Evidence map›Paper›PMID 40426451›Full record

ArticleBehavioral sciences (Basel, Switzerland)2025

The Influence of the Information Richness of Interfaces on Consumers' Purchase Intention: The Sequential Mediating Effects of Cognitive Load, Mental Imagery, and Flow Experience.

Jiayue Guo, Yuemeng Zhao, Wenqian Zhang, Ke Lu, Xiaochen Feng, Tiansheng Xia

Abstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Jiayue GuoSchool of Art & Design, Guangdong University of Technology, Guangzhou 510090, China.
Yuemeng ZhaoSchool of Art & Design, Guangdong University of Technology, Guangzhou 510090, China.
Wenqian ZhangSchool of Art & Design, Guangdong University of Technology, Guangzhou 510090, China.
Ke LuSchool of Art & Design, Guangdong University of Technology, Guangzhou 510090, China.
Xiaochen FengSchool of Public Administration and Policy, Dalian University of Technology, Dalian 116024, China.
Tiansheng XiaSchool of Art & Design, Guangdong University of Technology, Guangzhou 510090, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

E-commerce live streaming attracts consumers by displaying product information and anchor introductions. However, the complexity and variety of interface information pose challenges in design, and research on live-streaming interface design remains limited. This study examines how patch design affects the customer experience in live-streaming rooms, considering different product types and virtual backgrounds. Based on the flow theory and the Stimulus-Organism-Response model, we conducted experiments simulating live-streaming scenarios and collected behavioral and eye-tracking data. Our results confirmed that cognitive load negatively mediates, while mental imagery and flow experience positively mediate, the relationship between patch design and consumer behavior. Additionally, the interaction between product type and virtual background proximity was revealed, with product type moderating the effect of cognitive load on purchase behavior. This study contributes to understanding the impact of live-streaming interface design on consumer experience and purchase behavior, providing design guidelines for online retailers and managerial insights for retail platforms.

Indexed as

cognitive loade-commerce live streamingflowinterface designpurchase behavior

Identifiers

PMID40426451
PMCPMC12108799

What OpenQuestion holds

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Registered trials

None linked

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.