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A Text-Based Analysis of Corporate Innovation

Author

Listed:
  • Gustaf Bellstam

    (Facebook, Seattle, Washington 98109)

  • Sanjai Bhagat

    (Leeds School of Business, University of Colorado, Boulder, Colorado 80309)

  • J. Anthony Cookson

    (Leeds School of Business, University of Colorado, Boulder, Colorado 80309)

Abstract

We develop a new measure of innovation using the text of analyst reports of S&P 500 firms. Our text-based measure gives a useful description of innovation by firms with and without patenting and R&D (research and development). For nonpatenting firms, the measure identifies innovative firms that adopt novel technologies and innovative business practices (e.g., Walmart’s cross-geography logistics). For patenting firms, the text-based measure strongly correlates with valuable patents, which likely capture true innovation. The text-based measure robustly forecasts greater firm performance and growth opportunities for up to four years, and these value implications hold just as strongly for innovative nonpatenting firms.

Suggested Citation

  • Gustaf Bellstam & Sanjai Bhagat & J. Anthony Cookson, 2021. "A Text-Based Analysis of Corporate Innovation," Management Science, INFORMS, vol. 67(7), pages 4004-4031, July.
    • Handle: RePEc:inm:ormnsc:v:67:y:2021:i:7:p:4004-4031
    DOI: 10.1287/mnsc.2020.3682
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    References listed on IDEAS

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    3. Yi Yang & Kunpeng Zhang & Yangyang Fan, 2023. "sDTM: A Supervised Bayesian Deep Topic Model for Text Analytics," Information Systems Research, INFORMS, vol. 34(1), pages 137-156, March.
    4. Xue Wen Tan & Stanley Kok, 2024. "Explainable Risk Classification in Financial Reports," Papers 2405.01881, arXiv.org, revised May 2024.
    5. Fengler, Matthias & Phan, Minh Tri, 2023. "A Topic Model for 10-K Management Disclosures," Economics Working Paper Series 2307, University of St. Gallen, School of Economics and Political Science.
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