Mapping the landscape of Consumer Food Waste

Harvey, John; Nica-Avram, G.; Smith, M.; Hibbert, Sally; Muthuri, Judy

Abstract

Since 2015 there has been a surge of academic publications and citations focused on consumer food waste. To introduce a special issue of Appetite focused on the drivers of consumer food waste we perform a transdisciplinary and historical review of the literature through a co-citation network analysis and topic modelling approach. We show that the rapid increase in publications is largely attributable to an urgency caused by the Sustainable Development Goals and climate change. Topic modelling reveals that the dramatic quantitative increase of publications has also produced a variety of evolving themes, and that a metaphorical Cambrian Explosion is occurring after decades of academic inactivity. Network analysis results show that consumer food waste features in thousands of articles and hundreds of journals, but that the citation practices of academics are becoming highly concentrated, as 20% of journals attract over 80% of citations. Finally, by examining the burstiness and transdisciplinary structure of citation networks we show that though the field has historically been dominated by empirical articles, it is now starting to show signs of maturity as a flurry of review papers help to consolidate knowledge.

Citation

Harvey, J., Nica-Avram, G., Smith, M., Hibbert, S., & Muthuri, J. (2022). Mapping the landscape of Consumer Food Waste. Appetite, 168, Article 105702. https://doi.org/10.1016/j.appet.2021.105702

• Journal Article Type: Editorial
• Acceptance Date: Sep 21, 2021
• Online Publication Date: Sep 21, 2021
• Publication Date: Jan 1, 2022
• Deposit Date: Oct 28, 2021
• Publicly Available Date: Sep 22, 2022
• Journal: Appetite
• Print ISSN: 0195-6663
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 168
• Article Number: 105702
• DOI: https://doi.org/10.1016/j.appet.2021.105702
• Keywords: Food waste; Consumer behaviour; Consumer Food Waste; Co-citation network; Topic Modelling
• Public URL: https://nottingham-repository.worktribe.com/output/6542398
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S0195666321006097?via%3Dihub