Suwitho, Impact of Tourist Satisfaction Attributes^ 171

P-ISSN: 1978-2853

E-ISSN: 2302-8890


MATRIK: JURNAL MANAJEMEN, STRATEGI BISNIS DAN KEWIRAUSAHAAN

Homepage: https://ojs.unud.ac.id/index.php/jmbk/index

Vol. 17 No. 2, Agustus (2023), 171-183

Impact of Tourist Satisfaction Attributes on Behaviour of Sharing Tourism Experiece on Social Media

Suwitho1), Hindah Mustika2), Fastha Aulia Pradhani3)

1,2,3 Sekolah Tinggi Ilmu Ekonomi Indonesia (STESIA), Surabaya

Email: [email protected]


SINTA 2


DOI : https://doi.org/10.24843/MATRIK:JMBK.2023.v17.i02.p05

ABSTRACT

Tourist satisfaction is an emotion that is felt by visitors when they there are in a place, in this case a tourism place. The satisfaction felt by visitors makes certain behaviours, which in this case share information using social media. This objective study is examines and analyzes the predictors of tourist satisfaction and tourist engagement on the behaviour of sharing tourism experience on social media. Methode: quantitative research with analysis technique. Results all variables influence can be acceptable and positive impact. Novelty in this study is the existence of tourist engagement that is able to make something unique because both the visitor and the place visited have an emotional engagement. Implication of results that with social media so we can easy to share experience and for destination as a promotion place, communication with prospective customer and discussion.

Keywords: Attraction; Engagement; Satisfaction; Social Media.

INTRODUCTION

East Java Province is a densely populated province which ranks 2nd based on the results of the 2020 population census (Ningsih, 2021). The fact is that in this province, the dense population is also offset by rapid economic growth. This is evidenced by economic growth which is above the average national economic growth, of 4.73 (RoEkonomi, 2019). One of the sectors that contributed to economic growth came from the tourism sector, which was 5 (Kominfo, 2019). In 2022, the Gross Regional Domestic Product (GRDP) for the tourism sector will also continue to experience a significant increase (Febrianto, 2022). Based on data obtained from the East Java Provincial Culture and Tourism Office, GRDP at current prices for the tourism sector in the first quarter of 2022 was IDR 36,986.76 billion, then there was an increase in the second quarter to IDR 38,243.41 billion, and continued to increase again to IDR 39,408.48 Bn in the 3rd quarter (Rachma, 2022). One indicator of the increase in GRDP in the tourism sector can be seen from the number of visitors at tourist sites. Even though there had been a drastic decrease in the number of tourists in all destination places in Indonesia, due to the Covid-19 pandemic in 2020. In 2021 there was an increase again, even in January-September 2022 there was an increase of 134.90 , compared to the previous year in the same period, namely 20,441,579 for domestic tourists or domestic tourists (Hasanah, 2022).

Since the existence of social media, information dissemination has become faster and easier, therefore social media has become one of the marketing media that is considered quite effective. In the tourism business, social media is an important and effective marketing channel (Zeng & Gerritsen, 2014). In the current era of globalization, a person's decision to buy or shop is mostly decided through social media (Ayutiani & Putri, 2018). Likewise in the tourism business, one of the decisions of potential consumers to visit tourist attractions is determined through one's previous experiences shared on social media or commonly known as the behaviour of sharing tourism experiences on social media. According to research conducted by (Retnasary et al., 2019) that content from social media has an important role in the promotion of tourism objects. In this study, the factors that are thought to influence the behaviour of sharing tourism experience on social media are tourist satisfaction and tourist engagement. Visitor satisfaction in a tourist spot that has been visited and the involvement of visitors in a tour is thought to influence a person's behaviour to share experiences on social media. This condition is in line with research conducted by Al-Htibat & Garanti (2019) that the more tourists are involved in the Cap Go Meh Singkawang festival, the higher the tendency to share information or experiences with other people. Likewise research that was conducted by Widiana & Novani (2022) also shows that customers who feel satisfaction at tourist attractions tend to share their experiences on social media. General attraction and culture attraction are also thought to have an indirect influence on the behaviour of sharing tourism experience. The existence of facilities or elements that support the tourist location (general attraction) as well as elements that indicate historical value at the tourist location are things that also influence customer satisfaction and tourist engagement.

