Exploring Positive and Negative Emotions Through Motivational Factors: Before, During, and After the Pandemic Crisis with a Sustainability Perspective

Abstract

The tourism sector thrives on a comprehensive understanding of the factors that motivate individuals to explore new destinations. Identifying the push and pull factors that drive travel decisions is essential for analyzing tourist behavior and recognizing the external constraints that tourism enterprises and destinations must consider. Adopting a sustainable approach to these motivational forces underscores the need to balance tourism growth with the preservation of destinations, the well-being of local communities, and responsible travel practices. Push and pull factors in tourism are inherently linked to the emotional states that travelers experience throughout the decision-making process, from the initial intention to travel to the post-trip evaluation. The sector prospers by understanding the reasons that inspire individuals to discover new places. Determining these motivational factors is crucial for comprehending tourist behavior and addressing the external limitations that tourism businesses and destinations must navigate. A sustainability-focused approach highlights the significance of aligning tourism growth with destination preservation and community well-being, ensuring a responsible and enduring tourism model. This study aims to examine the impact of positive and negative emotions on push and pull motivational factors across different phases of the COVID-19 pandemic, adopting a sustainability perspective. The research was structured into four empirical studies: (i) pre-pandemic phase, involving a sample of 508 tourists; (ii) pandemic phase, with data collected from 507 participants; (iii) post-pandemic phase, comprising 488 respondents; (iv) comparative analysis, assessing variations across the three periods. The results indicate that emotional states exert a significant influence on push and pull motivational factors, with variations observed depending on the period of data collection: before, during, and after the COVID-19 pandemic. However, while emotions exhibited fluctuations across the three phases, push and pull factors demonstrated relative stability over time. These findings emphasize the critical role of emotional experiences in shaping travel motivations, highlighting the interplay between psychological drivers and destination attributes. This understanding is essential for tourism businesses and policymakers to develop strategies that align with evolving traveler expectations while promoting sustainable and responsible tourism practices.

1. Introduction

While providing economic and cultural benefits, tourism also demands a sustainable approach to mitigate its impact on destinations and communities. Sustainability ensures that the push and pull factors not only address the travelers’ motivations but align with the goals of preserving cultural heritage, biodiversity, and the well-being of the host communities [1]. The concept of sustainable tourism guarantees that these factors contribute to long-term environmental and social balance. The COVID-19 pandemic altered travel motivations significantly, leading to a noticeable shift toward less densely populated destinations, ecotourism, and sustainability-conscious travel options [2]. According to Boniface et al. [3], tourism can be driven by different factors that motivate people to travel out of their usual environment. The framework of push and pull factors has become very important in understanding the motivations, especially because it illustrates the interplay between people’s desire and the characteristics of the place that make it touristic [4]. Push factors are those that lead a person to leave their place of residence, which includes, among other things, personal, psychological, and socio-economic reasons that motivate people to travel [5]. On the other hand, pull factors relate to the attractions and appeal of a destination—its characteristics and assets that match the visitors’ desires and interests [6]. Hence, tourists are motivated by push and pull factors that can arise in isolation or due to a combination of different elements, and their decisions are often influenced by personal preferences, circumstances, and external conditions [7].

The literature regarding push and pull factors also addresses the synthesis of these two forces that determine where a particular tourist wants to travel compared to the available potential destinations [8]. Tourism as an open and dynamic system influences and is influenced by various external factors [9]. Criteria such as cultural and natural heritage, hospitable environment, and infrastructure are among some reasons that increase the attraction to tourists [6]. In a world characterized by increasing globalization, where the boundaries between cultures and geographies continue to get mixed up, understanding these factors is essential if policymakers, tourism companies, destination marketers, and others are to meet the diverse needs of travelers [10]. In times of crisis, relying solely on sentiment may not be enough to drive travel decisions. Health and economic crises, such as the COVID-19 pandemic, have further complicated these decisions [4]. The pandemic demonstrated a clear example of tourism’s vulnerability, causing a shift in travel behaviors [11]. In such unique circumstances, it became crucial to reevaluate what drove people to travel or held them back [12]. Prevailing emotions, such as fear and anxiety related to COVID-19, significantly influenced decision-making [13]. Thus, within the context of the pandemic, the interplay between emotions, motivations, and external conditions played a crucial role in shaping travel choices [14].

This study explores how sustainability concerns have influenced the evolution of push and pull factors. We analyzed whether travelers became more inclined toward eco-friendly destinations, low-impact tourism, and responsible travel choices after the pandemic. Additionally, this study examined whether emotional responses to travel restrictions and growing environmental awareness have shaped long-term behavioral changes in tourism. This information contributes to a growing body of literature on the intersection between tourism resilience, sustainability, and evolving consumer behavior in post-pandemic travel.

The research focuses on the influence of positive and negative emotions on push and pull factors in the decision-making process of choosing a tourist destination. Data collection began before the emergence of COVID-19 and was interrupted during the pandemic crisis. Subsequently, data collection resumed, allowing for a comparative study. Hence, this study aims (i) to evaluate how emotions before, during, and after the pandemic affected people’s motivation to travel, and (ii) to understand the main push and pull factors associated with travel decisions.

