Work

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

Year: 2026

Type: article

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.

Source: Foods

DOI: 10.3390/foods15081405

Authors: Chenhan Ruan, Yuanyuan Quan, Xu Li, Yi Zheng, Hengshan Deng, Xia Wei

Institutions: Fujian Agriculture and Forestry University, Shenzhen University

Language: English

Topic: AI in Service Interactions

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Zero hunger

Open Access status: gold

Estimated APC paid: $3,499