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https://doi.org/10.20867/thm.28.2.7

Examining factors influencing people's intention to staycation during covid-19: an extended model of goal-directed behaviour

Imas Chandra Pratiwi ; Institut Teknologi Bandung School of Business and Management Jl. Ganesa No. 10, Bandung, Indonesia
Santi Novani orcid id orcid.org/0000-0002-6574-6028 ; Institut Teknologi Bandung School of Business and Management Jl. Ganesa No. 10, Bandung, Indonesia


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Sažetak

Purpose – Staycation became a popular alternative to vacation during the pandemic. This
study seeks to examine the factors that influence Indonesian tourists’ staycation
intention during COVID-19 using an extended model of goal-directed behaviour.
Design – A model of goal-directed behaviour incorporates motivation variables,
perceptions of COVID, and personal non-pharmaceutical interventions developed to predict
people’s staycation intention during COVID-19.
Methodology – Purposive sampling was used to determine samples aged above 17, domiciled
in Indonesia, and willing to staycation during COVID-19. An online survey produced 534
responses and data were evaluated with PLS-SEM.
Approach – A quantitative exploratory study was used to identify how Indonesian tourists
intend to staycation during COVID-19. The measurement items were constructed from prior
studies to evaluate the model.
Findings – The staycation intention during COVID-19 was positively affected by desire,
followed by perceived behavioural control, with perception of COVID-19 showing the
opposite impact. Attitude plays essential role in influencing staycation intention.
However, staycation intention was not associated with personal nonpharmaceutical
interventions.
Originality of the research – This study provides novel insights into motivational and
non-pharmaceutical intervention variables in MGB, which are still underexplored in tourism
literature, to assist hospitality and tourism management in optimizing the staycation
trend and market during the pandemic.

Ključne riječi

Behavioural Intention; COVID-19; Motivation; Perception of COVID-19; Personal Non-Pharmaceutical Intervention; Staycation

Hrčak ID:

281112

URI

https://hrcak.srce.hr/281112

Datum izdavanja:

3.8.2022.

Posjeta: 444 *




INTRODUCTION

COVID-19 has been spreading globally since early 2020. Travel restrictions imposed by most nations have forced people to postpone their travel plans (Liu et al. 2021) and significantly impacted the tourism sectors (Neuburger and Egger 2020). In 2020, the potential global tourism sector GDP declined by 2.1 trillion USD (Škare et al. 2021). Before COVID-19, the tourism industry had prospered and contributed to the nation’s economic development through sustainable tourism (PWC 2021). However, due to the COVID-19 mitigations, Asia Pacific is predicted to be one of the hardest-hit tourisms’ regions, with a loss of about 4.5 billion USD (ADB 2021). United Nations also reported that Southeast Asia would lose 8.4 percent of its GDP in 2021 (ADB 2021). As one of the largest tourism industries in Southeast Asia, in 2020, Indonesia also experienced a decline in domestic tourists by 28% and caused the tourism revenue decreased by 5.87 billion USD (Akhlas 2020;Statistics Indonesia 2020).

Tourist behaviour has altered during COVID-19 (Bhrammanachote and Sawangdee 2021). Perceived risk of COVID-19 significantly lowered tourists’ intention to travel (Das and Tiwari 2021;Liu et al. 2021), and tourists prefer traveling within their region. During COVID-19, staycation became a new trend and its popularity continued to rise when the virus spread worldwide (Raj 2020). Based on Google Trends in Indonesia, the keyword “staycation” has been rising in the middle of 2020 (Eloksari 2020). According to Terry Massey in the Myrtle Beach Sun-News, “staycation” is an alternative vacation during the crisis (James et al. 2017). This trend started to emerge in 2008, amidst the United States’ economic crisis (Fox 2009). The term refers to people’s desire to visit a tourist destination near home rather than traveling to a distant area (Papatheodorou et al. 2010;Yesawich 2010). Hence, people have an interest to staycation during COVID-19.

The hotel industry has offered a staycation package to capitalise this trend (Noorashid and Chin 2021). With a growing number of domestic tourists who are willing to staycation, the tourism industry has begun to revive (Kherenhapukh et al. 2021). That is, the tourism and hospitality industry require to improve their services according to tourists’ need and motivation. However, empirical studies on tourists’ intention to staycation amid COVID-19 are still scarce. Although recent studies have revealed the tourists' intention for tourism amid COVID-19 (e.g., Das and Tiwari 2021;Qiao et al. 2021;Xu et al. 2021), empirical studies on tourist behaviour concerning the staycation market remain unclear (James et al. 2017).

The model of goal-directed behaviour (MGB) is adopted in the current study. It was developed byPerugini and Bagozzi (2001) and has been extensively applied in hospitality and tourism management (HTM) studies. MGB was applied to discover the personal decision-making process, while engaging in a given behaviour (Perugini and Bagozzi 2001).Das and Tiwari (2021) applied extended MGB to evaluate Indian intentions to travel during COVID-19, whereasQiao et al. (2021) used it to assess South Korean’s intention to visit China after COVID-19. Similarly,Xu et al. (2021) employed extended MGB to characterise cruise tourists’ decision-making amid COVID-19. Those studies proved that the perception of COVID-19 and personal non-pharmaceutical interventions (PNPIs) significantly affect tourists’ intention during the pandemic. Nonetheless, those studies failed to describe the personal motive that drives people to travel and staycation during COVID-19. In the HTM literature, motivation was considered to address “why do people travel?”(Jang et al. 2009). Roy and Sharma (2021) analysed tourist motivation for one-day traveling through content analysis on social media during COVID-19. However, they did not describe how motivation influenced the tourists’ decision-making process and conducted a survey-based study to provide in-depth insight regarding tourist motivation amid COVID-19 (Roy and Sharma 2021).

Given the gap above, study to explore tourist motivation and how it influences staycation decisions during COVID-19 require considerable attention. Accordingly, this study mainly aims to examine the influence of motivation, perception of COVID-19, and PNPIs towards tourists’ decision to staycation during COVID-19 using extended MGB. MGB is extended through the motivation to provide new insight into tourists’ drives and main goals for tourism during COVID-19 with a different context, which is staycation that prior studies have not revealed (Das and Tiwari 2021;Qiao et al. 2021;Xu et al. 2021). Moreover, to address the limitation ofRoy and Sharma (2021), a survey-based study in Indonesia is used to provide another insight into tourist motivation and decisions from different countries. As a result, the following research questions are addressed: What factors influenced tourists’ decision to staycation during COVID-19 based on the extended MGB proposed in this study? How does motivation affect attitude towards intention to staycation during COVID-19? How do perception of COVID-19 and willingness to use PNPIs affect tourists’ intention to staycation during COVID-19?

This study provides some contributions to support tourism management to attain a more comprehensive picture of the factors that significantly influence tourists’ intention to staycation. Accordingly, tourism can determine the attributes and features that should be promoted to appeal tourists during the pandemic. It leads tourism and hospitality marketers to recover more quickly from the crisis and mitigate future such crises. Moreover, this study also empirically examines the role of motivation in extended MGB, which is still underexplored in the HTM literature.

