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In a survey of 230 banking app users, human-like, smart, safe chatbots rated better
Study title: Sync or sink: ensuring synchronous service quality for effective human–AI chatbot collaboration
- Evidence type
- Survey
- Sample
- n = 230
- Sources
- 1 sourcePeer-reviewed
- Published
- 2 min read
- Truvace record
- TRV-2026-2693cite or check it
Study title: Sync or sink: ensuring synchronous service quality for effective human–AI chatbot collaboration
A study of mobile banking users examined how the design of AI-powered chatbots affects how well people work with them in real time. Of 263 users with prior chatbot experience surveyed, 230 valid responses were analysed.
Read the study abstract
Purpose This study investigates how the design characteristics of artificial intelligence (AI)-powered chatbots influence user performance in mobile banking, focusing on the mediating role of synchronous service quality. Understanding how consumers collaborate with AI chatbots in real time is increasingly critical as service interactions become more automated. Design/methodology/approach Data were collected from 263 mobile banking users with prior experience using AI-powered chatbots; 230 valid responses were re…
The gain
In a survey of 230 mobile banking users with chatbot experience, chatbots seen as human-like, intelligent and safe were linked to better perceived real-time service quality, which in turn related to better emotional and cognitive task outcomes.
In brief
The results indicate that anthropomorphic design, perceived intelligence and perceived safety each shape how users judge synchronous service quality. That judgment in turn affects task-oriented performance, in both emotional and cognitive terms.
The authors say designers who stress human-likeness, cognitive responsiveness and safety could improve user engagement and service efficiency in mobile banking. The findings come from one service context and a single point in time, so cause and effect and wider applicability remain untested.
Main points
- The survey drew on 263 mobile banking users with prior AI chatbot experience; 230 valid responses were kept.
- Partial least squares structural equation modeling was used to test antecedents and outcomes of synchronous service quality.
- Anthropomorphic design, perceived intelligence and perceived safety each significantly shaped perceived synchronous service quality.
- Perceived synchronous service quality affected task-oriented performance, in both emotional and cognitive responses.
- The authors combine Media Synchronicity Theory with the Computers Are Social Actors paradigm to explain real-time interaction quality.
The full story
Researchers surveyed mobile banking users who had already used AI-powered chatbots and analysed 230 valid responses out of 263 collected. They used partial least squares structural equation modeling to test what drives synchronous service quality and what follows from it.
Three chatbot characteristics, anthropomorphic design, perceived intelligence and perceived safety, all significantly shaped how users perceived real-time service quality. Perceived synchronicity emerged as the mechanism linking those traits to emotional and cognitive performance outcomes.
The authors shift the focus from user attitudes and adoption to how effective the interaction is. They recommend that banks emphasise human-likeness, cognitive responsiveness and safety in chatbot design to improve engagement and service efficiency.
Sources
1 on file- Information Technology & Peopledoi:10.1108/itp-06-2025-0863
Talk it over
Who gets this benefit, and who was left out of the study or story?
In a survey of 230 banking app users, human-like, smart, safe chatbots rated betterhttps://truvace.com/item/sync-or-sink-ensuring-synchronous-service-quality-for-effective-human-ai-chatbot
Who gets this benefit, and who was left out of the study or story?
The gain In a survey of 230 mobile banking users with chatbot experience, chatbots seen as human-like, intelligent and safe were linked to better perceived real-time service quality, which in turn related to better emotional and cognitive task outcomes.
Answer in the threadHow do we know? What can this kind of evidence show, and what can’t it?
The evidence This rests on a survey with a sample of 230, from Information Technology & People.
Answer in the threadWhat does it leave open? What else would you want to know before acting on it?
The record’s own caveat The study covered a single digital service context, mobile banking, and used a cross-sectional design, so generalizability to other services, cultures or over time is unproven.
Answer in the threadHave you seen AI used this way where you study, work or live? Did it go the same way?
Answer in the thread
The questions are the same on every record. The details under them are taken from this record as written.
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