Tourism is a strong economic sector capable of generating both direct and indirect income for various sectors of the economy, such as commerce, industry, and services, as well as generating revenue for the public sector through tax collection (Elliott, 2020). According to the Continuous National Household Sample Survey, in 2019, the period before the COVID-19 pandemic, the number of jobs in the accommodation and food sectors alone totaled 5.5 million workers (IBGE, 2019).

The factors involved in the significant development of this economic activity are closely related to how public administration executes its budget and promotes public policies. The development of tourism requires specific infrastructure aimed at tourists, as well as complementary infrastructure shared with the resident population of the tourist destination (Thommandru et al., 2023 Waheduzzaman, 2019).

Although part of the city’s infrastructure was planned to serve a different audience, tourists, like residents, also use public services and facilities in the city, albeit temporarily (Denhardt & Denhardt, 2015; Elliott, 2020). Tourists, as direct and indirect users of public services in certain locations, generally have limited participation in the development of the public policies that shape those services. However, involving these tourists in the formulation, implementation, and monitoring of essential public services in cities can introduce a new model of public policy planning. In this coparticipatory model, tourists act as cocreators of many public services (not only those available for tourism exploration) at tourist destinations, significantly contributing to the design of local experiences (Elliott, 2020; Joppe, 2018; Prebensen et al., 2013).

A concept developed in marketing and applied to tourism to encourage visitor engagement and satisfaction, the cocreation of tourist destinations can be defined as encouraging tourists’ participation in the planning and execution of a service or product that will be used by them. This involvement of different agents in the construction process is also used in public administration. The participation of the population or a specific audience in the development of public policies is the foundation of New Public Governance (NPG), an evolution in the way public policies and services are developed, placing the population’s participation at the center of the planning, execution, and control of public services (Carvalho & Alves, 2023; Zainal & Cahyadi, 2023; Pacheco, 2016; Liu & Wu, 2019).

The relevance of the co-participation strategy in the development of public services is based on understanding the impact of these services on residents’ satisfaction and the impact on tourists’ satisfaction when visiting the destination. Specifically, when discussing the importance of tourist participation in the development of public services, it is essential to recognize how the evaluation of these services can reveal important aspects of the users’ experiences. These evaluations help shed light on the motivations, expectations, and needs of tourists, as well as the challenges they face when interacting with public services (Denhardt & Denhardt, 2015; Elliott, 2020; Hall, 2021).

Perceived service quality is a key determinant of tourists’ satisfaction and plays a critical role in shaping their overall experience at a destination. In the context of public services, quality is evaluated based on tourists’ expectations and their actual experiences regarding accessibility, cleanliness, efficiency, and reliability of services such as public transportation, safety, and urban infrastructure. Recent studies highlight that perceived quality not only impacts satisfaction levels but also influences emotional responses and the formation of memorable experiences during a trip (Rita, Tiago & Sousa, 2024; Su et al., 2020).

As a consequence of positive perceptions and high satisfaction, tourists tend to develop behavioral intentions, such as revisiting the destination or recommending it to others. Intention to recommend, in particular, is considered a central behavioral outcome in tourism research, often used as an indicator of destination loyalty and competitiveness (Kanwel et al., 2019; Lee & Xue, 2020). Understanding how public service quality contributes to these behavioral outcomes is therefore essential for public managers and destination marketers seeking to strengthen tourism development and increase tourist satisfaction.

Through this information, public managers and those responsible for tourism can gain a deeper understanding of tourists’ perceptions and experiences regarding public services, identifying areas of excellence and opportunities for improvement. This enables a more user-centered approach in the development and provision of public services, ensuring that they effectively and efficiently meet tourists’ needs and contribute positively to their experience at the destination (McMullin, 2021).

By recognizing and valuing tourists’ contributions to the construction and evaluation of public services, tourist destinations can not only improve the quality of their infrastructure and services but also strengthen their attractiveness and competitiveness in the global tourism market. This integrated approach promotes the sustainable development of tourism, ensuring long-term economic, social, and environmental benefits for all stakeholders involved (Erkin & Elena, 2023; Mediotte, Emmendoerfer, & Oliveira, 2020).

The research was conducted in the city of Recife due to its prominence in the tourism scene of the northeastern region of Brazil. Recife’s Guararapes International Airport recorded the highest flight traffic in the region, serving as a key entry point for tourists. Additionally, the city achieved the highest hotel occupancy average over the last four years in 2023, with a quarterly average occupancy rate of 76.26%. These data indicate growing demand and the strategic importance of Recife as a tourist destination in Brazil, making it an ideal location to investigate the relationship between public service evaluation and tourists’ recommendations of the destination (OTREC, 2023).