1. LITERATURE REVIEW

1.1. Staycation

There is a distinction between vacation and staycation. Vacation refers to traveling to distant tourism destinations within a particular time using a vehicle (i.e., car, train, or airplane) to take a break and relax (Fox 2009). However, when the economic recession of 2008 forced most Americans to postpone conventional vacations, they began to recreate the ambience of vacations closer to home (Papatheodorou et al. 2010;James et al. 2017). This phenomenon is known as a “staycation” (Fox 2009;James et al. 2017). Staycation is also referred to as “vacationing at home” (Molz 2009).Yesawich (2010) reported that one of four people in the United States took at least one vacation within a 50-mile radius of their home as an alternative vacation destination within a year during a crisis. As a result, staycation becomes the greatest alternative for vacation amid a crisis (Fox 2009).

Prior to COVID-19, a staycation was a type of vacation in which one spent time at home and took advantage of everything that the home and its environs had to offer (Fox 2009). They spend time with household members, friends, and relatives in their residences (Jacobsen et al. 2021). By staying at home, people are encouraged to make informed decisions that enhance their subjective health and well-being (de Bloom et al. 2017). In such a case, staycation emphasizes the financial benefits of avoiding travel (Molz 2009). On the other hand, during COVID-19, people are forced to spend their leisure time at home and neighbourhood as COVID-19 mitigation. Before COVID-19, people took a staycation to save money and efficiency. Nevertheless, during COVID-19, they took a staycation to avoid the crowd or getting infected by the virus. As people are required to quarantine during the pandemic by the government, staycation with household members at home has become tedious, and they then started to spend their leisure time in hotels or lodging accommodations close to their homes. As a result, staycation in the hotel and lodging industries alone or with household members become popular during COVID-19 (Noorashid and Chin 2021).

1.2. Model of Goal-Directed Behaviour

For over a decade, social science scholars have been working to predict human behaviour in different manners (Kim et al. 2021). To advance the effectiveness of TPB (Theory of Planned Behaviour),Perugini and Bagozzi (2001) presented MGB as a new approach. Considering the lack of personal decision variables, such as desires reflecting the motivating state of mind and prior behaviour, MGB extended TPB (Perugini and Bagozzi 2001). Unlike the prior behaviour socio-psychology model (i.e., TRA and TPB), which included the volitional (attitude and subjective norm) and non-volitional (perceived behavioural control), MGB framework advances those constructs with motivational (desire), emotional (anticipated emotion), and habitual (frequency of past behaviour) predictors (Song et al. 2017).

According toPerugini and Bagozzi (2001), MGB has tremendous advantages, compared to TPB, as it is better at predicting behaviour. The significance of desire as a primary predictor of behavioural intention and a mediator of the attitude, subjective norm, anticipated emotions, and perceived behavioural control may counterbalance the loss of simplicity of the MGB (Leone et al. 2004).

MGB has been widely applied in HTM studies, particularly to describe tourists’ travel intention during the crisis. For instance, during the Hong Kong protest,Kim et al. (2020) analysed the Korean tourists’ intention to visit Hong Kong. During a pandemic, several scholars also employed MGB and extended it with the perception of disease and utilized PNPIs to examine tourist intention during and post-pandemic (Lee et al. 2012;Das and Tiwari 2021;Qiao et al. 2021;Xu et al. 2021).Lee et al. (2012) pioneered the use of extended MGB to understand travel intention during the 2009 H1N1 outbreak. Recently,Das and Tiwari (2021),Qiao et al. (2021), andXu et al. (2021) adopted and modified the model ofLee et al. (2012) to describe the decision-making process of people who travel amidst COVID-19.

Prior studies emphasize how the variables of pandemic perception and PNPIs affect tourists’ decisions during a pandemic (Lee et al. 2012;Das and Tiwari 2021;Qiao et al. 2021;Xu et al. 2021). Apart from emphasizing these two variables and having different tourism contexts, the proposed extended MGB in the current study also analyses the motivation variable to describe the main objective that drives people to staycation amid COVID-19. Hence, the novelty of the proposed model is to examine the role of motivation in extended MGB, which has not been revealed in prior studies, and provide an empirical study of staycation market.

1.2.1. Attitude and Subjective Norm to Desire

Attitudes toward a behaviour reflect people’s cognitive response to accomplish some behaviours (Fishbein and Ajzen 1977;Ajzen 1991). Hence, it is regarded as a critical aspect of human behaviour (Song et al. 2017). Another substantial predictor of MGB is the subjective norm, which entails that individuals will behave in response to their perceived social pressure (Fishbein and Ajzen 1977;Ajzen 1991). It is considered that attitude and subjective norms affect behaviour intentions indirectly through desire (Perugini and Bagozzi 2001).

Attitude and subjective norm have been demonstrated to influence desire in previous studies (Kim et al. 2012;Meng and Choi 2016;Lee et al. 2017). Recently,Das and Tiwari (2021) andQiao et al. (2021) discovered a positive correlation between attitude, subjective norm, and travel desire during COVID-19. It implies that optimistic people consider social pressure and other’s opinion when deciding to travel during pandemic. The more positive attitude and opinion from others, the more likely personal desire to travel in a particular situation. Accordingly, we developed the hypothesis:

H1: Positive attitude increases people’s desire to staycation during COVID-19.

H2: Subjective norms increase people’s desire to staycation during COVID-19.

1.2.2. Anticipated Emotions to Desire

Emotional factors are considered a predictor of desire in MGB (Perugini and Bagozzi 2001). It is comprised of positive and negative anticipated emotions. People are likely to experience various emotions linked with an action strongly associated with desire, intention, and actual behaviour (Song et al. 2017). Several studies have demonstrated that positive anticipated emotions significantly influence desire (Leone et al. 2004;Meng and Han 2016;Levitt et al. 2019;Wang et al. 2020).

On the other hand, negative anticipated emotions primarily reflect a negative emotional state that may happen to people who fail to achieve the desired goal (Lee et al. 2018). Such people may experience highly expected unpleasant feelings strengthen their desire for goal-directed behaviour (Perugini and Bagozzi 2001). Double negative emotions will generate a significant positive outcome. In this manner, the current study’s measurement items will use double negative emotions to have a positive impact on desire, such as “If I fail in achieving my goal to staycation during COVID-19, I will be disappointed” (see Appendix). Prior studies (e.g., Lee et al. 2017;Song et al. 2017;Kim et al. 2020;Xu et al. 2021) found that the negative anticipated emotions positively affected the desire when the measurement items used double negative statements. Therefore, the current study proposed the following hypotheses:

H3: Positive anticipated emotions increase people’s desire to staycation during COVID-19.

H4: Negative anticipated emotions increase people’s desire to staycation during COVID-19.

