• Business Management

Tourism Satisfaction: Importance, Measurability & Impacts

Tourism Satisfaction

January 05, 2020 •

5 min reading

These questions and more were covered at EHL’s 3 rd Annual Hospitality Finance & Economics Research Conference, with keynote speaker Dr. Gang Li.

As a hospitality business leader, or destination management professional, what do you need to know about tourism? Does it help you to know where tourists go most and how much money that adds to the economy? Maybe so, but the most important factors for your business are what pleases tourists the most and what makes them grow your business as satisfied customers.

The steady growth of tourism reflects an important evolution in human economic and leisure activities and this is how it is currently measured: “It is one of the world's largest and fastest-growing economic sectors, supporting one in 10 jobs (319 million) worldwide and generating 10.4% of world GD.” ( WTTC 2019 )

The industry collects data about the economic contribution, numbers of arrivals, jobs created and the popularity of destinations. Even with Online Travel Review sites, such as TripAdvisor, nobody is really measuring tourist happiness and the impact of tourism on well-being, yet these are the insights that would help hospitality businesses and destinations to perform better in the future.

These issues were addressed by keynote speaker Dr. Gang Li at EHL’s 3 rd Annual Hospitality Finance & Economics Research Conference. Dr. Gang Li is a Professor of Tourism and Economics at the University of Surrey (UK) where he is also the Director of International Relations for the School of Hospitality and Tourism Management, and the Lead of the Competitiveness of the Visitor Economy research group in the school. He devised an index system for measuring tourism satisfaction and the impact on tourists’ well-being, and the results of this research could be very useful for shaping tourism experiences.

An Index for Tourism Satisfaction and Well-Being, by Dr. Gang Li

Dr. Gang Li began building his index to determine how to best measure tourism satisfaction, and whether or not tourism is good for people. As he pointed out, the pursuit of happiness is a major focus of people’s lives and also of indices, these days. Indeed, Switzerland owes its popularity in part to its frequent rating among the happiest countries in the world. So, if tourists are seeking happiness, then their happiness – not just the amount of money they spent, or the places they went – should be the measure to shape the future of tourism.

Measuring tourism satisfaction is important for several reasons, outlined in Dr. Li’s presentation:

  • Satisfied tourists stay longer, spend more and come back
  • They promote the provider on social media and online ratings, thereby contributing to business and destination competitiveness
  • They bring friends and family on their next visit
  • Satisfaction with vacation time impacts their overall quality of life
  • Tourism is about consuming an unknown product in unfamiliar surroundings, and is classified as an “export” in economic terms

How to measure tourism satisfaction

In order to correctly measure tourism satisfaction, Dr. Li considered many factors which could be evaluated by collecting the responses of tourists after their experience, using questionnaires or interviews. Some of the key elements were:

  • Expectations versus reality : subjects must be asked what they expected and how that expectation was met or not
  • Satisfaction must be measured for every part of the experience : Transportation, Immigration, Accommodation, Food & Beverage, Feature Experiences
  • The data must include personal factors such as age and gender
  • Capturing the data must be done quickly at the end of the experience , as a feeling of satisfaction or an intention to log a complaint may fade with time

As Dr. Li explained, “Destination Management Organizations, tour operators and amusement parks may be interested in this data because if we can identify what makes a tourist have a good experience, then they can direct their energy to improve the most important aspects for tourists and thereby improve the overall reputation of the destination or provider.”

Four keys to a happy tourist

Using these methods to evaluate a tourism experience in South Africa, Dr. Li came to some conclusions about the results:

  • High-cost experiences generally equal less happiness because the product does not seem to be worth the cost
  • High-quality experiences make people happy and often feature interactive and interpersonal experiences, sensory experiences (touch, taste, smell, etc.) and humorous, fun or exciting activities and people (guides, staff)
  • Any disagreement or complaint makes a negative overall impact , so providers must be on the lookout for signs of dissatisfaction and identify and correct problem areas in their service or product
  • Good tourism experiences create well-being that spills over into other areas of life . Therefore, it is not unfair to market tourism as something that changes and shapes one’s life, but the experience has to live up to the expectations

In the end, the index system is a first experiment in measuring tourism satisfaction, and this study creates a solid framework for further work. These findings give a good idea of where the emphasis should go for measuring satisfaction for destinations and tourism-facing business, such as a tourism agency or tour provider. It also leaves a lot of room for further development, and shows that there are key elements that could be measured for different types of tourism (cruises versus air-travel), and for different populations.

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The future of destination management

According to Dr. Li, the future of destination management is going to play out in three main areas: smart cities, personalized or targeted guest experiences and a better cohabitation between tourists and local people. He said, “I’ve seen a lot of research and effort going into creating smart cities. In China, they are working on making several of the most visited cities smart cities. They are making it possible to gather the data about where people are, what they are doing, automating some alerts and increasing services in response to high or low demand. This technology is already within our reach and through the mobile phones, we can know where people are, in what concentration.”

Satisfaction data could also be useful in designing a unique visitor experience depending on guests’ profiles, he pointed out. “Within an entertainment park, for example, if you could see what areas of a park are most enjoyed by certain customers depending on gender, age etc., then you could design guided tours and activities for those groups to increase their enjoyment of the park experience.”

Bridging the gap from research to application

At the end of his presentation, Dr. Li was humble about the implications of his research, he said, “As an academic, I can say that we focus first on getting the data right and making a reliable system, making sure it works, we don’t often have time to reach out the industry professionals to encourage them to adopt the framework. We need a bridge, people to take the learnings and adapt it to a professional level. The industry can’t use our research findings alone, they need interpretation and adaptation for their region. For example, a provider or hotel in one city or region may not be able to apply the learnings from another region. This is why indices are useful, if they work, then they can be applied to other projects in the industry for benchmarking purposes.”

EHL hosts these types of conferences to create that bridge between research and academia and the industry. Being close to the industry, EHL is attuned to their needs for applied research and through the EHL Advisory Services branch, they connect businesses and institutions with the consultants who can take this type of research and extend or apply it to a business case.