Therefore, considering the importance of a deeper understanding and discussion on how public services can enrich tourists’ experiences in a location, this research is guided by the following research question: What is the relationship between tourists’ evaluation of public services and their intention to recommend the tourist destination? Based on this question, the study aims to verify the relationship between tourists’ evaluation of public services and their subsequent decision to recommend the tourist destination. The central hypothesis is that positive evaluations of public services, such as transportation, safety, cleanliness, and infrastructure, can significantly influence visitors’ overall perception of the destination, leading to a greater likelihood of recommending it to others.

Public administration has evolved to accommodate the demands of the population. Through various administrative reforms, the concept of management and the importance of the role of governments and society have evolved into a social and academic debate. Each era brings with it a specific need for government action, involving the way public policies are constructed and services are provided, including actions that impact the tourism sector (Joppe, 2018; Wei et al., 2020).

New Public Management (NPM) began in the 1990s, focusing primarily on the United States, with a different approach to the relationship between governments and society, emphasizing the quality of public services provided. The role of the population shifted from passive to active, with the public becoming the focus of services as users of public services. This shift changed the paradigm of citizens from submissive elements to clients and funders of public services (Denhardt & Denhardt, 2015).

Public services being oriented toward the satisfaction of the population represented a significant advancement from the previous bureaucratic system. However, this approach was focused on the quality of services provided, without involving citizens in the root of the service, i.e., in the planning stage (Waheduzzaman, 2019).

With the knowledge gained from the conception and implementation of the previous model, NPG recognizes the importance of the various agents involved in the provision of public services and emphasizes the active participation of civil organizations and the service users themselves in the formulation of public policies and the provision of public services. This active participation translates into the target audience’s involvement in the design of public services, starting from the planning stage (McMullin, 2021).

This new approach to public service management, therefore, means that citizens and tourists are no longer mere clients or recipients of public services. Instead, citizens and tourists become partners in the governance process. As such, they should actively participate in the planning, development, execution, and especially the control of public functions. This public service management perspective lays the foundation for the co-creation of tourist destinations (Carvalho & Alves, 2023; McMullin, 2021; Sugathan & Ranjan, 2019).

An important factor in studying the resources and elements that make up tourism is the complexity of analyzing the components of a tourist destination. In addition to the natural and cultural resources involved in a tourist’s experience, other elements act indirectly, such as the condition of public roads, security, the level of qualification of those involved in the economic activity-in other words, a set of public services that the public administration provides to its citizens and that is also shared by tourists (Pereira et al., 2014).

Other public services may also act indirectly. Although tourism has a distinct structure, in many situations it shares infrastructure with the local resident population. Therefore, proper infrastructure management benefits both society and visitors (Erkin & Elena, 2023).

Public services differ from services provided by private companies in terms of the way and scope in which they are provided. While companies offer exclusive services through a paid exchange, public services target the general public, which does not necessarily require direct payment. The private sector also provides exclusive tourism services, such as those in the hospitality and reception industries, through visitor payment. However, public services aimed at tourism fall under the same scope as the general public services provided in tourist locations by public entities, which are used by both residents and visitors (Wei et al., 2020).

The focus is what differentiates tourism-oriented public services from essential public services. Tourism-oriented public services focus more on tourists’ needs, supporting the infrastructure network that sustains and develops the tourism economy. These services may not be directly paid for through immediate consumption but are financed through tax collection. This form of indirect financing affects both residents and visitors, as the costs originate from the public budget and depend on fiscal planning for investment and service maintenance (Zainal & Cahyadi, 2023).

For public revenue, income from urban tourism is significant, even for large cities. According to a report by the Observatório do Turismo de São Paulo (2021), revenue from ISS (Service Tax) from Group 13, which includes taxes and levies paid by companies in the tourism, hospitality, events, and related sectors, averaged R$ 33.235.440,48 ($5,884,805.68 USD) per month during the first three months of 2020 (pre-pandemic).

According to Milano et al. (2019), urban tourism in cities creates relationship asymmetries and points that must be addressed by researchers and managers. Urban tourism is crucial for cities, but major urban destinations often lack the appropriate infrastructure to absorb urban tourists, who share the dysfunctions of public services provided to the population. This increased demand from new users places greater stress on public services, reflecting negatively on the perceptions residents of urban centers may have of tourists, as those services were not originally designed to accommodate tourists, but that has become a consequence (Erkin & Elena, 2023).

