Innovation and Strategic Management for the Development of Tourist Destinations: Development of Nightlife and Residents’ Attitudes in Punta del Este (Uruguay)

Abstract

Nightlife is a controversial offer for its possible negative social impacts, but it is also important for its media impact and as an element of differentiation of the tourist destination. In the coastal resorts it is a very important offer as it complements the main offer. This paper seeks to determine the background of residents’ attitudes towards the offer of nightlife. To do this, the responses of a sample of 420 residents of the Maldonado-Punta del Este conurbation (Uruguay) who responded to a questionnaire with items measured with Likert scales are analyzed using Structural Equation Models. A first analysis, which presents costs and benefits of three types (economic, social and cultural) as a possible background of the degree of acceptance of this offer, did not detect significant relationships. In a second analysis, the mediation of the overall attitude towards tourism and the degree of acceptance of sun and beach tourism were proposed. In this second analysis it was found that: only economic benefits and cultural costs have significant effects on the overall attitude; the overall attitude has a significant effect on the acceptance of sun and beach tourism, but not on the acceptance of nightlife; and the acceptance of sun and beach tourism has a significant effect on the acceptance of nightlife. The acceptance of nightlife follows the same guidelines as its business development (it is a consequence of sun and beach tourism).

1. Introduction

Tourism is considered to be one of the economic sectors which has developed most in the world in the last hundred years and is expected to continue its development in the coming decades [1]. During the last fifty years, the study of tourism and its economic and social implications has increased, with special importance in the analysis of the residents’ attitudes [2,3]. The huge numbers of tourists in the most established destinations have led to a significant increase in the concern and study of overtourism in recent years (e.g., [4,5,6,7,8,9,10,11,12,13]).

Tourist activity occurs in a different social context than other sectors of activity [2]. In the primary sectors (agriculture, livestock, fishing, etc.) and secondary (mining, industry and manufacturing), workers and residents (the rest of inhabitants) live in the same region but do not come into contact with the customers of the economic activity. In the vast majority of non-tourism-related services, residents are current or potential customers of the services marketed. In all these cases, there are only interactions amongst residents, some as industry workers, others as customers and others in neither of these roles [14]. In activities related to tourism, there is movement of population, the tourists, from their region of residence to tourist destinations. Therefore, in this sector there would be three groups interacting in the region: tourist workers, tourists and residents (whether or not they work in the sector) [3,14].

In addition, tourism is a complex product composed of multiple goods and services. This implies that everything that comes into contact with tourists in the tourist destination is part of the product, including interactions between tourists and residents [3]. These interactions are so important for the tourist’s satisfaction that favorable attitudes towards resident tourism have become fundamental for the correct development of tourist destinations [15,16]. This implies that knowledge of these attitudes is unavoidable for business managers and administrations operating in regions that claim to have a future in the tourism sector [15,16,17]. Knowledge of these attitudes is fundamental when planning future tourist developments or contemplating new offers in the region [18], especially if it is a type of offer that can be controversial as is the case of nightclubs [19].

The importance of the analysis of residents’ attitudes has been present in the academic world uninterruptedly for over fifty years [2,3,15,16,20], acknowledging the importance of residents for the tourist sector since the beginnings of the academic study of tourism. The sophistication of objectives and analysis methodologies has changed over the years [2]. In early works, they analyzed the attitudes of residents and also the perception of the impacts which could be attributed to tourism development, considered as the main explanatory variable of the attitudes expressed [21,22,23,24,25,26,27]. In more recent times, many more causal variables have been added to the analyses carried out [2].

Over the years, the objectives and analysis techniques posed increased in sophistication (e.g., [28,29,30,31,32,33,34,35]). Nowadays, the study of causal relationships which could explain residents’ attitudes is a priority (e.g., [3,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51]). There are also studies more focused on the consequences of residents’ attitudes [52,53,54]. These types of studies made it necessary to include new analysis techniques in the field of study, mainly multivariate techniques based on the use of multiple regressions, such as Structural Equation Models [52,55].

The result of all this research is that the division of the impacts of tourism has now been consolidated into benefits and costs of three (economic, sociocultural and environmental) or four (economic, social, cultural and environmental) types [15,56,57]. Although some more recent studies have merged these types of impacts into only two scales, one for benefits and one for costs [57,58,59], this study will maintain the breakdown as the intention is to find the types of benefits and costs which have significant effects on the dependent variables posed.

