Impact of the COVID-19 pandemic on travel behavior: A case study of domestic inbound travelers in Turkey

Attitude, Theory of Planned Behaviour, and subjective norms are important factors that have been studied for their impact on travel intention. Attitude is a concept that refers to individuals’ positive or negative evaluations regarding a particular object, person, event, or situation. These evaluations often correlate with emotional reactions, beliefs, and actions, and consequently can significantly influence individuals’ behaviours (Jhangiani & Tarry, 2022). Attitude is a critical psychological concept for understanding how individuals react to their environments and experiences, as well as how they shape their future behaviours (Jain, 2014). Within the context of tourism, attitudes are essential to comprehending how tourists feel about a specific destination, service, or experience, and how these feelings influence their travel decisions. For instance, a tourist’s positive attitude towards a destination can increase the likelihood of them visiting that location, while a negative attitude generally has the opposite effect. Consequently, tourism marketers and service providers frequently endeavour to positively influence tourists’ attitudes, with the goal of attracting more tourists and encouraging them to revisit. This aim may involve strategies such as improving service quality, building a more positive brand image, and enhancing customer satisfaction (Rajesh, 2013).

The Theory of Planned Behaviour (TPB) is a psychological theory designed to elucidate individuals’ intentions to perform a certain behaviour and how these intentions translate into specific actions. According to this theory, an individual’s intention to execute a specific behaviour is determined by their evaluation of the outcomes of the behaviour (attitudes), whether significant others approve of the behaviour (subjective norms), and the individual’s perception of their ability to perform the behaviour (perceived behavioural control) (Ajzen, 1991). In the context of tourism, the Theory of Planned Behaviour is commonly used to understand tourists’ intentions to visit a specific destination and how these intentions convert into actual travel (Yuzhanin & Fisher, 2016). For instance, a tourist’s intention to visit a destination can be influenced by their thoughts about the destination, whether their social circle approves of the visit, and their perceived ability to carry out the visit. This theory can be helpful in defining marketing and promotion strategies in the tourism industry. It can also be beneficial in enhancing comprehension of how tourism services can be designed and how destinations can be improved to meet tourists’ expectations (Quintal et al., 2010).

Subjective norms refer to individuals’ perceptions of whether significant others in their environment desire that they perform a specific behaviour, and their willingness to comply with these expectations. This concept plays a significant role in social psychology, especially as part of Ajzen’s Theory of Planned Behaviour. Subjective norms can greatly influence individuals’ behaviours and decisions because people often seek approval from their surroundings and desire to be in conformity with them. In the context of tourism, subjective norms can have a considerable impact on tourists’ travel decisions (Nguyen et al., 2023). For instance, if a tourist’s family or friends suggest visiting a particular destination, it could increase the tourist’s intention to visit that destination. Similarly, if a tourist’s social environment values a certain type of travel (for instance, ecotourism or adventure tourism), this could make the tourist more eager to try this type of travel. Consequently, tourism marketers and service providers often attempt to influence subjective norms using techniques such as social proof or referrals. These can be very effective in encouraging tourists to try a destination or service (Zhang & Cao, 2023).

The epidemics experienced in the past century have caused negative effects in many areas, leading to the closure of many businesses and the unemployment of millions of workers. Undoubtedly, this situation has tended to have its strongest impact on the tourism industry. Given that tourism continues to be perceived as a form of luxury consumption, it seems to be given up quickly in adverse situations where demand is easily lost.

SARS, which emerged in China in November 2002 and lasted for 6–12 months, affected all areas of life on a regional scale. This epidemic, which had a huge impact in many cities in China, dealt a great blow to China’s tourism activities, especially in large metropolises, and had a significant negative impact on travel intention and tourist behaviour; negative economic effects then ensued (Wilder-Smith et al., 2020). Many people cancelled their planned vacations and trips. The restrictions imposed by the government and municipalities and the loss of motivation brought about by the epidemic made those cancellations inevitable. Outdoor activities and rural tourism attracted the most attention during this period (Wen et al., 2005). SARS also negatively affected the vitality of tourism activities in Southeast Asia (Dombey, 2003).

