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. 2022 Dec 23;27:100757. doi: 10.1016/j.jdmm.2022.100757

How COVID-19 impacts travel-health information seeking and tourists’ travel intentions: A protection motivation theory-based model

Arej Alhemimah 1
PMCID: PMC9780641

Abstract

This study investigates health-information seeking influences on tourists' travel intentions during and after the COVID-19 pandemic, in the context of online information.An integrative model based on Protection Motivation Theory (PMT) is developed to examine the relationships between protection motivation behaviour incorporating COVID-19 involvement, and their influence on information seeking attitude and travel intention, while considering the role of subjective norms (SNs) as a moderator between attitude and intention.Using the data collected from 274 international tourists in Saudi Arabia, this research shows that, while not all PMT factors have a positive influence on travel intention, COVID-19 involvement has the strongest influence, while SNs found to have non-significant role as a moderator.This study's findings include important implications for industry practice within the online travel-health information seeking context.

Keywords: Online information seeking, Tourist risk behaviour, Travel intention, COVID-19 involvement, Subjective norms, E-marketing

1. Introduction

The sudden appearance in December 2019 of the SARS-COV2 virus and the resulting COVID-19 pandemic caused enormous loss of life and disruption, even destruction, of livelihoods.In order to limit the spread of COVID-19, one of the first measures taken by governments worldwide was to issue travel restrictions; most imposed stringent quarantine requirements and many closed their borders (Boros et al., 2020).People who had already planned or were in the process of planning travel (whether for business, tourism, or personal reasons) would normally have been searching online for details about their destinations.Search engine data shows that they began seeking information about “novel coronavirus” and “COVID-19”: not just regarding symptoms and prevention (Bento et al., 2020), but also about current COVID-related travel advisories and restrictions.Although both traditional mass media (e.g., newspapers, radio, television) and internet-based media (e.g., Google/Bing search, Instagram, Facebook, WhatsApp) serve as sources of information about COVID-19 and the pandemic (Soroya et al., 2021), when people want to book their own tourism trip, over 80% of them prefer to use online travel websites to arrange their flights bookings (Deane, 2021).In response to the sharp increases in online searches for travel information about COVID-19 restrictions and other risks related to travelling during and post-pandemic, Google augmented its search tools to include COVID-19 related travel advisories, up-to-date airline policies, and even public health data on current infection rates in destination countries (Holden, 2021a; 2021b).As people's social behaviours have changed and may not return to pre-pandemic norms in the near future, the same would apply to tourists' information seeking behaviour.The influence of perceived health threats stemming from the COVID-19 pandemic on tourists' protective behaviour and involvement, and the subsequent effect on travel intention, is a vital subject that has yet to be examined empirically.

In travel and tourism, there are intangibles and many unknowns for the consumer; moreover, the economic and health risks associated with travel decision-making can be substantial (Loda et al., 2009).One important way for tourists to try to reduce the risks associated with travel is to engage in information seeking (Wang, Liu-Lastres, Ritchie, & Mills, 2019a).To date, few studies have examined the influence of information seeking on tourists' travel intentions during high travel threat situations such as the COVID-19 pandemic.This study aims to address this gap by investigating the relationships between travellers’ health protection perceptions and their intentions to travel.

This paper is therefore concerned with the influence of information seeking from a protection motivation theory (PMT) perspective, and its influence on travel intention among tourists in Saudi Arabia.More specifically, it investigates the links between tourists’ perceptions of threat severity, susceptibility, self-efficacy, and response efficacy, together with their COVID-19 involvement, and the influence of all these factors on information seeking attitude, and in turn, on tourist travel intention, while assessing subjective norms role as a moderator between attitude and intention.

The current study examines the travel health-information about COVID-19 on travel websites, which provide links from official sources such as government public health and industry platforms, to the prospective tourists to read travel health-information and advisories pertaining to their destination.

1.1. Information seeking in tourism

When people perceive a gap between what they know and what they want or need to know (i.e., information insufficiency), they will engage in information seeking behaviour (ter Huurne, 2008; Chang & Huang, 2020).The trend continues in which people rely less and less on traditional print and broadcast media and have increasingly turned to online sources for information.In response to this long-term shift, tourism companies and advocates need to understand user behaviour in the online environment in order to appeal to customer interests and needs (Alhemimah, 2019; Radic et al., 2020).

As greater quantities (with varying degrees of quality) of health information have been made available on the web (Jaafar et al., 2017), more tourists now conduct their own health information seeking and are taking on the responsibility for evaluating the related risks (Wang, Liu-Lastres, Ritchie, & Mills, 2019a).Just as they would do in their local environment, when people plan travel or tourism, they try to minimize risk and stay away from settings that they perceive to be unsafe (Godovykh et al., 2021).They would access the information, then based on that information they would form a plan or strategy to manage the risk, and finally they would act in accordance with their strategy (Wang, Liu-Lastres, Ritchie, & Mills, 2019a; Wang, Liu-Lastres, Ritchie, & Pan, 2019b).Previous research on tourists’ health-related decision making has focussed on perceived health risk (Godovykh et al., 2021; Jonas et al., 2011; Zambrano-Cruz et al., 2018), risk reduction strategies (Lo et al., 2011; Wang, Liu-Lastres, Ritchie, & Pan, 2019b), and health protective behaviour (Chien et al., 2016; Wang, Liu-Lastres, Ritchie, & Mills, 2019a).

As mentioned earlier, prior to and during their trip, tourists will seek information as they try to manage and mitigate risk.The study samples in previous studies on information seeking and health protective behaviour have tended to be residents rather than tourists (Cahyanto & Pennington-Gray, 2015).Thus, the following section discusses information seeking as a risk reducing strategy—or protective behaviour—for tourists.