Although there are numerous types of tourist offers, one of the most important due to its volume is sun and beach tourism. Sun and beach tourism has grown enormously since the mid-20th century and is closely related to the development of the welfare state and the emergence of an ever-increasing middle class [1]. This type of tourism has meant an important economic boost in numerous coastal regions, both continental and insular, and is currently one of the offers related to the concept of mass tourism due to its huge global volumes. The main attractions of this tourism are climate and rest, meaning a break with tourists’ working routine, but needing some leisure activities that complement it. These leisure activities include various daytime activities, mainly linked to beaches, coastal areas and marinas, but there are also nightlife activities ranging from restaurants with shows to cocktail bars, large nightclubs or outdoor concerts. In all coastal holiday destinations specialized in the offer of sun and beach, some kind of nightlife offer has been developed. However, the level of development of this offer is different [19]. Whilst in some destinations it is minor and almost unknown, in others, the nightlife offer has achieved such prominence in its promotion that it has almost eclipsed the offer of sun and beach. Examples of the latter case are Ibiza, Mykonos and Pag in Europe, or Miami and Camboriú in America [19,60].

The media impact of nightlife is very important, especially on social media [61], and many coastal tourist destinations have increased this type of offer in order to improve its appeal and media impact. This has led to the creation of new companies within this sector or the conversion of pre-existing establishments to incorporate this type of offer. In addition, in recent years a large volume of tourist offers which seek to innovate by introducing events and electronic music in its offer have appeared [62].

The aim of this paper is to find the most probable causes or reasons for the acceptance or not of the nightlife offer, that is, as the perception of the impacts of tourism (both positive and negative) and the attitudes towards tourism in general and sun and beach tourism (the main and traditional in the analyzed destination) can help explain the attitudes of the residents towards the nightlife offer. For this, an exploratory analysis was carried out to find the most likely structure of causal relationships between residents’ perceptions and the degree of acceptance of various types of tourist offers (the traditional sun and beach tourism and the nightlife offer). For this purpose, we have based our work on a sample of residents of Maldonado-Punta del Este (Uruguay) and alternative causal relationships have been considered. The analysis was carried out using Structural Equation Models (SEM), specifically Partial Least Squares (PLS-SEM). The following sections review the literature, set out the methodology and results, and finally the main conclusion is drawn. The main result is that the acceptance of nightlife is a consequence of the acceptance of sun and beach tourism, highlighting the complementary function of this offer.

2. Literature Review

Within academic literature it is necessary to comment on various concepts that will be taken into consideration in this paper. These should include the perception of the impacts of tourism and the residents’ response to these impacts. It is also worth taking into account entrepreneurship and innovation in services that represent the offer of nightlife for traditional sun and beach tourist destinations, and the state of the research in relation to nightlife.

2.1. Residents’ Perceptions and Attitudes

As previously indicated, residents’ perceptions of the region’s tourism development are divided into benefits and costs and, within them, economic, social, cultural and environmental [56,57,63]. By focusing this study on nightlife and considering that its environmental impact is minimal, compared to the economic and socio-cultural, the environmental impact has been overlooked in the analysis.

Positive economic impacts are fundamental when generating the social support needed for the tourism sector [22,26,64,65,66,67]. In practice they consist of an improvement in the income of people and companies in the region [15,26,64,65,66,67]. This is generally due to an improvement in job opportunities in the form of tourism jobs [15,64,65,67], an increase in business opportunities which encourages local entrepreneurship and attracts investment from abroad and other sectors [15], and an increase in government revenue in the form of taxes [65,66]. Of these economic benefits, job creation is the most important for the resident population [15,64,65,67]. Considering all this, the ultimate goals of all regional tourism development are elements related to the well-being of residents [53].

The social improvements generated by tourism in the local community and which do not represent an increase in the direct income of its members are encompassed within social benefits. This includes physical improvements in the immediate social environment, i.e., infrastructures, public services and public spaces in general [15,21,22,26], and in the leisure offer in general and in the nightlife offer in particular [19,60]. The social benefits usually imply an improvement in the well-being [53] through an improvement of the urban and social environment. Normally, tourist destinations have a wider range of services and a more cosmopolitan society than regions with a similar population size but without significant tourism development.

The main positive impact of tourism on the culture of the region is to showcase the value of local tangible heritage (buildings and cultural landscapes) and intangible heritage (traditions and customs). This value makes the restoration and conservation of historical heritage, traditions and other cultural elements economically profitable [22,26,68]. Other cultural benefits are contact with and learning from other cultures [21,22], and a greater pride in one’s own culture [22,69] as it is no longer a symbol of out datedness, but an element admired by visitors. The two great cultural benefits of tourism are the enhancement of the material and immaterial heritage of the region, since with tourism this heritage have the capacity to generate income and finance their conservation, and the learning of other cultures that come into contact with local society through tourists or workers who have come to the region.