1.2.3. Perceived Behavioural Control to Desire and Intention

Perceived behavioural control describes how people believe they can perform their behaviour (Conner and Abraham 2001). Several resources or possibilities to engage in a certain behaviour can considerably impact people’s decision to perform that behaviour (Song et al. 2017). When people have money, time, chance, or any other opportunity to engage in a certain behaviour, the likelihood of desire and intention to engage in that behaviour increases significantly.Das and Tiwari (2021) andQiao et al. (2021) showed that perceived behavioural control significantly predicted desire and intention. It can be hypothesized that if people have sufficient resources to staycation during COVID-19, they are more likely to be desired and intended to perform it. Hence, the role of perceived behavioural control is hypothesized as follow:

H5: Perceived behavioural control increases people’s desire to staycation during COVID-19.

H6: Perceived behavioural control increases people’s intention to staycation during COVID-19.

1.2.4. Frequency of Past Behaviour

A habitual indicator, which relates to the frequency of past behaviour, contributes to an individual’s desire and intention to engage in a certain behaviour (Perugini and Bagozzi 2001;Leone et al. 2004). If behaviour is consistently performed in a similar situation, its frequency implies habitual strength and appears to have an effect on future behaviour (Perugini and Bagozzi 2001). However, it is hard to measure how to predict the past behaviour of Indonesian tourists during a pandemic, since the past pandemic occurred more than a century ago (Makdori 2020). Nonetheless,Lee et al. (2012) used traveling frequency during the normal situation to determine past behaviour in predicting the travel desire and intention during 2009 H1N1.Qiao et al. (2021) also found that people who travelled before pandemic were more likely to be desired and intended to vacation during COVID-19. Thus, we developed the following hypotheses:

H7: Frequency of past behaviour increase people’s desire to staycation during COVID-19.

H8: Frequency of past behaviour increase people’s intention to staycation during COVID-19.

1.2.5. Desire to Intention

Desire serves as the primary stimulus for intention and modifies the substance that motivates people to behave, such as attitudes, anticipated emotions, subjective norms, and perceived behavioural control (Perugini and Bagozzi 2001). Thus, desire as the central predictor in the MGB is expected to be the most potent predictor of behavioural intention. Desire transforms someone’s perceptions and reasons into a motivation to behave (Perugini and Bagozzi 2001). Despite having a positive attitude, supporting norms from others, and opportunities to execute a behaviour, it cannot be done if people lack the desire to motivate the behaviour (Lee et al. 2017). Prior studies have proved that desire was the strongest predictor of tourist intention (Levitt et al. 2019;Bui and Kiatkawsin 2020;Das and Tiwari 2021). Therefore, the following is hypothesized:

H9: Desire increases people’s intention to staycation during COVID-19.

1.3. Tourist Motivation

Motivation originates etymologically from “movere”, which means to move in Latin (Dann 1981). Motivation is described in HTM literature as an individual’s cognitive ability to decide their actions, such as travel or recreational activities. Like most goods and human beings, tourists also move and travel across the region (Dann 1981). Additionally,Fodness (1994) suggested that, while motivation is merely one of the numerous variables that might influence tourist behaviour, it is a key variable that serves as a primary driver of majority of behaviour.

Motivation seems to be a prevalent subject in tourism studies (Juvan and Omerzel 2017). Individuals’ motives for vacation have been investigated to provide valuable insight into the personal decision-making process, segmentation, and preference (Bogari et al. 2003;Jang et al. 2009;Kim and Ritchie 2012). Numerous scholars have investigated tourist sociological, psychological, and cultural motivation (Hsu et al. 2010). For instance,Jang et al. (2009) examined the psychological aspect of Taiwanese seniors’ tourists using five factors of travel motivation, namely relaxation, ego-enhancement, socialization, self-esteem, and novelty seeking. Meanwhile, the motivation dimension of relaxation, shopping, novelty, and knowledge was integrated with the planned behavioural model to explain Chinese tourists’ behaviour to visit Hong Kong (Lam and Hsu 2004).Allan (2014) evaluated the Jordanian tourist’s motivation to travel abroad through six push factors: escape, enjoyment, relaxation, knowledge, and novelty.

Despite being a prominent component in tourism literature, travel motivation’s association with intention requires scholars’ attention (Jang et al. 2009). For example, examining tourists’ motivation to take a staycation during pandemic, especially COVID-19, still has limited attention from scholars (Roy and Sharma 2021). Subsequently, valuable information on factors that drive people to vacation during a pandemic is hard to find by tourism management. At the same time, attitude in developing tourist motivation and planned behaviour is one of the most crucial issues in tourism (Vargas-Sánchez et al. 2016). Nevertheless, the association between motivation and other behavioural variables, such as attitude, is surprisingly understudied (Vargas-Sánchez et al. 2016). Therefore, extended MGB is used to examine tourist intention to staycation during COVID-19, and the findings of this study seek to bridge the gap in the literature. Although desire is included as a motivational aspect in MGB, the specific reason of people to execute a particular behaviour cannot be explained in that model. This constraint is addressed by including the motivation variables, i.e., relaxation and escape, to MGB in describing a tourist’s intention to staycation during COVID-19.

By including motivation variable into the planned behaviour model,Hsu and Huang (2012) reported that motivation effected tourists’ attitude toward intention to visit Hong Kong. Similarly,Levitt et al. (2019) andKim et al. (2021) examined the correlation between motivation and attitude in MGB. Accordingly, motivation was associated with a positive attitude towards consuming local cuisine when traveling (Levitt et al. 2019) and visiting undiscovered tourist attractions (Kim et al. 2021). It means motivation contributes to increasing human cognitive behaviour. Therefore, the following can be hypothesized:

H10: Motivation increases positive attitude towards intention to staycation during COVID-19.

1.4. Perception of COVID-19 and PNPIs to Desire

Perception is a person’s awareness, understanding, and experience in response to their cognition of objects and behaviours (Liu et al. 2021). In tourism, risk perception varies depending on tourist characteristics (Reisinger and Mavondo 2005). One aspect that influences changes in tourist behaviour is the perceived pandemic risk (Parady et al. 2020). The risk perception of tourists is influenced by crisis, natural disasters, political unrest, terrorism, war, and pandemic (Çakar 2021;Falahuddin et al. 2020;Neuburger and Egger 2020).

Considering the lack of vaccines and medicines to control COVID-19 during the early pandemic, most nations employed non-pharmaceutical interventions (NPIs) to mitigate COVID-19 (Sekine et al. 2020;Sun et al. 2020;Cao et al. 2021). The World Health Organization (WHO) defines NPIs as any procedures or actions that can be adopted to restrict the spread of influenza in a society without resorting to vaccinations or medications (WHO 2019). Additionally, PNPIs reflect an individual’s willingness to learn more about the diseases, improve personal hygiene habits (e.g., washing hands more frequently), avoid suspicious people and places through social and physical distancing, and control the personal health both before and after traveling (Liu et al. 2021). Adopting PNPIs resulted in a significant decrease in the number of infected people and a delay in the peak number of infected people (Cao et al. 2021). As a result, the government may have more time to develop strategies to deal with the peak spread of COVID-19.

