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AbstractThe aim of this study is to explore behavioral patterns behind household food waste with partial least square structural equation modeling (PLS-SEM). Results are based on a quantitative consumer survey with personal interviews. Sample (n = 1002) is representative of the adult population of Hungary in regard to age, sex, and geographical distribution. Statistical analysis included descriptive tests, variance analysis, principal component analysis, factor analysis, and PLS-SEM modeling. Based on multivariate tests, income, age, education, residence, and region were identified as the most influential socio-demographical factors of food wastage. Within the framework of the attitude model, the first PLS-SEM model (normative model) validated that all three—cognitive, affective, and conative—attitude components have an effect on food wastage behavior, but the conative component revealed to be the most important one. This underlines the importance of childhood education and awareness raising to shape routines and behavioral patterns with proper messages and impulses. Based on the second PLS-SEM model (explicative model), cooking too much food was identified as the most prominent pattern that influences food wastage. Contrary to anticipations, unplanned food purchase represented only minor significance. The results provided behavioral insights to a national level food waste prevention campaign in Hungary, called Wasteless (Maradék nélkül). This campaign plays an important role to meet the requirements of new EU legislation on food waste and the recommendations of EU Platform on Food Losses and Food Waste.

The aim of this study is to explore behavioral patterns behind household food waste with partial least square structural equation modeling (PLS-SEM). Results are based on a quantitative consumer survey with personal interviews. Sample (n = 1002) is representative of the adult population of Hungary in regard to age, sex, and geographical distribution. Statistical analysis included descriptive tests, variance analysis, principal component analysis, factor analysis, and PLS-SEM modeling. Based on multivariate tests, income, age, education, residence, and region were identified as the most influential socio-demographical factors of food wastage. Within the framework of the attitude model, the first PLS-SEM model (normative model) validated that all three—cognitive, affective, and conative—attitude components have an effect on food wastage behavior, but the conative component revealed to be the most important one. This underlines the importance of childhood education and awareness raising to shape routines and behavioral patterns with proper messages and impulses. Based on the second PLS-SEM model (explicative model), cooking too much food was identified as the most prominent pattern that influences food wastage. Contrary to anticipations, unplanned food purchase represented only minor significance. The results provided behavioral insights to a national level food waste prevention campaign in Hungary, called Wasteless (Maradék nélkül). This campaign plays an important role to meet the requirements of new EU legislation on food waste and the recommendations of EU Platform on Food Losses and Food Waste.