1.2. Information seeking as protective strategy for tourists

A protective strategy that combines risk reduction strategy and information seeking is risk communication.Risk communication has been defined as “the exchange of information and opinions concerning risk and risk-related factors among risk assessors, risk managers, consumers and other interested parties” (Food and Agriculture Organization (FAO) of the United Nations, 1999, Chapter 3; paragraph 3).Jeuring and Becken (2013) have noted that “risk communication is part of a social process, which includes active participation of end-users (e.g., tourists)” in which they “actively seek for information” (Jeuring & Becken, 2013, p.195).Additionally, a recent study has looked at the influence of risk perception on Chinese tourists’ travel intention during the COVID-19 pandemic and found that risk perception predicted their information seeking process (Meng et al., 2021).

2. Theoretical background and hypothesis development

In examining the relationship between protection motivation perceptions and travel intention within online information context, this study extends the PMT theory by including COVID-19 involvement as antecedent of information seeking attitude, and includes travel intention as the likely outcome resulting from health travel-information that posted on travel websites, while considering subjective norms as a moderator between attitude and intention.

According to PMT, people use both threat appraisal and coping appraisal in order to protect themselves from harm.Threat appraisal involves both the perceived severity of a threat and the individual's perceived susceptibility to a threat.Coping appraisal refers to how individuals respond to the threat, and involves both perceived response efficacy, which is their expectation that performing a certain action will remove the threat, and perceived self-efficacy: believing in their own ability to carry out that action with the desired end result (Rogers, 1983).

Researchers have put forward various theoretical frameworks to identify the factors that lead to information seeking behaviour.Among these are the Risk Information Seeking and Processing model (RISP: Griffin et al., 1999), Planned Risk Information Seeking Model (PRISM: Kahlor, 2010), and the Framework for Risk Information Seeking (FRIS: ter Huurne, 2008).These models all incorporate elements from Ajzen's (1991) theory of planned behaviour (TBP); specifically, they posit that subjective norms (informational/information seeking), perceived risk, perceived information (in)sufficiency, response efficacy, and issue engagement/involvement are predictors of risk information seeking (ter Huurne, 2008; Kahlor, 2010).

The influence of these factors on people's individual risk perceptions and in turn on their behaviour was manifested during the SARS-COV-2 global outbreak, for example: “While some people strictly follow government guidelines and generally accept rules of isolation, social distancing, and sanitation, others ignore these norms” (Godovykh et al., 2021, p.738).That is, subjective norms, individual differences, and contextual factors influence travellers' perceptions of risk, which in turn impact their attitudes, behavioural intentions, and ultimately, their behaviour (Jonas et al., 2011).

The aim of the present study is to examine empirically and thus to validate the moderating role of attitude towards information seeking in the relationships between tourists’ perceptions of severity (PSEV), susceptibility (PSUS), response efficacy (REFCY), self-efficacy (SEFCY), COVID-19 involvement (INVOLV), and travel intention (TINT), while considering subjective norms (SN) as a moderator between attitude and intention.In examining the influence of the aforementioned variables and identifying the most influential variables, the current study aims to contribute to and enhance knowledge of this topic.Fig.1 presents the conceptual framework and the study hypotheses.

Fig.1.

Fig.1

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Theoretical framework and hypothesis development based on PMT theory.

2.1. Protective behaviour and attitude towards information seeking

As discussed above, the body of literature on risk perception in travel and tourism is growing.Protection motivation theory (PMT; Rogers, 1983) is a framework that accounts for the perception and evaluation of aspects of risk.PMT has long been utilized in research in health (e.g., Guo et al., 2015; Pechmann et al., 2003; Rippetoe & Rogers, 1987), more recently in travel and tourism (e.g., Badu-Baiden et al., 2016; Chen et al., 2020; Horng et al., 2014), and quite recently in literature examining the intersection of health and travel/tourism (e.g., Fisher et al., 2018; Itani & Hollebeek, 2021; Wang, Liu-Lastres, Ritchie, & Mills, 2019a).Studies which empirically examine how or whether threat appraisal or coping appraisal influence protection motivation in travellers and tourists are still scarce, however, and their results seem to conflict.Horng et al.(2014) found that perceived severity (a construct of threat appraisal) had the strongest influence on protection motivation, whereas Fisher et al.(2018) reported nonsignificant influence from the threat appraisal constructs, but rather that coping appraisal significantly predicted protection motivation and subsequent intention (handwashing to prevent norovirus infection).Wang, Liu-Lastres, Ritchie, and Mills (2019a), in contrast, found that both threat appraisal and coping appraisal influenced protection motivation and behavioural intention.

It is clear that further research is needed to provide additional evidence as to the influence of these factors on tourists’ protection motivation and behavioural intention.Moreover, these studies focussed on intention to engage in protective behaviours, not on intention to travel.Therefore, this present study is aimed at understanding, not only the influence of threat and coping appraisal on protection motivation in terms of information seeking attitude, but also the subsequent influence of these relationships on travel intention.

2.1.1. Perceived threat severity and attitude towards information seeking

Perceived severity is one of two threat appraisal constructs in PMT.It refers to a person's evaluation of the degree of potential harm, including illness.People's behavioural intentions tend to modulate based on the degree of severity and risk of harm they perceive (Weinstein, 2000).This relationship can be explained as a push-and-pull effect: the perceived severity of an existing health threat increases negative attitudes towards behaviours that increase such a risk (the push), and simultaneously increases positive attitudes towards behaviours that reduce the risk (the pull) (Amuta et al., 2016).Furthermore, perceived threat severity influences motivation to seek information, which also applies to searching online for travel-health information (Basnyat et al., 2018).Thus, tourists who perceive a higher degree of threat severity are more likely to seek health travel-instructions about COVID-19 in order to reduce their health risks.This relationship can be explained as a push-and-pull effect.That is, a perceived risk of being susceptible to an existing health threat can result in less favourable attitudes towards behaviours that are associated with that threat, and at the same time foster more favourable attitudes towards actions that might reduce the threat (Amuta et al., 2016).Therefore,

H1

Perceived severity positively influences attitude towards information seeking.

