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Scraping innovativeness from corporate websites: Empirical evidence on Italian manufacturing SMEs

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  • Bottai, Carlo
  • Crosato, Lisa
  • Domenech, Josep
  • Guerzoni, Marco
  • Liberati, Caterina

Abstract

Research in innovation studies usually relies on financial statements, surveys, or patents as primary data sources, although these sources of information show some limitations when applied to Small and Medium Enterprises (SMEs). Our paper explores whether the HTML code of a company’s website is a further source to better inform innovation policies, under the assumption that how HTML is employed in crafting a corporate website provides insights into the company’s innovation capabilities. In particular, we leverage HTML tags and their associations to empirically show that the websites of innovative SMEs are different from non-innovative ones both in terms of their size and coding practices. Our findings, based on a sample of Italian companies, indicate that the features of the HTML code of corporate websites reflect unobservable characteristics related to the skills and creativity present in businesses.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:tefoso:v:207:y:2024:i:c:s0040162524003950
    DOI: 10.1016/j.techfore.2024.123597
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    1. Stefanie Haller & Iulia Siedschlag, 2011. "Determinants of ICT adoption: evidence from firm-level data," Applied Economics, Taylor & Francis Journals, vol. 43(26), pages 3775-3788.
    2. 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.
    3. Marco Guerzoni, 2010. "The impact of market size and users' sophistication on innovation: the patterns of demand," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 19(1), pages 113-126.
    4. Simon Kuznets, 1962. "Inventive Activity: Problems of Definition and Measurement," NBER Chapters, in: The Rate and Direction of Inventive Activity: Economic and Social Factors, pages 19-52, National Bureau of Economic Research, Inc.
    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. Hall, Bronwyn H. & Mairesse, Jacques & Mohnen, Pierre, 2010. "Measuring the Returns to R&D," 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 1033-1082, Elsevier.
    7. Bronwyn H. Hall, 2010. "Measuring the Returns to R&D: The Depreciation Problem," NBER Chapters, in: Contributions in Memory of Zvi Griliches, pages 341-381, National Bureau of Economic Research, Inc.
    8. Elizabeth M Daniel & Hugh N Wilson, 2003. "The role of dynamic capabilities in e-business transformation," European Journal of Information Systems, Taylor & Francis Journals, vol. 12(4), pages 282-296, December.
    9. Sanjay K. Arora & Yin Li & Jan Youtie & Philip Shapira, 2020. "Measuring dynamic capabilities in new ventures: exploring strategic change in US green goods manufacturing using website data," The Journal of Technology Transfer, Springer, vol. 45(5), pages 1451-1480, October.
    10. Bengt-ake Lundvall & Bjorn Johnson, 1994. "The Learning Economy," Industry and Innovation, Taylor & Francis Journals, vol. 1(2), pages 23-42.
    11. Sanjay K. Arora & Yin Li & Jan Youtie & Philip Shapira, 2016. "Using the wayback machine to mine websites in the social sciences: A methodological resource," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(8), pages 1904-1915, August.
    12. Fontana, Roberto & Nuvolari, Alessandro & Shimizu, Hiroshi & Vezzulli, Andrea, 2013. "Reassessing patent propensity: Evidence from a dataset of R&D awards, 1977–2004," Research Policy, Elsevier, vol. 42(10), pages 1780-1792.
    13. 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.
    14. Anthony Arundel & Keith Smith, 2013. "History of the Community Innovation Survey," Chapters, in: Fred Gault (ed.), Handbook of Innovation Indicators and Measurement, chapter 3, pages 60-87, Edward Elgar Publishing.
    15. Jan Kinne & Janna Axenbeck, 2020. "Web mining for innovation ecosystem mapping: a framework and a large-scale pilot study," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2011-2041, December.
    16. Wesley M. Cohen & Richard R. Nelson & John P. Walsh, 2000. "Protecting Their Intellectual Assets: Appropriability Conditions and Why U.S. Manufacturing Firms Patent (or Not)," NBER Working Papers 7552, National Bureau of Economic Research, Inc.
