Introduction (Введение). Tourism is a constantly evolving industry, as tourist profiles are volatile and tend to change sporadically according to people's lifestyles (Crotts, 1994; Dwyer et al., 2000; Gavurova et al., 2020), which determine the consumption of products.

The profile of tourists and their satisfaction with the consumed tourist services play a crucial role in the tourism economy (Brazales et al., 2018, 2021; Nowak et al., 2007; Rahayu, 2017; Shvets et al., 2015; Sugiyarto et al., 2003; Suhel & Bashir, 2018). The tourist profile, which includes demographic characteristics, preferences, and behaviors, influences the demand for tourism services (Balaguer & Cantavella, 2002; Brida & Risso, 2010; Dritsakis, 2004; Gupta & Dutta, 2018) and how economic resources are spent at the destination (Cheng et al., 2023; Rahayu, 2017; Tiwari et al., 2021; Tsakiri et al., 2021).

Tourist satisfaction with tourism services is a determining factor for the economic success of the sector (Borges et al., 2016; Cerón & Lechuga, 2018; Dmitrović et al., 2009; Liu & Dewancker, 2017; Tiwari et al., 2021). Satisfied tourists tend to spend more money (Brazales, 2018; Brazales et al., 2022; Oya et al., 2021), return to the destination on future occasions, and recommend it to other travelers (Urry, 2001). This boosts revenue flow and has a positive impact on the local economy (Brazales et al., 2021; Hirschman & Lindblom, 1962; Ngoc et al., 2022), stimulating spending on hotels, restaurants, transportation, and tourist activities (Mussina et al., 2019; Pearce, 1988; Spangenberg, 2005; Stauvermann & Kumar, 2016).

The economic growth of tourism in Ecuador not only positively impacts the country's balance of payments but is also fundamental to improving tourist satisfaction by fostering investments in infrastructure and services that meet their needs and expectations. As tourism expands, more jobs are created and local income increases, allowing communities to offer richer and more personalized experiences to visitors  (Brazales et al., 2025). This dynamism creates a virtuous cycle where tourist satisfaction improves, driving greater demand and attracting more travelers who, in turn, contribute to the sector's economic growth. This reinforces the importance of tourism as an engine of sustainable development in Ecuador and highlights the need for strategies that align economic growth with the interests of tourists and local communities (Brazales et al., 2025).

Several investigations have examined the profile (Alén et al., 2016; Buffa, 2015; De La Torre & Pérez, 2017; Franco et al., 2017; Magano et al., 2022; Merinov et al., 2023; Moral et al., 2021; Oltean & Gabor, 2022; Viñán et al., 2022) and the preferences of tourists (Alves et al., 2023; Astariningsih et al., 2020; Deng & Liu, 2021; Gao et al., 2024; Mahdi & Esztergár, 2023; Rachmawati, 2024; Teviana et al., 2021). These investigations have analyzed socio-demographic aspects, motivations and used various variables to evaluate perceived satisfaction (Gartner, 1994; Gunn, 1994).

Therefore, it is essential to understand the visitor profile and assess their level of satisfaction with the tourism services they have experienced (Brazales et al., 2022; Smolčić & Soldić, 2017; Vegara et al., 2018), as this has a direct impact on the economy of the sector (Fayissa et al., 2008; Hernández et al., 2017; Palafox, 2013). Tourist destinations must adapt their offer and improve the quality of their services in order to meet tourists’ expectations and preferences (Hernández, 2014; Nowak, 2007; Palafox & Garcia, 2018). These actions, in turn, will generate economic benefits, promote sustainability, and foster the long-term development of the tourism industry (Alhowaish, 2016; Babolian, 2020; Bianchi & Man, 2021).

In addition, a predictive development model as a strategic planning system is fundamental to addressing the dynamics of tourism, as it allows for the identification of trends in tourist behavior and the establishment of forecasts that facilitate the adaptation of services offered based on their expectations and needs. Formulating a long-term vision for tourism development not only guides the creation of policies that promote visitor satisfaction but also establishes clear priorities for the sector, integrating a management approach that considers the socioeconomic and cultural context of each destination. This ensures that strategies for improving service quality align with the characteristics of the tourist profile and, therefore, increase their satisfaction and foster loyalty, thus guaranteeing sustainable development in the tourism sector (Brazales et al., 2023).