2.1.2. Perceived susceptibility and attitude towards information seeking

Perceived susceptibility is the second threat appraisal construct in PMT.It can be defined as an individual's assessment of their personal vulnerability and exposure to risk.Perceived susceptibility, like perceived severity, involves the push-and-pull effect described above (Amuta et al., 2016).Perceived susceptibility has been found to correlate positively with preventive and protective health behaviour (Wang, Liu-Lastres, Ritchie, & Mills, 2019a).For instance, high perceived susceptibility to COVID-19 was found to be associated with preventive behaviours and information seeking (Gunderson et al., 2020).Perceived severity, like perceived susceptibility, involves the push-and-pull effect described above.Thus, the perceived severity of an existing health threat can result in less favourable attitudes towards actions associated with that threat, while it can also result in more favourable attitudes regarding actions that could reduce the health threat (Amuta et al., 2016).Therefore, tourists are more likely to seek travel-health instructions about COVID-19 when they perceive that they are vulnerable to catching COVID-19.Thus,

H2

Perceived susceptibility positively influences attitude towards information seeking.

2.1.3. Response efficacy and attitude towards information seeking

Response efficacy is the first of two coping appraisal constructs in PMT.It refers to an individual's evaluation of the effectiveness of the coping response at or removing or mitigating a threat.Response efficacy has been found to correlate positively with preventive and protective health behaviour (Itani & Hollebeek, 2021).Fisher et al.(2018) reported that response efficacy significantly predicted protection motivation and behavioural intention of cruise ship passengers (to engage in handwashing to prevent viral infection).Two meta-analyses conducted at around the same time (Floyd et al., 2000; Milne et al., 2000), showed positive relationships between response efficacy and protective health behaviour as well as self-efficacy and protective behaviour.

According to TPB, attitude refers to an individual's evaluation (positive, neutral, or negative) regarding carrying out a behaviour, and people's beliefs determine their attitudes (Ajzen, 1991).A person who thinks that engaging in a certain activity would reduce the risk of a perceived health threat would be more likely to have a positive attitude towards performing that behaviour.

Given that contracting COVID-19 is considered a threat, seeking information about it should lower the uncertainty or risk.If users feel that information seeking cannot effectively protect them from catching the disease during travelling, they are less likely to seek such information.Conversely, tourists with high response efficacy would be more likely to seek online travel-health instructions about COVID-19.Hence,

H3

Response-efficacy positively influences attitude towards information seeking.

2.1.4. Self-efficacy and attitude towards information seeking

Self-efficacy is the second coping appraisal construct in PMT.It refers to a person's assessment of the degree to which he/she is capable of carrying out a recommended coping action.Bandura (2004) noted that self-efficacy influences health behaviours.Itani and Hollebeek (2021) reported that self-efficacy was also an antecedent of protection motivation and behavioural intention (e.g., social distancing to prevent contracting COVID-19).Self-efficacy in performing health-protective behaviours is associated with health information seeking (Myrick, 2017).As mentioned, according to TPB, attitude moderates the relationship between beliefs and behaviour.A positive attitude towards a behaviour increases the likelihood of behavioural intention (Ajzen, 1991).Therefore, tourists with high self-efficacy would be more likely to seek online travel-health instructions about COVID-19.Thus,

H4

Self-efficacy positively influences attitude towards information seeking.

2.1.5. COVID-19 involvement and attitude towards information seeking

Involvement is an important construct from the Elaboration Likelihood Model of persuasion (Petty et al., 1983).Involvement has been defined as “a motivational state induced by an association between an activated attitude and the self-concept” (Johnson & Eagly, 1989, p.290).It refers to a person's ability and willingness to engage cognitively with something (e.g., a product, an ideology), including their level of personal interest and their evaluation of risk associated with that subject, such as financial risk or social risk (Cole et al., 1990).It is this process of recognizing a problem that activates people's involvement and thus their motivation to seek information (ter Huurne, 2008).

The higher the perceived risk, the greater the level of involvement (Johnson, 2005).Moreover, involvement correlates with positive attitude towards information seeking (Johnson, 2005; Kahlor et al., 2003; ter Huurne, 2008).Research has suggested that involvement was positively associated with affective (emotional) response and perceived information insufficiency, (the perceived gap between one's information needs and current knowledge) thus increasing information seeking motivation (ter Huurne, 2008).Therefore, tourists with high COVID-19 involvement would be more likely to seek online health travel-instructions about COVID-19.Hence,

H5

COVID-19 involvement positively influences attitude towards information seeking.

2.1.6. Attitude towards information seeking and travel intention

Information seeking as a protection motivation has been discussed in the Introduction.Travel-health information seeking can assist tourists in understanding what options are available to them, how to mitigate risk and uncertainty, and reduce fear and anxiety and thus influence travel-health decision making (Godovykh et al., 2021).In the case of the SARS-COV2 virus, information seeking behaviour has been seen to be driven by perceptions and beliefs about how COVID-19 is spread and how to prevent it (Skarpa & Garoufallou, 2021).Skarpa and Garoufallou (2021) posited that health information seeking behaviour, in particular, seeking information via authoritative sources (e.g., government websites and television channels) and avoiding doubtful sources (e.g., social media posts) influenced adoption of preventive or protective behaviours aimed at reducing the spread of COVID-19.

Perceived risk influences travellers’ decisions regarding tourist destinations (Cahyanto & Pennington-Gray, 2015; Meng et al., 2021).As mentioned, according to TPB, attitude moderates the relationship between beliefs and behaviour, such that having a positive attitude towards a behaviour increases intention to engage in that action, and conversely, an unfavourable attitude towards an activity negatively influences the intention to engage in it (Ajzen, 1991).Risk perception is a belief, so it influences attitude towards a behaviour that carries or mitigates risk, which in turn influences the intention to perform that behaviour (Griffin et al., 1999).

In the current study model, perceived threat severity, perceived susceptibility, self-efficacy, response efficacy, and COVID-19 involvement, each influence attitude towards online travel-health information seeking, and subjective norms moderate the relationship between attitude towards online travel-health information seeking and travel intention.Therefore, tourists with a high level of travel-health information seeking would have a greater intention to travel.Thus,

H6

Attitude towards information seeking positively influences travel intention.

