Big Data Analytics and Exports—Evidence for Manufacturing Firms from 27 EU Countries

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Big Data Analytics and Exports—Evidence for Manufacturing Firms from 27 EU Countries. / Wagner, Joachim.
In: Open Economies Review, 22.06.2024.

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@article{781d83cccafe40d68d7d7b780f5dc319,
title = "Big Data Analytics and Exports—Evidence for Manufacturing Firms from 27 EU Countries",
abstract = "The use of big data analytics (including data mining and predictive analytics) by firms can be expected to increase productivity and reduce trade costs, which should be positively related to export activities. This paper uses firm level data from the Flash Eurobarometer 486 survey conducted in February – May 2020 to investigate the link between the use of big data analytics and export activities in manufacturing enterprises from the 27 member countries of the European Union. We find that firms which use big data analytics do more often export, do more often export to various destinations all over the world, and do export to more different destinations. The estimated big data analytics premia for exports are statistically highly significant after controlling for firm size, firm age, patents, and country. Furthermore, the size of these premia can be considered to be large. Successful exporters tend to use big data analytics.",
keywords = "Big data analytics, D22, Exports, F14, Firm level data, Flash Eurobarometer 486, Economics",
author = "Joachim Wagner",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.",
year = "2024",
month = jun,
day = "22",
doi = "10.1007/s11079-024-09777-2",
language = "English",
journal = "Open Economies Review",
issn = "0923-7992",
publisher = "Springer",

}

RIS

TY - JOUR

T1 - Big Data Analytics and Exports—Evidence for Manufacturing Firms from 27 EU Countries

AU - Wagner, Joachim

N1 - Publisher Copyright: © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

PY - 2024/6/22

Y1 - 2024/6/22

N2 - The use of big data analytics (including data mining and predictive analytics) by firms can be expected to increase productivity and reduce trade costs, which should be positively related to export activities. This paper uses firm level data from the Flash Eurobarometer 486 survey conducted in February – May 2020 to investigate the link between the use of big data analytics and export activities in manufacturing enterprises from the 27 member countries of the European Union. We find that firms which use big data analytics do more often export, do more often export to various destinations all over the world, and do export to more different destinations. The estimated big data analytics premia for exports are statistically highly significant after controlling for firm size, firm age, patents, and country. Furthermore, the size of these premia can be considered to be large. Successful exporters tend to use big data analytics.

AB - The use of big data analytics (including data mining and predictive analytics) by firms can be expected to increase productivity and reduce trade costs, which should be positively related to export activities. This paper uses firm level data from the Flash Eurobarometer 486 survey conducted in February – May 2020 to investigate the link between the use of big data analytics and export activities in manufacturing enterprises from the 27 member countries of the European Union. We find that firms which use big data analytics do more often export, do more often export to various destinations all over the world, and do export to more different destinations. The estimated big data analytics premia for exports are statistically highly significant after controlling for firm size, firm age, patents, and country. Furthermore, the size of these premia can be considered to be large. Successful exporters tend to use big data analytics.

KW - Big data analytics

KW - D22

KW - Exports

KW - F14

KW - Firm level data

KW - Flash Eurobarometer 486

KW - Economics

UR - http://www.scopus.com/inward/record.url?scp=85196502522&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/6ce68d7b-4e39-39b7-94c1-9200c92c82a5/

U2 - 10.1007/s11079-024-09777-2

DO - 10.1007/s11079-024-09777-2

M3 - Journal articles

AN - SCOPUS:85196502522

JO - Open Economies Review

JF - Open Economies Review

SN - 0923-7992

ER -