24 MODELLING TOURISM BEHAVIOUR – Contributions by Antonia Correia
Introduction
Tourist consumer behaviour is derived from consumer behaviour research but is distinguished from that major study area due to the paradoxical characteristics of the tourist product (Correia, 2000). Buying a trip or a holiday is as demanding an effort as it is an enthusiastic pleasure! (Correia, 2009). It is demanding and requires a high level of involvement from the individual because it involves deciding on many aspects, in a context of uncertainty that brings about risk and anxiety. Most of the time, tourists are not familiar with the place they are travelling to, the hotel they are staying at, the activities they are enrolling in, and the transport they are being driven on, but they still need to decide (Correia, 2009).
The multifaceted decision-making process and intricacy of the tourism product (and its concepts) lead to a highly composite study, which is also as demanding as it is enthusing for tourist behaviour researchers. Furthermore, tourism is an experience and thus involves intricate emotions. In fact, the emotional component is transversal to the travel experience as it is present before, during and after each and every trip. Before travelling, people put great effort into collecting information about the tourist destination and day dream for weeks, months, even years, about their holidays and their travel experiences. Tourists plan their travels in advance and fantasise about their experiences just before leaving home and during travelling because tourists interact with the destination, in a mutual influence process which demands great involvement from the participant. After travelling, the post-purchase/experience phase is long-lasting, as tourists recall their travel experiences for ages, remembering their holidays with friends and family, telling stories and adventures to others, (re)seeing photographs, and writing travelogues (Pearce, 2005). The overall experience in a destination is the basis for tourists’ satisfaction and their image of that destination. Considering two main aspects of interest in consumer behaviour, namely the decision-making/choice and satisfaction, these concepts present also a particularity, as tourist expectations influence tourist satisfaction. Products’ quality attributes are easy to measure as they are tangible; tourism experiences are evaluated as a whole and incorporate not only destination attributes but also personal feelings/reactions and travelling consequences/benefits.
Further, tourism is not only an economic business but also a social one, a “stage” where many people interact, and an area where psychology plays a great role. Tourism is what Pearce (2005:11) calls “a people-to-people business”, so tourist behaviour incorporates social, psychological, and economic analysis while consumer behaviour research has had a strong economic and business focus.
These specificities of tourism purchase-consumption behaviour brought a very special challenge to the analysis. In fact, choices are directly or indirectly influenced by a plethora of variables and as such are feasible to be modelled. Nevertheless, models are simplifications of reality that analyse the impact of some variables on consumer behaviour when everything else remains constant. Over the last 20 years we have tested models of tourists’ behaviour with different variables and different methodologies and there is still a lot to be done; nevertheless, my team’s contributions are summarized here to allow to keep on building on a reality that is impossible to be completely modelled. Probably this is the reason why we decided to work on this.
Over the last 21 years we built on:
Conceptual and empirical tourist decision models, considering the different stages of tourists’ processes:
- Pre-decision,
- Decision
- On-site experience
- Post-experience.
to answer the questions of:
- Why people travel and what kind of needs they intend to achieve and satisfy;
- To what extent tourists’ social life influences the decision;
- How they choose, and what satisfaction and benefits they can get from their choices.
as tourism knowledge has to be built to help the industry to develop.
Conceptual and empirical tourist decision models
Correia (2002) presents a conceptual model with three sequential and organized stages: (i) pre-decision; decision; and post-purchase evaluation. The first, or pre-decision phase, relies on such conditions as predisposition to external stimuli, communication access between the consumer and the main sources of information, and ultimately, consumer learning. The learning process is made of receiving, filtering, and processing information about the options available. This learning process is fed by previous experiences, perceptions, motivations, and preferences. The second, or the decision phase, assumes their preferences and the traditional constraints of income and time available. The third, the evaluation of the post-purchase phase, is the consequence of other stimuli that influence the choice process and presupposes consumer satisfaction with the selected destination. This phase is important in evaluating the varying probabilities of repeating/recommending and/or becoming loyal. The conceptual model is developed with 18 variables and in three stages. Later, Correia and Crouch (2004) tested the model proposed by Correia (2002) by means of exploratory data analysis and concluded that the three stages defining the decision processes of international tourists travelling to the Algarve in the south of Portugal eventuate that decision processes vary across nationalities. Correia and Pimpão (2008) tested a two-stage model (pre-purchase and post purchase) by means of structural equation analysis with Portuguese tourists travelling to South America and South Africa. This model was tested with two paired samples, the first collected at the time of departure to the destination and the second collected at the time of return to Portugal from the same tourists. The model was developed with 18 hypothesis and eight variables.
