Cited by 6AI in Service InteractionsCustomer Service Quality and LoyaltyTechnology Adoption and User Behaviour

The Role of AI Chatbots on E-Commerce Platforms: Understanding its Influence on Customer Trust and Dependability

Christopher, Yabes, Sundjaja, Arta Moro, Mulvono·2024·2024 9th International Conference on Information Technology and Digital Applications (ICITDA)

Abstract

This study investigates the role of AI chatbots in enhancing customer trust and dependability on e-commerce platforms. With the changing landscape of business due to advancements AI chatbots have become crucial tools for customer engagement and simplifying transactions. The study explores factors that affect customer trust, such as chatbot knowledge, humanlike qualities, responsiveness and brand reputation. By collecting data from 209 e-commerce users in Indonesia through a survey using quantitative methods the study discovered that expertise and responsiveness play a significant role in enhancing trust in AI chatbots leading to increased reliance by customers on these systems. Surprisingly, brand reputation alone did not have a direct effect on chatbot trust. The research emphasizes the need to optimize chatbot features to build user trust and suggests that while humanlike characteristics can improve interactions the main focus should be on efficiency. These findings provide insights for businesses looking to use AI chatbots effectively to enhance customer satisfaction and loyalty in today's competitive e-commerce environment.

Integrity signals

Registry

Crossref · 10.1109/icitda64560.2024.10809919

Cites

28 of 28 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

Research works printed but not linked: 2

  1. Le, Designing a concept of chatbot mobile application to en-hance travel experiences using user-centred approach
  2. Hair, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)

Cited by

Sorted by citations

Authors
Christopher, Y., Sundjaja, A. M., & Mulvono
Affiliations
Binus University (ID)
Venue
2024 9th International Conference on Information Technology and Digital Applications (ICITDA)
Publisher
IEEE
Published
2024-11-07
Pages
1-8
OpenAlex
W4405845659
Cited by
5
References
27
Citations by year
2026: 3 · 2025: 2
FWCI
1.44
Type
conference paper
Language
en
Open access
closed
Locations
International Conference on Information Technology and Digital Applications (ICITDA) (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
  • Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Customer Service Quality and Loyalty
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
Keywords
AI chatbots, e-commerce platforms, consumer trust, dependability, chatbot responsiveness, brand reputation, customer satisfaction, customer loyalty

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review