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Using machine learning and 10‐K filings to measure innovation

Author

Listed:
  • Essi Nousiainen
  • Mikko Ranta
  • Mika Ylinen
  • Marko Järvenpää

Abstract

The purpose of this paper is to develop and validate a text‐based measure of innovation using latent Dirichlet allocation on a sample of 45,409 10‐K filings from US listed companies. We expect that the text‐based innovation measure is associated with innovation and can be used to measure innovation for companies without patents or significant research and development expenditures. The empirical results are consistent with these assumptions, but reveal that thorough initial testing is required to ensure robustness. This study extends the research on innovation measurement and company disclosures, and provides a new method for assessing innovation using company disclosures.

Suggested Citation

  • Essi Nousiainen & Mikko Ranta & Mika Ylinen & Marko Järvenpää, 2024. "Using machine learning and 10‐K filings to measure innovation," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(4), pages 3211-3239, December.
    • Handle: RePEc:bla:acctfi:v:64:y:2024:i:4:p:3211-3239
    DOI: 10.1111/acfi.13245
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    References listed on IDEAS

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    1. Professor Bronwyn Hall, 2013. "The importance (or not) of patents to UK firms," National Institute of Economic and Social Research (NIESR) Discussion Papers 410, National Institute of Economic and Social Research.
    2. Holmstrom, Bengt, 1989. "Agency costs and innovation," Journal of Economic Behavior & Organization, Elsevier, vol. 12(3), pages 305-327, December.
    3. Cooper, Michael & Knott, Anne Marie & Yang, Wenhao, 2022. "RQ Innovative Efficiency and Firm Value," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 57(5), pages 1649-1694, August.
    4. Yang Bao & Bin Ke & Bin Li & Y. Julia Yu & Jie Zhang, 2020. "Detecting Accounting Fraud in Publicly Traded U.S. Firms Using a Machine Learning Approach," Journal of Accounting Research, Wiley Blackwell, vol. 58(1), pages 199-235, March.
    5. Acharya, Viral & Xu, Zhaoxia, 2017. "Financial dependence and innovation: The case of public versus private firms," Journal of Financial Economics, Elsevier, vol. 124(2), pages 223-243.
    6. Leonid Kogan & Dimitris Papanikolaou & Amit Seru & Noah Stoffman, 2017. "Technological Innovation, Resource Allocation, and Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(2), pages 665-712.
    7. Yanjian Zhu & Zhaoying Wu & Hua Zhang & Jing Yu, 2017. "Media sentiment, institutional investors and probability of stock price crash: evidence from Chinese stock markets," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 57(5), pages 1635-1670, December.
    8. Dziallas, Marisa & Blind, Knut, 2019. "Innovation indicators throughout the innovation process: An extensive literature analysis," Technovation, Elsevier, vol. 80, pages 3-29.
    9. Chenhall, Robert H. & Moers, Frank, 2015. "The role of innovation in the evolution of management accounting and its integration into management control," Accounting, Organizations and Society, Elsevier, vol. 47(C), pages 1-13.
    10. Jeremy Bertomeu & Edwige Cheynel & Eric Floyd & Wenqiang Pan, 2021. "Using machine learning to detect misstatements," Review of Accounting Studies, Springer, vol. 26(2), pages 468-519, June.
    11. Anna Bedford & Le Ma & Nelson Ma & Kristina Vojvoda, 2021. "Patenting activity or innovative originality?," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(3), pages 4191-4207, September.
    12. Hirshleifer, David & Hsu, Po-Hsuan & Li, Dongmei, 2013. "Innovative efficiency and stock returns," Journal of Financial Economics, Elsevier, vol. 107(3), pages 632-654.
    13. Bronwyn H. Hall & Christian Helmers & Mark Rogers & Vania Sena, 2013. "The importance (or not) of patents to UK firms," Oxford Economic Papers, Oxford University Press, vol. 65(3), pages 603-629, July.
    14. John Donovan & Jared Jennings & Kevin Koharki & Joshua Lee, 2021. "Measuring credit risk using qualitative disclosure," Review of Accounting Studies, Springer, vol. 26(2), pages 815-863, June.
    15. Mikko Ranta & Mika Ylinen & Marko Järvenpää, 2023. "Machine Learning in Management Accounting Research: Literature Review and Pathways for the Future," European Accounting Review, Taylor & Francis Journals, vol. 32(3), pages 607-636, May.
    16. James M. Plečnik & Leo L. Yang & Joseph H. Zhang, 2022. "Corporate innovation and future earnings: does early patent disclosure matter?," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(S1), pages 2011-2056, April.
    17. Xianjun Cai & Huifeng Pan & Chengcheng Gao & Chunyang Wang & Liping Lu, 2021. "Top executive tournament incentives and corporate innovation output," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(5), pages 5893-5924, December.
    18. Peter M. Clarkson & Jordan Ponn & Gordon D. Richardson & Frank Rudzicz & Albert Tsang & Jingjing Wang, 2020. "A Textual Analysis of US Corporate Social Responsibility Reports," Abacus, Accounting Foundation, University of Sydney, vol. 56(1), pages 3-34, March.