Due to the specific needs of tourists and their importance in the economic context of cities, public managers must adopt strategies of constant innovation and quality in the provision of public services to continuously attract tourists. When observing the division of urban space and public services between the resident population and tourists, public managers tend to consider only residents in the planning of public policies, although tourists also participate in the daily dynamics of cities (Aguinis et al., 2023).

Participation at various levels in the construction of public services requires a level of intermediation and integration between the stakeholders involved. The cocreation of public services demands the development of network governance and participatory public management. This process presents a challenge in scenarios where planning is deficient. According to Mediotte et al. (2020), this form of strategic planning in tourism in Brazil still needs improvement, as there is little participation from tourists in the decision-making process of public policies. Without this cooperation among stakeholders, NPG is unable to develop actions that add value and competitiveness to Brazilian destinations.

The perspective of public management regarding the population and tourists in NPM is of a state oriented towards the market, with public administration providing public services and other stakeholders acting as clients in this relationship. With the advent of NPG, both the population and tourists are cooperative and engaging participants through the construction, monitoring, and participation in the results of essential public and tourism services (Mediotte et al., 2020).

The creation of public services aims to add value to the services provided and increase the satisfaction of those impacted. However, in the active participation process among various stakeholders, the cocreation experience will depend on groups and individuals with their interests. The uniqueness of each person affects the cocreation process and is thus directly linked to the customization of services. In many instances, those interests may conflict. Consequently, the role of public administration should be one of mediation, seeking to meet demands while always focusing on the constitutional principle of the supremacy of the public interest when opposing views arise (Soares & Azevedo, 2020; Zainal & Cahyadi, 2023).

Managing potential conflicts of interest is not the only obstacle to the smooth functioning of the cocreation process. The development of public policies involves a framework of specific knowledge that may not be understood by stakeholders involved in cocreative methodologies for public services, which can result in delays or ineffective outcomes. Processes aimed at increasing stakeholder participation in the development of public services may significantly raise the costs involved. Mediating interested groups can take time and require resources spent on meetings and decision-making sessions (Saraceni, 2015; Wu & Wang, 2024).

Despite the structural and operational challenges associated with participatory governance, its effective implementation in tourism destinations can lead to substantial improvements in perceived quality and user satisfaction with public services. In a cocreated service environment, tourists are no longer passive recipients but active contributors to service development. Their involvement increases the legitimacy and relevance of public policies and services, enhancing their perception of responsiveness and efficiency. Research has shown that tourists who perceive higher service quality-particularly in aspects such as cleanliness, mobility, safety, and information-report greater satisfaction with the destination experience (Abuamoud et al., 2019; Lee & Xue, 2020). This is particularly true in contexts where public infrastructure is integrated with tourism-oriented policies.

Satisfaction, in turn, is a critical mediator between perceived quality and behavioral outcomes, such as the intention to revisit or recommend a destination. According to recent tourism behavior models, satisfaction operates not only as an emotional reaction but as a cognitive assessment that directly influences future behavior (Prayag et al., 2017; Li et al., 2023). In destinations governed through the principles of NPG (characterized by inclusiveness, transparency, and responsiveness), tourists are more likely to experience higher satisfaction because they perceive services as tailored to their needs and experiences. This perception fosters trust in public institutions and encourages a sense of belonging and reciprocity, even among nonresidents such as tourists.

As a result, the intention to recommend the destination emerges as a powerful indicator of success in both tourism development and participatory public governance. Tourists who are satisfied with the quality of public services are more inclined to engage in positive word-of-mouth, contributing to the destination’s image and attracting new visitors (Kanwel et al., 2019; Lee & Xue, 2020). Therefore, integrating performance indicators that capture tourists’ perceived quality and satisfaction into the planning and evaluation processes of public services proves to be not only beneficial for destination management but also essential for consolidating a user-centered, sustainable, and competitive tourism governance model (Prayag et al., 2017; Li et al., 2023).

This study used an exploratory approach due to the limitations of studies with objectives and methodologies related to public services. The research also has a descriptive aspect, aiming to build a structural model through the use of multivariate statistics to describe aspects of a daily phenomenon and its studied population (Gil, 2008).

The sociodemographic variables collected in the research were: gender, age, state of residence, education level, reason for travel, and type of accommodation used. Table 1 presents the sociodemographic characteristics of the 770 tourists who participated in the study. The majority of respondents were female, with a balanced distribution between genders. The average age was 42 years. Most participants had higher education, and leisure was the main reason for visiting Recife. Hotels were the most frequently used type of accommodation.

