The main objective of this study is to challenge the assumption of structural invariance in innovation measurement by examining whether established models, traditionally designed for manufacturing, are valid for the service sector. To achieve this, a large, harmonized dataset was constructed by merging microdata from the Brazilian Innovation Survey (PINTEC) with the Annual Industrial (PIA) and Annual Services (PAS) surveys for the 2012–2014 period. The final sample comprises 11,876 firms (10,034 from manufacturing and 1,842 from services). Using covariance-based structural equation modeling (CB-SEM), the relationship between multidimensional innovative capacity and financial performance was tested. The findings reveal a stark structural divergence: while the measurement model is statistically robust for manufacturing, showing a positive association between innovation and financial returns, it proves invalid for the service sector, where it fails to meet minimum reliability criteria. These results provide a rigorous empirical demonstration of a theoretical boundary, alerting scholars and managers against the application of ill-suited, manufacturing-centric metrics to services. The study concludes by discussing the implications for measurement theory and the limitations imposed by the cross-sectional design and administrative data constraints.
Taques et al. (2026) studied this question.