Assessing tourist satisfaction, future behavior, and destination image: a case study of Pantai Pasir Putih in Blitar

ABSTRACT


INTRODUCTION
Tourism is one of the sectors that can contribute to the economic growth of a region.The developed tourism sector can contribute to socio-economic development, improving the livelihoods of local communities and preserving biodiversity (Admasu, 2020).Based on data from Kemenparekraf, the tourism sector is able to contribute 4. percent to GDP in 2023 (Hendriyani, 2023).This indicates that the tourism sector needs to be given attention regarding accessibility, accommodation, attractions, and various activities (Megawati et al., 2023).Good tourism management can allow tourists to enjoy the variety of activities available and provide benefits in the form of welfare for the surrounding local community (Morgan & Xu, 2009).
East Java is one of the provinces with biodiversity and natural potential that can attract tourists.One of them is Blitar Regency, which has a number of beaches with unique attractions and characteristics, such as Pasir Putih Beach al, also known as Gondo Mayit Beach, located in Tambakrejo Village, Wonotirto District, Blitar Regency.Although it has an unusual name, like other tourist attractions, Pasir Putih Beach is considered natural and clean, offering enchanting natural scenery.
Destinations are products that cannot stand alone; instead, they are a combination of various attributes considered by tourists who decide to visit (Framke, 2002).Tourist attractions and tourist sites refer to various structures and facilities that attract the attention of tourists or visitors to a particular area or place.In the tourism industry, several things are worthy of being a tourist attraction, such as interaction with other tourists and local communities (Tung & Ritchie, 2011), adequate facilities (Yang et al., 2020), service (accommodation and food), reputation, and economic attractiveness (Herington et al., 2013).
Satisfaction is one of the essential elements in the tourism industry.Satisfaction can be described as a person's overall feeling or attitude about the services that have been purchased (Zhao et al., 2021).Martin et al., (2008) explain that satisfaction can be described as an emotional state and is subjective regarding what the customer needs.A high tourist travel experience significantly impacts tourist satisfaction (Y.Wang & Chiu, 2015), so it can contribute to tourist loyalty.Tourist loyalty can be reflected through re-visit and providing recommendations to tourists (Adinegara et al., 2021).The form of satisfaction that is reflected can make longterm and recurring relationships.Dmitrovic et al., (2009) says that increasing tourist satisfaction can increase the income of service providers.A higher level of customer satisfaction can increase customer loyalty (Flint et al., 2011) (Qi et al., 2012).
Tourist satisfaction, as consumers or recipients of services, can be measured through the overall evaluation made by tourists of the quality of the experience they had while visiting the destination.The Behavior exhibited by tourists after their visit can be reflected in what is referred to as "Future Behavior."Individual preferences and intention to return to a tourist destination are relevant phenomena to study in the tourism industry (Darnell & Johnson, 2001).This is because the tourism sector relies heavily on tourists' visits to the same destination to reduce costs (Um et al., 2006).The intention to revisit a tourist destination is influenced by various complex factors, including the level of satisfaction and experience that motivates tourists to return (Y.Wang & Chiu, 2015).
Therefore, destination image has an impact on tourists' level of satisfaction and their future Behavior.Empirical research shows that online reviews significantly influence destination image (Guo & Pesonen, 2022).The travel experience begins before arriving at the destination and continues afterward through memories of the experience and plans for future revisits (Pine II & Gilmore, 1998).Success in the tourism industry lies in creating high-quality hedonic experiences (Ali et al., 2015) and creating travel experiences that have meaning, uniqueness, and deep impressions (Coudounaris & Sthapit, 2017) so that they can encourage customer retention.
Tourism development strategies are increasingly vital in achieving long-term and short-term tourism goals.To achieve this, active participation of the government, community, and other stakeholders is required to increase the number of tourist visits.Destination image, which refers to the perceptions and information that potential tourists have about a tourist spot before they visit it, becomes a significant factor in their travel decisions (Zhang et al., 2017) (Souiden et al., 2017).The development of a positive image plays a crucial role in the success of tourism destinations (Chaulagain et al., 2019) in attracting tourist visits to Blitar Regency.The ultimate goal of destination marketing efforts is to influence travelers' travel choices by creating a positive image of the destination.The image of a tourism destination reflects tourists' perceptions and beliefs regarding the destination, which also affects their level of satisfaction when visiting (Prayag & Ryan, 2012).This, in turn, affects their desire to return and recommend the destination to others.Studies conducted by Bigne et al., (2001) confirm the positive relationship of Destination Image, Satisfaction, and Future Behavior.
For more than 30 years, a lot of previous literature has focused on Destination Image research (Pinos Navarrete & Shaw, 2021).Previous research by Angessa et al., (2022) Pan et al., (2021) suggests that tourism development has a positive effect on local tourism as seen from the perceptions of the community and tourists.Similarly, Suban, (2024) a higher degree of satisfaction would encourage visitors to revisit the location.Especially strong competition and development of tourist areas is the key to sustainable development of the tourism industry (Phi et al., 2021).Therefore, it is essential to realize that a tourism destination's positive image greatly influences consumer behavior, especially in the context of the desire to return and share the experience with others.(Bigne et al., 2001) Given the importance of destination image, maximum efforts are needed to ensure that tourists who visit tourist destinations feel motivated to return, invite friends and family, and recommend the destination to others.For this reason, research exploring the factors that influence the positive image of tourism destinations is highly relevant and vital to investigate.More specifically, research on the level of satisfaction and the potential for tourists to return and recommend Pasir Putih Beach has never been done.
Based on the information and background that has been conveyed, research on tourists' perceptions of the image of Pasir Putih Beach is essential, so that tourism development at this location can be tailored to the preferences of tourists.This study also aims to ascertain the level of satisfaction and the potential for tourists to return and recommend Pasir Putih Beach to others in the future.