Ebola, another epidemic disease that emerged simultaneously in Sudan and Zaire in 1976 (Pourrut et al., 2005), also significantly affected tourist behaviour. Due to its impact on travel intention and tourism demand, Ebola caused a sudden decrease in the number of tourists in Africa (Sifolo & Sifolo, 2015). Ebola also significantly affected tourism activities in other regions where cases occurred. Cahyanto et al. (2016), in their research conducted in the United States, revealed that Ebola caused Americans to avoid domestic travel. The perception of risk brought by the epidemic is the most important reason for avoiding travel. In addition to Ebola, influenza epidemics (bird and swine) have negatively affected travel decisions and behaviours, though not to the extent of COVID-19. Flu epidemics have had the most severe negative effects on vacation and airline reservations (McKibbin, 2009).

On the other hand, in a study by Terziyska and Dogramadjieva (2020) on COVID-19 and travel intention, it was determined that the majority of the participants (90%) had a desire to travel after 2020. In addition, 70% of the participants stated that they would be able to travel in the spring and summer in the same year and that they would like to carry out activities such as entertainment, excursions, and visits to acquaintances (friends/relatives) once COVID-19 subsided. Ivanova et al. (2020) found that the participants had an intention to travel within the first two months after the travel restrictions were lifted. Though most of those travels were domestic family trips in their personal vehicles, hygiene and trust in destinations’ health systems were crucial deciding factors in whether they were actually carried out. Another finding obtained from the study was that the health and safety preferences of women and people in older age groups were more prominent.

Zheng et al. (2021), in their study on the fear of travel after the pandemic, concluded that post-pandemic fear could lead to cautious travel behaviour. In a study by Wachyuni and Kusumaningrum (2020), it was investigated how tourist behaviour would change after the COVID-19 pandemic. Their results indicated that tourists would tend to prefer nature tourism among tourism types (66%) and limit their travel times to 1–4 days. Wen et al. (2020) investigated the changes in Chinese tourists’ preferences for tourism movements in terms of life, travel, and tourism due to the COVID-19 epidemic. They found a shift in tourist movements toward of slow and smart tourism for the future. Şengel et al. (2020) investigated the effects of death anxiety caused by the COVID-19 pandemic on travel behaviour. Their results showed that anxiety about death due to the pandemic affected travel and destination intentions.

Luo and Lam (2020) revealed in their research on travel anxiety, risk, and intention that travel intention is negatively affected by anxiety and risk attitudes. Neuburger and Egger (2021) investigated the relationship between travel risk and tourist behaviours during the pandemic, concluding that the pandemic (COVID-19) has caused a serious increase in perceived travel risk and shortened travel times. According to Nazneen et al. (2020), who studied the perceptions of risk among tourists during COVID-19, it was found that tourists were seriously worried about traveling, especially in the first 12 months. Another finding of that study was that the pandemic seriously affected the decisions of tourists regarding their travels and perceptions of hygiene and safety.

Li et al. (2021) conducted a study on the effects of tourists on planned travel behaviour after the pandemic. They found a preference for private vehicles over public transportation, and that tourists tended to shorten their holidays in the wake of a crisis environment.

In a study by Matiza (2020), the possible effects of the COVID-19 pandemic on tourist behaviour in the short and medium terms were examined. The researcher determined the dimensions of tourist behaviour for the post-COVID-19 period and recommended some short-term measures can be taken to mitigate travel-related risks. The research indicates that tourist behavior in the post-COVID-19 period has evolved, with a greater emphasis on safety, health, and responsible travel. The tourism industry is advised to adapt to these changes by implementing strategies that address these new preferences and concerns, ensuring a safe and comfortable travel experience for tourists. In another study, Nair and Sinha (2020) investigated people’s intentions regarding their future travel actions. As a result, it was determined that accessibility, discounts, hygiene, and health issues were the most important motivation factors in destination selection. Aydın and Doğan (2020), on the other hand, in a study on the effects of the COVID-19 epidemic on tourist consumption behaviours in Turkish tourism, confirmed that COVID-19 has had an effect on the consumption behaviours of tourists, who must adust to a “new normal.”

