Cost-Cutting or Trust Building: Consumer Motive Inference and Purchase Intention Toward AI-Produced Food

Artificial intelligence (AI) has gradually been applied to food production. Many companies now face a choice between adopting AI technology and adhering to the traditional methods of food production. Existing studies have reported inconsistent findings regarding consumer perceptions of AI-produced food, yet little research has examined how consumers form motive inferences on businesses that transition from traditional practices to adopting AI in new food development. Based on motivation inference theory, this paper investigates the impact of food production methods on consumer inferences and purchase intention. Through three experiments, we find that AI-produced food evokes more negative motive inference in trust building and lowers purchase intention than traditionally produced food. Furthermore, such effect is driven by a serial mediating effect through cost-cutting attribution and perceived ulterior motive. Additionally, it is attenuated when the food company has a high corporate reputation. This research advances research on AI application in food from a consumer motive inference perspective, providing suggestions on firms' adoption of AI-based practices in food production.

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Publication Details

Journal
Foods
Published
2026-04-17
DOI
https://doi.org/10.3390/foods15081405
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00

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article

Cost-Cutting or Trust Building: Consumer Motive Inference and Purchase Intention Toward AI-Produced Food

Yi Quan, Xia Wei, Hengshan Deng, Chenhan Ruan et al.
Foods
AI in Service Interactions
article

Cost-Cutting or Trust Building: Consumer Motive Inference and Purchase Intention Toward AI-Produced Food

Yi Quan, Xia Wei, Hengshan Deng, Chenhan Ruan, Yi Zheng, Xu Li
article en

Abstract

Artificial intelligence (AI) has gradually been applied to food production. Many companies now face a choice between adopting AI technology and adhering to the traditional methods of food production. Existing studies have reported inconsistent findings regarding consumer perceptions of AI-produced food, yet little research has examined how consumers form motive inferences on businesses that transition from traditional practices to adopting AI in new food development. Based on motivation inference theory, this paper investigates the impact of food production methods on consumer inferences and purchase intention. Through three experiments, we find that AI-produced food evokes more negative motive inference in trust building and lowers purchase intention than traditionally produced food. Furthermore, such effect is driven by a serial mediating effect through cost-cutting attribution and perceived ulterior motive. Additionally, it is attenuated when the food company has a high corporate reputation. This research advances research on AI application in food from a consumer motive inference perspective, providing suggestions on firms' adoption of AI-based practices in food production.

FoodsVol. 15(8)
Shenzhen University (CN), Fujian Agriculture and Forestry University (CN)
China Scholarship Council
Zero hunger
Openalex Percentile: Top 20%
AI in Service Interactions
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Cost-Cutting or Trust Building: Consumer Motive Inference and Purchase Intention Toward AI-Produced Food — Yi Quan, Xia Wei, et al. · Foods (2026) | TGRS Research Map | TGRS