Jarumas Saneha*
| Saad Shahrin | Maruf Gbadebo Salimon
© 2024 The authors. This article is published by IIETA and is licensed under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).
OPEN ACCESS
Thailand’s southern region is home to a number of prominent cultural tourism destinations, particularly those that offer gastronomy tourism. Hence, it is paramount that Southern Thailand develops its gastronomy tourism sector. It is crucial to enhance service quality to create a positive tourist experience and ensure their satisfaction. This study aimed to analyse the association between service quality and tourist satisfaction and its impact on gastronomy experience. Data from 387 valid questionnaires were analysed using a variance-based PLS-SEM method. Findings indicate that service quality and tourists’ gastronomy experience have a positive and significant effect on tourist satisfaction. Furthermore, the relationship between tourists’ gastronomy experience and service quality negatively moderates tourist satisfaction. This study has made an invaluable contribution to the existing corpus of knowledge on gastronomy tourism and presents implications for practitioners and interested parties as well as recommendations for future research.
service quality, gastronomy experience, tourists’ satisfaction, gastronomy tourism, sustainable tourism, environmental impact
A growing awareness on sustainable tourism’s impact has prompted a significant shift in of tourist operators’ tourism formats. The contemporary concept of travel is grounded in economic, social, resource, environmental, and cultural considerations. Tourism developers who work with WTO (World Tourism Organization) and PATA (Pacific Asia Travel Association) advocate eco-friendly travel in order to foster economic, community, cultural, and environmental development through community-wide participation and the generation of economic benefits [1]. Thailand’s tourism sector plays a significant role in its economy and its people, as outlined in the National Tourism Development Plan No.3 (2023-2027). This plan emphasises the importance of sustainable tourism based on inherent resources and the environment [2], while the National Innovation Agency or NIA (public organization) has identified opportunities for driving tourism growth by integrating innovation with tourism and the utilization of local identities to help enhance the travel experience for Thai and foreign tourists in efforts to enhance stakeholders’ experience and interests. Sustainable Tourism Innovation also intends to operate under the “City & Community Innovation Challenge 2024”. It plans to demonstrate that travel experience, gastronomy tourism, culture, and entertainment are integral to the development of a local identity and the enhancement of tourists’ travel experience. These elements are essential for the creation of tourism innovation to ensure that tourists derive satisfaction from their travel experiences. This is achieved through the provision of high-quality services [3].
The WEF (World Economic Forum) had ranked Thailand's tourism competitiveness at No.35, out of 141 countries in the world [4]. Thailand has an abundance of food sources with innumerable agriculture resources that can be used as raw materials, such as rice, Thai herbs, etc., for cooking a variety of local cuisines. Thai food is unique in food flavours and cooking methods vary from region to region, which makes Thai food even more delicious, unique as well as distinct in taste and identity that impresses tourists compared to other national dishes from other countries [5]. Tourists’ attitude towards Thai food in terms of variety, value for money and convenience in dining is highly commendable [6]. The Ministry of Tourism and Sports Thailand reported that the income generated from gastronomy tourism in Thailand was 456 billion Baht or 20% of the total revenue from tourism [7]. In 2019, foreign tourists spent 1,645.43 Baht on accommodation, followed by 1,270.77 Baht on food and beverage, while expenditure on food increased from the previous year (+ 1.07%) [1]. This clearly indicates that foreign tourists prioritize gastronomy experience and seek to immerse themselves in local Thai cuisine by paying a premium for the culinary experience [8].
Southern Thailand is a popular destination for foreign tourists, with the highest number of visits registered in 2023. Southern Thailand boasts two astonishing coastlines, namely the Andaman Sea to the west and the Gulf of Thailand to the east. Both these destinations offer plenty of natural resources and man-made attractions, such as marine parks with beautiful beaches and islands, including undersea natural resources (corals, fishes, etc.). These natural resources facilitate activities, such as diving and water sports, that attract both Thai and foreign tourists. In addition, the southern region is home to a prominent cultural tourist attraction, namely the local cuisine. Phuket was the first city in Thailand and in ASEAN, out of 18 cities worldwide, that received the Creative Gastronomy Science Recognition (among the seven categories contested) by UNESCO in 2014 [9].
However, Thailand faces challenges in developing its food tourism sector into a desirable travel destination for tourists due to their negative perception towards Thai food in relation to the standard of cleanliness, safety, services, etc [10]. Southern Thailand mainly lacks tourism promotions, diversity and service quality [9]. With all these factors affecting the development of gastronomy tourism, it is crucial to enhance service quality so that tourists leave with an unforgettable experience and a high level of satisfaction [11]. Naturally, tourists search for significant and memorable experiences in their travels. Unique events encourage tourists to develop a loyal bond and revisit their favourite tourist destination due to their positive experiences [12, 13]. Moreover, the experience affects the level of satisfaction and the intention to repurchase or revisit a particular tourist destination [14]. Tourist satisfaction has emerged as a significant factor in the tourism business. Numerous countries promote gastronomy tourism to increase their national income in the competitive tourism market by implementing marketing strategies, high-quality service, and unique selling points not found elsewhere to ensure tourists’ satisfaction. However, achieving a standardized effect and addressing tourist dissatisfaction presents both opportunities and limitations for gastronomy tourism [15].
Service quality dimensions include tangibility, reliability, responsiveness, assurance, and empathy, which many studies have attentively studied. Service quality is the key to customer satisfaction and one study, related to the UK fast food market, found the tangibility variable to be notably the most important factor that drives customer satisfaction [16]. Extensive research has found that substantial levels of customer satisfaction prevail in terms of interest and productivity, but there was a decline over time in service quality [17]. This current study applied the PLS-SEM technique to explore the relationship between service quality and tourist satisfaction and its moderating influence on gastronomy experience.
2.1 Service quality and tourists’ satisfaction
Service quality is a measure that gauges a service provider’s capability to meet the needs of service recipients (customers). Delivering quality service means responding to clients based on the client’s expectations [18]. Service quality includes the assessment of the customer’s overall experience and it serves as an indicator for assessing the customer’s level of satisfaction in order to offer top-notch service. It is crucial to determine the precise criteria for outstanding preferences and satisfaction that will become a standard that is beyond the client’s expectations [19]. Service quality is important because it impacts the growth of the service business, enables companies to establish a competitive advantage, enables consumers to determine repeat purchases or maintain brand loyalty, and reflects economic conditions [20]. Parasuraman et al. [21] identified five dimensions of SERVQUAL, namely tangibility, reliability, responsiveness, assurance and empathy. In gastronomy tourism, tangibility refers to the physical aspects, such as location, personnel, equipment, communication tools and symbols, as well as the environment. Reliability refers to the ability to provide services that match the common standards perceived by the customer. Every service rendered must be accurate, comprehensive, appropriate and consistent every time the service is provided [22]. Responsiveness is the service provider’s ability to respond to the service recipient’s needs within a reasonable time frame. Assurance refers to a service that features staff who are knowledgeable, capable, honest, polite, and possess good communication skills to establish trust in using the service. Empathy refers to the service provider’s equal attention to each customer and the ability to solve problems faced by each customer individually with effective communication skills so that the customer feels valued [23].