Demir, Kozak and Correia (2011) tested an overall model of tourists’ decision processes in five stages. This model, with motivations, information search, evaluation of the alternatives, holiday experience and post-purchasing behavioural intentions was tested in Turkey. This model is grounded on 10 hypotheses. Demir, Kozak and Correia (2014) tested the above-mentioned model within domestic tourists in Turkey to conclude that motivations, expectations, and satisfaction are of utmost importance in understanding tourists’ choices. Conceptual contributions are also found in Correia, Kozak and Tão (2014), who, based on prospect theory, stress that decisions are dynamic and risky and are constrained by individual and social contexts of tourists, from which emotional and cognitive factors play a role in the final choice. Furthermore, Correia, Kozak and Ferradeira (2013) tested the empirical impact of motivations on tourists’ satisfaction. This research, based on multivariate techniques, suggests that overall satisfaction reflects the tourist assessment of push and pull dimensions of satisfaction. Later Correia and Kozak (2019) developed a conceptual model to understand the full process of browsing and shopping in tourism contexts. Twenty research proposals were proposed to be tested later in which motivations, personal factors, emotions, enjoyment, involvement, opinion leadership, market stimulus, preferences, social value, variety of selection, time, price, satisfaction, and loyalty appear interconnected.
Table 1 summarizes the aims, variables and methods used in each of the models presented in this section.
Table 1. Models of tourists’ decision processes.
|
References |
Aims |
Methods |
Variables |
|
Correia (2002) |
This study presents a conceptual model with three stages, pre-decision, decision, and post-decision. |
Conceptual |
Information sources, evaluation of alternatives, motivations, perceptions, satisfaction and behavioural intentions |
|
Correia and Crouch (2004) |
This study empirically tests tourists’ decisions processes of international tourists travelling to Algarve, Portugal. |
Multivariate statistics |
Information sources, evaluation of alternatives, motivations, perceptions, satisfaction and behavioural intentions |
|
Correia and Pimpão (2008) |
This study estimates the decision-making processes of Portuguese tourists traveling to South America and Africa destinations. |
Structural equation models |
Information sources, motivations, perceptions, satisfactions and behavioural intentions |
|
Demir, Kozak and Correia (2011) and Demir, Kozak and Correia (2014) |
This study proposes and tests a model covering the five stages of decision processes of domestic and international tourists in Turkey. |
Structural equation models |
Motivations (push and pull), information search, evaluation of alternatives, experience and behavioural intentions. |
|
Correia, Kozak and Ferradeira (2013) |
This study develops the concept of push and pull satisfaction and correlates motivations with satisfaction. |
Multivariate statistics |
Motivations and satisfaction |
|
Correia, Kozak and Tão (2014) |
This research develops a conceptual model based on prospect theory that suggests that emotion, cognitions and affect as well as intuition and perception influence decision making. |
Conceptual |
Emotions, affect, cognitions, intuitions and perceptions |
|
Correia and Kozak (2019) |
This study proposes a conceptual model able to explain tourists’ shopping behaviour. |
Conceptual |
Motivations, personal factors, emotions, enjoyment, involvement, opinion leadership, market stimulus, preferences, social value, variety of selection, time, price, satisfaction and loyalty |
Bearing in mind that models are simplifications of the reality, our contributions in each of the stages of decision models are outlined in the following sections.