Table 1

Sociodemographic Profile of Respondents
Variable	Category	Frequency (n)	Percentage (%)
Gender	Female	400	52%
	Male	370	48%
Age	Average	-	42 years
State of Residence	São Paulo	200	26%
	Rio de Janeiro	162	21%
	Minas Gerais	116	15%
	Pernambuco	62	8%
	Other States	230	30%
Education Level	Higher Education	470	61%
	High School	185	24%
	Postgraduate	85	11%
	Elementary Education	30	4%
Travel Purpose	Leisure	277	36%
	Work/Business	223	29%
	Congress/Conventions	100	13%
	Visiting Friends/Relatives	92	12%
	Health	38	5%
	Religious	30	4%
Accommodation Type	Hotel	385	50%
	Friends/Relatives	239	31%
	Short-term Rental	123	16%
	Own Residence	23	3%

Source: research Data (2023).

Public services were analyzed using 39 independent variables grouped into seven distinct constructs. For the first construct-Health-to obtain the evaluation of health services, data collection was conducted in health facilities specialized in serving tourists. The variables were formatted and evaluated according to Table 2. The highest averages were attributed to the evaluation of the competence of healthcare professionals during service, with a score of 6.

Table 2

Descriptive Statistics for the Health Construct
Variable	Valid Cases	Mean	Median	Standard Deviation	Variance
V1 - The facility where the service took place had processes that expedited my service	109	5.4	5.0	1.4	2.0
V2 - The healthcare professionals were competent in their service	109	6.0	6.0	2.0	3.9
V3 - The facility had modern equipment for service and comfort in its facilities	109	5.2	5.0	2.3	3.0

Source: research Data (2023).

For the analysis of the variables in the Health construct, 109 respondents participated in the sample analysis. These respondents stated that they had used public health services during their stay. The mean, median, and standard deviation show a strong concentration of the assigned ratings. Although the highest mean was attributed to the variable “The healthcare professionals were competent in their service,” when compared with the Travel Reason variable, as shown in Table 3, respondents who were segmented based on Health as their reason for travel gave the lowest average rating in the sample.

Table 3

Segmentation of Respondents by Reason for Travel
Travel Reason	Mean for “The facility where the service took place had processes that expedited my service.”	Mean for “The healthcare professionals were competent in their service.”	Mean for “The facility had modern equipment for service and comfort in its facilities.”
Work/Business	5.5	5.9	5.1
Congress and Conventions	5.4	5.8	5.2
Leisure	5.4	6.1	5.2
Religious	5.5	6.1	5.3
Health	5.7	5.8	5.0
Visiting Relatives and Friends	5.3	6.0	5.2
Overall Total	5.4	6.0	5.2

Source: research Data (2023).

Although the variable “The healthcare professionals were competent in their service” maintained the highest average in the Health construct, the lowest rating was given by visitors whose main reason for their visit was to seek healthcare services.

For the analysis of the “Qualification” construct, the sample base consisted of the 770 valid cases, as shown in Table 4. The overall arithmetic mean of the variables was 7.2.

Table 4

Variables in the Qualification Construct
Variable	Valid Cases	Mean	Median	Standard Deviation	Variance
V4 - The professionals were courteous to me during the service (waiters, drivers, guides, receptionists, housekeepers, etc.).	770	7.9	8.0	2.2	4.7
V5 - The professionals appeared to have good knowledge in their respective areas of expertise.	770	5.9	6.0	2.0	4.3
V6 - The service was fast and of good quality (waiters, drivers, guides, receptionists, housekeepers, etc.).	770	8.0	9.0	2.3	5.0
V7 - I was satisfied with the level of qualification of the professionals I interacted with.	770	7.0	8.0	2.0	4.1

Source: research Data (2023).

The evaluation behavior for the variables forming the construct was uniform, except for the evaluation given to the variable “V5,” which received an average rating below 7 points. Although the average rating for variable “V7” was higher than that for “V5,” the quality of service may seem satisfactory to visitors, but there remains a latent need for improvement. As Xu and Sun (2015) point out, the quality of tourism services is intrinsically linked to the level of education and qualification of the workforce providing these services. The authors argue that while it may be intuitive to expect a direct correlation between workforce qualification and positive service evaluations, the reality may present more complex nuances. According to them, the qualification of professionals and the evaluation of tourism services can display a contrary behavior, without necessarily being correlated. This suggests that high levels of training and education do not automatically guarantee positive service evaluations, as other factors, such as tourists’ expectations, the specific nature of the services, and the conditions under which services are delivered, also play crucial roles.

The next construct evaluated was related to the city’s infrastructure and cleanliness. For the analysis of this construct, 770 cases were used, and the arithmetic mean of the evaluations is presented in Table 5.

