Travelling pre- and post-pandemic: will the climate be taken into account?
Author: Charlot Oudbier Student number: 12249149
Program: BSc Business Administration
Specialisation: Management in the Digital Age Supervisor: Lita Napitupulu
Date: June 30, 2021
Statement of Originality
This document is written by Student Charlot Oudbier who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document are original and that no sources other than those mentioned in the text and its references have been used in creating it.
UvA Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
Abstract
One-third of the Dutch citizens experience the corona pandemic as a wake-up call for the climate. The travel restrictions during the pandemic resulted in a decrease in the travelling frequency, which had a positive effect on the air quality worldwide. This study aims to explore the effect of the corona pandemic on the travelling behaviour of Dutch consumers with regard to sustainability. An online survey was distributed among Dutch consumers and resulted in 229 respondents of 18 years or above. A linear regression was used to test for the first hypothesis, which states that there is a negative association between the sustainable behaviour and travelling behaviour of a Dutch consumer. The second hypothesis was tested using a moderation analysis, which investigates whether this association is moderated by the perception of the corona pandemic. No support was found for the hypotheses. The results from the paired sampled t-tests suggest that after the corona pandemic, Dutch consumer will travel to domestic destinations more often compared to international destinations. In addition, an increase in the use of more sustainable ways of transportation is expected. The most frequently used mode of transportation when going on a holiday remains the car. Thereafter, it changes from airplane to public transport and shows an increase in the use of a bike. By outlining the sustainable and travelling behaviour of the Dutch consumer, awareness can be raised about the impact of the consumer’s travelling behaviour on the climate.
Keywords: sustainability, corona pandemic, travelling behaviour.
Contents
1. Introduction ... 5
2. Theoretical framework ... 8
3. Methods ... 12
3.1. Data collection ... 12
3.2. Data analysis ... 12
3.3. Variables ... 13
3.4. Data preparation ... 14
4. Results ... 15
4.1. Baseline characteristics ... 15
4.2. Correlation matrix ... 16
4.3. Hypothesis 1 testing ... 17
4.4. Hypothesis 2 testing ... 18
5. Discussion ... 20
6. Reference list ... 23
7. Appendix ... 26
1. Introduction
One-third of the citizens in the Netherlands perceive the COVID-19 pandemic as a wake-up call for the climate (ABN AMRO, 2020). This perception matches the clear examples presented in the literature of a positive effect of the corona measures on the climate when humanity is slowing down. For example, research by Wang, Liu and Zheng (2020) has shown that, when looking at 325 cities in China, air pollutants have reduced by 12.2% in cities that experienced a lockdown. In Western Europe, it has also been shown that NO2 concentrations decreased up to 50% as a result of the lockdown measures (Menut et al., 2020). In the Netherlands, the regulations to keep COVID-19 under control already showed an impact at the beginning of March 2020. There was a reduction of 22.6% in NO2 concentrations, 10.4% in the fine particles in the air, and an increase of 8.2% in oxygen levels (Menut et al., 2020). Altogether, these numbers show that the regulations to control the corona pandemic, led to improved air quality in several places in the world (Menut et al., 2020). A possible explanation for this reduction in carbon emissions could be a reduction in the travelling behaviour of consumers. The travel restrictions set in place during 2020 and 2021 influenced travellers all over the world (European Commission, n.d.). For instance, with regard to the Netherlands, the travel restrictions resulted in a reduction of 82% in the passengers of airport Schiphol in October of 2020 compared to the year before (AD, 2020).
The concept of sustainability has been around for less than a century. However, consciousness of Western society regarding nature, natural resources and environmental problems has increased significantly since the late 1960s (Juárez-Nájera, Rivera-Martínez, &
Hafkamp, 2010). Sustainable behaviour can be defined as “a set of effective, deliberate, and anticipated actions aimed at accepting responsibility for conservation and preservation of physical and cultural resources.” (Juárez-Nájera, Rivera-Martínez, & Hafkamp, 2010, p. 687).
With regard to the Netherlands, Dutch consumers are aware of the responsibility and impact they have on the climate. In 2017, 70% of Dutch citizens perceived climate change as one of the four most important problems they encountered (CBS, 2018). Moreover, among Dutch citizens, climate consciousness has increased in the past years. For example, 90% of the citizens are conscious of their energy consumption (CBS, 2018).
There are some recent studies that investigated the impact of COVID-19 on travelling behaviour (Wachyuni & Kusumaningrum, 2020; Li, Nguyen, & Coca-Stefaniak, 2020). A study by Wachyuni and Kusumaningrum (2020) shows that after the COVID-19 pandemic, about half of the Indonesian respondents would prefer to travel to domestic destinations only and the other half to both domestic and foreign destinations. The majority said they would
travel again around 0-6 months after the end of the pandemic (Wachyuni & Kusumaningrum, 2020). The most preferred type of travelling was nature tourism since 66% of the respondents claim they would like to make a trip to nature. This study implies that the tourism industry will recover fast since the “majority of respondents in this study have planned when and where they will travel, immediately (0-6 months) after the COVID-19 pandemic ends.” (Wachyuni &
Kusumaningrum, 2020, p. 74).
On the one hand, the findings of the study by Wachyuni and Kusumaningrum (2020) are contradictory to the findings of Li et al. (2020), who state that it is expected that around 50% of the population will go on a holiday when the pandemic is under control but only after six months or longer. On the other hand, the consensus between the outcome of the studies is that consumers will most likely take shorter holidays. Moreover, a study by Zheng, Luo and Ritchie (2021) shows another issue regarding the tourism industry. Namely, the occurrence of
‘travel fear’ ever since the outbreak of COVID-19. Travel fear increases psychological resilience and causes cautious travelling behaviour (Zheng et al., 2021).
It is currently unclear what the specific effects of the corona pandemic will be on the tourism industry, only predictions can be made since the corona pandemic is still ongoing.