METHODS
This research is a quantitative approach that aims to measure and analyze the relationship between the variables studied, namely Tourist Satisfaction, Future Behavior, and Destination Image at the Pasir Putih Beach tourist destination in Blitar Regency.The quantitative approach allows researchers to collect numerically measurable data for more in-depth statistical analysis.Based on its findings, this research can be classified as basic research.Primary research is a method for testing theories or hypotheses that can be useful in developing previous research.This study has two types of variables: endogenous and exogenous.The endogenous variables include Tourist Satisfaction and Future Behavior, while the exogenous variable is the Destination Image.
The data used in this study came from completing an online questionnaire by 200 respondents who had visited the beach in the past five years.Data collection was conducted through a questionnaire distribution and completion process, with several steps to ensure appropriate respondent criteria.Furthermore, validity and reliability tests were conducted to check the accuracy and consistency of the measurement tools used.SEM (Structural Equation Model) analysis was conducted to test the relationship between variables.The results of this analysis will determine whether the proposed hypothesis can be accepted or rejected.
Descriptive analysis method is used to describe the data that has been obtained as it is without making general conclusions.The data described in this study are data on the characteristics of respondents which include 1) Characteristics of Gender, 2) Place of Origin, 3) Status, 4) Age, 5) Education, 6) Occupation, and 7) Travel Budget.In addition, this study uses descriptive statistical analysis to analyze respondents' answers regarding the level of satisfaction and the potential for tourists to return and recommend Pasir Putih Beach.

