Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Examining the Factors Influencing Diffusion and Adoption of AI Chatbots in Tourism and Travel Industry. / Благов, Евгений Юрьевич; Hanji, Sanjay; Hungund, Sumukh; Desai, Sumanth; Hanji, Savita.
TDIT 2023: Transfer, Diffusion and Adoption of Next-Generation Digital Technologies. 2024. p. 150-160 (Advances in Information and Communication Technology; Vol. 699).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
}
TY - GEN
T1 - Examining the Factors Influencing Diffusion and Adoption of AI Chatbots in Tourism and Travel Industry
AU - Благов, Евгений Юрьевич
AU - Hanji, Sanjay
AU - Hungund, Sumukh
AU - Desai, Sumanth
AU - Hanji, Savita
PY - 2024
Y1 - 2024
N2 - AI chatbots have become increasingly important in various industries, especially with the rise of artificial intelligence and other emerging technologies. Chatbots engage with customers, address common inquiries, and perform specific tasks. The tourism and travel industry uses AI chatbots to enhance customer service for travellers. However, there is a lack of comprehensive research on the adoption of AI chatbots by the customers in tourism sector. To bridge this research gap, the present study utilizes the theoretical lens of Roger’s diffusion model to investigate the factors that impact the adoption of AI chatbots in the tourism and travel industry. The study employs a quantitative research approach with a cross-sectional design and collects data from 495 frequent travellers through random sampling technique using Google forms. The analysis of the data is conducted using the Partial Least Squares (PLS) approach. The study findings show that relative advantage and trialability have a positive impact on adoption of AI chatbots. Compatibility, complexity and observability remain to be hindering factors for its adoption. Trust significantly moderated the relationship between adoption intention and their actual usage. This paper provides valuable and distinctive perspectives for executives, practitioners, and managerial-level employees within the tourism sector, as well as for system designers and creators of AI chatbot technologies.
AB - AI chatbots have become increasingly important in various industries, especially with the rise of artificial intelligence and other emerging technologies. Chatbots engage with customers, address common inquiries, and perform specific tasks. The tourism and travel industry uses AI chatbots to enhance customer service for travellers. However, there is a lack of comprehensive research on the adoption of AI chatbots by the customers in tourism sector. To bridge this research gap, the present study utilizes the theoretical lens of Roger’s diffusion model to investigate the factors that impact the adoption of AI chatbots in the tourism and travel industry. The study employs a quantitative research approach with a cross-sectional design and collects data from 495 frequent travellers through random sampling technique using Google forms. The analysis of the data is conducted using the Partial Least Squares (PLS) approach. The study findings show that relative advantage and trialability have a positive impact on adoption of AI chatbots. Compatibility, complexity and observability remain to be hindering factors for its adoption. Trust significantly moderated the relationship between adoption intention and their actual usage. This paper provides valuable and distinctive perspectives for executives, practitioners, and managerial-level employees within the tourism sector, as well as for system designers and creators of AI chatbot technologies.
KW - Adoption
KW - Artificial intelligence
KW - Chatbots
KW - Diffusion of Innovation
UR - https://www.mendeley.com/catalogue/c14951b2-68cb-3ea4-8b0c-461b8e8fdcd3/
U2 - 10.1007/978-3-031-50204-0_13
DO - 10.1007/978-3-031-50204-0_13
M3 - Conference contribution
SN - 9783031502033
T3 - Advances in Information and Communication Technology
SP - 150
EP - 160
BT - TDIT 2023: Transfer, Diffusion and Adoption of Next-Generation Digital Technologies
T2 - IFIP WG 8.6 International Working Conference on Transfer and Diffusion of IT (TDIT 2023)
Y2 - 15 December 2023 through 16 December 2023
ER -
ID: 116328394