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  • Open access
  • Published: 16 August 2023

Exploring the determinants of destination satisfaction: a multidimensional approach

  • Ubais Parayil Iqbal   ORCID: orcid.org/0000-0002-5551-010X 1 ,
  • V. K. Hamza 2 ,
  • Lenin Kumar Nooney 1 &
  • Shajeer Sainudeen 3  

Future Business Journal volume  9 , Article number:  59 ( 2023 ) Cite this article

2100 Accesses

Metrics details

Tourism, as one of the major contributors to the world GDP, offers a wide range of economic and non-economic benefits to global society. The exchange of culture and values through travel and tourism improves harmony among people, which is essential for global peace. Consequently, governments have started giving policy significance to the tourism sector and making budget allocations for its promotion in their respective countries. This increased attention on tourism promotion through policy initiatives has fostered research attempts on various aspects of tourism, making it relevant and contemporary. However, few research attempts have been made to study the precursors of destination satisfaction. Therefore, the present study aims to fill this gap by studying the determinants of destination satisfaction through a multidimensional approach. The current study aimed to examine the dimensions of destination satisfaction and its role in deciding the destination loyalty. The study reveals interesting findings that helps the administrative apparatus in the tourism industry to come up with tailor-made policies to sustain and further enhance economic growth. The study findings reveal that factors such as satisfaction with destination characteristics, destination environment, and price significantly influence destination satisfaction among tourists visiting the Maldives. These findings underscore the importance of price as a determining factor in tourists' decision to visit the Maldives, suggesting the promotion of guesthouse tourism to provide a range of price options to attract a diverse tourist base. Additionally, the study emphasizes the necessity to enhance the quality of destination characteristics and prioritize environmental conservation efforts to ensure a positive tourist experience. The results highlight the important dimensions that determine the destination satisfaction of tourists visiting Maldives.

Introduction

The world is more open than ever, the standard of living is higher, and people are now traveling for tourism. Much research has been done to support the importance of repeat tourism, which is the most critical factor in tourism sustainability [ 32 , 81 ]. Scholars have suggested that consumers accumulate some degree of satisfaction by assessing various experiences in the process of purchase and consumption [ 4 ]. This customer experience rating leads to two approaches: item-specific satisfaction and cumulative satisfaction/overall satisfaction [ 22 , 63 ]. In contrast to this approach to destination satisfaction, the present study uses a multidimensional structure and four sub-dimensions to explain tourist destination satisfaction. The cumulative approach seems to be more practical for assessing destination satisfaction, as it can better assess tourist behavior [ 31 , 56 ]. Additionally, this study uses attributes that contribute most to the formation of tourist satisfaction from prior studies [ 7 , 34 ].

The Destination Satisfaction Index (DSI), jointly developed by Norstat and dp2research, declared Maldives as the top destination among mainstream tourist destinations during the second quarter of 2017. Moreover, Maldives scored the highest in terms of safety and beach satisfaction in the index, which is exceptional compared to other global destinations. This has attracted the attention of many scholars, and there are few studies conducted in the Maldives on the antecedents of destination satisfaction [ 23 , 44 , 99 ]. According to Weaver et al. [ 98 ], there is a significant association between loyalty and older married and high-income visitors who recognized the Maldives as an Islamic State and included the capital Male' in their itinerary. Furthermore, Jaleel et al. [ 45 ] reported that customer satisfaction is not mediating between perceived value and behavioral intent in the context of Maldives. A study conducted by Hameed [ 35 ] highlighted that policymakers should focus more on novelty, adventure, socializing, escape, relaxation, and social media marketing to improve the revisit intention. According to Popp et al. [ 75 ], customer feedback is an essential source of information for the hospitality industry and a powerful tool to help analyze and understand customer satisfaction as drivers to improve the quality of service.

Being one of the most sought-after destinations globally, the case of Maldives requires special attention. Moreover, the uniqueness of the supply-side factors also makes the case of Maldives unique and interesting. Unfortunately, no proper research has been conducted focusing on the destination satisfaction of the Maldives.

Even though the concept of customer satisfaction, loyalty and the connection between these two are widely discussed in the literature, there are only meager studies attempted to examine these in the tourism context. Moreover, the significance of this study also lies in the unique characteristics and high demand for the Maldives as a global tourist destination. While the tourism industry in the Maldives is thriving, there is a lack of focused research conducted in the Maldives to understand tourist preferences and satisfaction. By filling this gap, the study provides valuable insights that can have practical implications for the tourism industry in the Maldives. The findings of this study will contribute to identifying specific areas that require attention and improvement, based on the feedback from tourists. This knowledge can guide policymakers, tourism authorities, and industry stakeholders in enhancing the facilities and services offered in the Maldives. By understanding the key determinants of destination satisfaction, strategies can be developed to address any shortcomings and further enhance the overall tourist experience. Another significant aspect of this study is its approach to categorizing respondents' nationalities and their corresponding satisfaction levels. This unique perspective allows for a comprehensive analysis of how different nationalities perceive and evaluate their experiences in the Maldives. Such insights can help tailor marketing efforts and services to cater to the specific expectations and preferences of diverse tourist groups.

Any failure to identify the missing elements that lead to goal satisfaction is claimed to lead to industry failure [ 60 ]. Therefore, this study helps the tourism sector focus on the significant dimensions of destination satisfaction. Some of the beneficiaries involved in this survey include the Maldives Travel Agency and Tour Operators Association (MATATO), Ministry of Tourism, Maldives Marketing and Public Relations Corporation (MMPRC), Travel Agency Association (ATA), Destination Management Companies, and so on.

Aims and objectives

The study focused to evaluate the level of Destination Satisfaction among the tourists and its impact on generating Destination Loyalty. The specific objectives of the study are:

To Study the Impact of Various Dimensions of Destination Satisfaction on Destination Loyalty.

To Study the Moderation and Mediation Role of Tourists’ Demographics on their Destination Satisfaction to Destination Loyalty.

Theoretical contribution

Destination satisfaction and the revisit intention by the travelers can be explored with the theory of destination selection by [ 27 ]. According to the destination selection theory, travelers choose the destination based on the attributes of the spot which satisfy their desires. Adding on, the revisit intention is determined by the level of satisfaction of the traveler with regard to the ability of the spot in catering to their demands [ 6 , 16 , 17 , 20 , 58 , 61 , 73 , 78 , 89 , 103 ]. The return intention of tourists related to the recognition of the possibility of returning to the same destination is a specific element of favorable behavior after consumption and an important element of tourism loyalty [ 25 , 61 ]. Destination satisfaction, on the other hand, is specifically defined as "the overall emotions that result from visiting a tourist attraction" [ 25 ].

Although the positive impact of destination satisfaction on the intent of tourists revisiting the destination seems undeniable, the destination experience has been shown to be complex and involved in many ways [ 74 ]. Previous studies have focused on various factors of goal satisfaction, including unforgettable experience [ 103 ], and public transport [ 94 ].