These three types of benefits are matched with their corresponding costs. The first thing to note is that all tourist destinations have a certain differentiation from other regions which leads to an increase in tourist prices, which is passed on to the other prices in the region. This causes higher price indexes than in non-tourist regions and produces a loss of purchasing power for residents, this therefore being the main economic cost caused by tourism [21,22]. Another negative economic impact occurs on jobs, as working conditions (timetables, remuneration, stability, etc.) in the tourism sector are worse than in other sectors [67] and price increases caused by tourism are depleting the purchasing power of the already meagre remuneration. Tourism is usually considered a sector that generates many jobs but with low incomes.

The social costs of tourism, especially in small communities with a very rapid tourism growth, are several: increased crime and sense of insecurity [21,23,24,26]; congestion of public spaces, especially roads [24,26,65,66]; and other various nuisances (noise, access to private property, etc.). The social problems that have appeared in the most developed and overcrowded tourist destinations [12] have become a subject of academic attention (e.g., [4,5,6,7,8,9,10,11,12,13]), under the concept of overtourism [70,71,72,73,74,75]. Normally, overtourism is understood as the situation in which the tourist activity exceeds the carrying capacity of the region, producing overcrowding and inconvenience to residents [11,12], generating a loss of well-being for residents and a loss of tourist satisfaction [76]. Problems linked to overtourism often involve irritation among the local population [12], anti-tourism attitudes [9] and protest movements [74,75]. Given the importance of residents, and their attitudes, for sustainable tourism development [77,78], among them it is necessary to highlight the promotion of the resilience of society local [72] and the increased participation of residents in decision-making affecting the region [77].

The main negative impact that can occur on culture is its alteration by coming into contact with the cultures of tourists or residents from abroad [64,79]. Another negative effect is that traditions and customs become disconnected from their context and historical sense as they turn into theatrical representations offered as a tourist attraction [80]. In any case, it should be noted that culture is a dynamic element and it is difficult to determine whether these changes are negative [81] or simply the natural evolution of culture in a context of tourism development [82]. In this case, the person’s vision of culture (as a dynamic or static element) is fundamental for determining the effect of cultural changes (positive when there is a dynamic perception and negative when the perception of culture is static).

Finally, it should be noted that academic work has adopted various theories as an explanatory tool for residents’ attitudes, highlighting the Social Exchange Theory as one of the most popular [7,52,83,84]. This theory suggests those residents’ attitudes towards tourism in general, or particular elements thereof, are based on a balance between perceived benefits and perceived costs. If benefits are clearly higher than costs, attitudes will be favorable or very favorable, and if the costs outweigh the benefits, they will have unfavorable attitudes.

2.2. Nightlife

Analyses of residents’ attitudes normally focus on the main tourism of the destination or ask about tourism generically, but some studies have analyzed specific sectors. One of the specific offers with the greatest presence in literature is gambling and casinos [83,85,86,87]. This is due to the concern possible social negative impacts generate amongst the local population.

Nightclubs and nightlife also cause concern due to their potential negative impacts on society and have become a context for studying various problems: drugs, alcohol, tobacco and drugs [88,89,90], violent behavior [91,92,93], risky sexual intercourse [94,95], accidents or disasters [96,97] and health problems [79,98]. Social behavior has also been analyzed in the context of nightlife [99,100,101,102], but studies are scarcer from the management field [103,104,105,106,107]. In the specific case of residents’ attitudes, previous studies are few and initial [19,60] and, therefore, much remains to be carried out in this area. As mentioned in the introduction, the thesis proposed in this study is that nightlife is a complementary element to the offer of sun and beach of coastal tourist destinations, and not an independent tourist offer and that can be developed in an isolated way. In large cities, nightlife has different technical characteristics and client profiles (they are mostly residents and not tourists), so this hypothesis could not be generalized to nightlife in urban areas.

