Motivation, Satisfaction and Recommendation Behaviour Model in a Touristic Coastal Destination—Pre and During the COVID-19 Pandemic Compared

Abstract

The growth of tourism in coastal destinations has attracted academic attention due to the link between tourists’ motivations and their likelihood of recommending the destination. This study explores changes in tourist motivations, satisfaction, and recommendation behaviours in a coastal destination during the summers of 2019 (pre-COVID-19) and 2020 (during the pandemic). Employing quantitative analysis with Confirmatory Factor Analysis and Structural Equation Modelling, data from 394 pre-pandemic and 468 pandemic-period visitors were analysed. The findings reveal a shift in the tourist profile during the pandemic, with a predominance of younger visitors from nearby regions. Despite heightened uncertainty, satisfaction and the intention to recommend remained relatively high, albeit lower than pre-pandemic levels. The study underscores the importance of adapting marketing and management strategies to evolving tourist preferences, emphasising safety and sustainability in response to global crises. These results highlight the need for resilient policies to ensure positive visitor experiences and long-term growth in coastal tourism, contributing to the broader understanding of how external disruptions impact destination dynamics and tourist behaviour.

1. Introduction

Tourism is a key driver of sustainable development in many regions; however, it remains highly vulnerable to health crises and natural disasters, including those of relatively small scale [1,2]. Studies highlight how events such as terrorism, earthquakes, floods, and pandemics significantly impact the sector, creating uncertainty in markets [3,4]. The COVID-19 pandemic reconfigured the perception of these crises, prioritising protection and resilience in tourist destinations [5,6].

In response to these challenges, current strategies focus on strengthening response and recovery capacities to mitigate future disasters [7,8]. These efforts include improvements in infrastructure, the involvement of local communities, and a proactive approach to prevention [9,10]. Furthermore, the pandemic underscored the importance of understanding tourist behaviour during crises and identifying the most vulnerable sectors [11]. Effective information management is essential to developing mitigation strategies and accelerating recovery. Cases such as the attacks in Paris and earthquakes in Japan illustrate the importance of reliable information and agile response plans in restoring traveller confidence and revitalising local economies [12,13]. Meanwhile, tourist satisfaction has been extensively studied, particularly in relation to the intention to recommend a destination [14,15,16] and the likelihood of returning in the future [17,18,19]. Motivations vary among tourists and studies, typically distinguished as internal (“push”, such as relaxation) [20,21] and external (“pull”, such as the destination’s attractions) [22,23].

The aim of this study is twofold. Firstly, it seeks to identify the influence of tourist motivations on destination satisfaction and its effect on the intention to recommend the destination. Secondly, it aims to compare these effects across two time periods: one prior to the COVID-19 pandemic (summer 2019) and another during the pandemic (summer 2020), specifically a few months after the pandemic was officially declared. This study focuses on Platja d’Aro, a coastal tourist destination located on the Costa Brava in the northeast of Spain. The research adopts a quantitative methodology, employing Multiple Group Structural Equation Modelling (MGSEM) to compare the two periods of interest (2019, pre-pandemic, and 2020, during the pandemic) and to analyse the relationship among motivation, satisfaction, and recommendation. Data were collected through surveys conducted in 2019 (pre-pandemic) and 2020 (during the pandemic), with a total of 862 respondents.

The article is structured as follows: first, the theoretical framework on tourist motivation, satisfaction, and recommendation is presented, alongside the presentation of the estimated model and relevant COVID-19 pandemic studies. This is followed by an explanation of the survey design, sampling methods, and analytical approach. Results are then presented and compared between the pre-COVID-19 and pandemic periods. Finally, the conclusions and implications are discussed.

2. Literature Review

The travel restrictions and public health measures imposed by the pandemic led to a historic decline in global tourism demand, severely impacting destinations dependent on this sector and exposing their lack of preparedness [24]. Mobility restrictions redirected tourist flows to perceived “safe” areas, such as coastal destinations that leveraged open spaces to attract visitors [25,26]. Understanding tourist motivations, both internal and external, became crucial, particularly as safety and health emerged as key factors [27,28]. Satisfaction, linked to the quality of the experience and the fulfilment of expectations, significantly influences loyalty and destination recommendations, particularly in coastal settings. It has become an essential element for post-pandemic economic recovery and the sustainable development of tourism [29,30].

Based on previous literature, this study proposes the following general hypotheses:

H1. 

There is a significant positive relationship between tourists’ motivations to visit Platja d’Aro and their level of satisfaction with the tourist experience.

H2. 

There is a significant positive relationship between the satisfaction of tourists in Platja d’Aro and their willingness to recommend the destination to friends and family.

2.1. COVID-19 and Tourism

The COVID-19 pandemic triggered an unprecedented crisis across various aspects of global society, with the tourism sector being one of the most severely impacted [31]. One of the primary effects of the pandemic was the suspension of international mobility due to government restrictions [32]. This disproportionately affected destinations dependent on international tourism, particularly those focused on mass tourism, such as beaches, islands, and urban centres [7,33]. The crisis exposed the limited resilience of the sector and the inadequacy of recovery plans, leading to reactive and unsustainable strategies [10].

In this context, the pandemic altered tourists’ perceptions and behaviours, leading them to prioritise destinations with stronger healthcare infrastructure and more rigorous hygiene protocols [32,34]. The perception of health risks became a decisive factor in destination selection. Consequently, new demands emerged, focusing on less crowded destinations, with greater proximity to nature and an emphasis on sustainability [35].

Governments, in turn, responded by promoting public–private collaborations to facilitate recovery and adaptation to new demands [5,6]. In Macao, for example, these alliances supported product innovation and financial assistance [36], while in Japan, trust in governance increased visitor loyalty and destination recommendations [18]. The pandemic accelerated the growth of Smart Tourist Destinations (STDs) to rebuild tourist confidence. Digital tools such as health certificates and real-time visitor flow management became critical, along with social media platforms used to maintain engagement and promote safety [37].

