Corresponding Author: Haniek
Listyorini
E-mail: [email protected]
INTRODUCTION
Tourism
is considered capable of being a source of economic growth and world employment
because it creates 300 million jobs and contributes 13% of the world's total
Gross Domestic Product. In line with the recovery from the Covid-19 pandemic
conditions in 2022, the World Travel and
Tourism Council (WTTC) predicts that tourism will create 328 million jobs
or absorb 1 in 10 workers worldwide (ILO, 2022).
The
importance of tourism to the economy causes tourism development to become an essential
issue for cities in the World (Bălan & Burghelea, 2015)� (Ginting & Wahid, 2015). Cities
are racing to innovate and travel at night into an innovation developed as a
competitiveness strategy� (Rodrigues et al., 2014). Night
tourism is becoming a trend through the new habit of tourists visiting a
destination (Aytuğ & Mikaeili, 2017). Cities
in the world have their character, both the uniqueness of tourism products and
their tourist market segments, but several cities are known for their many
night trip activities (Guo et al., 2011)
In
Indonesia, significant cities that experience the development of night tourism
include Jakarta, Surabaya, Bandung, Medan, Makasar, Semarang, Solo, and
Yogyakarta. One of the cities that steals the attention in the development of
night tourism is the city of Semarang. So far, Semarang is known as a transit
city; now, it is a tourist destination and a night tourism city. Various
buildings and historical areas have been restored as landmarks of the city of Semarang and developed into night tourist
locations. Lawang Sewu, Kota Lama, Tugu Muda, Mandala Bhakti Museum, Semawis
Market, and Jawi Village are more attractive locations to enjoy Semarang
tourism at night.�
Previous
research stated that an essential factor that encourages tourists to travel at
night in big cities is the attractiveness of culinary tourism. Therefore, many
destinations try introducing traditional to modern foods to provide a varied
culinary experience. The quality of the knowledge sought after in food tourism
is related to the destination's image,
lifestyle, and the influence of word of mouth�
(Lee et al., 2020).
The
decrease in the status level of restrictions on socio-cultural gatherings in
Semarang since October 2021 has encouraged tourists to return to travel with
health protocols in various places. Besides enjoying the modernization of the
city of Semarang, tourists can enjoy the local wisdom of the city of Semarang.
The uniqueness of a city's tourist attractions can increase tourists' interest,
and the added value of local knowledge further encourages tourists to visit (Sekarlangit & Devi S., 2020). Tourism based on local wisdom
prioritizes unique offerings that grow and develop in the community, both
physical and non-physical aspects, such as community cultural values (Maturbongs
& Lekatompessy, 2020).
Membranding the city using the essence of local wisdom and then being marketed
digitally can build tourist interest.��
Local products still exist and must be maintained at the regional and
central levels (Zulkarnain & Nugroho, 2019). Culinary creations based on local wisdom
have attracted domestic and international tourists, and various authentic
regional foods have attracted tourists to culinary tours in multiple cities (Zahrulianingdyah,
2018).
The purpose of this study is to analyze
seven problems�first, the influence of local wisdom products on night travel
decisions. Second, the impact of local wisdom products on the travel
experience. Third, the result of night travel decisions on the travel
experience. Fourth, night travel decisions' role in mediating local wisdom
products' influence on the travel experience.
METHOD
This research was conducted in Semarang City in 6 points
of popular night tourism places, namely the Old City Area, Simpang Lima Area,
Tugu Muda Area, Jawi Village, Semawis Market, and Pandanaran Souvenir Center. This research uses quantitative research
type. The entire population is tourists who make night tourism visits in
Semarang City, which cannot be known to the people for sure by researcher so the
researcher will use a sample of part of the tourists based on the
Lemeshow formula used a selection of 100 visitors (Sulaju
et al., 2021).
The sampling technique is based
on accidental convenience sampling (Sugiyono,
2019), namely the comfort and
willingness of tourists to fill out questionnaires when encountered at night
tourist attractions or provide WhatsApp contact numbers. Next will be sent a google
form questionnaire.
The
data were processed using SPSS for descriptive statistics and SEM PLS to test
data analysis requirements in the outer and inner models (Sihombing, n.d.). The criteria in the Outer Model using validity tests are carried
out by measuring individual and simultaneous convergent
validity and discriminant
validity. The reliability test includes Cronbach Alpha and Composite
Reliability. At the same time, the Inner Model criteria include R square, Q square, F
square, and Goodness of Fit (GoF). After the requirement test, it is continued by testing the
hypothesis of several effects of relationships between variables, namely the difficulty
of direct and indirect associations (mediation effects).