However, the World Travel and Tourism Council (WTTC) estimates that the industry will not return to normal until after 10 to 35 months (Wachyuni & Kusumaningrum, 2020). Therefore, it is important to examine the consumer’s intention to travel. However, it is unclear if the pandemic will influence the travelling behaviour of Dutch citizens. The fact that 84% of the Dutch citizens travelled in 2019 and went on more than 40 million holidays in total showed that travelling is an important aspect of the Dutch lifestyle (CBS, 2020). In 2013, global tourism accounted for 8% of the worldwide carbon emissions (Lenzen et al., 2018). This percentage also includes carbon emissions as a result of tourism activities, such as commodities purchased. Transport, as an element of travelling, is highly energy and carbon intensive (Lenzen et al., 2018). In fact, it accounts for 50 to 97.5% of the total emissions of a tourism trip (Dickinson, Lumsdon, & Robbins, 2011). The carbon emissions resulting from travelling show that travelling is not always sustainable.
Thus, it is important to gain insight into the association between the sustainable behaviour and travelling behaviour of Dutch citizens. Moreover, it is important to investigate the impact of the corona pandemic on this association. By doing so, businesses in, for example, the tourism industry can anticipate how to respond to this change after the pandemic. Moreover, the role of sustainability in the impact of the corona pandemic on travelling behaviour has not been examined in the context of the Netherlands. This implies that it has not been examined
whether the positive effects on the climate as a result of the pandemic, cause a change in the expected future travelling behaviour of the consumer. Therefore, this study aims to investigate whether there is a difference in the travelling behaviour of consumers after the corona pandemic. The research question will be: “What is the effect of the corona pandemic on the travelling behaviour of Dutch consumers with regard to sustainability?”
In the next chapter the relevant literature applicable to the research question is highlighted. Chapter 3 contains the methods used in this study and thereafter, Chapter 4 focuses on the results. Finally, the discussion reviews the main findings of this study, the limitations, recommendations for future research and a conclusion reflecting on this study.
2. Theoretical framework
Taking into account the fact that 8% of the worldwide carbon emissions is caused by travelling, it becomes clear that travelling can be very polluting. A type of travelling that aims to tackle the issue of unsustainable and polluting travelling is called slow travelling, which includes all types of travelling excluding travelling by air and car (Dickinson et al., 2011). As a slow traveller, instead of perceiving travelling as a mode of transportation, one may include place, personal identity and the environment as part of their travel experience (Dickinson et al., 2011).
Due to the increasing consciousness of sustainability among tourists, the slow travel market is expanding. The elements place, personal identity and the environment might influence consumer behaviour, and slow travelling might be an option in reducing the carbon footprint.
Moreover, one of the dilemmas that consumers face is called the flyers’ dilemma.
Higham, Cohen, & Cavaliere (2014) describe the flyers’ dilemma as “the tension that now exists between the personal benefits of tourism and the climate concerns associated with high levels of personal aeromobility.” (p. 1). This can be seen as the relationship between sustainable behaviour and travelling behaviour. This study found evidence for the flyers’ dilemma among consumers in Norway and Germany, implying that consumers are aware of the impact of the airline industry on the climate. An important factor that plays a role in the decision whether or not to travel by air is costs since cheap flight tickets are hard to resist (Higham et al., 2014).
Moreover, the sociological element of this dilemma was also investigated and could be approached as an element of social standing. Since air travelling is embedded in social practices, it could be the case that air travelling is something of the upper class (Higham et al., 2014).
Another dilemma regarding flying occurred because of the corona pandemic. Some travellers and non-travellers got anxious to travel considering the risks associated with COVID- 19 (Zenker, Braun, & Gyimóthy, 2021). Recently, a new condition has been diagnosed, namely coronaphobia, which means coronavirus anxiety (Zenker et al., 2021). Due to the corona pandemic, there is not only a flyer’s dilemma that refers to the tension between sustainability and travelling, but also between the risks associated with the coronavirus and travelling. Zenker et al. (2021) developed a Pandemic Anxiety Travel Scale (PATS) that measures how much of the traveller’s anxiety is induced by the corona pandemic.
With regard to consumer behaviour, there is a need for inclusion as well as a need for differentiation at the same time. This can be explained by the Optimal Distinctiveness Theory, which claims that people have two opposing needs, namely a need for assimilation and inclusion and a need for differentiation (Leonardelli, Pickett, & Brewer, 2010). The need for
inclusion refers to preferring to belong in a social group. These two needs are opposing, which means that when you feel like you belong to an inclusive group, the need for inclusion is satisfied. However, this also results in dissatisfaction of the need for differentiation which results in activation of this need. This constant opposition ensures that both needs are met and that the need for one is not sacrificed by meeting the other need. The model, which can be seen in Figure 1, proposes that “social identities are selected and activated to the extent that they help to achieve a balance between the needs for inclusion and differentiation in a given social context.” (p. 67). The optimal point of this balance between both needs can be seen as an equilibrium where both needs are satisfied.
Connecting the model by Leonardelli et al. (2010) with the flyer’s dilemma, it seems likely that a traveller needs to find an equilibrium. On the one hand, one wants to travel, for example, to explore the world or to visit loved ones. On the other hand, when someone has active sustainable behaviour, which means that he/she takes responsibility for the preservation of resources, they prefer to travel less since this has a negative impact on the climate (Higham et al., 2014; Juárez-Nájera et al., 2010). These two needs, to travel and to act sustainably, are opposing each other. This implies that when you meet one need, you sacrifice the other.
Therefore, the model by Leonardelli et al. (2010), which discusses the need for assimilation and differentiation, can also be applied to the flyer’s dilemma.
Figure 1. Optimal Distinctiveness Theory model (Leonardelli et al., 2010).
Due to the restrictions in place during the corona pandemic, people had to adapt elements of their lifestyle, for instance, dining out and travelling (European Commission, n.d.).
A study by Kim and Jang (2017) showed that “travelling and dining out can provide significant
therapeutic benefits by repairing feelings of loneliness.” (p.1). Another study by Kwon and Lee (2020) showed results in line with the positive effects of travelling. They found that travelling causes an increase in life satisfaction and affect, both before and after travelling (Kwon & Lee, 2020). Moreover, taking into account the coronaphobia discussed above, it raises the question what the effects of the corona pandemic are on one’s mental health.