2.2. Motivation

Motivation is a fundamental element in a tourist’s decision-making process when choosing a destination and is therefore a key topic in tourism research, as it plays a crucial role in understanding tourist behaviour and improving satisfaction [27]. There is a widespread idea that motivation is defined as a set of forces that stimulate individual behaviour to satisfy needs and wants through different appropriate activities [38], which arise from an inconsistency between a desired and an existing condition [39]. Since motivation is one of the main indicators of tourists’ behaviour which influences their preferences and expectations, its study allows the identification of the reasons why travellers engage in tourism activities [40]. According to Correia et al. [41], tourist motivation is a multidimensional phenomenon driven by the search for unique experiences, the need for rest and detachment from daily routine, interest in exploring new destinations, and curiosity about discovering other cultures. It is commonly accepted that tourists’ travel motivations are relevant not only because they influence certain behaviours but also because they provide criteria by which tourists evaluate their experience at the destination [42].

The push–pull concept has been one of the most widely used approaches to explain tourists’ motivations [5,20,43], satisfaction [44], and destination choice [45,46]. This concept particularly suggests that push factors refer to internal elements (intrinsic motivators), which are related to the decision to travel [47,48], while pull factors (destination attributes) are characteristics of the destination that attract travellers to choose a particular destination [38].

In the case of coastal destinations, Orams and Lück [49] state that recreational motivation of tourist in coastal areas is continuously growing, making them particularly interesting for research. For Yoon and Uysal [50], there are “push” motivational factors, understood as internal forces related to tourists’ desires, such as relaxation, achievement, family togetherness, and safety/fun. In contrast, previous studies have identified “attraction” motivational factors, referring to external forces linked to destination attributes, including destination size, reliable (pleasant) climate, cleanliness, shopping, nightlife, and local cuisine. In this sense, Koutra and Karyopouli [51] suggested that the geographical and climatological characteristics of a destination such as climate, sun, or sea are relevant in tourist motivation, and hence seasonality has a high incidence on visits during specific time periods.

In addition to these general motivations, tourists often feel attracted by external “pull” factors such as natural resources—including beaches, biodiversity, or scenic landscapes—and cultural heritage, both tangible (e.g., monuments, traditional architecture) [48] and intangible (e.g., local festivities, culinary traditions) [52]. These destination attributes shape how tourists perceive attractiveness, as marketing strategies and collective imaginaries frequently highlight their symbolic and visual appeal.

At the same time, internal “push” factors influence tourist behaviour, regardless of the specific features of a destination [28]. For instance, many tourists choose to travel based on personal passions such as gastronomy [35], cultural learning [53], ecotourism [54], or participation in traditional local celebrations [55]. These motivations foster a stronger connection with the travel experience and lead individuals to seek destinations whose environmental or cultural characteristics reflect their lifestyles and cultural preferences [20,28,56]. This distinction helps explain why tourists tend to choose destinations that match both their expectations and their personal interests.

Previous studies suggest that motivations—both internal (push) and external (pull)—can significantly influence tourist satisfaction when expectations are met [20,41,43]. In line with this, we propose the following specific hypotheses:

H1a 

Prior to the COVID-19 pandemic, tourists’ motivations to visit Platja d’Aro had a positive relationship with their overall satisfaction during the stay.

H1b. 

During the COVID-19 pandemic, despite travel restrictions and health concerns, there was a positive relationship between tourists’ motivations and their satisfaction with the experience in Platja d’Aro.

2.3. Satisfaction

Satisfaction is fundamental in tourism planning as it influences destination choice, product consumption, loyalty, and the intention to recommend [50]. This multidimensional construct reflects visitors’ subjective evaluation, influenced by emotional, cognitive, and contextual factors [52]. Regalado-Pezúa et al. [53] describe satisfaction as an emotional response resulting from the comparison between tourists’ prior expectations and their lived experience, encompassing both tangible and intangible aspects. Therefore, understanding tourist satisfaction is a key parameter for assessing the performance of destination products and services [38].

Perceived value is one of the main determinants of satisfaction, as it contributes significantly to the construction of the tourism image. This value is conceptualised as a combination of emotional, functional, economic, and social benefits associated with the tourist experience [57]. In coastal destinations, factors such as the conservation of the natural environment, the quality of infrastructure, and staff attention have a significant impact on visitor satisfaction [58]. When the attributes of a destination meet tourists’ needs and desires, a pleasant experience is created, fostering intentions to recommend and revisit the destination [59]. This understanding of satisfaction can be further expanded by drawing on John Urry’s concept of the tourist gaze, which emphasises that tourist experiences are also shaped by culturally constructed visual and symbolic expectations [60]. Tourists bring with them shared imaginaries and aesthetic frameworks that influence how they perceive, interpret, and evaluate a destination [16]. In this sense, tourist satisfaction can stem as much from the symbolic resonance of a place as from the fulfilment of practical expectations [15]. This occurs particularly when the experience reflects the cultural narratives and aesthetic values that shape the visitor’s gaze [61]. Thus, motivations linked to heritage, landscape, or relaxation may generate greater satisfaction when they align with such imagined meanings.

Satisfaction also plays a mediating role in the construction of a destination image, which integrates cognitive and affective dimensions [62]. The cognitive dimension is associated with knowledge and beliefs about the destination, while the affective dimension reflects the emotions and feelings it evokes [53]. Additionally, trust in the destination is a critical factor that strengthens satisfaction and loyalty. This trust is built upon perceptions of safety, service quality, and the authenticity of the tourism experiences offered [57,58]. This element is positively correlated with tourist satisfaction, making it a key indicator for assessing the quality and attributes of a destination [35].

Furthermore, recent studies have demonstrated that marketing strategies that integrate specific attributes and the authenticity of each destination—such as its natural, cultural, and recreational offerings, alongside service availability—significantly influence perceptions of satisfaction [46,63]. Wang et al. [64] assert that tourists tend to choose destinations that optimally meet their needs and offer differentiated benefits. Satisfaction levels are based on expectations that, in turn, shape tourists’ motivations [56]. When these expectations are met, tourists are likely to consider their experience satisfactory and exhibit stronger intentions to return [65]. Finally, in determining a tourist’s level of satisfaction, a comparison is made between the quality of the visited attraction and the motivation behind the trip [59].

2.4. Recommendation

Recommendations play a crucial role in the development of the tourism industry [54]. Within the context of coastal tourism, the behavioural intentions of visitors, manifested in the likelihood of revisiting a destination or recommending it to others, stand as key indicators of customer loyalty in the sector [17]. These intentions can be influenced by various factors, including the perceived attractiveness of the destination, perceived quality, motivations, and visitor satisfaction [38,57]. According to Carvache-Franco et al. [59], motivations related to “escape and novelty” are significant predictors for recommendation in coastal tourist destinations.