2.1.7. Subjective norms as a moderator

Subjective norms (SN) are a concept central to TPB (Ajzen, 1991).It refers to an individual's perception of how people who are important to that individual—and these may include family, friends, colleagues, or others in their social network—might evaluate or judge that individual positively or negatively for performing a particular action or behaviour (Alhemimah, 2019).In the literature on risk information seeking, informational subjective norms (ISN) are a person's perception of whether those significant referents attach value to risk information seeking (ter Huurne, 2008).According to TPB, subjective norms influence an individual's behavioural intention and subsequently, the actual behaviour (Ajzen, 1991).In the same way, ISN influences information seeking behaviour, which aids a person's decision making (Griffin et al., 1999).As with involvement, ISN has been found to be associated with perceived information insufficiency and affective response, indirectly motivating information seeking (Kahlor, 2007; ter Huurne, 2008).

A cross-cultural study comparing tourists from China and tourists from the United States (Aliperti & Cruz, 2019) showed the significant role played by SN on tourists’ information seeking behaviour, finding that tourists who were highly influenced by subjective norms would seek more information about a health/safety risk at the destination prior to travel.That is, in accordance with TPB, those tourists pay attention to the opinions of the people or groups who are important to them (Ajzen, 1991), and if those important referents indicated their approval of travel-health information seeking behaviour, the individual tourists had a higher probability of seeking such information prior to travel.In other tourism research, SN have been found to have either direct (Alhemimah, 2019) or indirect (Kim et al., 2009; Wong et al., 2021) influence on behavioural intention.In the latter, other factors may interact with SN to increase or decrease the influence of SN on behavioural intention.Hence,

H7

Subjective norms moderate the relationship between attitude towards information seeking and travel intention.

3. Methods

Data was collected from 263 international tourists in Saudi Arabia.In this research, the sampling frame comprised individual potential tourists, aged 18 years or older, residing in Saudi Arabia, who during the previous 12 months had tourism trip.This time frame was employed in another tourism study (Ayeh et al., 2013) in which an online survey elicited data from participants who reported engaging in online travel information seeking and had taken at least one tourism trip during the previous year.

The respondents were sourced from potential travellers encountered at the main international airport in Jeddah, Saudi Arabia.The survey took place from 7 June to August 15, 2021.Due to COVID-19 precautions, an online barcode was generated to access the questionnaire, then the survey link was distributed via barcode.The participants were asked to share it among their companions.At the start of the questionnaire, respondents were given an explanation of what was meant by “COVID-19 travel instructions” and “travel websites”.To ensure data quality, a screening question was asked at the beginning of the questionnaire: respondents were asked whether they had used travel websites to book their tourism flight during the past year.If “‘never” was the selected response, they would not be able to complete the questionnaire.The survey proceeded with relevant questions, such as requests to indicate their frequency of reading travel instructions before a tourism trip (always, usually, sometimes, rarely, never) and to name a specific travel website.These questions were intended to assist respondents in recalling the required information.

Of the 263 participants who accessed and completed the Arabic questionnaire, 253 passed the screening question.There were 24 respondents who accessed the English version of the questionnaire, of which 21 passed the screening question.All items in the questionnaire were mandatory, so there could be no incomplete responses.A total of 274 completed questionnaires were received, comprising the entire dataset for this study.As shown in Table 1 , the largest cohort of participants were 35–44 years old (28%), followed by 45–54 years old (27.7%).The sample was not evenly distributed with regard to gender: the proportion of male participants was substantially higher (approx.83%).However, the gender distribution of this sample is typical for Saudi Arabia:, in 2018, a statistical report on gender distribution of various activities shows that only 27% of travellers abroad were female (General Authority for Statistics, 2018).With regard to educational attainment, half of the sample (50%) held a bachelor degree.Most of the sample participants were Saudi nationals; only around 12% of the participants were of other nationalities.

Table 1.

Participant characteristics.

Characteristics Percent
Gender
Male 83%
Female 16%
Age
18–24 9.4%
25–34 17.8%
35–44 28%
45–54 27.7%
55–64 9.9%
>65 1%
Education
High school 16.7%
Diploma 14.6%
Bachelor degree 50%
Master degree 13.9%
PhD 4.7%
Other 1%
Marital status
Single 17%
Married 78.8%
Divorced 4%
Number of trips
Have not travelled 15%
1-3 times 65.7%
4-6 times 12.7%
More than 6 times 5.5%
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In order to ensure the absence of common method bias, Harman's single-factor test was performed.If factor analysis results in a single factor that accounts for more than 50% of the variances in the model, this would indicate the presence of common method bias.The first factor explained less than 50%, thus common method bias can be considered absent (Podsakoff et al., 2003).

3.1. Measures

Perceived severity (PSEV) was measured by four items adapted from Witte (1996) to describe perceived seriousness of COVID-19.For perceived susceptibility (PSUS), four items were adapted from Rippetoe and Rogers (1987) and Witte (1996).Response efficacy (REFCY) was measured by three items adapted from Floyd et al.(2000), Rippetoe and Rogers (1987), and Witte (1996).A 3-item scale adapted from Witte (1996) was employed to measure self-efficacy (SEFCY).COVID-19 involvement (INVOLV) was assessed by adapting two items from Johnson (2005).Five items measuring subjective norms (SN) were adapted from Ajzen (2002) and Kahlor (2010).Four items to capture travel-health information seeking attitude (ISEEK) were adapted from Lee et al.(2012).Finally, travel intention (TINT) was captured using three relationship statements adapted from Erkan and Evans (2016) and Coyle and Thorson (2001).Responses to all items were captured by a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree).(See Appendix for details.)

3.2. Control variables

The study controlled for tourists’ gender, age, education, marital status, and number of previous trips.The survey respondents were mostly male (85.8%), while only 14.2% were female.The average age was between 35 and 44 years.About half of the participants held a bachelor degree (50.2%), and most were married (80.2%).A substantial proportion (68.4%) of participants had travelled 1–3 times during the previous year.

