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World Economy
Article . 2024 . Peer-reviewed
License: CC BY NC ND
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Robots in action

Authors: Taraneh Shahin; María Teresa Ballestar de las Heras; Ismael Sanz;

Robots in action

Abstract

AbstractThis empirical study delves into the intricate factors that shape firms' choices regarding the adoption of robots within the Spanish context. Using a dataset encompassing a diverse set of industries, we employ an empirical analysis to uncover the determinants of robot adoption and investigate the associated outcomes on market variables. Our findings reveal several key factors that significantly influence a firm's likelihood of adopting robots. We find that firm profitability, exporter status, the control variables including share of R&D, and capital intensity exhibit strong positive relationships with robot adoption. Conversely, the impact of the level of human capital on adoption decisions is less pronounced. Furthermore, our study explores the impact of robot adoption on firm performance. We observe that firms embracing robotisation experience notable improvements in the output, exporting activities, and reduction in labour cost share. This study incorporates a gradient boosting‐based machine‐learning model, specifically XGBoost, along with instrumental variable regression models, to conduct rigorous robustness analyses and validate the obtained results. These findings contribute to the understanding of the dynamics and implications of robot adoption in the manufacturing sector, explaining the factors that drive firms' decisions and the subsequent market effects.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
hybrid