In this context, segmenting tourists based on their motivations reveals a variety of interests, such as learning and experiencing coastal life, enjoying nature, and participating in water sports, all of which influence satisfaction and loyalty towards the destination [66]. This implies that a segmented approach in tourism management can be effective in meeting the specific needs of different tourist groups and achieving higher levels of satisfaction [35,62]. Consequently, a satisfactory experience at a tourist destination not only improves the image and quality of service but also leads to positive future behaviour, such as a greater willingness to recommend the destination to others [38,67].

Another essential aspect of recommending coastal destinations is the perception of the destination’s image and its relationship with tourist loyalty. Carvache-Franco et al. [66] note that factors such as “Personal Attention” and “Tourist Infrastructure” are essential in forming a positive image and fostering loyalty towards the destination. While the perception of a destination’s image is often measured in either objective or subjective terms, it constitutes a multidimensional construct that encompasses various factors, from brand creation to the types of products, services, interactions with local populations, and activities offered at the destinations [52,68].

In relation to the destination’s image, it is essential to consider the influence of tourists’ perceptions of environmental impact and the management of tourist overload, as environmentally responsible behaviour among tourists in coastal destinations is increasingly relevant [46]. Panwanitdumrong and Chen [69] highlight that the implementation of sustainable practices, especially in coastal destinations, is key not only to prevent and mitigate environmental problems such as marine litter but also to enhance the destination’s image and the intention to recommend it. This means that the perceived adaptation of the destination to the challenges of mass tourism is also essential for maintaining the quality of the tourist experience and promoting positive recommendations [16,70,71].

This becomes especially relevant as it is essential to consider how tourists perceive not only environmental initiatives but also the broader social and economic efforts under-taken by the destination. While environmental management contributes significantly to the perceived responsibility of the destination [46,72], recent studies suggest that social equity and economic resilience are also critical elements shaping post-pandemic image perceptions in coastal contexts [24,73].

Tourists increasingly value destinations that demonstrate commitment to improving local well-being, supporting small-scale businesses, and promoting inclusive tourism practices [23,26,74]. In Mediterranean and southern European regions, where seasonality and over-dependence on low-cost mass tourism persist, the failure to address these dimensions may negatively affect the perceived authenticity, responsibility, and quality of the destination experience [11,33,70]. Therefore, projecting a sustainable destination image in the post-COVID era requires integrating environmental, social, and economic narratives that reflect systemic adaptations rather than superficial rebranding.

The literature shows that satisfaction plays a key role in shaping tourists’ behavioural intentions, particularly their willingness to recommend a destination [15,50,66]. Accordingly, we propose the following specific hypotheses:

H2a. 

Prior to the COVID-19 pandemic, the level of satisfaction of tourists with their visit to Platja d’Aro directly influenced their likelihood of recommending the destination to friends and family.

H2b. 

During the COVID-19 pandemic, despite the restrictions and changes in the tourist experience, visitor satisfaction continued to be a key predictor of their willingness to recommend Platja d’Aro.

2.5. Relationship Among Tourist Motivation, Satisfaction and Recommendation

An important research interest in tourism is understanding the reasons why tourists travel to a certain destination, what are their needs to fulfil during their stay, and its relationship with their satisfaction [28,54]. This relationship has been widely studied; however, contradictory results are still found in the literature [23,66,75,76]. The success of destination marketing is mainly based on identifying the relationship between tourist motivation, satisfaction, and recommendation in a touristic context [65]. Satisfaction has been shown to have a positive influence on tourist loyalty and subsequent recommendation of the destination [20]. For several authors, people travel because they are “pushed” to make travel decisions based on their interests and “attracted” by destination attributes [21,22,48]. Thus, satisfaction derived from tourists’ motivation to travel contributes to destination recommendation [77].

Within this framework, tourist satisfaction can be interpreted as the result of the extent to which initial motivations are fulfilled during the actual travel experience [28]. A strong alignment between what tourists seek (push and pull motives) and what the destination delivers contributes to a more positive evaluation of the overall tourist experience [21,63]. Thus, motivation acts as a psychological precursor to satisfaction, shaping expectations that influence how tourists perceive and assess their visit [15,56].

Tourist satisfaction is a key indicator of the likelihood of recommending a destination, as a positive experience encourages other travellers to visit [78]. Conversely, dissatisfaction reduces this likelihood and negatively affects destination choice [19,64]. This underscores the causal relationship between recommendation, motivation, and satisfaction, where satisfied tourists are more inclined to recommend the destination [38,53].

The relationship between motivation and satisfaction has been examined through various frameworks. Push and pull factors are a common classification [44,79,80], while other studies focus on individual motivations [5,14,16,45]. Albayrak and Caber [20] propose three perspectives: (1) motivation as the sole determinant of satisfaction, highlighting factors such as escape and cultural interest [81,82]; (2) motivation combined with additional variables, such as destination image, which indirectly influences satisfaction [14,83]; and (3) employing motivational factors to assess satisfaction at the attribute level, with elements like relaxation, attractiveness, and socialising having a significant impact [28,84].

Destination quality, including attributes, activities, and services, is also a strong predictor of satisfaction and loyalty [55]. High satisfaction fosters loyalty, recommendations, and repeat visits, underscoring its importance in shaping tourists’ positive intentions [19,64]. According to Ferreira da Silva et al. [85], previous and on-site experience directly influences the cognitive image of the destination, affecting attributes such as scenic beauty, gastronomy, and natural heritage, while the affective image shows less variability among groups. Visitors with greater experience have a more favourable perception of the destination and a higher intention to recommend and return, confirming the positive relationship between familiarity, destination perception, and loyalty [86,87].

Tourist recommendations are regarded as significant sources of information that allow potential visitors to evaluate the attributes and quality of a tourist destination. In this context, Prayag et al. [15] methodologically employed Structural Equation Modelling (SEM) to conclude that there is an interdependent relationship between the perception of the destination’s image and tourist satisfaction. They also found a relationship between the destination’s image and its loyalty, which directly affects the intention to recommend that destination. Similarly, Huang et al. [14] used a structural equation model to investigate how motivation, satisfaction, and perceived value affect tourist recommendations, finding that both perceived value and satisfaction have a significant influence on recommendations. Santoso [88] explored the theoretical and empirical connections between the destination image, tourist motivation, satisfaction, and the intention to visit using Structural Equation Modelling analysis. The results concluded that the quality, value, and satisfaction with the destination have a direct and positive impact on the intention to recommend a visit.