2.3. Innovation and Entrepreneurship

The latest studies focus their research on innovation and entrepreneurship in the tourist destination, focusing on the factors and characteristics of innovation and entrepreneurship of the tourist business. Canestino et al. [108] identify the key factors for the successful creation of social value, through the application of a social model (SBM), to a case study (a social cooperative in Italy). Kallmuenzer et al. [109] investigate the ideal set of factors that lead the company to having a high performance. The study was carried out in Austria and its informants were the managers or owners of tourism SMBs. Ageeva and Foroudi [110] investigated the implications for tourism planning and management, the factors which identify the place, and how it influences a traveler’s behavior in Russia. All this gives rise to implications in terms of entrepreneurship, as well as adaptations for improving the planning and management of tourism organizations. Khmelyarchuk et al. [111] investigate strategic alternatives for tourism business development, which will allow companies to select their own strategy based on different factors. Cucari et al. [112] investigate the case study of the business model based on the sustainable development of a hotel in Italy. This study serves as an example to learn good practices for future entrepreneurs in this field. Gonçalves et al. [113] developed a method to evaluate the competitiveness of SMEs. This research makes it possible to disentangle the factors that make it possible to identify the competitiveness of these companies in order to obtain competitive advantages. This study is ideal for developing mechanisms to evaluate the business performance of SMEs. Zvyagintseva et al. [114] study the factors involved in the development of small enterprises in Russia. Chim-Miki and Batista-Canino [115] develop a model of cooperation in a tourist destination. This will allow one to monitor the strengths and weaknesses of the destination towards tourist cooperation, as well as to optimize relations to increase the competitiveness in tourist entrepreneurship. Triantafillidou and Tisiaras [116] focus their research on Greece, examining several case studies, the relationship between sustainable tourism, innovation and entrepreneurship.

These authors identify the factors which help or limit the promotion of sustainable tourism practices among entrepreneurs, the dimensions of sustainability and their relationship to competitiveness. Zhou et al. [117] investigate internal business mobility in tourist destinations in rural China, as well as identifying the factors affecting this type of mobility. Panfiluk and Szymariska [118] identify optimal measures for the innovation of participation and its effects on the business of health tourism services in Poland. Metaxas and Karagiannis [119] investigate culinary tourism based on the exploitation of ancient Greek values. These authors explore how a field of new business and regional development is combined with knowledge, innovation and quality. These researchers analyze real business ventures using the case studies. Strobl and Kronenberg [120] study the dynamics of business networks throughout the life cycle of the hospitality company in Austria. These authors identify the factors which trigger the configuration of these networks along with findings to address challenges encountered by growth within hotel ventures.

3. Methodology

The methodology used has consisted of an exploratory analysis applied to a quantitative database. Although no initial hypotheses have been proposed, alternative causal models have been formulated based on the literature on residents’ attitudes [64,65,66,67], considering as a starting point the perception of the impacts generated by tourism [56,57,63] and as a dependent variable the acceptance of nightlife by residents. The residents’ attitudes and the acceptance of the traditional tourist offer in the region have also been taken as possible moderating variables. As for the data, they come from a sample of residents of the Maldonado-Punta del Este conurbation who were interviewed using a closed-ended questionnaire. Data analysis was performed using Structural Equation Models (SEM), a very common technique in academic research in the areas of marketing and business management [52,55,121]. In essence, SEM consists of the simultaneous analysis of several multiple linear regressions, having the same advantages and limitations as linear regressions: on the one hand, it is almost the only way to analyze possible causal relationships in a non-experimental context; on the other hand, rather than affirming the existence of a causal relationship, it rules out the existence of causal relationships through statistical correlations. In addition, in the SEM methodology, the variables used are constructs that measure abstract concepts through scales previously transformed by factor analysis. Finally, it indicates that the region taken for the analysis is an important international tourist destination, supporting the relevance of the study.

Punta del Este is a coastal tourist destination in the Eastern Republic of Uruguay (Figure 1). It is characterized by two extensive beaches (Playa Mansa and Playa Brava) and an urbanism with low levels of population density. The population in Punta del Este is less than 10,000 people. However, Punta del Este is located next to the city of Maldonado, the capital city of the department with the same name and other small adjacent towns. These urban areas form the Maldonado-Punta del Este conurbation, whose population is more than 135,000 inhabitants [15]. Punta del Este received 584,000 foreign tourists in 2019, mostly from Argentina [122].

The main and traditional tourist offer in Punta del Este is sun tourism and family beach holidays as the area has a significant offer of hotels and holiday homes to cater for this type of tourism. The offer of activities linked to sun and beach tourism is complemented by the nightlife offer. This offer has a large presence in the areas of La Barra and the port, with a total of a dozen nightclubs and around 50 bars. In recent years, new nightlife formats have appeared which are especially linked to the new beachfront hotels. They are nightclubs and restaurants which offer entertainment within the beach-front hotels and beach clubs. They are an innovative tourism offer in Punta del Este as there is no previous tradition in the area; however, there are other tourist destinations in the world with a wide tradition and reputation for this type of offer [19].

