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

Table 5.
Standardized Structural Estimates and Hypotheses Tests.
Hypothesis/Path
Estimate
SE
t
Value
Results
Hypothesis 1a: Accessibility 
→
Memorable experience
0.06
0.05
1.25
Not supported
Hypothesis 1b: Informativeness 
→
Memorable experience
0.22*
0.07
2.93
Supported
Hypothesis 1c: Interactivity 
→
Memorable experience
0.53**
0.10
5.21
Supported
Hypothesis 1d: Personalization 
→
Memorable experience
0.28*
0.10
2.84
Supported
Hypothesis 3: Memorable experience 
→
Satisfaction
0.75**
0.03
28.94
Supported
Hypothesis 4: Satisfaction 
→
Intention
0.50**
0.12
4.13
Supported
Hypothesis 5: Memorable experience 
→
Intention
0.26*
0.10
2.65
Supported
R
2
for memorable experience 
=
.70; 
R
2
for satisfaction 
=
.86; 
R
2
for Intention 
=
.51.
χ
² 
=
1084.61, df 
=
196, CMIN/df 
=
5.53, NFI 
=
0.94, IFI 
=
0.95, TLI 
=
0.95, CFI 
=
0.95, RMSEA 
=
0.067.
*p 
<
.01, **p 
<
.001.
Table 6.
Moderating Effect Tests of Security/Privacy.
Δχ
²
Regression weight (L)
a
Regression weight (H)
b
Hypothesis Test
Hypothesis 2a
Accessibility

Memorable Experience
3.28
−0.08
−0.04
Not supported
Hypothesis 2b
Informativeness

Memorable Experience
8.01
0.10
0.28
Supported
Hypothesis 2c
Interactivity

Memorable Experience
4.73
0.60
0.48
Supported
Hypothesis 2d
Personalization

Memorable Experience
4.69
0.37
0.23
Supported
Note: 
χ
² 
=
1412.38, df 
=
392, CMIN/df 
=
3.60, NFI 
=
0.93, IFI 
=
0.95, TLI 
=
0.94, CFI 
=
0.95, RMSEA 
=
0.051.
a
Less concerned about security/privacy.
b
highly concerned about security/privacy.
**p 
<
.01, ***p 
<
.001, 
Δχ
²
0.05,1
= 3.84.

