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

Methodology
Data Collection and Instruments
This study used a convenient, yet national, sampling 
approach by working with an online survey and database 
marketing company, Qualtrics, to contact those who had 
traveled to one of the following smart tourism destinations 
during the year of 2016: Boston, MA; Chicago, IL; New 
York City, NY; San Francisco, CA; and Seattle, WA. These 
five cities ranked top five smart cities in the United States, 
representing three different regions (East, West, and Midwest 
of the United States) where advanced ICTs were embedded 
in the city and they were top US tourism destinations as well 
(Cohen 2017). Furthermore, in the year 2017, four of the five 
cities ranked top 15 smart cities in the world—New York 
City (1st), Boston (4th), San Francisco (5th), and Chicago 
(12th) (Dhiraj 2017). For these reasons, the five US destina-
tions provided the sample setting for this study. Prior to the 
nationwide survey, this study conducted a series of prelimi-
nary tests including a pretest and expert reviews of the sur-
vey instrument to enhance its clarity and reliability. The 
pretest sampled 155 students majoring in hospitality and 
tourism management at a southeast university in the United 
States who helped refine the wordings and readability of the 
instrument. Three hospitality and tourism researchers then 
reviewed the instrument again to provide feedback for addi-
tional refinement before field administration.
The nationwide survey questionnaire included four sec-
tions. The first section consisted of an informed consent form 
and a screening question asking whether the respondent trav-
eled to one of the five sample cities in the previous 12 
months. If the respondent did not choose one of the five cit-
ies, the survey terminated his or her participation. The sec-
ond section included questions asking about what type of 
technology devices the respondents used during their travel 
and questions inquiring about the type of STTs they used 
during their visit to one of the five destinations. Before 
responding to the question, they read the definition of STTs 
to understand what STTs were. The questionnaire listed 28 
different STTs (e.g., mobile payment, such as Apple Pay and 
Samsung Pay) from which the respondents checked the ones 
they used at the visited destination. The third section con-
tained items measuring the key constructs of the study. All 
measurement items in the third section were adopted from 
previous studies to secure their initial reliability and validity: 
four STT attributes and security/privacy from the study of 
Huang et al. (2017), memorable experience from Oh, Fiore, 
and Jeoung (2007), and satisfaction and behavior intentions 
from Lin and Hsieh (2007). All constructs had multiitem 
measures, anchored on a scale ranging from 1=strongly dis-
agree to 7=strongly agree: three items for accessibility, three 
for informativeness, three for interactivity, three for person-
alization, four for security/privacy, four for memorable expe-
rience, three for satisfaction, and three for intention (see 
Table 3). The last section contained questions about sociode-
mographic backgrounds of the respondents.
Data Analysis
A descriptive analysis summarized the characteristics of the 
respondents’ sociodemographic profile and the mean values 
of each measure. The main analysis to test the hypotheses 
was two-step structural equation modeling (SEM) via IBM