    17. Dirk Libaers & Diana Hicks & Alan L. Porter, 2016. "A taxonomy of small firm technology commercialization," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 25(3), pages 371-405.
    18. 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.
    19. Giotopoulos, Ioannis & Kontolaimou, Alexandra & Korra, Efthymia & Tsakanikas, Aggelos, 2017. "What drives ICT adoption by SMEs? Evidence from a large-scale survey in Greece," Journal of Business Research, Elsevier, vol. 81(C), pages 60-69.
    20. J Sylvan Katz & Viv Cothey, 2006. "Web indicators for complex innovation systems," Research Evaluation, Oxford University Press, vol. 15(2), pages 85-95, August.
    21. Nathan, Max & Rosso, Anna, 2022. "Innovative events: product launches, innovation and firm performance," Research Policy, Elsevier, vol. 51(1).
    22. Blazquez, Desamparados & Domenech, Josep, 2018. "Big Data sources and methods for social and economic analyses," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 99-113.
    23. Nagaoka, Sadao & Motohashi, Kazuyuki & Goto, Akira, 2010. "Patent Statistics as an Innovation Indicator," 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 1083-1127, Elsevier.
    24. Marco Guerzoni & Consuelo R. Nava & Massimiliano Nuccio, 2021. "Start-ups survival through a crisis. Combining machine learning with econometrics to measure innovation," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 30(5), pages 468-493, July.
    25. Jorge Guzman & Aishen Li, 2023. "Measuring Founding Strategy," Management Science, INFORMS, vol. 69(1), pages 101-118, January.
    26. 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.
    27. Benn Lawson & Danny Samson, 2001. "Developing Innovation Capability In Organisations: A Dynamic Capabilities Approach," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 5(03), pages 377-400.
    28. Alessandra Colombelli, 2016. "The impact of local knowledge bases on the creation of innovative start-ups in Italy," Post-Print halshs-01340050, HAL.
    29. Anthony Arundel & Kieran O’Brien & Ann Torugsa, 2013. "How firm managers understand innovation: implications for the design of innovation surveys," Chapters, in: Fred Gault (ed.), Handbook of Innovation Indicators and Measurement, chapter 4, pages 88-108, Edward Elgar Publishing.
    30. Li, Yin & Arora, Sanjay & Youtie, Jan & Shapira, Philip, 2018. "Using web mining to explore Triple Helix influences on growth in small and mid-size firms," Technovation, Elsevier, vol. 76, pages 3-14.
    31. Eduardo Cebrián & Josep Domenech, 2023. "Is Google Trends a quality data source?," Applied Economics Letters, Taylor & Francis Journals, vol. 30(6), pages 811-815, March.
    32. Nathan, Max & Rosso, Anna, 2015. "Mapping digital businesses with big data: Some early findings from the UK," Research Policy, Elsevier, vol. 44(9), pages 1714-1733.
    33. Zdenek Sulc & Jana Cibulkova & Hana Rezankova, 2022. "Nomclust 2.0: an R package for hierarchical clustering of objects characterized by nominal variables," Computational Statistics, Springer, vol. 37(5), pages 2161-2184, November.
    34. Roberto Antonietti & Francesca Gambarotto, 2020. "The role of industry variety in the creation of innovative start-ups in Italy," Small Business Economics, Springer, vol. 54(2), pages 561-573, February.
    35. Rand R. Wilcox & David M. Erceg-Hurn, 2012. "Comparing two dependent groups via quantiles," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(12), pages 2655-2664, August.
    36. J. Gower & P. Legendre, 1986. "Metric and Euclidean properties of dissimilarity coefficients," Journal of Classification, Springer;The Classification Society, vol. 3(1), pages 5-48, March.
    37. Jan Kinne & David Lenz, 2021. "Predicting innovative firms using web mining and deep learning," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-18, April.
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    More about this item

    Keywords

    Unconventional data; SMEs; Innovation; Corporate websites; HTML tags;
    All these keywords.

    JEL classification:

    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

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