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Using web content analysis to create innovation indicators—What do we really measure?

Mikaël Héroux-Vaillancourt, Catherine Beaudry and Constant Rietsch

Article (2020)

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Abstract

This study explores the use of web content analysis to build innovation indicators from the complete texts of 79 corporate websites of Canadian nanotechnology and advanced materials firms. Indicators of four core concepts (R&D, IP protection, collaboration, and external financing) of the innovation process were built using keywords frequency analysis. These web-based indicators were validated using several indicators built from a classic questionnaire-based survey with the following methods: correlation analysis, multitraits multimethods (MTMM) matrices, and confirmatory factor analysis (CFA). The results suggest that formative indices built with the questionnaire and web-based indicators measure the same concept, which is not the case when considering the items from the questionnaire separately. Web-based indicators can act either as complements to direct measures or as substitutes for broader measures, notably the importance of R&D and the importance of IP protection, which are normally measured using conventional methods, such as government administrative data or questionnaire-based surveys.

Uncontrolled Keywords

construct validity; innovation measurement; multitraits multimethods; web content analysis; web-mining; word frequency analysis

Additional Information: Canada Research Chair on the Creation, Development and Commercialization of Innovation
Subjects: 2950 Applied mathematics > 2950 Applied mathematics
2950 Applied mathematics > 2959 Mathematics of communications
Department: Department of Mathematics and Industrial Engineering
Research Center: Other
Funders: Social Sciences and Humanities Research Council, Canada Research Chair program
Grant number: 435-2013-1220, 895-2018-1006
PolyPublie URL: https://publications.polymtl.ca/48758/
Journal Title: Quantitative Science Studies (vol. 1, no. 4)
Publisher: MIT Press
DOI: 10.1162/qss_a_00086
Official URL: https://doi.org/10.1162/qss_a_00086
Date Deposited: 18 Apr 2023 15:00
Last Modified: 23 Nov 2024 07:59
Cite in APA 7: Héroux-Vaillancourt, M., Beaudry, C., & Rietsch, C. (2020). Using web content analysis to create innovation indicators—What do we really measure? Quantitative Science Studies, 1(4), 1601-1637. https://doi.org/10.1162/qss_a_00086

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