Green IT in Agriculture: A Bibliometric and Theoretical Analysis of Digital Agriculture Research
Mots-clés :
Green IT management, adoption, Sustainable agriculture, Information systems, Bibliometric analysis, InnovationRésumé
This study provides a bibliometric and conceptual analysis of Green Information Technology (Green IT) management in the agricultural sector. Despite the growing interest in sustainable digital technologies, existing research remains fragmented and lacks a clear management-oriented perspective. Literature is largely dominated by technological approaches, with limited attention to managerial and user-centered dimensions. This research adopts a positivist epistemological stance, consistent with the objective of mapping and structuring a scientific field based on bibliometric data. It aims to identify the main research themes, clarify the terminology used in the field, and highlight key gaps related to the adoption, acceptance, and actual use of Green IT in agriculture.
Using a dataset of 5,984 publications extracted from the Scopus database, a co-word analysis was conducted with VOSviewer to map the intellectual structure of the field. The findings reveal four dominant thematic clusters: precision agriculture, remote sensing, Internet of Things (IoT), and irrigation systems, reflecting a strong technological orientation. The results also show significant conceptual fragmentation, with terms such as smart agriculture, digital agriculture, and climate-smart agriculture being widely used, while “Green IT” itself remains marginal in the literature.
This study relies exclusively on secondary data from Scopus and a bibliometric co-word analysis, which limits causal interpretation of the findings and does not capture the qualitative and contextual dimensions of the studied phenomena. Nevertheless, it contributes to clarifying the conceptual landscape of Green IT in agriculture and proposes a research agenda integrating technological, organizational, and sustainability perspectives.
Classification JEL : O33, M15, Q16, O13, Q55.
Paper type: Empirical Research
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© Houda ZITAN, Khalid CHAFIK 2026

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