Lee et al. [24] found that the level of service quality has a direct impact on the level of customer satisfaction in Korean restaurants. Furthermore, Adundo [25] observed that desirable service quality not only enhances customer satisfaction, but it also encourages repeat purchases. Subsequently, the level of service influences tourism satisfaction [26]. Experiencing good quality service leads to tourist satisfaction, which has a significant effect on the tourist’s return intentions [27]. Hence, tourist satisfaction is a dynamic component of company policy in the travel industry that depends on the quality of a tourist’s experience and the service quality offered at a tourist destination [28].
2.2 Moderating effect of gastronomy experience
Chaney and Ryan [29] found that gastronomy tourism portrays and transmits the host culture to tourists through the historical and cultural identity of food or characteristics of the gastronomy experience. Mathwick et al. [30] pointed out that experiential principles refer to direct or indirect observation of a consumer’s impression of the goods or services offered, while experiential value is characterized as the interaction between customers and products or services, including direct or indirect use of products or services, which forms the basis of individual desires and interactions. Cuisine plays a significant role in tourism spending, and therefore, it is essential for tourists visiting any destination [31]. Gastronomic encounters either influence the satisfaction or dissatisfaction of tourists [32]. Majority of restaurants heavily rely on sensory qualities, such as aesthetics, environment, flair, feeling and sound. Research has indicated that the tourism and food industries play a significant role in providing practical value. Therefore, customers find that the attraction of experiential or meaningful enjoyment in restaurants does elicit emotions during meals [33].
The tourist’s experience directly impacts the overall satisfaction, including service quality satisfaction. Previous tourism experiences serve as a benchmark for assessing or anticipating expectations of tourists [34]. A tourist’s experience can lead to the overall perception of service quality, customer satisfaction, and post-consumption behaviour [35]. It affects the level of satisfaction derived from the service quality provided mainly when tourists come to visit or recognize the quality of service or recall previous positive experiences. Hence, if the service quality fulfils or surpasses the basic necessities and expectations of tourists, then a high level of satisfaction accruing from the quality of service will be achieved. Conversely, if the tourist’s experience falls short of the expected quality of service, the level of satisfaction is low [36]. Therefore, a tourist’s experience will contribute towards improving the satisfaction accruing from the standard of service quality offered [37]. Tourist satisfaction based on the experience gained will suggest a likelihood of returning to the same tourist destination or service provider [38].
Literature indicates that the tourist’s perspective influences the level of satisfaction. In particular, when enhancing aspects of an organisation’s growth and promotion, both satisfaction and dissatisfaction should be taken into account [39]. The experience gained by tourists from appreciable service quality directly impacts the level of satisfaction [40]. This study selected this variable as a moderator based on previous studies, such as Bradley et al. [41], Patterson and Johnson [42], and Prebensen et al. [38]. This study intended to investigate how gastronomy experience affects the relationship between service quality and tourist satisfaction.
This research used the stratified sampling method and collected data from foreign tourists who had visited Thailand, mainly places like Krabi, Phang Nga, Phuket and Surat Thani. Data were collected using self-administered questionnaires, which involved 420 questionnaires that were distributed and 410 valid questionnaires were returned in January 2022. The acceptable response rate was 98% [43]; however, only 387 datasets (92.14%) were ultimately selected for analysis. The dimensions and items that measure service quality were adopted by Parasuraman et al. [21], while gastronomy experience was adopted by Lai et al. [44] and tourist satisfaction was adopted by Castaldo et al. [45]. All preceding measures were modified to reflect the study context, ranging from "strongly agree" to "strongly disagree" on an assessment scale of 7 to 1 using a Likert scale.
3.1 Theoretical framework
Figure 1. Research framework
The research framework proposed in this study comprises three latent constructs, as in service quality, gastronomy experience, and tourist satisfaction. Figure 1 illustrates the causal relationship between these constructs.
3.2 Research hypotheses
H1: Service quality has a positive effect on tourists’ satisfaction.
H2: Gastronomy experience has a positive effect on tourists’ satisfaction.
H3: The relationship between service quality and tourist satisfaction moderates gastronomy experience.
This study utilized PLS-SEM path modelling to perform data analysis and validate the study’s hypotheses, which focus on reflective constructs, such as tourist satisfaction, service quality, and gastronomy experience. PLS-SEM was preferred because it is appropriate for this study, as demonstrated in previous researches [46, 47]. Fornell and Larcker [48] argued that PLS-SEM is the most appropriate method when a research aims to construct a theory and account for variability (predict the constructs). PLS-SEM has been utilised by scholars in various disciplines, such as marketing, consumer behaviour, as well as the travel, business and tourism industries. For example, it has been applied to comprehend elements that influence marketing efficacy and destination management [49]. In order to anticipate or investigate the research model, Partial Least Squares (PLS) can be employed as either a path model or a regression model to examine the correlation between numerous independent variables and one or more dependent variables.
3.3 Sample characteristics
Figure 2. Gender
Out of the 387 respondents, 55.3% were males, while 39.3% were females and 5.4% preferred not to disclose their gender (see Figure 2).
Figure 3. Age
Majority of the respondents were within the age range of 26 to 35 (58.1%) years. This was followed by the 36 to 45 (23.0%) age group, below 25 (10.1%), 46 to 55 (3.6%) as well as the 56 to 65 and over 65, both comprising 2.6% of the population (see Figure 3).
Figure 4. Number of times traveling to Southern Thailand
Most tourists were first-time travellers (51.4%), while the rest were returning tourists (48.6%), as shown in Figure 4.
Figure 5. Educational background
As for educational background, majority of the respondents held a Bachelor's degree (52.5%), followed by a Technical School/ Diploma (40.6%), Graduate School (5.9%), and Secondary School (1.0%) (see Figure 5).
Figure 6. Amount spent on food tourism
Majority of the tourists spent less than 10,000 Baht on food tourism (41.3%) per trip, followed by 10,001-20,000 Baht (37.2%), 20,001-30,000 Baht (14.2%), 30,001-40,000 Baht (3.9%), 40,001-50,000 Baht (2.6%), and lastly, more than 50,000 Baht (0.8%) (see Figure 6).
