Evidence map›Paper›PMID 40414907›Full record

ArticleScientific reports2025

Research on the purchase intention of museum digital cultural and creative products based on value adoption model.

Mengen Gu, Tongtong Zhao

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Mengen GuSchool of Art, Hunan University of Information Technology, Maotang Industrial Park, Xingsha Economic Development Zone, Changsha, 410151, Hunan Province, China.
Tongtong ZhaoSchool of Fine Arts, Hunan Normal University, 638 Lushan South Road, Yuelu District, Changsha, 410012, Hunan Province, China. melvingu6530@gmail.com.

Funding

General Projects of the Social Science Achievement Evaluation Committee of Hunan Province No. XSP24YBC253
6 · The paper itself

Abstract

Museum digital cultural and creative products rejuvenate ancient treasures and promote the development of cultural and creative industries. With the surge in purchases over the past few years, investigating the underlying factors has become a compelling question. Therefore, based on the Value-Based Adoption Model, this paper explores the factors and intrinsic mechanisms influencing consumers' purchase decisions regarding these products. The collected data were analyzed using SPSS for preliminary analysis, and structural equation modeling was conducted using AMOS to test the research hypotheses. Results showed: (1) Perceived benefits positively influence purchase intention and value. (2) Perceived sacrifices negatively influence purchase intention and value. (3) Perceived value positively influences purchase intention and mediates the effects of perceived benefits and sacrifices. (4) Social influence positively moderates the relationship between perceived value and purchase intention. Specifically, entertainment experience, cultural experience, and perceived value positively influence purchase intention, while perceived cost and perceived risk negatively impact it. Based on these findings, developers should enhance product playability and cultural significance. Relevant departments should employ various strategies to reduce consumers' cybersecurity risks and copyright issues during shopping while also minimizing selling costs to attract more consumer attention and purchases.

Indexed as

Consumer BehaviorCreativityIntentionMuseumsAdultCommerceCultureFemaleHumansMaleMiddle AgedSurveys and QuestionnairesYoung AdultConsumer behaviorCultural and creative industriesMuseum digital productsPurchase intentionValue-based adoption model

Identifiers

PMID40414907
PMCPMC12104383

What OpenQuestion holds

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LicenceCC BY
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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.