As mentioned above, tourism accounts for 8% of the worldwide global emissions (Lenzen et al., 2018). This indicates that travelling can be very polluting and thereby, can result in a dilemma between behaving sustainably and travelling. The framework of Leonardelli, Pickett and Brewer (2010), can be used to explain the flyer’s dilemma (Higham et al., 2014).
They show that when faced with the dilemma between sustainability and travelling, one tries to find the equilibrium. Since the need to act sustainably and the need to travel are two opposing needs, it causes tension. Therefore, the first aim of this research is to shed light on the flyer’s dilemma by investigating the association between sustainable behaviour and the travelling behaviour of the Dutch consumer. The corona pandemic has made it difficult to travel due to restrictions (European Commission, n.d.), which could result in dissatisfaction of one’s need to travel. However, research shows that travelling has therapeutic benefits and results in an increase in life satisfaction and affect (Kim & Jang, 2017; Kwon & Lee, 2020). It could be predicted that the needs for inclusion and differentiation would affect the intention to travel, which in turn, influences the travelling behaviour of the consumer. Moreover, it is likely that the extent to which the consumer cares about the environment also influences their intention to travel and thus, their travelling behaviour. Therefore, this research aims to explore the effect of the corona pandemic on the travelling behaviour of consumers with regard to sustainability.
H1: There is a negative association between the sustainable behaviour of a consumer and consumer travelling behaviour. This implies that when the consumer has active sustainable behaviour, it will result in a reduction in their travelling behaviour.
Moreover, the pandemic challenged consumers in the need to act sustainably and the need to travel. Research shows that travelling has therapeutic benefits and results in an increase in life satisfaction and affect (Kim & Jang, 2017; Kwon & Lee, 2020). Therefore, it is important to investigate the level of psychological stress one encounters due to the pandemic. This allows for exploration of the impact of the corona pandemic on the association between sustainable behaviour and the travelling behaviour of the Dutch consumer. Thus, the aim of this research is to explore the effect of the corona pandemic on the travelling behaviour of consumers with regard to sustainability, which is possibly moderated by the effect of the corona pandemic. A visual representation of this model can be seen in Figure 2.
H2: The association between sustainable consumer behaviour and travelling behaviour is positively moderated by the perception of the corona pandemic. This argues that when the consumer’s behaviour is sustainable, their travelling behaviour decreases more when experiencing high levels of stress due to the corona pandemic.
Figure 2. A graphical representation of the model tested in this study.
3. Methods 3.1. Data collection
The basis of this research is composed of primary data, collected by conducting a survey among Dutch consumers. This resulted in quantitative data that can be analysed with the use of SPSS (IBM, n.d.). Quantitative data was collected since this allows for patterns to be identified in the data. The data can be expressed in numerical terms, which allows for statistical tests to be conducted. Moreover, this allows for exploration of the relationship between the variables (Gelo et al., 2008). A survey approach is most suitable for this research since a survey allows for a larger number of respondents, which increases the reliability of the quantitative research (Heale & Twycross, 2015). The data was collected via an online survey, available in both English and Dutch. This survey consists of questions using a Likert scale, apart from the demographic questions. Respondents were gathered using a voluntary response sampling, with an aim of a minimum of 200 responses. Voluntary response sampling means that the survey was filled in by Dutch consumers willing to participate in this research (Murairwa, 2015). The survey was distributed via the personal network. The survey was conducted online using the online survey tool Qualtrics, ensuring a low threshold for the participants. The population of this study is the Dutch consumer. Therefore, the inclusion criteria were:
1. The respondent is older than 18 years.
2. The respondent is a resident of the Netherlands.
The survey was based on pre-validated scales that will be discussed in further detail below.
The scales whose Cronbach’s Alpha was higher than 0.7 were taken into consideration since this is an acceptable reliability score (Heale & Twycross, 2015). The aim of the research is to investigate the impact of the corona pandemic on travelling behaviour, therefore, some questions are asked about the situation before the pandemic and the expected behaviour after the pandemic. At the beginning of the survey, the respondent has been asked to give informed consent. The scales used in the questionnaire and thus in this study are presented in Table A2.
3.2. Data analysis
The statistical analysis will be carried out using IBM SPSS Statistics 27 for Windows (IBM, n.d.). When the p-value is less than 0.05, it is considered to be statistically significant.
To investigate whether there is a significant effect of sustainable behaviour on travelling behaviour, a regression analysis will be conducted after ensuring the assumptions are met. This statistical analysis is most appropriate since the dependent variable is a continuous variable and the independent variable can be treated as such. Moreover, a paired sampled t-test will be
conducted to investigate changes in the variables measured both before and after the pandemic.
This statistical test is suitable since the variables are measured twice, namely positive holiday environmental attitudes and travelling frequency, can be treated as continuous variables.
Moreover, the independent variable in that case is the corona pandemic, with the two categories before and after the pandemic. Finally, a moderation analysis will test whether there is a moderation effect, using the PROCESS macro (model 1) of Hayes (2017).
3.3. Variables
The questionnaire is based on existing scales from the literature (see Table A4). The Cronbach’s alphas of the pre-validated scales are displayed in Table A2. The variables are measured on a 5-point Likert scale unless indicated otherwise. The Likert scale ranges from strongly disagree to strongly agree. Firstly, the independent variable in this study is measured as the consumer’s active sustainable behaviour as well as positive holiday environmental attitudes. Active sustainable behaviour is measured using 8 items concerning the extent to which the consumer’s behaviour is sustainable, e.g. I have switched products for environmental reasons (Paswan, Guzmán, & Lewin, 2017). Positive holiday environmental attitudes are measured using 6 items questioning to what extent one acts sustainably when going on a holiday, e.g. I prefer to avoid highly polluting forms of transport like air travel when I go away (Barr & Prillwitz, 2012). Secondly, the dependent variable is measured as travelling frequency (domestically and internationally) as well as intention to travel. Travelling frequency is a continuous variable, where respondents can enter a number representing their travelling frequency. Travelling frequency is measured twice, asking about the situation before and after the corona pandemic to be able to compare those outcomes. Intention to travel is measured on a 3 item scale from Lee, Agarwal & Kim (2012). Psychological stress due to the corona pandemic, which can also be measured using the Pandemic Anxiety Travel Scale (PATS), is the moderating variable in the beforementioned relationship. Psychological stress is represented by the perceived stress scale, which measures the perception of stress (Lee, 2012).
