A Cross-Sectional Analysis of the Relationship between Digital Technology Use and Agricultural Productivity in EU Countries

C. Bocean
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Abstract

Amidst the rapid evolution of digital technologies and their prospective implications for agricultural productivity, farmers are increasingly turning to Agriculture 4.0. As digitization permeates every facet of agriculture, the potential for boosting productivity while ensuring sustainability and resilience becomes increasingly tangible. The objective of this study is to understand how the adoption of digital technologies influences agricultural productivity within the diverse socioeconomic and agricultural landscapes of EU nations. The research of this study aims to address questions concerning the impact of digital technology use on agricultural productivity across EU countries. This study employs a robust analytical framework combining equation modeling (SEM), artificial neural networks, and cluster analysis. SEM analysis reveals significant associations and influences between digital technology use and productivity related to the total labor force across EU countries. Moreover, cluster analysis outlines distinct clusters of EU member states distinguished by varying degrees of digital technology incorporation and corresponding agricultural productivity, emphasizing the diverse socioeconomic contexts that influence these associations. These findings underscore the significance of embracing digital technology as a catalyst for enhancing agricultural productivity across EU nations. Future research could focus on devising strategies to promote the widespread adoption of digital technologies in agriculture across EU member states, and longitudinal analyses could offer insights into the dynamic relationship between digital technology use and agricultural output, informing policy interventions.
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欧盟国家数字技术使用与农业生产力之间关系的横断面分析
随着数字技术的快速发展及其对农业生产力的潜在影响,农民们越来越多地转向农业 4.0。随着数字化渗透到农业的方方面面,在提高生产力的同时确保可持续性和复原力的潜力变得越来越明显。本研究的目的是了解在欧盟各国不同的社会经济和农业环境中,数字技术的采用如何影响农业生产率。本研究旨在解决欧盟各国数字技术的使用对农业生产力的影响问题。本研究采用了稳健的分析框架,将方程建模(SEM)、人工神经网络和聚类分析结合在一起。SEM 分析揭示了欧盟各国数字技术的使用与总劳动力相关的生产力之间的重要关联和影响。此外,聚类分析还勾勒出欧盟成员国的独特聚类,这些聚类因不同程度的数字技术应用和相应的农业生产率而有所区别,强调了影响这些关联的不同社会经济背景。这些研究结果强调了采用数字技术作为提高欧盟各国农业生产力的催化剂的重要性。未来的研究可侧重于制定战略,促进欧盟各成员国在农业领域广泛采用数字技术,纵向分析可深入了解数字技术使用与农业产出之间的动态关系,为政策干预提供参考。
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