RESULTS AND DISCUSSION
Model Measurement Evaluation (Outer Model)
In testing, outer models
aim to see the validity and reliability of a model. This test analysis can be
seen from the influence of factor loading, Average Variance Extracted (AVE),
Discriminate Validity, and Composite Reliability. Here are the results of the outer model
test that shows the external loading value using the SmartPLS 3 analysis tool.
1.
Factor Loading
The aal stage in testing the
validity of a model is to test the convergent validity, which can be
seen from the loading factor for each construct indicator. The
requirement for the needle to be declared valid is if the value of the loading factor > 0.7. The hand should be removed from a Model (Umar, 2013).
Figure
1. Results of Alogarithm Outer Model.
Source: Processed primary data, 2022
When viewed from the picture above, the latent variable
of local wisdom products with seven indicators, all indicators have a loading
factor > 0.7. Then in the night travel decision variable, all five hands
have a loading factor > 0.7, and for the travel experience variable, all eight
hands have a loading factor of� 0.7. So
it can be concluded from the results of the analysis showing that the loading
factor of all items from the three variables has a value of > 0.7, so it can
be said to be valid.
2. Average Variance Extracted (AVE)
AVE is a value that is also used in Convergent Validity
tests. In the study results, the expected AVE value to be declared valid is
> 0.5. In the table below, the constructs of latent variables all have a
value of > 0.5.
Table 1. AVE Output Results Influence of Local Wisdom Products on
Travel Decisions and Travel Experiences
|
Construct
|
AVE
|
|
X Local Wisdom Products
|
0.663
|
|
Y Night Tourism Travel
Decisions
|
0.710
|
|
Z Travel Experience
|
0.756
|
Source: Primary data processed, 2022.
The table above shows that the entire construct of a
latent variable has a value of > 0.5, so it is declared valid.
3.
Discriminate validity
Because there is no problem with convergent
validity, an issue related to discriminant validity is then tested. This test
is used to test the validity of a model. The discriminate validity value is
seen through the cross-loading value, which shows the magnitude of the
correlation between the construct and its indicators and indicators of other
constructs. The results of cross-loading in the analysis of discriminate
validity are found in Table 4, below
Table 2. Cross Loading Value Discriminant Validity
|
|
Night Trip Decision
|
Travel Experience
|
Local Wisdom Products
|
|
Night trip Decisions
|
0.870
|
|
|
|
Travel Experience
|
0.862
|
0.843
|
|
|
Local Wisdom Products
|
0.746
|
0.701
|
0.814
|
Source: Processed
primary data, 2022
This result shows that each indicator is appropriate to
explain the construct of each variable and prove that the discrimination of the
validity of all items is valid.
4. Composite Reliability
To ensure that there are no measurement-related problems,
the final step in evaluating the outer model is to test the unidimensionality
of the model. This unidimensionality test was carried out using composite
reliability and Alpha Cronbach. For the three variables, the cut-off value is
0.7. The results of the data processing are presented in the following table:
Table 3. Composite Reliability
|
Construct
|
Composite Reliability
|
|
X Local Wisdom Products
|
0,932
|
|
Y Night Tourism Travel
Decisions
|
0,939
|
|
Z Travel Experience
|
0,951
|
Source: Primary data
processed, 2022
The table above shows that all constructs have a composite reliability value above
0.7. Therefore there are no problems found in the unidimensionality of the influence of local wisdom products on the decision to travel night
and experiences in the city of Semarang. The entire variable is declared reliable.
Evaluation of Inner Model Testing
Coefficient of Determination R2�
(R-Square)
The value can know the
goodness of fit on PLS of Q2. The value of Q2 has the same meaning as the
coefficient of determination (R-Square) in regression analysis.
Table 4. R-Square
|
Construct
|
R Square
|
R Square Adjusted
|
|
Y Night Tourism Travel
Decisions
|
0.557
|
0.552
|
|
Z Travel Experience
|
0.751
|
0.746
|
Source: Primary data
processed, 2022
Based on the R-Square Table, it can be known the value of
Q2, where the importance of Q2 = 1 � (1-R 1) ( 1-R2). The
result is 1- (1-0.557) (1-0.751) = 0.889 or 88.9%, meaning that the model can
explain data of 88.9% consisting of Night Travel Decisions of 55.7% and Travel
Experiences of 75.1%, other factors influence the rest. The value of R square
shows that 55.7% of the variable product of local wisdom can affect travel
decisions, and the rest is influenced by other variables outside the variables
in this study. The value of R Square shows that 75.1% of local wisdom products
and travel decisions can affect the travel experience; the rest is influenced
by other variables outside the variables in this study.