1. Pre-decision
The pre-decision stage is conditioned by the reception of stimuli from the external environment; the communication that takes place between the consumer and the main channels; the learning process, that is, the way in which they receive information, filtering what interests them, in order to develop a list of preferences. At this stage it is necessary to consider the conditioning factors of the decision to travel. The variables included are motivations, perceptions, preferences and choices (Correia, 2000).
Correia and Crouch (2003) considered motivations and perceptions as multidimensional constructs and depict the main factors by means of factorial analysis, explaining motivations and perceptions. This research stresses that motivations and perceptions vary with the nationality of the tourists travelling to the Algarve, with non-parametric tests. Later, Serra, Correia and Rodrigues (2014a), based on a longitudinal data base of low-cost tourists travelling to the Algarve, tested the heterogeneity of motivations across the years and by nationalities to explain international tourism demand. This research emphasizes the importance of the inclusion of behavioural and motivational variables in econometric models of tourism demand. This research explains international tourism demand with seven hypotheses.
Furthermore, Correia, Oom do Valle and Moço (2007) prove that perceptions of tourism destinations are formed based on push and pull factors. This research was developed with three hypotheses with Portuguese tourists travelling to exotic places.
Considering the different experiences tourism may proportionate, Madeira, Correia and Filipe (2019) present a conceptual model to analyse what drives tourists to visit wineries and how this visit may contribute to their perceptions of wine destinations. This model, aside from the multidimensionality of motivations, tested 10 hypotheses to depict tourist behaviour in emergent wine destinations, as is the case of Lisbon, in Portugal.
Table 2 summarizes the aims, variables and methods used in each of the models presented in this section.
Table 2. Modelling pre-decision stage.
|
References |
Aims |
Methods |
Variables |
|
Correia and Crouch (2003) |
This study investigates tourist perceptions and motivations in the Algarve. |
Multivariate statistics |
Motivations and perceptions |
|
Correia, Oom do Valle and Moço (2007) |
This study proposes an integrated approach to understand tourist motivations and perceptions about exotic destinations. |
Structural equation models |
Motivations and perceptions |
|
Serra, Correia and Rodrigues (2014a) |
This study aims to estimate tourism demand, measured by overnights stays, by country of residence within a longitudinal database. |
Multivariate statistics |
Motivations, socio-demographics, intentions and lagged satisfaction |
|
Madeira, Correia and Filipe (2019) |
This research aims to understand what drives tourists to visit wineries and how this experience may improve the image, the intention to return and retain tourists. |
Structural equation models |
Motivations, experience, brand equity, satisfaction and image |
2. Decision
Assuming a certain budget available for tourist consumption, the problem of the different choices of tourist consumers will arise within their budget set for travel. This phase comprises the evaluation of the preferences based on which they decide. The variables included are perceptions, preferences, restrictions and purchase (Correia, 2000).
Correia, Santos and Barros (2007) use a logit model to analyse the decision of Portuguese tourists travelling to Latin America. This model comprises nine variables and nine hypotheses to conclude that awareness and facilities available in Latin America as well as the budget available explain the probability of travelling to Latin America. Silva and Correia (2008) analyse the decision to participate in leisure travel activities with qualitative methods to conclude that the decision to travel for leisure derives from the tourist’s causal historical wave, and that most of the factors which influence the decision are aggregate ones rather than individual.
Returning to econometric models, Barros, Butler and Correia (2008) show that the decision to go on holidays is facilitated by the social and economic profile of the tourists, their previous experience, and the attributes of the destinations considered, by means of a mixed logit model.
