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Forecasting food trends using demographic pyramid, generational differentiation and SuperLearner

Food Science and Technology

Forecasting food trends using demographic pyramid, generational differentiation and SuperLearner

D. Loginova and S. Mann

This innovative study predicts food consumption patterns across social groups until 2050 using extensive Swiss household data. With insights from Daria Loginova and Stefan Mann, discover how generational changes impact our dining tables in the future.

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Playback language: English
Abstract
This paper aims to predict future food consumption patterns for different social groups, considering generational changes. Using over 20 million Swiss household observations (1990-2017), four forecasting techniques are developed and applied, progressing from linear extrapolations to population-driven models. Each method defines social groups based on household characteristics, projects the group proportions until 2050, forecasts consumption of 75 food items for each group, and weighs these to obtain aggregate consumption. Despite variations across food items and methods, the results converge on a narrow range of future consumption until 2050. The study offers insights into forecasting techniques using big data and future food consumption.
Publisher
Humanities & Social Sciences Communications
Published On
Oct 28, 2024
Authors
Daria Loginova, Stefan Mann
Tags
food consumption
social groups
forecasting techniques
big data
generational changes
Swiss households
aggregate consumption
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