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10
 
Journal of Travel Research 00(0)
The effect of informativeness on memorable experience was 
significantly stronger for the low familiar group (
β
=
0.300, 
p
<
.01) than the high familiar group (
β
=
0.01, p
>
.05), 
which indicated that the less familiar respondents wanted 
more reliable, real-time, and accurate information than the 
more familiar respondents did for enhancing their travel 
experience. However, personalization significantly and posi-
tively affected the high familiar group (
β
=
0.506, p
<
.001) 
stronger than the low familiar group (
β
=
0.124, p
>
.05). 
Thus, respondents with high STT familiarity had more mem-
orable experience than those with low STT familiarity when 
STTs suited their own needs and offered personalized and 
customized features.
Conclusion
As one of a few empirical studies in the field of STTs and 
tourists’ experience at the smart tourism destinations, this 
study identified, in general, tourists used various STTs and 
had memorable travel experience in the select US smart tour-
ism destinations. As expected, such STTs as Google maps, 
ride-sharing programs, city guide app, mobile payment, and 
parking apps were tourists’ top five most used STTs at the 
smart tourism destinations. Even though the majority of 
respondents consisted of generation Y, advanced digital 
STTs such as virtual reality, IoTs, augmented reality, and 
mobile concierge were not commonly used at smart tourism 
destinations, yet.
Adopting the four attributes of STTs from the studies of 
Huang et al. (2017) and No and Kim (2015), this study 
attempted to measure key STT attributes that affected tour-
ists’ memorable experience, which in turn led to their satis-
faction with STTs and future behavior intention to visit the 
destination again. Findings of this study indicated that inter-
activity, personalization, and informativeness appeared to be 
the key factors that affected tourists’ memorable experience. 
Accessibility was not a main factor for tourists to maximize 
the memorability of their experience. This might be due to 
the current technological infrastructure of smart tourism des-
tinations in the sense that the cities selected for this study 
were all advanced smart cities in the United States and were 
fully equipped with a high capacity of bandwidth.
Of the three significant STT attributes, interactivity was 
the most influential contributor to tourists’ memorable travel 
experience. Reasons may be that various interactive features 
of STTs at the destinations helped tourists be more engaged 
in tourism activities, keep them informed about all events 
and activities, build social space in a digital environment, 
and share with others about their memorable and unique 
travel experience. These technology-based travel experi-
ences could induce high satisfaction with STTs and stronger 
intent to visit the destinations again. STTs’ personalization 
was also an influential feature that enhanced tourists’ experi-
ence at the destinations. By recognizing individual tourists’ 
requests, needs, and issues and by offering tailored responses 
and services, STTs could play a role of self-operated tour 
guides and help tourists actively participate in their inter-
ested tourism activities. Another influential attribute of STTs 
was informativeness. STTs’ quality and trustworthy features 
were starting points for tourists to build a loyal relationship 
with the destination. Using STTs at destinations enables 
tourists to enjoy their trip with degrees of freedom and inde-
pendence and to participate selectively in unique and memo-
rable tourism activities to maximize their travel experience.
The perceptions of security/privacy in using STTs at des-
tinations moderated the relationships between the three STT 
attributes—informativeness, interactivity, and personaliza-
tion—and tourists’ memorable experience. Findings showed 
that the respondents would use STTs more for their memo-
rable experience in a high-security/privacy-protected envi-
ronment than in a less protected environment in the sense 
that they viewed STTs as carriers of high quality and trust-
worthy information as well as enhancers of tailored service 
and interactions. Thus, for an effective use of STTs at smart 
tourism destinations, tourists need a technological environ-
ment with a high level of guaranteed security and privacy of 
the users.
Findings of this study offer both theoretical and practical 
implications. Although the researchers adopted four attri-
butes of STTs from the previous studies (i.e., Huang et al. 
2017), the context of the present study was different from 
that of Huang et al.’s (2017). Their study examined how trav-
elers used STTs in planning their travel in order to maximize 
their travel satisfaction, while the present study focused on 
evaluating respondents’ actual use of STTs at smart tourism 
destinations in the post travel stage. Apparently, the results of 
this study are slightly different from those of Huang et al.’s 
(2017). From the theoretical perspective, by examining the 
importance of the four STT attributes and their relationships 
with tourists’ memorable experience, this study found that 
three of the four STT attributes, Interactivity (
β
=.53), 
Personalization (
β
=.27), and Informativeness (
β
=.21), were 
positively and statistically significant factors affecting tour-
ists’ memorable experience at smart tourism destinations. 
The memorable experience appears to be a key predictor of 
tourists’ satisfaction with STTs (
β
=
.75, p 
<
0.001) and 
behavior intention (
β
=
.26, p 
<
0.01). In contrast, Huang 
et al. (2017) examined tourists’ perceived travel satisfaction 
(i.e., transaction and travel experience) by using second-
order STT attributes to understand how respondents per-
ceived and used STTs at the pretravel stage. In their study, 
STTs included online-based tourism applications and travel 
agents, blogs, websites, social media, and smartphone apps. 
The present study, however, examined how the respondents 
used 28 different STTs and tested their effectiveness based 
on the four attributes of STTs.
The current study seems to be one of the first attempts to 
evaluate tourists’ holistic experience with STTs after they 
used them at smart tourism destinations, instead of measur-
ing the effects of STT usage on tourists’ travel satisfaction at 

