Dissatisfaction Responses of Tourists in the Havana World Heritage Site

Abstract

This paper aims to assess the relationships between tourists’ negative evaluation of key management areas in the cultural city, their overall satisfaction and future intentions. More specifically, this paper proposes a covariance-based structural equations model (CB-SEM) to assess the influence of tourists’ dissatisfaction caused by failures in tourist and cultural services, hygiene and infrastructure on their overall satisfaction with the cultural trip and their intentions to repeat it. Using data collected from 1500 tourists visiting Old Havana on a cultural trip, this paper confirms that a negative opinion on the management of hygiene, cleanliness and crowding is dominant in explaining cultural tourists’ lower levels of satisfaction. In addition, this was found to be the only factor with a negative impact on tourists’ intentions to revisit the city in the future. The results are useful for helping managers of cultural destinations to distinguish the areas that are most relevant in their attempt to promote satisfaction and loyalty in the context of cultural tourism.

1. Introduction

Cultural tourism worldwide accounts for over 39% of international tourism arrivals [1], with some 500 million tourists a year [2,3]. Strengthening cultural tourism has a positive effect on those destinations subject to high seasonality [4], since for this particular market segment, the weather conditions of the destination are not a limiting factor. Cultural tourists spend more and stay longer at the destination on average, thus resulting in a high profitability potential compared to other segments [5]. Thanks to its potential, cultural tourism stands out as a key sector for the sustainability of many coastal and island destinations that are highly dependent on tourist activity, especially ‘sun, sea and sand’ tourism [1,4].

At the same time, for a cultural tourist, whose main motivation is to discover, learn about, experience and consume cultural products and services at a tourist destination, the tourism superstructure, infrastructures, transport, crowding, and hygiene are fundamental attributes and components of the cultural experience [1,6,7,8]. However, previous studies have not analyzed how the negative opinions of tourists about these features in a cultural city affect their evaluation to the trip and attitudes towards the visited destination. This type of information can help cultural destinations to better explain and predict tourists’ decision making [9,10,11].

Thus, the purpose of this article is to assess the impact of tourists’ dissatisfaction with key areas of weaknesses in the cultural city on their overall satisfaction with the trip and their intentions to repeat it. To the best of our knowledge, this is the first study analyzing the dissatisfaction-based evaluation of tourists as a predictor of their overall satisfaction and future intentions towards cultural destinations.

The novelties of the paper are in the design and validation of a structural equations model (SEM) that explains the relationships between dissatisfaction, satisfaction and loyalty (in its attitudinal dimension) in the context of cultural tourism, which can be easily verified in several typologies of cultural destinations and sub-segments.

This study is therefore of great importance for destination management and marketing organizations that plan the development of cultural tourism as a key driver for tourism competitiveness and positioning improvement, alerting them as to which areas of the destination present a higher probability to generate dissatisfaction among cultural tourists, and thus affect their overall evaluation of the destination and their intentions to revisit it.

The proposed model is empirically investigated by surveying 1500 cultural travelers visiting Havana’s old city, a World Heritage Site since 1982. This destination is seeking to promote cultural tourism as part of its tourism diversification strategy. In recent years, Havana, the capital of Cuba, has become a leading destination, receiving more than 60% of all international tourists visiting the country, and placing in the top three of the most visited cities in the Caribbean region. However, this positioning may be fundamentally affected by the tremendous uncertainty caused by the COVID-19 pandemic. The post-COVID-19 scenario for this destination is uncertain, as it is for many other cultural destinations worldwide [6,12].

This paper is structured as follows: (i) the following section is dedicated to presenting the results of a literature review on the study of satisfaction/dissatisfaction and loyalty in the context of cultural tourism; (ii) the review section pays special attention to empirical works that have been undertaken in coastal regions and islands, as well as to the role of destination attributes that may be relevant in explaining the behavior of cultural tourists; (iii) the third section describes the study—the model, the fieldwork, and the research instruments utilized for data collection; (iv) the fourth section is dedicated to presenting the results of the study; finally, (v) the remaining sections are dedicated to the discussion, the conclusions of the research and the references.

2. Theoretical Foundations

2.1. Cultural Tourism

As articulated by Norval [13], the history of travel begins in the most remote antiquity, its origins springing from human needs and desires. On the other hand, cultural heritage is testimony to the values and work of people; it is unique in a physical space and its authenticity provides a potential tourism resource able to trigger visits and generate activity at destinations [14,15]. Thus, cultural heritage becomes a differentiation key for destinations and capitalizes on the interest generated by its attractions in order to support its rehabilitation and maintain its values [16,17].

Defining cultural tourism is still the cause of major debate in the literature because the notions of culture, heritage and tourism themselves are so diverse and open to differing interpretations [1]. Very recently, a new operational definition for the segment was set by the UNTWO at the 22nd Session of the General Assembly held in Chengdu, China. Cultural tourism is a type of tourism activity in which the visitor’s essential motivation is to discover, learn about, experience and consume the tangible and intangible cultural attractions/products at a tourist destination. These attractions/products relate to a set of distinctive material, intellectual, spiritual and emotional features of a society that encompass arts and architecture, historical and cultural heritage, culinary heritage, literature, music, creative industries and the living cultures with their lifestyles, value systems, beliefs, and traditions [18]. Thus, cultural tourism destinations can be defined as places that facilitate experiential offerings [19,20].

