The world’s population continues to grow at an unprecedented rate, with urban areas experiencing a more rapid rise in population density than rural regions. This demographic shift compels decision-makers to address pressing urban challenges and rethink future structures of cities. However, a vision for global sustainable urban growth remains elusive, as planners often lack comprehensive, credible and dynamic models to guide decision-making. The main purpose of this study is to propose a process-oriented methodology that integrates cognitive mapping, interpretive structural modeling (ISM) and a matrice d’impacts croisés multiplication appliquée à un classement (MICMAC) analysis to evaluate and prioritize key determinants of urban development. Group work sessions involving decision-makers from diverse fields were conducted to identify critical variables influencing urban development. Unlike traditional models, the proposed approach emphasizes participatory decision-making. By combining cognitive mapping and ISM-MICMAC, this study enables the identification of causal relationships among variables and allows decision-makers to anticipate trends and prioritize challenges effectively. The findings were further validated by an external expert to ensure neutrality and reliability. Overall, this study provides a theoretical contribution to decision-making methodologies while offering a practical framework for urban planners to influence cities toward a sustainable future.

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Cognitive mapping,Decision making,Interpretive Structural Modeling (ISM),Matrice d’Impacts Croisés Multiplication Appliquée à un Classement (MICMAC),Population density,Urban areas,World population

• Economics and Business - Social Sciences