Tourist Risk Perception, Destination Image and Tourist Experience towards Revisit Intention Post COVID-19 Pandemic

. West Nusa Tenggara Province, especially the island of Lombok, has many tourist destinations, namely nature tourism, cultural tourism, and tourist attractions (sports tourism). Still, the tourism sector in NTB is one of the sectors most affected by the COVID-19 pandemic era. This study aimed to determine tourist risk perception, destination image and tourist experience on revisit intention after the Covid-19 pandemic. This study uses a quantitative approach with an explanatory research design. This research was conducted in Kuta Tourism Destinations, Central Lombok Regency, Lombok Island, West Nusa Tenggara Province, Indonesia. The research population is all people who have visited the Mandalika KEK tourist attraction on the island of Lombok after the COVID-19 pandemic in March 2020. The sampling technique is non-random sampling, so the number of research samples is 85 people. Data collection techniques used are questionnaires and documentation. Data analysis was carried out using the Partial Least Square approach. The results showed that 1) Tourist Risk Perception has a negative and significant effect on Destination Image; 2) Destination Image has a positive and significant impact on Tourist Experience; 3) Tourist Experience has a positive and significant effect on Revisit Intention; 4) Tourist Risk Perception has a negative and significant effect on Kuta Lombok Tourist Destinations after the COVID-19 pandemic; and 5) Destination Image has a positive and significant impact on the Revisit Intention of Tourists of Kuta Lombok Tourism Destinations after the COVID-19 pandemic.


INTRODUCTION
West Nusa Tenggara Province, especially the island of Lombok, has many tourist destinations, namely nature tourism, cultural tourism, and tourist attractions (sports tourism).In 2018, tourism in West Nusa Tenggara (NTB) was shaken by a powerful earthquake.Not even two years after continued recovery efforts after the devastating earthquake, the economic COVID19downturn has occurred again, which is marked by a drastic decline in tourist visits to NTB.
Several studies related to tourism have discussed the relationship between vacation motivation and risk perception.Tourism researchers classify risk perceptions in several ways.For example, risk perception can influence medical tourists to avoid specific destinations or even a tendency not to travel at all [1].Research conducted by [2] identified that two dimensions of risk perception (namely financial risk and performance risk) significantly impact the destination's image.At the same time, the author [3] categorises risk perceptions into six dimensions: physical, financial, performance, social, psychological, and economic.For example, backpacker tourists may not face the same risk factors as recreational tourists.Another approch is that the risk perceived by potential tourists may change from time to time and from destination to destination.
In addition, many studies have examined risk perceptions about tourist destination images that lead to revisiting intentions [4,5,6,7].Customer complaints against tourist destinations can result in lower post-purchase behaviour because what is desired does not materialise [8].Destination image is necessary to influence tourist decisionmaking, destination choice, post-trip evaluation, and future behaviour [9,10,11].Many destinations range from city/rural, region or country.If the goal is the whole country, the image of the country/nation may be an essential factor in influencing the idea of the destination and the choice of international tourist destinations [11,12].Existing international trade and marketing studies show that consumers' perceptions of the country's image influence attitudes, evaluations and purchase intentions of the country's products [13].
Destination image plays two critical roles in behaviour.Some researchers have suggested that such behaviour allows one to test places, thereby influencing decision-making [14,15].Others have argued that decision-making behaviour [16,17] consists of participation (onsite experience), evaluation (satisfaction), and future behavioural intentions (intention to revisit and willingness to recommend).More theoretical and empirical research needs to be done in this area.This study aimed to examine the relationship between destination image, experience, perceived expertise and decision-making for future behavioural intentions.
Restoring tourist trust is needed, amid anxiety and the need to travel, especially during the COVID-19.This research was conducted using a quantitative approach to analyse consumer behaviour (tourists), identify behaviours that can change the tourism industry and understand their needs.Based on relevance data review, it illustrates the low awareness of the people of the island of Lombok about the importance of the natural beauty of tourism that is required to create interest in revisiting on the island of Lombok.