This scale consists of 9 items and the question asked about one’s thoughts and feelings during the corona pandemic, such as: How often have you been upset because of something that happened unexpectedly? The PATS consisted of 5 items measuring how anxious someone is to travel due to the corona pandemic (Zenker et al., 2021), by asking for example: I am afraid to risk my life when I travel, because of COVID-19.
3.4. Data preparation
After collecting the data, it became apparent that not every respondent had completed the survey. Therefore, it was decided to exclude respondent’s data when they completed less than half of the questionnaire. This was the case for 40 respondents, which means that 230 respondents were included in this study. After that, one more outlier was removed due to an invalid age. Thus, the statistical analysis was conducted with n = 229.
Before the variables could be used for statistical analysis, several items had to be recoded, for instance: During the corona pandemic, how often have you felt confident about your ability to handle your personal problems? Afterwards, a reliability analysis was conducted for each scale. In Table A3, the results of the reliability analysis for each scale are presented. The Cronbach’s alphas are all above 0.75 so the internal consistency of the scales used in this study was either acceptable or good.
4. Results 4.1. Baseline characteristics
The baseline characteristics of the study population showed that the majority is female (83.8%) (see Table A1). The mean age was 47 years, which ranged from 18 to 83 years. With regard to their education, most of the respondents obtained a Master’s degree (33.2%), closely followed by a Bachelor’s degree (31.9%).
When a paired sampled t-test was conducted, a difference variable was computed to compare the values pre- and post-pandemic. The box plot showed that there were five major outliers (difference pre- and post-pandemic travelling behaviour ≥ 10), which were excluded from the analysis. Since travelling for a holiday more than 10 times a year seems unlikely, it is expected that the respondents misinterpreted the question. The paired sampled t-test was also conducted including the outliers. However, this did not result in significant findings, M = .332, 95% CI [-0.407, 1.071], t(225) = .885, p = .377. After excluding the outliers, the Normal Q-Q plot was normally distributed. The paired sampled t-test compared domestic travelling frequency, which showed an increase in the domestic travelling frequency after the corona pandemic (M = 2.82, SD = 3.452) compared to before the pandemic (M = 1.95, SD = 1.757).
There is a statistically significant increase of domestic travelling frequency after the pandemic compared to before of 0.867 times per year, 95% CI [0.411, 1.324], t(225) = 3.744, p < .0005.
Moreover, the paired sampled t-test was also used to investigate a possible change in international travel behaviour. The computed variable showed the difference between pre- and post-pandemic. After computing a variable describing the difference before and after the pandemic, it was tested for outliers and normal distribution. The box plot showed several outliers. However, outliers were not excluded from the analysis since the difference was within the predefined value (<10 pre- and post-pandemic). The Normal Q-Q plot showed that the data was normally distributed, therefore, a paired sampled t-test was executed. It showed that respondents travelled more frequently before the pandemic for an international holiday (M = 1.96, SD = 1.760) compared to after the pandemic (M = 1.58, SD = 1.542). Travelling internationally after the corona pandemic resulted in a statistically significant decrease of the mean frequency in which the respondents travel internationally compared to before the pandemic of 0.371 times per year, 95% CI [0.215 to 0.527], t(224) = 4.685, p < .0005.
In addition, the preferred mode of transportation was also investigated. As outlined in Figure 3 below, the top three most used transportation modes before the pandemic were car (60.7%), airplane (23.1%) and public transport (8.7%). After the pandemic, this consisted of car (60.3%), public transport (18.3%) and airplane (11.4%). In addition, an increase of 100%
can be seen for going on a holiday by bike comparing before (2.6%) and after the pandemic (5.2%).
Figure 3. Visual representation of the preferred mode of transportation when going on a holiday, comparing before and after the pandemic.
The independent variable can be measured in both active sustainable behaviour and positive holiday environmental attitudes. The difference between positive holiday environmental attitudes before and after the pandemic showed no extreme outliers and was normally distributed. The paired sampled t-test showed that respondents experienced a more positive holiday environmental attitude after the corona pandemic (M = 3.83, SD = 0.740) compared to before the pandemic (M = 3.75, SD = 0.725). Thus, there is a statistically significant increase of positive holiday environmental attitudes after the pandemic compared to before of 0.076 points on a 5-point Likert scale, M = 0.076, 95% CI [0.021, 0.131], t(206) = 2.708, p = .007.
4.2. Correlation matrix
A correlation matrix was calculated to check for correlations and multicollinearity (see Table 1). The first notable significant moderate positive relationship is found between positive holiday environmental attitudes before and after the corona pandemic (r = 0.850, p < 0.01). In addition, a positive correlation was found between supportive public transportation on a holiday before and after the pandemic (r = 0.841, p < 0.01). A weak negative correlation was found between intention to travel and both positive holiday environmental attitudes before (r = -0.183, p < 0.01) and after the pandemic (r = -0.236, p < 0.01). This indicates that when people
0 20 40 60 80 100 120 140 160
Car Airplane Public transport Bike Boat Other Motorcycle Walking
Frequency
Mode of transportation
Most frequently used mode of transportation when going on a holiday
Before the corona pandemic After the corona pandemic
have a higher intention to travel, they generally score lower on their positive holiday environmental attitudes. Finally, a significant weak correlation was found between psychological stress and the Pandemic Anxiety Travel Scale (r = 0.231, p < 0.01). Since there is no correlation between the independent variable and moderator, there is no multicollinearity in this regression.
Table 1
Correlation matrix of the variables used in this study
4.3. Hypothesis 1 testing
H1: There is a negative association between sustainable consumer behaviour and consumer travelling behaviour. This implies that when the consumer has active sustainable behaviour, it will result in a reduction in their travelling behaviour.