2. Literature Review

2.1. Push and Pull Factors as Trigger in Tourism

Motivation factors can vary from person to person and can even change over time, but they often play an important role in the decision to travel [15]. Thus, the various motivations are what lead tourists to visit a particular destination, determine the adoption of different types of behavior, and the criteria that contribute to the evaluation of the tourist experience [7]. The designation of push and pull factors, initially studied by Dann [16] and Crampton [17], has served as the basis for many studies on motivations. There is currently a consensus among researchers that push and pull factors in tourism influence people’s decisions to travel and their specific choice of destinations [7]. Push factors in tourism usually refer to conditions intrinsic to the traveler and are related to personal desires, beliefs, interests, and needs [18]. Push motives include hedonic tourist experiences, such as relaxation, leisure, escapism, seeking adventure and new sensations, or family togetherness [7]. However, in the context of sustainable tourism, these intrinsic motivations are evolving. Travelers may also be driven by ethical concerns, such as reducing their carbon footprint, engaging in ecotourism, or avoiding overcrowded destinations [6]. Pull factors in tourism refer to the characteristics and attractions of a given destination that led travelers to visit it [18]. These factors are fundamental to attracting tourists and can vary greatly from one place to another, depending on the characteristics of each destination [6]. Pull motives are conditioned by the tourists’ evaluations of the perceived usefulness and attributes of the destination, with the image of the destination being one of the most efficient ways of evaluating these attributes [6]. Increasingly, these attributes incorporate sustainability-related aspects, such as protected natural areas, responsible tourism infrastructure, and community-based tourism experiences [18]. This suggests that a tourist’s attitude towards the destination can be a measure of the ability of that destination to attract tourists [19].

2.2. Emotions Impact on Push and Pull Factors

Emotions are responses to external stimuli based on cognitive evaluations of different experiences [20]. They function as a barometer with which individuals positively or negatively assess their surroundings [8]. In the context of tourism, emotions are essential as they influence all phases of the tourist experience and allow visitors to connect with destinations [21].

There is a close connection between motivations and emotions. The desire to travel is related to the conscious and subconscious, which means that the motives, perception, and subsequent evaluation of experiences are not only rational acts, but involve emotional elements [7]. Tourist destinations are made up of a vast set of experiential attributes, which allow visitors to have memorable experiences [22].

Memorable experiences are naturally associated with hedonism, which in turn leads us to positive emotions that involve pleasure and satisfaction with the tourist destination [23]. However, although tourism activity is based on hedonism and the pursuit of pleasure, the impact of negative emotions on the evaluation of the tourist experience must be considered [21]. While consumers tend to respond to positive emotions with positive behaviors, negative emotions often result in negative behaviors [24].

Although positive and negative emotions are, in principle, antagonistic, this does not mean that they cannot be experienced simultaneously in the same event [25]. That is, in the same event, participants may be faced with mixed emotions and feel happy in a certain situation and dissatisfied in others [24]. In this sense, emotions related to tourism (positive and negative) play a significant role in the visitors’ motivations, whether they are push factors or pull factors [8].

During the COVID-19 pandemic, environmental and public health concerns became fundamental determinants of travel, shaping both push and pull factors [26]. As travel restrictions were eased, many travelers began prioritizing destinations with strong sustainability credentials, including those promoting ecotourism, eco-friendly accommodations, and conservation efforts [27]. Furthermore, push factors evolved to place greater emphasis on well-being, nature-based tourism, and more responsible travel behaviors [28]. This suggests that the pandemic not only reshaped travel habits in the short term but may have accelerated a long-term shift toward sustainable tourism behaviors.

2.3. Push and Pull Factors in Tourism During and After the Pandemic COVID-19

During the pandemic, factors of health and safety became priorities, creating opportunities for the development of more sustainable forms of tourism (Table 1). These included valuing less densely populated destinations and those in closer contact with nature, contributing to tourism practices that respect the environment and local communities [2].

Push and pull factors in tourism are particularly relevant when considering the tourists’ feelings and behaviors during a particular external event, such as the COVID-19 pandemic [4]. During the pandemic, the push factors were intensified, as travel was restricted, or even banned, creating a need to travel, to leave one’s place of residence, or even the need to leave for more distant and less affected places due to the fear of contamination [19]. Travel also became a way of coping with the psychological stress caused by the pandemic [29]. Regarding the pull factors, some positive feelings were resisted, such as the relief and comfort of reaching less affected destinations, the perceived need to avoid large concentrations of people, and the desire to get more in touch with nature, contributing to new forms of tourism [30].

Table 1. Key elements of the push and pull factors, in the context of the COVID-19 pandemic.

Factors	Push Factors	Pull Factors	Authors
Social	Escapism, psychological stress, travel restrictions creating a need to travel	Positive accessibility, social conditions, political and security conditions in destinations	[19,31,32,33]
Cultural	Interest in different cultures, traditions, gastronomy, and languages	Destinations with rich cultural heritage (tangible and intangible), gastronomy	[2,6,18,27]
Economic	Financial difficulties due to the pandemic, employment, and income levels	Affordable prices, competitive packages, value for money in destinations	[2,34,35,36]
Psychological	Desire for relaxation, break from stress, curiosity, coping with psychological stress of the pandemic	Relief and comfort in destinations, escape from lockdown stress, resilience, and adaptation during travel	[14,19,37,38]
Environmental	Desire to escape environmental dangers, seeking nature, health, and well-being needs	Natural resources, unique geological and geographical features, sustainable practices in destinations	[15,18,39,40]
Service quality	Seeking personal development, professional reasons, watching/practicing sports	Quality of accommodation, transportation, services, infrastructure, hospitality of residents	[18,41,42,43]

Table 1. Key elements of the push and pull factors, in the context of the COVID-19 pandemic.

