Is AI Food a Gimmick or the Future Direction of Food Production?—Predicting Consumers’ Willingness to Buy AI Food Based on Cognitive Trust and Affective Trust

In recent years, artificial intelligence (AI) has been developing rapidly and has had a broad impact on the food industry, with food produced from AI-generated recipes already appearing to actually go on sale. However, people's trust and willingness to purchase AI food are still unclear. This study builds an integrated theoretical model based on cognitive trust and affective trust, taking into account consumers' quality value orientations, social norms, and perceived risks of AI food, with the aim of predicting and exploring consumers' trust and acceptance of AI food. This study utilized the questionnaire method and 315 questionnaires were collected. The results of structural equation modeling (PLS-SEM) indicated that food quality orientation, subjective norms, perceived trust, and affective trust all had a significant positive effect on consumers' purchase intentions. Perceived risk had a negative effect on affective trust and consequently on consumers' purchase intention, but the effect on cognitive trust was not significant. The results also suggest that cognitive trust is the basis of affective trust and that consumer trust and acceptance of AI food can be enhanced by augmenting two antecedents of cognitive trust (food quality orientation and subjective norms). Possible practical implications and insights from the current findings are discussed.

Authors

Institutions

Publication Details

Journal
Foods
Published
2024-09-20
DOI
https://doi.org/10.3390/foods13182983
Citations
11
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
12.45
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Is AI Food a Gimmick or the Future Direction of Food Production?—Predicting Consumers’ Willingness to Buy AI Food Based on Cognitive Trust and Affective Trust

Tiansheng Xia, Xiaoqi Shen, LI Lin-li
11 citations
Foods
Digital Marketing and Social Media
12.45
article

Is AI Food a Gimmick or the Future Direction of Food Production?—Predicting Consumers’ Willingness to Buy AI Food Based on Cognitive Trust and Affective Trust

Tiansheng Xia, Xiaoqi Shen, LI Lin-li
article en
11 citations

Abstract

In recent years, artificial intelligence (AI) has been developing rapidly and has had a broad impact on the food industry, with food produced from AI-generated recipes already appearing to actually go on sale. However, people's trust and willingness to purchase AI food are still unclear. This study builds an integrated theoretical model based on cognitive trust and affective trust, taking into account consumers' quality value orientations, social norms, and perceived risks of AI food, with the aim of predicting and exploring consumers' trust and acceptance of AI food. This study utilized the questionnaire method and 315 questionnaires were collected. The results of structural equation modeling (PLS-SEM) indicated that food quality orientation, subjective norms, perceived trust, and affective trust all had a significant positive effect on consumers' purchase intentions. Perceived risk had a negative effect on affective trust and consequently on consumers' purchase intention, but the effect on cognitive trust was not significant. The results also suggest that cognitive trust is the basis of affective trust and that consumer trust and acceptance of AI food can be enhanced by augmenting two antecedents of cognitive trust (food quality orientation and subjective norms). Possible practical implications and insights from the current findings are discussed.

FoodsVol. 13(18)
Guangdong University of Technology (CN)
Zero hunger
Openalex Percentile: Top 1%
Digital Marketing and Social Media
12.45
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.