Several previous studies related to the behaviour of sharing tourism have been carried out, one of which is regarding the analysis of factors that influence tourists' travel experience sharing on social media. The results show that overall satisfaction, perceived enjoyment, personal fulfillment, and self-actualization reasons have been significant predictors (Widiana & Novani, 2022). Research that was conducted by Sultan et al (2019) also shows that sharing on social media about positive experiences influences the positive effect of destination choice, while sharing about negative experiences will affect to decrease the choice of destination options.

Most of the previous research only focused on the factors that influence sharing behaviour on social media and the effect of this behaviour on tourist visits to a destination place, even though there are still many things related directly or indirectly to sharing behaviour on social media. This makes researchers interested in conducting research on the factors that influence sharing behaviour on social media in terms of tourist satisfaction and tourist engagement and their relation to general attraction and cultural attraction. Because after all, the satisfaction and engagement that impact on sharing behaviour comes from an attraction that causes visitor interest in these tourist attractions. In constructing all these variables in a model, the PLS SEM method is used. The end result of this research is that it is hoped that there will be an increase in tourists which will also have an impact on several aspects such as food, transportation, hotels, SMEs to the creative industry, even further on growth in East Java which comes from tourism contributions.

Behaviour is a behaviour that leads to a certain goal because there is a strong push either from internal factors or external factors, so it can be said that the behaviour of sharing tourism experience on social media as a behaviour or action to share on social media this can be in the form of an experience gained when visiting a certain place with the aim of expressing

or conveying a sense of emotion within (Jeong & Shin, 2020; Liu et al., 2018; Prayag et al., 2012).

According to Haneef et al., (2019); Wang et al., (2020) general attraction is something that is provided by tourism places with the aim of being able to be enjoyed and felt by visitors, so that visitors can feel safer, more comfortable and without any sense of worry in the sense that visitors get what they want when they are in tourism place. Visitors feel that there is selfinvolvement in tourism places because visitors feel valued and made as comfortable as possible, so it can be said that general attraction has an influence on tourist satisfaction and engagement.

H1: General attraction influence on tourist satisfaction

H2: General attraction influence on tourist engagement

Culture attractions in this case can be in the form of museums, galleries, culture (traditional), buildings that have historical value and monuments, or can be in the form of heritage attractions, crafts, architecture, past sights and art, but this cannot be separated from the existence of a maintenance factor. Specifically designed to maintain sustainability so that there is feedback for both visitors and places visited (tourism sites) (El Sheikh, 2020; Sergio Moreno-Gil, 2017). The research states that culture attraction has an effect on tourist satisfaction and tourist engagement.

H3: Culture attraction influence on tourist satisfaction

H4: Culture attraction influence on tourist engagement

Tourist satisfaction is a standard that measures how successful a service or goods provider is in meeting the expectations of visitors or customers or connoisseurs of the services or products provided or offered (Garanti et al., 2019; Leon & Choi, 2020). Previous research (Prayag et al., 2012) states that satisfaction can be interpreted as a person's feelings that describe a feeling of pleasure or disappointment, for the results of comparing the benefits of products or services, so that the results have an impact, if the impact on positive benefits then visitors will feel satisfied, and if what is felt exceeds expectations, then the visitor will be very satisfied. It can be concluded that tourist satisfaction has an influence on the behaviour of sharing tourism experience on social media

H5: Tourist satisfaction influence on behaviour of sharing tourism experiences on social media

According to García-Milon et al., (2020); Tiamiyuet al., (2020) the existence of an existence in the form of emotional and rational that is owned by visitors to tourist destinations, this makes the two components interrelated so that there is direct involvement of visitors to what they have experienced when they are in a place that has more value. Previous research conducted by García-Milon et al., 2020; Tiamiyuet al., 2020) that there is an effect of tourist engagement on tourist satisfaction and behaviour of sharing tourism experience on social media.