The association between sustainable consumer behaviour and consumer travelling behaviour is presented in Figure 4 below. The assumption of linearity was not met, but it was decided to continue with the analysis. The Durbin-Watson statistic of 2.039 indicated independence of residuals. The plot of standardized residuals versus standardized predicted values indicated homoscedasticity. Finally, the normal probability plot indicated that the residuals were normally distributed. The linear regression shows that active sustainable behaviour accounted for 0.7% of the variation in international travelling frequency with adjusted R2 = 0.2% which is a weak size effect according to Cohen (2013). There is no statistically significant result, which means that active sustainable behaviour does not predict international travelling
frequency, F(1, 223) = 1,466, p = 0.227. Also after excluding the outliers where the standardized residual is higher than 3 standard deviations, there was no statistically significant result, F(1, 219) = 3,314, p = 0.070. Thus, no support has been found and therefore, hypothesis 1 has been rejected.
Figure 4. Frequency of travelling internationally for a holiday after the pandemic, categorized by active sustainable behaviour.
4.4. Hypothesis 2 testing
H2: The association between sustainable consumer behaviour and travelling behaviour is positively moderated by the perception of the corona pandemic. This argues that when the consumer’s behaviour is sustainable, their travelling behaviour decreases more when experiencing high levels of stress due to the corona pandemic.
To test for hypothesis 2, model 1 of PROCESS macro by Hayes (2017) was used, the results are summarized in Table 2. The results showed no significant interaction effect (b = .3417, se = .2053, t = 1.6644, p = .0977, 95% CI = -.0631, .7466). Therefore, no support can be found for the second hypothesis and has been rejected. It has to be taken into account that the assumption of linearity was not met and that could affect the results. A notable finding was a significant relationship between positive holiday environmental attitudes and international travelling frequency. Since the unstandardized B coefficient is -0.7672, this implies that when a Dutch consumer moves up one point on the 5-point Likert scale measuring positive holiday environmental attitudes, their international travelling frequency decreases by 0.7672 (p < 0.05).
0 2 4 6 8 10 12
Before the corona pandemic After the corona pandemic
Travel frequency
Active sustainable behaviour
Frequency of travelling internationally for a holiday after the pandemic, categorized by active sustainable
behaviour
Low Moderate High
Table 2
Moderator Analysis: Sustainable behaviour and Travelling frequency Dependent variable: International travelling frequency after the corona pandemic
Model Variable Unstandardized B coefficient
SE t p 95% CI
LL UL
Model 1 Constant 2.1626 1.8271 1.1836 .2379 -1.4389 5.7641 ASBa -.2050 .5046 -.4062 .6850 -1.1995 .7896
PATSb .0189 .6289 .0300 .9761 -1.2207 1.2585
ASB x PATS .0115 .1739 .0660 .9474 -.3312 .3542 Model 2 Constant 5.2620 2.0636 2.5499 .0115 1.1920 9.3319
ASB -1.1088 .5578 -1.9878 .0482 -2.2089 -.0087 PSCc -1.1318 .7587 -1.4919 .1374 -2.6281 .3645 ASB x PSC .3417 .2053 1.6644 .0977 -.0632 .7466 Model 3 Constant 3.6438 1.6558 2.2006 .0289 .3780 6.9095
PHEAd -.6095 .4364 -1.3968 .1641 -1.4702 .2511
PSC -.1713 .6485 -.2641 .7920 -1.4503 1.1077
PHEA x PSC .0670 .1733 .3870 .6992 -.2747 .4088 Model 4 Constant 4.3226 1.4764 2.9278 .0038 1.4114 7.2337
PHEA -.7672 .3778 -2.0304 .0436 -1.5122 -.0221
PATS -.3379 .5355 -.6309 .5288 -1.3939 .7181
PHEA x PATS .1081 .1379 .7841 .4339 -.1637 .3799 Note. Dependent variable is international travelling frequency after the corona pandemic. The variables are measured on a 5-point Likert scale unless mentioned otherwise. a ASB = Active sustainable behaviour. b PATS = Pandemic Anxiety Travel Scale. c PSC = Psychological stress corona. d PHEA = Positive holiday environment attitudes (after the pandemic).
5. Discussion
The main finding of this study was that the international travelling behaviour after the corona pandemic resulted in a statistically significant decrease of 0.371 times per year compared to before the pandemic (p < .0005). Moreover, concerning domestic travelling, there is a statistically significant increase of 0.867 times per year after the pandemic (p < .0005).
Finally, while the car is still the most used mode of transportation both before and after the pandemic, public transport is expected to be the second most used mode of transportation after the pandemic instead of the airplane. In addition, going on a holiday by bike increased by 100%. These findings indicate that the travelling behaviour of the Dutch consumer is expected to change after the pandemic, namely a decrease in international holidays and an increase in domestic holidays. This conforms with the increased use of public transport and decreased use of an airplane.
The first hypothesis of this study stated that there was a negative association between sustainable consumer behaviour and consumer travelling behaviour. The regression analysis did not show significant effects (F(1, 219) = 3,314, p = 0.070), therefore no support was found for the first hypothesis. The flyer’s dilemma might explain why there is no relationship between active sustainable behaviour and international travelling frequency, since these two needs are opposing. Secondly, the moderation effect of the corona pandemic on the relationship above was investigated. No support was found for this hypothesis. Nonetheless, a significant relationship was found between positive holiday environmental attitudes and international travelling frequency (b = -0.7672, p < 0.05). This implies that when a Dutch consumer has a more positive holiday environmental attitude, their international travelling frequency decreases.
The CBS (2018) showed that in the past years there has been an increase in the consciousness of the environment among Dutch consumers. This is in line with this research, indicating that the sustainable behaviour of Dutch consumers will continue to increase comparing before and after the pandemic. The fact that an increase in the positive holiday environmental attitude of the Dutch consumer is expected after the corona pandemic is demonstrated in this study (M = 0.076, p = .007). Moreover, a study by Wachyuni and Kusumaningrum (2020) shows that when the corona pandemic has ended, about half of the respondents prefer to travel to domestic destinations only. The results of this study complement these findings since a significant increase in domestic holidays will be expected after the pandemic (M = 0.867, p < .0005), while foreign holidays will decrease (M = -0.371, p < .0005).