Numerous scholars studied the relationship between the perception of pandemic and PNPIs during COVID-19 (Das and Tiwari 2021;Liu et al. 2021;Neuburger and Egger 2020;Parady et al. 2020;Bae and Chang 2021;Xu et al. 2021). They highlighted that perception of COVID-19 weakened the travel desire and intention during the pandemic. However, it was observed that PNPIs could reduce the negative impact of COVID-19’s perception on travel intention during a pandemic (Das and Tiwari 2021;Liu et al. 2021;Xu et al. 2021). For instance,Lee et al. (2012) presented that when mediated by PNPIs, the perception of 2009 H1N1 significantly increased the intention among South Korean tourists to travel abroad. Additionally, the perception of COVID-19 significantly increased the travel intention of people during the pandemic if mediated by PNPIs (Das and Tiwari 2021;Liu et al. 2021;Xu et al. 2021). Perception of diseases or pandemics may discourage tourists from vacationing during a pandemic. Alternatively, if people are willing to adopt PNPIs, their desire and intention for travelling can rise. Considering past studies, we posit the hypothesis for the perception of COVID-19, PNPIs, and desire as follows:

H11: Perception of COVID-19 decreases people’s desire to staycation during COVID-19.

H12: Perception of COVID-19 decreases people’s intention to staycation during COVID-19.

H13: Perception of COVID-19 increases people’s intention to staycation during COVID-19 if mediated by the adoption of PNPIs.

2. METHODOLOGY

2.1. Research design and data collection

A quantitative approach with a cross-sectional method was employed to test the associations among variables in the proposed research model (seeFigure 1). The observed variables were assessed using a self-administered questionnaire, which began with describing the research’s purpose. The authors guaranteed the confidentiality of respondents’ data, and respondents voluntarily confirmed their commitment to complete the questionnaire. The respondent’s demographic profile comprises gender, age, education, occupation, expenditure for one staycation, and staycation companion.

Figure 1: The Proposed Model

./THM-28-361-f1.png

A total of 38 questionnaire items were constructed based on previous studies (See Appendix). The MGB’s construct comprises 24 items adopted from prior studies (Lee et al. 2012;Das and Tiwari 2021). Meanwhile, motivation (Allan 2014;Wijaya et al. 2019) was assessed with five items, perception of COVID-19 (Liu et al. 2021) with four items, and the five measurement items for PNPIs (Kim et al. 2012;Lee et al. 2012;Liu et al. 2021). A five-point Likert scale evaluated all those items. A pilot survey was done to avoid ambiguity of measurement items and ensure that respondents have the same understanding of each measurement items with the researchers. According toWhitehead et al. (2016), the minimum pilot study’s sample size is 24 with 90% average power prediction. Hence, 25 samples were used in this pilot study.

Indonesian who are willing to staycation amid COVID-19 are the target population in this study. Based on the inverse square root approach for the Partial Lease Square-Structural Equation Modelling (PLS-SEM), the minimum sample for a significance level of 5% is 155 (Kock and Hadaya 2018). The judgment sampling technique (as a purposive sampling approach) was selected to obtain the sample. This technique enables us as researchers to use our judgment based on several sample criteria to determine the appropriate sample (Sekaran and Bougie 2016). Several sample criteria are above 17 years and domiciled in Indonesia. A total of 558 samples were obtained from an online survey at the end of April 2021 through social media. Of which, 24 responses were excluded due to incomplete, insincere, and unreliable responses. Finally, 534 responses were used for the analysis and have met the minimum sample size requirement.

The proposed model was evaluated with PLS-SEM through SmartPLS 3.0 (Ringle et al. 2015). This method is consistent with the current study’s objective of examining the correlation between the various constructs to better understand people’s intention to staycation during COVID-19 (Hair et al. 2014). Moreover, PLS-SEM is well-suited for a complex model with several constructs, including the proposed model in this study (Hair et al. 2014).

3. RESULTS

3.1. Demographic Profile

Among the 534 samples, almost 70% were female (seeTable 1). Additionally, the samples’ age groups were relatively young, as only 2.5 percent were older than 40 years. A total of 374 samples (70%) held bachelor’s degrees, while 64% were employees. Furthermore, half of the total samples indicated that they were likely to choose an affordable staycation destination with a budget of less than IDR 1 million (around 70 USD) for a single staycation.

Table 1: Demographic Profile of Sample
ItemsGroupsFrequenciesPercentages (%)

Gender

Male

Female

166

368

31.1

68.9

Age

18-20

21-30

31-40

>40

11

450

60

13

2.1

84.2

11.2

2.5

Education Level

High school

Diploma

Bachelor's degree

Master/doctoral degree

Others

33

63

374

60

4

6.2

11.8

70.0

11.2

0.8

Occupation

Student

Housewife

Employee

Others

117

11

342

64

21.9

2.1

64.0

12.0

Staycation Expenditure (IDR)

<1,000,000

1,000,001-3,000,000

3,000,001-5,000,000

5,000,001-7,000,000

>7,000,001

299

184

40

10

1

56.0

34.5

7.5

1.9

0.1

3.2. Outer Model Test

The outer model evaluation assessed the construct’s reliability and validity. As reported in Table 2, the outer loading (λ) for all observed variables met the threshold between 0.563 and 0.938 (Hair et al. 2014). Thus, these observed variables were reliable as measurement items for each latent variable. The Cronbach alpha (α) and composite reliability (CR) for all latent variables were accepted and their values were above 0.6, which indicates that they had strong internal consistency reliability (Hair et al. 2014). Whereas the average variance extracted (AVE) values were all higher than 0.5, which implies that the items for each latent variable can explain the variance of the constructed variable (Hair et al. 2014). Since a single item was evaluated the frequency of past behaviour, it was not examined in the outer model, followingLee et al. (2012) andDas and Tiwari (2021).

Table 2: Outer Model Test
ConstructsλαCRAVE
Motivation0.8470.8910.621
MOT10.823
MOT20.811
MOT30.823
MOT40.779
MOT50.695
Attitude0.8910.9240.754
ATT10.861
ATT20.862
ATT30.868
ATT40.881
Subjective Norm0.8930.9330.823
SN10.895
SN20.915
SN30.912
Perceived Behavioural Control0.6220.7940.565
PBC10.837
PBC20.753
PBC30.653
Positive Anticipated Emotions0.9200.9490.862
PAE10.910
PAE20.938
PAE30.937
Negative Anticipated Emotions0.9110.9440.849
NAE10.912
NAE20.920
NAE30.931
PNPIs 0.7810.8510.537
PNPI10.574
PNPI20.701
PNPI30.814
PNPI40.821
PNPI50.725
Perception of COVID-190.7650.8530.598
POC10.563
POC20.875
POC30.768
POC40.848
Desire0.8940.9340.825
DES10.881
DES20.926
DES30.918
Behavioural Intention0.9330.9520.833
  • BI1

0.914
  • BI2

0.933
  • BI3

0.925
  • BI4

0.878

The next stage is discriminant validity, which is determined by comparing the square root of each construct’s AVE using Fornell-Larcker. As reported inTable 3, each construct had a greater value than the others. Hence, all constructs have a high degree of discriminant validity.