H6: Tourist engagement influence on the behaviour of sharing tourism experiences on social media.

H7: Tourist engagement influence on tourist satisfaction.

Figure 1. Conceptual Framework of Research

Source: Hypothetical model was developed by researches

METHOD

The approach used in this study is a quantitative approach which is a test of theories by means of measurement that emphasizes numerical data (numbers) on the variables studied and continues using one of the statistical test tools (Leavy 2017:9). The variables in this study consist of behaviour of sharing tourism on social media, tourist satisfaction, tourist engagement, general attraction and culture attraction. Behaviour of sharing tourism acts as an endogenous variable, while tourist satisfaction, tourist engagement are exogenous variables for behaviour of sharing tourism, and are endogenous variables for general attraction and culture attraction. Meanwhile, general attraction and culture attraction only act as exogenous variables. All types of variables in this study are latent variables, so that the measurement of each variable is carried out through several indicators. All indicators are adapted from several previous studies. Kim et al's research was adapted for general attraction variable indicators. Previous research belonging to Atsiz O & Akova, 2021 adopted for culture attraction. Own research (Jalilvand et al., 2012) adapted for tourist satisfaction variable. Tourist engagement is measured by indicators adapted from (Folgado-Fernández et al., 2021). Meanwhile, research (Wang et al., 2020) is referred to as the Behaviour of sharing toursme experience on social media indicator. All of these indicators are used as statement items in the questionnaire. Measurements were carried out using a five-point Likert scale with a range of values or numbers from 1 for strongly disagree to 5 for strongly agree.

The population in this study were all domestic tourists who had visited tourism sites in East Java. The research sample was determined using the non-probability sampling method, which is a sampling method based on a non-random selection concept, each element of the population has unequal opportunities to become a sample (Cooper & Schindler, 2014: 349). This sample method was chosen because there is no definite population frame for data on domestic tourists visiting tourist sites in East Java. The sample was only selected based on several criteria, namely domestic tourists who have visited tourist sites in East Java for the last 2 years (2021-2022). Tourist locations only cover the areas of Surabaya, Malang, Jember and Mojokerto. Based on some of these criteria, 115 respondents were selected for this study. The statistical technique used is the Structural Equation Modeling (SEM-PLS) method, which is a structural equation model based on data variance. This method is used to find the effect of a variable on its indicators or between variables in modeling. This method is more flexible

than the covariance-based SEM method which has a number of assumptions that cannot be violated in modeling. This method has several stages of analysis such as constructing path diagrams, converting path diagrams to a system of equations, estimating the outer model and inner model, and evaluating goodness of fit Goodness of fit, indicators and acceptance criteria. In this study the significant levels used were 90 and 95 .

RESULTS AND DISCUSSION

In this section, a discussion of the results of data analysis is carried out. For the initial stage is a discussion of the characteristics of the respondents as well as a summary of the descriptive statistics of the respondents' answers. In the next section is an explanation of the results of the analysis of the influence of exogenous variables on endogenous using the SEM-PLS method. A more detailed explanation is discussed in each of the following sub-chapters. Characteristics of Respondents and Descriptive Statistics of Respondents' Answers. The characteristics of the respondents in this study are presented in a Table 1. In the Table 1 above show that most of the respondents were female, with ages in the range of 21-25 years. Nearly half of the respondents had an undergraduate degree, and most of the sources of information obtained were from friends. Instagram is a social media that is often used by respondents in their daily lives. The Table 2 is a summary of the descriptive statistics for each answer given by the respondents from the five variables.