METHODS
This research uses a quantitative approach.According to the conventional wisdom, quantitative research is closely related to social survey techniques, including structured interviews and structured questionnaires, experiments, structured observations, content analysis, formal statistical analysis and many more.The design or design of this research includes explanatory research, namely research that aims to analyse the relationships between one variable and another or how one affects other variables [18].This research was conducted in Kuta Tourism destinations, Central Lombok Regency, Lombok Island, West Nusa Tenggara Province, Indonesia.The researchers took the location because the location is one of the areas that is a means of proving Indonesian tourism, especially Lombok Island, in the international arena.Population refers to the whole group of people, events, or things of interest investigated by the research-er [19].The population in this study were all people who had visited the Mandalika SEZ tourist attrac-tion on the island of Lombok after the COVID-19 in March 2020.The sample was part of the population.The model comprises some members selected from the people [19].
The sampling technique used in this study is nonrandom sampling, namely using the purposive sampling technique, which is one of the sampling techniques by selecting samples based on the required information that can be obtained from a particular target group to be able to provide the information desired by the researcher.This study involved 17 manifest variables from 4 existing latent variables, so the sample taken is based on the above criteria: several 5 x 17 = 85 people.
In this study, the data collection techniques used were questionnaires and documentation.
The quantitative approach used in this analysis is the Partial Least Square (PLS) approach.
Outer Model Analysis.The outer model analysis is carried out to ensure that the measurement used is feasible to be used as a measurement (valid and reliable).This model's analysis specifies the relationship between latent variables and their indicators.Outer model analysis can be seen from several indicators: 1. Convergent Validity is an indicator assessed based on the correlation between the item score score and the construct score, which can be seen from the standardised loading factor, which describes the magnitude of the correlation between each measurement item (indicator) and its construct.The individual reflexive measure is said to be high if it has a correlation > 0.7 with the construct to be measured.According to [20], the outer loading value between 0.5-0.6 is considered sufficient.

Discriminant
Validityis, a measurement model with reflexive indicators, assessed based on cross-loading measurements with constructs.If the construct's correlation with the measurement item is more significant than the size of the other constructs, it indicates that their block size is better than the other blocks.Meanwhile, another method to assess discriminant validity is by comparing the square root value of the average variance extracted (AVE).1. Significance of weights.The value of the formative indicator weight with its construction must be significant.
2. Multicollinearity.A multicollinearity test was conducted to determine the relationship between indicators.To determine whether the formative indicators have multicollinearity by knowing the VIF value.The VIF value between 5-10 can be said that the hand occurs multicollinearity.
Inner Model Analysis.Inner model analysis, usually referred to as inner relations, structural models and substantive theory describe the relationship between latent variables based on substantive theory.The inner model analysis can be evaluated by using R 2 for the dependent construct, the Stone-Geisser Q 2 test for predictive relevance and the t-test, and the significance of the coefficients of structural path parameters.In evaluating the inner model with PLS, it begins by looking at the R 2 for each latent dependent variable.Then the interpretation is the same as the interpretation of the regression.Changes in the value of the R 2 can be used to assess the effect of certain independent latent variables on the latent dependent variable and whether it has a substantive impact.In addi-tion to looking at the R 2 value, the PLS model is also evaluated by looking at the predictive Q 2 relevance value for the constructive model.Q 2 measures how well the model and its parameter estimates generate the observed values.A Q 2 value greater than 0 indicates that the model has predictive relevance, while if the Q 2 value is less than zero, the model lacks predictive relevance.
Hypothesis test.In testing the hypothesis, it can be seen from t-statistics and probability values.To test the idea using statistical values, for Alpha 5%, the t-statistic value used is 1.96.So the criteria for acceptance/rejection of the hypothesis are that Ha is accepted and H0 is rejected when the tstatistic > 1.96.To reject/accept the hypothesis using probability, Ha is accepted if the p-value <0.05.

Hypotheses:
H1: Getting lower tourist risk perception the higher the Destination Image.H2: The higher the Destination Image, the higher the Tourist Experience.
H3: The higher it is tourist Experience so the higher the revisit intention H4: Lower Tourist risk perception so the higher it Revisits intention.H5: The higher the destination Image so the higher is Revisit intention.
The conceptual framework of this research is shown in Figure 1.

RESULTS AND DISCUSSION
Measurement Model.Testing with the PLS approach is practical be-cause this test is not limited by the fulfilment of normally distributed data and limitations on the number of data samples.Data analysis using the PLS approach was first carried out by evaluating the measurement model.Using SmartPLS, Figure 2 is obtained, the output path diagram in SmartPLS 3.3.

Loading factor (convergent validity).
Convergent validity testing looks at the loading factor value (the correlation between item scores and construct scores).The indicators that measure the construct whose value is greater than 0.5 are considered significant so that they meet the convergent validity criteria [21].

