Evidence map›Paper›PMID 42293191›Full record

ArticleFrontiers in nutrition2026

When tradition meets technology: perceived value integration and consumer purchase behavior in the smart agriculture era.

Yan Zheng, Ziyi Liu, Dayu Cao, Xiaoying Yao, Geng Liu, Qi Tian

Abstract read
In one paragraph

Article in Frontiers in nutrition, 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
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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

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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.

Yan ZhengSchool of Economics and Management, Jiangxi Agricultural University, Nanchang, China.
Ziyi LiuSchool of Economics and Management, Jiangxi Agricultural University, Nanchang, China.
Dayu CaoSchool of Economics and Management, Jiangxi Agricultural University, Nanchang, China.
Xiaoying YaoVocational Normal College, Jiangxi Agricultural University, Nanchang, China.
Geng LiuSchool of Economics and Management, Jiangxi Agricultural University, Nanchang, China.
Qi TianVocational Normal College, Jiangxi Agricultural University, Nanchang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Smart agriculture prompts consumers to reconcile recognition of traditional farming culture with trust in smart agricultural technology when evaluating agri-food products. This study examines how the congruence between these two perceptions influences perceived value integration and purchase behavior. Methods: Survey data from 703 Chinese consumers were analyzed using structural equation modeling and response surface analysis. The study assessed the congruence and incongruence effects of recognition of traditional farming culture and trust in smart agricultural technology on perceived value integration, as well as the mediating role of perceived value integration and the moderating role of trust in government. Results: Greater congruence between recognition of traditional farming culture and trust in smart agricultural technology was associated with higher perceived value integration, whereas incongruence reduced it regardless of direction. Perceived value integration mediated the relationship between the congruence of these two perceptions and purchase behavior. Trust in government negatively moderated the effect of this congruence on perceived value integration. Discussion: The alignment of cultural recognition and technological trust plays an important role in shaping consumer responses to smart agriculture. Cultural narratives and technological credibility should be integrated into marketing communication, while institutional endorsement should be used cautiously to avoid weakening consumers' independent value judgment.

Indexed as

perceived value integrationpurchase behaviorresponse surface analysistechnological trusttraditional farming culture

Identifiers

PMID42293191
PMCPMC13253445

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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.