Table 5

Variables in the Structure and Cleanliness Construct
Variable	Valid Cases	Mean	Median	Standard Deviation	Variance
V8 - The places I visited had an adequate water supply	770	7.9	8.0	1.8	3.2
V9 - The roads leading to the places I visited were in good condition and paved	770	6.2	7.0	2.0	4.1
V10 - The places I visited were clean	770	5.7	6.0	2.0	4.2
V11 - Overall, I am satisfied with the cleanliness of the city	770	5.8	6.0	2.2	4.1
V12 - During my stay, I noticed trees and good urban greenery in the city	770	8.2	8.0	2.7	3.0
V13 - During my stay, I noticed good telephone and internet coverage	770	6.6	7.0	3.0	3.8
V14 - I noticed a low level of pollution in the city during my stay	770	5.9	6.0	2.0	3.1

Source: research Data (2023).

The overall arithmetic mean for the construct was 6.4, with only one variable scoring above 7 points, which was for the adequate water supply. The variables assessing infrastructure and road maintenance, as well as cleanliness, received ratings below 7 points, indicating possible dissatisfaction with these aspects of the visited destination. As Castellani et al. (2007) state, cleaning services are primarily aimed at the local resident population, but their impact extends beyond the intended audience and affects various other sectors, such as tourism. Therefore, the rating below 7 points for the Structure and Cleanliness construct may reflect an evaluation shared by the resident population. As Rua (2014) classifies, such services are indivisible in the context of economics and public service theory. When these services are provided to one individual, they are available to everyone in the same quantity.

In other words, one person’s consumption of the service does not reduce the amount available to others. In the context of municipal management, certain strategic areas may receive higher-intensity or better-quality services. However, visitors’ impressions as they move through the destination will encompass both tourist spots and urban areas. This does not seem to align with the experience of the sample’s visitors, who rated these aspects below seven.

For the Transportation construct, the overall arithmetic mean of the variables was 6.3, with differences between valid cases distributed across the variables, as shown in Table 6.

Table 6

Transportation construct
Variable	Valid Cases	Mean	Median	Standard Deviation	Variance
V15 - Public transportation was easy to use	750	6.2	7.0	2.5	2.2
V16 - The buses, taxis, and ride-hailing cars I used were comfortable	764	6.1	6.0	1.7	2.8
V17 - The waiting time for transportation was appropriate	764	6.3	7.0	1.3	1.6
V18 - The transportation methods used were punctual	770	6.5	7.0	1.2	1.5
V19 - I am satisfied with the public transportation service in the area	770	6.5	7.0	1.1	1.2

Source: research Data (2023).

The arithmetic means for the evaluated variables showed little variation, ranging from 6.1 to 6.5. Specifically in terms of planning and execution, Wei et al. (2020) affirm that there is a difference between the aspects that form the transportation service in a locality and traffic organization. Therefore, traffic organization was analyzed, as shown in Table 7.

Table 7

Traffic Organization Construct
Variable	Valid Cases	Mean	Median	Standard Deviation	Variance
V20 - The agents responsible for organizing traffic helped the flow of cars and motorcycles	770	6.6	7.0	1.3	1.7
V21 - The area has good road and street conditions	770	6.5	7.0	1.3	1.6
V22 - The locality has pedestrian crossings and good urban signage	770	6.4	7.0	1.2	1.5
V23 - Traffic was smooth, with little waiting time	770	6.3	7.0	1.2	1.6
V24 - I am satisfied with the traffic organization service in the locality	770	6.5	6.0	1.0	1.0

Source: research Data (2023).

As shown by the results in Table 7, the evaluation averages did not vary significantly, ranging from 6.3 to 6.6 for the 770 valid cases. These results indicate a consistent perception among tourists regarding traffic organization in the city, suggesting a relatively uniform experience across different visitor profiles. Following this analysis, attention was directed toward another essential aspect of the tourist experience: the availability and quality of tourist information in the city. The analysis of the variables involving aspects of tourist information in the city resulted in 770 valid cases, and the following variables were investigated:

Table 8

City Information Construct
Variable	Valid Cases	Mean	Median	Standard Deviation	Variance
V25 - I was able to identify Tourist Information Centers in the area	770	6.9	7.0	1.3	1.7
V26 - The area has good tourist signage	770	7.4	8.0	1.1	1.1
V27 - During my stay, I had access to good quality maps and guides	770	6.8	7.0	1.5	2.3
V28 - I am satisfied with the provision of information in the city	770	7.0	7.0	1.1	1.1

Source: research Data (2023).

