Smart Cities in Brand Management and Smart Cities Ranking of Turkish Metropolitan Municipalities

Abstract

Purpose – The aim of this study is to develop a smart city index system using different decision support models and various objective criteria weighting methods, and to implement it in 30 metropolitan cities in Turkey. Design/methodology/approach – To demonstrate the impact of different decision support models, a comparative analysis was conducted by combining Gray Relational Analysis, TOPSIS, and Principal Component Analysis methodologies with CRITIC, Entropy, equal weight, and standard deviation criteria weighting methods. The index consists of 88 indicators across 7 sub-dimensions. A total of 9 rankings were created, including 8 separate rankings and one KASO (cumulative arithmetic ranking average), in order to minimize the influence of a single method on the ranking results. Findings – The analysis revealed that, while there are similarities in the rankings, there can also be significant differences. However, in all rankings, Istanbul consistently holds the first position. The cities that appear in the top 5 and bottom 5 vary across different methods, exhibiting both similarities and differences. The best-performing cities are predominantly the most densely populated metropolitan areas. Discussion – In this study, much of the data was derived from municipal reports. There is a notable lack of detailed indicators and data characterizing living conditions and quality of life in urban areas in our country. In this context, developing publicly accessible data is crucial and necessary for our country. Future studies should focus on investigating the impact of different methods and indicators on the results.