IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0249583.html
   My bibliography  Save this article

Innovation indicators based on firm websites—Which website characteristics predict firm-level innovation activity?

Author

Listed:
  • Janna Axenbeck
  • Patrick Breithaupt

Abstract

Web-based innovation indicators may provide new insights into firm-level innovation activities. However, little is known yet about the accuracy and relevance of web-based information for measuring innovation. In this study, we use data on 4,487 firms from the Mannheim Innovation Panel (MIP) 2019, the German contribution to the European Community Innovation Survey (CIS), to analyze which website characteristics perform as predictors of innovation activity at the firm level. Website characteristics are measured by several data mining methods and are used as features in different Random Forest classification models that are compared against each other. Our results show that the most relevant website characteristics are textual content, the use of English language, the number of subpages and the amount of characters on a website. In our main analysis, models using all website characteristics jointly yield AUC values of up to 0.75 and increase accuracy scores by up to 18 percentage points compared to a baseline prediction based on the sample mean. Moreover, predictions with website characteristics significantly differ from baseline predictions according to a McNemar test. Results also indicate a better performance for the prediction of product innovators and firms with innovation expenditures than for the prediction of process innovators.

Suggested Citation

  • Janna Axenbeck & Patrick Breithaupt, 2021. "Innovation indicators based on firm websites—Which website characteristics predict firm-level innovation activity?," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-23, April.
    • Handle: RePEc:plo:pone00:0249583
    DOI: 10.1371/journal.pone.0249583
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0249583
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0249583&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0249583?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Crepon, B. & Duguet, E. & Mairesse, J., 1998. "Research Investment, Innovation and Productivity: An Econometric Analysis at the Firm Level," Papiers d'Economie Mathématique et Applications 98.15, Université Panthéon-Sorbonne (Paris 1).
    2. Kinne, Jan & Lenz, David, 2019. "Predicting innovative firms using web mining and deep learning," ZEW Discussion Papers 19-001, ZEW - Leibniz Centre for European Economic Research.
    3. Bryan Kelly & Dimitris Papanikolaou & Amit Seru & Matt Taddy, 2021. "Measuring Technological Innovation over the Long Run," American Economic Review: Insights, American Economic Association, vol. 3(3), pages 303-320, September.
    4. Bertschek, Irene & Kesler, Reinhold, 2022. "Let the user speak: Is feedback on Facebook a source of firms’ innovation?," Information Economics and Policy, Elsevier, vol. 60(C).
    5. Bronwyn H. Hall & Adam Jaffe & Manuel Trajtenberg, 2005. "Market Value and Patent Citations," RAND Journal of Economics, The RAND Corporation, vol. 36(1), pages 16-38, Spring.
    6. Becker, Wolfgang & Dietz, Jurgen, 2004. "R&D cooperation and innovation activities of firms--evidence for the German manufacturing industry," Research Policy, Elsevier, vol. 33(2), pages 209-223, March.
    7. David Lenz & Peter Winker, 2020. "Measuring the diffusion of innovations with paragraph vector topic models," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-18, January.
    8. Rachel Griffith & Elena Huergo & Jacques Mairesse & Bettina Peters, 2006. "Innovation and Productivity Across Four European Countries," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 22(4), pages 483-498, Winter.
    9. Quinn McNemar, 1947. "Note on the sampling error of the difference between correlated proportions or percentages," Psychometrika, Springer;The Psychometric Society, vol. 12(2), pages 153-157, June.
    10. 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.
    11. Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
    12. Sanjay K. Arora & Jan Youtie & Philip Shapira & Lidan Gao & TingTing Ma, 2013. "Entry strategies in an emerging technology: a pilot web-based study of graphene firms," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(3), pages 1189-1207, June.
    13. Frenz, Marion & Ietto-Gillies, Grazia, 2009. "The impact on innovation performance of different sources of knowledge: Evidence from the UK Community Innovation Survey," Research Policy, Elsevier, vol. 38(7), pages 1125-1135, September.
    14. Fred Gault (ed.), 2013. "Handbook of Innovation Indicators and Measurement," Books, Edward Elgar Publishing, number 14427.