4.1 Assessment measurement model
As for the first-order construct, assessment of reflective measurement models involved four steps, namely examining item reliability, evaluation of composite reliability and internal consistency (Cronbach's alpha tests the reliability of a measure using statistical methods). Construct validity is determined by examining the loading and cross-loading of items, Convergent validity is measured by calculating AVE (average variance extracted) and Discriminant validity is assessed using the Fornell-Larcker criterion, cross loading, and the HTMT criterion [48].
Hair et al. [49] proposed that the indication reliability should be deemed acceptable when the loading is less than 0.70. Researchers should thoroughly analyse the impact after removing the indicator on other reliability and validity measures. The analysis revealed that the outer loading values varied from 0.708 to 0.943, as specified in Table 1. Consequently, all indicators were incorporated into the model.
Fornell and Larcker [48] suggested that the Internal Reliability (Cronbach’s alpha) and Composite Reliability value of 0.7 or higher is considered acceptable. This study included Cronbach's alpha and Composite Reliability values, which were between 0.777 and 0.944 (see Table 1) and these values reflect adequate Internal Reliability.
Table 1. Findings from the reflected measurement model
|
Latent Constructs |
Indicator |
α |
Loading |
CR |
AVE |
|
Tourist satisfaction |
|
0.944 |
|
0.953 |
0.695 |
|
|
SAT1 |
|
0.782 |
|
|
|
|
SAT2 |
|
0.868 |
|
|
|
|
SAT3 |
|
0.721 |
|
|
|
|
SAT4 |
|
0.765 |
|
|
|
|
SAT5 |
|
0.791 |
|
|
|
|
SAT6 |
|
0.879 |
|
|
|
|
SAT7 |
|
0.925 |
|
|
|
|
SAT8 |
|
0.855 |
|
|
|
|
SAT9 |
|
0.893 |
|
|
|
Horizontal Tourist Gastronomy Experience |
|
0.942 |
|
0.952 |
7.111 |
|
|
HGE1 |
|
0.864 |
|
|
|
|
HGE 2 |
|
0.844 |
|
|
|
|
HGE 3 |
|
0.824 |
|
|
|
|
HGE 4 |
|
0.875 |
|
|
|
|
HGE 5 |
|
0.857 |
|
|
|
|
HGE 6 |
|
0.814 |
|
|
|
|
HGE 7 |
|
0.837 |
|
|
|
|
HGE 8 |
|
0.830 |
|
|
|
Vertical Tourist Gastronomy Experience |
|
0.922 |
|
0.936 |
0.649 |
|
|
VGE1 |
|
0.730 |
|
|
|
|
VGE 2 |
|
0.763 |
|
|
|
|
VGE 3 |
|
0.854 |
|
|
|
|
VGE 4 |
|
0.719 |
|
|
|
|
VGE 5 |
|
0.807 |
|
|
|
|
VGE 6 |
|
0.832 |
|
|
|
|
VGE 7 |
|
0.875 |
|
|
|
|
VGE 8 |
|
0.849 |
|
|
|
Tangibles |
|
0.777 |
|
0.871 |
0.692 |
|
|
TAN1 |
|
0.819 |
|
|
|
|
TAN3 |
|
0.826 |
|
|
|
|
TAN4 |
|
0.849 |
|
|
|
Reliability |
|
0.915 |
|
0.940 |
07.98 |
|
|
REL1 |
|
0.915 |
|
|
|
|
REL3 |
|
0.827 |
|
|
|
|
REL4 |
|
0.929 |
|
|
|
|
REL5 |
|
0.898 |
|
|
|
Responsiveness |
|
0.935 |
|
0.949 |
0.755 |
|
|
RPS1 |
|
0.889 |
|
|
|
|
RPS 2 |
|
0.915 |
|
|
|
|
RPS 3 |
|
0.846 |
|
|
|
|
RPS 4 |
|
0.831 |
|
|
|
|
RPS 5 |
|
0.855 |
|
|
|
|
RPS 6 |
|
0.876 |
|
|
|
Assurance |
|
0.939 |
|
0.953 |
0.803 |
|
|
ASS 2 |
|
0.909 |
|
|
|
|
ASS 3 |
|
0.904 |
|
|
|
|
ASS 4 |
|
0.863 |
|
|
|
|
ASS 5 |
|
0.929 |
|
|
|
|
ASS 6 |
|
0.873 |
|
|
|
Empathy |
|
0.841 |
|
0.895 |
0.682 |
|
|
EMP 1 |
|
0.708 |
|
|
|
|
EMP 3 |
|
0.803 |
|
|
|
|
EMP 4 |
|
0.943 |
|
|
|
|
EMP 5 |
|
0.833 |
|
|
The minimum acceptable AVE level for each indicator in the construct is 0.5, which is used to assess the convergent reliability. This study's AVE values are between 0.649 and 0.803, as indicated in Table 1, and this confirms the convergent reliability.
In order to measure discriminant validity, the Fornell-Larcker criterion, cross loading, and HTMT criterion were used. The Fornell-Larcker criterion (square root of the average variance extracted (AVE) for each construct) is higher than the bivariate correlation values. The assessment was based on the item’s cross-loadings and an ideal standardised loading estimate of 0.7 or greater is regarded favourable [48].
The discriminant validity was confirmed by comparing the square root of the average variance extracted (AVE) in each construct with the bivariate correlation values, as shown in Table 2.
Table 2. Fornell-Larcker Criterion (First-Order Construct)
|
ASS |
EMP |
HGE |
REL |
RPS |
SAT |
TAN |
VGE |
|
|
ASS |
0.896 |
|||||||
|
EMP |
0.720 |
0.826 |
||||||
|
HGE |
0.504 |
0.591 |
0.843 |
|||||
|
REL |
0.585 |
0.555 |
0.419 |
0.893 |
||||
|
RPS |
0.777 |
0.794 |
0.562 |
0.658 |
0.869 |
|||
|
SAT |
0.512 |
0.550 |
0.739 |
0.476 |
0.520 |
0.834 |
||
|
TAN |
0.590 |
0.477 |
0.284 |
0.500 |
0.648 |
0.296 |
0.832 |
|
|
VGE |
0.482 |
0.531 |
0.758 |
0.389 |
0.568 |
0.679 |
0.315 |
0.806 |
Table 3 shows that all the cross-loadings are higher than 0.70, which indicates that the indicators’ outer loadings on the related constructs are greater than their cross-loadings on other constructs.
