New technologies have transformed the way businesses around the world communicate with customers. The tourism industry has kept abreast of developments and adopted new service delivery methods. Aided by artificial intelligence, chatbots reshape tourists’ attitudes by accompanying themduring all stages of their journey, from planning to travelling, providing exceptional convenience benefits as well as autonomy in time and place. Tourist enterprises offer the solution of chatbots as a communication and service alternative for saving money and human resources.

The present research attempts to investigate the factors influencing users’ chatbot adoption intention. The relevant literature review from 2017 to 2022 reveals that anthropomorphism and perceived intelligence are common factors influencing adoption intention. Habit, social influence, performance expectancy as well as trust, utility, interaction, and attitudes, in combination with variables affecting chatbot quality, such as reliability, understandability, and assurance, also affect usage. In addition, the research can trigger investigation and assessment of the factors encouraging users and non-users to take advantage of chatbots to a great extent, and encourage further research of various other factors, which have not yet been explored.

1.
M.
Fannakhosrow
,
S.
Nourabadi
,
D. T. N.
Huy
,
T. D
Nguyen
, and
M. A.
Tashtoush
, ‘A Comparative Study of Information and Communication Technology (ICT)-Based and Conventional Methods of Instruction on Learners. Academic Enthusiasm for L2 Learning’.
Educational Research International
,
Hindawi
(
2022
).
2.
Z.
Khan
,
S.
Afifa
, and
W.L.
Chang
, ‘
Robotics Utilization for Healthcare Digitization in Global COVID-19 Management
’.
International Journal of Environmental Research and Public Health.
17
(
11
),
3819
(
2020
).
3.
N.
Carlino
, ‘
With Online Tool, Hotels Can Offer Personalization in a Socially Distant World. Hotel Business (online)
’, https://www.hotelbusiness.com/with-online-tool-hotels-can-offer-personalization-in-a-socially-distant-world/ (
2020
) (Accessed 8 October 2022).
4.
C. M.
Kuo
,
L. C.
Chen
, and
C.Y.
Tseng
, ‘
Investigating an innovative service with hospitality Robots
’,
International Journal of Contemporary Hospitality Management.
29
(
5
),
1305
1321
. DOI: (
2017
).
5.
S.
Ivanov
, and
C.
Webster
, ‘
Robots in tourism: a research agenda for tourism economics
’,
Tourism Economics.
26
(
7
),
1065
1085
(
2019b
).
6.
C.
Prentice
,
S. D.
Lopesand
and
X.
Wang
, ‘
The impact of artificial intelligence and employee service quality on customer satisfaction and loyalty
’,
Journal of Hospitality Marketing & Management.
1
. DOI: (
2020
).
7.
O. H.
Chi
,
G.
Denton
and
D.
Gursoy
Artificially intelligent device use in service delivery: A systematic review, synthesis and research agenda
’,
Journal of Hospital Marketing Management.
29
,
757
786
(
2020
).
8.
M.
Ivanovic
and
M.
Semnic
, ‘
The Role of Agent Technologies in Personalized Medicine
’. In:
2018 5th International Conference on Systems and Informatics (ICSAI)
, (
2018
),
IEEE
, pp.
299
304
.
9.
P.B.
Brandtzaeg
, and
A.
Folstad
, ‘
Why People Use Chatbots
’,
International Conference on Internet Science
,
Thessaloniki
, 22-24 November 2017,
377
392
. (
2017
)
10.
J. F.
Almahri
,
D.
Bell
and
M.
Merhi
, ‘
Understanding student acceptance and use of chatbots in the United Kingdom universities: a structural equation modeling approach
’ In:
6th IEEE International Conference on Information Management
, (
IEEE Xplore
,
UK
,
2020
),
284
288
.
11.
D.R.
Cardona
,
A.
Janssen
,
N.
Guhr
,
M.H.
Breitnet
and
J.
Milde
, ‘
A matter of trust? Examination of chatbot usage in insurance business
’,
In: Proceedings of the 54th Hawaii International Conference on System Sciences, 2021
Maui, Hawaii
(
2021
).
12.
K.
Kvale
,
E.
Freddi
,
S.
Hodnebrog
,
O.A.
Sell
and
A.
Folstad
, ‘
Understanding the user experience of customer service chatbots: what can we learn from customer satisfaction surveys?
