Comparing food waste interests and environmental concerns in young adults: A qualitative reasoning approach

IF 2.1 3区心理学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Cognitive Systems Research Pub Date : 2025-01-01 DOI:10.1016/j.cogsys.2024.101318

Konstantina Zacharaki, Queralt Prat-i-Pubill, Jennifer Nguyen, Nil Agell, Núria Agell

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引用次数: 0

Abstract

The large amount of food waste produced worldwide highlights the urgent need to investigate this phenomenon promptly with new methods in order to reduce it. In the present work, we consider a qualitative reasoning approach in an attempt to understand people’s interest in the food waste (FW) problem. In this direction, we run an in-person taste experiment and acquire data from 310 participants. We apply a measure based on hesitant linguistic terms sets (HLTS) to capture the degree of interest towards the environment as individuals respond to the New Environmental Paradigm scale (NEP) (Dunlap et al., 2000). We also calculate an index of hesitancy based on participants’ responses. Previously, they had to decide on whether a piece of fruit allegedly coming from the supermarket tastes better than another one allegedly coming from an alternative source such as applications designed to reduce food waste.

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来源期刊

Cognitive Systems Research 工程技术-计算机：人工智能

CiteScore

9.40

自引率

5.10%

发文量

审稿时长

>12 weeks

期刊介绍： Cognitive Systems Research is dedicated to the study of human-level cognition. As such, it welcomes papers which advance the understanding, design and applications of cognitive and intelligent systems, both natural and artificial. The journal brings together a broad community studying cognition in its many facets in vivo and in silico, across the developmental spectrum, focusing on individual capacities or on entire architectures. It aims to foster debate and integrate ideas, concepts, constructs, theories, models and techniques from across different disciplines and different perspectives on human-level cognition. The scope of interest includes the study of cognitive capacities and architectures - both brain-inspired and non-brain-inspired - and the application of cognitive systems to real-world problems as far as it offers insights relevant for the understanding of cognition. Cognitive Systems Research therefore welcomes mature and cutting-edge research approaching cognition from a systems-oriented perspective, both theoretical and empirically-informed, in the form of original manuscripts, short communications, opinion articles, systematic reviews, and topical survey articles from the fields of Cognitive Science (including Philosophy of Cognitive Science), Artificial Intelligence/Computer Science, Cognitive Robotics, Developmental Science, Psychology, and Neuroscience and Neuromorphic Engineering. Empirical studies will be considered if they are supplemented by theoretical analyses and contributions to theory development and/or computational modelling studies.