Factors	Push Factors	Pull Factors	Authors
Social	Escapism, psychological stress, travel restrictions creating a need to travel	Positive accessibility, social conditions, political and security conditions in destinations	[19,31,32,33]
Cultural	Interest in different cultures, traditions, gastronomy, and languages	Destinations with rich cultural heritage (tangible and intangible), gastronomy	[2,6,18,27]
Economic	Financial difficulties due to the pandemic, employment, and income levels	Affordable prices, competitive packages, value for money in destinations	[2,34,35,36]
Psychological	Desire for relaxation, break from stress, curiosity, coping with psychological stress of the pandemic	Relief and comfort in destinations, escape from lockdown stress, resilience, and adaptation during travel	[14,19,37,38]
Environmental	Desire to escape environmental dangers, seeking nature, health, and well-being needs	Natural resources, unique geological and geographical features, sustainable practices in destinations	[15,18,39,40]
Service quality	Seeking personal development, professional reasons, watching/practicing sports	Quality of accommodation, transportation, services, infrastructure, hospitality of residents	[18,41,42,43]

Doğan et al. [42] demonstrated that fear of COVID-19 had a significant negative impact on travel intentions, reducing the tourists’ willingness to visit new destinations. According to the authors, trust in the vaccines did not have a significant effect on the relationship between fear and travel intention. This finding suggests that, despite the progress of vaccination campaigns, fear of the disease continued to negatively influence travel decisions. The present study builds upon these findings by analyzing the interaction between push and pull motivational factors and positive and negative emotions before, during, and after the pandemic. Additionally, it provides further evidence on how emotions can influence and modify the motivations that drive tourists to travel, emphasizing their role as key determinants in travel decision-making.

In one study, the positive feelings of being able to travel again, the escape from the stress and monotony of lockdowns, as beneficial psychological stimulus, resilience, and adaptation during the pandemic had an impact when choosing a tourist destination [19]. In another study, the negative emotions experienced during the pandemic were complex and varied from person to person [38]. In another study, fear and anxiety limited the intention to travel, while frustration and disappointment were caused by canceled plans, in addition to feelings of guilt for traveling in a context where not traveling was recommended, due to the danger of contamination to the tourists themselves and the potential spread of the virus, as well as feelings of nostalgia and longing, because people may experience nostalgia for past travel experiences, and a longing to return to a sense of normality in tourism [32]. However, given the impact of the spread of the pandemic, the demand for certain destinations was largely affected, not only by the difficulty in accessing certain destinations, but by the very impediment or conditions required, such as vaccination, negative tests, even the impediment to visiting certain cultural attractions and recreational activities [33].

The pandemic forced tourists, the tourism sector, and destinations alike to adapt to a new reality characterized by health and safety concerns, but the restrictions implemented after the outbreak have resulted in the development of trends in how people consume tourism, affecting the push and pull factors [14]. Considering the above, the first hypotheses were derived:

Hypothesis 1:

Emotions have an impact on the factors that influence the choice of tourist destination.

Hypothesis 1a:

Push factors are negatively influenced by emotions when choosing a tourist destination.

Hypothesis 1b:

Pull factors are positively influenced by emotions when choosing a tourist destination.

The economic crisis caused by the pandemic has had profound effects on tourism, encompassing push and pull factors, as well as a complex web of emotions, reshaping travel motivations [44]. The COVID-19 pandemic economic crisis affected push factors because many individuals and families faced financial difficulties due to job losses or reduced income [4]. This economic strain decreased their ability to afford travel, as they grappled with more immediate concerns and lacked the emotional or financial resources to plan trips [35]. In addition, the pandemic not only imposed travel restrictions to contain disease spread but impacted tourism by reducing tourist numbers and driving up prices in destinations [36]. Importantly, these developments, together with the ensuing economic crisis, significantly influenced the pull factors in the tourism industry [45]. Under these assumptions, the second hypothesis was outlined:

Hypothesis 2:

The economic crisis triggered by the COVID-19 pandemic has influenced the motivation to choose a tourist destination.

Before the pandemic, positive emotions included enthusiasm, joy, and happiness (pre-trip), and good memories and a feeling of personal accomplishment (post-trip), depending on when the trip took place [19]. Negative emotions included anxiety, doubts, and fears related to the trip (pre-trip) and sadness, anger, disappointment, and dissatisfaction (post-trip) [31]).

As mentioned above, during the pandemic negative emotions were particularly prominent, with fear and social concerns emerging as key factors related to the risk of contagion and the restrictions imposed upon travelers returning to their home countries, including mandatory isolation [26]. Furthermore, the uncertainty surrounding the pandemic heightened anxiety in the travel decision-making process, leading many tourists to reconsider or postpone their plans. However, positive emotions also played a significant role in shaping travel behavior. Enthusiasm and anticipation for the opportunity to explore new destinations were evident during the pre-travel phase, while post-travel experiences were predominantly characterized by relaxation, personal satisfaction, and a sense of accomplishment. The perception that the trip unfolded as expected contributed to a positive evaluation of the overall tourism experience [46]. These findings highlight the complex interplay between negative and positive emotions in travel motivation, reinforcing the ambiguity and variability of tourist behavior during the pandemic.

In the post-pandemic period, tourism has changed. More rural and sustainable areas, as well as services more concerned with the preservation and sanitization of spaces, have become more sought after [28,47]. Considering all the above, the following hypotheses were developed:

Hypothesis 3:

Emotions varied depending on when the data was collected.

Hypothesis 3a:

Positive emotions varied depending on when the data was collected.

Hypothesis 3b:

Negative emotions varied depending on when the data was collected.

Before the pandemic, pull motivations varied according to individual characteristics, shaped by psychological, social, cultural, financial, and demographic contexts. Meanwhile, push motivations encompassed factors such as leisure, the pursuit of novel experiences, cultural exploration, the desire to escape daily routines, and relaxation [13]. However, the COVID-19 pandemic introduced an unprecedented shift in these motivational dynamics, as health and safety concerns became primary determinants of travel decisions [48]. The fear of infection and the imposition of travel restrictions intensified repulsion factors, leading travelers to prioritize destinations perceived as safe and spacious, where close interpersonal contact could be minimized [49]. As a result, push and pull motivations during the pandemic were largely influenced by the search for low-density environments, contributing to the rise of rural and nature-based tourism as a coping mechanism to alleviate pandemic-related stress [2].