When deciding on a vacation spot, travelers don't forget vacation spot attributes that could increase their memorable experiences [ 52 ], and buying travelers isn’t any exception. Although they allocate greater time and price range to buying than entertainment travelers [ 24 ]. Shopping travelers revel in traveling landmarks and well-known attractions, attempting the neighborhood cuisine, and admiring landscapes and road scenes [ 40 ]. Thus, a vacation spot must be located as attractive, affordable, safe, and reachable to travelers to meet their supposed journey purpose.

Literature review

The precursors of tourism have been extensively studied in different cultural and geographical contexts [ 1 , 5 , 8 , 13 , 33 , 44 , 48 , 57 , 72 , 77 , 96 , 100 ]. However, there is still a lacuna for a better comprehension of the terms and attributes which affect the destination satisfaction. Furthermore, the impact of destination satisfaction on loyalty has not been explored properly in the existing literature.

Destination satisfaction in tourism

Customer satisfaction and its implications by service providers play a major role in customer loyalty and travel destination approval [ 19 , 36 , 88 ]. According to Valle [ 95 ] tourists with more positive experiences at travel destinations are more likely to endorse and revisit. In a recent study, Chen and Liu [ 18 ] confirm that customer satisfaction comes from retaining that particular customer. Many studies look at why customers are dissatisfied with their travel destination and what influences their intention to return home. If tourists are dissatisfied with the experience, it is most likely due to their expectations not being met. However, in some studies, destination satisfaction diverges from an individual [ 97 ], and each experience accumulates overall satisfaction [ 3 ]. Clubs and others reportedly support discussions of predictability in different dimensions in generating destination satisfaction [ 43 , 82 ]. Previous studies have shown that tourists are more satisfied and attracted to destinations when their expectations are communicated during destination planning [ 17 , 71 ]. A dissatisfied tourist spreads negative reviews to his peers [ 86 ]. Satisfaction is a fundamental element of the travel and tourism market [ 84 ] and is the only way operators can generate revenue [ 36 ] and improve their strategies to increase the number of tourists to their destinations [ 54 , 79 , 84 , 101 ]. A conceptual framework by [ 13 ] was used in this study to determine the level of satisfaction and loyalty to a destination. Therefore, a set of variables that consumers reported to have influenced their satisfaction was selected.

Destination loyalty in tourism

Tourist satisfaction and loyalty are complementary, without satisfaction no loyalty cannot be created [ 79 ] (Hamza 2016), and tourists revisit intention is based on the experience of their previous visits [ 91 , 103 ]. In the context of tourism, loyalty means optimistic recommendations and willingness to return to a destination [ 70 ]. The personal experience of the traveler determines the satisfaction and loyalty of the destination [ 2 , 37 , 55 ], as the marketers are aggressive in market conditions, they should consider loyal customers as an asset to gain a competitive advantage [ 36 ]. Destination loyalty is measured using return intent and word of mouth as a measure of the individual items of each predictor.

Revisit intention

Tourist retention depends on the success of liberation [ 60 ]. Tourist behavior, willingness to revisit, and willingness to recommend are important factors that can be used to calculate destination loyalty [ 47 ]. Much research has been done in terms of willingness to revisit the destination [ 46 , 64 ], and the willingness to return to the destination may be a temporary rather than a permanent commitment. Mckerecher and Guillet [ 65 ] stated that there is sufficient data leading to a deadlock in repeated visits by tourists. These studies emphasize the inclusion of environmentally friendly destinations to continuously monitor destination loyalty and pay more attention to tourists [ 52 ]. Destination needs must be aware to understand their selling points to position themselves for loyal tourists [ 83 ]. Tourists' intention to return home can be measured as a cumulative assessment using a single-item scale [ 38 ].

Destination word of mouth

Another aspect of this survey is how overall satisfaction with the destination has contributed to the visitor's good recommendations in the past. Word of mouth is an important aspect of loyalty [ 30 , 39 ] found that positive reviews create social intent to recommend a product or service to others. First-time travelers who are reluctant to arrange travel due to risk will gain trust through word of mouth [ 93 ]. Kandampully et al. [ 49 ] argued that a travel customized trip increases customer satisfaction and spread positive reviews and then becomes loyal customers. So, travel and tourism are encouraging tourists to spread positive word of mouth. Satisfied customers are ready to provide positive insights to at least 5 people, and satisfied customers are excellent for travel and tourism who want to help others decide on their vacation destination [ 85 , 102 ].

Destination loyalty formation and demographic characteristics

Previous studies in the hospitality and tourism sector show that there is increasing academic interest in studying the demographic characteristics of various tourist destinations [ 51 , 70 ]. However, contradictory results can be seen in surveys based on demographics in tourism literature. Age and education are reported as the most important determinants of destination satisfaction, but income, occupation, marriage history, etc., are not related to tourist demographics and their image perception [ 9 , 11 ]. Adding on, previous studies have shown different results regarding the relationship between demographics and satisfaction [ 28 , 41 , 87 ].

Research gap

While the literature review highlights the importance of destination satisfaction and its impact on destination loyalty, there is a need for further research specifically focusing on the determinants of destination satisfaction in the context of the Maldives. While previous studies have explored factors such as customer satisfaction, revisit intention, word of mouth, and demographic characteristics in the tourism industry, there is a lack of research that specifically investigates the determinants of destination satisfaction in the Maldives. By conducting a study that examines the determinants of destination satisfaction in the Maldives, researchers can fill this research gap and contribute to the existing literature. Such a study would provide valuable insights into the factors that influence tourists' satisfaction levels and help identify areas that require attention and improvement to enhance the overall tourist experience in the Maldives. Furthermore, considering the unique characteristics and high demand for the Maldives as a tourist destination, understanding the specific determinants of destination satisfaction in this context would be highly relevant and practical for policymakers, tourism authorities, and industry stakeholders.

Therefore, it is important to examine the moderating role of demographics in the current study. In line with the above discussions the following hypotheses have been proposed.

Satisfaction with Destination Characteristics Influences Destination Satisfaction.

Satisfaction with Environment Influences Destination Satisfaction.

Satisfaction with Price Influences Destination Satisfaction.

Satisfaction with Hospitality Influences Destination Satisfaction.

Destination Satisfaction Influences Destination Loyalty

Age Moderates the Destination Satisfaction to Destination Loyalty.

Booking References moderates the Destination Satisfaction to Destination Loyalty.