The Figure 1 presents the conceptual model that underpins this study. It summarises the hypothesised relationships among tourist motivation, satisfaction, and the intention to recommend the destination. In this model, satisfaction is treated as a latent construct, measured by two indicators: perceived fulfilment of expectations and overall satisfaction with the decision. The model reflects both pre-pandemic and pandemic contexts, as detailed in specific hypotheses H1a, H1b, H2a, and H2b. The squares in the model represent observed indicators, the circle denotes the latent construct (tourist satisfaction), and the random measurement error for each observed variable is represented by e_i.

3. Materials and Methods

This section presents the study area along with the main tourism indicators of the destination. Methodologically, it explains the questionnaire design and the operationalisation of the questions. It also outlines the sampling strategy, data collection process, and method of analysis.

3.1. Tourist Destination

Platja d’Aro is a municipality located in the Baix Empordà region of Catalonia, along the Costa Brava, approximately 30 km from Girona and 100 km from Barcelona. Its strategic location and excellent connectivity via road networks and public transport make it an attractive year-round destination for leisure and cultural tourism [89].

Demographically, the municipality’s population has grown significantly, increasing from 5785 inhabitants in 1998 to 12,773 in 2024 [89]. Additionally, the full-time equivalent annual seasonal population reaches 9328 inhabitants, 73% higher than the resident population (ETCA population/resident population), highlighting the region’s strong dependence on tourism [89].

Tourism is a major economic driver, supporting local employment and business activity. Events like “La Santa Market” attract hundreds of thousands of visitors, with the 2024 edition generating EUR 31.8 million in economic impact [90]. Furthermore, the destination holds cultural significance, with the Castell de Benedormiens standing out as an important historical monument that underscores the area’s heritage, in contrast to the modern coastal resorts [90]. Platja d’Aro boasts a diverse tourism infrastructure, including 32 hotels with 5111 beds, 5 campsites with a capacity for 10,422 campers, and 1 rural tourism establishment with 9 beds, expanding its offerings to nature tourism and rural getaways [89].

The selection of Platja d’Aro as a case study is based not only on its representativeness as a Mediterranean coastal destination but also on specific governance and planning dynamics that enrich the analysis. While traditionally linked to sun-and-beach tourism, local authorities have sought to reduce seasonality by promoting cultural events and retail-oriented activities during the low season. In addition, the high presence of second homes makes it a valuable setting to understand the relationship between residential tourism and destination loyalty.

During the pandemic, a temporary change was introduced in the main commercial street (Avinguda de S’Agaró), which was closed to car traffic in order to increase safety and allow for better social distancing. This measure was supported by some stakeholders but also generated disagreement among others, especially tourism service providers who considered that it affected accessibility and reduced visitor numbers. These elements—diversification strategies, residential dynamics, and local policy decisions during the pandemic—make Platja d’Aro a relevant case for studying changes in tourist behaviour and the role of destination management in times of crisis.

3.2. Questionnaire Design and Operationalisation

The questionnaire was developed collaboratively by the research team and the Municipality of Castell-Platja d’Aro. It was administered in Spanish, English, and French to accommodate the linguistic needs of both domestic and international visitors. The instrument included questions across several dimensions: socio-demographic characteristics (e.g., gender, age, country of origin), travel behaviour (e.g., accommodation, length of stay, means of transport), tourist expenditure, familiarity with the destination, sources of information, perceptions, motivations, satisfaction, and recommendation.

To assess tourist motivation, a set of 14 items was initially included, derived from the push–pull theoretical framework widely used in tourism research [20,21,38]. This approach distinguishes internal drivers (push factors), such as the desire for relaxation or adventure, from external attractions (pull factors), such as beaches or cultural offerings. Tourists were asked to rate the importance of each motive using a 5-point Likert scale (1 = not important at all; 5 = very important). Based on conceptual relevance and empirical performance, ten motivations were retained for modelling purposes: (1) to enjoy sun and beach [23], (2) to do water activities [67], (3) to do sport activities (e.g., hiking, cycling) [91], (4) to enjoy gastronomy [35], (5) to discover new places [70], (6) to explore historical and cultural heritage [52], (7) to enjoy shopping facilities [21], (8) to find good value for money [53], (9) to enjoy nature [57], and (10) to rest and relax [62].

Tourist satisfaction was assessed through two indicators: “The place satisfies my expectations” and “I am pleased with my decision,” both measured on a 5-point Likert scale (1 = strongly disagree; 5 = strongly agree). Recommendation was measured using the question “To what extent will you recommend this destination to your friends and relatives?” on an 11-point Likert scale ranging from 0 (not recommended) to 10 (highly recommended). These constructs were used in the structural equation model to analyse the relationships between motivations, satisfaction, and recommendation.

The questionnaire’s content was reviewed by academic experts and municipal tourism professionals to ensure its conceptual clarity, relevance, and suitability for the study context. A pre-test was conducted with a small sample to validate question comprehension and technical functionality prior to the full deployment of the instrument.

3.3. Sampling and Data Collection

Data collection was carried out in person during the peak tourist seasons of August 2019 and July–August 2020, allowing for the comparison of visitor behaviour before and during the COVID-19 pandemic. Surveys were administered across different days of the week, including both weekdays and weekends, and at various times of day to ensure temporal diversity and enhance representativeness. Fieldwork took place in three strategically selected areas with high tourist concentration (see Figure 2): the Passeig Marítim (seafront promenade), the Eix Comercial (main commercial axis), and the Parc d’Aro (a prominent leisure and shopping centre).

Interviewers were trained to identify potential tourists in situ, explain the purpose of the study, and request their voluntary participation. Verbal informed consent was obtained prior to the administration of the questionnaire. The final sample comprised 862 valid responses: 394 collected in 2019 and 468 in 2020. The consistency of the sampling strategy, locations, and timeframes across both years ensures the comparability of data and enhances the robustness of the subsequent analyses.

