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Cited by 438

The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.

Artificial intelligence and firm-level productivity

Open access
Czarnitzki, Dirk, Fernández, Gastón P., Rammer, Christian·2023·Journal of Economic Behavior & Organization
DOI 10.1016/j.jebo.2023.05.008
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Abstract

Artificial Intelligence (AI) is often regarded as the next general-purpose technology with a rapid, penetrating, and far-reaching use over a broad number of industrial sectors. The main feature of new general-purpose technology is to enable new ways of production that may increase productivity. However, to date, only a few studies have investigated the likely productivity effects of AI at the firm-level, presumably due to limited data availability. We exploit unique survey data on firms’ adoption of AI technology and estimate its productivity effects with a sample of German firms. We employ both a cross-sectional dataset and a panel database. To address the potential endogeneity of AI adoption, we also implement IV estimators. We find positive and significant associations between the use of AI and firm productivity. This finding holds for different measures of AI usage, i.e., an indicator variable of AI adoption, and the intensity with which firms use AI methods in their business processes.

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Metadata

Authors
Czarnitzki, D., Fernández, G. P., & Rammer, C.
Venue
Journal of Economic Behavior & Organization
Publisher
Elsevier BV
Published
2023-07
Volume
211
Pages
188-205
ISSN
0167-2681 (ISSN-L)
DOI
10.1016/j.jebo.2023.05.008
OpenAlex
W4376633190
Cited by
438
References
11
FWCI
80.76
Type
journal article
Language
en
Open access
hybrid

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.