The Determinant Factors of Continuance Use of Customer Service Chatbot in Indonesia E-Commerce: Extended Expectation Confirmation Theory
Abstract
Purpose The implementation of customer service chatbots in various industries is increasingly accepted globally. Previous research has not extensively explored the relationship between chatbot disclosure, technology anxiety, chatbot quality, customer experience and customer satisfaction derived from using chatbot customer service in e-commerce. Therefore, this paper aims to examine the determinant factors of customer service chatbot continuance intention by extending the expectation confirmation theory (ECT). The researchers integrate chatbot quality, technology anxiety and disclosure into ECT to comprehensively understand the phenomena. Design/methodology/approach The quantitative study uses the partial least square structural equation model disjoint two-stage approach with a sample of 310 respondents collected using purposive sampling. Findings The study reveals that perceived usefulness, confirmation and satisfaction positively affect customer service chatbot continuance intentions. Moreover, chatbot disclosure can enhance chatbot quality. However, technology anxiety negatively affects chatbot quality. Originality/value This research contributed to adapting customer service chatbots in Indonesian e-commerce, focusing on chatbot quality, technological anxiety and transparency. Furthermore, it underscores the need for clarity, addresses transaction-specific concerns and artificial intelligence-driven customer assistance in the Indonesian market.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
The empirical research on the effects of agentic commerce is still dispersed but suggests an interrelated set of commerce and psychological effects.
“The empirical research on the effects of agentic commerce is still dispersed but suggests an interrelated set of commerce and psychological effects”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [50]
As systems move toward truly agentic, transaction-executing commerce, the main limitation is measurement: a significant portion of the evidence deduces delegation from adoption or continuation intentions, rather than from direct observation of explicit delegation choices or verified execution.
“As systems move toward truly agentic, transaction-executing commerce [24,40,44,45,50,52,67], the main limitation is measurement: a significant portion of the evidence deduces delegation from adoption or continuation intentions, rather than from direct observation of explicit delegation choices or verified execution.”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [50]
Studies focusing on intention usually follow extended TAM/ECT/TPB logic, in which quality/usefulness and confirmation lead to higher satisfaction and/or attitudes, which then predict continued use, purchase intention, or loyalty.
“Studies that focus on intention usually follow the extended TAM/ECT/TPB logic, which says that quality/usefulness and confirmation lead to higher satisfaction and/or attitudes, which then predict outcomes like continued use, purchase intention, or loyalty”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [50]
Systems designed to minimize friction augment perceived utility and user satisfaction, thereby reinforcing trust and subsequent intention outcomes.
“Systems designed to minimize friction (e.g., expedited information access, simplified input, structured guidance, enhanced navigation) augment perceived utility and user satisfaction, thereby reinforcing trust and subsequent intention outcomes (e.g., retention, purchase intention, reliance-oriented metrics) [6,44,45,48,50,52,67,69].”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [50]
The net-positive pattern is evident in dominant satisfaction/continuance pathways according to numerous studies.
“According to numerous studies [44,46,48,50,69], this pattern is evident in dominant satisfaction/continuance pathways.”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [50]
In the main empirical cluster (Autonomy-1, recommendation/support scope), positive outcomes usually follow a utility/assurance chain: performance cues and interaction quality make people feel more useful and satisfied, which builds trust and leads to downstream adoption/continuance or purchase-intent outcomes.
“In the main empirical cluster (Autonomy-1, recommendation/support scope), positive outcomes usually follow a utility/assurance chain: performance cues and interaction quality make people feel more useful and satisfied, which builds trust and leads to downstream adoption/continuance or purchase-intent outcomes (e.g., [44,46,48,50,69]).”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [50]
Perceived usefulness/satisfaction mediating design cues to trust/continuance and trust mediating performance cues to intention are mediation structures frequently reported in the mapped studies.
“Perceived usefulness/satisfaction mediating design cues → trust/continuance and trust mediating performance cues → intention are two examples of mediation structures frequently reported in the mapped studies [44,46,48,50,69].”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [50]
The utility/assurance lane predominates in cross-sectional SEM studies within the corpus.
“This lane predominates in crosssectional SEM studies within the corpus [44,46,48,50,69].”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [50]
Satisfaction rises via problem-solving, confirmation, usefulness, and interaction/service quality.
“Satisfaction rises via problem-solving, confirmation, usefulness, and interaction/service quality.”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [50]
Satisfaction/CX/perceived service quality is mostly positive, but design can introduce negative affect (reactance, overload).
“Mostly positive, but design can introduce negative affect (reactance, overload)”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [50]
Satisfaction declines when designs trigger reactance or cognitive/affective overload, which depress downstream evaluations.
“It declines when designs trigger reactance or cognitive/affective overload, which depress downstream evaluations.”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [50]
Cites
Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook
Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021) · Classroom Companion: Business · doi:10.1007/978-3-030-80519-7 · Cited by 10,343 · see citing works
Descriptive statistics and normality tests for statistical data
Gupta, A., Mishra, P., Pandey, C., Singh, U., Sahu, C., & Keshri, A. (2019) · Annals of Cardiac Anaesthesia · doi:10.4103/aca.aca_157_18 · Cited by 2,628 · see citing works
AI-based chatbots in customer service and their effects on user compliance
Adam, M., Wessel, M., & Benlian, A. (2021) · Electronic Markets · doi:10.1007/s12525-020-00414-7 · Cited by 1,195 · see citing works
Nguyen, D. M., Chiu, Y.-T. H., & Le, H. D. (2021) · Sustainability · doi:10.3390/su13147625 · Cited by 269 · see citing works
Can AI chatbots help retain customers? Impact of AI service quality on customer loyalty
Chen, Q., Lu, Y., Gong, Y., & Xiong, J. (2023) · Internet Research · doi:10.1108/intr-09-2021-0686 · Cited by 260 · see citing works
Creepiness: Its antecedents and impact on loyalty when interacting with a chatbot
Rajaobelina, L., Prom Tep, S., Arcand, M., & Ricard, L. (2021) · Psychology & Marketing · doi:10.1002/mar.21548 · Cited by 252 · see citing works
Chatbots or me? Consumers’ switching between human agents and conversational agents
Li, C.-Y., & Zhang, J.-T. (2023) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2023.103264 · Cited by 128 · see citing works
Is chatting with a sophisticated chatbot as good as chatting online or FTF with a stranger?
Drouin, M., Sprecher, S., Nicola, R., & Perkins, T. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2021.107100 · Cited by 75 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Balaskas, S. (2026) · Information · doi:10.3390/info17030222 · Cited by 8 · see citing works
- Authors
- Sundjaja, A. M., Utomo, P., & Colline, F.
- Affiliations
- Binus University (ID)
- Multimedia Nusantara University (ID)
- Krida Wacana Christian University (ID)
- Corresponding author
- Sundjaja, Arta Moro
- Venue
- Journal of Science and Technology Policy Management
- Publisher
- Emerald
- Published
- 2024-10-22
- Volume
- 16
- Issue
- 1
- Pages
- 182-203
- ISSN
- 2053-4620 (ISSN-L)
- 2053-4639
- OpenAlex
- W4403544019
- Cited by
- 24
- References
- 8
- Citations by year
- 2026: 12 · 2025: 12
- FWCI
- 3.55
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Science and Technology Policy Management (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Customer Service Quality and Loyalty
- Keywords
- customer service chatbots, continuance intention, expectation confirmation theory, technology anxiety, perceived usefulness, customer satisfaction, customer experience, e-commerce, Indonesian e-commerce
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