Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 533690
Title Model selection and averaging in the assessment of the drivers of household food waste to reduce the probability of false positives
Author(s) Grainger, Matthew James; Aramyan, Lusine; Piras, Simone; Quested, Thomas Edward; Righi, Simone; Setti, Marco; Vittuari, Matteo; Stewart, Gavin Bruce
Source PLoS One 13 (2018)2. - ISSN 1932-6203
DOI http://dx.doi.org/10.1371/journal.pone.0192075
Department(s) WASS
LEI Consumer and Chain
Publication type Refereed Article in a scientific journal
Publication year 2018
Abstract Food waste from households contributes the greatest proportion to total food waste in developed countries. Therefore, food waste reduction requires an understanding of the socioeconomic (contextual and behavioural) factors that lead to its generation within the household. Addressing such a complex subject calls for sound methodological approaches that until now have been conditioned by the large number of factors involved in waste generation, by the lack of a recognised definition, and by limited available data. This work contributes to food waste generation literature by using one of the largest available datasets that includes data on the objective amount of avoidable household food waste, along with information on a series of socio-economic factors. In order to address one aspect of the complexity of the problem, machine learning algorithms (random forests and boruta) for variable selection integrated with linear modelling, model selection and averaging are implemented. Model selection addresses model structural uncertainty, which is not routinely considered in assessments of food waste in literature. The main drivers of food waste in the home selected in the most parsimonious models include household size, the presence of fussy eaters, employment status, home ownership status, and the local authority. Results, regardless of which variable set the models are run on, point toward large households as being a key target element for food waste reduction interventions.
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