Evidence map›Paper›PMID 36118462›Full record

ArticleFrontiers in psychology2022

Improving consumer stickiness in livestream e-commerce: A mixed-methods study.

Lihong Shen, Yuning Zhang, Ying Fan, Yiduo Chen, Yi Zhao

Abstract read
In one paragraph

Article in Frontiers in psychology, 2022. 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

5 authors.

Lihong ShenCollege of Science and Technology, Ningbo University, Ningbo, China.
Yuning ZhangCollege of Science and Technology, Ningbo University, Ningbo, China.
Ying FanCollege of Science and Technology, Ningbo University, Ningbo, China.
Yiduo ChenCollege of Science and Technology, Ningbo University, Ningbo, China.
Yi ZhaoNingbo City College of Vocational Technology, Ningbo, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the continuous development and improvement of Internet media technologies in China, the influence of livestream e-commerce is becoming increasingly prominent, and an increasing number of people are engaging in consumption activities in this field. It is important to study consumer stickiness in livestream e-commerce to promote economic structure adjustment and innovation-driven development. Therefore, in this study, we adopted the expectation confirmation theory (ECT) as the theoretical framework and analyzed the ECT and stickiness. The study considered satisfaction as the previous influencing factor of user and consumer stickiness, replaced the continuance intention in the expectation confirmation model with consumer stickiness as the explanatory variable, introduced the variable of perceived playfulness as the value perception after user experience, and established a consumer stickiness factors model. A total of 262 valid questionnaires were collected in this study, and SmartPLS analysis along with interviews were used to justify the limitations of data analysis. The results of the study demonstrated a significant effect of perceived usefulness and confirmation on satisfaction, a significant effect of confirmation on perceived usefulness, a significant effect of satisfaction on stickiness, and a significant effect of confirmation on perceived playfulness. Based on findings from the data analysis and interviews, we further proposed rationalized recommendations, and aimed to provide some theoretical guidance for future research on live streaming.

Indexed as

expectation confirmation theorylivestream e-commercemixed-methods studyplayfulnessSmartPLSstickiness

Identifiers

PMID36118462
PMCPMC9473288

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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.