Table 1. Characteristics of Respondents

Gender

Female

79

Background of Education

D3

10

Male

36

S1

100

S2

5

15-20 Years

41

Colleagues

15

21-25 Years

50

Information Source

Family

15

26-30 Years

10

Friends

85

Age

31-35 Years

9

36-40 Years

2

Social Media to Used

Whatsapp

15

41-45 Years

3

Instagram

100

Source: processed data using SPSS version 27, 2023

In the Table 2 show that Respondents gave answers ranging from strongly disagree to strongly agree. If you look at the distribution of the answers, it shows that the number of categories that strongly agree has a fairly high value. So it can be said that the respondent understands and understands the context of the statement that must be answered.

Influence analysis using the SEM-PLS method through 2 stages, namely the analysis of the outer model and analysis of the inner model. The first stage is an analysis of the outer model. At this stage, several tests were carried out to measure the accuracy of using the indicators for each variable. All variables in this study are latent variables that are measured using several indicators, so it is hoped that the indicators used are appropriate and representative indicators in reflecting each variable. The tests carried out consisted of several stages, namely as follows.

Table 2. Descriptive Statistics of Respondents' Answers

Variable

Min

Max.

Average

St.dev

General Attraction

2

5

20.104

2.535

Cultural Attraction

1

5

19.791

2.296

Tourist Satisfaction

2

5

16.035

1.919

Tourist Engagement

2

5

16.757

2.539

Behavior of sharing tourism experiences on social media

1

5

18.922

3.333

Source: processed data using SPSS version 27, 2023

The testing phase of the outer model begins with convergent validity testing. This test is indicated by the value of the loading factor on each indicator. The indicator criteria are said to have met convergent validity if the resulting loading factor value is more than 0.5 (Chin, 1998). If there are variables that do not meet these criteria, then the indicator must be eliminated. The culture attraction variable is measured using 5 indicators, but the two indicators namely "obtaining the necessary information" and "positive things for the facilities offered" have a loading factor value that does not meet the criteria, so elimination is carried out for the two indicators. The results of the loading factor after elimination on all indicators in each variable are presented in the Table 3.

Table 3. Convergent Validity Test

Behaviour

of Sharing Tourism Experience on Social Media

Culture Attraction

General Attraction

Tourist Engagement

Tourist Satisfaction

0.782

0.788

0.744

0.832

0.803

0.835

0.591

0.724

0.825

0.676

0.874

0.828

0.776

0.914

0.713

0.772

0.708

0.901

0.845

0.828

0.674

Source: processed data using smart PLS version 3, 2023

In the Table 3 shown that all indicators in each variable have a loading factor value of more than 0.5 so that it can be indicated that all indicators have met the convergent validity criteria. This means that all indicators can be used appropriately and representatively to measure each variable in the study. The next test is the discriminant validity test. This test is conducted to test whether or not there is a difference in each latent variable. The difference in each latent variable indicates that the variable is unique and able to explain the phenomenon being measured. This test was carried out using 2 criteria, namely Fornell Lacker. Testing the discriminant validity using Fornell Lacker was carried out by comparing the square root of the AVE with the correlation between latent variables. A variable is said to have met discriminant validity if the AVE root in the latent variable is of greater value than the correlation with other latent variables. The results of the AVE value and the correlation of each variable are presented in the Table 4 below.

Based on the Table 4, it can be seen that the discriminant validity has a greater value when compared to the correlation between each latent variable (Cha, 1994). The AVE square

root value of each latent variable is the value that is located at the top position in each latent variable. This indicates that all latent variables in this study have met discriminant validity.