The overall arithmetic mean for the Tourist Information construct was 7.0, with the highest rating given to variable “V26” and the lowest rating for variable “V27,” as shown in Table 8.

When comparing the averages with sociodemographic variables, the Travel Reason variables provided distinct information regarding the ratings based on the reason for visiting the destination. As shown in Table 9, the average rating for those who visited for religious reasons and to visit relatives and friends was the lowest in the sample.

Table 9

City Information vs. Travel Reason
Travel Reason	V26 Mean	V27 Mean	V28 Mean	V25 Mean	Average
Work/Business	7.6	7.0	7.1	7.0	7.2
Congress and Conventions	7.4	6.8	7.1	6.9	7.0
Leisure	7.3	6.9	7.1	7.0	7.1
Religious	7.0	6.4	6.8	6.5	6.7
Health	7.3	6.7	6.9	6.9	7.0
Visiting Relatives and Friends	7.2	6.3	6.7	6.7	6.7

Source: research Data (2023).

The differences in ratings may be based on the different tourist attractions characteristic of each type of tourism. The places visited are driven by the motivation that leads the tourist to visit a location. Attractions are chosen for a specific purpose, so visitors on leisure trips are less likely to visit attractions related to congresses and conventions. However, regardless of the motivation, as Tavares (2019) points out, tourist signage influences tourists’ perceptions by conveying important information about the attraction and adding value to the experience, ultimately affecting their recommendation. The next construct analyzed included variables that sought to measure the feeling of safety when visiting the area. For the analysis of this construct, 770 valid cases were examined, yielding an overall average of 6.5 among the four evaluated variables. As shown in Table 10, there was little variation between the responses, with the mean range being two-tenths of a percentage point, with the same behavior for the median, standard deviation, and variance of the ratings.

Table 10

Safety Construct
Variable	Valid Cases	Mean	Median	Standard Deviation	Variance
V29 - I noticed a good number of police officers and stations in the area.	770	6.6	7.0	2.0	4.1
V30 - I felt safe walking around the city.	770	6.4	7.0	1.9	3.8
V31 - I noticed good police infrastructure in the city.	770	6.6	7.0	2.0	4.1
V32 - I evaluate the municipality as having good public safety performance.	770	6.5	7.0	1.8	3.4

Source: research Data (2023).

When analyzing the intersection with sociodemographic variables, the most significant discrepancy between the variables was identified when comparing the Safety construct with the variable Sex. The highest rating was given by female participants. The overall average rating of the construct for the female audience was 6.6, while for the male audience, the overall average was 6.3. This percentage difference followed the same pattern across all variables in the construct when compared by gender.

The variable “I recommend the visited tourist destination to a friend or acquaintance” was measured using a numerical scale ranging from 0 to 10. In this study, the variable was treated as continuous, based on the assumption of equal intervals between points on the scale and supported by the large sample size (n = 770), which meets the conditions of the Central Limit Theorem. The average score was 8.1, with a median of 8 and a standard deviation of 3.1, indicating a generally favorable intention to recommend the destination among respondents.

This section presents the analysis of how tourists’ evaluations of public services influence their intention to recommend the destination, using Partial Least Squares Structural Equation Modeling (PLS-SEM). The approach allows for estimating complex causal relationships between latent variables and is particularly suitable for exploratory studies with non-normally distributed data. To analyze the relationship between the evaluation of public services and the recommendation variable, the SEM technique was used. Due to the data’s nonadherence to the normality curve and the exploratory nature of the research, the estimation method employed in SEM was PLS, estimated using the Smart PLS software version 4. The model included the 7 constructs as second-order latent variables, while a new construct titled “Public Services Evaluation” was developed as a first-order latent variable, directly related to the final variable, “I recommend the visited tourist destination to a friend or acquaintance.” To assess the impact of tourist services both independently and dependently, the construct has a direct connection with both latent variables.

The adoption of second-order latent constructs was based on theoretical and methodological justifications. The constructs represent multidimensional concepts frequently modeled as higher-order in the tourism and public services assessment literature (Lee & Xue, 2020; Prearo, 2013; Hair et al., 2009). For example, perceptions of public infrastructure involve interconnected dimensions such as urban mobility, cleanliness, traffic, and safety, which are best captured by a hierarchical structure.

From a methodological point of view, the repeated indicator approach was used in SmartPLS to estimate higher-order reflective-reflective constructs. All first-order constructs demonstrated satisfactory levels of internal consistency (α > 0.80; CR > 0.80), convergent validity (AVE > 0.50), and strong external loadings (> 0.70), supporting their aggregation. Furthermore, the second-order specification contributes to the interpretability of the model without compromising predictive power, as indicated by the R² values for the dependent variable, as shown in Figure 1, which presents the tested model:

Figure 1 Source: research Data (2023).