3.4. Method

As two years of comparison are involved, the primary method of analysis was Multiple Group Structural Equation Modelling (MGSEM) [92,93,94,95,96]. This technique allows for the evaluation of the latent construct of satisfaction and its relationship with recommendation, as well as the effect of each type of motivation on tourist satisfaction in 2019 (pre-COVID-19) and 2020 (during COVID-19). When comparison among groups is of interest for a latent variable, satisfaction construct in this study, measurement invariance among the groups should be established. In this article, metric invariance, which requires equal factor loadings across groups, was analysed. If invariance holds, the relationships among variables can be meaningfully compared [96]. Mplus 7 [97] was used for these analyses.

Multiple Group Confirmatory Factor Analysis [92,94,95,96] is commonly employed in cross-cultural comparisons to test whether a latent variable of interest is comparable across groups, countries, and/or time periods, while accounting for measurement invariance. If invariance is confirmed, both relationships and latent means of the constructs can be compared across groups (countries and/or time periods).

4. Results

This section first describes the sample profile, followed by the pre-pandemic and during-pandemic model, that conceptualise the relationships between motivation, satisfaction, and recommendation. The model highlights how these dynamics shifted over time, offering a basis for comparing the two periods and understanding the changes resulting from the pandemic.

4.1. Sample Description

Table 1. Characteristics of the sample profile.

	2019 (n = 394)	(%)	2020 (n = 468)	(%)
Gender
Man	190	48.2	255	54.5
Woman	204	51.8	213	45.5
Total	394	100.0	468	100.0
Age
24 or less	53	13.9	119	25.6
25–34 years	74	19.5	95	20.5
35–44 years	99	26.1	92	19.8
45–54 years	92	24.2	82	17.7
55–64 years	39	10.3	46	9.9
65 and over	23	6.1	30	9.5
Total	380	100.0	464	100.0
Min	16		16
Max	80		81
Average	41		38.1
SD	13.5		15.4
Origin
Catalonia	169	43.4	262	57.7
France	86	22.1	72	15.9
Rest of Spain	30	7.7	37	8.1
Netherlands	30	7.7	22	4.8
UK	16	4.1	11	2.2
Belgium	14	3.6	12	2.6
Germany	11	2.8	12	2.6
Russia	10	2.6	15	3.3
Rest of Europe	11	2.8	20	2.2
Rest of the world	12	3.1	2	0.4
Total	389	100.0	454	100.0

shows the distribution of the sample profile for the pre-COVID-19 pandemic and during COVID-19 at the destination and their demographic characteristics. The data show a similar proportion of men and women in 2019, with an increase in the proportion of men in 2020. The mean age in 2019 was 41.0 (sd = 13.5), while in 2020 it was 38.1 (sd = 15.4), indicating that visitors were, on average, younger during the pandemic year. The proportion of visitors aged 34 or under increased during the pandemic (46.1%) compared to the pre-pandemic period (33.4%).

Tourists were mainly from the region of Catalonia, especially during 2020, due to worldwide restrictions caused by the COVID-19 pandemic. They were followed by French tourists, due to proximity, and tourists from the rest of Spain. As expected, the traditional tourism markets for the destination, such as The Netherlands, UK, Belgium, and Germany, reduced their proportion in the total of visitors. In summary, during the pandemic period, tourists at the destination were younger and travelled from nearer locations than those in 2019.

Table 2. Selected characteristics of the sample profile.

	Factor	2019	2020
Motivations
1. To enjoy sun and beach	Pull	93.6%	86.6%
2. To do water activities	Push	58.8%	76.2%
3. To do sport activities	Push	48.6%	62.8%
4. To enjoy gastronomy	Push	48.8%	74.5%
5. To discover new places	Push	44.5%	72.3%
6. To explore heritage	Push	35.5%	67.2%
7. Good value for money	Pull	34.5%	76.8%
8. To take a rest and relax	Push	73.9%	80.6%
9. To enjoy nature	Push	63.4%	74.7%
10. To enjoy shopping	Push	50.4%	70.4%
Satisfaction
I am pleased with my decision		4.51	4.04
The place satisfies my expectations		4.61	4.07
Recommendation
Recommendation to friends and relatives		8.48	7.80

presents the variables used to estimate the structural model: tourist motivations (push and pull), satisfaction, and recommendation to friends and family. The table compares the percentage of agreement with each motivation in 2019 and 2020, alongside mean values for satisfaction (measured on a 5-point Likert scale) and recommendation (on a 0–10 scale).

The descriptive results indicate that both satisfaction and recommendation remained high in the two periods, though slightly decreased during the pandemic. However, the most notable differences were observed in motivations. In 2020, visitors reported higher levels of agreement across nearly all motivation categories, particularly those related to nature (from 63.4% to 74.7%), relaxation (from 73.9% to 80.6%), and value for money (from 34.5% to 76.8%). Motivations associated with exploration (e.g., discovering new places, heritage, gastronomy) also saw sharp increases, suggesting that visitors in 2020 approached the destination with more specific and varied intentions.

4.2. Pre-COVID-19 Pandemic and Pandemic Models’ Comparison

Table 3. Fit measures.

	χ2	df.	P	CFI	TLI	RMSEA	SRMR
Metric Invariance
Model 1. To enjoy sun and beach	7.700	6	0.261	0.996	0.992	0.026 (CI 90%: 0.000, 0.071)	0.024
Model 2. To do water activities	20.521	6	0.002	0.969	0.938	0.075 (CI 90%: 0.041, 0.104)	0.034
Model 3. To do sport activities	18.107	6	0.006	0.975	0.950	0.068 (CI 90%: 0.034, 0.106)	0.036
Model 4. To enjoy gastronomy	9.046	6	0.171	0.993	0.987	0.034 (CI 90%: 0.000, 0.058)	0.031
Model 5. To discover new places	9.815	6	0.133	0.992	0.983	0.038 (CI 90%: 0.000, 0.080)	0.032
Model 6. To explore heritage	13.428	6	0.037	0.984	0.968	0.054 (CI 90%: 0.013, 0.093)	0.031
Model 7. Good value for money	11.747	6	0.068	0.988	0.976	0.047 (CI 90%: 0.000, 0.087)	0.036
Model 8. To take a rest and relax	5.597	6	0.470	0.999	0.999	0.000 (CI 90%: 0.000, 0.060)	0.002
Model 9. To enjoy nature	6.876	6	0.332	0.998	0.996	0.018 (CI 90%: 0.000, 0.067)	0.021
Model 10. To enjoy shopping	11.199	6	0.082	0.989	0.978	0.045 (CI 90%: 0.000, 0.085)	0.028

shows the fit measures for the model from Figure 1, for the different motivations. The Maximum Likelihood Robust (MLR) estimator was used for each model.