Figure 2 -PLS-SEM Outputs
Variable tourist risk perception.The Table 1 presents the results of the calculation of the loading factor of the tourist risk perception variable.Variable Destination Image.The following Table 2 presents the results of the calculation of the loading factor for the destination image variable.Variable tourist experience.Table 3 presents the calculation results for the tourist experience variable loading factor.From Table 4, it can be seen that all of the revisit intention indicators have a factor loading value of > 0.50.Therefore, these indicators have met the criteria.
In addition to looking at the loading factor, Convergent Validity can be evaluated by looking at the Average Variance Extracted (AVE) value.The AVE > 0.50 is said to have met the convergent validity criteria [20].The value can be seen in Table 5.
It can be seen in Table 5 that the AVE value is more than 0.50.Therefore, the convergent validity criteria have been met.The rule of thumb usually used to assess construct reliability is that the composite reliability value must be greater than 0.7 [20], although 0.6 is still accepted [21].The value of the test results can be seen in Table 6.
It can be seen in Table 6 that the composite reliability value of each variable is more significant than 0.70, as well as the Cronbach's alpha value is by the recommended value (> 0.70).Therefore, composite reliability has been met.[20].
Table 7 shows that the value of the square root of the AVE (the number that is in the diagonal) for each variable is greater than the value of the correlation with the other variables (the number that is in one row and one column with the corresponding variable AVE).Thus, the research model has met discriminant validity. where able in the equation model.
The value of determination Q 2 generated as a result of the evaluation of this research model can be seen in the following Table 8.
The value of Q 2 > 0 is 0.769, which indicates that the model has very good predictive relevance.This means that the diversity of data that can be explained by this research model is 76.9%.While the rest is explained by other variables from outside the model that is not included in this research model.

Results Significance Test (Hypothesis Testing).
To determine the significance level, the p-value generated by running the Bootstrapping algorithm is used to determine whether the proposed hypothesis is accepted.The hypothesis will be supported at a significance level of 0.05 if the p-value is less than the critical value of 0.05 (5%).The results of the significance level test can be seen in Table 9, summarising the results of hypothesis testing with the PLS approach.The coefficient value is obtained from the SmartPLS output, which can be seen below.The results of the significance of the SmartPLS output image can be seen in Figure 3.

