brainstorming (Caldatto et al, 2021) and cognitive maps (Caldatto et al, 2021; Fernandes et al, 2018) are among the decision‐making techniques that were used for this purpose; and Principal Component Analysis (Lombardi et al, 2012; Manitiu & Pedrini, 2016; Shmelev & Shmeleva, 2018), Correlation Analysis (Buzási & Jäger, 2021) and Inter‐relationship Analysis (Jiao et al, 2018) are among the statistical methods that were used. Additionally, the DPSIR Framework (Driver‐Pressure‐State‐Impact‐Response Framework) developed by the European Commission was used for determining environmental, social, and cultural indicators to assess the sustainability and smartness of cities (Manitiu & Pedrini, 2016; Xue et al, 2021), and the MobiSim Simulation Tool (Hély & Antoni, 2019) was used for geographical analysis to support sustainable planning.…”

“…In this context, the Delphi method (Chan & Lee, 2019;Liu et al, 2018;Mohsin et al, 2020;Wey & Peng, 2021), brainstorming (Caldatto et al, 2021) and cognitive maps (Caldatto et al, 2021;Fernandes et al, 2018) are among the decision-making techniques that were used for this purpose; and Principal Component Analysis (Lombardi et al, 2012;Manitiu & Pedrini, 2016;Shmelev & Shmeleva, 2018), Correlation Analysis (Buzási & Jäger, 2021) and…”

Assessing the Level of Urban Sustainability in the Capital of Pakistan: A Social Analysis Applied through Multiple Linear Regression

“…Ground truthing is a suitable way to understand the social issues of any area. Different researchers use multiple dependent and independent indicators in social sciences to examine urban sustainability in urban areas around the world [44,45]. Therefore, these indicators vary from area to area and from region to region based on their geographical requirements and needs.…”

Research on multi-objective optimization of energy power system under low carbon constraints

“…From the perspective of controlling CO2 emissions, to achieve the coordinated development of energy, economy and society, we need a reasonable allocation of energy. Therefore, the problem to be studied is a continuous decision-making problem, and a weighted algorithm is adopted [9][10].…”