From the set of attributes that intervene in the conformation of a cultural experience, it has been proven that safety is very important [21], as well as authenticity, transportation and hygiene [8]. Other diminishing aspects such as traffic, noise, crowding, chaos and lack of health standards have also been found to be components of a cultural experience, and hence their relationship with the behavioral responses of cultural tourists is an under-researched field [8]. This study aims to fill this gap by offering insights into the negative feelings of cultural tourists about these features and their relationship with satisfaction and future intentions.

2.2. Satisfaction/Dissatisfaction

For almost four decades, researchers have shown an increasing level of interest in developing empirical and conceptual studies on tourist satisfaction [22]. This has led to important contributions to the tourism sector [23]. The importance of studying satisfaction is attributed to its influence on tourists’ decision-making processes [23], spending, repetition, and future intentions [24,25]. In this context, destination attributes have the greatest potential to explain the variance of tourist satisfaction with destinations [22].

In addition, research is consistent in explaining that the absence of satisfaction (i.e., tourists valuing cultural activities with the lowest rate on a satisfaction scale) does not necessarily mean dissatisfaction [9]. The reverse can also occur, where situations can only generate dissatisfaction, but their absence does not necessarily lead to satisfaction [10].

For several tourism segments, it has been demonstrated that there exists a direct relationship between dissatisfaction, satisfaction and the future intentions of tourists. This is the case in the study of Alegre and Garau [10], who demonstrated that displeasure stemming from overcrowding and environmental problems can partially explain tourists’ overall satisfaction and negative intentions to return to sun, sea and sand destinations. Too much traffic, poor accessibility and congestion are also considered negative attributes and are usually regarded as undesirable by tourists in general, thus affecting their future intentions [22,23].

Tourist dissatisfaction is often measured by using a symmetrical, one-dimensional scale. The scale is utilized to rate aspects of the destination, services and products that are showing a negative performance. These negative statements are often selected from a group of factors that are key components of the tourist experience [25].

Some authors affirm that the analysis of dissatisfaction gives more accurate results regarding destinations’ inability to meet tourists’ expectations [10,22,26]. There are, however, relatively few studies that analyze the negative experiences of tourists at cultural destinations alongside the impact that this may have on decision making. Therefore, examining which attributes of the destination can dissatisfy cultural tourists has critical implications for business practice and tourism policy.

2.3. Loyalty

Loyalty has received special attention in the tourism marketing literature, since loyal tourists represent not only a stable source of income for destinations, but also act as a channel of information that informally connects networks of friends and other potential travelers [27,28]. Repeat tourists are also less sensitive to prices, and the cost of catering for this type of tourist is lower [29,30].

Tourism loyalty is a construct that has been tackled in a very homogeneous way, generally adopting three main conceptual approaches: behavioral, attitudinal, and an approach that integrates both attitude and behavior [27,31]. From the behavioral perspective, loyalty is usually measured as the number of times a destination is visited [31].

Intentions are also important, as the willingness to engage in a particular behavior constitutes the best direct predictor of that behavior [30,31]. The latter is recognized as the attitudinal dimension of loyalty, which is the dimension studied in this research. This is due to the fact that Havana is considered as an emerging cultural heritage destination, welcoming new tourism flows in recent years.

Regarding the attitudinal dimension, the leisure science literature confirms that tourism loyalty is positively influenced by satisfaction and past behavior, with loyal tourists being those who are more satisfied, and have greater disposition to revisit/recommend the destination in the future [29].

In the context of cultural tourism, loyalty has been analyzed by mostly focusing on events and festival market niches [11]. Research has demonstrated that authenticity, service quality and perceived value are determinants of tourists’ repeat purchases of cultural events [32].

Finally, although satisfaction is a major antecedent of tourist loyalty for the majority of segments [29,33,34], it has been demonstrated that for cultural tourists, loyalty does not depend on satisfaction [8]. In addition, the relationship between dissatisfaction and loyalty has not been verified within the cultural segment, which is an aim of the present paper.

2.4. Hypotheses and Model

Dissatisfaction in this research is defined as the evaluation that cultural tourists give of different negative attributes of the destination. In order to assess the relationship between dissatisfaction, overall satisfaction and the future intentions of cultural tourists, four key areas of dissatisfaction were previously identified: D- HYG: dissatisfaction with the management of hygiene, cleanliness and crowding; D-INFRA: dissatisfaction with the conditions of the infrastructure; D-TOUR: dissatisfaction with the service quality and the tourism superstructure; and D-CULT: dissatisfaction with the management of cultural heritage and activities. Dissatisfaction constructs were adapted from general attributes of the destination that have been ratified as key components of the cultural tourism experience [1,35].

