Evidence map›Paper›PMID 42073294›Full record

ArticleFoods (Basel, Switzerland)2026

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

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

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Chenhan RuanSchool of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou 350002, China.ORCID 0000-0002-4023-3779
Yuanyuan QuanSchool of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Xu LiSchool of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Yi ZhengSchool of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Hengshan DengSchool of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Xia WeiSchool of Management, Shenzhen University, Shenzhen 518060, China.ORCID 0000-0002-9555-6209

Funding

Fujian Provincial Department of Finance Higher Education Subsidy Fund KSYC2513AGuangdongProvincial Philosophy and Social Sciences Planning Fund GD25CSG33Ministry of Education Fund for Humanities and Social Sciences 24YJA630095Program of China Scholarship Council CSC202508350040
6 · The paper itself

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.

Indexed as

artificial intelligencecorporate reputationfood productionmotive inference

Identifiers

PMID42073294
PMCPMC13115341

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.