Perceived accessibility matters: Unveiling key urban parameters through traditional and technology-driven participation methods

The demand for innovative solutions to address urban complexities, with accessibility being crucial for sustainable environments, is growing globally. As demographic shifts and disability prevalence evolve, understanding spatial dynamics affecting accessibility becomes urgent. The research hypothesis suggests that investigating both physical and perceived accessibility realms reveals critical insights into challenges individuals face in public spaces. This study explores public participation methods of different nature to evaluate their effectiveness and complementarity in portraying perceived accessibility in urban spaces. A multi-method approach, integrating participant observation tools like self-completion questionnaires and semi-structured interviews with non-participant technology-driven data sources like Foursquare, Twitter, and Google Places, was employed. The analysis focused on two areas in Alicante, Spain. Findings emerge in four phases: (1) identifying perceived accessible public spaces via questionnaires, (2) discerning influential parameters from interviews, (3) conducting a comprehensive analysis incorporating quantitative and qualitative methods, and (4) establishing correlations between parameters gathered through the methods. The results underscore the importance of diverse public participation methods in urban planning, offering a comprehensive framework for future research to improve accessibility and inclusivity in urban environments. Understanding the relationship between physical urban features and citizens' perceptions advocates targeted interventions for improved accessibility and socially inclusive environments. • Traditional and tech-driven methods are used for assessing perceived accessibility. • Critical parameters that impact perceived accessibility are identified. • Familiarity, presence and mixed uses are key for perceived accessibility. • Perceived accessibility parameters are assessed through social media data.