The following goodness-of-fit measures were applied for the model fit: standardised root mean square residual (SRMR), and root mean square error of approximation (RMSEA). SRMR values of 0.08 or lower [98], and RMSEA values of 0.06 or lower, indicate acceptable fit [99]. The comparative fit index (CFI) and Tucker–Lewis index (TLI) are incremental fit indices used to calculate improvements over competing models. Values above 0.90 for both indices indicate acceptable model fit [98]. Therefore, the estimated models demonstrate acceptable fit. Moreover, metric measurement invariance [96] for the latent variable “satisfaction” was confirmed, which means that the relationships can be interpreted across the pre-COVID and pandemic periods.

Results of the structural model relationships in Figure 1 are shown in

Table 4. (a,b). Unstandardised coefficients of the model.

(a) Motivation → Satisfaction (Hypothesis H1)
	2019 (H1a)	2020 (H1b)	Sig. Effect
Model 1. To enjoy sun and beach	0.323 **	0.502 ***	2019 and 2020
Model 2. To do water activities	0.281 ***	0.139	2019
Model 3. To do sport activities	0.062	0.341 ***	2020
Model 4. To enjoy gastronomy	0.068	0.174	-
Model 5. To discover new places	0.156 **	0.180	2019
Model 6. To explore heritage	0.103	0.160	-
Model 7. Good value for money	0.377 ***	0.207	2019
Model 8. To take a rest and relax	0.256 **	0.261 *	2019 and 2020
Model 9. To enjoy nature	0.175 **	0.395 ***	2019 and 2020
Model 10. To enjoy shopping	0.182 **	0.362 ***	2019 and 2020
(b) Satisfaction→recommendation (Hypothesis H2)
	2019 (H2a)	2020 (H2b)	Sig. Effect
Model 1. To enjoy sun and beach	1.100 ***	0.873 ***	2019 and 2020
Model 2. To do water activities	1.103 ***	0.846 ***	2019 and 2020
Model 3. To do sport activities	1.105 ***	0.860 ***	2019 and 2020
Model 4. To enjoy gastronomy	1.106 ***	0.869 ***	2019 and 2020
Model 5. To discover new places	1.106 ***	0.860 ***	2019 and 2020
Model 6. To explore heritage	1.104 ***	0.860 ***	2019 and 2020
Model 7. Good value for money	1.109 ***	0.850 ***	2019 and 2020
Model 8. To take a rest and relax	1.101 ***	0.864 ***	2019 and 2020
Model 9. To enjoy nature	1.101 ***	0.869 ***	2019 and 2020
Model 10. To enjoy shopping	1.099 ***	0.859 ***	2019 and 2020

*** p < 0.001; ** p < 0.01; * p < 0.05.

. Relations between motivation and tourist satisfaction (Table 4a)—which corresponds to specific hypotheses H1a and H1b—and between satisfaction and recommendations (Table 4b)—which corresponds to specific hypotheses H2a and H2b—are shown previously and during the COVID-19 period.

The relationships between motivations and tourist satisfaction (H1a and H1b) vary depending on the motivation type and the period analysed. In any case, motivations with statistically significant effects on satisfaction exhibit positive relationships. Specifically, gastronomy and cultural heritage exploration were not statistically significant in either period, indicating that these motivations had no measurable effect on satisfaction before or during the pandemic.

Motivations concerning water activities, discovering new places, and good value for money had a statistically significant effect on tourist satisfaction only in the pre-pandemic period. However, during the COVID-19 period, these motivations did not significant effect on the level of tourist satisfaction. In contrast, sport activities had a statistically significant effect on satisfaction only during the summer of 2020.

Four motivations—sun and beach, relaxation, nature, and shopping—had a statistically significant effect on satisfaction in both periods. When comparing the strength of these effects using unstandardised estimates, the results clearly show that the effects were stronger in 2020, the pandemic period.

Regarding the relationship between satisfaction and recommendation (H2a and H2b), a positive and statistically significant effect was observed for both 2019 and 2020. This suggests that the more satisfied tourists were, the more likely they were to recommend the destination to friends and family. These effects were stronger in 2019, before the pandemic.

In summary, the statistically significant effects of motivations on satisfaction were greater in 2020, while the effects of satisfaction on recommendation were stronger in 2019. This implies that motivation became a more decisive factor for satisfaction during the pandemic, highlighting a shift in the internal dynamics of tourist behaviour across the two periods.

5. Discussions and Conclusions

The analysis of tourists’ motivations and satisfaction in Platja d’Aro before and during the pandemic revealed changes in the relationship between internal and external factors influencing their decisions. Before the pandemic, tourists prioritised recreational and cultural experiences, whereas during the pandemic, they placed greater emphasis on safety and personal well-being, reshaping their motivational dynamics and their connection to the tourism experience. Despite the shift in motivations, the fundamental link between satisfaction and the intention to recommend remained strong, albeit slightly weakened by the heightened perception of risk. This behaviour aligns with the “push and pull” theory, which highlights how internal factors (such as the desire for relaxation) and external factors (such as destination attractions) interact to shape the tourism experience, even in contexts of uncertainty [21].

This motivational shift should be interpreted not solely as a reaction to mobility restrictions or health concerns but as part of a broader reconfiguration of tourist behaviour shaped by contextual and demographic transformations, but also as the outcome of a demographic transformation in the visitor profile [5,32]. The predominance of younger and domestic tourists brought forward a set of motivations more closely aligned with their travel culture—including preferences for outdoor environments, low-cost experiences, and recreational autonomy. Moreover, as highlighted in the literature review, the pandemic broadened the meaning of destination attractiveness [16,34]. Beyond traditional pull factors such as natural beauty or heritage, tourists increasingly valued new attributes such as perceived safety, hygiene protocols, and spatial decongestion [6,10,35]. These emerging priorities became central in shaping travel decisions, particularly among national visitors who were more attuned to local contexts and sensitive to real-time health-related signals [1,11,46,100].