Also, the Balanced Scorecard is an essential strategic tool for companies in Ecuador's tourism sector that allows them to align their financial objectives with customer satisfaction by measuring not only profitability but also how tourist experiences affect their economic success. Proper management of the quality of tourism products improves the tourist's perception and encourages investment in services that meet their expectations, thus establishing a positive cycle between business growth and tourist satisfaction (Illapa & Brazales, 2024).

Tourism in the city of Latacunga represents 0.01% of the total tourism in the country based on records of the number of air arrivals to the canton (Ministerio de Turismo Ecuador, 2024), it has a low hotel occupancy averaging 45% occupancy (Brazales et al., 2022), a negative growth rate and a limited tourist offer (GAD Latacunga, 2020) compared to Ambato or Quito, which are markets adjacent to Latacunga.

In the context of tourism in Latacunga, understanding the tourist profile and its relationship to satisfaction with the services consumed is fundamental. Characterizing tourists, including demographics, motivations, and expectations, allows tourism service providers to tailor their offerings to the specific needs of this segment (Brazales et al., 2024). Particularly in emerging destinations like Latacunga, where the tourism offering is still developing, it is crucial to use these insights to optimize the visitor experience, foster loyalty, and ultimately, positively impact the local economy. Tourist satisfaction not only influences their desire to return but also contributes to increased spending in the region, promoting sustainable development and continuous improvement of the tourism services offered (Brazales et al., 2024).

In this framework, one possible reason for the problem of lack of knowledge about the profile and satisfaction of services consumed is due to causes such as products not being in line with the tourist or these products not fully satisfying the tourist due to factors exogenous to their profile, such as the quality of the service, natural and heritage attractions, climate, among other factors.

The objective of the research is to analyze the tourist profile and their perception of satisfaction with tourism services in the Latacunga canton. The hypothesis was if the tourist profile has a significant impact on satisfaction with tourism services in the Latacunga canton.

Literature Review (Обзорлитературы). Tourist Profile. Tourist profile refers to the detailed description of the characteristics, behaviors, preferences and demographic, psychographic and behavioral attributes of an individual or group participating in tourist activities (Ibañez et al., 2016). Tourist demand refers to the number of individuals interested in participating in tourist activities in a given place and time (Brazales et al., 2018).

Tourist profiles are configured based on the different typologies that exist worldwide (Ceylan et al., 2021; Chebli et al., 2024; Mudarra et al., 2019). The tourist profile is closely linked to the satisfaction obtained through the consumption of tourist products, and varies depending on their motivations (Çalişkan, 2018; Carvache et al., 2019; Gisbert et al., 2018).

Even today, the profile of tourists can be identified through the Internet (Buhalis & Law, 2008), through social networks (Guerreiro et al., 2024; Sánchez et al., 2024), through photos they share  (Bakos, 1998; Baloglu & Pekcan, 2006), GPS routes (Delouche & Stehly, 2023; Kou et al., 2024), payment and consumption receipts (Deng & Liu, 2021).

It is worth noting that tourist profile studies have managed to create personalized travel itineraries (Chen et al., 2023; De La Torre & Pérez, 2017; Folgado et al., 2014; Franco et al., 2017; Y. Liu et al., 2024; Magano et al., 2022; Merinov et al., 2023; Teviana et al., 2021), have improved the tourists' experience through the identification of travel patterns (Mahdi & Esztergár, 2023), just as personality is related to the choice of tourist attractions (Urry, 2002), travel motivations and preferences and concerns related to travel (Alves et al., 2023).

The tourist profile is associated with cultural practices (Bourdieu, 2015; Bourdieu & Wacquant, 2013), hat is, the amount of traditions and folklore that they incorporate and how it is reflected in their behavior in the place of origin (Álvarez & Martínez, 2016). Consequently, it is recognized that the tourist can present both positive and negative behaviors in the destination (Krippendorf, 1984; Urry, 2002). Tourist profiles represent the different market segments within the tourist activity (Sandoval et al., 2018).

It is important to highlight that the tourist profile is not equivalent to the promotional profile of the destination (Solís et al., 2016), in other words, the evaluation of the tourist profile is carried out both quantitatively, considering aspects such as the expenditure made both in the place of origin and in the place of destination (Alegre & Pou, 2006), as well as the duration of the stay (Brazales et al., 2020; Ibañez et al., 2016; Lavín et al., 2017; Palafox & Garcia, 2018); and qualitatively (Quintana & Feijoó, 2002).

