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How are digital technologies changing innovation?: Evidence from agriculture, the automotive industry and retail


  • Caroline Paunov
  • Sandra Planes-Satorra


Digital technologies impact innovation in all sectors of the economy, including traditional ones such as agriculture, the automotive industry, and retail. Similar trends across sectors include that the Internet of Things and data are becoming key inputs for innovation, innovation cycles are accelerating, services innovation is gaining importance and collaborative innovation matters more. Sector-specific dynamics are driven by differences in opportunities such technologies offer for innovation in products, processes and business models, as well as differences in the types of data needed for innovation and the conditions for digital technology adoption. The analysis calls for revisiting innovation policy mixes to ensure these remain effective and address emerging challenges. A sectoral approach is needed when designing innovation policies in some domains, especially regarding data access and digital technology adoption policies. The current focus of innovation policies on boosting R&D to meet R&D intensity targets also requires scrutiny.

Suggested Citation

  • Caroline Paunov & Sandra Planes-Satorra, 2019. "How are digital technologies changing innovation?: Evidence from agriculture, the automotive industry and retail," OECD Science, Technology and Industry Policy Papers 74, OECD Publishing.
  • Handle: RePEc:oec:stiaac:74-en
    DOI: 10.1787/67bbcafe-en

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    Cited by:

    1. Krzysztof Bartczak & Stanisław Łobejko, 2022. "The Implementation Environment for a Digital Technology Platform of Renewable Energy Sources," Energies, MDPI, vol. 15(16), pages 1-16, August.
    2. Radicic, Dragana & Petković, Saša, 2023. "Impact of digitalization on technological innovations in small and medium-sized enterprises (SMEs)," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    3. Chong Guan & Wenting Liu & Jack Yu-Chao Cheng, 2022. "Using Social Media to Predict the Stock Market Crash and Rebound amid the Pandemic: The Digital ‘Haves’ and ‘Have-mores’," Annals of Data Science, Springer, vol. 9(1), pages 5-31, February.

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