Table 1. Negative attributes analyzed and references supporting their relevance as components of the cultural tourism experience.

Attributes	References
D-HYG: Dissatisfaction with the management of hygiene, cleanliness and crowding	Crowding, lack of hygiene and health insecurity [1,7,8], as well as traffic, noise and transportation chaos [8] are recognized as key components of the cultural tourism experience. However, these aspects have not been yet studied in relation to the overall satisfaction and loyalty of cultural tourists, which is the main aim of this study.
Natural environment lacking cleanliness
Bad hygiene conditions in urban areas
Crowding
D-INFRA: Dissatisfaction with the conditions of the infrastructure
Bad signposting of roads
Road in bad conditions
Problems at the airport
Highways in bad conditions
D-TOUR: Dissatisfaction with the service quality and the tourism superstructure	High-quality accommodation, shopping and gastronomy services are antecedents of a satisfactory cultural experience [8,10,15,26]. In addition, it can be explored as to whether the overall satisfaction of cultural tourists is also determined by their negative opinion of these features.
Lack of quality of food services
Accommodation facilities in bad conditions
Few shopping options
Car rental/taxis unavailable
D-CULT: Dissatisfaction with the management of cultural heritage and activities	The authenticity and quality of the cultural products and activities, as well as the rescue of local traditions are important aspects impacting on the satisfaction and future intentions of cultural tourists [15,32]. However, dissatisfaction-based evaluations of these attributes are rather a neglected area.
Bad promotion of cultural events and programs locally
Cultural attractions lacking maintenance
Cultural activities less developed or lacking a business approach

shows the four attribute dimensions proposed in the model, along with the papers from which these constructs were identified and reformulated. In total, fourteen specific aspects were elicited from the tourists’ opinions of the city, which are the observed variables. These aspects are expected to be grouped into the four dissatisfaction constructs previously mentioned (D-HYG, D-INFRA, D-TOUR and D-CULT).

The model explains the overall satisfaction of the tourist with the cultural experience provided by the destination (SAT) and the willingness to revisit it (REVI). Both variables are expected to be influenced by the negative opinions that tourists have of the cultural destination. Hence, the starting point was the assumption that lower levels of dissatisfaction with respect to the management of hygiene, cleanliness and crowding in the city (D-HYG) lead to higher levels of satisfaction with the cultural experience (SAT), and the first hypothesis was established.

Hypothesis 1 (H1).

A lower level of dissatisfaction with hygiene, cleanliness and crowding at the destination (D-HYG) determines a greater level of satisfaction with the cultural destination (SAT).

Tourists’ dissatisfaction regarding the poor conditions of the infrastructure (D-IFRA), the tourism superstructure (D-TOUR), and the cultural heritage and activities (D-CULT) at the destination are also expected to affect cultural tourists’ overall satisfaction (SAT). Thus, the next three hypotheses of the model were established.

Hypothesis 2 (H2).

A lower level of dissatisfaction with the conditions of the infrastructure of the destination (D-INFRA) leads to a greater level of satisfaction with the cultural destination (SAT).

Hypothesis 3 (H3).

A lower level of dissatisfaction with the destination’s tourism superstructure (D-TOUR) leads to a greater level of satisfaction with the cultural destination (SAT).

Hypothesis 4 (H4).

A lower level of dissatisfaction with the on-site cultural heritage, activities, and their promotion locally at the destination (D-CULT) determines a greater level of satisfaction with the cultural destination (SAT).

Given that tourist dissatisfaction has been found to be an antecedent of loyalty variables for other tourism segments [26], this model verifies whether there is a direct relationship between dissatisfaction and cultural tourists’ willingness to revisit the destination (REVI). Thus, the following four hypotheses of the model were established.

Hypothesis 5 (H5).

Tourists who show higher levels of dissatisfaction with the hygiene, cleanliness and crowding at the destination (D-HYG) will not be willing to revisit the destination (REVI).

Hypothesis 6 (H6).

Tourists who show higher levels of dissatisfaction with the conditions of the infrastructure at the destination (D-INFRA) will not be willing to revisit the destination (REVI).

Hypothesis 7 (H7).

Tourists who show higher levels of dissatisfaction with the destination’s tourism superstructure (D-TOUR) will not be willing to revisit the destination (REVI).

Hypothesis 8 (H8).

Tourists who show higher levels of dissatisfaction with the on-site cultural heritage, activities, and their promotion locally at the destination (D-CULT) will not be willing to revisit the destination (REVI).

As the majority of studies prove that satisfaction is a major antecedent of tourism loyalty [33], it can be proposed that tourists declaring a satisfactory cultural experience at the destination (SAT) will show a greater willingness to revisit it (REVI). Therefore, the ninth hypothesis is proposed:

Hypothesis 9 (H9).

A greater level of satisfaction with the cultural destination (SAT) leads to a greater willingness to revisit it in future (REVI).