Regarding the post-pandemic period, more countries, regions, and cities have reopened following widespread vaccination, travel motivations have also begun to change, although not always to the pre-pandemic standards [14]. Tourists in post-pandemic times have been more avid about the sustainability of the trips taken and health-centered tourism, showing that the change in push and pull motivations is long-term; they now include mental health, outdoor activities, reconnecting with family or friends, and searching for more memorable experiences [50].

Hence, the temporal evolution of tourism motivation allows us to consider how external crises, such as the COVID-19 pandemic, can radically change the classical model of push and pull factors. In the period before the onset of the pandemic, the motivational factors were mostly aimed at leisure and adventure [7]. Thus, the following hypotheses are presented:

Hypothesis 4:

Motivations to travel differed significantly depending on when the data was collected.

Hypothesis 4a:

Push factors differed significantly depending on when the data was collected.

Hypothesis 4b:

Pull factors differed significantly depending on when the data was collected.

Figure 1 illustrates the connections between the variables.

3. Methodology

3.1. Study Design and Procedures

This study examines the impact of positive and negative emotions on push and pull motivational factors in travel decision-making before, during, and after the COVID-19 pandemic. A quantitative approach was employed, using structured surveys administered to the independent samples of tourists across different time periods.

Data collection occurred in three distinct phases: (i) pre-pandemic phase, in which tourists who traveled between June and December 2019 participated; (ii) pandemic phase, which covered the period of restrictions between June and December 2020; and (iii) post-pandemic phase, which included the participation of tourists who traveled between June and December 2023. Subsequently, a comparative analysis was conducted across the three periods to assess potential changes in push and pull factors as well as the emotional responses associated with the tourism experience over time. The questionnaires were administered face-to-face at the most tourist-frequented locations in Lisbon, Portugal, ensuring a diverse and representative sample of travelers.

3.2. Sample and Sampling Technique

The research included a total sample of 1503 participants, distributed across three distinct time periods. Independent samples were used at each stage to prevent response bias, with participants eligible for inclusion if they had undertaken a leisure trip within the six months preceding the survey administration. To ensure statistical robustness, a probabilistic sampling approach was employed, with data collected at strategic high-tourist-traffic locations to ensure that respondents were actively engaged in a travel context.

The consistent application of the same sampling method across the three periods (pre-pandemic, during the pandemic, and post-pandemic) enabled a reliable comparative analysis over time. The sampling strategy was designed to capture a diverse range of travelers, considering factors such as age, gender, and travel purpose, to encompass a broad spectrum of travel experiences and behaviors.

To ensure population representativeness, two key criteria were applied: (i) a 95% confidence level with a 5% margin of error, ensuring that the sample size remained within the recommended range (approximately 483 to 533 participants per group), thereby maintaining statistical robustness and generalizability; and (ii) replication of the sampling method across different timeframes, combined with participant diversity and rigorous statistical controls, which strengthened the validity and reliability of the findings.

3.3. Measures

Pull and push. The motivational factors to travel were evaluated using the items developed by Crompton and McKay [17], adapted for the Portuguese population by Correia et al. [51]. Then, Rodrigues and Mallou [52] used a version with 34 items: 15 items were meant to measure pull factors (e.g., learning about other cultures and ways of life, meeting interesting people), and 19 items were meant to measure push factors (e.g., weather, food). This was the version used in this study. To measure the respondents’ degree of agreement with the questionnaire items, a five-point Likert scale was employed, where one indicated “strongly disagree” and five indicated “strongly agree”. In the three aforementioned studies, Cronbach’s alpha coefficients ranged between 0.80 and 0.88, demonstrating that, regardless of the context in which the instrument is applied, it exhibits high internal consistency.

Scale of Positive and Negative Experience (SPANE). The emotions were measured using the scale developed by Diener et al. [53] and validated for the Portuguese population by Junça Silva and Caetano [54]. This is a self-report instrument composed of six positive emotions (e.g., joyful, happy) and six negative emotions (e.g., sad, unpleasant), where participants were asked to indicate the frequency with which they experienced each emotion during their most recent trip. In both the original and the Portuguese versions, responses were recorded on a five-point Likert scale ranging from Never (1) to Always (5). In both the validation study of the SPANE scale and its adaptation for Portugal, Cronbach’s alpha coefficients demonstrated high reliability, with values ranging between 0.81 and 0.90.

Sociodemographic questions. Sociodemographic variables were collected to characterize the sample (e.g., sex, age).

3.4. Data Analysis

The data were analyzed using SPSS (version 29) and AMOS (version 29). Confirmatory factor analysis (CFA) was employed to validate the measurement instruments, while multivariate analysis of variance (MANOVA) was conducted to compare the three time periods. Additionally, multigroup structural equation modeling (MGSEM) was utilized to assess the stability of the factors over time.

4. Results

This section presents only the specific findings for each sub-study, avoiding redundancy in methodological descriptions.

4.1. Study 1—Pre COVID-19 Pandemic

4.1.1. Sample

This study included 508 participants who had traveled abroad within the six months immediately before the pandemic. The participants’ ages ranged from 18 to 70 years (M = 36.6, SD = 10.5), with 76.85% being male. Among the participants, 76.8% traveled for leisure, 17.1% for work, and 6.1% to visit family. Additionally, 27.2% of the trips were taken as a couple, 25.8% traveled alone, 24.4% with friends, and 22.6% with family. The high proportion of male participants may be attributed to the period during which the data were collected, as it coincided with the Web Summit 2019, the largest technology event in Europe.