Gender Moderates the Destination Satisfaction to Destination Loyalty.

Number of Visits (Previous Visit to the Destination) moderates the Destination Satisfaction to Destination Loyalty.

Age Mediates the relationship between Destination Satisfaction to Destination Loyalty.

Booking References mediates the relationship between Destination Satisfaction to Destination Loyalty.

Gender mediates the relationship between Destination Satisfaction to Destination Loyalty.

Number of Visits (Previous Visit to the Destination) mediates the relationship between Destination Satisfaction to Destination Loyalty.

Research methodology

Considering the nature of the research objectives, the study used a quantitative descriptive approach with survey design to study the research problem. The study has structured a questionnaire by adopting elements from previous literature. Random sampling method has applied to identify the respondents for the study. The study successfully collected 319 questionnaires from random international tourists who visited Velena international airport, Male’, Maldives during 2022.

Instrument development

In order to develop the instrument, similar studies in tourism sector in which tourist experiences and satisfaction were mapped have been reviewed. After thorough discussion on various instruments, the one developed for measuring destination satisfaction and loyalty by [ 13 ] has been considered. As per the validated scale, there are item-specific questions for measuring Satisfaction with the Destination Characteristics, Environmental satisfaction, Satisfaction with Prices and Satisfaction with Hospitality that constitute Destination Satisfaction for the current study. In order to check the Destination Loyalty, two sub-dimensions such as word of mouth and revisit intention has been used [ 39 ]. Besides, the demographic variables such as age, gender, number of visits and booking references have been identified to check the mediation and moderation role of Destination Satisfaction to Destination Loyalty. The final instrument undergone for face and content validity with 5 academicians and 5 tourist operators in Maldives and their suggestions on rewording few questions has been incorporated prior to the final data collection.

Data collection and analysis

The number of foreign tourists vising the Maldives constitutes the population of the study, since it is highly fluctuating each year the study assumes it as undetermined. Accordingly, the study determined the sample size of 385 by using the standard sample size formula. The study chose a confidence level of 95%, population size and proportion as undefined. The survey was conducted at the Velana International Airport in the Maldives with international inbound tourists through random sampling. The random tourists who returned to Velena international Airport after their visit to islands and resorts were requested to fill out the questionnaire after explaining the purpose of the study to them. Collection of responses after the experiences of tourist destinations helps the tourists to evaluate and share their agreeableness on various destination experiences and satisfaction levels. All the responses are collected under free will, and the respondents were given a chance to withdraw their responses before a reasonable time through email. Self-administered approach has been used in which each respondent read the questionnaire and marked the responses themselves. Out of the 385 questionnaires circulated, a total of 350 questionnaires were received back. At the end of the data collection, 319 completed questionnaires were received. The study used structural equation modeling to fit the model and test the hypotheses. The study adopted composite-based partial least squares structural equation modeling since it is more suitable for non-normal data. Adding on, both IBM SPSS and Smart PLS 3.0 software were used to analyze the data. The sample characteristics were generated through descriptive analysis in SPSS.

Description of the sample

The sample profile is summarized in Table 1 . The 319 respondents consist of 185 Female and 134 Male. Sufficient representation from various age groups were also gathered that includes 23 respondents belonging to 18–24 (7%), 100 respondents belonging to 25–34 with maximum tourists (31%), 74 respondents belonging to 35–44 (23%), another 74 respondents belonging to 45–54 (23%) and 48 respondents belonging to 55 and above (15%). Out of the total respondents, 199 visited Maldives before (62%) and 120 tourists are first-time visitors (38%). Tour agents plays a vital role in referring the destinations to tourists and influenced 149 tourists (47%), followed by online travel agency with 85 tourists (27%), resort/hotel website 34 (11%) and other categories such as own decision, family members, etc. accounts 51 (16%) tourists in persuading them to decide Maldives as a destination. Sufficient representation from each sub categories of demographic profiles has been ensured as the research hypothesized to study the moderating roles between antecedents and consequences of destination satisfaction.

Descriptive and general PLS analysis

Table 2 summarizes the descriptive statistics for all the manifest variables. The results show that the respondents were pleased with most of the attributes of tourists’ destination satisfaction. The mean score of various determinants of destination satisfaction shows above average that supports to conclude that most of the tourists are happy with the attributes. The mean score of 4.56 is reported for overall satisfaction with destination, indicating that the tourists’ expectations were met and that they were willing to revisit Maldives in future and recommend to their friends.

The study has used PLS-SEM to analyze the data. The result depicts the relationships between the proposed latent variables in a path model. The estimation procedures focus on estimating the structural path coefficients represented by the inner model. The outer model represents the measurement model and specifies the relationship between the latent variables and their indicators. PLS-SEM does not rely on distributional assumptions [ 29 ], and t -values is considered to check the significance of each path [ 36 ].

Table 3 provides the composite reliability and average variance extracted (AVE) scores as measures for internal consistency and convergent validity. All measurement items had significant extractions from the manifest items as the AVEs are greater than the threshold value of 0.5 so that the latent variables explain more than half of the variance of its indicators. The Fornel-Larker criterion has been used to assess the discriminant validity that states that the AVE of each latent construct should be greater than the highest squared correlations between any other constructs and the loadings of each indicator should be greater than all its cross loadings [ 21 , 29 ]. The square root of AVEs (Shows on the diagonal of the correlation matrix in bold) for each construct is higher than the correlation between that construct and any other construct, so the researchers concluded the data for the research shows internal consistency and convergent validity.

Table 4 shows the hypothesized path coefficients with t -statistic and P value. The original factor structure was retained to provide as much information as possible for the predictive analysis stage. Before testing the moderation of age, gender, number of visits and booking references on destination satisfaction to destination loyalty, the entire sample was submitted for analysis of the structural model. The results showed that all of the structural path estimates are significant except satisfaction with hospitality to destination satisfaction ( β 0.069, t  = 0.602). But theoretically, this path becomes very relevant as satisfaction with the hospitality does have impacts on determining overall destination satisfaction of tourists and retained these dimensions for analyzing moderation role of destination satisfaction with loyalty. Satisfaction with the price is the strongest predictor of destination satisfaction ( β 0.286, t  = 4.02) followed by satisfaction with destination characteristics ( β 0.228, t  = 2.236) and satisfaction with environments ( β 0.205, t  = 1.99). It shows that satisfaction with the price is the major influencer of destination satisfaction followed by destination characteristics and environments. It seems most of the tourists are price sensitive, and the tourist operators should bother about this aspect. The table shows destination satisfaction is an important predictor of destination loyalty ( β 0.538, t  = 8.788). Accordingly, first six hypotheses have been tested and found significant except hypothesis 4 as the t -statistic and P value are lesser than the threshold limit.