Knowing the tourist profile plays a crucial role in the consumption of tourism products in a given geographical area (Franco et al., 2017; Gisbert et al., 2018; Mudarra et al., 2019), whether in a specific locality or in several territories within the same area (Deng & Liu, 2021). This approach allows for the existence of multiple tourist offers in a single locality in order to satisfy tourists' demands (Ascanio, 2010; Leiper, 1979; Teviana et al., 2021). This, in turn, significantly increases the likelihood that tourists will choose a particular destination for their trip (Pina & Delfa, 2003).

In summary, the main objective of creating a tourist profile is to increase the probability that tourists select the destination offered (Alén et al., 2016; Baloglu & Pekcan, 2006; Ibañez et al., 2016; Nicolau, 2009; Sánchez et al., 2024). Such a profile is built considering the attributes that best fit the needs of tourists and that are available at the host destination (Inkinen et al., 2024; Valle et al., 2020). The selection of a tourist destination depends of the personal preferences (Krippendorf, 1986; Sirkis et al., 2022).

Satisfaction with tourist services. Tourist satisfaction is a key factor in the traveler's experience, as it reflects the degree of satisfaction and contentment experienced by travelers regarding their trip and the expectations they had about the destination and tourist services (Chebli et al., 2024; Gao et al., 2024; Martínez et al., 2021), but it is still in its early stages due to an insufficient satisfaction assessment system in countries with GDPs that do not depend largely on tourism (Krishnamoorthy & Holladay, 2023; Qu, 2024).

The quality of tourism service plays a fundamental role in customer satisfaction (Fuller & Ricker, 2021), and it is vital to analyze this relationship to provide creative solutions and improve the experience in a tourist destination (Bronner & Neijens, 2006) and thus position itself in the tourist context (Saqib, 2019).

Strategic planning of a territory can be significantly boosted by understanding and satisfying the consumer and being served according to their market segmentation (Ibrahim & Gill, 2005) or niche (Saqib, 2019). The importance of the length of stay is highlighted as a central characteristic in consumer satisfaction in tourist destinations, highlighting the need to understand the dynamics of tourist choice to improve satisfaction in tourist destinations (Alegre & Llorenç, 2007; Bhattacharya et al., 2023). Satisfaction can be measured through evaluation indices in scenic tourist places based on multiple data fusions or multivariate analysis (Xu, 2024).

Tourists seek satisfying experiences (Acerenza, 2003; Acerenza, 2015) as well as professional services (Croes et al., 2021), green spaces (Gkavra et al., 2023; Krippendorf, 1982), he culinary experience directly affects tourist satisfaction and loyalty (Hendriyani et al., 2020) and especially the climate influences tourist satisfaction and spending at the destination (Lam et al., 2019).

It is argued that traditional measures of service quality are insufficient to assess the satisfaction of 'new' tourists (Brunner & Peters, 2009; Sharafuddin et al., 2022), which is why the flow of experiences of all services consumed during the consumption of tourist activities should be measured (Brunner & Peters, 2009).

The interactions between cultural environment and tourist attractions in relation to tourist satisfaction have positive, high and significant correlations, while the correlation between tourist destination facilities and tourist satisfaction shows less robustness, as well as tourist destination service factors and tourist satisfaction is also weak (Gong et al., 2023).

This indicates that the quality of cultural environment and tourist attractions play a more prominent role in the overall satisfaction of tourists visiting outdoor mountain tourism destinations (Gong et al., 2023; Gu, 2023), but on the other hand tourists in commercial destinations value comfort, facilities and service quality with value for money, while tourists in religious destinations prioritize location, cleanliness and breakfast (Singh et al., 2023).

However, studies highlight that the entertainment factor (Abdul et al., 2023; Sheehan & Ritchie, 2005; Tham et al., 2023; Wang, 2015; Yao et al., 2023; Yi et al., 2020) has the most significant impact on the value of the experience (Tseng et al., 2023) and on the satisfaction of the visitor's experience (Cegur, 2021; Lyu et al., 2019; Tseng et al., 2023) which is supported by the quality of the destination (not only the services) (Hussain et al., 2023) with connectivity (Zhao et al., 2023), with novelty (Son et al., 2023) and above all with security (Sapkota et al., 2023). 