RESULT AND DISCUSSION
The respondents in this study are tourists who have visited Pasir Putih Beach in Blitar Regency and are over 16 years old.  1, it can be seen that 81.5% are female, while the place of origin of the respondents themselves varies greatly from various cities but is dominated by 87.5% from Blitar city.As many as 53.5% of respondents had married status.Meanwhile, according to the age composition, most are in the age range of 21-30 years, which is as much as 45.5%.Based on formal education, tourists who take S1 / S2 Strata Education are 51%, and the type of work that is mainly found as a student, as much as 34%.The traveling budget that tourists will spend also varies, but as many as 57.5% of respondents have a traveling budget of Rp 0 -Rp 500,000.
A validity test is conducted to determine whether an instrument is said to be valid or not in research.In this study, the validity test was carried out on each question that 200 respondents had filled in.The validation test uses the SPSS for the 26.0 Windows version program.The questions tested will later form the research variables: Destination Image, Tourist Satisfaction, and Future Behavior.Each question item is valid if the results of the Pearson correlation between each question and the total score have significant results <0.05 (ɑ-5%) and a high Pearson correlation value of 0.3..698 .000 VALID Sources: Primary Data, data processed using SPSS In Table 2, each indicator of the tourist satisfaction variable (X1), future Behavior (X2), and destination image (Y) is valid and can be used for analysis at a later stage.In the tourist satisfaction variable, the Pearson correlation value, which has the lowest value, is 0.643, which is located on indicator X1.2, while the highest Pearson correlation value is 0.741 on two indicators, namely X1.4 and X1.5.In the future behavior variable, the Pearson correlation value has the lowest value, namely 0.828, located on indicator X2.3, while the highest value is 0.899, located on indicator X2.2.In the destination image variable, the Pearson correlation value, which has the lowest value, is 0.660, which is located at Y6, and the highest value is 0.785 at indicator Y1.
The reliability test is carried out by knowing the consistency of the measuring instrument used so thaitnt is reliable anproducesas consistent results if the measurement is repeated.This reliability is achieved using the Cronbach Alpha method (ɑ-0.6), and then the statement indicator can be reliable (Hair et al.,20,14 p. 123).Destination Imagee (Y) .854 .000 Reliability Sources: Primary Data, data processed using SPSS Based on table 3, shows that the Satisfaction, Future Behavior, and Destination Image Variables have a Cronbach alpha value of more than 0.6 so that all indicators of each variable can be said to be reliable.The entire validity and reliability test shows that the indicators of the statements made to test the hypothesis in the study have met the requirements, and the second researcher can proceed to obtain the sample that has been determined.
In Structural Equation Modeling (SEM), the measurement model is a model that describes the relationship between variables and their indicators.The measurement model stage is carried out to test whether the measuring instrument used in the research has been valid and reliable.The measurement model analysis was carried out using the Confirmatory Factor Analysis (CFA) method on all variable indicators in this study.The measurement model must meet the Goodness of Fit Index (GoF) criteria so that the model can be analyzed further.The results of the Goodness of Fit Index (GoF) measurement model are as follows:  Good Fit Sources: data processed by the author using Amos26 for windows Table 4 shows that several indices of goodness of fit must be met before continuing to the structural model.Furthermore, by looking at standardized loading, measurement is used to determine the accuracy of statements when compiling a construct.Questions can be used if they have a standardized loading of ≥ 0.5; if the question has a standardized Loading value of ≤ 0.5, then the research cannot be continued to the next stage.The following are the results of standardized loading, AVE, and CR mode of measurement, which show the standardized loading value for each indicator on each variable.Confirmatory factor analysis (CFA) will be carried out based on the standardized loading value.Ghozali (2013) explains that the indicators of the variables are called reliable if the AVE value ≥ 0.05 and CR ≥ 0.07 on each indicator above.Thus, it can be said that all variables are reliable.Table 6 shows the results of the research hypothesis test of the three hypotheses.Where it can be seen that the hypothesis is not supported or supported by the C.R., which is > ± 1.96.While the summary results indicated that : 1) the effect of tourist satisfaction on destination image directly has a value of 4.410 with a significant p-value of 0.000 or below 0.05, which means that the destination image variable has a mediating effect between each satisfaction mediation.This indicates that the first hypothesis (H1) is accepted; 2) In Future Behavior, tourist satisfaction has a value of 3.929 with a significant p-value of 0.000 or below 0.05, which means that the variable tourist satisfaction mediates between each future behavior mediation means that the second hypothesis (H2) is accepted; 3) Future Behavior on the destination image directly has a value of 4.120 with a significant p-value of 0.000 or below 0.05, which means that the future behavior variable has a mediating effect between each destination image mediation means that the third hypothesis (H3) is accepted.
From the theoretical point of view, this study provides several findings to research in local tourism, hospitality, and tourist future behavior.Destination image is the overall picture of feelings expressed by tourists.This can be a representation described by individuals or communities regarding ideas, knowledge, and emotions expressed in a place (Kanwel et al., 2019).This study's results destination image variable has a mediating effect between each satisfaction mediation.It supports previous research by Lestari et al., (2022) that the destination image affected emotional bonding.Hultman et al., (2015), found that destination personality promotes tourist satisfaction, tourist-destination identification, pos 2itive word-of-mouth, and revisit intentions.
Tourists who have a strong psychological attachment to a tourism destination not only intend to revisit but can also act as a promotion media.This study's results show that the variable tourist satisfaction mediates between future behavior mediation.It is inline by the findings of Rasoolimanesh et al., (2022) T. Wang et al., (2017) which indicate a significant relationship between tourist satisfaction and future tourist behavior that will recommend through WOM.
Many studies mention Tourist satisfaction is the key to future behavior.As finding Nanggong & Mohammad, (2024) that the experience gained by tourists can increase e-WOM activities carried out independently by tourists.This study's results show that the future behavior variable has a mediating effect between each destination image mediation.It aligns with Bayih & Singh, (2020), Kilic & Adem (2012) and Jeong et al., (2019) research regarding the intention to revisit which tourists will carry out and recommend tourist destinations.The result of these actions will help tourists distinguish a destination and make decisions (Önder & Marchiori, 2017).