Table 5 shows the results of moderation analysis. It is hypothesized that the age, gender, booking references and number of visits moderate the influence of Destination Satisfaction on Destination Loyalty. Better understanding of these predictors could be achieved if we can explore the circumstances under which these relationships vary depending upon various categories of tourists and destination managers can realign their marketing strategies to segment and focus the most relevant customer groups. The researchers classified tourists based on their age, gender, frequency of visits (first time or more than once) and booking references/influencers such as tourist agent, online travel agencies, etc., and run the PLS-SEM to know the moderation of these attributes in predicting destination loyalty. Barron and Kenny [ 10 ] said that moderating effects would be evoked by variables whose variation influences the strength or the direction of relationship between an exogenous variable and the endogenous variable. In our study, it is hypothesized the destination satisfaction in predicting destination loyalty is moderated by age, gender, number of visits and booking references.

The moderation test results (Fig.  1 ) shows the results of each hypothesized paths. Satisfaction with destination characteristics ( β  = 0.228, t  = 2.245), satisfaction with environment ( β  = 0.205, t  = 1.981) and satisfaction with price ( β  = 0.286, t  = 4.133) significantly influence destination satisfaction. The hypothesized influences of satisfaction with hospitality did not predict destination satisfaction ( β  = 0.069, t  = 0.600). The destination satisfaction explains 50.2% variances on its determinants and can be confirmed as significant outcome of its predictors. The hypothesized influences of destination satisfaction to destination loyalty have been proven ( β  = 0.518, t  = 7.887). Accordingly, it is established that the tourists’ destination satisfaction significantly impacts on generation destination loyalty. Besides, destination loyalty accounts 31.7% variances in destination satisfaction, which can be considered as significant outcome. The moderation effect of age, booking reference, gender and number of visits has been tested with SmartPls, and the results of the analysis show age, booking references and number of visits to the destination did not moderate the destination satisfaction to destination loyalty. The moderating role of gender among the destination satisfaction and destination loyalty shows a p value of 0.082, which is more than the threshold limit of 0.05. But the researchers concluded that this path is not a significant one at 10% level of significance.

figure 1

Model fit results

Mediation effects

To investigate the mediation effect of age, gender, number of visits and booking references on the relationship between destination satisfaction (exogenous) and destination loyalty (endogenous), bootstrapping analysis was applied using 95% of confidence interval and 5000 subsamples in order to find out PLS-SEM means and standard deviations. The results of mediating effect of any of the variables over the relationship between destination satisfaction and destination loyalty can have three options such as no mediation, full mediation and partial mediation depending on P values and t -statistics [ 42 ]. If there is no direct relationship between exogenous and endogenous variables but shows significant relation between mediator and endogenous variable, we can conclude as full mediation effect. If the direct relationship between exogenous and endogenous variables is significant and the mediator to endogenous is not significant, we can conclude as no mediation effect. While both exogenous and mediator variables show significant path toward the endogenous variable, it is to be concluded as partial mediation.

Table 6 shows the results of mediation analysis. The results of the tables indicate the direct and indirect effects of exogenous, mediator and endogenous variables with the t-statistics and P value. The test results verify that age, gender and booking references did not mediate the relationship between destination satisfaction and loyalty. However, the test reveals number of visits has standardized indirect effect between destination satisfaction and destination loyalty. Accordingly, hypotheses 10, 11 and 12 have been rejected and hypothesis 13 has been confirmed with partial mediation.

Multicollinearity test for SEM

The multicollinearity test is used to check whether there are high inter-correlations among the independent constructs within the model. The multicollinearity test aims to approve the absence of problematic inter-collinearity among independent constructs that inflates the standard deviations for the exogenous variables and affects the significance test (t-statistic) for those variables unreliable. This test has the ability to show any problem that may occurs if there is a noteworthy correlation among the constructs, that is exogenous to endogenous. Theoretically, variance inflation factor (VIF) shouldn’t exceed 10. Moreover, the values between 5 and 10 are considered high collinearity and unfavorable data. The table shows that all of variance inflation factor (VIF) values for every constructs is less than 5 and the data used for PLS-SEM are free from any multicollinearity issues (Table 7 ).

Hypotheses testing

Table 8 shows the test results for all hypothesis. Hypothesis 1 investigates the level of influence on satisfaction with the destination’s characteristics on the overall destination. The hypothesis is significant, and the study shows that there is a positive influence of the destination’s characteristics on the overall destination satisfaction. This relationship was confirmed with previous studies [ 3 , 26 ]. Hypothesis 2 of the research investigates whether environmental satisfaction has an influence on the overall destination satisfaction. This hypothesis is significant and confirmed the path with previous literatures [ 62 , 68 ] and contradict with the findings of Khuong and Nguyen [ 50 ]. Hypothesis 3 of the study was confirmed as the satisfaction with price significantly influences destination satisfaction. The results were also confirmed by previous studies by Hamza and Zakkariya, [ 38 ]. Besides, price is the most influencing dimension in predicting destination satisfaction with highest t -statistic and path coefficient among the dimensions of destination satisfaction. Hypothesis 4 of the study is disproved as the t -statistic and P value are less than the threshold limit. But the researcher continued with this path as theoretically this influence is significant in predicting destination satisfaction [ 80 , 90 ].

Altogether, the destination satisfaction accounts 50.2% variances in its dimensions and statistically significant. Hypothesis 5 investigates the impact of destination satisfaction to destination loyalty and proved a significant influence in predicting tourists’ destination loyalty that holds 31.7% variances of its hypothesized determinants. The moderating role of age, gender, number of visits and booking references were disproved as the respective hypotheses were insignificant (H6, H7, H8 and H9). Therefore, it is concluded that selected demographics does not have any moderating role in predicting destination satisfaction to destination loyalty with respect to Maldives as a tourist destination. There are studies in another context where demographics moderate the impacts and vice versa [ 59 , 66 , 76 , 92 ].

The study has conducted a mediation analysis with selected constructs. The results shows that age, booking references and gender do not mediate the influences of destination satisfaction to destination loyalty as the respective hypotheses (H10, H11 and H12) do not show significance as per the validation criteria of their respective paths. However, hypothesis 13 shows partial mediation as both destination satisfaction and number of visits significantly predict destination loyalty. This finding can be attributed only to the scope of the study and Maldives as an identical destination as demographics may mediate destination satisfaction to destination loyalty in other contexts and destinations.