Regarding the relationship between tourist motivations and satisfaction (specific hypotheses H1a and H1b), the results from the pre-pandemic period showed a strong correlation between specific motivations and satisfaction. These findings are consistent with studies that emphasise how satisfaction is significantly influenced by a destination’s capacity to meet or exceed tourists’ expectations [50]. This relationship is also aligned with the “push and pull” theory [101], whereby internal motivational factors (such as the search for relaxation or adventure) and external pull factors (such as destination attributes) interact to shape the overall tourism experience. In this phase, when visitors found that their motivations were fulfilled—especially through recreational and cultural activities—they reported higher levels of satisfaction.

Tourists motivated by sun and beach and water activities found their expectations well met, as shown by 93.6% of visitors motivated by sun and beach and 58.8% by water activities, supporting the theory that satisfaction increases when there is congruence between what tourists seek and what they find [20,43]. Specific hypothesis 1a is therefore confirmed for seven out of ten motivational variables. However, no significant relationship was found for sport activities, gastronomy, and heritage. Thus, the hypothesis cannot be fully accepted in the context of the pre-COVID-19 period, revealing that not all motivations held equal weight in shaping the satisfaction response.

During the pandemic, motivations influencing satisfaction showed an adjustment towards activities perceived as safer, reflecting a shift in the ‘push’ factors influenced by a new context of health restrictions. This aligns with the work of Higgins-Desbiolles [74], who argues that motivational priorities tend to shift in times of crisis, favouring safety and well-being. It also supports the theory of tourism demand elasticity in response to external shocks [24], illustrating how tourist motivations and expectations are highly sensitive to macro-environmental changes.

The rise in the proportion of tourists motivated by activities perceived as safe, such as sports (from 48.6% to 62.8%), and a good value for money (from 34.5% to 76.8%), reflected an adjustment in preferences and expectations. This supports previous research showing that tourists adapt their motivations in response to environmental disruptions [5,16,74]. Specific hypothesis 1b is supported by five out of ten motivational variables, while motivations related to water activities, gastronomy, discovering new places, heritage, and value for money did not show a significant effect on satisfaction. Therefore, the hypothesis must be considered partially rejected for the pandemic period, highlighting a shift in the relative importance of certain motivations.

Concerning the effect of tourist satisfaction on the intention to recommend (specific hypotheses H2a and H2b), pre-pandemic data revealed a strong relationship between visitor satisfaction and the willingness to recommend Platja d’Aro, consistent with other studies [15,38]. Essentially, visitors who felt their expectations had been exceeded, not only in terms of the destination’s attractions but also in their interaction with it, tend to become more fervent promoters of the destination. Recommendation scores were high (8.48/10), reinforcing the idea that satisfaction leads to a higher intention to recommend [53,66,67]. Thus, specific hypothesis 2a, related to the previous period of COVID-19, is fully supported by the structural model.

During the pandemic, although the relationship between satisfaction and recommendation remained significant, its intensity decreased slightly (7.8/10). This can be interpreted, from a theoretical perspective, in terms of increased risk perception and uncertainty, as discussed in the literature on tourism and crises. Although these variables were not directly measured in our model, previous research has shown that, in times of crisis, psychological dimensions such as fear, perceived risk, and uncertainty can influence consumer behaviour and affect their willingness to recommend a destination [24,102]. Higgins-Desbiolles [72], for example, highlights how altered perceptions about safety may negatively influence tourists’ inclination to promote a destination, even if their experience was positive. This phenomenon can be further explained by the concept of “perceived risk”, which has been shown to be a significant moderator in the relationship between customer satisfaction and loyalty in crisis contexts [19]. Concerns about health and safety during the pandemic could have elevated the perceived risk associated with traveling and, consequently, recommending travel to others.

Despite the slight decrease in recommendation, visitors were still satisfied with their experience in Platja d’Aro. This satisfaction continued to influence their intention to recommend, consistent with studies suggesting that tourists tend to value and share satisfying experiences during times of uncertainty as a form of support for the destination [67,74]. These findings reflect the resilience demonstrated by the tourism sector and the ability of Platja d’Aro to maintain a positive image despite adversities through strategies oriented towards crisis management and tourism recovery [11]. Thus, specific hypothesis 2b, related to the pandemic period, is fully supported by the structural model.

Although a direct path from motivation to recommendation was tested during the model specification process, the relationship was not statistically significant. This finding supports the role of satisfaction as a mediating variable: tourists do not recommend a destination solely because they were initially motivated to visit, but rather because their motivations were fulfilled and translated into a satisfactory experience.

Understanding tourist motivation is key to designing effective destination strategies. The distinction between “push” and “pull” factors helps explain how internal drivers and external attributes converge in tourist decision-making [38,101]. These findings, together with the existing literature on tourist behaviour in crisis contexts [16,27,45], suggest that motivations related to perceived safety and well-being—previously secondary—gained prominence during the pandemic. This shift opens opportunities for tourism professionals to customise services that align with evolving traveller expectations, especially by leveraging the destination’s unique and safe attributes [46,53].

The continued growth of recreational activities in coastal areas highlights the need to better understand what motivates tourists to choose specific destinations [42]. Similarly, research on seasonality and preferences is essential for tourism demand management [41,101]. These dynamics must be considered in the design of effective tourism strategies, particularly those that prioritise long-term sustainability [11].

Satisfaction, for its part, remains a strong predictor of recommendation, even during a pandemic, as it influences both return visits and word-of-mouth. This study complements the existing literature by demonstrating that while satisfaction drivers may vary in crisis contexts, the fundamental relationship between motivation, satisfaction, and recommendation persists [5,10,36]. Nevertheless, the persistence of this relationship should not lead to the assumption that satisfaction alone guarantees loyalty. In times of crisis, tourists may still hesitate to recommend a destination despite being satisfied due to uncertainty or social responsibility concerns [18,34]. Furthermore, although several motivations continued to significantly predict satisfaction, the diminished influence of others suggests that certain motivational factors may operate differently under exceptional circumstances [13].

Although some tourism-dependent destinations began reactivating their activity under certain constraints [102], the case of Platja d’Aro reflects a progressive and locally adapted approach. Policymakers adopted measures to support tourism during the summer of 2020, aligned with broader strategies observed in other destinations. Across different contexts, tourism authorities promoted proximity and rural tourism to offer safer, open-air experiences and reduce long-distance travel [7,32]. Service providers implemented sanitation and biosecurity protocols, reduced capacity, and introduced distancing measures in both public and private spaces [8,36]. In areas such as parks, squares and beaches, local governments redesigned spaces to avoid crowding and improve the visitor experience. Rather than focusing solely on increasing tourist numbers, many destinations shifted their efforts toward offering personalised services and activities that prioritised safety and comfort [37,100].