The rise of the COVID-19 pandemic has heightened concerns for individual safety (Rettie & Daniels, 2021). As a response, people have adopted numerous precautions, like limiting outdoor activities or selecting destinations with minimal infection risks (Zheng et al., 2021). In this context, the drive to sidestep illness and hazards can be viewed as motivations for travel (Karl et al., 2021). Qiao et al. (2021) explored the link between the COVID-19 outbreak and travellers’ self-preservation motives.

In his conceptual study, Yaşar (2020) investigated the effects of the pandemic on the tendency of individuals to participate in the holiday movement, determining that tourists wanted to stay away from crowded environments. In a study by Zhu and Deng (2020), the relationship between COVID-19 risk and rural tourism participation intention was investigated. It was found that greater knowledge levels among participants about the risk of pneumonia decreased the perceived risks related to rural tourism.

Silik et al. (2020) evaluated domestic tourist behaviour in terms of generational differences after the COVID-19 pandemic. The results revealed that after the end of the COVID-19 epidemic, behavioural changes varied between different age cohorts. Kılıç et al. (2020) determined that there have been changes in the consumption attitudes of tourists during the post-epidemic period. It was determined that domestic tourists would be able to participate in holiday activities after the pandemic became normalized. These tendencies refer to behaviours within the borders of a country, and the measures taken by that country will be effective in the decisions of the tourists planning their vacations abroad.

The literature contains a myriad of studies probing the connection between the COVID-19 pandemic and travel intent. Zenker et al. (2021) delved into the influence of individual concerns on tourists’ travel aspirations. Meanwhile, Zheng et al. (2021) identified risks during the COVID-19 era as impactful on travel desires. Luo and Lam (2020) discerned that COVID-19 apprehensions had a direct, adverse bearing on travel intentions. Similarly, Riestyaningrum et al. (2020) concluded that the pandemic substantially sways tourist travel inclinations. Notably, while the majority of research emphasizes the adverse effects of pandemic-related information on travel plans, some studies, like Isaac and Keijzer (2021), suggest potential positive shifts in travel intent as circumstances become more favourable.

The main purpose of this research is to reveal the perceptions of Turkish tourists during the early stages of the COVID-19 pandemic and their planned post-pandemic domestic travel behaviour. The effect of the pandemic on the travel intentions of domestic tourism participants will is investigated.

In this study, Ajzen’s (1991) Theory of Planned Behaviour (TPB) was used to investigate planned changes in travel behaviour after the pandemic. This scale has also been adapted to research in the field of tourism (Hasan et al., 2020; Li et al., 2021; Meng & Choi, 2019; Meng & Cui, 2020). The scale for the present study was adapted from Li et al. (2021). Hospitality (HOS) and Impression (IMP) were added to the model with two sub-expressions each. Likewise, Attitude (ATT), Subjective Norm (SUN), and Perceived Behavioural Control (PBC) consist of two statements each. Finally, post-pandemic travel intention (PPT) was also represented. Interpandemic perceptions of destinations (IPP) were measured through perceptions of destination hospitality during the pandemic and impressions were based on cognitive information about the pandemic at the destination.

Based on this information, people’s opinions, behaviours, and attitudes can be shaped according to their perceptions. One of the factors most strongly affecting opinions, behaviours, and attitudes is undoubtedly risk perception (Neuburger & Egger, 2021). Risk perception also plays an important role in the perception of pandemics (Poletti et al., 2011). Pandemic risk perception in tourism also affects travel decisions and purchasing experiences with tourism products (Das & Tiwari, 2021).

Another issue that influences travel decision making is attitudes (Sánchez-Cañizares et al., 2021). Prior to COVID-19, Epidemics such as SARS, H1N1, and influenza caused disruptions in tourism activities on regional and global scales. The main reasons for said disruptions were risk and the perception of a pandemic (Yang & Nair, 2014). The effects of risk perception and attitudes related to the pandemic were also examined in studies on the COVID-19 epidemic (Godovykh et al., 2021; Nazneen et al., 2020). The measures taken during the pandemic process have been effective in shaping perceptions of the pandemic. It has accordingly been observed that perception has affected travel intention after the pandemic (Benjamin et al., 2020). Based on this, the following hypotheses have been developed:

H1: IPP has a significant effect on ATT.