Hypothesis Testing
Partial t-statistical coefficient
PLS-SEM Bootsrapping Test To see
if a hypothesis can be accepted or rejected, among others, by paying attention
to the significance values between constructs, t - statistics, and p - values.
In the bootstrap resampling
method in this study, the significance value
used (two-tailed) t-table was 1.96 (significance level = 5%), provided that the
t-statistical value must be greater than the t-table value of 1.96. The figure
below shows a picture of the path hypothesis as follows
Figure 2. Results of t-statistical Test (Bootstrapping)
Based on the picture above, the t-statistical value of the
influence of local wisdom products on night travel decisions is 16,403 > t
table 1.98 shows the impact of local wisdom products significantly on night
travel decisions in Semarang City.
The t-statistical value of night travel decisions on
travel experiences is 8,878 > t table 1.98, indicating that the influence of
night travel decisions is significant on travel experiences.
The t-statistical value of the influence of local wisdom
products on travel experiences is 1,431 < t table 1.98, this shows that the
impact of local wisdom products is not significant on travel experiences.
Table 5. Significance Test Results
|
No
|
Indicator
|
Original
Sample
|
Sample
Mean
|
Standard Deviation
|
t-statistic
|
P
value
|
|
H1
|
PK � KP
|
0.746
|
0.753
|
0.049
|
15.336
|
0.000
|
|
H2
|
PK � PW
|
0.131
|
0.130
|
0.090
|
1.449
|
0.148
|
|
H3
|
KP � PW
|
0.765
|
0.771
|
0.090
|
8.481
|
0.000
|
|
H4
|
PK� KP� PW
|
0.571
|
0.581
|
0.078
|
7.298
|
0.000
|
|
Hypothesis 1
|
:
|
The Influence of Local Wisdom Products on Night Travel Decisions
|
|
Result
|
:
|
|
Hypothesis
testing showed a t - statistical value of 16,405 >1.98 and a p-value of
0.000 < 0.05.
|
|
|
Conclusion
|
:
|
Based on the results of the calculations above, it can be concluded that
hypothesis 1 is accepted and that there is a significant influence of local
wisdom products on night travel decisions.
Based on the results of the calculations above, it can be concluded that
hypothesis 1 is accepted, and it is stated that there is a significant
influence of local wisdom products on night travel decisions.
|
|
Hypothesis 2
|
:
|
The influence of local wisdom products on travel experiences
|
|
Result
|
:
|
|
Hypothesis
testing showed a t - statistical value of 0.149< 1.96 and a p-value of
0.90 > 0.05
|
|
|
|
Conclusion
|
:
|
Based on the results of the calculations above, it can be concluded that
hypothesis 2 is rejected, and it is stated that there is no significant
influence of local wisdom products on travel experiences.
|
|
Hypothesis 3
|
:
|
The influence of night travel decisions on the travel experience
|
|
Result
|
:
|
Hypothesis testing showed a t - a statistical value of 8,481 > 1.96
and a p-value of 0.000 < 0.05.
|
|
Conclusion
|
:
|
Based on the results of the calculations above, it can be concluded that
hypothesis 3 is accepted, and it is stated that there is a significant
influence of night travel decisions on the travel experience.
|
|
Hypothesis 4
|
:
|
The influence of local wisdom products on the travel experience through
night trip decisions
|
|
Result
|
:
|
The partial hypothesis test shows the value of t - independent
statistical variable of local wisdom product against the dependent variable
of the travel experience of 1,449 < 1.96 and the importance of t - independent
statistical variable of local wisdom product to the intervening variable of
night travel decision of 15,336 > 1.96. Simultaneous hypothesis testing
showed the importance of t - independent statistical variables of local
wisdom products against dependent variables of travel experience through intervening
variables of night travel decisions of 7.289 > 1.96. �
|
|
Conclusion
|
:
|
Based on the results of the calculations above, it can be concluded that
hypothesis 4 is accepted, and it is stated that there is a significant
influence of local wisdom products on the travel experience through the
decision to travel at night.
|
Mediation Effect Test
SEM Analysis With Mediation Effect Testing of the
mediation effect in PLS using the procedure developed by (Baron and Kenny 1998
in Ghozali and Latan 2015) with the following stages :
1. The first model tests the influence of independent
variables on dependent variables and should be significant at t - statistics
1.98.
2. The second model tests the influence of independent
variables on intervening variables and should be significant at t - statistics
1.98.