One of the strengths of this research is that the survey was conducted among more than 200 respondents. A larger sample size results in more statistical power and thus more precision in the results (Jerosch-Herold, 2005). A sufficient sample size ensures validity and reliability in the research, which was also achieved by the use of pre-validated scales. The reliability analyses showed Cronbach’s alphas of above 0.75 which means the scales used in this study have an acceptable or good internal consistency and are thus reliable.
A limitation of this study was that there was no homogeneity in this population since 83,8% of the respondents were female. However, the mean age of this study was 47 years, and the CBS (2021) shows that in this category there are slightly more women than men. Moreover, with regard to demographics, the country of origin has not been taken into account. The only criterium was that the respondent had to be Dutch and above 18 years. Country of origin could be an interesting variable to measure in the future since foreigners might travel more to visit relatives or friends on a holiday. Finally, the last limitation of this study concerns the heterogeneity of this population, since it is difficult to identify associations between variables as well as to compare results. This variability in the population could be an explanation for the violation of assumptions in the first hypothesis. Moreover, it could also explain why the moderation analysis did not result in many insights.
To the best of my knowledge, this is the first study investigating the association between sustainable behaviour and travelling behaviour including the role of the corona pandemic.
Therefore, this study contributes to the existing literature by showing the differences between pre- and post-pandemic. Moreover, concerning the tourism industry, travel agencies could benefit from this research by addressing the needs to consider the travelling frequencies both internationally and domestically. Furthermore, they could adapt to travellers by taking into account the preferred mode of transportation.
For the generalizability of the results, future research should focus on the inclusion of a larger sample size to have a more homogeneous population. Nonetheless, even though the current population is heterogeneous, this research contributed to the literature by showing the spectrum with regard to travelling behaviour and sustainable behaviour. Moreover, this study also showed how a pandemic can influence the travelling behaviour of Dutch consumers.
Finally, it is important to notice that the country is still facing a pandemic and therefore, it is unclear what the eventual consumer behaviour will be. Therefore, it would be valuable to conduct a similar study investigating both the travelling and sustainable behaviour of the Dutch consumer when the pandemic has actually ended. This way, it is possible to check whether the
expectations of this study have become reality and to actually show the extent to which sustainable behaviour influences travelling behaviour.
In conclusion, this study outlined the sustainable and travelling behaviour of the Dutch consumer. While no support has been found for both hypotheses, it still provided some remarkable insights. In particular, the expectation after the pandemic is that there will be an increase in domestic travelling behaviour, while there will be a decrease in international travelling behaviour. With regard to the consumer’s attitude towards sustainability, this study shows an expected increase in the positive holiday environmental attitude of the Dutch consumer after the pandemic. In addition, the preferred mode of transportation is still firstly car, but secondly, it has been changed from airplane to public transport. Since global tourism accounts for more than 8% of the worldwide carbon emissions, it is important to raise awareness about the impact of the consumer’s travelling behaviour on the climate.
6. Reference list
ABN AMRO. (2020). Zorgen over klimaatverandering flink toegenomen tijdens corona Corona zorgt voor gedragsverandering ten gunste van het klimaat. Retrieved from https://www.abnamro.nl/nl/media/20201117_rapport-zorgen-over-klimaatverandering- flink-toegenomen-tijdens-corona_tcm16-91202.pdf
AD. (2020, November 23). Deze grafieken tonen hoe corona invloed heeft op ons reisgedrag . Retrieved June 22, 2021, from https://www.ad.nl/auto/deze-grafieken-tonen-hoe-corona- invloed-heeft-op-ons-reisgedrag~a6f70293a/
Barr, S., & Prillwitz, J. (2012). Green travellers? Exploring the spatial context of sustainable mobility styles. Applied Geography, 32(2), 798–809.
https://doi.org/10.1016/j.apgeog.2011.08.002
CBS. (2018). Milieu en duurzame energie. Retrieved from https://www.cbs.nl/nl- nl/achtergrond/2018/43/milieu-en-duurzame-energie-opvattingen-en-gedrag CBS. (2020). Vakanties van Nederlanders; kerncijfers. Retrieved March 17, 2021, from
https://www.cbs.nl/nl-nl/cijfers/detail/84363NED
CBS. (2021). Mannen en vrouwen. Retrieved June 16, 2021, from https://www.cbs.nl/nl- nl/visualisaties/dashboard-bevolking/mannen-en-vrouwen
Cohen, J. (2013). Statistical Power Analysis for the Behavioral Sciences. Academic Press Inc.
Dickinson, J. E., Lumsdon, L. M., & Robbins, D. (2011). Slow travel: issues for tourism and climate change. Journal of Sustainable Tourism, 19(3), 281–300.
https://doi.org/10.1080/09669582.2010.524704
European Commission. (n.d.). Travel during the coronavirus pandemic . Retrieved June 22, 2021, from https://ec.europa.eu/info/live-work-travel-eu/coronavirus-response/travel- during-coronavirus-pandemic_en
Gelo, O., Braakmann, D., Benetka, G., Gelo, O., Braakmann, D., & Benetka, G. (2008).
Quantitative and Qualitative Research: Beyond the Debate.
https://doi.org/10.1007/s12124-008-9078-3
Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford publications.
Heale, R., & Twycross, A. (2015, July 1). Validity and reliability in quantitative studies.
Evidence-Based Nursing. BMJ Publishing Group. https://doi.org/10.1136/eb-2015- 102129
Higham, J. E. S., Cohen, S. A., & Cavaliere, C. T. (2014). Climate Change, Discretionary Air
Travel, and the “Flyers’’ Dilemma".” Journal of Travel Research, 53(4), 462–475.
https://doi.org/10.1177/0047287513500393
IBM. (n.d.). SPSS Statistics | IBM. Retrieved June 16, 2021, from https://www.ibm.com/products/spss-statistics
Jerosch-Herold, C. (2005). An evidence-based approach to choosing outcome measures: A checklist for the critical appraisal of validity, reliability and responsiveness studies.