Figure 3 -Bootstrapping Test Results on SmartPLS
The H1 in this study states, "It is suspected that Tourist risk perception has a negative and significant influence on destination image Kuta Lombok destinations after the COVID-19 ".Through hypothesis testing with PLS, the test results show that the coefficient value is -0.387 with a p-value of 0.028 (smaller than the 5% (0.05) error tolerance) which is significant.It can be stated that the first hypothesis is accepted.
The H2 in this study states, "It is suspected that destination image has a positive and significant influence on tourist experience tourist destination Kuta Lombok after the COVID-19 ".Hypothesis testing with PLS with test results shows that the coefficient value of 0.385 with a p-value of 0.000 (lower than the error tolerance of 5% (0.05) means significant.It can be stated that the second hypothesis can be accepted.
The H3 in this study states, "It is suspected that tourist experience has a positive and significant influence revisit intention Kuta Lombok tourism destination after the COVID-19 ".Hypothesis testing with PLS test results shows that the coefficient value is 0.180 with a p-value of 0.003 (lower than the error tolerance of 5% (0.05), which means it is positive and significant.It can be stated that the third hypothesis is accepted.
The H4 in this study states, "Allegedly tourist risk perception has a negative and significant effect on revisit intention tourists at Kuta Lombok tourism destination after the COVID-19 ".Hypothesis testing with PLS test results shows that the coefficient value is -0.247 with a p-value of 0.031 (lower than the error tolerance of 5% (0.05), which means it is significant.It can be stated that the fourth hypothesis can be accepted.
The H5 in this study states, "Allegedly destination image has a positive and significant influence on the revisit intention of tourists of Kuta Lombok tourism destination after the COVID-19 ".Hypothesis testing with PLS test results shows that the coefficient value is 0.599 with a p-value of 0.000 (lower than the error tolerance of 5% (0.05), which means it is significant.It can be stated that the fifth hypothesis can be accepted.
Influence tourist risk perception to destination image.Researchers in tourism studies classify risk perceptions in several ways.For example, a study by [22] discussed the perceptions of risk associated with travellers when making their travel decisions and categorised them into four groups: war and political instability, health problems, crime and terrorist attacks.Five years later, authors [23] identified seven types of risk such as physical, financial, time, equipment, satisfaction, social, and psychological risks.
When tourists perceive a destination as an uncertain place to visit, it can influence the minds of potential tourists and discourage them from travelling to the destination or sometimes the entire region [24].
After an extensive literature review on the perceived risks associated with tourism activities, a study by [3] categorises them into six dimensions: physical risk, financial risk, performance risk, social risk, psychological risk, and security risk.Authors [25] identified six common types of risk associated with tourist destinations.However, due to the difficulty of interviewing tourists to distinguish between psychological and social risks, they combined these two types into one point.As a result, this study uses five dimensions of risk perception by [25]: perceived physical risk, perceived financial risk, perceived time risk, perceived socio-psychological risk and performance.
Natural disasters and associated risks can undermine the favourable image of the affected destination [26].Authors [27] empirical evidence reveals that physical constraints related to security and safety are very significant to goal images.This empirical evidence implies that perceived risk tends to influence the image of a destination [5].
The results obtained through hypothesis testing with a coefficient value is -0.253 with a p-value of 0.032, so it can be stated that Tourist risk perception has a negative and significant effect on destination image.
Influence destination image to tourist experience.Destination image is an essential factor that influences the tourist experience.Tourism experience research has evolved from the basics of the initial incident through satisfying experiences, quality experiences, and extraordinary experiences, to unforgettable experiences [28].During the satisfying and quality experience stage, satis-faction is considered one of the components of the tourist experience [29].The satisfaction level is determined by tourists' response to service quality subjectively and effectively [30].Previous studies have shown that the image of a destination significantly influences tourist satisfaction and revisit intention.For example, research by [31] found that destination image affects perceived quality, influencing satisfaction and behavioural choices.Authors [32] designed a quantitative study to examine the relationship between destination image, experience quality, perceived value, satisfaction and behavioural intention.The results reveal that the image of the destination has a direct positive influence on perceived value and experience quality.The quality of experience has a direct impact on satisfaction and an indirect effect on satisfaction through perceived value.
Authors [33] investigated the effect of destination image on tourist experience (i.e.satisfaction) and supported the relationship.Authors [32] designed a quantitative study to examine the relationship between destination image, experience quality, perceived value, satisfaction and behavioural intention.The results reveal that the idea of the destination has a direct positive influence on perceived value and experience quality.The quality of experience has a direct impact on satisfaction and an indirect effect on satisfaction through perceived value.
Based on the findings of this study, the researcher expands on the effect of destination image on experience quality and satisfaction on the tourist experience as an unforgettable experience.In a recent survey, [34] explores destination attributes related to MTE (Memorable Tourism Experience).These attributes essentially comprise a cognitive destination image, including the following ten dimensions: local culture, diversity of activities, friendliness, infrastructure, environmental stewardship, accessibility, service quality, physiography, place attachment, and superstructure.However, the author did not empirically test how this attribute affects MTE.
The results obtained through hypothesis testing with a coefficient value of 0.288 with a p-value of 0.027.It can be stated that destination image has a positive and significant effect on tourist experience.
Influence Tourist Experience to revisit intention.
According to [35] experience is an event that involves the individual personally.While [36] de-fine the experience as something fun, attractive, an unforgettable form of encounter for those who consume this event.Authors [35] revealed that the concept of consumer experience (customer experience) is the final stage of economic development that has evolved from the form of commodities, shifting to products and finally to the level of service (service).Authors [37] say that the experience economy is a comprehensive concept for service providers in the entertainment and recreation industry whose primary goal is to provide a high-quality experience.
Research conducted by [38] states that there is the more perceived value after experiencing a pleasant impression and experience so that the experience experienced will always be remembered in the consumers' lives after the consumer uses these services.This is in line with research conducted by [39], which states that to develop the tourism sector it is necessary to create pleasant conditions that will be a memorable experience consisting of components: hedonism, novelty, local culture, reflection, meaningfulness, involvement and knowledge.
Tourists who visit for tourist trips prioritise experience, visit, see, learn, and enjoy, and try to get out of routine activities that are usually felt daily.Tourists travel to gain experience, whether behavioural or perceptual, cognitive or emotional, or implied or explicit.
Results were obtained through hypothesis testing with a coefficient value of 0.176 with a pvalue of 0.009.So it can be stated that tourist experience has a positive and significant effect on revisit intention.
Influence of Tourist risk perception on revisit intention.In general, risk perception is used to describe the concept of people's attitudes and intuitive assessments of risk [40].Author [41] define it as a certain probability level that can be attached to risk to determine the probability of loss.Perceived risk can also be defined as the probability that an action may expose a traveller to a hazard that could influence travel decisions if the perceived threat is deemed to be beyond an acceptable level [42].
The involvement of tourist activities occurs due to motivations such as adventure, excitement, religious purposes, sporting events, and sometimes looking for new things [43].The last thing a traveller wants is to waste valuable vacation time and be in an unsafe destination; therefore, per-ceived risk has become a pressing concern among travellers around the world.In addition, based on the fact that the tourism industry is an intangible and experiential service-oriented industry, tourism products or services are considered more risky and vulnerable to threats such as crime, socio-political instability, terrorists, attacks [44], disease [45] and disaster [36].
From a marketing point of view, destinations that are considered safe are considered a pull factor, as well as a very important destination attribute that initiates travel desires.Thus, tourism destination managers go to great lengths to demonstrate that their destination is a risk-free place to visit as perceived risk has a significant impact on pre-visit decision-making by reminding rational decision-making regarding destination choice [44].That means that potential tourists should consider the destination safe and protected from the dangers posed by unwanted events.
Results research obtained through hypothesis testing with the coefficient value is -0.249 with a p-value of 0.028.It can be stated that tourist risk perception has a negative and significant effect on Kuta Lombok tourist destination after the COVID-19.
Influence destination image against revisit intention.Destination image is an impression created by tourists in their minds through several compressions, namely cognitive, affective, conative and also some things related to the way they view a tourist destination [46].Meanwhile, [47] proved that destination image significantly influences tourist satisfaction and the desire of tourists to visit again.
Destination image is defined as an individual's mental representation of knowledge (beliefs), feelings and overall perceptions about a particular destination [14].Goal images play two critical roles in behaviour: 1) influencing destination choice decision-making processes; 2) behavioral conditions after decision making including participation (on-the-spot experience), evaluation (satisfaction) and future behavioural intentions (intention to revisit and willingness to recommend) [16,31].Following a marketing perspective, [31] suggest that individuals have a favourable attitude toward destination imagery to view their onsite experience (i.e.travel quality) positively.
Results research obtained through hypothesis testing with coefficient value of 0.602 with a p-value of 0.000.So it can be stated that the destination image has a positive and significant effect on the revisit intention of tourists of Kuta Lombok tourism destination after the COVID-19.