Table 3: Discriminant Validity (Fornell-Larcker Criterion)
MOTATTSNPBCPAENAEPNPIPOCDESBI
MOT0.788
ATT0.5060.868
SN0.3620.6630.907
PBC0.3510.5670.5290.751
PAE0.5000.6540.5420.5750.928
NAE0.1660.2410.2480.1480.2670.921
PNPI0.0650.0110.0110.0420.022-0.1360.732
POC-0.116-0.246-0.291-0.134-0.124-0.0290.3530.756
DES0.4580.5740.5030.4360.5790.338-0.053-0.2230.909
BI0.4810.6150.5220.4890.5760.394-0.049-0.2450.8570.913

3.3. Inner Model Test

The inner model test was done to assess the proposed hypotheses. As provided inTable 4, 10 out of 13 hypotheses were accepted. Perceived behavioural control and frequency of past behaviour did not correlate with desire, as their p-values were above 0.05. Furthermore, it was reported that the adoption of PNPIs did not moderate the perception of COVID-19 with the intention to staycation during the pandemic. Accordingly, H5, H8, and H13 failed to be proved in this study.

Table 4: Hypotheses Testing
HypothesesβP-ValueDecisions
H1 (ATT→DES)0.2080.000Accepted
H2 (SN→DES)0.0990.000Accepted
H3 (PAE→DES)0.2890.000Accepted
H4 (NAE→DES)0.1740.000Accepted
H5 (PBC→DES)0.0450.156Rejected
H6 (PBC→BI)0.1380.000Accepted
H7 (FPB→DES)0.0450.220Rejected
H8 (FPB→BI)0.0170.010Accepted
H9 (DES→BI)0.7810.000Accepted
H10 (MOT→ATT)0.5060.000Accepted
H11 (POC→DES)-0.940.005Accepted
H12 (POC→BI)-0.0540.015Accepted
H13 (POC→PNPI→BI)-0.0710.153Rejected

The variance (R2) of attitude, PNPIs, desire, and intention to staycation were 0.256, 0.125, 0.455, and 0.754, respectively. According toHair et al. (2014), a variance of 0.75 can be described as a substantial model. In this manner, the antecedent variable of behavioural intention has substantial power to predict the staycation intention during the pandemic and the desire to travel during COVID-19 has moderate power. Contrastingly, the constructs of attitude and PNPIs were weak, as the R2 of these variables was around 0.25 or below.

4. DISCUSSION AND CONCLUSION

This study aimed to investigate the influence of motivation, perception of COVID-19, and PNPIs in the extended MGB to describe the decision-making process of Indonesian tourists to staycation during COVID-19. According to the statistical analysis, 10 out of 13 hypotheses were successfully proved. The findings confirmed that the tourists’ decision to staycation amid COVID-19 was positively influenced by desire, perceived behavioural control, and past behaviour, where the perception of COVID-19 has a significant negative effect. Desire to staycation was determined by attitude, subjective norm, anticipated emotions, and perception of COVID-19. Motivation has a substantial role in enhancing people’s attitude towards desire and intention to staycation amid COVID-19. Besides, tourists’ desire and intention to staycation during COVID-19 were lowered by the perception of COVID-9. However, the role of adoption of PNPIs failed to mediate the negative influence of perception of COVID-19 to staycation intention in this study.

The results show the role of motivation in influencing someone’s attitude to staycations during COVID-19. This finding corroborates previous studies, which demonstrated a substantial correlation between motivation and attitude towards intention to consume local food (Levitt et al. 2019) and visit unfamiliar tourist destinations (Kim et al. 2021). It can be assumed that motivation factors can strengthen the positive cognition of tourists. Motivation plays a decisive role in enhancing people’s perception to staycation. Based on the constructs of motivation variables in this study, escaping from the daily routine and enjoying a happy time with family and friends are the most powerful indicators that influence people to staycation during the pandemic. Hence, tourism and hospitality managements are required to design and provide some appealing and affordable group activities for staycation package without ignoring the health protocol during pandemic to attract more tourists.

Another reported finding showed that staycation desire during COVID-19 was positively correlated with attitude, subjective norm, anticipated positive and negative emotions, and past behaviour. Simultaneously, the desire was the strongest predictor of staycation intention during COVID-19. These findings complement the prior studies that discovered desire as a decisive variable in influencing the intention to travel abroad (Kim et al. 2012), bicycle travellers (Meng and Han 2016), visit South Korea (Song et al. 2017), and adventure tourism (Bui and Kiatkawsin 2020). On the contrary, perceived behavioural control insignificantly influenced the desire but strongly relates to staycation intention during COVID-19. These results corroborate the finding ofKim et al. (2021) that only perceived behavioural control had an insignificant correlation with the desire to visit unfamiliar destinations in North Korea. Overall, these results indicate that staycation desire during COVID-19 is mainly determined by other opinions or perceptions, travel experience before the pandemic, emotional factors, and personal attitude, which was influenced by their motivation. That is, in spite of having positive attitudes, travel experiences, and emotions towards staycation during COVID-19, people also use opinions from their family or close friends before intending to staycation. As a result, the more remarkable the people’s desire to travel, the more likely they are willing to staycation during the pandemic. Additionally, if people have sufficient resources such as money and time, they have a great potential to staycation during COVID-19.

On the other hand, like past studies in China (Liu et al. 2021) and Korea (Xu et al. 2021), perception of COVID-19 lowered people’s desire and intention to staycation during COVID-19. The negative perception of COVID-19 diminishes people’s desire and intention to staycation during the pandemic. To improve people’s desire and intention to staycation during COVID-19, tourist destinations and hospitality industries must adhere to stringent health protocols and ensure the cleanliness and sanitation of their facilities. Consequently, if tourist destination facilities and services provide a low risk of COVID-19 transmission, the negative perception of COVID-19 can be mitigated. Thus, this study confirms that pandemic perception can change people’s travel behaviour (Parady et al. 2020).

One interesting finding was that adoption of PNPIs had no significant impact on intention to staycation during COVID-19. Although the perception of COVID-19 boosts people’s tendency to adopt PNPIs, it has no impact on their intention to staycation during COVID-19 in Indonesia. This result failed to demonstrate that the adoption of PNPIs has a relationship with travel intention during a pandemic as presented by past studies (i.e.,Lee et al. 2012;Das and Tiwari 2021;Liu et al. 2021). Prior studies found that the adoption of PNPIs can alter the negative perception of disease to travel amid a pandemic. However, in Indonesia, the adoption of PNPIs did not affect people’s intention to staycation during COVID-19. The different results are likely related to the fact that adoption of PNPIs and risk perception varies depending on demographic factors (Das and Tiwari 2021). Moreover, this finding may be explained by the COVID-19 vaccine availability during the survey. At that time, the vaccine distribution was still limited, with only medical workers, public servants, employees, and the elderly who got the vaccine. Based on the respondent’s profile in the present study, the employee has dominated the survey by 64%. Accordingly, those facts can eliminate the significant role of PNPIs in mediating the perception of COVID-19 with staycation intention during a pandemic. Therefore, this finding relates to the correlation of perception of pandemic and PNPIs with behavioural intention, which is a novelty contribution to the literature presented by this study.