Table 4. Discriminant Validity (Fornell Lacker)

Behavior of sharing tourism experiences on social media

Culture Attraction

General Attraction

Tourist Engagement

Tourist Satisfaction

Behaviour of Sharing tourism experience on social media

0.819

Culture Attraction

0.429

0.743

General Attraction

0.439

0.484

0.726

Tourist Engagement

0.447

0.592

0.460

0.869

Tourist Satisfaction

0.483

0.657

0.530

0.682

0.762

Source: processed data using smart pls version 3, 2023

Table 5. Results of Validity and Reliability Test

Composite Reliability

AVE

Behavior of sharing tourism experiences on social media

0.910

0.671

Culture Attraction

0.784

0.552

General Attraction

0.848

0.527

Tourist Engagement

0.925

0.755

Tourist Satisfaction

0.846

0.581

Source: processed data using smart PLS version 3, 2023

The next stage is testing convergent validity and reliability. Convergent validity testing was carried out to test the correlation of indicators on each variable. According to Ghozali (2014) ,the correlation between indicators of each variable should have a high value. Reliability testing reflects the ability of indicators to measure their latent variables. So the more it has high reliability, the better. Convergent validity testing was carried out using AVE criteria, while reliability testing was carried out using composite reliability criteria. The two values are summarized in the Table 5. Based on the Table 5 it can be seen that the composite reliability value of all variables is greater than 0.7, meaning that all variables are reliable (Hair et al., 2011). The AVE value for entire variables are more than 0.5. It means whole variables have met the requirements of construct validity.

After going through several stages for testing the outer model, it can be concluded that all indicators can accurately and representatively measure the research variables. So that it can proceed to the next stage, namely testing the inner model. At this stage the test focuses on whether or not there is influence between variables in accordance with the previous research hypothesis. However, in the early stages, an assessment was made of the goodness of the model. This study uses 3 criteria to assess the goodness of the model, namely R-Square, R-Square Adjusted, and Q-Square. The R-Square value is the coefficient of determination, while the R-Square Adjusted value is the R-Square value that has been corrected for the standard error. Therefore the R-Square Adjusted tends to be more accurate in assessing the goodness of the model. The Q-Square criterion is also used to measure the goodness of the model but is more focused on the goodness of the observed values produced by the model and also the

SSE parameter estimates (Ghozali, 2014). The Q2 statistic formula is calculated as 1 -    . SSE is

sum of squared prediction errors based on comparison of the original data and predicted data while SSO is taken from prediction with mean. These three values have been summarized in the Table 6.

Table 6. Results of R-Square, R-Square Adjusted, Q-Square

R-Square

R-Square Adjusted

Q-Square

Behavior of sharing tourism experiences on social media

0.259

0.246

0.16

Tourist Engagement

0.390

0.379

0.286

Tourist Satisfaction

0.589

0.577

0.33

Source: processed data using smart PLS version 3, 2023

In the Table 6, it can be shown that the adjusted R-square value is 24.6 for the effect of exogenous variables on behaviour, 37.9 for the effect on tourist engagement while the good value of the model for tourist satisfaction is 57.7 . Based on these two values, it can only be categorized as a model that measures the effect of exogenous variables on behaviour which is included in the low category, while the other two models are included in the moderate category. The Q-Square value generated for all models is greater than 0, so it can be indicated that the model has a predictive relevance value, and the goodness of the resulting observation value is included in the large category for the tourist satisfaction model and included in the medium category for the other 2 models.

Table 7. Direct Test of Hypothesis

Variable

Standard Deviation

T Statistics

P Values

Culture Attraction >

Tourist Engagement

0.093

5.168

0.000*

Culture Attraction >

Tourist Satisfaction

0.089

3.718

0.000*

General Attraction >

Tourist Engagement

0.086

2.627

0.009*

General Attraction >

Tourist Satisfaction

0.070

2.638

0.009*

Tourist Engagement social media

> Behavior of sharing tourism experiences on

0.133

1.658

0.098**

Tourist Engagement

> Tourist Satisfaction

0.099

4.050

0.000*

Tourist Satisfaction > social media

Behavior of sharing tourism experiences on

0.125

2.673

0.008*

Note : * = significant at a significance level 95%

** = significant at a significance level 90% Source: processed data using smart PLS version 3, 2023

The next stage is testing the influence according to the initial research hypothesis. The results of the test are shown in the Table 7. In the Table 7 it can be seen that all hypotheses are accepted, because all variable influences have p-values that are smaller than the predetermined alpha values. The path diagram of the modeling is shown in the Figure 2.

