Navigating stakeholder engagement for inclusive urban planning: Introducing the Generative Method Recommender Model

The integration of a diverse array of stakeholders is essential to ensure sustainable and inclusive development of cities that aligns with community needs while supporting social cohesion and decision-making legitimacy. Although existing literature on urban planning offers valuable insights into the ways of stakeholder engagement, yet a systematic approach to selecting the most suitable method of stakeholder engagement remains absent. This study introduces the Generative Method Recommender Model (GMRM) to satisfy this need. Through a combination of Multi-Criteria Decision-Making and Bayesian Belief Network techniques, GMRM provides a tailored method-selection paradigm that considers contextual specifications for stakeholder engagement. This model transcends traditional boundaries by illuminating the relationships between practical principles of stakeholder engagement and offering conditional recommendations, enabling urban planners and practitioners to make well-informed choices of methods for engagement realization, even in the face of uncertainties. The model's reliability is validated through sensitivity analysis, establishing GMRM as a solution to navigate the intricate landscape of method selection, fostering inclusive urban development and sustainability.