Evidence map›Paper›PMID 34744902›Full record

ArticleFrontiers in psychology2021

Factors Affecting Consumers' Online Choice Intention: A Study Based on Bayesian Network.

Weibin Deng, Ting Su, Yiming Zhang, Chunli Tan

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.6field-weighted citation impact, top 10% of its field
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

3 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
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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

4 authors at 1 institution in 1 country.

Weibin DengKey Laboratory of Electronic Commerce and Modern Logistics, Chongqing University of Posts and Telecommunications, Chongqing, China.
Ting SuKey Laboratory of Electronic Commerce and Modern Logistics, Chongqing University of Posts and Telecommunications, Chongqing, China.
Yiming Zhang78111 Troops, People's Liberation Army of China, Chengdu, China.
Chunli TanKey Laboratory of Electronic Commerce and Modern Logistics, Chongqing University of Posts and Telecommunications, Chongqing, China.
Chongqing University of Posts and Telecommunications · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In China, the mature development of online retail channels provides consumers with multiple consumption choices, and the factors that affect whether consumers choose to search or purchase online are numerous and complex. In this context, this paper reports on experimental research regarding consumers' willingness to choose channels based on the two-stage decision-making theory. Using structural equation modeling, the factors influencing consumers' online search intention and purchase willingness and the relationship between them are studied. In particular, the perceived benefits, channel trust, and channel transfer costs are explored. Furthermore, a Bayesian network is used in order to analyze the degree of influence of each factor quantitatively. It is found that online trust is an important factor affecting consumers' online search intention, and the most important factor for consumers' online purchase intention is their perceived benefits of online shopping. At the same time, there is a positive relationship between online search intention and purchase intention. This study can provide management decision support for online retail enterprises and help to promote the healthy development of online shopping.

Indexed as

Bayesian networkpurchase intentionsearch intentionstructural equation modeltwo-stage decision-making theory

Identifiers

PMID34744902
PMCPMC8563582
OpenAlexW3205424334

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.