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February 3, 2026Scientometrics1 citations

Measuring innovation—a composite index of innovation volume at firm level

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ASAman Preet SinghThapar Institute of Engineering & TechnologySGSonia GargThapar Institute of Engineering & Technology

Key Points

  • To create a composite index for measuring innovation volume at the firm level.
  • Developed a conceptual framework from literature on innovation measurement and models.
  • Identified eight basic indicators across input, throughput, and output stages of innovation.
  • Validated the index using sensitivity analysis and longitudinal studies on US firms.
  • Composite index positively impacts abnormal stock returns in a longitudinal study.
  • Sensitivity analysis shows the index's robustness across various aggregation, normalization, and weighting methods.

Abstract

A composite index measuring the volume of innovation outcomes is constructed at firm level suitable for both external and internal stakeholders. The theoretical framework underlying this index was identified after an extensive review of the innovation measurement, the innovation model, and the innovation index literatures identified across four decades. Findings reveal that, for measurement of innovation volume, innovation is most appropriately considered a conversion process consisting of three stages – inputs, throughputs, and outputs. The framework was identified to be a formative model and operationalized using eight basic indicators. These indicators are counts of patent applications and organizational innovations at the input stage, counts of process innovations and organizational innovations at the throughput stage, counts of marketing, product, and organizational innovations at the output stage, and a count of firm-wide organizational innovations that cut across the three stages. The indicators were combined appropriately (in a six-step process) into a composite index measuring the volume of innovation outcomes. This composite index was validated utilizing three techniques including sensitivity analysis and external validation. External validation was accomplished after the composite index was shown to positively impact abnormal stock returns in a longitudinal study on US firms comprising ten-year panel data. Sensitivity analysis revealed that the composite index is robust to choice of aggregation, normalization, and weighting methods. In its applications, this index is suitable for both external and internal stakeholders of the firm.

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Cite This Study

Singh et al. (2026) studied this question.

synapsesocial.com/papers/6981456cf607237d8b54d463https://doi.org/10.1007/s11192-026-05555-8
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