Tourist satisfaction also depends on perceived experiences of the service consumed in hotels (hospitality), especially services consumed in luxury hotels (Jahmani et al., 2023; Mehnaz et al., 2023; Şanlıöz & Kozak, 2021) and the unique and positioned gastronomy of the sector (Sangkaew et al., 2023).

 In the field of tourism, cognitive models can be used to understand how tourists perceive and evaluate destinations, services, and tourist experiences (Alegre & Llorenç, 2007; Brunner & Peters, 2009; Ibrahim & Gill, 2005). These models help to analyze the mental processes and subjective perceptions that influence tourists' decisions (Borges et al., 2016), highlighting the importance of quality and emotional experiences in tourist satisfaction highlighting the importance of quality and emotional experiences in tourist satisfaction (Dmitrović et al., 2009).

However, satisfaction with the services consumed is related to an exponential growth in the tourist offer (Brinca et al., 2021; Zhang et al., 2009), based on a marked growth in human capital and technological (Lucas, 1988; Rebelo, 1991). For this reason, the perceived usefulness of the application of augmented reality and virtual reality positively influences the satisfaction of tourists, encouraging them to adopt these technologies for hotel reservations (Lim et al., 2024).

Therefore, the city and scenic spots should improve the level of smart tourism service (Ku & Chen, 2024), strengthen the construction of hardware and software facilities, and focus on protecting the rights and interests of tourists (Shao et al., 2023).

MaterialsandMethods (Материалы и методы исследования). Quantitative, correlational, field, cross-sectional study using deductive and bibliographic logic as support for the quantitative, non-experimental.

Below is the research design with its variables and constructs according to Figure 1.

Fig .1.  Research design

Рис. 1. Дизайн исследования

Note: The research design was adapted from the Book “Indicadores para un Observatorio Turístico” (Brazales, 2018).

The research design is structured by two variables, tourist profile and satisfaction with tourist services. Each of the variables is composed of constructs.

Population and sample. The population is made up of tourists who arrive at the Latacunga canton and have consumed tourist services, N= 233,181 (Valle et al., 2020) (the population of tourists who entered the Cotopaxi National Park in 2023 was taken as a reference), with a simple random probability sampling, n=69; with 90% confidence and 10% margin of error, given that the country is currently experiencing a security crisis, which compromises the physical and mental state of both the interviewer and the respondent.

Information gathering. The instruments used were surveys using structured questionnaires, using questions on variables with decimal, numerical, ordinal, continuous and discrete scales for tourists, both for the two instruments of each variable respectively.

Validity. By theoretical correspondence between items and by concept of validity through the questions of the book Indicators for a Tourism Observatory focused on the provinces of Zone 3 of Ecuador (Brazales, 2018).

Reliability. The pilot test and Cronbach's alpha were used.

Statistical tool. First, principal component analysis (PCA) was used to obtain non-rotated component indices of the variables.

Secondly, the non-rotated indices of each variable were used to test the hypothesis using the Pearson correlation coefficient and based on its significance (p<0.05).

Thirdly, linear regression was performed between the indices of each variable.

Data processing. Using the Stata statistical package.

Econometric model: satisfaction with tourist services based on the tourist profile. To model the satisfaction of tourist services based on the tourist profile, we started from formula 1 to build formulation 2, where β0 is the ordinate at the origin (satisfaction of tourist services when the tourist profile is equal to zero, and is significant at 0.05). Meanwhile, β1 is the slope coefficient that indicates any change in the variables and ε is the error term, which captures the variability not explained by the linear relationship between the variables:

y= β0  + β1×X+ε        (1)

Satisfaction with tourist services =  β0  + β1× Tourist Profile + ε          (2)

Structuring the instrument. A literature review was conducted, constructs were also sought in the literature and the questions were taken from the validated instruments of the book of (Brazales, 2018).

For the independent variable “Tourist Profile” 23 questions were obtained, which are divided into constructs as follows:

5 questions from the socio-demographic construct; 1 question from the income construct; 5 questions from the travel organization and travel reservation method construct; 1 question from the positioning construct; 3 questions from the motivation construct; 3 questions from the tourist offer preference construct; 1 question from the tourist creation activities construct; 4 questions from the expenditure distribution construct.

