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Factors Influencing AI Chatbot Adoption in Government Administration: A Case Study of Sri Lanka's Digital Governmentopen access

Authors
Rathnayake, Arjuna SrilalNguyen, Truong Dang Hoang NhatAhn, Yonghan
Issue Date
Apr-2025
Publisher
MDPI
Keywords
AI chatbots; digital government; technology acceptance model; sustainable AI adoption; user acceptance; trust; e-government
Citation
ADMINISTRATIVE SCIENCES, v.15, no.5, pp 1 - 29
Pages
29
Indexed
SCOPUS
ESCI
Journal Title
ADMINISTRATIVE SCIENCES
Volume
15
Number
5
Start Page
1
End Page
29
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/125520
DOI
10.3390/admsci15050157
ISSN
2076-3387
2076-3387
Abstract
This study investigates the factors in acceptance of artificial intelligence (AI)-based chatbot application in Sri Lanka's government administration services, which can be applied to developing countries, using an extended technology acceptance model (extended TAM) as a new research framework by adding external constructs such as trust, application design/appearance, and social influence to the technology acceptance model (TAM). Considering the sustainable implementation of AI, it is critical to understand user perspectives given the expanding and intricate integration of AI technology in government operations. Based on previous research, this study provides a structured survey to find out respondents' thoughts on using AI chatbots to enhance government service delivery. With a valid sample size of 207 responses obtained from Sri Lanka, the data were analyzed using a covariance-based structural equation model (CB-SEM) to test the hypothesized relationships. The findings revealed that social influence (SI) has a positive and significant impact on trust (TR). Also, trust and application design (AD) have a positive and significant impact on perceived ease of use (PE), which in turn positively influenced perceived usefulness (PU) and then PE positively influenced attitude (AT) toward behavioral intention (BI) to accept AI chatbot applications in government administrative services. Therefore, this new model proved the effect of new external factors and highlights the importance of those factors in policy implementations for future AI-driven digital government initiatives.
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ERICA 공학대학 (MAJOR IN ARCHITECTURAL ENGINEERING)
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