How urgent environmental challenges and tech advancements reshape commercial food systems: A bibliometric analysis leveraging natural-language processing
Chee Perng Ng et al.
What the paper says
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.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.