Figure 1 depicts the path diagram considering all the elements described above and the hypotheses presented. The variable REVI is drawn as a box, because it represents actual data collected during the fieldwork. The negative factors (D-HYG, D-INFRA, -D-TOUR, and D-CULT) and the overall satisfaction (SAT) are displayed as circles, as they are constructs obtained from data processing.

Mathematically, the model is represented by two structural equations:

ε₅ = ɣ₁ε₁ + ɣ₂ε₂+ ɣ₃ε₃ + ɣ₄ε₄ + ɕ₁,

(1)

y₁ = ɣ₅ε₁ + ɣ₆ε₂ + ɣ₇ε₃ + ɣ₈ε₄ + ɣ₉ε₅ + ɕ₂,

(2)

where y₁ = REVI the endogenous and observed variable of the model. The constructs are ε₁ = D-TOUR; ε₂ = D-INFRA; ε₃ = D-HYG; ε₄ = D-CULT, and ε₅ = SAT. ɣ_1…9 are the regression coefficients to be estimated.

3. Methodology

3.1. Study Site

The location chosen for the research study was Havana city, an urban cultural destination located in the Havana province and the capital of Cuba. In Cuba, international tourism has been strengthened since the beginning of the nineties, as a response to the economic problems that the country was facing [6]. To date, the Cuban tourism strategy has been based on the sun, sea and sand model, based on its status as a Caribbean island and the natural potentialities it possesses. The cultural heritage of the country has been set aside, although its importance is publicly recognized [6,36]. The cities, especially the capital of Cuba, Havana, are thought of merely as transit hubs.

The last thirty years of tourism in Cuba have been characterized by a timid rate of growth in the main indicators of income and arrivals [37]. There is public recognition of the need to work towards a more competitive industry [6,38]. This, together with the obsolescence of the sun, sea and sand tourist model, the increase in international competition, and the change in the preferences of the demand at a global level [39], define the need to implement new strategies for tourism diversification.

In this scenario, Havana, possessing a great variety of culturally valuable assets, both tangible and intangible, historical and contemporary, including its status as a World Heritage site (“The Old Havana”), stands out as an ideal vehicle to foster the development of cultural tourism in Cuba [40,41]. Further knowledge of the sector and the market is essential in this process.

Recently, Havana City has positioned itself as a leading destination in Cuba. According to official statistics [37,40], in the last eight years (before the COVID-19 pandemic), the city has received more than 60% of all the international tourists in the country, with 2.5 million tourists per year on average [36]. Havana is also positioned at the top of the three most visited destinations in the Caribbean region (Santo Domingo and Puerto Rico received 2.1 and 1.6 million tourists annually in the same period, respectively) [40]. In addition, its strategic location in the Atlantic, and because of its enclave at a junction between the European and American continents, constitutes a remarkable strength for the archipelago.

3.2. Data Collection

The target population of the study was defined as tourists visiting Havana’s old city, motivated by the enjoyment of cultural attractions, museums and the cultural heritage. This also includes cultural activities—music, dance, theatre, etc. The questionnaire was the main research instrument utilized. Prior to the surveying phase, the questionnaire was translated into four languages. A three steps back-translation method was utilized as a form of quality control. In addition, a focus group was conducted with ten cultural tourists of different nationalities visiting the city.

The purpose of the focus group was to ensure that the questions were going to be clearly understood by the respondents. Once the questionnaire was pre-tested and the pertinent corrections were made to the items that raised comprehension difficulties, the surveying phase took place.

The questionnaire was structured into three groups of questions. The first group consisted of socio-demographic aspects related to gender, age, nationality, occupation and annual income of the respondents. It also focused on the characteristics of the cultural trip, asking respondents for the number of nights spent in the tourist site. Multi-choice questions allowed interviewees to select different cultural motivations.

The second group of questions focused on the evaluation of the fourteen negative attributes presented in Table 1. In order to rate these aspects of the cultural city, a 7-point Likert scale (1 = I totally disagree; 7 = I totally agree) was utilized. In the third and final section, tourists rated their overall satisfaction with the cultural trip, by using a 7-point Likert scale (1 = I totally disagree; 7 = I totally agree) and four expectation–satisfaction statements. In this same section, the tourist’s intention to revisit the cultural destination (REVI) was measured by using a dichotomous reply.

Table 2. Structure of the survey instrument and the variables.