4. Analysis

Partial least squares structural equation modelling (PLS-SEM) using WarpPLS 7.0 to investigate the multiple relationships in the study model.PLS-SEM uses factor analysis and regression and involves a number of different techniques and multivariate methods, in order to analyse a network of related effects.PLS-SEM is often employed in travel and tourism literature (e.g., Ayeh et al., 2013; Alhemimah, 2019).Moreover, PLS-SEM is recommended for research involving development and testing of a theory (Hair et al., 2016).The current research examines the influence of protection motivation behaviour on online information seeking.The study expands the PMT model by including COVID-19 involvement, and linking protection motivation behaviour to travel intention, while considering subjective norms as a moderator between information seeking attitude and travel intention, hence involving theory development.PLS-SEM can also be used with non-normal data.Furthermore, PLS-SEM is suitable for research that aims to identify key constructs, and/or to predict outcomes (Hair et al., 2016).Scores are assigned to latent variables, such that when analysed together, the residuals (the difference between observed and predicted correlations) are minimized.Using PLS-SEM, the relationships between the constructs in the path model are analysed to ensure that R 2 values are maximized.Indicators of endogenous latent variables are evaluated using Stone-Geisser Q 2 values (Hair et al., 2016).This study seeks to explain how attitude towards information seeking mediates between tourists’ perceptions of severity, susceptibility, response efficacy, and self-efficacy, their COVID-19 involvement, and their travel intention.It also seeks to understand the role of subjective norms in the relationship between attitude to information seeking and travel intention.The study model is complex and involves 8 constructs, making PLS-SEM an appropriate analytical tool.

4.1. Measurement model

The measurement model was evaluated by examining both reliability and validity of the constructs.The convergent validity of all constructs was tested.The loadings (correlation coefficients for variables and factors), composite reliability (CR) and Cronbach's alpha of the constructs were checked.However, composite reliability may exaggerate the reliability of scores for constructs, whereas Cronbach's alpha may present them as less reliable than they are.When the model has common factors, Dijkstra and Henseler (2015) advise the use of an additional coefficient for reliability: rho (ρA).This version of PLS is known as consistent PLS (PLSc).The threshold for ρA is 0.7 for exploratory research (Dijkstra & Henseler, 2015).

As shown in Table 2 , all factors had Cronbach's alpha values were between 0.67 and 0.91 for all constructs: greater than the recommended minimum convergent validity value, and the reliability coefficient ρA of each measurement construct is above 0.7.

Table 2.

Indicator loadings, CR, ρA, and Cronbach's alpha.

Construct CR ρA Cronbach's alpha VIF
Perceived Severity .935 .915 .908 2.302
Perceived Susceptibility .885 .891 .827 2.163
Response Efficacy .912 .905 .855 2.627
Self-Efficacy .915 .894 .860 2.896
COVID-19 Involvement .914 .910 .811 1.968
Subjective Norms .916 .914 .884 2.240
Attitude towards Information Seeking .858 .845 .669 1.660
Travel Intention .919 .902 .867 1.157
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With PLS-SEM, the structure and content of the survey instrument may introduce common method bias (Kock, 2015).Thus, it is advised to use the full variance inflation factor (VIF) for each predictor variable in order to identify any common method bias, as well as to measure full collinearity (Kock & Lynn, 2012).As can be observed in Table 2, all VIFs are lower than 3, which indicates an absence of both multicollinearity and common method bias between the constructs (Kock, 2015, p.7).Item loadings were used to check the validity of each construct (see Appendix).Additionally, in order to determine whether or not a measurement was a reflection of any other measurement, discriminant validity was checked.The square roots of AVE for each variable are presented in Table 3 .As shown in Table 4 , the Heterotrait–Monotrait ratio (HTMT), values were lower than the recommended maximum (0.90) for comparable constructs, such as response efficacy with self-efficacy (Henseler et al., 2015).All other HTMT values fell far below the more stringent threshold of 0.85.In all, the HTMT ratio, together with Dijkstra-Henseler's rho (ρA) and the cross-loading, strongly supported the discriminant validity of all constructs.The measurement model has been assessed, establishing reliability and validity of the study constructs.The structural model is analysed next.

Table 3.

Squared roots of AVEs.

PSEV PSUS REFCY SEFCY INVOLV SN ISEEK TINT
PSEV (.885)
PSUS .705 (.812)
REFCY .421 .437 (.880)
SEFCY .364 .396 .761 (.884)
INVOLV .472 .472 .551 .615 (.917)
SN .559 .506 .520 .509 .551 (.828)
ISEEK .400 .360 .303 .352 .408 .577 (.867)
TINT .035 .116 .152 .250 .116 .096 .266 (.889)
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Table 4.

Heterotrait–Monotrait ratio (HTMT).

PSEV PSUS REFCY SEFCY INVOLV SN ISEEK TINT
PSEV
PSUS .814
REFCY .477 .521
SEFCY .412 .470 .889
INVOLV .550 .576 .662 .736
SN .626 .595 .598 .585 .654
ISEEK .513 .485 .401 .464 .554 .753
TINT .068 .139 .177 .290 .139 .115 .352
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4.2. Structural model

The model shown in Fig.2 denotes the relationships hypothesized and tested in this study; these relationships are represented by the path coefficients (β).

Fig.2.

Fig.2

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Results of hypothesis testing for 7 relationships in study model.

With respect to the influence on information seeking attitude, Fig.2 illustrates that COVID-19 involvement had the strongest impact (β = 0.21), followed by the relatively lower influences of perceived severity (β = 0.17), perceived susceptibility (β = 0.13), and self-efficacy (β = 0.11), respectively, however, all their beta values are small, which means information seeking was influenced just slightly by these variables.In contrast, the influence of response efficacy and the influence of subjective norms were nonsignificant.Information seeking attitude had a significant effect on travel intention (β = 0.28).Thus, H1, H2, H4, H5, and H6 are accepted, whereas H3, and H7 are rejected.The results of the analysis indicated that COVID-19 involvement, perceived severity, perceived susceptibility, and self-efficacy explain 42% of information seeking attitude; information seeking attitude explains .08% of travel intention.

In the current study, Stone-Geisser's Q2 was employed to assess the relevance of the indicators of endogenous variables and those associated with the other constructs, in predicting the dependent variables.If the value of Q2 is greater than 0, the predictive relevance of a model is considered good (Hair et al., 2016).Q2 for information seeking was 0.377, and for travel intention, 0.088, which supports the predictive relevance of the study model.

