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

Mikaël Héroux-Vaillancourt, Catherine Beaudry et Constant Rietsch

Article de revue (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.

Mots clés

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

Renseignements supplémentaires: Canada Research Chair on the Creation, Development and Commercialization of Innovation
Sujet(s): 2950 Mathématiques appliquées > 2950 Mathématiques appliquées
2950 Mathématiques appliquées > 2959 Mathématiques des télécommunications
Département: Département de mathématiques et de génie industriel
Centre de recherche: Autre
Organismes subventionnaires: Social Sciences and Humanities Research Council, Canada Research Chair program
Numéro de subvention: 435-2013-1220, 895-2018-1006
URL de PolyPublie: https://publications.polymtl.ca/48758/
Titre de la revue: Quantitative Science Studies (vol. 1, no 4)
Maison d'édition: MIT Press
DOI: 10.1162/qss_a_00086
URL officielle: https://doi.org/10.1162/qss_a_00086
Date du dépôt: 18 avr. 2023 15:00
Dernière modification: 23 nov. 2024 07:59
Citer en 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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