As presented in Figure 1, the 32 remaining variables are organized into 7 reflective constructs, while these 7 constructs form a formative relationship with the latent variable “Service Evaluation.” The model assesses the dependent relationship between the latent variable “Service Evaluation” and the recommendation variable.

To evaluate the model and its interactions, the following parameters, as suggested by Chin (1998), were used:

Table 11

	Parameters
Indicators:	Reflective Models
Factor Loadings	Above 0,605
Composite Reliability	From 0,703
Internal Consistency (Cronbach’s Alpha)	From 0,703,6
R² Explanation Coefficient	0.25 to 0.49: weak
	0.50 to 0.74: moderate
	0.75 or more: substantial
Average Variance Extracted (AVE)	From 0,50123
Discriminant Validity	AVE should be greater than the variance between the construct and other constructs in the model123
Coefficient Significance	Assessed through bootstrapping
Collinearity Statistics (VIF):	Internal VIF values

Source: Prearo (2013) (1) Fornell and Larcker (1981); (2) Sharma (1995); (3) Chin (1998); (4) Hulland (1999); (5) Bido et al. (2010); (6) Hair et al. (2009).

Using the algorithm calculation of the PLS estimation method and applying the “Path” weighting scheme, with 300 iterations and a stopping criterion of 7, the results of the relationships between indicators and constructs were obtained.

After three attempts to adjust the variables to achieve the best model with the research sample, the results met the parameters outlined in Table 11. As shown in Figure 2, the factor loadings present a relationship index above 0.60 for all variables, indicating a correct association with the constructs. The AVE, Cronbach’s alpha, and composite reliability demonstrate good quality of the measures obtained from the SEM analysis.

Figure 2 Source: research Data (2023)

In the developed model, the Explanation Coefficient (R²) for the relationship between service evaluation and city recommendation was 58.1%, indicating a positive relationship between service evaluation and the recommendation variable for the visited destination.

According to Bido et al. (2010) and Hair et al. (2009), explanation coefficients with values between 0.25 and 0.49 are considered weak, 0.50 to 0.74 moderate, and above 0.75 strong. Therefore, the index of 0.581, as shown in Figure 2, demonstrates a positive, moderate-intensity influence between the evaluated services and respondents’ recommendations of the destination.

Figure 3 Source: research Data (2023).

These findings align with recent literature that highlights the pivotal role of perceived service quality in influencing tourists’ behavioral intentions, particularly their likelihood to recommend a destination. As observed in studies by Prayag et al. (2017) and Kanwel et al. (2019), service quality impacts tourist satisfaction, which in turn strengthens loyalty and recommendation behaviors. The positive and moderately strong influence identified in this study reinforces the theoretical expectation that public service quality-when aligned with tourists’ needs-acts as a critical driver of destination competitiveness. Furthermore, the high average score for recommendation found among respondents supports the idea that even public services traditionally aimed at residents can significantly shape tourists’ perceptions and future intentions when well-managed.

To analyze the significance of the structural coefficients between variables in the SEM, a resampling test was performed using bootstrapping, a method that assesses the bias or variance of a dataset to deepen the analysis of relationships. The resampling test was conducted with an analysis based on 5,000 subsamples. The Student’s t-test provided by the model presents two hypotheses: the null hypothesis, stating that the calculated parameter is equal to zero, and the alternative hypothesis, where the parameter is different from zero. According to Prearo (2013), t-statistic values above 1.96 indicate statistically significant parameters. For all relationships, the p-value was 0.00, and t-statistic values were above 1.96, confirming the hypothesis and the statistical significance of the relationships between constructs.

Public services are inherently indivisible, meaning they cannot be provided individually. They are developed, evaluated, and managed to serve a target audience-the local population. As Denhart and Denhart (2015) emphasized the need to consider citizens as both managers and primary beneficiaries of public services within the framework of NPG, this concept may need to be expanded to include agents who, although temporarily, share these services.

This aspect holds significant importance, as temporary users like tourists are vital sources of revenue and funding for public services. However, in the development of public policies resulting in public services, only local population assessment indicators are considered. Public service construction and evaluation tools, such as participatory budgeting, exist to include the primary users of public services, yet they are still used only by an exclusive segment of users. Given that tourism is a crucial source of revenue for public administration, this research sheds light on the importance of including these users in the management of public services in a locality.