In order to assess how strong a predictor variable is relative to the other constructs within the model, the effect size is examined (Hair et al., 2016).Peng and Lai (2012) describe effect size as “the increase in R 2 relative to the proportion of variance that remains unexplained in the endogenous latent variable” (p.473).Table 5 reports the values for the effect sizes.

Table 5.

Effect sizes.

Correlations Effect size
PSEV →ISEEK .019
PSUS →ISEEK .021
REFCY → ISEEK .026
SEFCY → ISEEK .027
INVOLV → ISEEK .048
SN Moderating effect: → TINT .283
ISEEK →TINT .087
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Large, medium, and small effect size values might typically be .35, .15, and 0.02 (Hair et al., 2016; Peng & Lai, 2012).As can be seen from Table 5, the effect size for perceived severity, perceived susceptibility, response efficacy, self-efficacy, and involvement on information seeking were all small, and the effect size for information seeking on travel intention was also small.The effect size for the subjective norms’ moderating effect was 0.283, which indicates a medium effect.

Regarding the mediating effect, only subjective norms had any significant indirect influence on travel intention (p < .001), in addition to the significant direct relationship between subjective norms and attitude.A significant indirect relationship indicates the presence of a mediating effect (Hair et al., 2016; Kock, 2015).Thus, subjective norms had a positive significant effect on travel intention, without the mediation of attitude towards seeking information.

For the moderation test, the results indicate that the effect of subjective norms on the relationship between attitude towards information seeking and travel intention is nonsignificant.Therefore, it can be interpreted that subjective norms do not moderate the influence of attitude towards information seeking on travel intention.Table 6 summarizes the results for each hypothesis tested in this study.

Table 6.

Summary of results for each hypothesis tested.

Hypothesis Test
H1: Perceived severity positively influences attitude towards information seeking. Accepted
H2: Perceived susceptibility positively influences attitude towards information seeking. Accepted
H3: Response-efficacy positively influences attitude towards information seeking. Rejected
H4: Self-efficacy positively influences attitude towards information seeking. Accepted
H5: COVID-19 involvement positively influences attitude towards information seeking. Accepted
H6: Attitude towards information seeking positively influences travel intention. Accepted
H7: Subjective norms moderate the relationship between attitude towards information seeking and travel intention. Rejected
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5. Discussion and conclusion

Understanding tourists' online information seeking behaviour is important to the hospitality, travel and tourism industry, in order to be able to offer adequate services that serve the diverse needs and desires of their customers.COVID-19 adds a new challenge to the industry, as tourists during the pandemic who plan to travel often are recommended/required to follow travel-health instructions issued by authorities and/or travel and hospitality service providers.However, research on seeking health information within the travel and tourism context is scant.Previous studies have looked at travellers' health risk perceptions (e.g., Godovykh et al., 2021; Jonas et al., 2011), how they intend to reduce risk (Lo et al., 2011; Wang, Liu-Lastres, Ritchie, & Pan, 2019b), and the health protective behaviours they engage in before and during travel (Badu-Baiden et al., 2016; Chien et al., 2016; Wang, Liu-Lastres, Ritchie, & Mills, 2019a), and most recently, how health risk perception may influence travel or visit intention (Godovykh et al., 2021; Itani & Hollebeek, 2021).However, few, if any, have examined the influence of tourists’ protective behaviour on attitude towards seeking information in conjunction with involvement, and the subsequent effect on travel intention, while considering the moderating role of subjective norms on the relationship between attitude towards information seeking and travel intention, thus this study has investigated an important research gap.

In order to better understand tourists' travel-health information seeking attitude, this study examined the influence of tourists' COVID-19-related threat appraisal (i.e., tourists' perceptions of the severity of the threat and of their own susceptibility to catching the disease), on information seeking attitude.This research also examined the role of tourists’ coping appraisal vis-à-vis COVID-19 (i.e., their perceived response efficacy and self-efficacy) on information seeking attitude.Moreover, this study investigated the influence of COVID-19 involvement on information seeking attitude.Lastly, it examined the moderating role of subjective norms on the relationship between information seeking attitude and travel intention.

The study results revealed that COVID-19 involvement has the strongest influence on information seeking attitude, leading tourists to actively seek information (i.e., travel-health instructions).Thus, involvement is a significant predictor of seeking information attitude, as previous literature has indicated its influence on information seeking (Johnson, 2005; Kahlor et al., 2003; ter Huurne, 2008).

This finding might be explained by the culture of the majority of participants in the sample, who were Saudi nationals, as the data was collected in Saudi Arabia.One of the dimensions in Hofstede's (1980, 2001) cultural dimensions model is individualist–collectivist.According to Hofstede, Saudi Arabia scores high on collectivism, in which members of a society tend to think of themselves as part of a group rather than as individuals (Hofstede, 1980).Therefore, Saudi people might look for - travel-health related information and consider taking protective behaviour against COVID-19 just because those around them were doing so.Furthermore, previous studies have found differences along lines of nationality in adoption and use of social media (Gretzel et al., 2008), which is relevant for online information seeking.

Moreover, in this study, threat appraisal was found to positively affect tourists' information seeking attitude.In particular, tourists’ perceptions of threat susceptibility and severity influence their attitudes towards information seeking.That is, when individuals perceive that their current travel-health information is not enough, they seek more travel health-information.Thus, the more severe that tourists perceive the threat and contagiousness of COVID-19 to be, the more they seek travel-health information.Previous research has found gender differences in travel information seeking behaviour.For example, men were more likely than women were to seek information related to practicalities such as flights and weather (Kim et al., 2007).Most of the sample respondents were male, which could explain this result in the current study.