    15. J Sylvan Katz & Viv Cothey, 2006. "Web indicators for complex innovation systems," Research Evaluation, Oxford University Press, vol. 15(2), pages 85-95, August.
    16. Bruno Crepon & Emmanuel Duguet & Jacques Mairesse, 1998. "Research, Innovation And Productivity: An Econometric Analysis At The Firm Level," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 7(2), pages 115-158.
    17. Jeremy Ginsberg & Matthew H. Mohebbi & Rajan S. Patel & Lynnette Brammer & Mark S. Smolinski & Larry Brilliant, 2009. "Detecting influenza epidemics using search engine query data," Nature, Nature, vol. 457(7232), pages 1012-1014, February.
    18. Bersch, Johannes & Gottschalk, Sandra & Müller, Bettina & Niefert, Michaela, 2014. "The Mannheim Enterprise Panel (MUP) and firm statistics for Germany," ZEW Discussion Papers 14-104, ZEW - Leibniz Centre for European Economic Research.
    19. Belderbos, Rene & Carree, Martin & Lokshin, Boris, 2004. "Cooperative R&D and firm performance," Research Policy, Elsevier, vol. 33(10), pages 1477-1492, December.
    20. Matthew Gentzkow & Bryan Kelly & Matt Taddy, 2019. "Text as Data," Journal of Economic Literature, American Economic Association, vol. 57(3), pages 535-574, September.
    21. Abdullah Gök & Alec Waterworth & Philip Shapira, 2015. "Use of web mining in studying innovation," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 653-671, January.
    22. Max Nathan & Anna Rosso, 2017. "Innovative events," Development Working Papers 429, Centro Studi Luca d'Agliano, University of Milano, revised 08 Apr 2019.
    23. Stefan Lachenmaier & Ludger Wößmann, 2006. "Does innovation cause exports? Evidence from exogenous innovation impulses and obstacles using German micro data," Oxford Economic Papers, Oxford University Press, vol. 58(2), pages 317-350, April.
    24. Bronwyn H. Hall & Francesca Lotti & Jacques Mairesse, 2013. "Evidence on the impact of R&D and ICT investments on innovation and productivity in Italian firms," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 22(3), pages 300-328, April.
    25. Katz, J. Sylvan, 2006. "Indicators for complex innovation systems," Research Policy, Elsevier, vol. 35(7), pages 893-909, September.
    26. M. Kirbach & C. Schmiedeberg, 2008. "Innovation And Export Performance: Adjustment And Remaining Differences In East And West German Manufacturing," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 17(5), pages 435-457.
    27. Luuk Klomp & George Van Leeuwen, 2001. "Linking Innovation and Firm Performance: A New Approach," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 8(3), pages 343-364.
    28. Kinne, Jan & Axenbeck, Janna, 2018. "Web mining of firm websites: A framework for web scraping and a pilot study for Germany," ZEW Discussion Papers 18-033, ZEW - Leibniz Centre for European Economic Research.
    29. Arundel, Anthony & Kabla, Isabelle, 1998. "What percentage of innovations are patented? empirical estimates for European firms," Research Policy, Elsevier, vol. 27(2), pages 127-141, June.
    30. Belderbos, Rene & Carree, Martin & Lokshin, Boris, 2004. "Cooperative R&D and firm performance," Research Policy, Elsevier, vol. 33(10), pages 1477-1492, December.
    31. Ilaria Gandin & Claudio Cozza, 2019. "Can we predict firms’ innovativeness? The identification of innovation performers in an Italian region through a supervised learning approach," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-16, June.
    32. Bruno Cassiman & Elena Golovko, 2011. "Innovation and internationalization through exports," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 42(1), pages 56-75, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Abbasiharofteh, Milad & Kinne, Jan & Krüger, Miriam, 2021. "The strength of weak and strong ties in bridging geographic and cognitive distances," ZEW Discussion Papers 21-049, ZEW - Leibniz Centre for European Economic Research.
    2. Axenbeck, Janna & Breithaupt, Patrick, 2022. "Measuring the digitalisation of firms: A novel text mining approach," ZEW Discussion Papers 22-065, ZEW - Leibniz Centre for European Economic Research.
    3. Cruciata, Pietro & Pulizzotto, Davide & Beaudry, Catherine, 2024. "First impressions on sustainable innovation matter: Using NLP to replicate B-lab environmental index by analyzing companies' homepages," Technological Forecasting and Social Change, Elsevier, vol. 205(C).
    4. Breithaupt, Patrick & Hottenrott, Hanna & Rammer, Christian & Römer, Konstantin, 2023. "Mapping employee mobility and employer networks using professional network data," ZEW Discussion Papers 23-041, ZEW - Leibniz Centre for European Economic Research.