For the dependent variable “Satisfaction with tourist services” 23 questions were obtained, divided as follows: 2 questions from the tourist destination construct; 4 questions from the tourist satisfaction level construct by segment; 3 questions from the accommodation quality construct; 3 questions from the food and beverage quality construct; 3 questions from the tourist resource quality construct; 4 questions from the recommendation construct; 4 questions from the product/service evaluation construct.

Pilot and instrument correction. The pilot was conducted between the first and second week of January 2024 with 46 tourists, which resulted in a Cronbach's Alpha of 0.79 for the independent variable and a Cronbach's Alpha of 0.96 for the dependent variable. The Alpha values ​​of the variables were within their ranges. However, questions 12 and 14 were eliminated from the independent variable questionnaire since they were similar and redundant questions.

Survey Application. The surveys were subsequently conducted from the third week of January to the first week of February 2024 among tourists who had consumed Latacunga's tourism products.

Cronbach's alpha. The Cronbach's alpha of the standardized variables for the validated instruments had the following values: Tourist Profile variable instrument: 0.70; Tourist Services Satisfaction variable instrument: 0.94.

The values ​​are within the ranges, showing that they are reliable and validated instruments.

Results (Результаты исследования и их обсуждение). Principal component analysis (PCA) of the variables. In order to carry out the multivariate analysis of principal components, the variables were standardized using the mean, variance and standard deviation. In this process, the standardized variables were given a mean of 1, while the variance and standard deviation were set to 0.

Tables 1 and 2 express the main components of each of the study variables.

Table 1

Tourist Profile, PCA

Таблица 1

Туристическийпрофиль, PCA

Note: with PCA the explained variance for the tourist profile index was 0.1947.

Subsequently, the indices for each variable were obtained, as shown in Table 2.

Table 2

Satisfaction with tourist servicesPCA

Таблица 2

Удовлетворенность туристическими услугами, PCA

Note: with PCA the explained variance for the satisfaction with tourist services index was 0.4917.

Table 3

Indices of the variables obtained by PCA

Таблица 3

Показатели переменных, полученные с помощью (PCA)

Note. Own elaboration using PCA with non-rotated components in Stata 16.1.

The indices presented in Table 3 were constructed using an unrotated Principal Component Analysis (PCA) from standardized variables and represent synthetic measures of tourist profiles and satisfaction with tourism services. These indices represent linear combinations of the original standardized variables and allow for the summarization of multivariate information into comparable quantitative measures.

In the case of tourist profiles, positive index values ​​reflect visitors with more intensive characteristics in terms of experience, level of information, demands, and specialization, while negative values ​​represent less specialized profiles or those with lower expectations regarding the tourism offerings. The dispersion observed in the indices suggests high heterogeneity in the profiles of tourists visiting the Latacunga canton. Meanwhile, the indices of satisfaction with tourism services show considerable variability, while negative values ​​reflect less demanding profiles and unfavorable perceptions of the service.

The variability observed in both indices demonstrates the heterogeneity of tourists visiting the Latacunga canton and justifies the use of these indicators as summary variables. The use of indices derived from the PCA helps to minimize multicollinearity problems and provides a solid empirical basis for subsequent econometric analysis, allowing for a more efficient evaluation of the relationship between the tourist profile and their level of satisfaction.

Hypothesis testing. Pearson coefficient is showed in the table 4

Таблица 4

Pearson coefficient between variables

Таблица 4

Коэффициент корреляции Пирсона между переменными

Note. Own elaboration. Correlation between variables obtained by processing the response data in STATA

*p-sig <0.05, means that the results were not random.

The correlation between the tourist profile and satisfaction with tourist services, measured by the Pearson coefficient is -0.3188. This value indicates a moderate negative correlation between the two variables.

A negative correlation means that as one variable increases, the other tends to decrease. In this case, it indicates that as the tourist profile increases (which implies specific characteristics of the tourist, such as age, income, preferences, etc.), satisfaction with tourist services tends to decrease. However, it is important to note that correlation does not imply causality.

• regression. The regression is analyzed in table 5.

Table 5

Linear regression of tourist service satisfaction based on tourist profile

Таблица 5

Линейная регрессия удовлетворенности туристическими услугами на основе профиля туриста

Note. Own elaboration. Formula: Satisfaction with tourist services = 0.00000000708 - 0.5301 x Tourist profile.