4.1.2. Preliminary Analyses

In an initial phase, an exploratory factor analysis was conducted, utilizing the principal component analysis (PCA) technique to uncover the internal structure of the instruments. The composite reliability (CR) and the average variance extracted (AVE) values were calculated following the criteria recommended by Fornell and Larcker [55] and subsequently validated by Almén et al. [56] and Hair et al. [57]. The analysis confirmed that the CR and AVE values for all variables exceeded the recommended thresholds of 0.70 and 0.50, respectively, thereby establishing convergent validity.

Furthermore, it was determined that the maximum shared variance (MSV) values were lower than the AVE values, ensuring discriminant validity. These results suggest that the measurement model meets the necessary psychometric properties for validity and reliability.

Table 2. Descriptive statistics.

Variable	M	SD	CR	AVE	MSV	1	2	3	4
1. Push	4.16 1	0.85	0.95	0.80	0.88	(0.94)
2. Pull	4.00 1	0.84	0.95	0.77	0.88	0.793 **	(0.94)
3. PE	3.31 1	0.67	0.89	0.73	0.36	0.110 *	0.203 **	(0.83)
4. NE	2.98 1	0.72	0.86	0.78	0.37	0.142 **	0.118 **	−0.309 **	(0.79)

Note. * p < 0.05; ** p < 0.001; PE = positive emotions; NE = negative emotions; M = mean; SD = standard deviation; CR = composite reliability; AVE = average variance extracted; MSV = maximum shared variance. ¹ Scale ranging from 1 to 5; Cronbach’s alpha is in brackets.

presents the descriptive statistics and correlations among the variables under study. The data analysis revealed that all variables were significantly correlated, indicating strong relationships between them. Additionally, it was observed that individuals predominantly travel for intrinsic reasons, with positive emotions outweighing negative ones in their travel experiences.

With the aim of verifying whether the measured variables adequately represented the latent factors underlying the manifest variables [57] a confirmatory factor analysis (CFA) was conducted. The results indicated that, after incorporating the error covariations suggested by the AMOS modification indices, the model demonstrated a good fit to the sample data [χ²₍₅₁₃₎ = 3.78, p < 0.001, CFI = 0.90, GFI = 0.81, RMSEA = 0.07, LO90 = 0.70, HI90 = 0.70].

4.1.3. Validation of Research Hypotheses

The first hypothesis (Hypothesis 1: Emotions have an impact on the factors that influence the choice of tourist destination), was corroborated through regression analyses. The results demonstrated the existence of a direct and statistically significant relationship between negative emotions and push factors (β = 0.194, t = 4.254, p < 0.001; Hypothesis 1a: Push factors are negatively influenced by emotions when choosing a tourist destination). It was also determined that the model is linear (F_(2,505) = 12.230, p < 0.001) and that 3.4% of intrinsic motivations are explained by the negative feelings experienced by individuals at the time of travel.

On the other hand, it was found that pull factors are predominantly influenced by positive emotions (β = 0.265, t = 5.901, p < 0.001; Hypothesis 1b: Pull factors are positively influenced by emotions when choosing a tourist destination). The results suggest that 6.3% of the participants’ perception of the characteristics of the destination they traveled to is explained by the positive emotions it evokes.

The results suggest that emotions play a crucial role in motivating individuals when traveling, with positive emotions having a greater impact on pull factors and negative emotions influencing push factors. Positive emotions, such as joy and positivity, evoke the desire to explore new places and engage in pleasant experiences, which are characteristic of pull factors. Conversely, negative emotions, such as sadness and fear, act as push factors, encouraging individuals to distance themselves from undesirable situations or environments and seek change through travel. It is observed that the balance between these two types of emotions is pivotal in destination choice and traveler behavior.

4.2. Study 2—During the COVID-19 Pandemic

4.2.1. Sample

The second study included 507 participants, aged between 19 and 59 years (M = 37.25; SD = 10.2). The majority were male (76.5%), and approximately 60.0% were over the age of 35. The findings revealed that 70.4% of participants traveled for work, while 24.1% traveled to visit family members. During the pandemic period, 80.3% of participants traveled alone, 10.3% traveled as a couple, and 9.5% traveled with their family.

4.2.2. Preliminary Analyses

As in Study 1, a principal component analysis (PCA) was conducted to determine the factor structure of the instruments. Composite reliability (CR) and average variance extracted (AVE) were also analyzed, with values exceeding the thresholds recommended by Hair et al. [57], thereby confirming the convergent validity of the measures. The maximum shared variance (MSV) values were found to be lower than the AVE, confirming discriminant validity.

Table 3. Descriptive statistics.

Variable	M	SD	CR	AVE	MSV	1	2	3	4
1. Push	1.80 1	0.86	0.85	0.66	0.37	(0.79)
2. Pull	4.02 1	0.85	0.92	0.79	0.45	−0.058	(0.89)
3. PE	2.82 1	0.60	0.72	0.63	0.49	−0.083	0.101 *	(0.72)
4. NE	3.46 1	0.47	0.69	0.54	0.48	−0.050	0.046	−0.120 *	(0.67)

Note. * p < 0.05; PE = positive emotions; NE = negative emotions; M = mean; SD = standard deviation; CR = composite reliability; AVE = average variance extracted; MSV = maximum shared variance ¹ Scale ranging from 1 to 5; Cronbach’s alpha are in brackets.

presents the descriptive statistics and correlations among the analyzed variables, showing that during the pandemic period, only pull factors were associated with positive emotions (r = 0.101, p < 0.05). Furthermore, it was observed that during this period people traveled mainly due to the characteristics of the destination, as most participants traveled alone and for work. It is noteworthy that negative emotions predominated, which can be explained by the pessimism experienced in a period characterized by uncertainty.