CONCLUSIONS
From the results of research and discussion, it is concluded that.
1. Tourist risk perception has a negative and significant effect on destination image.This means that the higher the tourist risk perception felt by the Kuta Lombok destination after the COVID-19, the lower destination image they.On the other hand, if the lower tourists risk perception what tourists feel about Kuta Lombok after the COVID-19, the higher the perception destination image they.
2. Destination image positive and significant effect on tourist experience.That is, the higher the perception of the destination image, the higher the tourist experience is perceived by tourists.
On the other hand, the lower the perception of the Kuta Lombok tourism destination image, the lower the tourist experience they have.
3. Tourist experience has a positive and significant effect on revisit intention.The higher the tourist experience, the higher the revisit intention of tourists.Conversely, if the lower the tourist experiences of the tourists, the lower the revisit intention of tourists to the Kuta Lombok tourism destination.
4. Tourist risk perception has a negative and significant effect on Kuta Lombok tourist destination after the COVID-19.The higher the tourist risk perception felt by the Kuta Lombok tourism destination tourists, the lower their Revisit intention.On the other hand, the lower the tourist risk perception felt by the Kuta Lombok tourist destinations, the higher their revisit intention.
5. Destination image positively and significantly affects the revisit intention of tourists of Kuta Lombok tourism destinations after the COVID-19.This means that the higher the tourists' perception of the destination image Kuta Lombok after the COVID-19, the higher their revisit intention.On the other hand, the lower the destination image perception, the lower their revisit intention to the Kuta Lombok tourism destination after the COVID-19.

Table 1 -
Loading factors tourist risk perception

Table 2 -
Loading factors for destination image

Table 2
, it can be seen that all destination image indicators have a factor loading value > 0.50.Therefore, these indicators are then used as items in model testing.

Table 3 -
Loading factor for tourist experience

Table 3
, it can be seen that all tourist experience indicators have a factor loading val-ue>0.50.Therefore, these indicators are then used as items in model testing.Revisit intention.The following are the results of the calculation of the Reliability of the Revisit intention Variable.

Table 4 -
Loading factors for revisit intention

Table 6 -
Composite ReliabilityThe method can be used to compare the value of each construct's square root AVE with the correlation between other constructs in the model.If the AVE root value of each construct is greater than the correlation value between the construct and other constructs in the model, it is said to have a good discriminant validity value

Table 9 -
Structural Model Test Results