Section	Variables	Description
1a. Socio-demographic aspects	Gender	Dummy. It takes value 1 if the respondent is a male, zero otherwise
	Age	Five age-related intervals, ranging from 1 (18–24) to 5 (>60).
	Nationality	Categorical, nationality.
	Occupation	Five occupation categories, where 1 (business owners), 2 (student), 3 (retired), 4 (professional), and 5 (other).
	Annual income	Seven income-related intervals ranging from 1 (<$10,000) to 7 (>$60,000).
1b. Trip characteristics	Length of stay	Four intervals of the number of nights spent in the destination, from 1 (less than 1 night) to 4 (more than 7 nights).
	Motivation	Five categories of cultural purposes for the trip: 1 (visit historic center/heritage), 2 (Population/traditions), 3 (Music/dance), 4 (History), 5 (Architecture).
2. Opinion about the cultural destination	Dissatisfaction items	Ordinal, 1–7 level of agreement; 1 = I totally disagree; 7 = I totally agree 14 negative statements as shown in Table 1.
3. Satisfaction with the cultural trip and revisit intentions	Overall satisfaction (SAT)	Ordinal, 1–7 level of agreement, ranging from 1 = I totally disagree to 7 = I totally agree, and four expectation–satisfaction statements: (i) I am happy with my decision to visit the cultural destination (ii) I am satisfied with the experience I had during my cultural visit (iii) The cultural destination has met my expectations (iv) I am really satisfied with my visit to the cultural destination.
	Willingness to revisit (REVI)	Dummy. It takes value 1 if the respondent is willing to revisit the cultural site, and zero otherwise.

presents the structure of the survey and the measurement of the variables extracted from it.

The surveys were implemented during five continuous months between May and October 2017. The departures room (sterile area) of the “Jose Marti” International Airport of Havana was the place chosen to conduct the fieldwork. This is the largest and most important airport in Cuba and receives most of the tourists arriving to the country. This way, there was a likelihood of collecting the desired questionnaires in a shorter time. It also allowed us to conduct the survey at the end of the tourists’ trip, which increased the chance of obtaining the total evaluation of the cultural trip. A special license was obtained to undertake the research activity in this location.

The sample was randomly formed by international tourists after screening for the visits to cultural attractions and heritage in Havana’s old city. That is, if the visit to historical/cultural sites, museums, etc., in Havana’s historic center was not among the main purposes and activities conducted in Cuba, and the tourists did not spend at least one night in Havana, the interview was terminated.

A final sample of 1500 international tourists pursuing different cultural activities in Old Havana was obtained. A specialized company in market research was hired. Nevertheless, some meetings and training sessions with the interviewers were necessary prior to the fieldwork to ensure that the communication of the questions to the respondent was clear and accurate.

All tourists were briefly introduced about the structure of the survey, the purpose of the study and the way in which they had to rate their perceptions regarding the destination attributes. The percentage of tourists approached that did not agree to participate was 12%. All completed questionnaires were revised in situ. As a result, no invalid questionnaires were obtained.

3.3. Data Analysis

After coding the answers to the questionnaires, a t-test was employed to assess the differences between respondents in early May and late October. The former represented more than 70% of the total sample. The results show non-significant differences at the 0.05 level. Frequency analysis was utilized to characterize the general profile of the respondents.

An exploratory factor analysis (EFA) was previously implemented in order to verify whether the proposed structure of the dissatisfaction constructs (Table 1) fitted the data.

A CB-SEM was employed to make inferences about the research hypotheses formulated previously. This is an appropriate technique for identifying linear regression relationships between several constructs and variables at the same time, to be expressed through hierarchical or non-hierarchical structural equations [42]. CB-SEM focuses on the minimization of the discrepancy (differences) between the observed covariance matrix and the estimated covariance matrix [42].

The model was validated in AMOS, a statistical program marketed by SPSS (version 26.0, IBM Corp., released 2019. IBM SPSS Statistics for Windows, Armonk, NY, USA, under the terms of the license agreement accompanying the Program). Following [43,44], a three-step process was adopted. Figure 1 illustrates the working of the model. First, the CFA allows the measurement model fit to be determined. The analysis ratified the structure of the proposed dissatisfaction constructs D-HYG, D-INFRA, D-TOUR, D-CULT, considered as latent and exogenous variables in the model. Then, the variable SAT (overall satisfaction-dependent) was included in one full measurement model. Third, the complete structural model was examined after including the REVI (future intentions) variable as the second dependent variable. REVI was drawn as boxes, because this represents actual data collected during the fieldwork.

Therefore, the model proposes that SAT and REVI variables are predicted by D-HYG, D-INFRA, D-TOUR, D-CULT, while the SAT variable also predicts the REVI variable, in that no other variables intervene in this particular model. Once the theoretical framework of the model was drawn, the data were incorporated, to determine whether it fitted the theoretical model and test the proposed hypotheses.

The analysis was also carried out utilizing Smart PLS-SEM as a form of quality control (version 3.2.9, SmartPLS GmbH, 2015, Boenningstedt, Germany, under the terms of the license agreement accompanying the Program) [45,46]. Similar results leading to the same conclusions were obtained. Therefore, it can be stated that the value of this study to managers depends less on the model than whether or not the solution is meaningful and useful for action [46].

The R² parameter was utilized to evaluate the explanatory power of the variance of the two dependent variables (SAT and REVI). Additionally, considered were the values of the root mean square error of approximation (RMSEA) index, which indicates the degree of adjustment of the theoretical model with the population covariance, the degrees of freedom (df), and the CFI [46].

4. Results

This section is structured into three subsections. The first corresponds to the characterization of the general profile of the respondents and their cultural trip to Havana, the second shows the results of the factorial analysis and the formal definition of the constructs of the model, and the third presents the results of the structural model and hypotheses testing.