Discussion and practical implication

The study has adopted a four-dimensional approach to examine the destination satisfaction of international tourists, namely satisfaction with destination characteristics, destination environment, price and hospitality. The study has accepted the first three dimensions as significant predictors of destination satisfaction and rejected the fourth dimension, hospitality. However, this finding is contradicting with the findings of the study conducted by Bam and Nirajan [ 69 ] on the antecedents of tourist satisfaction in Nepal. According to a study conducted by Campo-Martínez and Garau-Vadell, [ 14 ], hospitality has been reported as a significant contributor of destination satisfaction. However, the current study rejects this hypothesis and this could be because of the uniformity in the hospitality received across the multinational resorts in different countries. Adding on, the study has found satisfaction with price as the most significant predictor of destination satisfaction. This finding is corroborating with the main stream literature that found a negative influence of price on destination satisfaction. According to Campo and Yague [ 15 ], the negative impact of price and tourism satisfaction could be due to considering price as a sacrifice. Another study by [ 67 ] has found price as an important reason for tourist’s revisit intention. However, there is another popular view that price is the indicator of quality. Hence, tourists perceive lower quality for less priced services and vice versa. However, the study results show that the tourists in Maldives are satisfied with the price charged for the services and that leads to the overall destination satisfaction. Therefore, it is important to note that the price of the service can influence the international tourist’s arrival in the Maldives. Moreover, the Ministry of tourism Maldives can focus on fostering guesthouse tourism in islands to make different price options available for the international tourists. Moreover, Maldives Travel Agency and Tour Operators Association (MATATO), Maldives Marketing and Public Relations Corporation (MMPRC) and Travel Agency Association (ATA) should try to keep the price competitive and reasonable measures should be taken to avoid any sort of price discrimination to foreign tourists.

The study has also reported destination characteristics as significant precursor of destination satisfaction. Hence, the tourism promotion apparatus in the country, which includes Ministry of Tourism and Destination Management Companies, should focus on building the necessary infrastructure to improve the quality of the destination characteristics. In addition, satisfaction with the environment is also found as significant in predicting the destination satisfaction. Therefore, the beneficiaries and the Government should take necessary action to protect the environment from different types of exploitations. Interestingly, age and gender are not moderating the path between destination satisfaction and brand loyalty. This finding is surprising and contradicting with the mainstream literature [ 12 , 53 ], which confirms the moderating role of age and gender. Moreover, number of visits is also not moderating the path between the destination satisfaction and loyalty. Adding on, number of visits partially mediates the relationship between destination satisfaction and destination loyalty. However, booking reference, age and gender are not mediating the path between destination satisfaction and destination loyalty.

In conclusion, the study has adopted a multidimensional approach to examine the destination satisfaction and loyalty of international tourists in the Maldives. While there is extensive literature on destination satisfaction and loyalty, there is a lack of evidence to support the role of predecessors of destination satisfaction on predicting the destination loyalty.

The findings provide empirical evidence that satisfaction with destination characteristics, destination environment, and price are significant predictors of destination satisfaction, while hospitality is not. The study highlights the importance of price in influencing tourists' arrival in the Maldives and suggests the promotion of guesthouse tourism to offer different price options. The study also emphasizes the need to improve the quality of destination characteristics and protect the environment. Surprisingly, age and gender do not moderate the path between destination satisfaction and brand loyalty, and the number of visits partially mediates the relationship between destination satisfaction and destination loyalty. It is therefore recommended that the Maldives tourism industry should focus more on building and maintaining better infrastructure and keeping the price competitive. Maldives has a good organic environment which attracts the tourists; however, the built-in environment and infrastructure in islands still requires improvements.

Limitations of the study and scope for future research

The current study used a cross-sectional research design with a survey method of data collection. While this approach has some advantages, it also has limitations. For example, the study was not able to explore micro-factors that may be unique to the islands of Maldives, which could have influenced destination satisfaction and loyalty. To address this limitation, future research could adopt a qualitative inquiry to explore more themes and factors that determine destination satisfaction and loyalty. Furthermore, future studies could compare the level of satisfaction in the northern and southern regions of the islands to identify areas that require government intervention. This comparison could provide insights into regional differences in satisfaction and help policymakers allocate resources more effectively. Finally, future research could focus on some of the peculiar features of the Maldives, such as the fact that the majority of the people speak English, and the availability of Halal restaurants. Understanding the impact of these unique features of the Maldives on destination satisfaction could not only enhance the literature but also help to identify areas of strength and areas for improvement in the tourism industry, and could inform strategies for promoting sustainable tourism development in the country.

Availability of data and materials

The collected data are available with the researcher; however, sharing of data will breach the ethical policies already undertaken.

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We acknowledge the support extended by the Villa College, Male, Maldives, for giving ethical approval for conducting this study in the Maldives.

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Iqbal, U.P., Hamza, V.K., Nooney, L.K. et al. Exploring the determinants of destination satisfaction: a multidimensional approach. Futur Bus J 9 , 59 (2023). https://doi.org/10.1186/s43093-023-00240-1

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  • Destination characteristics
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  • Destination loyalty

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tourist satisfaction index

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A Review on Tourist Satisfaction of Tourism Destinations

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The present paper is a detailed sort-out and critical review of the foreign literature on tourist satisfaction at destinations in the last decade. Four dimensions that the relevant research surrounded are identified: tourist satisfaction theoretical model; the relation between tourist satisfaction and loyalty, expectation and service quality; the tourists’ cultural backgrounds and cultural differences of the tourist satisfaction; and evaluation model of tourist satisfaction at destinations. The limitations of the previous research are briefly discussed, and future research directions are suggested attempting to provide reference and inspiration for the relevant domestic research and the tourism industry.

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  • Tourist satisfaction
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This work was supported by the Fundamental Research Funds for the Central Universities (No.2011JBM035) and Beijing philosophy and Social Science Fund(No.11JGC103).