4.1. Theoretical and Practical Contributions

The finding contributes to the HTM literature. The proposed model for predicting people’s intention to staycation during COVID-19 has substantial power, explaining 75.4% of the variance. This study supported the suggestion ofPerugini and Bagozzi (2001) that adding a new construct in MGB can increase the overall variance in behavioural intention. It confirms that extended MGB is a suitable and relevant behavioural model to examine the tourists’ intention during a pandemic. Additionally, the current extended MGB proved that motivation has an essential role in the staycation decision-making process during the COVID-19 pandemic, which has not been well documented in the HTM literature. In Indonesia's context of a staycation, PNPIs had no significant impact on people's perception of COVID-19. It indicates that Indonesian did not perceive PNPIs as reasonable preventive measures when staycation. Hence, this study provides novel insight into the role of PNPIs and how the context and social demographic determine the role of PNPIs.

Several practical contributions for the government and tourism industry were also provided. First, considering the insignificant PNPIs in staycation decision-making process, the government should educate the community on the importance of PNPIs as effective personal mitigation of COVID-19. By doing so, people will receive PNPIs as plausible preventive measures during a staycation. Second, tourists exhibit a high tendency to travel during the pandemic due to an emotional component. When people staycation during COVID-19, they often have great expectations of being pleased and fulfilled. Therefore, tourism should provide services that meet tourists' expectations, needs, and motivation for staycation during the pandemic—for instance, designing a pleasant atmosphere that can make people forget their daily routine during the pandemic. Moreover, tourism can provide group activities for quality time with family members or friends. Third, during COVID-19, the tourism industry needs to demonstrate the value and benefits of staycations as a safe and affordable alternative to traveling. Strict COVID-19 mitigation and health protocols should be prioritized to ensure the comfort and safety of tourists. For instance, the personnel always wear a mask and gloves when interacting with tourists, ensure that all destination attributes are always sterile and cleaned regularly, and provide information that all personnel has passed COVID-19 screening. Such situations create a positive value and benefits of staycation amid the pandemic. As a result, the impact of perceptions on COVID-19 for staycation can be reduced and people will be attracted to staycation. Besides, if tourists feel satisfied, they will recommend others to staycation during a pandemic. The possibility of people to staycation during a pandemic will increase since opinion from others is also essential in influencing staycation intention.

4.2. Limitation and Future Study Recommendations

Although the present study has a considerable contribution for theoretical and practical implications, it is unfortunate that it did not include the actual behaviour variable. This gap could be filled by a longitudinal study that includes actual staycation behaviour, and it would provide a better idea of how tourists will act during a pandemic. The statistical analysis in this study shows the different findings of adopting PNPIs. Hence, further study using a qualitative approach to confirm the finding is required to better understand this phenomenon.

Acknowledgements

This study was supported by the Indonesian Endowment Fund for Education (LPDP) Scholarship with Grant Number 20200711022796.

References

 

ADB (2021), "Southeast Asia Faces GDP Loss of 8.4 % in 2021 as COVID-19 Roils Tourism", viewed 01 August 2021 https://seads.adb.org/index.php/solutions/southeast-asia-faces-gdp-loss-84-2021-covid-19-roils-tourism

 

Ajzen I. (1991), "The theory of planned behavior", Organizational Behavior and Human Decision Processes, Vol. 50, No. 2, pp. 197 - 211. https://doi.org/10.1016/0749-5978(91)90020-T

 

Akhlas A.W. (2020), "Pandemic erases $5.9b of Indonesia’s tourism revenue as businesses seek help", viewed 27 July 2021 https://www.thejakartapost.com/news/2020/07/14/pandemic-erases-5-9b-of-indonesias-tourism-revenue-as-businesses-seek-help.html

 

Allan M. (2014), "Why do Jordanian tourists travel abroad? Push and pull theory perspective", Dirasat: Human and Social Sciences, Vol. 41, No. 1, pp. 662–67 https://doi.org/10.12816/0026940

 

Bae S.Y., Chang P.-J. (2021), "The effect of coronavirus disease-19 (COVID-19) risk perception on behavioural intention towards ‘untact’ tourism in South Korea during the first wave of the pandemic", Current Issues in Tourism, Vol. 24, No. 7, pp. 1017–103 https://doi.org/10.1080/13683500.2020.1798895

 

Bhrammanachote W., Sawangdee Y. (2021), "Sustaining or surviving? an exploratory case study on covid-19’s impact towards hotel businesses", Tourism and Hospitality Management, Vol. 27, No. 2, pp. 273–29 https://doi.org/10.20867/thm.27.2.3

 

Bogari N.B.; Crowther G.; Marr N. (2003), "Motivation for domestic tourism: A case study of the Kingdom of Saudi Arabia", Tourism Analysis, Vol. 8, No. 2-4, pp. 137 - 141. https://doi.org/10.3727/108354203774076625

 

Bui N.A., Kiatkawsin K. (2020), "Examining Vietnamese hard-adventure tourists’ visit intention using an extended model of goal-directed behavior", Sustainability, Vol. 12, No. 5 https://doi.org/10.3390/su12051747

 

Çakar K. (2021), "Tourophobia: fear of travel resulting from man-made or natural disasters", Tourism Review, Vol. 76, No. 1, pp. 103–12 https://doi.org/10.1108/TR-06-2019-0231

 

Cao W., Dai H., Zhu J., Tian Y., Peng F. (2021), "Analysis and Evaluation of Non-Pharmaceutical Interventions on Prevention and Control of COVID-19: A Case Study of Wuhan City", International Journal of Geo-Information, Vol. 10, No. 7 https://doi.org/10.3390/ijgi10070480

 

Conner M., Abraham C. (2001), "Conscientiousness and the theory of planned behavior: Toward a more complete model of the antecedents of intentions and behavior", Personality and Social Psychology Bulletin, Vol. 27, No. 11, pp. 1547–156 https://doi.org/10.1177/01461672012711014

 

Dann G.M.S. (1981), "Tourist Motivation: An Appraisal", Annals of Tourism Research, Vol. 8, No. 2, pp. 187–21 https://doi.org/10.1016/0160-7383(81)90082-7

 

Das S.S., Tiwari A.K. (2021), "Understanding international and domestic travel intention of Indian travellers during COVID-19 using a Bayesian approach", Tourism Recreation Research, Vol. 46, No. 2, pp. 228–24 https://doi.org/10.1080/02508281.2020.1830341

 

deBloom J., Nawijn J., Geurts S., Kinnunen U., Korpela K. (2017), "Holiday travel, staycations, and subjective well-being", Journal of Sustainable Tourism, Vol. 25, No. 4, pp. 573–58 https://doi.org/10.1080/09669582.2016.1229323

 

Eloksari E.A. (2020), "Demand for staycations to surge as tourist destinations reopen", viewed 18 March 2022 https://www.thejakartapost.com/news/2020/08/07/demand-for-staycations-to-surge-as-tourist-destinations-reopen.html

 

Falahuddin A.F., Tergu C.T., Brollo R., Nanda R.O. (2020), "Post COVID-19 pandemic international travel: Does risk perception and stress-level affect future travel intention?", Jurnal Ilmu Sosial Dan Ilmu Politik, Vol. 24, No. 1, pp. 1–1 https://doi.org/10.22146/JSP.56252

 

Fishbein M.A.; Ajzen I. (1977), "Belief, attitude, intention and behaviour: An introduction to theory and research", Philosophy and Rhetoric, Vol. 10, No. 2, pp. 130 - 132.

