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Analysis of institutional authors

Domenech, JosepAuthor

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February 4, 2026
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Does AI boost firm productivity? A web scraping and LLMs approach

Publicated to: TELECOMMUNICATIONS POLICY. 50 (2): 103138- - 2026-03-01 50(2), DOI: 10.1016/j.telpol.2025.103138

Authors:

Pastor-Merino, Ana; Martinez-Barbero, Xavier; Vicente, Maria R; Domenech, Josep
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Affiliations

Univ Oviedo, Appl Econ, Campus Cristo S-N, Oviedo, Asturias, Spain - Author
Univ Politecn Valencia, Dept Econ & Social Sci, Valencia, Spain - Author

Abstract

Artificial Intelligence (AI) is widely seen as a transformative technology with the potential to reshape firm productivity across sectors. However, empirical evidence on its actual impact at the firm level remains limited, mainly due to the lack of extensive firm-level data. Leveraging web scraping and Large Language Models (LLMs), this study develops a novel framework to detect and quantify AI adoption among 62,525 Spanish firms. The approach distinguishes between firms that adopt AI and those that integrate it intensively across business functions, constructing both binary and continuous measures of AI use. Using entropy-balanced instrumental variable estimations to address endogeneity, we find that AI-adopting firms exhibit approximately 53%-55% higher sales and 48% higher value added than comparable non-adopters. Moreover, increasing the intensity of AI use is associated with an even larger productivity premium of 74%-76% in sales and up to 67% in value added, highlighting the substantial returns from deeper AI integration. In dynamic terms, AI adoption is linked to 9%-13% faster annual sales growth. These findings provide evidence that AI significantly enhances firm performance, underscoring its role as a key driver of productivity growth.
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Keywords

Annual salesArtificial intelligenceBusiness functionsEndogeneityFirm productivityInstrumental variablesIntelligence integrationLanguage modelLarge language modelLarge language modelsModeling approachSalesWeb scrapingWeb scrapings

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal TELECOMMUNICATIONS POLICY due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2026, it was in position 2/227, thus managing to position itself as a Q1 (Primer Cuartil), in the category Communication.

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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-06:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 18 (PlumX).
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Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (Pastor-Merino, Ana) and Last Author (Doménech De Soria, Josep).

the author responsible for correspondence tasks has been Pastor-Merino, Ana.

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Awards linked to the item

This work was supported by the Generalitat Valenciana, Spain under Grant CIAICO/2023/272; the Agencia Estatal de Investigacion, Spain (MCIN/AEI/10.13039/501100011033) and ERD-F/EU under Grant PID2023-152106OB-I00; and the Universitat Politecnica de Valencia, Spain (PAID-01-24) and FPU24/01116, Ministerio de Ciencia e Innovacion (Spain) .
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