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Chen, Y., Zhang, H., Qiu, L. (2013). A Review on Tourist Satisfaction of Tourism Destinations. In: Zhang, Z., Zhang, R., Zhang, J. (eds) LISS 2012. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32054-5_83

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The Hong Kong tourist satisfaction index

  • School of Hotel and Tourism Management
  • The Hong Kong Polytechnic University

Research output : Journal article publication › Journal article › Academic research › peer-review

  • MIMIC model
  • Tourist satisfaction

ASJC Scopus subject areas

  • Development
  • Tourism, Leisure and Hospitality Management

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  • 10.1016/j.annals.2011.06.001

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  • Hong Kong Keyphrases 100%
  • Satisfaction Index Keyphrases 100%
  • Tourist Satisfaction Keyphrases 100%
  • Tourist Satisfaction Index Keyphrases 100%
  • Indexes Social Sciences 100%
  • Satisfaction Social Sciences 100%
  • Tourists Social Sciences 100%
  • Model Computer Science 100%

T1 - The Hong Kong tourist satisfaction index

AU - Song, Haiyan

AU - van der Veen, Robert

AU - Li, Gang

AU - Chen, Jason L.

PY - 2012/1/1

Y1 - 2012/1/1

N2 - This study develops a tourist satisfaction assessment system based on a dual-model framework and demonstrates its general applicability. The first model concerns tourist satisfaction and its key antecedents and consequences. Structural equation modelling is employed to investigate the relationships amongst the constructs in the theoretical framework, and is then used as a basis for the computation of sectoral-level tourist satisfaction indexes. The second model is designed to estimate an aggregate service satisfaction index and an overall destination satisfaction index using a multiple indicator and multiple cause approach. The framework is applied to a large dataset that represents six tourism-related sectors and seven major source markets of inbound tourism to Hong Kong.

AB - This study develops a tourist satisfaction assessment system based on a dual-model framework and demonstrates its general applicability. The first model concerns tourist satisfaction and its key antecedents and consequences. Structural equation modelling is employed to investigate the relationships amongst the constructs in the theoretical framework, and is then used as a basis for the computation of sectoral-level tourist satisfaction indexes. The second model is designed to estimate an aggregate service satisfaction index and an overall destination satisfaction index using a multiple indicator and multiple cause approach. The framework is applied to a large dataset that represents six tourism-related sectors and seven major source markets of inbound tourism to Hong Kong.

KW - Hong Kong

KW - MIMIC model

KW - Tourist satisfaction

UR - http://www.scopus.com/inward/record.url?scp=82755189494&partnerID=8YFLogxK

U2 - 10.1016/j.annals.2011.06.001

DO - 10.1016/j.annals.2011.06.001

M3 - Journal article

SN - 0160-7383

JO - Annals of Tourism Research

JF - Annals of Tourism Research

Assessment of tourist satisfaction index: evidence from Armenia

he paper summarizes the arguments and counterarguments within the scientific discussion on the issue of tourist satisfaction evaluation. Satisfaction is the fulfilment of human needs. The distinction between tourist expectations and perceived performance shows the level of satisfaction or dissatisfaction. If expectations exceed perceived performance, this means that the customer is satisfied. Satisfaction leads to loyalty and revisits. Hence, it is crucial to evaluate the satisfaction level of tourists and find out gaps. Systematization literary sources and approaches for solving the problem indicate that many countries have their indexes to measure customer satisfaction. The main purpose of the research is to measure tourist satisfaction in Armenia. Investigation of the topic in the paper is carried out in the following logical sequence: the main literature was observed, the index and model of tourist satisfaction evaluation were elaborated for Armenia, and a survey was conducted among 385 incoming tourists during 2018. Methodological tools of the research methods were sociological survey, IPA analysis, CSAT, NPS methods. As a result of the calculations, the main issues of service quality were detected. The main results were analyzed using Importance-performance matrix. Also Customer satisfaction score and Net promoter score were calculated. The paper presents the results of an empirical analysis that shows the main gaps in the quality of tourism services

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Tourist satisfaction and subjective well‐being: An index approach

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The purpose of this research is to propose an index approach to study the impact of travel experience on tourists' satisfaction and the further impact on their sense of well‐being. Based on the latest development of tourist satisfaction research, that is, the tourist satisfaction indices, this innovative study further extends the two‐stage framework of tourist travel experiences to account for subjective well‐being and subsequently calculates a tourist well‐being index. A questionnaire with 496 respondents was used, which focused on four service sectors' tourist satisfaction indices. From this, a destination overall tourist satisfaction index and a tourist well‐being index were produced using the results of structural equation modelling. Some key findings include the higher the impact of the trip on tourist's sense of well‐being the higher the loyalty towards the destination. Different cultures had different results concerning the trip experiences (satisfaction) and the ...

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ahmad habib

Walter L Ruzzo

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IMAGES

  1. Pie-chart on tourist's satisfaction

    tourist satisfaction index

  2. The overall tourist satisfaction index model.Note: HTS, STS and TTS

    tourist satisfaction index

  3. Theoretical Framework of the Tourism Satisfaction Index at the Sectoral

    tourist satisfaction index

  4. The hypothesised sectoral-level tourist satisfaction index model

    tourist satisfaction index

  5. Tourist satisfaction statistics by gender.

    tourist satisfaction index

  6. RESEARCH SUMMARY

    tourist satisfaction index

COMMENTS

  1. Tourism Satisfaction: Importance, Measurability & Impacts

    An Index for Tourism Satisfaction and Well-Being, by Dr. Gang Li. Dr. Gang Li began building his index to determine how to best measure tourism satisfaction, and whether or not tourism is good for people. As he pointed out, the pursuit of happiness is a major focus of people's lives and also of indices, these days. Indeed, Switzerland owes ...

  2. Tourist satisfaction and subjective well-being: An index approach

    From this, a destination overall tourist satisfaction index and a tourist well-being index were produced using the results of structural equation modelling. Some key findings include the higher the impact of the trip on tourist's sense of well-being the higher the loyalty towards the destination. Different cultures had different results ...

  3. (PDF) Tourist Satisfaction Index for Tourism Destination, Integrating

    This paper integrates tourist engagement through social media into the European consumer satisfaction index to propose a destination tourist satisfaction index that can examine the tourist ...

  4. Exploring the determinants of destination satisfaction: a

    Additionally, this study uses attributes that contribute most to the formation of tourist satisfaction from prior studies [7, 34]. The Destination Satisfaction Index (DSI), jointly developed by Norstat and dp2research, declared Maldives as the top destination among mainstream tourist destinations during the second quarter of 2017.