The database in this investigation is composed of the responses of a sample of residents in the Maldonado-Punta del Este conurbation, the area under study in this investigation. A questionnaire containing item scales for each concept measured along with a set of socio-demographic questions were used to obtain the database. The items used contained an option to answer Likert scale of five points; 1 “Total disagreement”, 3 “Indifferent” and 5 “Total agreement”. These items had been used in previous studies [15,65] and several preliminary tests were carried out in the area under study to verify that the questions were correctly understood.

The fieldwork was carried out over a whole year in order to cover the high and low seasons of the destination (Punta del Este is a destination with important tourist seasonality). Although sampling was carried out for convenience, socio-demographic variables were controlled in order to avoid biases with respect to the population demographic profile described in the population censuses [122]. As a result of the fieldwork, 420 valid surveys were obtained from residents of Punta del Este and Maldonado, with the socio-demographic profile described in

Table 1. Socio-demographic profile (own elaboration).

Variable	Frequency	%
Sex:
Man.	230	54.76%
Woman.	190	45.24%
Age:
Less than 25.	104	24.76%
From 25 to 34.	67	15.95%
From 35 to 44.	81	19.29%
From 45 to 54.	80	19.05%
From 55 to 64.	49	11.67%
65 or more.	39	9.29%
Birthplace:
In the region.	181	43.10%
Outside the region.	239	56.90%
Level of studies:
No Studies.	8	1.90%
Primary Studies.	39	9.29%
Secondary Studies.	177	42.14%
University Studies.	196	46.67%
Works in Tourism:
Yes.	243	57.86%
No.	177	42.14%

. The sample size implies a maximum margin of error of 4.88% for a 95% confidence level.

The SEM analysis was performed using a variance-based technique through Partial Least Squares (PLS-SEM), used extensively in previous studies [15,123,124]. The methodology based on variance and, in particular, the use of PLS-SEM is traditionally considered suitable for predictive studies or theoretical developments, i.e., testing new alternative causal models as in this case. The other main SEM methodology is the covariance-based techniques, but its methodological characteristics make it better for confirmatory analyses and problematic for exploratory analyses, as in this case. Smart PLS software [125] has been specifically used in this paper. This software has several alternatives for analysis; however, the most recommended is path weighting which has been used in this case. This procedure allows for a higher R² for the endogenous variables of the model [126].

This paper has an exploratory approach, and the priority being the search for causal alternative schemes, based on previous literature [64,65,66,67], to determine which is most supported based on the data analyzed. The perception of three types of benefits and costs (economic, social and cultural) was taken as a starting point [56,57,63]. Three variables were taken as dependents in the models; the overall attitude of residents towards tourism, as an overall assessment of the sector; the degree of acceptance of traditional tourism in the region, i.e., sun and beach tourism, implicitly hotels, holiday homes and second residence; and the degree of acceptance of the nightlife offer, which would include everything from small pubs and bars to the most important nightclubs. This is intended to determine the most logical causal relationships for independent variables (impact perception) and dependent variables (tourism assessment and different tourism offers).

4. Results

Although the objective of the study is to review the causal relationships between the proposed variables, it is necessary to carry out various verifications of the model of measure to guarantee the reliability and validity of the results along with the conclusions reached. The first element to analyze is individual and construct reliability. Reliability is a requirement focused on analyzing whether the items taken into consideration are correctly integrated into the resulting construct. In the case of individual reliability, the factorial load of the elements of the construct is used as a reference, and must be greater than 0.700, although in exploratory studies, values greater than 0.600 are admissible [127]. In the case of construct reliability, the Alpha of Cronbach [128] and the composite reliability [129,130] is used. It is considered to be a good level of reliability when the Alpha of Cronbach and the composite reliability give values greater than 0.700. However, in exploratory studies such as this investigation, the values are acceptable when they are greater than 0.600 [129,130]. Once the measurement model and the scales used have been reviewed, the reliability levels indicated for both individual reliability (

Table 2. Loadings of structural models (own elaboration).

