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Robots and the origin of their labour-saving impact

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  • Montobbio, Fabio
  • Staccioli, Jacopo
  • Virgillito, Maria Enrica
  • Vivarelli, Marco

Abstract

This paper investigates the presence of explicit labour-saving heuristics within robotic patents. It analyses innovative actors engaged in robotic technology and their economic environment (identity, location, industry), and identifies the technological fields more exposed to labour-saving innovations. It exploits advanced natural language processing and probabilistic topic modelling techniques applied to the universe of USPTO patent applications between 2009 and 2018, matched with the ORBIS (Bureau van Dijk) firm-level dataset. The results show that labour-saving patent holders comprise not only robot producers, but mainly adopters. Consequently, labour-saving robotic patents appear along the entire supply chain. Additionally, labour-saving innovations are directed towards manual activities in services (e.g. in the logistics sector), activities entailing social intelligence (e.g. in the healthcare sector) and cognitive skills (e.g. learning and predicting).

Suggested Citation

  • Montobbio, Fabio & Staccioli, Jacopo & Virgillito, Maria Enrica & Vivarelli, Marco, 2022. "Robots and the origin of their labour-saving impact," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
  • Handle: RePEc:eee:tefoso:v:174:y:2022:i:c:s0040162521005552
    DOI: 10.1016/j.techfore.2021.121122
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    3. Jacopo Staccioli & Maria Enrica Virgillito, 2021. "Back to the past: the historical roots of labor-saving automation," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 11(1), pages 27-57, March.
    4. Lucrezia Fanti & Dario Guarascio & Massimo Moggi, 2020. "The development of AI and its impact on business models, organization and work," LEM Papers Series 2020/25, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    5. Fernández-Macías, Enrique & Klenert, David & Antón, José-Ignacio, 2021. "Not so disruptive yet? Characteristics, distribution and determinants of robots in Europe," Structural Change and Economic Dynamics, Elsevier, vol. 58(C), pages 76-89.
    6. Domini, Giacomo & Grazzi, Marco & Moschella, Daniele & Treibich, Tania, 2022. "For whom the bell tolls: The firm-level effects of automation on wage and gender inequality," Research Policy, Elsevier, vol. 51(7).
    7. Fabio Montobbio & Jacopo Staccioli & Maria Enrica Virgillito & Marco Vivarelli, 2021. "Labour-saving automation and occupational exposure: a text-similarity measure," DISCE - Quaderni del Dipartimento di Politica Economica dipe0021, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    8. Fossen, Frank M. & Sorgner, Alina, 2022. "New digital technologies and heterogeneous wage and employment dynamics in the United States: Evidence from individual-level data," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
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    10. Marco Vivarelli, 2022. "Innovation and employment: a short update," DISCE - Quaderni del Dipartimento di Politica Economica dipe0024, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).

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    More about this item

    Keywords

    Robotic patents; Labour-saving technology; Search heuristics; Probabilistic topic models;
    All these keywords.

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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