British Journal of Occupational Therapy, 68(8), 347–353.
https://doi.org/10.1177/030802260506800803
Juárez-Nájera, M., Rivera-Martínez, J. G., & Hafkamp, W. A. (2010). An explorative socio- psychological model for determining sustainable behavior: Pilot study in German and Mexican Universities. Journal of Cleaner Production, 18(7), 686–694.
https://doi.org/10.1016/j.jclepro.2009.09.018
Kim, D. H., & Jang, S. C. (Shawn). (2017). Therapeutic benefits of dining out, traveling, and drinking: Coping strategies for lonely consumers to improve their mood. International Journal of Hospitality Management, 67, 106–114.
https://doi.org/10.1016/j.ijhm.2017.08.013
Kwon, J., & Lee, H. (2020). Why travel prolongs happiness: Longitudinal analysis using a latent growth model. Tourism Management, 76, 103944.
https://doi.org/10.1016/j.tourman.2019.06.019
Lee, B. K., Agarwal, S., & Kim, H. J. (2012). Influences of travel constraints on the people with disabilities’ intention to travel: An application of Seligman’s helplessness theory.
Tourism Management, 33(3), 569–579. https://doi.org/10.1016/j.tourman.2011.06.011 Lee, E. H. (2012, December). Review of the psychometric evidence of the perceived stress
scale. Asian Nursing Research. https://doi.org/10.1016/j.anr.2012.08.004
Lenzen, M., Sun, Y. Y., Faturay, F., Ting, Y. P., Geschke, A., & Malik, A. (2018). The carbon footprint of global tourism. Nature Climate Change, 8(6), 522–528.
https://doi.org/10.1038/s41558-018-0141-x
Leonardelli, G. J., Pickett, C. L., & Brewer, M. B. (2010). Optimal Distinctiveness Theory. A Framework for Social Identity, Social Cognition, and Intergroup Relations. In Advances in Experimental Social Psychology (Vol. 43, pp. 63–113). Academic Press Inc.
https://doi.org/10.1016/S0065-2601(10)43002-6
Li, J., Nguyen, T. H. H., & Coca-Stefaniak, J. A. (2020). Coronavirus impacts on post- pandemic planned travel behaviours. Annals of Tourism Research.
https://doi.org/10.1016/j.annals.2020.102964
Menut, L., Bessagnet, B., Siour, G., Mailler, S., Pennel, R., & Cholakian, A. (2020). Impact of lockdown measures to combat Covid-19 on air quality over western Europe. Science of the Total Environment, 741, 140426. https://doi.org/10.1016/j.scitotenv.2020.140426 Murairwa, S. (2015). Voluntary Sampling Design. International Journal of Advanced
Research in Management and Social Sciences.
Paswan, A., Guzmán, F., & Lewin, J. (2017). Attitudinal determinants of environmentally sustainable behavior. Journal of Consumer Marketing, 34(5), 414–426.
https://doi.org/10.1108/JCM-02-2016-1706
Wachyuni, S. S., & Kusumaningrum, D. A. (2020). The Effect of COVID-19 Pandemic: How are the Future Tourist Behavior? Journal of Education, Society and Behavioural
Science. https://doi.org/10.9734/jesbs/2020/v33i430219
Wang, M., Liu, F., & Zheng, M. (2020). Air quality improvement from COVID-19 lockdown: evidence from China. Air Quality, Atmosphere and Health.
https://doi.org/10.1007/s11869-020-00963-y
Zenker, S., Braun, E., & Gyimóthy, S. (2021). Too afraid to Travel? Development of a Pandemic (COVID-19) Anxiety Travel Scale (PATS). Tourism Management, 84, 104286. https://doi.org/10.1016/j.tourman.2021.104286
Zheng, D., Luo, Q., & Ritchie, B. W. (2021). Afraid to travel after COVID-19? Self-
protection, coping and resilience against pandemic ‘travel fear.’ Tourism Management.
https://doi.org/10.1016/j.tourman.2020.104261
7. Appendix Table A1
Baseline characteristics of travelling behaviour of Dutch consumers
Total (n = 229)
Demographics Female, n (%) 192 (83.8)
Age 47 [28.3-59.0]
Education
Master’s degree 76 (33.2)
Bachelor’s degree 73 (31.9)
High school 59 (25.8)
Other 21 (9.1)
Annual household incomea,b 3.0 [2.0-4.0]
Travelling behaviour Pre-
pandemic
Post- pandemic
Domestically n = 226 n = 226
0x 27 (11.9) 20 (8.8)
1-3x 160 (70.8) 160 (70.8)
4-10x 30 (13.1) 37 (16.3)
>10x 17 (7.3) 9 (3.8)
Internationally n = 226 n = 225
0x 21 (9.3) 36 (16.0)
1-3x 177 (78.2) 170 (75.5)
4-10x 27 (11.8) 18 (7.9)
>10x 2 (0.8) 1 (0.4)
Pre- pandemic
Post- pandemic Mode of transportation
Car 139 (60.7) 138 (60.3)
Airplane 53 (23.1) 26 (11.4)
Public transport 20 (8.7) 42 (18.3)
Bike 6 (2.6) 12 (5.2)
Motorcycle 0 (0.0) 1 (0.4)
Walking 1 (0.4) 0 (0.0)
Boat/ship 5 (2.2) 5 (2.2)
Other 5 (2.2) 5 (2.2)
Note. Data is outlined as n (%), when not normally distributed as mean [SD]. a not normally distributed, outlined as mean [SD]. b 1: less than 25.000, 2: 25000-50.000, 3: 50.000-100.000, 4:
100.000-200.000, 5: >200.000, 6: I prefer not to say.
