How Digitalization Shapes Export Potential: Firm-Level Insights From The EU and Beyond
Öz
The primary objective of this study is to examine the relationship between the adoption of advanced digital technologies, such as artificial intelligence (AI), and the probability of exporting, utilizing a probit model. The results indicate that the adoption of artificial intelligence, cloud computing, and robotics technologies is positively and statistically significantly associated with the likelihood of exporting. Big data analytics, smart devices, and blockchain technologies do not show a statistically significant association with firms’ likelihood of exporting. The study investigates the relationship between specific digital technologies and export destinations as a secondary objective by applying a multivariate probit model, which accounts for potential correlations among the error terms across destination-specific export decisions. The findings show that artificial intelligence and smart devices are significantly associated with exports to EU countries. Cloud computingis significantly associated with export activities to all countries except China. Big data analytics is significantly associated with exports to non-EU countries. Incontrast, blockchain technology does not exhibit a statistically significant relationship with export destinations. Robotics technologies exhibit a consistentand positive association with export participation across all export regions.
Anahtar Kelimeler
Kaynakça
- Acemoglu, D. and Restrepo, P. (2020). Robots and jobs: Evidence from US labor markets. Journal of Political Economy, 128(6), 2188-2244. https://doi.org/10.1086/705716
- Alguacil Marí, M.T., Lo Turco, A. and Martínez-Zarzoso, I. (2020). What is so special about robots and trade? (Cege Discussion Papers No. 410). Retrieved from https://dx.doi.org/10.2139/ssrn.3756787
- Amadu, A.W. and Danquah, M. (2019). R&D, human capital and export behavior of manufacturing and service firms in Ghana. Journal of African Business, 20(3), 283-304. https://doi.org/10.1080/15228916.2019.1581003
- Aw, B.Y., Roberts, M.J. and Xu, D.Y. (2008). R&D investments, exporting, and the evolution of firm productivity. American Economic Review, 98(2), 451-56. https://doi.org/10.1257/aer.98.2.451
- Balci, G. and Surucu Balci, E. (2021). Blockchain adoption in the maritime supply chain: Examining barriers and salient stakeholders in containerized international trade. Transportation Research Part E: Logistics and Transportation Review, 156, 102539. https://doi.org/10.1016/j.tre.2021.102539
- Ballestar, M.T., Díaz-Chao, Á., Sainz, J. and Torrent-Sellens, J. (2020). Knowledge, robots and productivity in SMEs: Explaining the second digital wave. Journal of Business Research, 108, 119-131. https://doi.org/10.1016/j.jbusres.2019.11.017
- Baruffaldi, S., van Beuzekom, B., Dernis, H., Harhoff, D., Rao, N., Rosenfeld, D. and Squicciarini, M. (2020). Identifying and measuring developments in artificial intelligence: Making the impossible possible (OECD Science, Technology and Industry Working Papers No. 2020/05). https://doi.org/10.1787/5f65ff7e-en.
- Bekkers, E., Koopman, B. and Teh, R. (2018). Long run trends in international trade. The impact of new technologies. Paper presented at the GTAP Annual Conference on Global Economic Analysis. Cartagena, Colombia. Retrieved from https://ageconsearch.umn.edu/record/332962/
Ayrıntılar
Birincil Dil
İngilizce
Konular
Yatay Kesit Analizi, Mikroekonomik Teori, Kalkınma Ekonomisi - Mikro, Uluslararası İktisatta Bölgesel Gelişme ve Küreselleşme, Sürdürülebilir Kalkınma
Bölüm
Araştırma Makalesi
Yayımlanma Tarihi
31 Mart 2026
Gönderilme Tarihi
31 Ekim 2025
Kabul Tarihi
30 Mart 2026
Yayımlandığı Sayı
Yıl 2026 Cilt: 11 Sayı: 1