Table 3. Cross-Loading
|
|
ASS |
EMP |
HGE |
REL |
RPS |
SAT |
TAN |
VGE |
|
ASS2 |
0.909 |
0.686 |
0.431 |
0.535 |
0.717 |
0.454 |
0.555 |
0.423 |
|
ASS3 |
0.904 |
0.591 |
0.355 |
0.598 |
0.657 |
0.410 |
0.488 |
0.367 |
|
ASS4 |
0.863 |
0.485 |
0.289 |
0.498 |
0.577 |
0.321 |
0.480 |
0.277 |
|
ASS5 |
0.929 |
0.667 |
0.514 |
0.457 |
0.694 |
0.496 |
0.526 |
0.483 |
|
ASS6 |
0.874 |
0.730 |
0.586 |
0.540 |
0.786 |
0.537 |
0.571 |
0.535 |
|
EMP1 |
0.567 |
0.708 |
0.352 |
0.621 |
0.688 |
0.364 |
0.414 |
0.219 |
|
EMP3 |
0.560 |
0.803 |
0.425 |
0.467 |
0.571 |
0.412 |
0.336 |
0.448 |
|
EMP4 |
0.675 |
0.943 |
0.562 |
0.535 |
0.739 |
0.534 |
0.432 |
0.515 |
|
EMP5 |
0.576 |
0.833 |
0.578 |
0.261 |
0.634 |
0.487 |
0.401 |
0.527 |
|
HGE1 |
0.541 |
0.568 |
0.864 |
0.405 |
0.574 |
0.671 |
0.379 |
0.669 |
|
HGE2 |
0.547 |
0.552 |
0.844 |
0.458 |
0.578 |
0.675 |
0.413 |
0.609 |
|
HGE3 |
0.371 |
0.459 |
0.824 |
0.392 |
0.487 |
0.578 |
0.224 |
0.589 |
|
HGE4 |
0.408 |
0.508 |
0.875 |
0.363 |
0.509 |
0.605 |
0.215 |
0.657 |
|
HGE5 |
0.531 |
0.544 |
0.857 |
0.384 |
0.503 |
0.679 |
0.308 |
0.676 |
|
HGE6 |
0.321 |
0.407 |
0.814 |
0.262 |
0.380 |
0.577 |
0.143 |
0.606 |
|
HGE7 |
0.296 |
0.450 |
0.837 |
0.282 |
0.359 |
0.590 |
0.092 |
0.663 |
|
HGE8 |
0.338 |
0.476 |
0.830 |
0.254 |
0.373 |
0.593 |
0.088 |
0.639 |
|
REL1 |
0.568 |
0.571 |
0.386 |
0.915 |
0.671 |
0.476 |
0.543 |
0.355 |
|
REL3 |
0.538 |
0.446 |
0.389 |
0.827 |
0.482 |
0.438 |
0.375 |
0.346 |
|
REL4 |
0.518 |
0.495 |
0.346 |
0.929 |
0.581 |
0.384 |
0.403 |
0.317 |
|
REL5 |
0.449 |
0.456 |
0.367 |
0.898 |
0.605 |
0.387 |
0.448 |
0.366 |
|
RPS1 |
0.682 |
0.690 |
0.450 |
0.690 |
0.889 |
0.438 |
0.529 |
0.396 |
|
RPS2 |
0.725 |
0.725 |
0.560 |
0.590 |
0.915 |
0.502 |
0.575 |
0.523 |
|
RPS3 |
0.705 |
0.762 |
0.581 |
0.402 |
0.846 |
0.481 |
0.515 |
0.547 |
|
RPS4 |
0.582 |
0.660 |
0.512 |
0.513 |
0.831 |
0.455 |
0.582 |
0.586 |
|
RPS5 |
0.677 |
0.622 |
0.377 |
0.629 |
0.855 |
0.404 |
0.620 |
0.424 |
|
RPS6 |
0.675 |
0.664 |
0.421 |
0.628 |
0.876 |
0.416 |
0.563 |
0.466 |
|
SAT1 |
0.469 |
0.521 |
0.595 |
0.395 |
0.512 |
0.783 |
0.318 |
0.481 |
|
SAT2 |
0.450 |
0.529 |
0.649 |
0.514 |
0.538 |
0.870 |
0.333 |
0.619 |
|
SAT3 |
0.251 |
0.401 |
0.586 |
0.257 |
0.354 |
0.723 |
0.234 |
0.605 |
|
SAT4 |
0.298 |
0.299 |
0.488 |
0.485 |
0.351 |
0.765 |
0.197 |
0.453 |
|
SAT5 |
0.342 |
0.335 |
0.624 |
0.291 |
0.323 |
0.789 |
0.096 |
0.517 |
|
SAT6 |
0.444 |
0.442 |
0.629 |
0.384 |
0.394 |
0.878 |
0.224 |
0.589 |
|
SAT7 |
0.516 |
0.543 |
0.683 |
0.460 |
0.506 |
0.924 |
0.308 |
0.642 |
|
SAT8 |
0.535 |
0.531 |
0.629 |
0.367 |
0.451 |
0.854 |
0.237 |
0.567 |
|
SAT9 |
0.460 |
0.486 |
0.642 |
0.410 |
0.443 |
0.893 |
0.250 |
0.597 |
|
TAN1 |
0.560 |
0.429 |
0.188 |
0.423 |
0.589 |
0.237 |
0.819 |
0.189 |
|
TAN3 |
0.495 |
0.401 |
0.192 |
0.495 |
0.498 |
0.238 |
0.826 |
0.229 |
|
TAN4 |
0.424 |
0.365 |
0.321 |
0.337 |
0.531 |
0.261 |
0.850 |
0.359 |
|
VGE1 |
0.650 |
0.554 |
0.589 |
0.309 |
0.542 |
0.573 |
0.358 |
0.730 |
|
VGE2 |
0.398 |
0.429 |
0.540 |
0.195 |
0.375 |
0.478 |
0.219 |
0.763 |
|
VGE3 |
0.279 |
0.426 |
0.644 |
0.349 |
0.487 |
0.547 |
0.239 |
0.855 |
|
VGE4 |
0.153 |
0.310 |
0.540 |
0.295 |
0.367 |
0.439 |
0.102 |
0.720 |
|
VGE5 |
0.216 |
0.344 |
0.617 |
0.327 |
0.442 |
0.497 |
0.218 |
0.807 |
|
VGE6 |
0.216 |
0.348 |
0.595 |
0.333 |
0.414 |
0.519 |
0.205 |
0.832 |
|
VGE7 |
0.537 |
0.490 |
0.671 |
0.348 |
0.508 |
0.652 |
0.326 |
0.875 |
|
VGE8 |
0.534 |
0.475 |
0.662 |
0.332 |
0.489 |
0.620 |
0.305 |
0.849 |
Criteria involve using the Herotrait-Monotrait (HTMT) statistical test with bootstrapping (Table 4). This involves creating 5,000 random subsamples and using bootstrap confidence intervals to determine whether the HTMT value is below the threshold value of 0.9 [50]. The HTMT ratio in this study is less than 0.90; therefore, this study has established discriminant validity.