3. The third model simultaneously tests the influence of independent
and intervening variables on dependent variables. In this test, if the result
of independent variables on dependent variables through intervening variables
is significant at t -statistics 1.98, then the intervening variables are shown
to mediate the influence of independent variables on dependent variables.
Table 6. Simultaneous Significance Test
|
Construct
|
Original
Sample
|
Sample
Mean
|
Standar Deviation
|
t-statistic
|
P
value
|
|
PK� KP �PW
|
0.571
|
0.581
|
0.078
|
7.298
|
0.000
|
Source: Primary data processed, 2022
CONCLUSION
The study concludes that local wisdom
products influence the decision to travel at night. Secondly, local wisdom
products also affect travel; thirdly, the decision to travel at night affects
the travel experience and the decision to travel at night mediates the
influence of local wisdom products on the travel experience. To feel the
experience of traveling, tourists must take a night tour in the city of
Semarang to enjoy the effects of local wisdom.
REFERENCES
Aytuğ, H. K., & Mikaeili, M. (2017). Evaluation of
Hopa's Rural Tourism Potential in the European Union Tourism Policy Context. Procedia
Environmental Sciences, 37, 234�245.
https://doi.org/10.1016/j.proenv.2017.03.039
Bălan, M., & Burghelea, C. (2015). Rural Tourism and
its Implication in the Development of the Fundata Village. Procedia-Social
and Behavioral Sciences, 188, 276�281.
Ginting, N., & Wahid, J. (2015). Exploring Identity's
Aspect of Continuity of Urban Heritage Tourism. Procedia - Social and
Behavioral Sciences, 202(December 2014), 234�241.
https://doi.org/10.1016/j.sbspro.2015.08.227
Guo, Q., Lin, M., Meng, J. H., & Zhao, J. L. (2011). The
development of urban night tourism based on the nightscape lighting projects-A
case study of Guangzhou. Energy Procedia, 5(40771002), 477�481.
https://doi.org/10.1016/j.egypro.2011.03.083
ILO. (2022). Tourism is a powerful tool to tackle the
crisis. International Labour Organisation.
Lee, S., Park, H., & Ahn, Y. (2020). The influence of
tourists' experience of quality of street foods on destination's image, life
satisfaction, and word of mouth: The moderating impact of food neophobia. International
Journal of Environmental Research and Public Health, 17(1).
https://doi.org/10.3390/ijerph17010163
Maturbongs, E. E., & Lekatompessy, R. L. (2020).
Kolaborasi Model Pentahelix Dalam Pengembangan Pariwisata Berbasis Kearifan
Lokal Di Kabupaten Merauke. Transparansi : Jurnal Ilmiah Ilmu
Administrasi, 3(1), 55�63.
https://doi.org/10.31334/transparansi.v3i1.866
Rodrigues, A. L. ., Rodrigues, A., & Peroff, D. M.
(2014). The Sky and Sustainable Tourism Development: A Case Study of a Dark Sky
Reserve Implementation in Alqueva. International Journal of Tourism Research,
113(November 2012), 101�113. https://doi.org/: 10.1002/jtr.1987
Sekarlangit, N., & Devi S., L. V. R. (2020). Architecture
Branding in a Local Wisdom Based on Tourism Development 4.0 in Bali. Undagi :
Jurnal Ilmiah Jurusan Arsitektur Universitas Warmadewa, 7(2), 56�65.
https://doi.org/10.22225/undagi.7.2.1564.153-162
Sihombing, P. R. (n.d.). Aplikasi SEM AMOS Untuk
Statistisi Pemula.
Sugiyono. (2019). Metode Penelitian Kuantitatif Kualitatif
dan R&D. ALFABETA.
Sulaju, A. P., Latif, I. N., Bakrie, I., & Milasari, L.
A. (2021). Statistik Ekonomi 1. In Zahir Publishing (1st ed.).
Umar, H. (2013). Metode penelitian untuk skripsi dan tesis
bisnis.
Zahrulianingdyah, A. (2018). Kuliner Sebagai Pendukung
Industri Pariwisata Berbasis Kearifan Lokal. Teknobuga, 6(1),
1�9. https://doi.org/10.1529/jtbb.v6i1.16667
Zulkarnain, I., & Nugroho, H. (2019). Analisis Perilaku
Produsen Dalam Mengembangkan Produk Berbasis Kearifan Lokal Tangerang Selatan. Inovasi,
6(2), 69. https://doi.org/10.32493/inovasi.v6i2.y2019.p69-79