Regarding coping appraisal, only self-efficacy was found to have significant influence on information seeking attitude.This result suggests that tourists evaluate information seeking as a protective behaviour that they would be able to do.In contrast, response efficacy was found to have nonsignificant influence on information seeking attitude.This result is surprising, as prior studies have found response efficacy to be predictive of behavioural response to perceived health threats (e.g., Fisher et al., 2018; Floyd et al., 2000; Itani & Hollebeek, 2021; Milne et al., 2000).Therefore, although tourists' assessment is that they are able to seek this information, they do not evaluate this information as an effective protective behaviour.An explanation for the non-significant influence of response efficacy could be that people find the travel-health information to be too complex and difficult to follow.This finding accords with Jeuring and Becken's (2013) finding that “high information needs and low self-efficacy result in attributing responsibility to an external source” (p.200).

In conclusion, although tourists think that COVID-19 poses a severe threat and that they are personally susceptible, and they think seeking information about it is a protective behaviour, they do not assess the current travel-health information as a valid effective protection behaviour from the disease.This finding points out the need to develop and enhance the travel-health information posted on travel websites.

Moreover, the results of this study suggest that tourists’ travel intentions are affected by their information seeking attitude, even though the influence was modest.In other words, when tourists seek travel-health information about COVID-19, this would imply that travel intention is present, which suggests that information seeking may be a behaviour that tourists would engage in when considering travelling in the near future.However, the results show that 92% of variance in travel intention is not explained by attitude towards information seeking.Therefore, more research ought to be conducted about the antecedents of travel intention within the e-information context.

Conversely, those who are not as actively seeking travel-health information tend to have lower intention to travel soon.The study results indicate a nonsignificant moderating role of subjective norms between the relationship of information seeking attitude and travel intention.This result implies that the effect of information seeking attitude on travel intention is not influenced by social influence, whether SN is high or low.Tourists are adjusting their behaviour due to COVID-19.This implies that destination websites should provide a new strategy for online travel-health instructions and advisories that consider tourists' health and safety.In response to the pandemic, tourists are advised or required by the destination authorities to follow updated travel-health information, thus it is expected that more tourists will be searching for and looking at online travel-related information.As previously mentioned, it was reasonable to examine the role of information seeking attitude, and to emphasize its influence on tourists' intentional behaviour.The study confirms the influence of perceived severity, perceived susceptibility, self-efficacy, and response efficacy on information seeking attitude, which indicates how travellers protect themselves and behave during a global health threat.Additionally, it highlights the significant influence of COVID-19 involvement, while subjective norms would not have a moderating influence on the relationship between information seeking attitude and travel intention.The findings point out the necessity of understanding tourists' risk reducing behaviour.Also, it brings attention to the important role of information seeking on tourists' travel intentions.The findings of this study provide new insights into tourists' health behaviours.Beyond using PMT solely to explain tourists' perceptions regarding risky situations, this model extended the PMT by adding two relevant variables within the travel and tourism context and showed the resulting effect on tourists’ travel-health attitudes and intentions.

5.1. Implications and limitations

The analysis conducted in this study extends the existing PMT-based understanding by applying PMT, in conjunction with two other constructs: involvement from ELM, and subjective norms from TPB, to the problem of travel and tourism during a global health threat (COVID-19).In the study model, information seeking is the central protection motivation mechanism.Based on the insights attained, this new model offers a theoretical framework for other health threat/travel-related research.This conceptual model has now been tested and can be utilized to investigate the influence of online travel-health information seeking on behavioural intentions of tourists and travellers in a range of health and safety-related contexts.Another contribution of this research is that through its examination of the role of travel-health information seeking as a protective motivation it adds to the literature in tourism, travel, and health information seeking.Although previous research has shown the positive effects of health information seeking (Basnyat et al., 2018; Gunderson et al., 2020; Jaafar et al., 2017), those studies did not examine it within the travel and tourism context while considering the important roles of subjective norms and involvement.

Additionally, the significant influence of involvement implies that tourists would have a more positive attitude towards seeking travel-health information if they were involved.This finding encourages further research to clarify the aforementioned relationship.

The current study findings provide significant theoretical implications; in particular it found that not all PMT factors are relevant in the Saudi tourism context.This finding could be due to the role of national culture; thus, the study encourages further research to examine the role of culture in the relationship between tourists’ COVID-19 involvement, attitude towards information seeking, and travel intention.Considering the social influence on cognitive and behaviour changes, information provided should be tailored to the local context.

This study contributes to the existing body of knowledge on tourists’ risk reduction behaviour, pointing out for tourism companies, local and national government tourism boards, and travel and destination marketing and management organizations, the importance of providing online travel-health and/or safety information about the destination.The research provides important implications for policy and industry practice regarding online travel-health related information, with a view to improving protection effectiveness and enhancing information content and presentation to serve the needs of tourists from a health protection/prevention motivation perspective.

The implications from these research findings for travel, tourism and hospitality websites are as follows:

First, the results suggest that travel-related sites operated by destination authorities and other stakeholders would benefit from providing the travel information in multiple languages.This has been made clear during the COVID-19 pandemic, when more than ever before, tourists began looking to travel-related websites for information.Second, the study results indicate that those tourists who are more cautious about the disease do not necessarily engage in seeking such information.Hence, tourism managers are advised, not only to update their travel instructions/advisories, but also to improve their websites in terms of accessibility, appearance, features, and so on, in order to ensure that their online information platforms provide the information that tourists and travellers seek and need to feel reassured, safe, and comfortable about booking and taking a trip.

Third, travel and tourism providers should consider the content of travel-health information as a key factor, such that when offered in an adequate way that matches tourists’ needs and desires, it would motivate these customers to engage more actively with the websites and proceed to book their trip.Thus, the study recommends for managers to prepare for potential future pandemics and other public health threats by improving their online travel websites to include most of what a tourist would need to know to be able to travel to the destination.

Travel and tourism industries are among the most affected industries from health threats.Therefore, providing the relevant online information on travel websites is effective within travel and tourism industries (Abubakar & Ilkan, 2016, Chen, Shang, & Li, 2014).In addition, this study highlights that appropriate travel health information should be made available on travel websites/apps and other online platforms, including social media.Tourism marketers should understand their customers’ wants and concerns, and thus deploy appropriate marketing strategies.Travellers often have to comply with multiple requirements (security, health, etc.) before their trip.Therefore, travel companies, airlines, and destination marketers should make as many of these requirements as possible accessible from the same webpage via links (e.g., to updated travel-health advisories, basic travel advice for popular destinations, online portals for uploading COVID-19 vaccination certification and/or PCR certificate, etc.), that would simplify the travel planning process for tourists, and thus strengthen their intention to travel.