Table 4. Heterotrait-Monotrait
|
Construct |
ASS |
EMP |
HGE |
REL |
RPS |
SAT |
TAN |
VGE |
|
ASS |
- |
|
|
|
|
|
|
|
|
EMP |
0.796 |
- |
|
|
|
|
|
|
|
HGE |
0.508 |
0.651 |
- |
|
|
|
|
|
|
REL |
0.627 |
0.648 |
0.445 |
- |
|
|
|
|
|
RPS |
0.816 |
0.899 |
0.588 |
0.714 |
- |
|
|
|
|
SAT |
0.520 |
0.608 |
0.780 |
0.508 |
0.548 |
- |
|
|
|
TAN |
0.687 |
0.597 |
0.319 |
0.591 |
0.762 |
0.342 |
- |
|
|
VGE |
0.481 |
0.582 |
0.810 |
0.420 |
0.602 |
0.719 |
0.360 |
- |
4.2 Assessment measurement model (Second-Order construct)
Second-Order constructs in this study include service quality and gastronomy experience, both of which are also reflective measurement models, like the assessment of the measurement model, which involves the First-Order construct [51].
Table 5 and Figure 7 show that the outer loading is between 0.722 and 0.942, Cronbach's alpha is between 0.859 and 0.900, both Composite Reliability have a value of 0.926, and AVE values are between 0.716 and 0.873. Therefore, this study confirms the convergence reliability.
Table 5. Results of the reflective measurement model (Second-Order construct)
|
Latent Constructs |
Indicator |
α |
Loading |
CR |
AVE |
|
Service Quality |
|
0.900 |
|
0.926 |
0.716 |
|
Tangibles |
|
0.722 |
|
|
|
|
Reliability |
|
0.798 |
|
|
|
|
Responsiveness |
|
0.932 |
|
|
|
|
Assurance |
|
0.898 |
|
|
|
|
Empathy |
|
0.865 |
|
|
|
|
Tourists’ Gastronomy Experience |
|
0.859 |
|
0.926 |
0.876 |
|
Horizontal Tourists’ Gastronomy Experience |
|
0.942 |
|
|
|
|
Vertical Tourists’ Gastronomy Experience |
|
0.930 |
|
|
Figure 7. Measurement Model (Second-Order construct)
Discriminant validity was established in this study (see Table 6) and the square root of AVE in each construct is greater than the bivariate correlation values.
Table 6. Fornell-Larcker Criterion (Second-Order construct)
|
|
EXP |
SAT |
SQ |
|
EXP |
0.936 |
|
|
|
SAT |
0.750 |
0.833 |
|
|
SQ |
0.579 |
0.566 |
0.846 |
According to Table 7, all the cross-loadings exceed 0.70. This suggests that the indicators have higher loadings on the constructs they are related to, compared to their loadings on other constructs.
Table 7. Cross-Loading (Second-Order construct)
|
|
SQ |
EXP |
SAT |
|
TA |
0.722 |
0.298 |
0.296 |
|
REL |
0.798 |
0.425 |
0.470 |
|
RES |
0.932 |
0.594 |
0.520 |
|
AS |
0.898 |
0.480 |
0.502 |
|
EM |
0.865 |
0.585 |
0.549 |
|
HO |
0.556 |
0.942 |
0.733 |
|
VE |
0.528 |
0.930 |
0.668 |
|
SA1 |
0.544 |
0.570 |
0.785 |
|
SA2 |
0.566 |
0.671 |
0.871 |
|
SA3 |
0.350 |
0.635 |
0.727 |
|
SA4 |
0.407 |
0.505 |
0.765 |
|
SA5 |
0.338 |
0.613 |
0.787 |
|
SA6 |
0.449 |
0.638 |
0.877 |
|
SA7 |
0.558 |
0.697 |
0.923 |
|
SA8 |
0.509 |
0.623 |
0.852 |
|
SA9 |
0.492 |
0.648 |
0.891 |
As illustrated in Table 8, HTMT is less than 0.90, thus, this study has demonstrated the establishment of discriminant validity.
Table 8. Heterotrait-Monotrait (Second Order construct)
|
Construct |
EXP |
SAT |
SQ |
|
EXP |
- |
|
|
|
SAT |
0.829 |
- |
|
|
SQ |
0.640 |
0.596 |
- |
4.3 Assessment of the structural model (Second-Order construct)
The structural model illustrates the hypothesized correlation between the constructs or latent variables in this study.
4.3.1 Collinearity issue in the structured model
VIF values were employed to assess collinearity issues in the structured model. The rule of thumb value acceptable for a VIF score is less than 5 [51]. The VIF values for this study ranged from 1.534 to 2.011, and none of them were above the cutoff value.
4.3.2 Significance of path coefficients (Hypothesis Testing)
Hair et al. [51] recommended using bootstrapping with 5,000 sub-samples for establishing the significance of path coefficients in order to evaluate the hypothesized model. Table 9 illustrates the significance of the paths, with t-values shown along the key paths. Hence, this study's hypotheses are directed. The values indicate that the hypothesized relationships between the constructs are statistically significant at a 5% level of significance, except for one of the relationships. In addition, a t-value of 1.645 was compared to critical levels.
Table 9. Structural model assessment (Second-Order Construct)
|
Hypothesis/Path |
Path Coefficients |
t Value |
p Value |
95% Confidence Intervals |
Significance (p<0.05) |
Decision |
|
|
H1: SQ -> SAT |
0.100 |
2.020* |
0.022 |
[0.015, 0.177] |
Yes |
Support |
|
|
H2: EXP -> SAT |
0.611 |
15.866*** |
0.000 |
[0.543, 0.670] |
Yes |
Support |
|
|
H3: EXP*SQ -> SAT |
-0.119 |
4.661*** |
0.000 |
[-0.162, -0.079] |
Yes |
Not Support |
|
According to Table 9, the finding supports H1 (β = 0.100, t-value = 2.020, p > 0.05). Thus, service quality has a positive and significant effect on tourist satisfaction.
Tourists’ gastronomy experiences have a positive and significant effect on tourist satisfaction. This finding supports H2 (β = 0.119, t-value = 15.866, p > 0.01). The relationship between tourists’ gastronomy experiences and service quality is positively moderated by the effect of tourist satisfaction. However, the results do not support H3, as the interaction impact is negative (β = -0.119, t-value = 4.661, p > 0.05).
4.3.3 Predictive relevance and effect size
Evaluation of a model's quality relies on its capacity to accurately forecast endogenous constructs. The coefficient of determination (R²) quantifies the level of prediction accuracy exhibited by the model. According to Hair et al. [51], it is generally considered acceptable for the R² value to be higher than 0.25 for important target constructs. A value of 0.25 is considered weak, 0.50 is considered medium, and 0.75 is considered significant for target constructs. In the present investigation, the R² value is 0.608 (see Table 10); hence, the R² value for the target construct is classified as medium.