* p<0.05

Validation of assumptions: Multicollinearity: (VIF=1.00).

Heteroscedasticity with a Breusch-Pagan P-value > .05, therefore the null hypothesis of homoscedasticity is accepted.

Normality of errors with a P-value > .05 in the Jarque-Bera test.

Independence of errors with a p-value of zero (= .0000) between the errors and the independent variable.

The regression coefficients from the table 5 are then interpreted: Coefficient of the variable Tourist Profile: The coefficient β is -0.5301253. This means that, holding all other variables constant, a one-unit increase in tourist profile is associated with a decrease of approximately 0.53 units in satisfaction with tourist services. This negative coefficient indicates an inverse relationship between tourist profile and satisfaction with tourist services. It is important to note that this coefficient has a significant p-value (0.008), indicating that the coefficient is unlikely to be equal to zero by chance.

The coefficient of the constant is very close to zero (0.00000000708), suggesting that it does not have a substantial impact on satisfaction with tourism services. Furthermore, the p-value associated with this coefficient is high (1.000), indicating that it is not statistically significant. Regarding the model adjustment measures: R-squared: The value of R-squared is 0.1016, which means that approximately 10.16% of the variability in satisfaction with tourism services can be explained by the tourist profile and the other 89.84% of the satisfaction with the consumed services depends on other variables outside this econometric model. In other words, the linear regression model has a moderate fit for predicting satisfaction with tourism services.

Adjusted R-squared (Adj R-squared): The Adjusted R-squared value is 0.0882. This measure adjusts the R-squared taking into account the number of variables in the model and the sample size.

It is important to note that the regression results also include information on the statistical significance of the coefficients. In this case, the t-value associated with the Tourist Profile coefficient is -2.75, with a p-value of 0.008. This indicates that the coefficient is statistically significant and suggests that there is a significant relationship between the tourist profile and satisfaction with tourist services in the Latacunga canton.

Conclusions Заключение). The analysis of the tourist profile allowed for the identification of a set of sociodemographic, motivational, and behavioral characteristics, from which the constructs corresponding to the variables of the research model were developed. Subsequently, these variables were measured and analyzed to evaluate their relationship with satisfaction regarding the tourism services consumed in the Latacunga canton, using correlation and linear regression techniques.

The results show a moderate negative relationship between the tourist profile and satisfaction with tourism services, with a Pearson correlation coefficient of r = -0.3188. This result indicates that as the tourist profile is characterized by higher levels of specialization, experience, or demands, the level of perceived satisfaction tends to decrease.

This relationship is confirmed through the estimated linear regression model, in which the coefficient associated with the tourist profile variable has a negative sign and is statistically significant (β = -0.5301; p < 0.05). In economic terms, the estimated coefficient suggests that a one-unit increase in the tourist profile index is associated, on average, with a reduction of approximately 0.53 units in the level of satisfaction with the tourism services consumed. Consequently, the alternative hypothesis (H₁) is accepted, which states that the tourist profile significantly influences satisfaction with tourism services in the Latacunga canton.

The model's coefficient of determination (R² = 0.10) indicates that the tourist profile explains approximately 10% of the observed variability in satisfaction. While this value can be considered moderate, it is consistent with the empirical literature on tourism satisfaction, where this type of variable exhibits high heterogeneity and depends on multiple unobservable factors. Furthermore, the diagnostic tests confirm compliance with the classic assumptions of the linear regression model, ruling out problems of multicollinearity, heteroscedasticity, autocorrelation, and non-normality of the errors, thus supporting the statistical validity of the results obtained.

Economic Discussion of the Results. From an economic and tourism perspective, the inverse relationship identified between tourist profile and satisfaction is not contradictory, but rather reflects a structural misalignment between the characteristics of tourism demand and the destination's service supply. In particular, tourists with higher levels of income, education, travel experience, or planning tend to have higher expectations regarding the quality, diversity, and professionalism of tourism services. When these expectations are not met by the local offerings, the overall assessment of the tourist experience is negatively affected.

Likewise, the result can be interpreted as evidence of a mismatch between the visitor profile and the destination's current positioning, which seems to cater more to traditional or low-specialization tourism. In this context, the arrival of tourists with more sophisticated profiles generates a greater propensity to compare with other destinations, which reduces the relative perception of quality and, consequently, the level of satisfaction.