A confirmatory factor analysis (CFA) was subsequently conducted to assess whether the observed variables adequately reflected the underlying latent factors [58]. The results indicated that, after accounting for error covariation suggested by the AMOS modification indices, the model demonstrated a good fit to the sample data [χ²₍₁₈₀₎ = 3.61, p < 0.001, CFI = 0.93, GFI = 0.90, RMSEA = 0.07, LO90 = 0.06, HI90 = 0.07].

The study also aimed to understand whether the economic crisis triggered by the pandemic influenced the participants’ decisions regarding destination choice, type of transportation, and accommodation during their travels (

Table 4. Influence of the economic crisis.

The Economic Crisis Impacted the Choice of …	DNI	IS	I	ISig	FI
Tourist destination	0.2	0.6	25.6	15.8	57.8
Type of transportation	2.4	8.1	23.5	22.5	43.6
Type of accommodation	0.2	4.3	17.6	27.8	50.1

Note. DNI = did not influence; IS = influenced slightly; I = influenced; ISig = influenced significantly; FI = fully influenced.

). The results revealed that 99.2% of participants reported that their choice of tourist destinations was affected by the pandemic, as well as their choice of transportation (89.6%) and accommodation (95.5%).

4.2.3. Validation of Research Hypotheses

In light of the above, it was deemed pertinent to analyze how the choice of tourist destination, type of transport, and type of accommodation influenced the participants’ emotions and the push and pull motives that led them to travel. For this purpose, regression analyses were conducted, revealing that only the choice of tourist destination, influenced by the economic crisis, impacted the participants’ external motivation (β = −0.173, t = −2.849, p < 0.05). The results suggest that the greater the influence of the economic crisis on the choice of tourist destination, the lower the participants’ willingness to explore new places and cultures (push factors), thereby validating the second research hypothesis (Hypothesis 2: The economic crisis triggered by the COVID-19 pandemic has influenced the motivation to choose a tourist destination).

4.3. Study 3—Post COVID-19 Pandemic

4.3.1. Sample

A total of 488 individuals participated in the study, ranging in age from 18 to 62 years (M = 31.21; SD = 14.56), with 58% identifying as female. It was observed that, following the COVID-19 pandemic, the primary motivation for travel reverted predominantly to leisure (65.8%), rather than professional (7.6%) or for familial reasons (26.6%), as noted in Study 2. Furthermore, it was determined that 86.7% of participants traveled with companions (37.7% with friends, 32.0% with family, and 17.0% with a partner).

4.3.2. Preliminary Analyses

The statistical analysis was similar to that conducted in Studies 1 and 2, and the results are presented in

Table 5. Descriptive statistics.

Variable	M	SD	CR	AVE	MSV	1	2	3	4
1. Push	4.13 1	0.67	0.90	0.70	0.67	(0.87)
2. Pull	3.67 1	0.64	0.83	0.69	0.37	0.499 **	(0.76)
3. PE	3.67 1	0.69	0.87	0.77	0.68	0.448 **	0.385 **	(0.82)
4. NE	2.82 1	0.82	0.82	0.76	0.36	−0.136 **	0.041	−0.341 **	(0.68)

Note. ** p < 0.001; PE = positive emotions; NE = negative emotions; M = mean; SD = standard deviation; CR = composite reliability; AVE = average variance extracted; MSV = maximum shared variance. ¹ Scale ranging from 1 to 5; Cronbach’s alpha are in brackets.

. The CFA demonstrated that, after covarying the errors suggested by the AMOS modification indices, the model exhibited good fit to the sample data [χ²₍₂₉₁₎ = 4.94, p < 0.001, CFI = 0.79, GFI = 0.82, RMSEA = 0.08, LO90 = 0.08, HI90 = 0.09].

It was observed that, following the pandemic, individuals resumed traveling primarily for leisure, resulting in push factors dominating the participants’ motivations. It was also noted that negative emotions decreased, with positive emotions becoming predominant.

Table 6. Mean values of the variables across the three assessed time points.

Variables	Before the Pandemic	During the Pandemic	After the Pandemic
Push factors	4.16	1.80	4.13
Pull factors	4.00	4.20	3.67
Positive emotions	3.31	2.82	3.67
Negative emotions	2.98	3.46	2.82

Note. Scale ranging from 1 to 5.

provides a summary of the changes in the mean values of the variables under study across the three time points.

Following the results presented in Table 6, it was deemed pertinent to conduct a fourth study with the entire sample to determine whether significant differences exist in the variables under investigation based on the timing of data collection.

4.4. Study 4—Multigroup Analysis

4.4.1. Sample

The fourth study brought together participants from the previous studies (n = 1503). The sociodemographic characteristics are presented in

Table 7. Sample characterization.

Sociodemographic Variables	n (%)
Sex
Male	712 (47.4%)
Female	791 (52.6%)
Age group (M = 35.10, SD = 12.59)
25 years old and below	498 (33.1%)
Between 26 and 35 years old	276 (18.4%)
Between 36 and 45 years old	341 (22.7%)
46 years old and over	388 (25.8%)
Reason for travel
Work	481 (32.0%)
Leisure	773 (51.4%)
Visiting Family	249 (16.6%)
Travel Companions
Alone	603 (40.1%)
Couple	273 (18.2%)
Family	319 (21.2%)
Friends	308 (20.5%)

.

4.4.2. Validation of Research Hypotheses

To compare the statistical models across the different time points at which the studies were conducted and to identify significant differences among them, multigroup structural equation modeling (MGSEM) was performed. This statistical technique allowed for testing whether the theoretical model applied similarly to the different groups by comparing the structure of relationships between variables across the three distinct time points. MGSEM enables the assessment of whether the relationships between variables remain consistent or varies depending on the time when the data were collected (

Table 8. Structure of the measurement model.