4.1. Sample Socioeconomic and Travel Characteristics

The sample consists mainly of professional females. More than 50% of tourists indicated annual incomes of between 40,000 and 60,000 US dollars at the time of being interviewed. The most frequent nationalities within the sample are Canadian, American, English, and Italian (

Table 3. Sociodemographic profile of cultural tourists visiting Havana.

Variables	Categories	Percentage
Gender	Male	45.7
	Female	54.3
Age	>60	19.1
	45–59	14.8
	35–44	14.9
	25–34	39.4
	18-24	12.1
Occupation	Business owner	12.8
	Student	21.3
	Retired	18.1
	Professional	30.9
	Other	16.9
Nationality	Canadian	28.0
	US	10.0
	English	10.0
	Italian	9.0
	Other	43.0
Annual Income	>USD60,000	9.9
	USD50,001–60,000	26.4
	USD40,001–50,000	24.9
	USD30,001–40,000	9.0
	USD20,001–30,000	13.8
	USD10,001–20,000	12.8
	<USD10,000	3.2

).

Official statistics of the cultural tourism segment do not exist in Cuba. Considering the total population of 2.1 million of tourists visiting Havana every year on average, and the characteristics of the sample, consistent with the structure of the international tourism market in Cuba [41], we can assume that this is a representative sample of the population of tourists visiting the cultural destination under study.

A great number of travelers (68%) spent at least four nights in Havana, while the average length of stay in the country is 2 nights, according to official statistics [37]. Visiting heritage sites and seeking knowledge of cultural traditions were the main motivations of the cultural tourists interviewed. Almost half of the total sample were not willing to repeat the cultural visit to Havana. Finally, with regard to the level of knowledge of the destination’s cultural promotion, 80% of the tourists in the sample did not remember or had not seen or heard any cultural promotion of Havana in their country of origin (

Table 4. Travel description.

Variables	Categories	Percentage
Length of stay	More than 7 nights	36.8
	4–6 nights	31.6
	2–3 nights	21.1
	Less than 1 night	10.5
Motivation	Historic center/heritage	78.0
	Population/traditions	71.0
	Music/dance	57.0
	History	55.0
	Architecture	53.0
Willingness to revisit (REVI)	yes	50.2
	no	49.8

).

4.2. Measurement Model

CFA validated the final factor structure and the measurement scales, distinguishing four areas of products and services generating dissatisfaction in the cultural tourists (

Table 5. Results of the confirmatory factorial analysis (CFA).

Factors/Variables	Standardized Loadings	Skewness	Kurtosis
D-HYG: Dissatisfaction with the management of hygiene, cleanliness and crowding
Natural environment lacking cleanliness	0.85	0.310	−0.507
Bad hygiene conditions in urban areas	0.71	−0.361	0.489
Crowding	0.77	−0.470	0.592
D-INFRA: Dissatisfaction with the conditions of the infrastructure
Bad signposting of roads	0.77	0.220	−0.507
Road in bad conditions	0.72	0.120	−0.417
Problems at the airport	0.74	−0.471	0.592
Highways in bad conditions	0.68	−0.644	0.285
D-TOUR: Dissatisfaction with the service quality and the tourism superstructure
Lack of quality of food services	0.71	0.190	−0.677
Accommodation facilities in bad conditions	0.70	−0.510	0.471
Few shopping options	0.70	0.110	−0.471
Car rental/Taxis unavailable	0.67	0.200	−0.644
D-CULT: Dissatisfaction with the management of cultural heritage and activities
Bad promotion of cultural events and programs locally	0.72	0.140	−0.471
Cultural attractions lacking maintenance	0.63	0.120	−0.344
Cultural activities less developed or lacking a business approach	0.53	0.110	−0.344
SAT—Overall satisfaction with the cultural experience
I am happy with my decision to visit the cultural destination	0.56	0.240	−0.264
I am satisfied with the experience I had during my cultural visit	0.54	0.100	−0.144
The cultural destination has met my expectations	0.53	0.110	−0.354
I am really satisfied with my visit to the cultural destination	0.50	−0.270	0.192

). The first dimension of the analysis, D-HYG, refers to problems of cleanliness in the natural environment, crowding, and hygiene conditions in the city. In this regard, tourists’ higher levels of dissatisfaction may be considered as a measure of the poor public management of these aspects. Second, D-INFRA is a construct grouping destination weaknesses into four core infrastructure services (roads, signposting, airport and highways). The D-TOUR dimension provides four negative aspects related to the quality of tourism services and facilities. Finally, the D-CULT dimension refers to tourists’ negative opinion of the management of cultural products and activities on offer at the destination.

All the factor coefficients (standardized loadings) were above 0.50, which indicates a high correlation inside the constructs [46]. The overall fit of the measurement model was adequate (RMSEA = 0.079, CMIN/DF = 1.00 and CFI = 0.978), which confirms a correct adjustment of the factors structure to the data [46].