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Jeong and Shin 
11
the pretravel stage. Although Huang et al. (2017) identified 
the key STT attributes and examined customers’ satisfaction 
with STTs, their study focused on use of STTs for travel 
planning, while this study centered on SST usage at smart 
tourism destinations based on actual experiences and recall 
of such experiences. Additionally, by examining the explana-
tory power of tourists’ memorable experience with STTs in 
the proposed model (R
2
=
.70), this study asserted that the 
three STT attributes could be key indicators in measuring the 
effectiveness of STTs in smart tourist destination. This study 
also confirmed the importance of perceived security/privacy 
when tourists used STTs at destinations as shown in its mod-
erating effects in multigroup analyses.
This study provides destination tourism organizations with 
practical insights into effective deployment of STTs at destina-
tions to enhance tourists’ memorable experience. Regardless 
of tourists’ age, the majority of tourists used at least two STTs 
from their smartphone while traveling in the destination. 
Tourists’ usage rate of STTs at destinations expects to increase 
in the future. To accommodate tourists’ needs and their pre-
ferred environment for STT usage, destination marketers 
should ensure high performance on at least three key 
STT attributes, namely, Interactivity, Personalization, and 
Informativeness. When tourists use STTs to browse destina-
tions, they expect STTs to be highly interactive sharing local 
information, highly personalized to their preferences and 
requests, and reliable and useful for their trip. When tourists 
use City Guide Apps to find a local museum in San Francisco, 
for example, they want to have information about the exact 
location of the museum, the distance from their location, local 
traffic conditions incorporating accidents and constructions, 
reliable reviews about local restaurants, and so forth.
Because one fundamental goal in most trips is to have a 
memorable experience through participation in various 
activities, marketers of smart tourism destinations should 
ensure tourists’ privacy by providing a secure and worry-free 
environment for those who use STTs at the destination. 
Findings of this study indicated that although three STT attri-
butes were key predictors of tourists’ memorable experience, 
such memorable experience with STT usage would deterio-
rate if security and privacy were concerns in using STTs. 
Thus, destination tourism organizations must have IT secu-
rity personnel check their Internet platforms on a regular 
basis and update their security system frequently.
Although there are various destination-specific factors 
that affect tourists’ behavior, their satisfaction with STTs 
and intention to visit the destination again are highly depen-
dent on how they experienced STTs in the highly digital 
tourism destination environment. It is clear that tourism 
organizations of smart destinations should pay more atten-
tion to enhancing tourists’ memorable experience with 
STTs. Although tourists’ use of augmented reality, virtual 
reality, and other STTs appeared to be relatively low in this 
study, local smart tourism organizations need to begin 
incorporating these features in their destinations, as tourists 
start showing interest.
The findings of this study are subject to several limita-
tions. This study selected only five smart tourism destina-
tions in the United States to test the study’s model. These 
five smart tourism destinations are located in large, metro-
politan areas representing key US smart cities. The findings 
could be different if smart tourism destinations were located 
in suburban or smaller cities. Future studies can sample dif-
ferent scales of smart tourism destinations featuring different 
levels of STTs’ availability and functionality in an effort to 
increase generalizability of the findings across more destina-
tions and tourists’ memorable experiences.
Of another question is whether the proposed framework is 
applicable to smart tourism destinations in different coun-
tries and across travelers of foreign origins. More studies are 
encouraged to replicate this study in different countries with 
different travelers in order to assess the model’s applicabil-
ity. As a starting point, this study used security/privacy as a 
moderator and found outcomes of theoretical as well as prac-
tical importance. Examinations of additional moderators 
and/or mediators along the destination location and traveler 
origins or cultural background will greatly enhance the 
explanatory power of tourists’ memorable experience.
Because of a potential selection bias in sampling STT 
users, the results of the study may be unique to the sample. 
Future studies may explore differences and similarities of 
STT users versus nonusers in responding to STT attributes 
and their relationships with tourism experience and intention 
to revisit the smart tourism destinations. It would be also 
interesting to investigate and understand what kind of digital 
environments can cater to tourists’ STT needs and usage. 
Lastly, since tourists’ perceived destination image has been 
one of the key pull factors in destination marketing, assess-
ing the effects of STTs on destination image may result in 
valuable contributions to theoretical progress as well as to 
industry practice.
Acknowledgments
We greatly thank USC College of Hospitality, Retail, and Sport 
Management for the financial support for this research.