    5. Bottai, Carlo & Crosato, Lisa & Domenech, Josep & Guerzoni, Marco & Liberati, Caterina, 2024. "Scraping innovativeness from corporate websites: Empirical evidence on Italian manufacturing SMEs," Technological Forecasting and Social Change, Elsevier, vol. 207(C).
    6. Davide Lanfranchi & Laura Grassi, 2022. "Examining insurance companies’ use of technology for innovation," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 47(3), pages 520-537, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Axenbeck, Janna & Breithaupt, Patrick, 2019. "Web-based innovation indicators: Which firm website characteristics relate to firm-level innovation activity?," ZEW Discussion Papers 19-063, ZEW - Leibniz Centre for European Economic Research.
    2. Max Nathan & Anna Rosso, 2017. "Innovative events," Development Working Papers 429, Centro Studi Luca d'Agliano, University of Milano, revised 08 Apr 2019.
    3. Breithaupt, Patrick & Kesler, Reinhold & Niebel, Thomas & Rammer, Christian, 2020. "Intangible capital indicators based on web scraping of social media," ZEW Discussion Papers 20-046, ZEW - Leibniz Centre for European Economic Research.
    4. Nathan, Max & Rosso, Anna, 2022. "Innovative events: product launches, innovation and firm performance," Research Policy, Elsevier, vol. 51(1).
    5. Rammer, Christian & Es-Sadki, Nordine, 2023. "Using big data for generating firm-level innovation indicators - a literature review," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    6. Mairesse, Jacques & Mohnen, Pierre, 2010. "Using Innovation Surveys for Econometric Analysis," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 2, chapter 0, pages 1129-1155, Elsevier.
    7. Dziallas, Marisa & Blind, Knut, 2019. "Innovation indicators throughout the innovation process: An extensive literature analysis," Technovation, Elsevier, vol. 80, pages 3-29.
    8. Hall, B.H., 2011. "Innovation and productivity," MERIT Working Papers 2011-028, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    9. Mohnen, Pierre, 2019. "R&D, innovation and productivity," MERIT Working Papers 2019-016, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    10. Baumann, Julian & Kritikos, Alexander S., 2016. "The link between R&D, innovation and productivity: Are micro firms different?," Research Policy, Elsevier, vol. 45(6), pages 1263-1274.
    11. Eric J. Bartelsman & Martin Falk & Eva Hagsten & Michael Polder, 2019. "Productivity, technological innovations and broadband connectivity: firm-level evidence for ten European countries," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 9(1), pages 25-48, March.
    12. Abbasiharofteh, Milad & Kinne, Jan & Krüger, Miriam, 2021. "The strength of weak and strong ties in bridging geographic and cognitive distances," ZEW Discussion Papers 21-049, ZEW - Leibniz Centre for European Economic Research.
    13. Scandura, Alessandra, 2016. "University–industry collaboration and firms’ R&D effort," Research Policy, Elsevier, vol. 45(9), pages 1907-1922.
    14. Aronica, Martina & Fazio, Giorgio & Piacentino, Davide, 2022. "A micro-founded approach to regional innovation in Italy," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    15. Robin, Stéphane & Schubert, Torben, 2013. "Cooperation with public research institutions and success in innovation: Evidence from France and Germany," Research Policy, Elsevier, vol. 42(1), pages 149-166.
    16. Colombelli, Alessandra & Belitski, Maksim & D’Amico, Elettra, 2023. "Artificial Intelligence and Firm Innovation: The Resource-Allocation Perspective," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202316, University of Turin.
    17. Enrique López-Bazo & Elisabet Motellón, 2013. "“Firm exports, innovation, … and regions”," AQR Working Papers 201305, University of Barcelona, Regional Quantitative Analysis Group, revised May 2013.
    18. Xianzhong Cao & Bo Chen & Yuefang Si & Senlin Hu & Gang Zeng, 2021. "Spatio-temporal evolution and mechanism of regional innovation efficiency: Evidence from Yangtze River Delta Urban Agglomeration of China," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-13, July.
    19. Graciela Corral De Zubielqui & Janice Jones & Laurence Lester, 2017. "KNOWLEDGE INFLOWS FROM MARKET- AND SCIENCE-BASED ACTORS, ABSORPTIVE CAPACITY, INNOVATION AND PERFORMANCE: A STUDY OF SMEs," World Scientific Book Chapters, in: Joe Tidd (ed.), Promoting Innovation in New Ventures and Small- and Medium-Sized Enterprises, chapter 15, pages 359-391, World Scientific Publishing Co. Pte. Ltd..
    20. James Foreman-Peck, 2013. "Effectiveness and efficiency of SME innovation policy," Small Business Economics, Springer, vol. 41(1), pages 55-70, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0249583. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.