Correia, Pimpão and Crouch (2008) introduce the variables risk and novelty seeking as moderators of decision to travel. A dual process was suggested, as first tourists are willing to take risks, but they are also afraid of uncertainty. The uncertainty and risk were revisited through a qualitative research with Silva, Reis and Correia (2010) to explain different decision-making styles. It is concluded that although risks are unknown to decision makers to some extent, they may influence tourist choices, expressed by delaying, postponing or avoidance behaviours. Decisions are, however, context dependent and unique, deriving from individuals’ own life settings and backgrounds; thus, motivations, travel companion, family support and reduced costs of participation may invert the negative impact of risks and facilitate the decision.
Considering that previous research suggested that decisions are heterogeneous across nationalities or countries of residence, Correia, Kozak and Ferradeira (2011) introduce the cultural traits of Hofstede (1980) to explain decision-making styles.
Correia, Pimpão and Tão (2012), via a stated preference experiment, analyse the willingness to pay for frills while travelling in low-costs flights (Table 3). The results reveal not only the implicit values of service attributes, but also the preference differences in attributes between passengers. In order to estimate daily spending, Serra, Correia and Rodrigues (2015a) use yielding preferences to understand the most profitable international markets in the Algarve.
Table 3 summarizes the aims, variables and methods used in each of the models presented in this section.
Table 3. Modelling decision stage.
|
References |
Aims |
Methods |
Variables |
|
Correia, Santos and Barros (2007) |
This study analyses the decision of Portuguese tourists traveling to Latin America. |
Discrete choice models |
Budget, pull motivations, socio-demographics, information, intentions to return, time, travel experience and expectations |
|
Silva and Correia (2008) |
This study analyses facilitators and constraints Portuguese residents face when making decisions for leisure travel participation. |
Content analysis |
Individual and social contexts |
|
Barros, Butler and Correia (2008) |
This study analyses the decision of travelling to Africa of Portuguese tourists. |
Discrete choice models |
Budget, pull motivations, socio-demographics, information, intentions to return, time, travel experience and expectations |
|
Correia, Pimpão and Crouch (2008) |
This study analyses how risks and novelty seeking moderates’ tourists’ decisions. |
Structural equation models and multivariate analysis |
Novelty seeking, risk, socio-demographics, travel experience and familiarity |
|
Silva, Reis and Correia (2010) |
This study aims to analyse how risks influence Travel Decision Making (TDM). |
Content analysis |
Risks, socio-demographics and decision-making styles |
|
Correia, Kozak and Ferradeira (2011) |
This study relates cultural traits with tourists’ decisions. |
Structural equation models and multivariate analysis |
Cultural traits and decision-making styles |
|
Correia, Pimpão and Tão (2012) |
This study aims to analyse the willingness to pay more to have frills in low-cost flights. |
Stated preference experiment |
Fare, baggage fee, sports equipment fee and meal price |
|
Serra, Correia and Rodrigues (2015a) |
This study analyses the yield potential of different markets’ preferences. |
Multivariate analysis |
Daily spending, average stay and preferences |
3. On-site experience
After travelling to the destination, tourists live their on-site travel experiences. Travel experiences are materialized in length of stay, spending and activities undertaken at the destination.
Length of stay was modelled by Barros, Correia and Crouch (2008), Barros, Butler, Correia (2010) and Bavik, Correia and Kozak (2021) in different settings and with different models. These papers contribute to building on determinants of demand but also on discussing the best methods to estimate the length of stay of tourists. These papers concluded that the model to be used depends on the distribution of the data, with survival and Poisson models being those that best fit the data.
Overnight stays were estimated by Serra, Correia and Rodrigues (2014b) with aggregate data acting as proxies of tourism demand, through panel data. In light of experiences at the destination, Correia and Kozak (2016) propose and test a conceptual model that assesses how price consciousness and perceived utility drive attitudes in street markets, also contributing to explaining how this experience influences tourist satisfaction and future intentions. This is in the same vein, but now supported by game theory.
Kozak, Correia and del Chiappa (2017) analyse how utilitarian and non-utilitarian bargaining values in tourism contexts moderate the intentions of tourists to return to the same destination to bargain.