Skewness and kurtosis were utilized to examine the data for univariate normality [45], which is necessary for covariance-based structural models. Values were in the expected range of −1 and +1 [45]. Therefore, the researchers assumed that the data had close to a normal distribution.

To assess the quality of the measurement model, both validity and reliability of the latent variables were examined through the average variance extracted (AVE). AVE can be accepted when the value is greater than 0.50 [45]. The constructs’ internal reliability was evaluated through the composite and Cronbach’s alpha coefficients. Composite reliability values between 0.60 and 0.90 are regarded as satisfactory, and Cronbach’s alpha coefficients greater than 0.70 indicate an adequate consistency [45]. The results of the validity and reliability tests are shown in

Table 6. Constructs’ descriptive statistics and correlation matrix.

Constructs	AVE	Mean	CR	CA	D-HYG	D-INFRA	D-TOUR	D-CULT
D-HYG	0.606	6.24	0.821	0.800	-	-	-	-
D-INFRA	0.530	5.31	0.818	0.761	0.40	-	-	-
D-TOUR	0.583	5.41	0.789	0.759	0.38	0.39	-	-
D-CULT	0.570	5.92	0.762	0.745	0.25	0.23	0.12	-
SAT	0.500	5.01	0.713	0.709	0.09	0.18	0.14	0.24

Notes: CR = composite reliability; CA = Cronbach’s alpha coefficients; AVE = average variance extracted; squared correlations are below diagonal.

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4.3. Hypotheses Testing

By validating the path diagram proposed in Figure 1, the model indicated an adequate adjustment to the data without proposals for modifications. Figure 2 summarizes the general results of the AMOS model, the regression weights that were significant and the general indices, as well as the test results of the hypotheses. The figure also presents the values of R², which denote a high reliability of the measure, explaining 68% of the variance for satisfaction (SAT) and 67% for future intentions (REVI). The measures of RMSEA = 0.078, CMIN/DF = 2.97 and CFI = 0.97 were found to be acceptable to validate the model and its suitability to the data.

The four constructs (D-HYG, D-INFRA, D-TOUR and D-CULT) had a direct and negative influence on the overall satisfaction of tourists (SAT), leading to the acceptance of H1 to H4. This denotes that tourists presenting higher dissatisfaction levels with the management of hygiene, cleanliness and crowding (D-HYG), the state of conservation of the infrastructure (D-INFRA), the quality of the tourism superstructure (D-TOUR), and the cultural heritage and activities on offer (D-CULT) declared lower satisfaction levels with the cultural experience found in the destination (SAT).

It was also found that tourists’ dissatisfaction with the hygiene, cleanliness and crowding (D-HYG) is the only factor with a direct and negative effect on tourists’ intentions to revisit the destination (REVI), leading to the acceptance of H5. The other negative factors (D-INFRA, D-TOUR and D-CULT) were found not to be relevant in explaining the REVI variable, leading to the rejection of H6, H7 and H8. In addition, it was confirmed that overall satisfaction (SAT) does not have a direct impact on tourists’ revisit intentions (REVI), leading to the rejection of H9.

This result affirms that there exists a significant health and environmental awareness among cultural travelers visiting Havana, with their negative opinion of the management of hygiene, conservation and crowding at the destination (D-HYG) being the only factor with a direct impact on both their satisfaction (SAT) and revisit intentions (REVI).

Thus, while overall satisfaction (SAT) is enhanced by improving many aspects of the destination that generate tourist dissatisfaction, the intentions of cultural tourists to revisit only depend on adequate levels of hygiene and crowding. At this point, planning for the cultural development of Havana should attempt to maximize health security, minimize the environmental impact, and correct any possible unnecessary excess in terms of cultural supply (i.e., mass cultural activities). The results open up a new perspective for cultural tourism managers, identifying the specific areas of the destination that enhance cultural tourism loyalty. With this information, operational marketing plans can be more efficient in their use of promotional resources and take advantage of the progress made in regard to public health and the environmental management of the destination.

5. Discussion

This paper supports and contrasts with earlier findings, and also reveals new insights. It supports previous research proving that higher levels of satisfaction among cultural tourists do not lead to a greater willingness to revisit the cultural destination [8]. This is an important result, as tourism managers should be aware that the benefits derived from an enhanced satisfaction are not necessarily linked to tourist repetition. At the same time, this evidence contrasts with other studies analyzing tourism loyalty in the context of cultural events [11]. Akhoondnejad et al. [11] proved that a higher level of satisfaction with service quality leads to a greater willingness to revisit the cultural event. This contradiction confirms the necessity to verify this type of relationships in as many modalities of cultural tourism and destinations as possible.

In our model, it was proven that the revisit intentions of cultural tourists only depend on their dissatisfaction level with the management of hygiene, cleanliness and crowding. Thus, it can be assumed that an improvement in hygiene, cleanliness and crowding conditions at the cultural destination has a double impact; it leads to higher levels of satisfaction of cultural tourists, and motivates tourist repetition.

