Linking Digital Agriculture Research and Export Outcomes: A Comparative Bibliometric Analysis of Production and Marketing Dimensions (2020–2024)

This study first analyses the use of digital technologies in agriculture from two different perspectives. Then, correlation analyses using these data aim to show which countries focus on which of the two perspectives are ahead in agricultural exports. In the study, publications containing the word ‘agriculture’ in the title, abstract, or keywords section of the Scopus database and the keywords ‘digital technology’ and ‘production’ in the all-fields section were selected and recorded as publications in which digital technologies in agricultural production were investigated. Then, in the Scopus database, publications containing the word ‘agriculture’ in the title, abstract or keywords section and the words ‘digital technology’ and ‘marketing’ in the all-fields section were kept in a separate category and recorded as publications in which digital technologies in marketing of agricultural products were investigated. These two data sets were subjected to correlation analysis with export data obtained from OECD databases, and interactions on the axes of agriculture, digital technologies, production, and marketing were revealed. After selecting the OECD member countries with export data from all the data obtained, the number of academic publications of these countries with the specified conditions is given in separate tables. The correlation analysis on OECD member countries revealed a statistically significant and strong positive relationship between the average agricultural export volumes for 2020-2024 and the number of scientific publications containing the terms agriculture, digital technologies, and production indexed in the Scopus database. The Pearson correlation coefficient was calculated as r = 0.813, and the significance level was p = 0.004. When a similar correlation analysis was conducted with publications containing agriculture, digital technologies, and marketing terms, the Pearson correlation coefficient was r = 0.958 with a significance level of p < 0.001. This finding indicates that countries that produce higher levels of academic output in agriculture (publications containing both production and marketing terms) tend to have higher export performance in the agricultural sector. The results suggest that there may be a significant relationship between academic productivity and economic output in international agricultural trade.

Authors

Institutions

Publication Details

Journal
Turkish Journal of Agriculture - Food Science and Technology
Published
2025-10-13
DOI
https://doi.org/10.24925/turjaf.v13i10.2156-2162.7873
Primary Topic
Digitalization and Economic Development in Agriculture
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Linking Digital Agriculture Research and Export Outcomes: A Comparative Bibliometric Analysis of Production and Marketing Dimensions (2020–2024)

Nebi Seren
Turkish Journal of Agriculture - Food Science and Technology
Digitalization and Economic Development in Agriculture
article

Linking Digital Agriculture Research and Export Outcomes: A Comparative Bibliometric Analysis of Production and Marketing Dimensions (2020–2024)

Nebi Seren
article en

Abstract

This study first analyses the use of digital technologies in agriculture from two different perspectives. Then, correlation analyses using these data aim to show which countries focus on which of the two perspectives are ahead in agricultural exports. In the study, publications containing the word ‘agriculture’ in the title, abstract, or keywords section of the Scopus database and the keywords ‘digital technology’ and ‘production’ in the all-fields section were selected and recorded as publications in which digital technologies in agricultural production were investigated. Then, in the Scopus database, publications containing the word ‘agriculture’ in the title, abstract or keywords section and the words ‘digital technology’ and ‘marketing’ in the all-fields section were kept in a separate category and recorded as publications in which digital technologies in marketing of agricultural products were investigated. These two data sets were subjected to correlation analysis with export data obtained from OECD databases, and interactions on the axes of agriculture, digital technologies, production, and marketing were revealed. After selecting the OECD member countries with export data from all the data obtained, the number of academic publications of these countries with the specified conditions is given in separate tables. The correlation analysis on OECD member countries revealed a statistically significant and strong positive relationship between the average agricultural export volumes for 2020-2024 and the number of scientific publications containing the terms agriculture, digital technologies, and production indexed in the Scopus database. The Pearson correlation coefficient was calculated as r = 0.813, and the significance level was p = 0.004. When a similar correlation analysis was conducted with publications containing agriculture, digital technologies, and marketing terms, the Pearson correlation coefficient was r = 0.958 with a significance level of p < 0.001. This finding indicates that countries that produce higher levels of academic output in agriculture (publications containing both production and marketing terms) tend to have higher export performance in the agricultural sector. The results suggest that there may be a significant relationship between academic productivity and economic output in international agricultural trade.

Turkish Journal of Agriculture - Food Science and TechnologyVol. 13(10)
Bursa Uludağ Üni̇versi̇tesi̇ (TR)
Openalex Percentile: Top 58%
Digitalization and Economic Development in Agriculture
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.