Figure 2. Final Model of PLS Result

Source : processed data using smart PLS version 3, 2023

In the first hypothesis (1) the effect of general attraction on tourist satisfaction has a standard deviation value of 0.070 with a P-Value of 0.009 which has a significant effect, the results of this influence test have the smallest value compared to other influence tests. Previous research (Liu et al., 2017; Lund et al., 2016) showed that there is a significant relationship between general attraction and tourist satisfaction. This has the meaning that tourism provides what visitors want so that visitors can feel satisfaction.In the second hypothesis (2) states general attraction has an effect on tourist engagement with a standard deviation value of 0.086 with a P-Value of 0.009, which means that the greater the general attraction possessed by visitors, the higher the value of tourist satisfaction.In the third hypothesis (3) states that culture attraction has an effect on tourist satisfaction with a standard deviation value of 0.089 with a P-Value of 0.009 which means that the higher the culture attraction possessed by visitors, the higher the tourist satisfaction felt or owned by visitors .

In the fourth hypothesis (4) which states that culture attraction has an effect on tourist engagement, this can be seen from the standard deviation value of 0.093 with a P-Value of 0.000, this shows that the value of culture attraction felt by visitors will have a major influence on tourist engagement. In the fifth hypothesis (5), there is an influence of tourist satisfaction on the behaviour of sharing tourisme experience on social which has a standard deviation value of 0.125 with a P-Value of 0.008, meaning that the satisfaction felt by visitors has meaning, because visitors feel fulfilled desires that are not just values but on the experience gained, so that this makes visitors want to convey deep impressions and messages through a social media they have, this research is in accordance with previous research (Dixit et al., 2019; Ghorbanzadeh et al., 2021; Liu et al., 2018; Zhou et al., 2020). In the sixth hypothesis (6) which states that tourist engagement has an effect on tourist satisfaction, this can be seen from the standard deviation value of 0.099 with a P-Value of 0.000, it can be indicated that there is strong involvement possessed by visitors resulting in a strong satisfaction Also. This is in accordance with research (Alrawadieh et al., 2019; Han et al., 2021; Teng, 2021; Xu et al., 2018). The seventh hypothesis (7), namely tourist satisfaction has an effect on the behaviour of sharing tourisme experience on social with a standard deviation value of 0.133 with a P-Value of 0.098, indicates that there is an involvement of visitors who are felt while in tourism places, visitors feel that there is an appropriate condition with the desired

expectations, visitors feel given the opportunity to be able to provide mutual benefits so that this has an influence on behaviour to share experiences on social media (behaviour of sharing tourism experience on social). The results of this study are in accordance with previous studies (Bilro et al., 2018; García-Milon et al., 2020; Tiamiyu et al., 2020) which states that there is sharing behaviour due to a strong encouragement from visitors because visitors feel given the opportunity by provider of tourism places. It can be concluded that the test of the greatest influence on H1 and H5 has the smallest influence value.

CONCLUSION

The focus of this study is to analyze predictors of behavior related to sharing experiences on social media which consist of general attraction, culture attraction, tourist satisfaction and tourist engagement where each has an important role in the formation of behavior. Further research identifies similarities and differences in general and culture attraction, both of which are activities that have their own charm for visitors. This is distinguished from the existence of an activity that exists or is presented in a certain concept, making it possible for visitors to enjoy everything that is presented in a different way. These two variables are able to give their own impression and satisfaction for the visitors who enjoy it, the experience that is poured in the form of a satisfaction gives a strong desire to be shared with everyone through several media. The reason why using social media is because social media is one of the media that has speed and ease in sharing information and communicating. On the other hand, the satisfaction possessed by a person is driven by the existence of a strong feeling or strong bond that a person feels involved with an existing condition so that it can also create a certain behavior. The implications of this research for tourism managers are as support for management policies and as a strategy for marketing.

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