 

Fodness D. (1994), "Measuring tourist motivation", Annals of Tourism Research, Vol. 21, No. 3, pp. 555–58 https://doi.org/10.1016/0160-7383(94)90120-1

 

Fox S. (2009), "Vacation or Staycation?", The Neumann Business Review. pp. 1 - 7.

 

Hair J.F.; Hult G.T.M.; Ringle C.M.; Sarstedt M. (2014), A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), Sage Publication, California, USA.

 

Hsu C.H.C., Cai L.A., Li M. (2010), "Expectation, motivation, and attitude: A tourist behavioral model", Journal of Travel Research, Vol. 49, No. 3, pp. 282–29 https://doi.org/10.1177/0047287509349266

 

Hsu C.H.C., Huang S. (2012), "An Extension of the Theory of Planned Behavior Model for Tourists", Journal of Hospitality and Tourism Research, Vol. 36, No. 3, pp. 390–41 https://doi.org/10.1177/1096348010390817

 

Jacobsen J.K.S.; Farstad E.; Higham J.; Hopkins D.; Landa-Mata I. (2021), "Travel discontinuities, enforced holidaying-at-home and alternative leisure travel futures after COVID-19", Tourism Geographies, pp. 1 - 19. https://doi.org/10.1080/14616688.2021.1943703

 

James A., Ravichandran S., Chuang N.-K., Bolden E. (2017), "Using Lifestyle Analysis to Develop Lodging Packages for Staycation Travelers: An Exploratory Study", Journal of Quality Assurance in Hospitality and Tourism, Vol. 18, No. 4, pp. 387–41 https://doi.org/10.1080/1528008X.2016.1250240

 

Jang S., Bai B., Hu C., Wu C.-M.E. (2009), "Affect, travel motivation, and travel intention: A senior market", Journal of Hospitality and Tourism Research, Vol. 33, No. 1, pp. 51–7 https://doi.org/10.1177/1096348008329666

 

Juvan E.; Omerzel D.G.; Maravic M.U. (2017), "Tourist Behaviour: An Overview of Models to Date", Management International Conference. pp. 24 - 27.

 

Kherenhapukh W.; Damiasih and Sarwono A.W. (2021), "A Hotel Recommendation System Based on Reviews of Staycation Preferences in Yogyakarta: A Collaborative Filtering Approach", Phuket International Tourism Conference pp. 145 - 158.

 

Kim J.H, Ritchie B.W. (2012), "Motivation-Based Typology: An Empirical Study of Golf Tourists", Journal of Hospitality and Tourism Research, Vol. 36, No. 2, pp. 251–28 https://doi.org/10.1177/1096348010388661

 

Kim J.S., Lee T.J., Kim N.-J. (2021), "What motivates people to visit an unknown tourist destination? Applying an extended model of goal-directed behavior", International Journal of Tourism Research, Vol. 23, No. 1, pp. 13–2 https://doi.org/10.1002/jtr.2388

 

Kim M.J., Lee C.-K., Petrick J.F., Kim Y.S. (2020), "The influence of perceived risk and intervention on international tourists’ behavior during the Hong Kong protest: Application of an extended model of goal-directed behavior", Journal of Hospitality and Tourism Management, Vol. 45, No. 2, pp. 622–63 https://doi.org/10.1016/j.jhtm.2020.11.003

 

Kim M.-J., Lee M.J., Lee C.-K., Song H.-J. (2012), "Does Gender Affect Korean Tourists’ Overseas Travel? Applying the Model of Goal-Directed Behavior", Asia Pacific Journal of Tourism Research, Vol. 17, No. 5, pp. 509–53 https://doi.org/10.1080/10941665.2011.627355

 

Kock N., Hadaya P. (2018), "Minimum sample size estimation in PLS-SEM: The inverse square root and gamma-exponential methods", Information Systems Journal, Vol. 28, No. 1, pp. 227–26 https://doi.org/10.1111/isj.12131

 

Lam T., Hsu C.H.C. (2004), "Theory of Planned Behavior: Potential Travelers from China", Journal of Hospitality and Tourism Research, Vol. 28, No. 4, pp. 463–48 https://doi.org/10.1177/1096348004267515

 

Lee C.-K., Song H.-J., Bendle L.J., Kim M.-J., Han H. (2012), "The impact of non-pharmaceutical interventions for 2009 H1N1 influenza on travel intentions: A model of goal-directed behavior", Tourism Management, Vol. 33, No. 1, pp. 89–9 https://doi.org/10.1016/j.tourman.2011.02.006

 

Lee S., Bruwer J., Song H.J. (2017), "Experiential and involvement effects on the Korean wine tourist’s decision-making process", Current Issues in Tourism, Vol. 20, No. 12, pp. 1215–123 https://doi.org/10.1080/13683500.2015.1050362

 

Lee S.J., Song H.J., Lee C.K., Petrick J.F. (2018), "An Integrated Model of Pop Culture Fans’ Travel Decision-Making Processes", Journal of Travel Research, Vol. 57, No. 5, pp. 687–70 https://doi.org/10.1177/0047287517708619

 

Leone L., Perugini M., Ercolani A.P. (2004), "Studying, practicing, and mastering: A test of the model of goal-directed behavior (MGB) in the software learning domain", Journal of Applied Social Psychology, Vol. 34, No. 9, pp. 1945–197 https://doi.org/10.1111/j.1559-1816.2004.tb02594.x

 

Levitt J.A., Meng F., Zhang P., DiPietro R.B. (2019), "Examining factors influencing food tourist intentions to consume local cuisine", Tourism and Hospitality Research, Vol. 19, No. 3, pp. 337–35 https://doi.org/10.1177/1467358417742687

 

Liu Y., Shi H., Li Y., Amin A. (2021), "Factors influencing Chinese residents’ post-pandemic outbound travel intentions: an extended theory of planned behavior model based on the perception of COVID-19", Tourism Review, Vol. 76, No. 4, pp. 871–89 https://doi.org/10.1108/TR-09-2020-0458

 

Makdori Y. (2020), "Sejarah Pandemi Virus di Indonesia Sebelum Wabah COVID-19", viewed 22 August 2021 https://www.liputan6.com/news/read/4326818/sejarah-pandemi-virus-di-indonesia-sebelum-wabah-covid-19

 