In this context, the literature underscores the importance of coordination between local stakeholders and public institutions. Local actors developed differentiated services based on quality and trust-building [36], while government support was essential for maintaining operations and creating policies for tourism-dependent regions [72]. While not measured in our model, the importance of such combined efforts is derived from the broader literature and the contextual observations of how other destinations responded to the crisis contributed to redefining tourism development priorities, with greater emphasis on flexibility, health security, and long-term resilience.

Although the COVID-19 pandemic is now behind us, documenting and analysing the behavioural changes it triggered remains essential for understanding both present and future dynamics of tourism. The contrast between pre-pandemic and pandemic-period tourist motivations and behaviours offers critical insights into how external disruptions—such as global health crises—can reshape travel patterns, influence destination preferences, and recalibrate visitor expectations [32,34]. Many of the motivational shifts observed during the pandemic—such as increased interest in nature, safety, and local or proximity-based tourism—continue to influence tourist preferences even in the absence of immediate health risks [100].

Tourism is inherently vulnerable to a wide range of crises—sanitary, environmental, economic, or geopolitical— and its future depends on the ability to adapt and learn from past events [8,11]. In this context, the present study not only helps explain how tourists responded to uncertainty and change, but also contributes to establishing an empirical precedent that may guide academic research and policymaking in future crises [6]. As Mediterranean destinations and other tourism regions prepare for renewed growth and record-breaking seasons [103], our findings offer a useful reference for anticipating tourist behaviour and developing more resilient and targeted strategies.

Beyond the immediate behavioural responses observed during the COVID-19 period, the pandemic has also contributed to amplifying critical debates around the future of tourism. Concepts such as sustainability, regenerative tourism, and structural transformation gained renewed visibility during the crisis and continue to influence academic, institutional, and policy discourses even after the health emergency has subsided [6,44,100]. Therefore, current and future tourism strategies must go beyond restoring demand levels and address broader issues of equity, environmental responsibility, and resilience [85].

5.1. Practical Implications

Several practical implications can be derived from the present study. Firstly, during the pandemic, a marked shift occurred towards younger and more local tourists, with preferences for outdoor and perceived-safe experiences. While this profile was context-specific, certain behavioural patterns (proximity travel, digital engagement, and interest in nature-based activities) may remain relevant beyond the crisis. Public managers could consider integrating these insights into flexible and resilient marketing approaches, particularly in preparation for future disruptions or in the search for more sustainable domestic tourism models.

Although variables such as safety and sustainability were not directly measured in this study, their relevance is interpreted from the broader pandemic context and supported by the literature reviewed. References to these aspects in the recommendations are interpretative, based on observed behavioural shifts and theoretical contributions that emphasise their growing importance during and after crises. These reflections aim to support destination managers in designing adaptive strategies that align with the evolving expectations of tourists under uncertain conditions.

Secondly, the results concluded that improving the visitor experience remains essential, as satisfaction continues to be a key predictor of destination recommendation, regardless of the pandemic. Therefore, destinations must ensure that their tourist offerings meet visitors’ expectations. This involves regularly assessing demand perceptions, providing staff training, and maintaining high standards of hygiene and perceived safety across infrastructure and services.

Thirdly, crisis management and resilience present challenges but also opportunities to adapt to environmental changes. Destinations should develop contingency plans and continuously update tourism management frameworks. It is also essential to promote collaboration between different levels of government and the business sector to ensure coordinated responses in times of crisis.

Fourthly, although government intervention was not directly measured in our model, the case analysis and the literature reviewed suggest that public policies and institutional support played a key role in facilitating tourism recovery. The experiences observed in Platja d’Aro—such as local coordination, the implementation of health regulations, and the adaptation of public spaces—highlight the relevance of governance in managing tourism during crises.

Beyond its relevance for understanding behavioural dynamics during the COVID-19 pandemic, this study provides relevant insights for current destination management. The shifts observed in tourist motivations—towards nature, safety, and proximity—highlight patterns that continue to shape post-pandemic travel behaviour. Destination managers can use this knowledge to enhance strategic planning, develop responsive tourism products, and incorporate resilience-based approaches in marketing and operations. The lessons from the pandemic period should not be viewed as exceptional or outdated, but as a critical interpretative foundation for anticipating and managing future shocks in a sector that remains highly sensitive to global disruptions [5,6,46].

5.2. Limitations of This Study

Despite the contributions made, this study also presents several limitations that open paths for further research. First, as it was applied to a single coastal destination, the findings may lack generalisability. Comparative research across different destinations would help identify broader patterns or significant divergences in motivational and satisfaction trends. Second, the exclusive use of quantitative methods limits a deeper understanding of tourists’ perceptions and emotions, aspects that could be enriched through qualitative approaches. Third, although the analysis covers two years, the surveys were only conducted during the summer, potentially excluding seasonal variations in tourist behaviour.

Based on these limitations, several future lines of research are proposed. First, the analysis should be extended to post-pandemic periods in order to assess whether the motivational and satisfaction patterns identified during the pandemic have persisted over time, reverted to pre-pandemic behaviours, or evolved into new forms of tourist demand. Longitudinal approaches would be particularly useful to distinguish between temporary behavioural adjustments and structural shifts in travel preferences. Second, qualitative methods—such as in-depth interviews—should be incorporated to capture more nuanced dimensions of tourist perceptions, emotions, and decision-making processes that cannot be fully understood through quantitative data alone. Third, further exploration into the role of governance as a key driver in tourism recovery is needed, particularly how policy decisions made by public managers shape both resident and tourist behaviour and influence the long-term sustainability and competitiveness of destinations.

Finally, future studies should examine whether the behavioural responses identified in this research are specific to the COVID-19 context or indicative of broader adaptive patterns. Comparative analyses involving other types of crises—such as climate-induced disasters, political instability, or economic disruptions—could clarify the extent to which certain motivational shifts and resilience mechanisms are transferable. By addressing this question across different types of crises, future research can move beyond reactive analysis and begin to shape a more strategic and anticipatory approach to destination planning.