Considering that intentions or willingness to revisit constitute the best direct predictor of that behavior, this finding has important managerial implications. Destination management organizations and decision makers aiming to promote the loyalty of the cultural tourism segment may revise and improve the environmental management and conservation plans, the spatial distribution and timetable of the cultural tours, cultural activities, and health security. More importantly, they should take advantage of the progress made in these areas, to design their communication campaigns. This may be enhanced by an increased application of technological advances; websites, social media and networks may be utilized [29]. This may be applied together with other interventions, such as the improvement of service quality [32], which also have the potential to promote cultural tourism loyalty, according to previous findings.

In summary, this study provides insights into crucial aspects that may be included in a wider tourism management agenda of cultural destinations. Hence, the question not only arises as to the need to design a supply of products and experiences to be coherent with cultural attractions and potentialities, but also to provide benefits for the environment and health, and ensure a mostly undisturbed cultural experience. These efforts can also be a differentiating resource and competitive advantage for the post-pandemic re-setting of cultural destinations.

Although there exists a wide range of dissatisfaction, and tourism loyalty studies for other tourism contexts [26,29], this is the first time that the negative experiences of cultural tourists have been analyzed in relation to some aspects of decision-making. Only the paper of [47] analyzed the impact of waste management as a constraining factor on tourism development for a cultural heritage destination.

Finally, according to this study, other aspects related to the poor conditions of the infrastructure, the tourism superstructure, and the cultural offer and its promotion do not influence tourists’ intentions to revisit the cultural destination. From a tourism policy perspective, these aspects do not need to become a priority in the avenue of promoting repeat visits to cultural destinations. However, destination managers should be aware of their importance, as they affect the perceived reputation and image [48] and the conformation of a satisfactory cultural tourism experience, and consequently the economic impact of the segment [25].

6. Conclusions

The main contributions of this work are that: (i) it provides a better and wider understanding of the behavior of cultural tourists; (ii) it proposes and empirically validates, for the first time, dissatisfaction constructs that have the potential to modify cultural tourists’ overall satisfaction and intentions to revisit destinations, and; (iii) it has proven the dominant role of dissatisfaction with the management of hygiene, cleanliness and crowding in explaining tourists’ satisfaction and intentions to revisit cultural destinations.

From the theoretical perspective, this study represents a substantial advance in the conceptualization and modelling of decision-making processes for the cultural segment, by validating four dissatisfaction dimensions that have the power to predict overall satisfaction and loyalty (attitudinal dimension) of tourists. By incorporating these under-investigated variables in a multidimensional model explanatory of cultural tourists’ satisfaction and future intentions, a higher reliability of the measure to explain the variance in the dependent variables may be obtained, which is a matter of future research works.

From a managerial perspective, the proposed theoretical framework can be easily verified in other cultural and heritage destinations, and the sub-segments can refine the recommendations to plan the future management actions. The question arises as to the need to offer a healthy and peaceful cultural heritage experience in the best possible conditions and with the highest consideration paid towards the environment. This requires close collaboration between authorities, the tourism industry and other public and private bodies, posing a challenge for the governance of a cultural city, which transcends cultural tourism management and requires more integrated frameworks of policy and action [29].

Havana, as a cultural tourism city, will be more successful insofar as it: (i) takes advantage of the most authentic resources of Cuban culture that make the destination unique, thus promoting creative cultural industries; (ii) provides peaceful cultural experiences with a minimal impact on the environment and in the healthiest possible conditions; (iii) avoids crowding and degradation of the urban infrastructure; and (iv) takes advantage of the use of information and communication technologies (ICTs) to the benefit of the cultural promotion, and communicates the progress in the above-mentioned aspects, before, during and after the visit.

The same applies to other cultural cities seeking to take advantage of the COVID-19 pandemic as a re-set button. This is the moment for cultural destinations to decide how they want to re-adapt their tourism systems, with greater health and environmental security. A matter of mutual interest is now to collectively learn from this global tragedy (COVID-19) in order to accelerate the transformation towards a more sustainable tourism industry. This is so important for Havana, which has fundamental problems in regard to the hygiene and cleanliness of urban areas. At the same time, existing initiatives for mass-cultural activities at this destination (i.e., Rutas and Andares) may be revised. In the case of Cuba, the government’s priorities, which are currently focused on saving lives and creating the conditions to restart the domestic economy and the education system, may be a limiting factor for efficient tourism recovery and resilience, while the juggernaut of international tourism will roll on.

This study has various limitations that substantially reduce the potential generalization of its results and the scope of its conclusions. First, it is based on a single destination of cultural tourism, and therefore there is a need to consider evidence on other alternative destinations in the Caribbean region. Moreover, the investigation requires a more profound and detailed examination of the relationship between tourists’ dissatisfaction with destination image, past destination choice, and the spending decisions of cultural tourists. Thus, future studies should investigate these effects, together with a more segmented analysis of the demand at different types of cultural destinations. Moreover, it is necessary to consider the analysis of safety and security, as they are also important aspects that influence decision making of the vast majority of tourism segments.