Denomination	Arithmetic Average	Standard Deviation	Loading
Economic Benefits:
Tourism creates many job opportunities for residents.	4.350	0.780	0.795
Tourism creates numerous business opportunities for residents and small businesses and greater investment opportunities in the town.	4.195	0.837	0.856
Tourism creates greater investment opportunities in the town	4.264	0.798	0.783
It allows for a significant increase in residents’ income levels.	4.048	0.940	0.739
Social Benefits:
Thanks to tourism, basic services are of a higher standard.	2.967	1.276	0.779
Thanks to tourism, public services are of a higher standard	2.855	1.225	0.807
Tourism promotes the restoration and conservation of historical heritage.	3.274	1.150	0.770
Tourism improves the quality of infrastructure and public works.	3.555	1.062	0.783
Cultural Benefits:
Tourism promotes the understanding of different cultures.	3.788	0.964	0.797
Tourism favors meeting people from other departments of the country and other countries.	4.198	0.812	0.878
Economic Costs:
Tourism has increased both prices and the cost of living.	4.076	1.007	0.716
Tourism has led to an increase in the cost of housing and land.	4.136	0.945	0.987
Social Costs:
Tourism has increased levels of citizen insecurity.	3.119	1.149	0.891
Tourism has increased levels of inconvenience to residents.	3.548	1.106	0.760
Cultural Costs:
Tourism makes it difficult to enjoy public spaces by massifying them.	3.269	1.164	0.703
Tourism has caused residents to feel like strangers in their own locality.	2.817	1.145	0.857
Tourism has had a negative effect on local culture.	2.588	1.023	0.787
Overall Attitude:
Tourism development has been very beneficial for the town and its inhabitants.	4.093	0.836	0.776
Tourism should continue to be promoted as a key part of the locality.	4.300	0.802	0.821
Tourist activity is beneficial for the day-to-day life of the residents.	3.988	0.930	0.806
Thanks to tourism, a better quality of life exists.	3.848	0.996	0.763
Sun & Beach Tourism:
Holiday homes and apartments for rent.	4.150	0.822	0.712
Second residence tourism.	3.990	0.902	0.774
Sun and family beach tourism.	4.533	0.788	0.818
Nightlife:
Tourism of discos, pubs, etc.	3.650	1.119	1.000

) and construct reliability (

Table 3. Construct reliability and convergent validity (own elaboration).

	AVE	Composite Reliability	R2	Cronbach’s Alpha
Economic Benefits	0.631	0.872	0.000	0.804
Social Benefits	0.616	0.865	0.000	0.793
Cultural Benefits	0.703	0.825	0.000	0.681
Economic Costs	0.743	0.849	0.000	0.744
Social Costs	0.615	0.757	0.000	0.696
Cultural Costs	0.616	0.827	0.000	0.688
Overall Attitude	0.627	0.871	0.384	0.802
Sun & Beach Tourism	0.592	0.813	0.102	0.659
Nightlife	1.000	1.000	0.086	1.000

) are reached.

Apart from reliability, it is necessary to check both the convergent and discriminant validity of the model. Convergent validity analyzes whether the items taken into consideration are measuring the same concept, that is, all the items are largely a reflection of the construct. Divergent validity analyzes whether the items are correctly assigned to the constructs or if there is a better assignment option for those items. Both types of validity seek to guarantee the adequate definition of the constructs and the items that compose them. In order to check convergent validity, the Average Variance Extracted (AVE), which must be greater than 0.500, is used as the main reference element [130]. The constructs used in this study meet the indicated requirement of an AVE greater than 0.500 (Table 3). To be able to consider that discriminant validity existed, we found that the loads of the items were greater with their own construct than with the other constructs and the square root of the AVE of each was greater than the correlations of that construct with the other constructs [129,130,131], this last check appears in

Table 4. Correlations and square root of the AVE (own elaboration).

	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)
Overall Attitude (1)	1.000
Economic Benefit (2)	0.520	1.000
Social Benefits (3)	0.347	0.398	1.000
Cultural Benefits (4)	0.364	0.349	0.354	1.000
Cultural Costs (5)	−0.311	−0.145	−0.076	−0.114	1.000
Economic Costs (6)	0.186	0.227	0.075	0.146	0.188	1.000
Social Costs (7)	−0.159	−0.131	−0.073	−0.109	0.447	0.169	1.000
Nightlife (8)	0.179	0.154	0.079	0.112	−0.084	0.026	−0.111	1.000
Sun & Beach Tourism (9)	0.319	0.291	0.166	0.309	−0.269	0.093	−0.161	0.276	1.000
$\sqrt{\mathrm{AVE}}$	0.792	0.794	0.785	0.838	0.785	0.862	0.784	1.000	0.769

.

Once the measurement model was verified to meet the reliability and validity requirements, the structural models were analyzed. PLS-SEM does not assume the normal distribution of the data which in turn requires the use of non-parametric procedures to analyze the significance of the proposed causal relationships. A non-parametric bootstrap procedure [132,133] based on the model estimate from over 5000 subsamples taken from the original sample is specifically used. The parameters of the subsamples determine the error of the estimates, calculate the t-values and estimate the significance levels in comparison to a Student’s t distribution.

