What Makes Innovation Inclusive? Identifying and Categorizing the Components by Categorical Principal Component Analysis (CATPCA)

Inclusive innovation is a promising concept aimed at reducing poverty and inequality by integrating the poor and marginalised into the development process through the use of technology. However, its conceptualisation remains ambiguous due to limited empirical research and its multidimensional nature, which often involves nominal and ordinal data. To address this, our study employed Categorical Principal Component Analysis (CATPCA) to identify the core components of inclusive innovation using 40 potential indicators. Unlike conventional Principal Component Analysis (PCA), CATPCA accommodates mixed-scale data and allows specification of measurement levels, thereby producing higher variance explanation. After eliminating 11 indicators with low variance accounted for (below 0.25), CATPCA grouped the remaining 29 variables into seven key components of inclusive innovation: significant outreach, higher income, inclusive quality service, affordable access, livelihood opportunities, marginalized population and better competition. These components represent critical dimensions of how inclusive innovation functions in practice. Confirmatory Factor Analysis (CFA) was conducted to assess the reliability and validity of the identified components, thereby confirming the proposed structure. The CFA results confirmed substantial factor loadings, strong composite reliability and acceptable convergent and discriminant validity. These findings confirm the robustness of the seven identified components in capturing the multidimensional nature of inclusive innovation.