Once the structured model's predictive relevance was assessed and verified, the magnitude of the impacts (f²) was examined. The effect size, denoted by f², measures the degree to which each element contributes to the model's adaptation.
The f² is determined by observing alterations in R² when a specific construct is removed from the model [51].
Cohen [52] suggested that an f² value of 0.35 indicates a large effect, an f² value of 0.15 indicates a medium effect, an f² value of 0.02 indicates a minimal effect, while an f² value of less than 0.02 indicates no effect.
This study’s f² values for the exogenous factors are shown in Table 10. It indicates that the f² value for gastronomy experience is 0.621 and the moderating effect of gastronomy experience and service quality is 0.049 (large effect). In contrast, the f² value for service quality is 0.013, thus, there is no effect.
In order to evaluate the forecasting significance of the structural model, this study analysed the Q² (cross-validated redundancy). Chin et al. [53] proposed that a Q² value greater than 0.5 indicates a high level of predictive relevance, a Q² value over 0.25 suggests a moderate level of predictive relevance, and a Q² value above 0 suggests a low level of predictive relevance. The current investigation revealed a Q² result of 0.412, as shown in Table 10. This suggests that the path model has a medium degree of predictive relevance.
Table 10. Results of the structured model
|
Construct |
Common Method Bias (VIF) |
f Square (f²) |
Q Square (Q²) |
R Square (R²) |
|
Tourists’ Satisfaction |
||||
|
EXP |
1.543 |
0.621 |
0.412 |
0.608 |
|
SQ |
2.011 |
0.013 |
||
|
EXP*SQ |
1.675 |
0.049 |
||
The main purpose of this study was to analyse the positive effects of service quality and gastronomy experience on tourist satisfaction and to determine whether gastronomy experience in association with service quality moderates tourist satisfaction in Thailand. The postulated hypotheses are supported by the empirical outcomes of this investigation, hence, H1 and H2 are supported, while H3 is not supported. This study provides practical suggestions that can assist stakeholders in developing and sustaining factors that influence tourist satisfaction in the context of gastronomy tourism in Thailand.
Findings demonstrate that service quality has a positive and significant effect on tourist satisfaction, which is consistent with previous studies [53, 54]. Therefore, it is confirmed that satisfaction increases due to a robust perception of service quality and its direct association with tourist satisfaction, hence, its estimation and development is a crucial aspect of destination management. Astuti and Dewi [55] found that service quality in a tourist destination must meet the expectations of tourists.
Tourists’ gastronomy experience has a greater positive and significant effect on tourist satisfaction compared to service quality. This finding is consistent with Ali et al. [56] and Rajan [57], who both found a positive relationship between tourists’ experience and satisfaction. Furthermore, a tourist’s real experience is construed as tourist satisfaction after experiencing the event and it stems from the psychological feeling produced by a person's traveling experience. This highlights the importance of focusing on tourists’ experience to ensure overall satisfaction [58].
Meanwhile, the correlation between tourists' gastronomy experience and service quality is adversely influenced by the level of tourist satisfaction. This suggests that the greater influential impact of gastronomy experience weakens the connection between tourist satisfaction and service quality. Conversely, the relatively minor influence of gastronomy experience amplifies the stronger connection between service quality and tourist satisfaction.
The results are consistent with Forgas-Coll et al. [59], who discovered that tourists with extensive travel experience exhibit a lower correlation between service quality and tourist satisfaction. Conversely, tourists with limited travel experience demonstrated a high correlation between service quality and tourist satisfaction. Tourists’ experience directly impacts the overall satisfaction, and thus, directly affects tourist satisfaction of the service quality.
Tourists' experience serves as a basis or consideration for assessing or anticipating expectations in the minds of tourists [60]. Therefore, if service quality meets the needs and expectations of tourists or exceeds the actual or acknowledged experience, it will result in a high level of service quality satisfaction. However, if tourists' experience do not meet the expected service quality, then their level of satisfaction will be low [61].
This study examined how gastronomy experience is influenced by the association between service quality and tourist satisfaction in Southern Thailand. It has contributed to the existing corpus of knowledge in the field of gastronomy tourism and presented implications for both practitioners and future research.
6.1 Practical implications
Firstly, it provides restaurants and gastronomy tourism agencies with an insight into gastronomy tourism regarding the significance of high-quality service in achieving competitive advantage in the gastronomy tourism sector.
Secondly, since tourist satisfaction depends on the tourist’s actual experience of gastronomy tourism, hence, restaurants and gastronomy tourism agencies must develop different strategies and activities tailored to the expectations and desires of gastronomy tourists.
Finally, this study’s findings suggest that tourists with a higher level of gastronomy experience will experience less satisfaction due to their higher initial expectations of gastronomy tourism that have been established by prior experiences with other destinations. Therefore, the Tourism Authority of Thailand and relevant gastronomy tourism agencies should develop effective policies for the management of gastronomy tourism in southern Thailand and other gastronomy tourism destinations. Conversely, tourists with less experience in gastronomy tourism might experience greater satisfaction upon receiving higher quality services. Consequently, restaurants and gastronomy tourism agencies should prioritize the offering of functional and technical high-quality services as well as positive experiences to meet the needs of these less experienced tourists.
6.2 Theoretical implications
The theoretical implications of this study can be observed from the extension of service quality and the moderators of gastronomic experience who are skilled in predicting tourist satisfaction. The present study offers a theoretical framework for the gastronomy tourism industry in southern Thailand. It offers a methodology that academic scholars can use to evaluate the generalizability of service quality and the factors that influence gastronomy experience theories as well as explore the potential for combining these concepts to predict tourist satisfaction. The results of this study also offer new insight into the field of entrepreneurship, Ministry of Tourism and Sports, Thailand and gastronomy tourism agencies.
6.3 Limitations and future research
This current study has limitations that can be further explored and mitigated. One area for further investigation is the application of this study’s model to a certain area in Thailand. Accessibility, time constraints and the repercussions of COVID-19 also posed limitations. Future research can be expanded to include other related variables, such as tourists’ intentions, tourists’ expectations and tourists’ loyalty. The hypothesized model can be replicated in another gastronomy tourism destination to verify its general applicability to other populations.
[1] Ministry of Tourism and Sports. (2019). The complete report of project to promote sustainable tourism. https://www.mots.go.th/download/Research/ProjectToPromoteSustainableTourism.pdf/, accessed on Jul. 26, 2024.