The current study assessed the variable “attitude towards seeking travel-health information” in order to examine how protection motivation is manifested in tourists in response to the COVID-19 pandemic.Further research on tourists' travel-health information seeking behaviour is needed in the post-pandemic phase, as it is expected that tourists' behaviour would not simply revert to their pre-pandemic “normal”, but rather tourists and travellers will continue to adapt and change in response to new perceived threats.Thus, tourism managers and marketers should make use of the most updated features within the e-information context, such as offering links in their apps and websites that provide customized information based on individual tourists' needs.This would enhance tourists’ information seeking experiences, which in turn would improve their travel decision-making and promote travel intention.

As with any research project, this study has its limitations.However, it is hoped that these limitations will provide avenues for further study.First, the study design was cross-sectional, meaning it can only depict the observed phenomena at one point in time, and as such, cannot account for changes in the modelled relationships over time.This limitation could be resolved via future longitudinal research using the study model.Second, this study focused on understanding tourists' risk protection attitude in order to predict their travel intentions.It therefore did not examine tourists' actual behaviour.Future studies should consider expanding it to examine tourists' actual travel.Third, the study results suggest that individuals exhibiting higher online information seeking attitude are likely to proceed with their travel intentions, regardless of their self-evaluation of the effectiveness of seeking travel health-information.Thus, future research could further explore this area and assess the relationship between tourists’ risk protection attitude and travel intention.

Fourth, this research only focused on information seeking as a protective behaviour for travelling during the pandemic, thus overlooking other types of protective behaviour to reduce risk of exposure to COVID-19 (e.g., travelling locally by car).Fifth, the research data was collected from only one country, Saudi Arabia, which may not be representative of how tourists in other countries would appraise the threat of COVID-19 and their own coping capabilities to such a travel-health concern.Hence, the generalizability of the research results must be further examined.It is therefore recommended to replicate this study in/across other countries.

The sixth limitation is that data was collected only from participants in an airport; most people who enter an airport have already made the intention to travel, so they would be more likely to have a positive attitude towards future travel as well.Therefore, the study recommends collecting data from participants in locations that are not directly related to travel, such as a shopping mall or the high street.

Author contribution

Dr.Arej Alhemimah: Conceived and designed the analysis, Collected the data, Contributed data or analysis tools, Performed the analysis, Wrote the paper.

Biography

Arej Alhemimah is an Assistant Professor at King Abdul-Aziz University, Jeddah, Saudi Arabia.Her main research interests lie in the areas of tourism marketing, destination management, sustainable tourism, travel behaviour and tourist experience.

Appendix.

TableA 1.

Confirmatory Factor Analysis (PLS Approach)

Constructs Loading Mean SD Confidence Interval
2.5% 97%
Perceived severity
I think COVID-19 pandemic is serious 0.861 4.361 0.908 0.758 0.963
I believe the threat of COVID-19 pandemic is significant 0.908 4.157 0.902 0.806 1.010
I think that COVID-19 pandemic is of high risk 0.915 4.124 0.972 0.813 1.017
COVID-19 pandemic is harmful 0.857 4.150 0.974 0.754 0.960
Perceived susceptibility
There is high probability for someone to contract COVID-19 pandemic 0.800 4.215 0.873 0.696 0.904
I am at risk of getting COVID-19 pandemic 0.837 3.964 1.030 0.734 0.940
COVID-19 pandemic is highly contagious 0.811 4.150 0.943 0.707 0.914
It is possible that I will contract COVID-19 pandemic 0.798 4.026 0.966 0.694 0.902
Response efficacy
COVID-19 travel regulations work in avoiding getting COVID-19. 0.875 3.964 1.082 0.772 0.977
COVID-19 travel regulations are effective. 0.903 3.934 1.043 0.801 1.005
The use of COVID-19 travel regulations, will stop COVID-19 pandemic from spreading 0.862 3.825 1.164 0.760 0.965
Self-efficacy
I can protect myself from being infected by COVID-19 pandemic by following COVID-19 travel regulations. 0.882 3.763 1.132 0.779 0.984
I can effectively follow COVID-19 travel regulations. 0.886 3.927 1.090 0.783 0.988
Personally, I can deal with COVID-19 pandemic by following COVID-19 travel regulations. 0.884 3.807 1.124 0.781 0.986
COVID-19 involvement
It is important to seek information about COVID-19 travel regulations. 0.917 4.164 1.034 0.815 1.019
I am interested in COVID-19 travel regulations. 0.917 4.044 1.054 0.815 1.019
Information seeking attitude
In general, I think travel health-instructions are valuable. 0.859 4.288 0.882 0.756 0.962
In general, I think travel health-instructions are informative. 0.867 4.146 0.877 0.764 0.969
In general, I think travel health-instructions are helpful. 0.739 4.153 0.901 0.623 0.777
In general, I think travel health-instructions are instructive. 0.773 4.088 0.957 0.722 0.846
Travel intention
It is very likely that I will travel to the tourist destination. 0.861 4.095 0.925 0.758 0.964
I will travel to the tourist destination next time I need a trip. 0.923 4.179 0.969 0.821 1.025
I will recommend travelling to the tourist destination to my friends. 0.883 4.164 0.941 0.780 0.985
Subjective norms
It is expected of me that I seek information about COVID-19 0.753 3.803 1.108 0.648 0.858
Most people who are important to me think that I should seek information about COVID-19 0.853 4.120 0.940 0.750 0.955
Others expect me to seek information about COVID-19 0.820 3.701 1.151 0.717 0.924
My family expects me to seek information about COVID-19 0.888 3.697 1.142 0.785 0.990
People in my life whose opinions I value seek information about COVID-19 0.820 3.533 1.164 0.717 0.924
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Data availability

The data that has been used is confidential.

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