In the context of wine tourism Madeira, Correia and Filipe (2019) define the fundamentals of wine tourism experiences within the triad of hosts, guests and places proposed by Pine and Gilmore (1998).
Table 4 summarizes the aims, variables and methods used in each of the models presented in this section.
Table 4. Modelling on-site experience.
|
References |
Aims |
Methods |
Variables |
|
Barros, Correia and Crouch (2008) |
This study analyses the length of stay of Portuguese Tourists in Latin America. |
Survival models |
Past behaviour, travel companion, satisfaction, behavioural intentions, economic and socio-demographic variables, motivations, length of stay and tourist’s spending’s |
|
Barros, Butler and Correia (2010) |
This study analyses the length of stay of golf tourists in the Algarve. |
Several duration models were presented for comparative purposes |
Past behaviour, travel companion, satisfaction, behavioural intentions, economic and socio-demographic variables, motivations, length of stay and tourist’s spending’s |
|
Serra, Correia and Rodrigues (2014b) |
This study estimates international tourism demand in Algarve across the years. |
Panel data |
Overnight stays and macroeconomic variables |
|
Serra, Correia and Rodrigues (2015b) |
This research aims to estimate the determinants of international tourists’ expenditure in the Algarve. |
Panel data |
Daily tourist expenditures, motivations, past behaviour, travel companions, overall satisfaction, return intention and socio-demographic variables |
|
Correia and Kozak (2016) |
This study proposes and tests a conceptual model to explain tourists’ attitudes in shopping markets. |
Structural equation analysis and multigroup |
Behavioural intentions, price consciousness, price utility, moral value and satisfaction |
|
Kozak, Correia and del Chiappa (2017) |
This study analyses how bargaining values in tourism contexts moderate the intentions of tourists to return to the same destination to bargain. |
Order probit model and marginal effects |
Behavioural intentions, transactional utility value, emotional value, social value, gender differences, satisfaction and experience |
|
Madeira, Correia and Filipe (2019) |
This study aims to define a conceptual model to explain wine experiences. |
Conceptual |
Motivations, involvement, satisfaction, winery service attributes, intentions and loyalty |
|
Bavik, Correia and Kozak (2021) |
This research aims to understand why Chinese tourists in Macau stay for a shorter period. |
Poisson regression model and marginal effects |
Overnight stays, availability of time, package, reservation time, companion, repeat times, spending’s, recommendation and pull motivations |
4. Post-consumption behaviour
Post-purchase choice assessment results from other stimuli that influence the choice process and presupposes the assessment of satisfaction derived from the “consumption” of a given destination. This phase is also important in assessing the different probabilities of repeat purchases of a specific destination. Some authors argue that despite a high level of satisfaction with a particular destination, they did not repeat the same purchase because they wanted to discover new destinations. This premise could be valid for market segments that will be classified as “risk-takers”, while others tend to repeat the destination depending on their degree of satisfaction, being loyal to the destination.
Tourist’s intentions to repeat the same destination are analysed with different models and in different contexts and within different markets. For instance, Correia, Barros and Silvestre (2007) use a random parameter logit model to analyse what drives golf tourists to return to play golf in the Algarve. Do Valle, Correia and Rebelo (2008) tested a logit model to explain the probability of returning to the same destination as a function of motivations, expectations, travel characteristics and the tourist’s socio-demographic profile. Correia and Pimpão (2013) use a mixed logit model to test the intention to return to the same destination. Silva and Correia (2017) test a structural equation model
to understand the relation the tourists established with the destination considering emotions and place attachment. The relation the tourists established with the destination was also analysed by Correia, Oliveira and Pereira (2017), regressing place attachment through an order probit model with emotions. Still mixing emotions and post-purchase intentions Dias, Correia and Cascais (2017) present a content and pictorial analysis of messages left by tourists that persist in visiting the Algarve. This research underlines how the place is perceived based on the five senses, and what messages were kept in their memories. Keeping on building on sense of place, Dias, Ribeiro and Correia (2013) analyse the sense of place meaning within online tourist vacation rentals. Also to understand behavioural intentions based on experiences, Correia, Kim and Kozak (2020) use a configurational design of four conditions (fuzzy set analysis) to understand how food attributes and restaurant settings influence tourists intentions to recommend gastronomic experiences in Hong Kong.