[2] Office of the National Economic and Social Development Council. (2023). National Economic and Social Development Plan No. 13 (2023-2027). https://www.nesdc.go.th/article_attach/article_file_20230307173518.pdf, accessed on Jul. 26, 2024.
[3] National Innovation Agency (Public Organization). (2024). Thailand's sustainable tourism innovation: New challenges on the global stage. https://www.nia.or.th/Sustainable-Tourism-Innovation-in-Thailand, accessed on Jul. 26, 2024.
[4] National Tourism Policy Committee. (2017). The second national tourism development plan (2017-2021). https://secretary.mots.go.th/ewtadmin/ewt/policy/download/article/article_20171130140746.pdf, accessed on Apr. 9, 2020.
[5] Thanasabkasem, S. (2013). A comparative study of Thai and American’s eating cultures for an adjustment of people of the two countries. Journal of Cultural Approach, 14(26): 70-82.
[6] Sinluksanatip, A., Groen, N. (2019). A study of Thai fine-dining experience to create a design guideline for Thai restaurant in United States (No. 177879). Thammasat University.
[7] Ministry of Tourism and Sports. (2016). Popular destinations in the South of Thailand among international tourists. http://www.kasikornresearch.com/TH/K-EconAnalysis/Pages/Search.aspx?cid, accessed on Jul 24, 2024.
[8] Henkel, R., Henkel, P., Agrusa, W., Agrusa, J., Tanner, J. (2006). Thailand as tourist destination: Perceptions of international visitors and Thai residents. Asia Pacific Journal of Tourism Research, 11(3): 269-287. https://doi.org/10.1080/10941660600753299
[9] Bunsirat, W. (2017). Guidelines for food development for tourism in Phuket. National Institute of Development Administration, Faculty of Tourism Management, PhuketCenter. http://www.tour.nida.ac.th/wp-content/phuket-gastronomy.pdf, accessed on Jan. 19, 2020.
[10] Sirilux Kesornpatumanunt, Piyathip Pradujprom and Kanok Panthong. (2023). The Development of Assessment Criteria in Gastronomic Tourism Management with Real-Time Delphi Techniques. https://so02.tci-thaijo.org/index.php/JRKSA/article/download/261541/176553/1038805.
[11] Narunchara kitwirakan. (2014). Thai food image, quality perceived and tendency to revisit Thailand. Journal of International and Thai Tourism, 10(1): 12-28.
[12] Niculescu, G. (2014). Economia experienței în turism șiindustriile creative. http://www.turismulresponsabil.ro/wp-content/uploads/2014/04/12.
[13] Pine, B.J., Gilmore, J.H. (2013). The experience economy: Past, present and future. In Handbook on the Experience Economy. Edward Elgar Publishing.
[14] Pappas, O., Pateli, I.G., Giannakos, A.N., Chrissikopoulos, V. (2014). Moderating effects of online shopping experience on customer satisfaction and repurchase intentions. International Journal of Retail & Distribution Management, 42(3): 187-204. http://doi.org/10.1108/IJRDM-03-2012-0034
[15] Singsomboon, T. (2014). Marketing strategids for Thai gastronomic tourism national promotion. Thailand: Institute of Development Administration.
[16] Nguyen, Q., Nisar, T.M., Knox, D., Prabhakar, G.P. (2018). Understanding customer satisfaction in the UK quick service restaurant industry: The influence of the tangible attributes of perceived service quality. British Food Journal, 12(6): 1207-1222. https://doi.org/10.1108/BFJ-08-2017-0449
[17] Oh, H., Kim, K. (2017). Customer satisfaction, service quality, and customer value: Years 2000-2015. International Journal of Contemporary Hospitality Management, 29(1): 2-29. https://doi.org/10.1108/IJCHM-10-2015-0594
[18] Lewis, B.R., Mitchell, V.W. (1990). Defining and measuring the quality of customer service. Marketing Intelligence & Planning, 8(6): 11-17. http://doi.org/10.1108/EUM0000000001086
[19] Parasuraman, A., Zeithaml, V.A., Berry, L.L. (1985). A conceptual model of service quality and its implications for future research. Journal of Marketing, 49(4): 41-50. http://doi.org/10.1177/002224298504900403
[20] Martin, D.W. (1995). An importance/performance analysis of service providers' perception of quality service in the hotel industry. Journal of Hospitality & Leisure Marketing, 3(1): 5-17. https://doi.org/10.1300/J150v03n01_02
[21] Parasuraman, A., Zeithaml, V.A., Berry, L.L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perc. Journal of Retailing, 64(1): 12-40.
[22] Zeithaml, V.A., Parasuraman, A., Berry, L.L. (1990). Delivering Quality Service: Balancing Customer Perceptions and Expectations. Simon and Schuster.
[23] Peter, P., Donnelly, J.H. (2004). Marketing Management: Knowledge and Skills. 7th ed. New York: McGraw - Hill.
[24] Lee, S.M., Lee, K.P., Liu, Y. (2013). Effects of Korean restaurant selection and service quality on customer satisfaction and loyalty of Chinese living in Korea. The Journal of the Korea Contents Association, 13(1): 447-455. http://doi.org/10.5392/JKCA.2013.13.01.447
[25] Adundo, M. (2023). Factors influencing customer satisfaction with services offered by tours and travel agencies in Nairobi. PhD Thesis., Strathmore University, 2023.
[26] Tefera, O., Govender, K. (2017). Service quality, customer satisfaction and loyalty: The perceptions of Ethiopian hotel guests. Journal of Hospitality, Tourism and Leisure, 6(2): 1-22.
[27] Nguyen Huu, T., Nguyen Ngoc, H., Nguyen Dai, L., Nguyen Thi Thu, D., Truc, L.N., Nguyen Trong, L. (2024). Effect of tourist satisfaction on revisit intention in Can Tho City, Vietnam. Cogent Business & Management, 11(1): 2322779. https://doi.org/10.1080/23311975.2020.1796249
[28] Soufivand, M. (2012). Enhancement of tourism service delivery performance through value co-creation: A system dynamic approach. Case study: Cultural heritage sector in Sicily. Master thesis, Production Engineering and Management, KTH Royal Institute of Technology, Department of Production Engineering.
[29] Jiménez-Beltrán, F.J., López-Guzmán, T., González Santa Cruz, F. (2016). Analysis of the relationship between tourism and food culture. Sustainability, 8(5): 418. https://doi.org/10.3390/su8050418
[30] Mathwick, C., Malhotra, N., Rigdon, E. (2001). Experiential value: Conceptualization, measurement and application in the catalog and internet shopping environment☆. Journal of Retailing, 77(1): 39-56. https://doi.org/10.1016/S0022-4359(00)00045-2
[31] Richards, G. (2012). Food and the tourism experience. Global Report on Food Tourism, UNWTO, Madrid, 20-21.