Perceived behaviour control explains the ability of individuals to perform a behaviour (Benjamin et al., 2020). Subjective norms, on the other hand, refer to the social pressure that a person perceives about performing or not performing a certain behaviour (Fischer & Karl, 2022). Perceived behavioural control and subjective norms have significant effects on destination choice and travel intention (Lam & Hsu, 2006). Perceived behavioural control and subjective attitudes have continued to affect travel behaviours in the wake of COVID-19 (Aschwanden et al., 2020). Based on this information, the following hypotheses were developed:

H4: PBC has a significant effect on PPT.

Figure 1:

The measurement tool utilized in this research is adapted from the TPB scale (Ajzen, 1991). Both HOS and IMP (Li et al., 2021), SUN (Chen & Tung, 2014; Li et al., 2021), ATT (Wang & Ritchie, 2012), and PBC (Chen & Tung, 2014; Li et al., 2021; Wang & Ritchie, 2012) comprise two statements each. PPT, from Li et al. (2021), is represented by a single statement. Respondents rate items on a 5-point Likert scale, with options spanning from strongly agree (scored as 5) down to strongly disagree (scored as 1). The latter section of the measurement tool gathers information on eight distinct demographic attributes, including factors like age, educational background, and income level.

The data for this study were collected through an online survey conducted during the pandemic (between 10 January 2022 and 29 April 2022). The improbable snowball sampling method was used, via LinkedIn, to target people who made at least one domestic trip every year (before the pandemic). They were asked to share the survey with others who exhibited similar travel behaviour. The questionnaires took about five minutes to complete. In all, 617 questionnaires were filled. Of those, 611 were retained for analysis, as six were found to be suspicious in terms of the authenticity of their answers. The proposed post-pandemic planned behaviour model was analysed using SmartPLS 3.

Examining and evaluating the structural model with PLS hinges on two essential viewpoints. Initially, it’s about normalizing the path coefficient; next, it’s about defining the explanatory model through R (Fornell & Larcker, 1981; Hair et al., 2014). Each prospective path coefficient between variables, combined with the R-value outcome, indicates the alignment level between the structural model and the observational data. The normalized path coefficient should be close to a 5% statistical significance. R is used to gauge analytical proficiency, with a higher R-value indicating enhanced capability. Table 3 displays the outcomes of the PLS path evaluation.

As a result of the hypothesis, it was determined that IPP had a positive effect on ATT (β = .305, t = 3.118). Based on this result, H1 was accepted. For the second hypothesis, the effect of ATT on PPT was measured. Analysis showed that ATT had a strong positive effect on PPT (β = .458, t = 12.291), so H2 was accepted. In addition, IPP’s effect on PPT (β = .280, t = 2.348), PBC’s effect on PPT (β = .872, t = 47.964), and SUN’s effect on PPT (β = .624, t = 35.542) were strong and positive. Thus, hypotheses H3, H4, and H5 were also accepted.

Table 4 showcases the pre-established 95% confidence intervals for the TPB linkage coefficients. Observing Table 3, it is evident that none of the dimension’s coefficients reach 1. This suggests a modest correlation amongst ATT, SUN, PBC, and PPT behavioural tendencies. Thus, this study upholds the discriminant validity of the theory of planned behaviour, as mentioned by Jang et al. (2009).

In the comprehensive assessment, this research employed seven metrics: the χ² test, the ratio of chi-square to degrees of freedom, GFI, AGFI, RMSEA (which are considered to gauge the fit between sample data and proposed theories), CFI, and PCFI. For this investigation, the relationship between χ² and degrees of freedom stands at 2.72, which is under 3. The respective values for GFI, AGFI, RMSEA, CFI, and PCFI were 0.98, 0.95, 0.06, 0.97, and 0.37. Post-adjustment, as depicted in Table 5, all the fit indices aligned with the acceptable benchmarks (Jang et al., 2009), pointing to an effective match between sample data and theoretical propositions. Consequently, the study’s model was deemed fitting.