From an economic standpoint, these reduced levels of satisfaction can translate into a lower propensity for tourism spending, a decreased likelihood of return visits, and fewer recommendations of the destination, negatively impacting the local economic dynamics and the tourism competitiveness of the Latacunga canton. In this sense, tourist satisfaction is not only an indicator of visitor well-being but also a relevant determinant of the destination's economic performance.

Practical implications. The importance of adapting and diversifying tourism services to meet the needs of the different tourist profiles visiting the destination is evident. Personalizing tourism products, designing differentiated experiences, and tailoring services to specific segments would reduce the gap between expectations and actual experience, contributing to improved satisfaction levels.

Likewise, the results highlight the need to strengthen the quality of tourism services, particularly through ongoing training for human capital, improved service standards, and professional development for service providers. Since tourists with more specialized profiles tend to have higher expectations, service quality becomes a key factor in avoiding negative perceptions and enhancing the destination's competitiveness.

Another relevant practical implication relates to the implementation of systematic feedback mechanisms. The continuous collection and analysis of tourists' opinions, perceptions, and suggestions will allow for the identification of specific weaknesses in the tourism offerings and enable timely adjustments in destination management, fostering continuous improvement of the tourist experience.

Furthermore, considering the tourist profile as a strategic variable can guide the promotion of sustainable tourism initiatives, aligned with the preferences of visitors interested in responsible practices, heritage conservation, and authentic experiences. This not only contributes to greater tourist satisfaction but also to the economic, social, and environmental sustainability of the destination.

Finally, the results suggest that segmenting the tourism market based on visitor profiles is a fundamental tool for designing more efficient marketing campaigns. A promotional strategy aligned with the destination's actual offerings would attract tourist segments whose expectations are compatible with local capabilities, avoiding negative effects on satisfaction and the image of the Latacunga canton.

Theorical implications. From a theoretical perspective, the study's results provide empirical evidence that reinforces the conceptual relationship between tourist profile and satisfaction with tourism services, contributing to the development of the literature in tourism economics. The statistical significance of tourist profile as an explanatory variable for satisfaction confirms the theoretical arguments that maintain that the characteristics, motivations, and behaviors of visitors directly influence their evaluation of the tourism experience.

Furthermore, the identified relationship provides relevant elements for understanding tourism from an experiential approach, in which satisfaction depends not only on the objective provision of services but also on the expectations, perceptions, and comparisons made by tourists based on their profile. In this sense, the study contributes to consolidating the notion that the tourism experience is a subjective and heterogeneous economic phenomenon, conditioned by the characteristics of the consumer.

Additionally, the results expand the traditional analysis of tourist satisfaction by incorporating tourist profiles as a relevant explanatory variable. This opens new lines of research focused on examining how different profiles influence satisfaction in diverse territorial contexts, especially in emerging or less established tourist destinations.

Finally, the study contributes conceptual elements for refining tourism market segmentation, demonstrating that not all tourist profiles react homogeneously to the services offered. From a theoretical-economic perspective, this heterogeneity reinforces the need to analyze tourism demand in a segmented manner, incorporating structural variables of the visitor profile into explanatory models of satisfaction and the tourism performance of destinations.

Limitations and Future Research.   This study has some limitations that should be considered when interpreting the results. First, the estimated linear regression model identifies statistical, not causal, relationships. Therefore, other factors not included in the analysis – such as public management of the destination, security, weather conditions, connectivity, or contextual variables – could influence the level of tourist satisfaction.

Second, the analysis is limited to the Latacunga canton, which restricts the generalizability of the results to other destinations with different structural characteristics and levels of tourism development. Furthermore, although simple random sampling was used, it may not have fully captured the heterogeneity of tourist profiles present in the destination.

Additionally, the quantitative approach employed may have overlooked relevant qualitative dimensions of the tourist experience, such as visitor perceptions, emotions, and expectations, which significantly influence satisfaction.

Future research could expand the model by incorporating new explanatory variables, analyzing specific tourist profiles, employing mixed methods approaches, and developing longitudinal studies to examine the evolution of tourist satisfaction over time. Likewise, comparative studies between destinations would contribute to a deeper understanding of the relationship between tourist profiles and satisfaction with tourism services.

Conflicts of Interest: the authors have no conflict of interests to declare.

Информация о конфликте интересов: авторы не имеют конфликта интересов для декларации.