As a starting point of the exploratory analysis, a simple model (Causal Model I) was used in which the three types of benefits and costs taken into consideration are explanatory variables of the level of acceptance of the nightlife offer (Figure 2). It is the essence of the Social Exchange Theory [7,52,83,84] and the most basic and consolidated model on the attitudes of residents. However, no meaningful relationship was found when analyzing the significance level of causal relationships (

Table 5. Path coefficients and significance analysis (Causal Model I).

Causal Relations	Path Coefficients	Standard Error	T Statistic	p Value
Economic Benefit→Nightlife	0.096 ns	0.142	0.673	0.501
Social Benefits→Nightlife	0.118 ns	0.195	0.607	0.544
Cultural Benefits→Nightlife	0.023 ns	0.130	0.175	0.861
Economic Costs→Nightlife	0.037 ns	0.128	0.293	0.770
Social Costs→Nightlife	−0.097 ns	0.133	0.729	0.466
Cultural Costs→Nightlife	−0.030 ns	0.136	0.218	0.827

p values: ^ns not significant.

).

A second model (Causal Model II) raised new causal relationships (Figure 3). In this case, the three types of benefits and costs would be variable, explanatory to the overall attitude towards tourism (this is a more conventional causal relationship than that raised in Causal Model I) [64,65,66,67]. The second part of the model proposes the acceptance of traditional sun and beach tourism and nightlife as final dependent variables, explained by the overall attitude towards tourism. In addition, the causal relationship between sun and beach tourism and nightlife was outlined as an expression of complementarity of the second versus the first.

The analysis of Causal Model II (

Table 6. Path coefficients and significance analysis (Causal Model II).

Causal Relations	Path Coefficients	Standard Error	T Statistic	p Value
Economic Benefits→Overall Attitude	0.354 **	0.113	3.142	0.002
Social Benefits→Overall Attitude	0.125 ns	0.094	1.327	0.184
Cultural Benefits→Overall Attitude	0.150 ns	0.109	1.381	0.167
Economic Costs→Overall Attitude	0.122 ns	0.126	0.964	0.335
Social Costs→Overall Attitude	0.009 ns	0.095	0.091	0.927
Cultural Costs→Overall Attitude	−0.260 **	0.098	2.666	0.008
Overall Attitude→Nightlife	0.101 ns	0.111	0.915	0.360
Overall Attitude→Sun & Beach Tourism	0.319 ***	0.097	3.278	0.001
Sun & Beach Tourism→Nightlife	0.244 *	0.111	2.195	0.028

p values: * p < 0.1; ** p < 0.01; *** p < 0.001; ^ns not significant.

) does not find a significant causal relationship in many case, but does so in others. Only the economic benefits have a positive (0.354) and significant effect on the overall attitude towards tourism. The cultural costs have a negative (−0.260) and significant effect on the overall attitude towards tourism. The overall attitude towards tourism has a positive (0.319) and significant effect on the degree of acceptance of traditional sun and beach tourism but does not however have a significant effect on the acceptance of the nightlife offer. The acceptance of sun and beach tourism has a positive (0.244) and significant effect on the acceptance of the nightlife offer.

5. Discussion

The exploratory analysis began with a bounded causal model (Causal Model I), based on the Social Exchange Theory [7,52,83,84], which proposed that the acceptance of nightlife depends on the perception of the benefits and costs generated by tourism in the region, these costs and benefits were structured according to the most common classifications in the academic literature [56,57,63], but adapted to the study aim of this paper. The analysis of this model did not detect any significant causal relationship, forcing the creation of a broader alternative model (Causal Model II).

The main interpretation of the Causal Model I results is that the explanatory variables adopted are not useful to analyze the causes of the acceptance of the nightlife, or at least not as a direct cause. In future models, the perception of the specific impacts of nightlife should be considered as explanatory variables.