CONCLUSION
The results confirm that tourist satisfaction plays an important role in shaping destination image, future behavior, and contribution to economic growth in Blitar Regency.The findings show that tourist satisfaction significantly affects the destination image of Pasir Putih Beach, indicating that the higher the satisfaction, the better the destination image.The positive impact of tourist satisfaction is also reflected in future behavior, where high levels of satisfaction encourage tourists to recommend the destination to others (Suban, 2024).
The results of this study are consistent with utility theory, which suggests that tourist satisfaction increases perceptions of destination value.In addition, tourists' future behavior also contributes significantly to the destination's image, which ultimately impacts local economic growth (Angessa et al., 2022).Thus, an increase in tourist arrivals not only increases local revenue through tourism levies and taxes, but also creates business opportunities for local communities, creating a positive multiplier effect in the local economy around tourism destinations.
Suggestion that can be given from the results, there were enough evidence to conclude there was a positive relationship between tourist satisfaction, destination image, and future behavior.Therefore, it is important for the local government to create an adequate tourism ecosystem in order to create a sustainable environment (nature and ecosystem) so that in the future Pasir Putih Beach can become a favorite destination for local tourists outside Blitar.When the ecosystem that is built is adequate, it will foster new business opportunities, for example local tour guides, vacation packages and even lodging around being able to level up according to the visitor's budget.
As in most studies, this research has limitations.The main limitations are the number of sample respondents and the questionnaire collection time.It can take several months to get accurate data regarding tourists' return visits.The second limitation is that there is no exact calculation of the added value generated through tourism visits to Pasir Putih Beach.So, in the future, it will significantly assist the government in increasing economic activities in the region.

Figure 1 .
Figure 1.Measurement modelSources: data processed by the author using Amos 26 for windows

Table 1 .
Table 1 presents the distribution of respondents based on their characteristics: Distribution of Respondents based on Characteristics of Gender, Place of Origin, Status, Age, Education, Occupation, and Travel Budget.Distribution of Respondents

Table 4 .
Measurement model fit test results

Table 5 .
Standardized Loading, AVE, and CR values for each variable

Table 5
explains that the indicators of tourist satisfaction, future Behavior, and destination image variables are valid because the Loading factor or Standardized Loading Estimate value is> 0.05.

Table 6 .
Hypothesis Test Summary Results