’,
Chatbot Research and Design, 4th International Workshop
, Nov 23-24, pp.
205
218
(
2021
).
13.
M.
Gonzalez
,
S.T.D.
Gutierrez
and
G.J.
Bulchand
, ‘
Predicting the intentions to use chatbots for travel and tourism
’.
Current Issues in Tourism.
24
(
2
),
192
210
(
2021
).
14.
E.
Mogaji
,
J.
Balakrishnan
,
C.A.
Nwoba
and
P.
Nguyen
, ‘Emerging-market consumers’ interactions with banking chatbots’,
Telematics and Informatics
.
65
, pp.
101711
.
Elsevier
(
2021
).
15.
T.
Nadarzynski
,
O.
Miles
,
A.
Cowie
and
D.
Ridge
, ‘
Acceptability of artificial intelligence (AI)-led chatbot services in healthcare: a mixed-methods study
’,
Digital Health.
5
,
1
12
(
2019
).
16.
S.
Boiano
,
A.
Borda
, and
G.
Guiliano
, ‘
Participatory innovation and prototyping in the cultural sector: a case study’.
DOI: (
2019
).
17.
M.
Dash
and
S.
Bakshi
, ‘
An exploratory study of customer perceptions of usage of chatbots in the hospitality industry
’,
International Journal on Customer Relations.
7
(
2
),
27
33
(
2019
).
18.
A.
Dalgic
, and
K.
Birdir
, ‘Smart hotels and technological applications’. In
E.
Çeltek
(Ed.),
Handbook of Research on Smart Technology Applications in the Tourism Industry
, edited by E. Çeltek (Ed.), (pp.
323
343
). (
IGI Global
, 2020) (
2020
).
19.
D.
Cai
,
H.
Li
and
R.
Law
, ‘
Anthropomorphism and OTA chatbot adoption: a mixed methods study
’,
Journal of Travel & Tourism Marketing.
39
(
2
)
228
255
. DOI: (
2022
).
20.
R.
Pillai
, and
B.
Sivathanu
, ‘
Adoption of AI-based chatbots for hospitality and tourism
’,
International Journal Contemporary Hospitality Management.
32
(
10
),
3199
226
(
2020
).
21.
F.
Rafiq
,
N.
Dogra
,
M.
Adil
, and
J.Z.
Wu
, ‘
Examining Consumer’s Intention to Adopt AI-Chatbots in Tourism Using Partial Least Squares Structural Equation Modeling Method
’.
Mathematics
,
10
,
2190
. (
2022
).
22.
E.
Go
and
S.S.
Sundar
, ‘
Humanizing chatbots: The effects of visual, identity and conversational cues on humanness perceptions
’,
Computers in Human Behavior.
97
,
304
316
(
2019
).
23.
C.
Yu
, ‘
Humanlike robots as employees in the hotel industry: Thematic content analysis of online reviews
’,
Journal of hospitality marketing & management.
29
(
1
),
22
38
. DOI: (
2019
).
24.
N.
Mirnig
,
G.
Stollnberger
,
M.
Miksch
,
S.
Stadler
,
M.
Giuliani
, and
M.
Tscheligi
, ‘
To Err Is Robot: How Humans Assess and Act toward an Erroneous Social Robot
’,
Frontiers in Robotics and AI.
4
(
21
). DOI: (
2017
).
25.
L.
Li
,
K.Y.
Lee
,
E.
Emokpae
, and
S.B.
Yang
, ‘
What makes you continuously use chatbot services? Evidence from Chinese online travel agencies
’,
Electronic Marketing.
Doi: (
2021
).
26.
W.C.
Cho
,
K.Y.
Lee
, and
S. B.
Yang
, ‘
What makes you feel attached to smartwatches? The stimulus–organism–response (S–O–R) perspectives
’,
Information Technology & People.
32
(
2
)2,
319
343
(
2019
).
27.
V.
Venkatesh
,
J.Y.L.
Thong
, and
X.
Xu
, ‘
Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology
’,
MIS Quarterly Management Information Systems.
36
(
1
),
157
78
(
2012
).
28.
S.
Kuberkar
, and
T.K.
Singhal
, ‘
Factors influencing adoption intention of AI powered chatbot for public transport services within a smart city
’,
International Journal of Emerging Technologies.
11
(
3
),
948
58
(
2020
).
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