The expanded alternative causal model (Causal Model II) included the perception of the most common positive and negative impacts [56,57,63], as in the previous causal model, but the explanatory variable of these perceptions is the residents’ attitudes towards tourism in general, adopting a more “conventional” structure based on previous studies [64,65,66,67] and the Social Exchange Theory [7,52,83,84]. In this part of the model, only two significant causal relationships were detected: economic benefits and cultural costs. The economic benefits had a positive and significant effect, being a fundamental element in the formation of favorable attitudes towards the tourism [22,26,64,65,66,67], normally being the greatest positive effect of the causal models [64,65,66,67]. Regarding the costs, only the negative cultural impacts, especially the alteration of the local culture, had a negative and significant effect. This negative effect of cultural costs on attitudes is commonly found in the academic literature [64,79]. The peculiarity is the lack of significant effect of social costs, an important negative impact in previous studies [21,23,24,26,65,66]. One of the reasons for this lack of significance of social costs in this case study may be due to the dispersion of the population and tourist activity within the Maldonado-Punta del Este conurbation, not yet generating a significant problem of overtourism.

The second part of the expanded alternative causal model (Causal Model II) incorporates the degree of acceptance of sun and beach tourism and the degree of acceptance of nightlife as a cause of attitudes towards tourism. In this case, the region’s main tourism (sun and beach tourism) has a strong positive relationship with residents’ attitudes towards tourism. Actually, it is not uncommon that in the academic literature (e.g., [64,65,66,67]) tourism in general or the main tourism in the region is used as a dependent variable, indistinctly or alternatively. Regarding the acceptance of nightlife, it only has a positive and significant relationship with the acceptance of sun and beach tourism, but not with general attitudes. This relationship is the main contribution of the exploratory analysis, since it indicates that nightlife is a complementary offer to the main tourism and has no potential as an independent offer in the eyes of residents.

In essence the results show that there is a sequence that begins with the formation of the overall attitude towards tourism based on the perception of residents on some types of impacts, mainly economic benefits and cultural costs, and continues with the decision whether or not to accept specific types of tourism. The majority of tourism in coastal destinations is that of sun and beach and based on the sample analyzed, has an important relationship with the overall attitude of the local residents: the more favorable the overall attitude towards tourism, the greater the acceptance of sun and beach tourism. In the case of the nightlife offer, only the acceptance of sun and beach tourism has significant effects and this suggests the subordination of nightlife to sun and beach tourism. It therefore seems plausible to consider nightclubs and pubs as a complementary offer to the beaches and water activities of coastal destinations. It is not possible to consider nightlife as an independent offer. In addition, it should be noted that the interrelationship between the two offers has increased in recent times with beach clubs (beach establishments with similar musical offer to nightclubs and pubs) and beach-front hotels with shows, events or nightclubs as part of their offer.

6. Conclusions

Nightlife causes great concern due to its possible social impacts on the local community however its management is poorly studied, especially in the context of tourist destinations. This paper sought to explore which position nightlife would occupy within the causal models of residents’ attitudes and has determined that it should be considered a consequence of the attitudes towards the main tourism of the destination, which in the case of coastal destinations is usually sun and beach tourism. Therefore, although the media impact of nightlife is greater than that of beaches, nightclubs and pubs complete the offer of beaches and should not be taken into account out of this context.

This implies that business projects and innovations in the nightlife sector of coastal regions must be considered as part of a more complex holiday product in which the beaches and the activities offered on the beaches are present. Therefore, the nightlife offer cannot be separated from the sun and beach offer, creating a night and day cycle for the tourist. The symbiosis between the two offers reaches its maximum expression in the case of beach clubs by bringing nightlife to the beach.

Tourist entrepreneurs should consider interaction with clients, residents and workers. Residents constantly interact with the tourist product one way or another, favoring or harming its development. Therefore, it is important to take this interaction into account as it affects customer satisfaction of the tourist product offered. The findings in this investigation highlight that residents are reluctant to certain business models (such as that related to nightlife). Entrepreneurs of nightlife tourism products should complement this offer with others or establish strategic synergies with other entrepreneurs, who are directly or indirectly related to the tourism sector.

It should be noted that as an exploratory investigation, this work needs to be undertaken in other coastal tourist destinations to confirm the results to conclude if they are generalized. The conclusions apply strictly to sun and beach destinations. The nightlife offer in large cities has multiple characteristics that differ from the nightlife of coastal tourist destinations and needs to be studied as a different sector and possibly not linked to tourist activity. It would also be necessary to test the model with other variables (e.g., attachment, economic dependence on tourism, etc.). Special measurement scales should be created and applied to this type of offer. It should also be noted that they are typical problems encountered in a field of study (the management of nightlife) which does not yet have very extensive literature.

Regarding the limitations of the work carried out, the main one is that it is an analysis with data from a case study and different results could be obtained in other case studies. On the other hand, the PLS-SEM technique has limitations derived from statistical analyses based on surveys when determining causal relationships, since it only determines the existence or not of significant correlations but does not confirm the existence of a causal relationship with total guarantee.