Alin-Cristian Maricuț

Bucharest University of Economic Studies, Bucharest, Romania

E-mail: alin.maricut@csie.ase.ro

ORCID 0000-0003-4599-1517

Transitioning to green cities: Analyzing European urban development models for sustainable growth

Diana Timiș

Bucharest University of Economic Studies, Bucharest, Romania

E-mail: diana.timis10@gmail.com

ORCID 0000-0002-5097-6007

Silvia Parusheva

University of Economics - Varna,

Varna, Bulgaria

E-mail: parusheva@ue-varna.bg

ORCID 0000-0002-7050-3514

Slaveya Zhelyazkova

University of Economics - Varna,

Varna, Bulgaria

E-mail: sjeliazkova@ue-varna.bg

ORCID 0000-0002-8133-9684

Giani Grădinaru

Bucharest University of Economic Studies, Bucharest, Romania

E-mail: giani.gradinaru@csie.ase.ro

ORCID 0000-0003-3336-1737

Zoltán Nagy

John von Neumann University,

Kecskemét, Hungary

E-mail: nagy.zoltan@nje.hu

ORCID 0009-0000-0757-1381

Abstract. The transition to green energy and sustainable urban planning, guided by EU policies and local community perceptions, has positioned the concept of the “green city” as a key topic in both academic and practical discourse. This study provides an in-depth analysis of the current understanding of green cities, while also identifying cities structurally prepared for this transition. The literature review highlights the significance of the green city concept, the strategic directions of the EU, and the perspectives of residents regarding what constitutes a green city. The research outlines two primary objectives: (1) identifying urban development models within a selected sample of cities, and (2) determining cities or groups of cities with the potential to implement the green city concept. Using data from the Organisation for Economic Co-operation and Development (OECD) and Open Street Map, we employed spatial indicators and calculated average distances to key points of interest, using R software for analysis. Principal Component Analysis and Random Forest predictive analysis algorithm were applied to classify urban development models, facilitating the identification of cities best equipped for green city implementation. The findings offer valuable insights into sustainable urban transitions, providing a data-driven approach to guide policymakers and city planners in fostering resilient and green urban environments. This research emphasizes the importance of integrating technological tools with human-centered urban planning for a sustainable future.

Received: March, 2024

1st Revision: November, 2024

Accepted: February, 2025

DOI: 10.14254/2071-789X.2025/18-1/11

JEL Classification: C38, C80, Q50, R15

Keywords: green city concept, random forest, predictive analysis, transition, European Commission, principal component analysis