[32] Fox, A., Berrick, J.D. (2007). A response to no one ever asked us: A review of children’s experiences in out-of-home care. Child and Adolescent Social Work Journal, 24(1): 23-51. https://doi.org/10.1007/s10560-006-0057-6
[33] Yang, S., Liu, Y., Xu, L. (2024). The effect of food tourism experiences on tourists' subjective well-being. Heliyon, 10(3): e25482. https://doi.org/10.1016/j.heliyon.2024.e25482
[34] Zeng, L., Yi Man Li, R. (2021). Tourist satisfaction, willingness to revisit and recommend, and mountain kangyang tourism spots sustainability: A structural equation modelling approach. Sustainability, 13(19): 10620. https://doi.org/10.3390/su131910620
[35] Jankingthong, W., Gonejanart, P. (2012). The relationships of factors affecting post-purchase behavioral intentions in tourism sector. Silpakorn University Journal of Social Sciences, Humanities, and Arts, 12(1): 72-90.
[36] Sawangrat, N. (2018). Evaluation of expected service quality compared with perceived service quality to develop quality and sustainable tourist attractions for the Agro tourism industry in Rayong Province, Thailand. Social Sciences Journal, 8(3): 53-66.
[37] Chareenpong, P. (2003). International tourists satisfaction with the quality of service in accommodation in Thailand. Master’s Thesis, Mahidol University, Thailand.
[38] Prebensen, N.K., Kim, H., Uysal, M. (2016). Cocreation as moderator between the experience value and satisfaction relationship. Journal of Travel Research, 55(7): 934-945. https://doi.org/10.1177/0047287515583359
[39] Correia, A., Moital, M., Da Costa, C.F., Peres, R. (2008). The determinants of gastronomic tourists’ satisfaction: A second-order factor analysis. Journal of Foodservice, 19: 164-176. https://doi.org/10.1111/j.17454506.2008.00097
[40] Chen, C.F., Chen, F.S. (2010). Experience quality, perceived value, satisfaction and behavioral intentions for heritage tourists. Tourism Management, 31(1): 29-35. https://doi.org/10.1016/j.tourman.2009.02.008
[41] Bradley, M.J., Maples, J., Lewis, A., Berend, K.J. (2017). Beer tourism in Central Kentucky: Identifying on-site experience preferences for Kentucky brewery tourists. Journal of Gastronomy and Tourism, 2(3): 153-161. https://doi.org/10.3727/216929717X14870140201035
[42] Patterson, P.G., Johnson, L.W. (1995). Focal brand experience and product-based norms as moderators in the satisfaction formation process. Journal of Consumer Satisfaction, Dissatisfaction and Complaining Behavior, 8: 22-31.
[43] Berdie, D.R., Anderson, J.F, and Niebuhr, M.A. (1986). Questionnaires: Design and Use. Scarecrow Press.
[44] Lai, I.K., Lu, D., Liu, Y. (2020). Experience economy in ethnic cuisine: A case of Chengdu cuisine. British Food Journal, 122(6): 1801-1817. https://doi.org/10.1108/BFJ-08-2018-0517
[45] Castaldo, S., Grosso, M., Mallarini, E., Rindone, M. (2016). The missing path to gain customers loyalty in pharmacy retail: The role of the store in developing satisfaction and trust. Research in Social and Administrative Pharmacy, 12: 699-712. https://doi.org/10.1016/j.sapharm.2015.10.001
[46] Henseler, J., Wilson, B., Westberg, K. (2011). Managers' perceptions of the impact of sport sponsorship on brand equity: Which aspects of the sponsorship matter most? Sport Marketing Quarterly, 20(1): 7-21.
[47] do Valle, P.O., Assaker, G. (2016). Using partial least squares structural equation modeling in tourism research: A review of past research and recommendations for future applications. Journal of Travel Research, 55(6): 695-708. https://doi.org/10.1177/0047287515569779
[48] Fornell, C., Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1): 39-50. https://doi.org/10.1177/002224378101800104
[49] Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E. (2010). Multivariate Data Analysis (7th Edition). NJ: Prentice Hall.
[50] Gold, A., Malhotra, A., Segars, A. (2001). Knowledge management: An organizational capabilities perspective. Journal of Management Information Systems, 18: 185-214.
[51] Hair, J.F., Ringle, C.M., Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice， 19(2): 139-152. https://doi.org/10.2753/MTP1069-6679190202
[52] Cohen J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd Edition). Lawre Associatesnce Erlbaum.
[53] Chin, W.W., Henseler, J., Wang, H. (2010). Handbook of Partial Least Squares: Concepts, Methods and Applications. Springer-Verlag Berlin Heidelberg.
[54] Anggara, A.P., Lin, C.W., Mao, T.Y., Susanto, E. (2023). Effects of food authenticity, food quality, and service quality on tourist satisfaction under multiple regression model during COVID-19. In AIP Conference Proceedings, 2685(1): 050005. https://doi.org/10.1063/5.0113828
[55] Astuti, N.S., Dewi, L. (2022). Analysis of service quality and tourism destination parts on visitor satisfaction at Taman Mini Indonesia Indah. TRJ Tourism Research Journal, 6(1): 140-151. http://doi.org/10.30647/trj.v6i1.142
[56] Ali, F., Ryu, K., Hussain, K. (2016). Influence of experiences on memories, satisfaction and behavioral intentions: A study of creative tourism. Journal of Travel & Tourism Marketing, 33(1): 85-100. https://doi.org/10.1080/10548408.2015.1038418
[57] Rajan, V. (2015). Factors affecting tourist destination loyalty: A case study of Munnar, India as a tourism destination. In International Conference on Business, Economics and Management, Phuket, Thailand, pp. 18-21.
[58] Baker, D.A., Crompton, J.L. (2000). Quality, satisfaction and behavioral intentions. Annals of Tourism Research, 27(3): 785-804. https://doi.org/10.1016/S0160-7383(99)00108-5
[59] Forgas‐Coll, S., Palau‐Saumell, R., Matute, J., Tárrega, S. (2017). How do service quality, experiences and enduring involvement influence tourists' behavior? An empirical study in the Picasso and Miró Museums in Barcelona. International Journal of Tourism, 19(2): 246-256. https://doi.org/10.1002/jtr.2107
[60] Larsen, S. (2007). Aspects of a psychology of the tourist experience. Scandinavian Journal of Hospitality and Tourism, 7(1): 7-18. https://doi.org/10.1080/15022250701226014
[61] Boonpat, O., Suvachart, N. (2014). Tourist expectation and tourist experience in cultural tourism. Journal of Tourism and Hospitality Management, 3(2): 124-132. https://doi.org/10.17265/2328-2169/2014.03.004
