Tourists’ Experiences with Smart Tourism Technology at Smart Destinations and Their Behavior Intentions

Table 2.
Tourists’ Use of Smart Technology Applications at the Destination (n=1,010).
List of smart technology applications
Frequency 
(%)
Type of Trip
a
Gender
Generation
1
2
3
Male
Female Boomer GenX
GenY
GenZ
Google Maps
780 (77.2)
38
558
169
354
426
99
135
460
86
Ride-sharing program
508 (50.3)
27
345
130
241
267
50
91
316
51
CityGuideApp (museums, parks, landmarks, 
public art, restaurants, real-time traffic)
422 (41.8)
35
275
111
200
222
48
77
251
46
Mobile payment
411 (40.7)
21
282
103
191
220
40
63
258
50
Parking Apps
267 (26.4)
11
173
80
136
131
28
53
157
29
Touchscreens (buying a MetroCard)
254 (25.1)
15
171
67
131
123
26
45
161
22
Airbnb
247 (24.5)
21
138
87
134
113
29
45
156
17
Charging stations
242 (24.0)
18
137
84
130
112
27
44
136
35
Traffic rerouting apps (Greenway, Waze)
237 (23.5)
17
141
75
124
113
25
55
135
22
Rec&Park APP
191 (18.9)
12
101
77
106
85
23
29
114
25
Dynamic kiosk (real-time information about 
traffic, weather, local news) like Urbanflow
182 (18.0)
14
97
71
100
82
10
30
127
15
My TSA
182 (18.0)
19
98
63
104
78
24
47
93
18
Ubiquitous WiFi
150 (14.9)
15
94
39
82
68
17
28
93
12
Smart climate control
140 (13.9)
15
66
59
75
65
8
24
84
24
Emergency alert system
136 (13.5)
7
76
51
70
66
12
25
82
17
Apps for Charities
132 (13.1)
19
39
73
90
42
8
27
84
13
Flight Track Pro
122 (12.1)
10
56
55
67
55
14
18
82
8
Smart street lights
115 (11.4)
18
48
49
72
43
8
26
69
12
Virtual Reality
101 (10.0)
14
39
47
64
37
5
24
56
16
Internet of Things
93 (9.2)
9
41
43
56
37
10
23
49
11
Street bump
91 (9.0)
10
35
46
59
32
5
22
55
9
Mobile NFC/RFID Boarding
90 (8.9)
10
45
33
45
45
7
14
58
11
Surveillance system
83 (8.2)
11
33
39
56
27
6
17
51
9
Augmented Reality
81 (8.0)
13
22
46
62
19
4
20
49
8
Bikesharing
74 (7.3)
8
33
31
50
24
4
18
49
3
CycleTracks
72 (7.1)
9
24
38
49
23
1
14
51
6
Beacon
51 (5.0)
8
19
24
33
18
3
8
36
4
Mobile concierge
48 (4.8)
3
23
22
28
20
5
8
33
2
No. of STTs used
5.6
5.1
4.8
7.6
5.8
5.1
4.2
5.9
5.6
5.0
a
Type of Trip: 1 
=
business; 2 
=
leisure; 3 
=
bleisure.

---

8
 
Journal of Travel Research 00(0)
The structural model showed a good fit with the data
(
χ
2
=
517.74, df 
=
219, CMIN/df 
=
2.36, 
p
=
0.00; NFI 
=
0.92; IFI 
=
0.96; CFI 
=
0.95; RFI 
=
0.91; TLI 
=
0.95; 
RMSEA 
=
0.067). All model fit index values were accept-
able. Table 5 indicates that the relationships between three of 
the four SST constructs (informativeness, interactivity, and 
personalization) and memorable experience were statisti-
cally significant at p
<
.01, lending support for hypotheses 
1b, 1c and 1d. However, the data showed that the relationship 
between accessibility and memorable experience was 
Table 3.
Results of the Measurement Model (n=1,010).
Construct and Measurement Items
Mean (SD)
a
Factor Loadings
Accessibility (composite reliability =0.939; Cronbach 
α
=
0.904; AVE 
=
0.838)
I used smart technology applications anytime and anywhere in the selected city.
5.58 (1.56)
0.89
Smart technology applications were easily available to use in the selected city.
5.75 (1.43)
0.94
In the selected city, smart technology applications were easily accessible.
5.80 (1.37)
0.92
Informativeness (composite reliability 
=
0.927; Cronbach 
α
=
0.883; AVE 
=
0.810)
Smart technology applications provided useful information on the selected city.
5.86 (1.33)
0.89
Smart technology applications assisted me in touring in the selected city.
5.82 (1.34)
0.92
Use of smart technology applications in the selected city completed my trip successfully.
5.85 (1.29)
0.90
Interactivity (composite reliability 
=
0.948; Cronbach 
α
=
0.918; AVE 
=
0.788)
Many other users’ questions, answers, and reviews were available on smart technology 
applications.
5.48 (1.31)
0.88
Smart technology applications were highly responsive to users.
5.65 (1.20)
0.89
It was easy to share local information through smart technology applications.
5.65 (1.28)
0.89
Personalization (composite reliability 
=
0.921; Cronbach 
α
=
0.872; AVE 
=
0.796)
Smart technology applications allowed me to receive tailored information.
5.60 (1.29)
0.88
I could interact with smart technology applications to get personalized information.
5.64 (1.22)
0.91
The personalized information provided by smart technology applications met my need.
5.78 (1.25)
0.89
Memorable Experience (composite reliability 
=
0.927; Cronbach 
α
=
0.895; AVE 
=
0.761)
I had wonderful memories using smart technology applications in the selected city during 
my trip.
5.37 (1.40)
0.89
Smart technology applications made my trip enjoyable in the selected city.
5.54 (1.28)
0.90
Smart technology applications made my trip beneficial in the selected city.
5.59 (1.24)
0.81
My experience with using smart technology applications was unforgettable.
5.23 (1.45)
0.89
Satisfaction (composite reliability 
=
0.918; Cronbach 
α
=
0.867; AVE 
=
0.790)
Overall, I was satisfied with the smart technology available in the selected city.
5.59 (1.09)
0.88
The smart technology available in the selected city exceeded my expectations.
5.87 (1.13)
0.89
The smart technology available in the selected city was close to my ideal technology.
5.42 (1.29)
0.89
Behavior Intention (composite reliability 
=
0.948; Cronbach 
α
=
0.918; AVE 
=
0.859)
I want to visit the selected city again.
6.15 (1.23)
0.92
I would recommend the selected city to family and friends.
6.09 (1.22)
0.94
I would say positive things about the selected city to other people.
6.09 (1.21)
0.93
Note: AVE 
=
average variance extracted.
a
A 7-point Likert-type scale from 1 being strongly disagree to 7 being strongly agree.