Robot Hubs and the Use of Robotics in US Manufacturing Establishments
Erik Brynjolfsson, Catherine Buffington, Nathan Goldschlag, J. Frank Li, Javier Miranda, Robert Seamans
American Economic Association Papers and Proceedings,
May
2025
Abstract
We use data from the Annual Survey of Manufactures to study the characteristics and geographic distribution of investments in robots across US manufacturing establishments. Robotics adoption and robot intensity (the number of robots per employee) cluster in "robot hubs." Establishments that report having robotics are larger and have a larger production worker share, lower pay per worker, lower labor share, and higher capital expenditures, including higher IT capital expenditures. Notably, establishments are more likely to have robots if other establishments in the same core-based statistical area and industry also report having robotics, suggestive of agglomeration and peer effects.
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Medienecho
Medienecho Juli 2025 IWH: Wirtschaft ist durch Talsohle in: Mitteldeutsche Zeitung Halle / Saalekreis, 16.07.2025 IWH: Schwankende Stimmung in der Wirtschaft in: Magdeburger…
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Forschungsdatenzentrum
Forschungsdatenzentrum (IWH-FDZ) Direkt zu unserem Datenangebot Das IWH-Forschungsdatenzentrum bietet externen Forscherinnen und Forschern Zugang zu Mikrodaten und…
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Forschungsorganisation
Forschungsorganisation Die Forschungsstruktur des Instituts ist darauf ausgelegt, die enge Verzahnung zwischen einzel- und gesamtwirtschaftlicher Forschung sowie zwischen Finanz-…
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Forschungscluster
Drei Forschungscluster Jede IWH-Forschungsgruppe ist einem themenorientieren Forschungscluster zugeordnet. Die Cluster stellen keine eigenen Organisationseinheiten dar, sondern…
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Exploring Accounting Research Topic Evolution: An Unsupervised Machine Learning Approach
June Cao, Zhanzhong Gu, Iftekhar Hasan
Journal of International Accounting Research,
Nr. 3,
2023
Abstract
This study explores the evolution of accounting research by utilizing an unsupervised machine learning approach. We aim to identify the latent topics of accounting from the 1980s up to 2018, the dynamics and emerging topics of accounting research, and the economic reasons behind those changes. First, based on 23,220 articles from 46 accounting journals, we identify 55 topics using the latent Dirichlet allocation model. To illustrate the connection between topics, we use HistCite to generate a citation map along a timeline. The citation clusters demonstrate the “tribalism” phenomenon in accounting research. We then implement the dynamic topic model to reveal the dynamics of topics to show changes in accounting research. The emerging research trends are identified from the topic analytics. We further explore the economic reasons and in-depth insights into the topic evolution, indicating the economic development embeddedness nature of accounting research.
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Forschungsabteilungen
Forschungsabteilungen Die Forschung am IWH ist in Form einer Matrix organisiert. Als Primärorganisation sind die Forschungsabteilungen mittel- bis langfristig angelegt und vor…
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Evolvement of China-related Topics in Academic Accounting Research: Machine Learning Evidence
June Cao, Zhanzhong Gu, Iftekhar Hasan
China Accounting and Finance Review,
Nr. 4,
2020
Abstract
This study employs an unsupervised machine learning approach to explore the evolution of accounting research. We are particularly interested in exploring why international researchers and audiences are interested in China-related issues; what kinds of research topics related to China are mainly investigated in globally recognised journals; and what patterns and emerging topics can be explored by comprehensively analysing a big sample. Using a training sample of 23,220 articles from 46 accounting journals over the period 1980 to 2018, we first identify the optimal number of accounting research topics; the dynamic patterns of these accounting research topics are explored on the basis of 46 accounting journals to show changes in the focus of accounting research. Further, we collect articles related to Chinese accounting research from 18 accounting journals, eight finance journals, and eight management journals over the period 1980 to 2018. We objectively identify China-related accounting research topics and map them to the stages of China’s economic development. We attempt to identify the China-related issues global researchers are interested in and whether accounting research reflects the economic context. We use HistCite TM to generate a citation map along a timeline to illustrate the connections between topics. The citation clusters demonstrate “tribalism” phenomena in accounting research. The topics related to Chinese accounting research conducted by international accounting researchers reveal that accounting changes mirror economic reforms. Our findings indicate that accounting research is embedded in the economic context.
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R&D Collaborations and the Role of Proximity
Philipp Marek, Mirko Titze, Clemens Fuhrmeister,
Regional Studies,
Nr. 12,
2017
Abstract
R&D collaborations and the role of proximity. Regional Studies. This paper explores the impact of proximity measures on knowledge exchange measured by granted research and development (R&D) collaboration projects in German NUTS-3 regions. The results are obtained from a spatial interaction model including eigenvector spatial filters. Not only geographical but also other forms of proximity (technological, organizational and institutional) have a significant influence on the emergence of collaborations. Furthermore, the results suggest interdependences between proximity measures. Nevertheless, the analysis does not show that other forms of proximity may compensate for missing geographical proximity. The results indicate that (subsidized) collaborative innovation activities tend to cluster.
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Benchmark Value-added Chains and Regional Clusters in R&D-intensive Industries
Reinhold Kosfeld, Mirko Titze
International Regional Science Review,
Nr. 5,
2017
Abstract
Although the phase of euphoria seems to be over, policy makers and regional agencies have maintained their interest in cluster policy. Modern cluster theory provides reasons for positive external effects that may accrue from interaction in a group of proximate enterprises operating in common and related fields. Although there has been some progress in locating clusters, in most cases only limited knowledge on the geographical extent of regional clusters has been established. In the present article, we present a hybrid approach to cluster identification. Dominant buyer–supplier relationships are derived by qualitative input–output analysis from national input–output tables, and potential regional clusters are identified by spatial scanning. This procedure is employed to identify clusters of German research and development-intensive industries. A sensitivity analysis reveals good robustness properties of the hybrid approach with respect to variations in the quantitative cluster composition.
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