Model	χ2(df)	CFI	GFI	RMSEA	SRMR	Δχ2	p
Before the pandemic	3.78(513)	0.90	0.81	0.07	0.05	-	-
During the pandemic	3.61(180)	0.93	0.90	0.07	0.06	-	-
After the pandemic	4.94(291)	0.79	0.82	0.08	0.08	-	-
Configural invariance	6638.00(164)	0.90	0.87	0.06	0.06	-	-
Metric invariance	5253.87(90)	0.93	0.85	0.06	0.05	1384.13(74)	0.001
Strict invariance	4690.37(74)	0.90	0.88	0.08	0.07	563.5(16)	0.001

).

The configural invariance model was conducted to assess whether the model structure remained consistent across the three time points. Metric invariance was tested by constraining the factor loadings, while strict invariance was examined by imposing constraints on the variances and covariances of the errors [Δχ²λ₍₁₆₄₎ = 6638.00, p < 0.001; Δχ²i₍₉₀₎ = 5253.87, p < 0.001; Δχ²Cov₍₇₄₎ = 4690.37, p < 0.001].

The results indicate that, although the relationships between the observed variables and the latent factors may vary across groups, the basic configuration of the model remains consistent. Furthermore, it was observed that, when factor loadings are constrained to be equal across groups, the model assumes that the observed variables hold the same relative importance within each group. A significant Δχ² result indicates a statistically significant difference between the configural model (less restrictive) and the metric model (more restrictive), suggesting that the factor loadings are not identical across groups. Strict invariance indicates significant differences when constraints are imposed, implying that the error variances and covariances are not identical between groups. The high and significant Δχ² values suggest that transitioning from a less restrictive model to a more restrictive one (configural → metric → strict) results in a significant deterioration in model fit.

The significance of positive and negative emotions on the push and pull factors was assessed using a MANOVA after verifying the assumptions of multivariate normality and homogeneity of variance–covariance matrices. The multivariate analysis of variance demonstrated that positive emotions had a significant effect on the multivariate composite [Pillai’s Trace = 0.116; F_(25,184) = 3.129; p < 0.001; η²p = 0.058; Power (π) = 0.871]. Regarding negative emotions, it was determined that their effect is both high and significant, as is the power of the test [Pillai’s Trace = 0.529; F_(19,184) = 2.125; p < 0.001; η²p = 0.929; Power (π) = 0.993].

Subsequently, an ANOVA analysis was conducted for each variable under study, revealing statistically significant differences in positive emotions [F_(2,1500) = 26.415, p < 0.001; Hypothesis 3a: Positive emotions varied depending on when the data was collected] and negative emotions [F_(2,1500) = 26.800, p < 0.001; Hypothesis 3b: Negative emotions varied depending on when the data was collected] based on the timing of data collection. These findings supported the confirmation of the third research hypothesis (Hypothesis 3: Emotions varied depending on when the data was collected;

Table 9. Comparison of the mean values of the variables under study based on the timing of data collection.

	Moment 1		Moment 2		Moment 3
	M	SD	M	SD	M	SD	F	Sig.
Positive emotions	3.61	0.83	3.35	0.66	3.57	0.49	26.415	0.001 **
Negative emotions	2.45	0.52	2.68	0.64	2.47	0.66	26.800	0.001 **
Push factors	4.16	0.85	4.17	0.84	4.15	0.65	0.033	0.968
Pull factors	3.86	0.83	3.86	0.83	3.77	0.61	2.030	0.132

Note. Moment 1 = before the pandemic; Moment 2 = during the pandemic; Moment 3 = after the pandemic; M = mean; SD = standard deviation; F = F-Snedecor ANOVA; Sig. = Significance; ** p < 0.001.

. Conversely, it was observed that travel motivations, represented in this study by the push and pull factors, did not differ significantly based on the timing of data collection, preventing the validation of the fourth research hypothesis (Hypothesis 4: Motivations to travel differed significantly depending on when the data was collected).

Throughout the four studies conducted, it was observed that emotions—both positive and negative—impacted the factors influencing destination choice and varied depending on the timing of data collection: before, during, and after the COVID-19 pandemic. On the other hand, it was found that the push and pull factors were not affected by the temporal variable (Hypothesis 4a: Push factors differed significantly depending on when the data was collected; Hypothesis 4b: Pull factors differed significantly depending on when the data was collected).

5. Discussion

This research demonstrated that emotions indeed have a determining impact on the push and pull motivational factor for traveling. The results show that positive emotions have a decisive impact on positive pull factors, while negative emotions unambiguously influence pull factors. Similar results were presented by Io [19], who not only confirmed the relationship between push and pull factors and the travelers’ emotions, but suggested that these factors can generate contradictory emotions. The results also confirm that the economic crisis influenced the choice of destination. Moreover, it was found that a greater influence of the pandemic crisis impact on the choice of destination corresponds to a lesser desire to explore new places and cultures. Similar results reported by Li et al. [50] show that tourists preferred destinations less affected by COVID cases. Additionally, it was found that there was a slight change in emotions (positive and negative) in the three moments of this study, namely during the COVID-19 crisis. The results demonstrate that positive emotions were indeed affected during the pandemic, and negative feelings regarding traveling increased during this period. These findings are corroborated by the study by Wu and Lau [33] which shows that during COVID-19 a spectrum of negative emotions hovered over visitors, due to the perception of the seriousness of the situation. Finally, the results show that travel motivations changed slightly when comparing the three moments: before, during, and after the pandemic crisis. Furthermore, there was a consistency between the push and pull factors, regardless of when the data was collected. Although no similar studies were found, Rice and Khanin [59] demonstrated that intrinsic and extrinsic motivational factors are determinant for tourists returning to the same destination instead of seeking new experiences. This means that, if the pull and push factors are consistent over several visits, the probability of returning is greater.