As concerns tourists’ recommendations, Pimpão, Correia, Duque and Zorrinho (2016, 2018) develop a conceptual and test a model of propensity to be ambassadors of a hotel chain and be loyal to this chain. These models show that commitment, trust and word of mouth are critical in enacting social and that recency, frequency and spending behaviour define loyalty patterns.
The life cycle loyalty of tourists with destinations were also analysed with duration models and discrete choice analysis. Correia, Zins and Silva (2015) use a Poisson model to analyse the past frequency of revisiting Portugal and the duration of this pattern. Whereas Artal-Tur, Correia, Serra and Osorio-Caballero (2019) test the relation of tourists and destinations over the time and how this shapes their repeat choice behaviour.
Table 5 summarizes the aims, variables and methods used in each of the models presented in this section.
Table 5. Modelling post-consumption stage.
|
References |
Aims |
Methods |
Variables |
|
Correia, Barros and Silvestre (2007) |
This study aims to estimate the probability of golfers to repeat Algarve to play golf. |
Discrete choice analysis |
Intention to return, motivations, expectations, travel characteristics and tourists’ socio-demographic profile |
|
Do Valle, Correia and Rebelo (2008) |
This study proposes a logit model to explain the probability of international tourists return to Algarve. |
Discrete choice analysis |
Intention to return, motivations, expectations, travel characteristics and tourists’ socio-demographic profile |
|
Dias, Ribeiro and Correia (2013) |
This study aims to explore how the concept of sense of place is verbalized by tourists’ online reviews. |
Content analysis |
Sense of place, trust and commitment |
|
Correia and Pimpão (2013) |
This study aims to estimate the tourists return intentions. |
Mixed logit models |
Intention to return, travel characteristics, tourists’ socio-demographic profile and satisfaction |
|
Correia, Zins and Silva (2015) |
This study aims to analyse why tourists persist in repeating the same destination. |
Poisson Model |
Number of visits to the destination, socio-demographic characteristics, tripographic characteristics, expectations, satisfaction, behavioural intentions, recency, monetary value and heterogeneity |
|
Pimpão, Correia, Duque and Zorrinho (2016) |
This study aims to assess how effective loyalty programs are in contributing to retain guests for hotels. |
Bass Model |
Loyalty, reservations, innovation, imitation and conformity |
|
Correia, Oliveira and Pereira (2017) |
This study aims to assess place attachment as an emotional state. |
Order probit model |
Duration of the relationship with the destination, emotions and socio-demographics |
|
Silva and Correia (2017) |
This study examines the tourist/destination relationship taking into account emotions and place attachment. |
Structural equation models |
Affective component, satisfaction, trust, place attachment and commitment, cognitive and conative behavioural intentions |
|
Dias, Correia and Cascais (2017) |
This study aims to explore emotions, memories and experiences tourists share. |
Content analysis |
Emotions and memory |
|
Pimpão, Correia, Duque and Zorrinho (2018) |
The study aims to define a model of social technology diffusion, comprising constructs that explain guests’ likelihood of recommending their hotel loyalty program to their peers. |
Structural equation models |
Satisfaction with user-to-user interactivity, satisfaction with user identifiability, commitment-trust, word-of-mouth and intentional sharing behaviour |
|
Artal-Tur, Correia, Serra and Osorio-Caballero (2019) |
This study aims to understand tourist behaviour, choices and tourism experiences evolve along a life cycle built between repeating tourists and destinations. |
Mixed logit models |
Socio-demographics, length of stay, travel frequency, package travel, tourism product, destination, trip purpose, type of accommodation, country of residence and satisfaction |
|
Correia, Kim and Kozak (2020) |
This study aims to investigate the function of local food attributes and satisfaction with local food in accounting for recommendation to others by using the configuration design, which is supported by fuzzy set theory. |
Fuzzy set |
Food quality, food uniqueness, food tradition and food service quality |
Conclusion
Over these 21 years, we have tried to contribute to answering the following questions:
Why people travel and what kind of needs they intend to achieve and satisfy.