Table A2
The pre-validated scales used for the questionnaire
Scale Cronbach’s alpha
1. Active sustainable behavior scale (Paswan et al., 2017) 0.690 – 0.820 2. Psychological stress - the perceived stress scale (Lee,
2012)
> 0.700
3. Intention to travel (B. K. Lee et al., 2012) 0.760 4. Positive holiday environmental attitudes (Barr &
Prillwitz, 2012)
0.762
6. Pandemic (COVID-19) Anxiety Travel Scale (PATS) (Zenker et al., 2021)
0.930
7. Support of public transport on holiday (Barr & Prillwitz, 2012)
0.705
Note. The items of the mentioned scales were measured with a Likert-scale (1 = strongly disagree, 5 = strongly agree).
Table A3
The results of the reliability analyses for each scale
Variable n Cronbach’s alpha
1. Active sustainable behaviour 229 0.855
2. Perceived psychological stress 200 0.885
3. Intention to travel 221 0.808
4. Positive holiday environmental attitudes_before pandemic
211 0.758
5. Positive holiday environmental attitudes_after pandemic
207 0.772
6. Pandemic Anxiety Travel Scale (PATS) 221 0.871
7. Support of public transport on holiday_before pandemic
211 0.842
8. Support of public transport on holiday_after pandemic
207 0.776
Note. Data is outlined as Cronbach’s alpha. The items of the mentioned scales were measured with a Likert-scale unless indicated otherwise (1 = strongly disagree, 5 = strongly agree).
Table A4 Questionnaire
Question Answer options
1. How would you describe your gender? Male Female
Non-binary / third gender Prefer not to say
2. What is your age Numerical input
3. What is the highest level of education you have achieved?
Master’s degree or above Bachelor’s degree Highschool Other
I prefer not to say 4. What is the level of your annual household
income?
Less than €25,000
€25,000 - €50,000
€50,000 - €100,000
€100,000 - €200,000 More than €200,000 I prefer not to say 5. Please read the following statements and rate
them from strongly disagree to strongly agree.
I make every effort to buy paper products made of recycled paper.
Whenever possible, I buy products in reusable containers.
Whenever possible, I buy products that come in packages that can be recycled.
I will not buy products which have excessive packaging.
I have switched products for environmental reasons.
I always purchase products that are less harmful to the environment.
I do not buy household products that harm the environment.
I have convinced my family or friends not to buy products that are harmful for the
environment.
6. On average, how many times per year did you travel before the start of the corona pandemic?
Please only consider travelling for a holiday.
Before the pandemic, domestically:
Before the pandemic, internationally:
7. What was your most frequently used mode of transportation when going on a holiday before the corona pandemic?
Car (or camper/caravan) Airplane
Public transport Bike
Motorcycle Walking Boat/ship Other 8. On average, how many times per year do you
expect to travel after the corona pandemic (assume the situation is back to before the pandemic)?
After the pandemic, domestically:
After the pandemic, internationally:
9. Please read the following statement and rate it from strongly disagree to strongly agree.
I only want to travel to countries where the major part of the citizens is vaccinated.
10. What do you expect will be your most frequently used mode of transportation when going on a holiday after the corona pandemic?
Car (or camper/caravan) Airplane
Public transport Bike
Motorcycle Walking Boat/ship Other 11. Please read the following statements
regarding your attitude towards travelling during the corona pandemic and rate them from strongly disagree to strongly agree.
COVID-19 makes me worry a lot about my normal ways of travelling.
It makes me uncomfortable to think about COVID-19 while planning my vacation.
I am afraid to risk my life when I travel, because of COVID-19.
When watching news about COVID-19, I become nervous or anxious in regards to travel.
I do not feel safe to travel due to COVID-19.
I am afraid to risk other people's lives when I travel, because of COVID-19.
12. After the corona pandemic, would you rather travel to closer destinations (NL or in Europe) or faraway destinations (Asia or South America)?
Closer destinations Faraway destinations Both
None I don't know 13. Please read the following statements
regarding your general intention to travel and rate them from strongly disagree to strongly agree.
Whenever I have a chance to travel, I will.
I try my best to travel frequently.
I will keep on gathering travel-related information in the future.
14. Imagine your life before the start of the corona pandemic. Please read the following statements regarding holiday travel and rate them from strongly disagree to strongly agree (from your viewpoint before the pandemic).
I don't worry about the environment when I make choices concerning my holiday travel.
I am unlikely to change my holiday plans in response to issues like global climate change.
I think about how I can reduce environmental damage when I go on holiday.
I am very concerned about environmental issues.
I prefer to avoid highly polluting forms of transport like air travel when I go away.
A 'personal carbon budget' would reduce the amount you travel using high-polluting travel modes.
I try to avoid public transport when I go on holiday.
I like to use public transport when I am on holiday.
15. Imagine your life after the corona pandemic, where you can travel without restrictions and testing, etc. Please read the following
statements regarding holiday travel and rate them from strongly disagree to strongly agree
I don't worry about the environment when I make choices concerning my holiday travel.
I am unlikely to change my holiday plans in response to issues like global climate change.
(from your estimated viewpoint after the pandemic).
I think about how I can reduce environmental damage when I go on holiday.
I am very concerned about environmental issues.
I prefer to avoid highly polluting forms of transport like air travel when I go away.
A 'personal carbon budget' would reduce the amount you travel using high-polluting travel modes.
I try to avoid public transport when I go on holiday.
I like to use public transport when I am on holiday.
16. The questions in this scale ask you about your feelings and thoughts during the corona pandemic. You will be asked to rate how often you felt or thought a certain way.
How often have you been upset because of something that happened unexpectedly?
How often have you felt that you were unable to control the important things in your life?
How often have you felt nervous and 'stressed'?
How often have you felt confident about your ability to handle your personal problems?
How often have you felt that things were going your way?
How often have you found that you could not cope with all the things that you had to do?
How often have you been able to control irritations in your life?
How often have you felt that you were on top of things?
How often have you been angered because of things that were outside of your control?
How often have you felt difficulties were piling up so high that you could not overcome them?
Note. The statements are rated on a 5-point Likert scale ranging from strongly disagree to strongly agree, unless indicated otherwise. a 1 = never , 5 = very often.
