Diagnosing coverage gaps in assessment tools for inclusive public environments: a multi-level performance analysis

Purpose This study evaluates the robustness and coverage performance of existing assessment tools used to measure inclusive public environments (IPEs). Specifically, it examines the extent to which current tools capture the multidimensional attributes of inclusivity in public buildings and places in terms of indicators used, breadth of coverage, and depth of measurement and their capabilities to assess IPEs. Design/methodology/approach A systematic literature review identified 16 indicator-based Inclusive Public Environment assessment tools, comprising 10 research-based tools and six operational, real-life tools. Structured content analysis was used to extract 574 indicators, of which 556 unique indicators. The unique extracted indictors were synthesized and organized into the comprehensive list of indicators for inclusive public environments (CLI-IPE). The framework comprises five categories and twelve subcategories grouped under two dimensions: physical and perceptual/cognitive. A multi-level coverage analysis was then conducted to evaluate comprehensiveness, representativeness, and depth of coverage of the examined tools. Findings The results reveal substantial variation in the number of indicators used across tools, ranging from 7 to 215 indicators. Indicator convergence was extremely low, with very few indicators used in more than two tools. Most tools demonstrated moderate-to-high comprehensiveness of coverage at the category level but substantially weaker representativeness at the subcategory level, indicating broad yet incomplete coverage of inclusivity attributes. The physical dimension was covered more consistently than the perceptual/cognitive dimension. Objective indicators dominated existing tools, accounting for 80.8% of all indicators, while depth of coverage varied considerably across categories and subcategories. Originality/value The study introduces the CLI-IPE framework as a structured reference model for inclusive public environment assessment and demonstrates the value of multi-level coverage analysis as a systematic approach for evaluating the validity, robustness and completeness of indicator-based assessment tools.