Our conclusions indicate that, although push and pull factors have remained stable over time, their underlying motivations have evolved, particularly concerning sustainability. Before the pandemic, tourism was largely driven by leisure and cultural curiosity, with limited emphasis on sustainable considerations. However, during the pandemic, travel restrictions and increased environmental awareness led to a significant rise in the preference for low-impact tourism, rural getaways, and environmentally conscious destinations. This shift persisted in the post-pandemic period, with sustainability becoming a more prominent factor in destination choice.

Emotions also play a crucial role in shaping travel behaviors oriented toward sustainability. Negative emotions, such as fear of crowded places and health concerns, reinforced preferences for outdoor and low-density destinations, while positive emotions associated with immersion in nature, well-being, and cultural authenticity strengthened the appeal of sustainable travel choices.

The implications for the tourism industry are substantial. Destinations seeking to attract post-pandemic travelers should emphasize sustainability certifications, eco-friendly accommodations, and responsible tourism initiatives. Furthermore, policymakers should integrate sustainable development goals (SDGs) into tourism strategies, ensuring that growth aligns with environmental conservation and community well-being.

6. Conclusions

This study examined the influence of positive and negative emotions on push and pull motivational factors for travel before, during, and after the COVID-19 pandemic. The findings indicate that emotions play a determining role in the tourists’ decision-making processes, with positive emotions predominantly associated with pull factors and negative emotions influencing push factors.

Before the pandemic, push factors were primarily driven by motivations such as leisure, the pursuit of new experiences, and the desire to escape routine, whereas pull factors were related to destination attributes, particularly cultural, and natural attractions. During the pandemic, health and safety concerns became central in destination selection, leading to a shift in travel motivations, with an increased preference for low-density destinations and nature-based tourism. In the post-pandemic period, pre-pandemic motivations gradually resumed, albeit with a heightened emphasis on sustainability and well-being.

The findings reveal that, despite emotional fluctuations across the three analyzed periods, push and pull motivational factors remained relatively stable. This suggests that, while emotions influence the intensity of motivation, they do not alter their fundamental structure. A comparative analysis of the three periods further demonstrated that negative emotions had a more pronounced impact during the pandemic, leading to a significant reduction in travel intentions. Conversely, positive emotions were a determining factor in the post-pandemic recovery of tourism. The health crisis also underscored the need for adaptations in tourism offerings to address the travelers’ concerns, particularly regarding safety protocols and sustainable tourism practices.

Furthermore, this study highlights the evolving role of sustainability in travel motivations. While emotions continue to influence push and pull factors, sustainability has emerged as a crucial determinant of destination choice in the post-pandemic era. The pandemic catalyzed a shift towards low-impact, environmentally conscious travel, reinforcing the need for integrating sustainability into tourism management. As travelers become increasingly aware of environmental and social responsibilities, future research should explore how these motivations continue to evolve and whether sustainability remains a primary concern in long-term travel behavior. These results reinforce the critical role of emotions in travel decision-making and demonstrate that, even in the face of external crises, motivational factors remain a fundamental element shaping tourist behavior. The findings suggest that destinations prioritizing sustainable practices will be more resilient in the face of future global challenges.

6.1. Theoretical and Practical Contributions

Theoretically, this study contributes to deepening the understanding of the interaction between positive and negative emotions and push and pull factors in tourism. It highlights those emotions serve as key mediators in shaping travel motivations, with positive emotions strongly linked to pull factors and negative emotions influencing push factors. By analyzing three distinct contexts—pre-pandemic, pandemic, and post-pandemic—the research adds a temporal perspective to theories of travel motivations, demonstrating how external crises, like COVID-19, can shift emotional drivers.

From a practical perspective, the findings provide actionable insights into the emotional foundations of push and pull factors, enabling marketers to design campaigns that align with the travelers’ evolving emotional states and motivations. Furthermore, this study emphasizes how destinations can adapt their offerings during crises, such as by prioritizing health safety measures and promoting low-density, nature-focused attractions, as seen during the pandemic. These insights underline the importance of emotional considerations in tourism management and strategy development.

Building on this, the pandemic’s impact underscores the critical need for continued research on tourist motivations, particularly in crisis contexts. The future of tourism is increasingly tied to sustainability, emotional well-being, and the adaptability of destinations. Identifying emerging trends, such as the rise of conscious tourism and the quest for meaningful experiences, will be pivotal in shaping effective policies and practices for a resilient and innovative tourism sector.

6.2. Limitations and Suggestions for Future Studies

The main limitation is related to the fact that the data are self-reported, which prevents the generalization of the results. Although this study provides valuable longitudinal information, the timing of the data collection may have influenced the participants’ emotional states and responses, potentially introducing temporal bias. The dichotomy between positive and negative emotions can simplify the more complex emotional experiences that travelers go through.

Another limitation to note is the fact that this study was carried out in an urban tourist destination that is highly sought after by visitors, which may have reduced the feeling of security, when compared to nature and less crowded destinations. Thus, it is suggested that future investigations analyze the interaction of emotions and push–pull factors in different cultural contexts and environments, as well as with different generations, to increase the robustness of the results. It is also considered pertinent to explore a broader set of emotions, including mixed or ambivalent feelings, as this may provide a more comprehensive understanding of their influence on travel motivations. Future researchers should also explore various levels of positive and negative emotions regarding experiences at the destination. It will also be pertinent to develop qualitative research. Future studies should also investigate how other types of crises (e.g., economic crises, political instability) impact the interplay between emotions and travel motivations.

The fact that gender proportions differed across the three studies may have influenced emotional responses and travel motivations, potentially introducing bias into the results. Therefore, it is recommended that future studies implement stratified sampling techniques to ensure a more balanced gender representation. Furthermore, research specifically examining gender differences in travel motivations could provide deeper insights into how men and women approach travel differently across various socioeconomic and crisis-related contexts.