    19. Lu, Qinli & Chesbrough, Henry, 2022. "Measuring open innovation practices through topic modelling: Revisiting their impact on firm financial performance," Technovation, Elsevier, vol. 114(C).
    20. Matthias M M Buehlmaier & Toni M Whited, 2018. "Are Financial Constraints Priced? Evidence from Textual Analysis," The Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2693-2728.
    21. Speckbacher, Gerhard & Wabnegg, Markus, 2020. "Incentivizing innovation: The role of knowledge exchange and distal search behavior," Accounting, Organizations and Society, Elsevier, vol. 86(C).
    22. Cynthia W. Cai & Martina K. Linnenluecke & Mauricio Marrone & Abhay K. Singh, 2019. "Machine Learning and Expert Judgement: Analyzing Emerging Topics in Accounting and Finance Research in the Asia–Pacific," Abacus, Accounting Foundation, University of Sydney, vol. 55(4), pages 709-733, December.
    23. Tatiana Garanina & Mikko Ranta & John Dumay, 2021. "Blockchain in accounting research: current trends and emerging topics," Accounting, Auditing & Accountability Journal, Emerald Group Publishing Limited, vol. 35(7), pages 1507-1533, October.
    24. Carly Moulang & Steven Cahan, 2015. "Performance measurement system use in generating psychological empowerment and individual creativity," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 55(2), pages 519-544, June.
    25. Stewart Jones & Nurul Alam, 2019. "A machine learning analysis of citation impact among selected Pacific Basin journals," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 59(4), pages 2509-2552, December.
    26. Zheyuan Zhang & Huiying Wu & Sammy Xiaoyan Ying & Jiaxing You, 2023. "Corporate Innovation and Disclosure Strategy," Abacus, Accounting Foundation, University of Sydney, vol. 59(1), pages 76-133, March.
    27. Xiangxi Tang & Jing Shi & Jianlei Han & Ao Shu & Fulong Xiao, 2021. "Culturally diverse board and corporate innovation," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(4), pages 5655-5679, December.
    28. Bedford, David S. & Bisbe, Josep & Sweeney, Breda, 2019. "Performance measurement systems as generators of cognitive conflict in ambidextrous firms," Accounting, Organizations and Society, Elsevier, vol. 72(C), pages 21-37.
    29. Henri, Jean-François & Wouters, Marc, 2020. "Interdependence of management control practices for product innovation: The influence of environmental unpredictability," Accounting, Organizations and Society, Elsevier, vol. 86(C).
    30. Josep Bisbe & Ricardo Malagueno, 2009. "The Choice of Interactive Control Systems under Different Innovation Management Modes," European Accounting Review, Taylor & Francis Journals, vol. 18(2), pages 371-405.
    31. Mukherjee, Abhiroop & Singh, Manpreet & Žaldokas, Alminas, 2017. "Do corporate taxes hinder innovation?," Journal of Financial Economics, Elsevier, vol. 124(1), pages 195-221.
    32. Nerissa C. Brown & Richard M. Crowley & W. Brooke Elliott, 2020. "What Are You Saying? Using topic to Detect Financial Misreporting," Journal of Accounting Research, Wiley Blackwell, vol. 58(1), pages 237-291, March.
    33. Kexing Ding & Baruch Lev & Xuan Peng & Ting Sun & Miklos A. Vasarhelyi, 2020. "Machine learning improves accounting estimates: evidence from insurance payments," Review of Accounting Studies, Springer, vol. 25(3), pages 1098-1134, September.
    34. Axel R. Helling & Benjamin Maury & Eva Liljeblom, 2020. "Exit as governance: do blockholders affect corporate innovation in large US firms?," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(2), pages 1703-1725, June.
    35. Craig Lewis & Steven Young, 2019. "Fad or future? Automated analysis of financial text and its implications for corporate reporting," Accounting and Business Research, Taylor & Francis Journals, vol. 49(5), pages 587-615, July.
    36. Bing Guo & Evita Paraskevopoulou & Luis Santamaría Sánchez, 2019. "Disentangling the Role of Management Control Systems for Product and Process Innovation in Different Contexts," European Accounting Review, Taylor & Francis Journals, vol. 28(4), pages 681-712, August.
    37. Müller-Stewens, Benedikt & Widener, Sally K. & Möller, Klaus & Steinmann, Jan-Christoph, 2020. "The role of diagnostic and interactive control uses in innovation," Accounting, Organizations and Society, Elsevier, vol. 80(C).
    38. Hedy Jiaying Huang & Ahsan Habib & Sophia Li Sun & Ying Liu & Huiting Guo, 2021. "Financial reporting and corporate innovation: a review of the international literature," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(4), pages 5439-5499, December.
    39. Guilherme Belloque & Martina K Linnenluecke & Mauricio Marrone & Abhay K Singh & Rui Xue, 2021. "55 years of Abacus: Evolution of Research Streams and Future Research Directions," Abacus, Accounting Foundation, University of Sydney, vol. 57(3), pages 593-618, September.
    40. Ahmed, Shaker & Ranta, Mikko & Vähämaa, Emilia & Vähämaa, Sami, 2023. "Facial attractiveness and CEO compensation: Evidence from the banking industry," Journal of Economics and Business, Elsevier, vol. 123(C).
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