Abstract
With the urgent call for sustainability and the rapid advancement of information technology, especially machine learning and artificial intelligence, the food industry faces unparalleled opportunities and challenges in optimizing resources and enhancing performance. By that call, we foresee a massive change, especially to the way research has been traditionally conducted, it is hypothesized for a surge of research and increasing adoption of innovative tools such as deep learning (DL) and optimization techniques by the research community and the field to address critical challenges in food systems. This study investigates the intersection of commercial, sustainability, and technology domains through advanced bibliometric analysis enhanced by deep document clustering, aims to uncover the multifaceted nature of these interconnected fields, addressing how emerging technologies and sustainability practices shape commercial strategies in the field, providing a panoramic perspective for reader about the dynamic development of the field. Utilizing a multi-tiered literature search strategy and employing deep document clustering techniques, the analysis reveals distinct thematic clusters—ranging from macroeconomic demand challenges to technical advancements in AI-driven agricultural practices and sustainable supply chain management—that underscore the deep connections among commercial, sustainability, and technological domains. The results not only validate the hypothesis of increasing convergence among these fields but also highlight the critical role of advanced methodologies in uncovering latent patterns and facilitating strategic and operational improvements. Moreover, the findings demonstrate that deep document clustering is a powerful tool for bibliometric analysis, offering nuanced insights that can be further refined in future studies. Overall, this research contributes to a holistic understanding of the field, emphasizing the need for continued interdisciplinary collaboration and innovation to drive sustainable development in a global business environment.
| Original language | English |
|---|---|
| Journal | International Journal of Engineering Business Management |
| Volume | 18 |
| DOIs | |
| Publication status | Published - 1 Jan 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 2 Zero Hunger
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SDG 4 Quality Education
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SDG 8 Decent Work and Economic Growth
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SDG 9 Industry, Innovation, and Infrastructure
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SDG 12 Responsible Consumption and Production
Keywords
- bibliometric analysis
- document clustering
- food systems
- sustainability
- technology
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