According to Chen et al. (2020), quality in service delivery is centered on understanding what visitors expect when they arrive at a destination. This expectation can only be met if tourist destinations provide public services designed to create an enjoyable experience. Such an experience may lead to the visitor’s return or to the recommendation of the destination to others. Therefore, investing in the improvement and enhancement of service quality in a locality is essential for the successful development of tourism activities.

While Chen et al. (2020) argue that delivering quality public services to meet tourist expectations can lead to positive outcomes, such as repeat visits and recommendations, a critical view raises questions about the feasibility and potential limitations of integrating tourists into public service planning through cocreation. Although cocreation aims to include tourists as stakeholders who help shape services, this approach risks over-prioritizing visitor needs at the expense of local residents, who are the primary beneficiaries of public services.

The findings of this research also corroborate previous studies that underscore the central role of perceived service quality and tourist satisfaction in influencing behavioral intentions, particularly the intention to recommend a destination. As highlighted by Prayag et al. (2017) and Rita et al. (2024), tourists are more likely to promote a destination when the services they experience, such as transportation, cleanliness, safety, and public information, are perceived as efficient, accessible, and responsive to their expectations.

In line with this perspective, Islamy et al. (2022) and Lee & Xue (2020) emphasize that satisfaction plays a mediating role between service quality and recommendation behavior. The positive relationship identified in this study, reflected in an R² of 58.1% for the recommendation variable, reinforces the idea that satisfaction is not merely a subjective emotional response but a cognitive evaluation that transforms positive experiences into behavioral intentions. When tourists perceive that the services offered by the destination are of high quality and meet their specific needs, this tends to strengthen their trust in the destination and increase their willingness to recommend it to others, either through interpersonal communication or digital platforms.

Expanding upon these findings, it is essential to consider that perceived quality in tourism is multidimensional and dynamic, influenced not only by the functional aspects of service delivery but also by symbolic and emotional factors, particularly when tourists are engaged as coparticipants in the development of these services. For instance, the cleanliness of urban spaces may convey a sense of safety and care, especially when tourists perceive that their feedback contributes to the planning and maintenance of these areas. Similarly, the availability of public information services can foster feelings of autonomy and welcome, particularly when tourists have participated in shaping how such information is communicated. As argued by Lee and Xue (2020), these dimensions collectively shape the overall image of the destination, which in turn mediates satisfaction and future behavioral intentions. In this context, the cocreation of public services, by incorporating tourists’ perspectives and experiences, enhances not only the functional quality of services but also their capacity to communicate inclusivity, attentiveness, and responsiveness, which are powerful drivers of positive perception and destination loyalty.

The significance of these results for science lies in their contribution to understanding the role of public services in enhancing the tourism experience and their potential impact on destination recommendation. By analyzing the direct relationship between service quality and visitors’ likelihood to recommend a destination, this research highlights the importance of including tourists as stakeholders in public service planning and evaluation, an area traditionally focused solely on local residents.

This study advances knowledge in public administration and tourism management by illustrating that tourists, as temporary users, can offer valuable insights for improving service quality. The findings reinforce the need to adopt NPG principles that incorporate a broader range of user feedback, thereby fostering more inclusive, effective, and sustainable service models. Additionally, this research underscores the broader economic and social implications of aligning public service provision with tourist expectations, ultimately suggesting that such alignment is crucial for competitive and sustainable tourism development.

Despite the valuable insights provided, this study has several limitations that should be acknowledged. First, the data were collected through a convenience sampling method, which may not fully represent the diversity of the tourist population visiting the destination. This limitation could impact the generalizability of the findings to other tourist demographics or destinations with different characteristics. Second, while the study relies on self-reported data, which are effective for capturing personal perceptions, they may be susceptible to social desirability bias, where participants provide responses they believe are expected or favorable rather than fully accurate reflections of their experiences.

This study also has certain limitations that should be acknowledged. The research was conducted in a single urban destination, which, despite its specificity, presents a diverse tourism infrastructure and a complex public service environment that reflects characteristics common to many other tourist destinations. Therefore, while the findings may not be universally generalizable, they offer a valuable understanding for destinations with similar profiles. From a managerial standpoint, the results highlight the importance of involving tourists in the evaluation and improvement of public services. Encouraging participatory mechanisms can enhance service responsiveness, increase tourist satisfaction, and foster positive recommendation behaviors, thereby contributing to the strategic positioning of the destination.

Future studies could examine a broader range of tourist destinations with different characteristics, such as urban, rural, coastal, and heritage sites, to assess how public service quality influences visitor satisfaction across diverse environments. This comparative approach would help identify which types of services are universally valued and which are unique to specific types of destinations.