Meng B., Choi K. (2016), "The role of authenticity in forming slow tourists’ intentions: Developing an extended model of goal-directed behavior", Tourism Management, Vol. 57, No. 397–410 https://doi.org/10.1016/j.tourman.2016.07.003

 

Meng B., Han H. (2016), "Effect of environmental perceptions on bicycle travelers’ decision-making process: developing an extended model of goal-directed behavior", Asia Pacific Journal of Tourism Research, Vol. 21, No. 11, pp. 1184–119 https://doi.org/10.1080/10941665.2015.1129979

 

Molz J.G. (2009), "Representing pace in tourism mobilities: Staycations, slow travel and the amazing race", Journal of Tourism and Cultural Change, Vol. 7, No. 4, pp. 270–28 https://doi.org/10.1080/14766820903464242

 

Neuburger L., Egger R. (2020), "Travel risk perception and travel behaviour during the COVID-19 pandemic 2020: a case study of the DACH region", Current Issues in Tourism, Vol. 24, No. 7, pp. 1003–101 https://doi.org/10.1080/13683500.2020.1803807

 

Noorashid N., Chin W.L. (2021), "Coping with covid-19: The resilience and transformation of community-based tourism in brunei darussalam, Sustainability", Vol. 13, No. 15 https://doi.org/10.3390/su13158618

 

Papatheodorou A., Rosselló J., Xiao H. (2010), "Global economic crisis and tourism: Consequences and perspectives", Journal of Travel Research, Vol. 49, No. 1, pp. 39–4 https://doi.org/10.1177/0047287509355327

 

Parady G., Taniguchi A., Takami K. (2020), "Travel behavior changes during the COVID-19 pandemic in Japan: Analyzing the effects of risk perception and social influence on going-out self-restriction", Transportation Research Interdisciplinary Perspectives, Vol. 7 https://doi.org/10.1016/j.trip.2020.100181

 

Perugini M., Bagozzi R.P. (2001), "The role of desires and anticipated emotions in goal-directed behaviours: Broadening and deepening the theory of planned behaviour", British Journal of Social Psychology, Vol. 40, No. 1, pp. 79–9 https://doi.org/10.1348/014466601164704

 

PWC (2021), "Revitalising tourism in Southeast Asia", viewed 01 August 2021 https://www.pwc.com/sg/en/publications/revitalising-tourism-in-southeast-asia.html

 

Qiao G., Zhao X.-L., Xin L., Kim S. (2021), "Concerns or desires post-pandemic: An extended MGB model for understanding South Korean residents’ perceptions and intentions to travel to China", International Journal of Environmental Research and Public Health, Vol. 18, No. 5, pp. 1–2 https://doi.org/10.3390/ijerph18052542

 

Raj S. (2020), "How staycation became a new trend in COVID-times", viewed 05 April 2021 https://www.financialexpress.com/lifestyle/travel-tourism/how-staycation-became-a-new-trend-in-covid-times/2067992/

 

Reisinger Y., Mavondo F. (2005), "Travel anxiety and intentions to travel internationally: Implications of travel risk perception", Journal of Travel Research, Vol. 43, No. 3, pp. 212–22 https://doi.org/10.1177/0047287504272017

 

Ringle C.M.; Wende S.; Becker J.-M. (2015), "SmartPLS (3.0), SAGE, Los Angeles, USA".

 

Roy G., Sharma S. (2021), "Analyzing one-day tour trends during COVID 19 disruption–applying push and pull theory and text mining approach", Tourism Recreation Research, Vol. 46, No. 2, pp. 288–30 https://doi.org/10.1080/02508281.2020.1858614

 

Sekaran U.; Bougie R. (2016), "Research Methods for Business: A skill-building approach, John Wiley & Sons, Chicherter, West Sussex, United Kingdom".

 

Sekine I., Uojima H., Koyama H., Kamio T., Sato M., Yamamoto T., Fukaguchi K., Fukui H., Yamagami H. (2020), "Impact of non-pharmaceutical interventions for the COVID-19 pandemic on emergency department patient trend in Japan: a retrospective analysis", Acute Medicine & Surgery, Vol. 7, No. 1 https://doi.org/10.1002/ams2.603

 

Škare M., Soriano D.R., Porada-Rochoń M. (2021), "Impact of COVID-19 on the travel and tourism industry", Technological Forecasting and Social Change, Vol. 163 https://doi.org/10.1016/j.techfore.2020.120469

 

Song H., Lee C.-K., Reisinger Y., Xu H.-L. (2017), "The role of visa exemption in Chinese tourists’ decision-making: a model of goal-directed behavior", Journal of Travel and Tourism Marketing, Vol. 34, No. 5, pp. 666–67 https://doi.org/10.1080/10548408.2016.1223777

 

Statistics Indonesia (2020), "Statistik Wisatawan Nusantara (Domestic Tourism Statistics)", viewed 17 December 2021 https://www.bps.go.id/publication/2021/12/14/fab1c19a78b537d19ced25db/statistik-wisatawan-nusantara-2020.html

 

Sun J., Shi Z., Xu H. (2020), "Non-pharmaceutical interventions used for COVID-19 had a major impact on reducing influenza in China in 2020", Journal of Travel Medicine, Vol. 27, No. 8, pp. 1– https://doi.org/10.1093/jtm/taaa064

 

Vargas-Sánchez A.; Plaza-Mejía M.Á.; Porras-Bueno N. (2016), "Attitude", in Jafari, J. and Xiao, H., Encyclopedia of Tourism, Springer, Switzerland pp. 58 - 61.

 

Wang J., Kim J., Moon J., Song H. (2020), "The Effect of Smog-Related Factors on Korean Domestic Tourists’ Decision-Making Process", International Journal of Environmental Research and Public Health, Vol. 17, No. 10 https://doi.org/http://dx.doi.org/10.3390/ijerph17103706

 

Whitehead A.L., Julious S.A., Cooper C.L., Campbell M.J. (2016), "Estimating the sample size for a pilot randomised trial to minimise the overall trial sample size for the external pilot and main trial for a continuous outcome variable", Statistical Methods in Medical Research, Vol. 25, No. 3, pp. 1057–107 https://doi.org/10.1177/0962280215588241

 

WHO (2019), "Non-pharmaceutical public health measures for mitigating the risk and impact of epidemic and pandemic influenza", viewed 03 April 2021 https://www.who.int/publications-detail-redirect/non-pharmaceutical-public-health-measuresfor-mitigating-the-risk-and-impact-of-epidemic-and-pandemic-influenza

 

Wijaya S., Wahyudi W., Kusuma C.B., Sugianto E. (2019), "Travel motivation of Indonesian seniors in choosing destination overseas", International Journal of Culture, Tourism, and Hospitality Research, Vol. 12, No. 2, pp. 185–19 https://doi.org/10.1108/IJCTHR-09-2017-0095

 

Xu W., Youn H.-J., Lee C.K. (2021), "Role of non-pharmaceutical interventions for COVID-19 in cruise tourists’ decision-making process: An extended model of goal-directed behavior", Sustainability, Vol. 13, No. 10 https://doi.org/10.3390/su13105552


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