Decisions to travel are social and individually driven; tourists are willing to be pampered, to learn new things, to relax, to have relief from daily life, but they are also willing to socialize and get the recognition of their peers.
To what extent tourists’ social life influences the decision.
Tourism is a social experience to share with companions or peers. Our research suggests that individuals with experience of travelling since childhood are more likely to travel. That means that previous experience moderates tourists’ decisions to travel. Also, tourists tend to behave differently while on holidays, as such experiences such as bargaining at open markets are allowed.
How they choose, and what satisfaction and benefits they can get from their choices.
Tourists decide with uncertainty but are willing to take the risk, with the constraints of time and budget available. Emotions, memories, experiences and pleasure are the benefits they could get from a experience that is only pleasant and satisfactory if managers are able to surprise tourists with experiences that are above their expectations.
Within this context, it is true that modelling tourist decision processes is limited as all the variables seem to contribute to the explanation of a certain decision or attitude. As Pearce (2011) postulates, tourists decision models are an intermingled orchestra where all the variables contribute to the explanation of their behaviour. Methodologically speaking, this orchestra could be represented by a configurational design of a fuzzy set choice experiment, where the decision is analysed assuming that the set of moderators considered may vary simultaneously.
Still bearing the orchestra model in mind, we propose that stages of decision could be analysed in an intermingled way. Diagrammatically, we propose a dynamic model of tourist decision processes that are inspired by the orchestra model of Pearce (2011) and based on the research did by our team over the years. We put forward a dynamic and organized model of tourist decision processes, as can be seen in Figure 1.
Tourists choose based on their intrapersonal values (personality, values and experience), interpersonal values (culture, companion, families, social contexts) and macrosystem values (culture, demographics, time and income). All these values, destination attributes and information available lead to expectations and motivations as well as to the identification of constraints and facilitators on choosing a certain destination. Expectations and destination image lead to perceptions and ultimately to choice.
The experience is assessed based on emotions, cognitions, senses and the relationships tourists which develop with the destination and to these components proposed by Pearce (2011), we added memories and contexts. The tourists’ response to the tourism experience are intermingled and harmonic. Their responses are materialized in pleasure, senses arousal, trust, commitment, place attachment and authenticity. Tourists’ responses to holiday experiences continue after the travel, and again post-experience evaluation is explained by emotions, satisfaction, behavioural intentions, relationships with the destination. Loyalty and ambassadors of the destination are the expected outcomes when the holidays come to an end if holidays ended.
Written by Antonia Correia, University of Algarve, Portugal
Read Antonia’s letter to future generations of tourism researchers
References
Artal-Tur, A., Correia, A., Serra, J., & Osorio-Caballero, M. I. (2019). Destination Choice, Repeating Behaviour and the Tourist-Destination Life Cycle. Trends in Tourist Behavior: New Products and Experiences from Europe, 175.
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Barros, C. P., Butler, R., & Correia, A. (2010). The length of stay of golf tourism: A survival analysis. Tourism management, 31(1), 13-21.
Barros, C. P., Correia, A., & Crouch, G. (2008). Determinants of the length of stay in Latin American tourism destinations. Tourism Analysis, 13(4), 329-340.
Bavik, A., Correia, A., & Kozak, M. (2020). What makes our stay longer or shorter? A study on Macau. Journal of China Tourism Research, 1-18.
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Correia, A., Kim, S., & Kozak, M. (2020). Gastronomy experiential traits and their effects on intentions for recommendation: A fuzzy set approach. International Journal of Tourism Research, 22(3), 351-363.
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