Evidence map›Paper›PMID 40596391›Full record

ArticleScientific reports2025

Exploring the varying effects of chatbot service quality dimensions on customer intentions to switch service agents.

Shaoyuan Chen, Pengji Wang, Jacob Wood

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 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

3 authors.

Shaoyuan ChenSchool of Management, Wenzhou Business College, Wenzhou, China.
Pengji WangJCUS Business School, James Cook University Singapore Campus, 149 Sims Drive, Singapore, 387380, Singapore. pengji.wang@jcu.edu.au.
Jacob WoodJCUS Business School, James Cook University Singapore Campus, 149 Sims Drive, Singapore, 387380, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to explore how the different dimensions of chatbot service quality influence customers' service-switching intentions when shopping online. The dimensions of chatbot service quality are identified through a critical review of the relevant literature. Subsequently, a structural equation model is applied to test the hypotheses utilizing 575 valid responses. This study reveals that synchronicity and perceived humanness do not have a significant direct impact on customers' willingness to switch from human services to chatbot services but ability to understand and problem resolution do. Moreover, perceived shopping enjoyment fully mediates the impact of synchronicity and perceived humanness, and partially mediates the impact of ability to understand and problem resolution on customers' intentions to choose chatbot services. Additionally, active control moderates the impact of ability to understand on willingness to switch. These findings empirically validate that the four dimensions of chatbot service quality are applicable to the context of the retail e-commerce industry and service quality research should consider specific industry contexts in which the services are delivered.

Indexed as

CommerceConsumer BehaviorIntentionAdultFemaleGenerative Artificial IntelligenceHumansInternetMaleMiddle AgedSurveys and QuestionnairesChatbot serviceService choiceService qualityService-switchingShopping enjoyment

Identifiers

PMID40596391
PMCPMC12217029

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.