  5. Analysis of Tourist Satisfaction Index Based on Structural ...

    3.2. Analysis of Tourist Satisfaction Index. In order to evaluate the tourist satisfaction index, the article uses normalization to process the original data, and the processing formula is The multilinear weighting algorithm calculates the tourist satisfaction index : Calculate the proportion of indicators:

  6. Tourist satisfaction and subjective well-being: An index approach

    The purpose of this research is to propose an index approach to study the impact of travel experience on tourists' satisfaction and the further impact on their sense of well‐being. Based on the latest development of tourist satisfaction research, that is, the tourist satisfaction indices, this innovative study further extends the two‐stage framework of tourist travel experiences to account ...

  7. Managing Tourist Satisfaction: An Index Approach

    ABSTRACT. In addition, by adopting a universal framework for performance evaluation and reporting, such as a tourist satisfaction index (TSI) system, service providers can establish internal targets to assess their performance over time and to provide useful comparisons with other organizations. The study computes the overall destination TSIs ...

  8. A Review on Tourist Satisfaction of Tourism Destinations

    Tourist satisfaction has become a hot topic for tourism research in the recent years. From foreign language databases like Wiley Blackwell, SCI (Web of Science) ISTP&ISSHP, Elsevier Science and Compendex (Ei village) etc., 68 research papers directly related to tourist satisfaction at destinations have been detected (up to March 23, 2012) with key words of "tourism satisfaction ...

  9. (PDF) Analysis of Tourist Satisfaction Index Based on Structural

    For the actual perceived quality, the observation index with a larger contribution rate to principal component 2 is mainly the tourists' evaluation of the satisfaction of the tourist attractions ...

  10. The Hong Kong tourist satisfaction index

    However, it is necessary to understand tourists' overall satisfaction with their entire travel experience in a destination in addition to their aggregate satisfaction with manageable services. Overall Destination Satisfaction Index for Hong Kong: 78.46. = (7.9809 × 0.3394 + 7.6045 × 0.3081 + 7.9280 × 0.3525) × 10.

  11. The tourist loyalty index: A new indicator for measuring tourist

    The tourist's global satisfaction is considered to be the most important antecedent of tourist destination loyalty (Chi and Qu, 2008, Chi, 2012, Mohamad et al., 2011, Neal and Gursoy, 2008). In the tourist area, satisfaction comes from tourists comparing their expectations with the results of the experience of the trip, the experience ...

  12. Full article: Tourists satisfaction in destination selection

    In the tourism context, satisfaction basically stands for the function of pre-visit expectations and post-visit encounters Asmelash & Kumar, Citation 2019). Pizam, Neumann, and Reichel ( Citation 1978 , p. 317) define tourist satisfaction as "a collection of tourists' attitudes about specific domains in their vacation experience".

  13. Determining satisfaction of international tourist: A different approach

    They focused on developing a tourist satisfaction index (TSI) based on the consumer satisfaction indexes (CSIs) by Chan et al. (2003), but with its own unique features. The research instrument of the present study was a structured questionnaire comprising three sections to measure the constructs in the proposed models. Section A was about the ...

  14. Tourist satisfaction and subjective well-being: An index approach

    From this, a destination overall tourist satisfaction index and a tourist well-being index were produced using the results of structural equation modelling. Some key findings include the higher the impact of the trip on tourist's sense of well-being the higher the loyalty towards the destination. Different cultures had different results ...

  15. The Hong Kong tourist satisfaction index

    Abstract. This study develops a tourist satisfaction assessment system based on a dual-model framework and demonstrates its general applicability. The first model concerns tourist satisfaction and its key antecedents and consequences. Structural equation modelling is employed to investigate the relationships amongst the constructs in the ...

  16. Assessing mainland Chinese tourists' satisfaction with Hong Kong using

    The first step estimates sectoral-level satisfaction indexes based on a structural equation model, and the second obtains an overall tourist satisfaction index by conducting second-order confirmatory factor analysis. This study is a pilot test of the theoretical framework based on three tourism-related service sectors in Hong Kong.

  17. Assessment of tourist satisfaction index: evidence from Armenia

    Investigation of the topic in the paper is carried out in the following logical sequence: the main literature was observed, the index and model of tourist satisfaction evaluation were elaborated for Armenia, and a survey was conducted among 385 incoming tourists during 2018.

  18. (PDF) The Satisfaction Index of Tourists Experience Quality: A Case

    This research aims to analyze the satisfaction index of tourism experience quality. The technique of collecting data was done by partipatory observation, questionnaire and interview. This study uses 14 indicators to measure the quality of the tourist experience. The data analysis technique was applying Customer Satisfaction Index.

  19. Tourist satisfaction and subjective well‐being: An index approach

    From this, a destination overall tourist satisfaction index and a tourist well‐being index were produced using the results of structural equation modelling. Some key findings include the higher the impact of the trip on tourist's sense of well‐being the higher the loyalty towards the destination. ...

  20. The Hong Kong tourist satisfaction index

    The second model is designed to estimate an aggregate service satisfaction index and an overall destination satisfaction index using a multiple indicator and multiple cause approach. The framework is applied to a large dataset that represents six tourism-related sectors and seven major source markets of inbound tourism to Hong Kong.

  21. Macao Tourist Satisfaction Index (MTSI)

    An overall satisfaction index (or TSI) for the tourism industry in Macao is then estimated based on the sectoral results. Essentially, the TSI tracks how well tourism services and organizations in Macao perform in satisfying visitors over time, identifying which sectors are weak or strong in performance. Information gathered from the MTSI is ...

  22. Full article: The moderating impacts of COVID-19 fear on hotel service

    The moderating impacts of COVID-19 fear on hotel service quality and tourist satisfaction: Evidence from a developing country. Md. Abu Issa Gazi a Faculty of ... Yeh, M. L., & Sung, M. L. (2013). A tourist satisfaction index model for international tourist hotels: Integrating consumption emotions into the American Tourist Satisfaction Index. ...

  23. Tourism satisfaction index (TSI) on traffic and non-traffic function in

    Tourist satisfaction should be understood by those involved in tourist activities and should serve as a basis for assessing the performance of products and service destinations (Noe and Uysal, 1997, Schofield, 2000). ... Methodology was developed to find the tourists' satisfaction index using traffic and non-traffic facilities which are ...

  24. PDF Analysis of Tourist Satisfaction Index Based on Structural Equation Model

    25-54 15-24. Over 55. Figure 3: Statistical chart of tourist satisfaction by age group. According to the statistical results in Table 5 and Figure 3, from the perspective of age, the 25-54 age group has the largest number of tourists, accounting for 59% of the surveyed, 14-24 years old accounted for 27%, and over.