Next Article in Journal
The Effect of Environmentally Sustainable Practices on Customer Citizenship Behavior in Eco-Friendly Hotels: Does the Green Perceived Value Matter?
Next Article in Special Issue
Heritage Tourism and Nation-Building: Politics of the Production of Chinese National Identity at the Mausoleum of Yellow Emperor
Previous Article in Journal
Predicting Pedestrian Crashes in Texas’ Intersections and Midblock Segments
Previous Article in Special Issue
The Preference Analysis for Hikers’ Choice of Hiking Trail
 
 
Article

Travel Motivation during COVID-19: A Case from Nepal

1
Kyushu University Institute for Asian and Oceanian Studies, Motooka 744, Fukuoka 819-0395, Japan
2
Faculty of Business Administration, Soka University, Tangimachi 1-236, Hachioji 192-8577, Japan
*
Author to whom correspondence should be addressed.
Academic Editors: Jun Li, Mang He, Wei Tao, Amy Siu Ian SO and Mark A. Bonn
Sustainability 2022, 14(12), 7165; https://doi.org/10.3390/su14127165
Received: 13 April 2022 / Revised: 8 June 2022 / Accepted: 9 June 2022 / Published: 10 June 2022

Abstract

The tourism industry is one of the most affected industries by the COVID-19 pandemic. Understanding travel motivation is necessary for the tourism movement, even in the COVID-19 pandemic. Thus, this quantitative study aimed to explore travel motivation and its determinants. We collected 181 samples through a web-based questionnaire survey of the Nepali people in January and February 2021. The data were analyzed using a probit regression model through two different travel companion perspectives, i.e., traveling with friends and traveling with family members. We found that travel motivation, attributes, travel purpose, and transport mode preferences differed in companion groups. Specifically, those who want to travel with friends are government employees, 20–29 years of age, set health and wellness purposes, choose the bike for transportation, are less willing to visit homestay and agritourism, and want to travel for around one week. Those who plan to travel with family members use the coach to travel, choose rural destinations, including villages, and spend around two weeks. Based on these findings, we suggest that the Nepalese tourism destination and public transport companies make tourism packages targeting the groups. Since both groups showed interest in visiting rural destinations, we can say that tourism in rural destinations may revive earlier than urban tourism after the pandemic. However, a low-risk travel environment should be ensured for traveling to attract more tourists during and the post-disaster.
Keywords: COVID-19; crisis; motivation; Nepal; pandemic; probit; South Asia; tourism; travel; travel motivation COVID-19; crisis; motivation; Nepal; pandemic; probit; South Asia; tourism; travel; travel motivation

1. Introduction

Due to the coronavirus (COVID-19) pandemic, the tourism industry lost over $4 trillion worldwide [1]. International overnight tourist arrival was decreased by 73% (highest in history) in 2020 and 72% in 2021 [2]. This trend in developing countries is much more severe and faced the most considerable reduction in tourism arrivals (estimated between 60–80%) in 2020 [1]. In order to revive the tourism industry in the earliest possible, it is necessary to explore people’s travel motivation during a pandemic. Additionally, investigating the factors influencing travel motivation, travel mode preferences, and travel companions directly contribute to making the strategies for the travel industries and other stakeholders.
Tourism is sensitive and vulnerable to external and internal factors [3]. Every time the international media spread the news about a destination, tourists immediately change their travel plans; either they postpone or cancel their prescheduled travel plans [4]. If the pandemic continues for a long time, it devastates the tourism supply chain, reduces significant revenue, and causes liquidity issues [5]. Ultimately, small and medium-sized tourism enterprises, tourism workers, and destinations are more vulnerable during pandemics [6]. Therefore, smooth tourist movement is necessary even in a crisis both for the travel industry and destination sustainability. In the last 20 years of tourism history, regional and national shocks greatly hampered international tourism arrival [7]. Terrorist attacks on 9/11 in the twin tower in 2001, the SARS outbreak in 2003, the global economic crisis in 2009, and the MERS outbreak in 2015 are some of the major destructive incidents that impacted international tourist arrival [8]. However, a COVID-19 pandemic that appeared in China at the beginning of 2020 has significantly decreased the number of international tourist arrival [2]. Just because of coronavirus, as of 18 May 2020, 100% of destinations worldwide continue to have some travel restrictions, and 75% have closed their borders entirely [7]. No such restrictions were imposed in the tourism industry in history [9]. As of 5 July 2021, in restriction report [10] mentioned that one-third of the travel destinations are partially closed, and 36% are required to demonstrate COVID-19 negative test results and quarantine requirements.
Further, vaccination increases travelers’ confidence; people like to travel where they feel secure from virus infection (as of June 1, 2021) [10]. Nevertheless, different variants appeared in the time being. The increasing number of infections worldwide raises public concerns about whether current vaccines really work for the different muted viruses. The virus mutation trends show the uncertainty of the complete settlement of coronavirus within a short period. Recent muted virus Omicron affected the recovery trend, and as of early 2022, some countries imposed travel restrictions [2]. Even after the booster vaccinations, people are not secure from COVID-19. Therefore, people now have no other option than to get used to COVID-19. Since we have to live with corona, the tourism industry must also move together. Thus, we need to explore whether people prefer traveling with corona and make strategies based on the factors that affect people’s travel motivation.
Although most destinations face traveling restrictions over time, the degrees of restrictions differ significantly region-wise. As of June 1, 2021, when 70% of all destinations were closed in the Asia Pacific, only 13% and 20% were fully closed in Europe and the Americas, respectively [10]. These resulted in a tourism reboot, plus 19% and 17% in America and Europe [2]. Due to the time lag, people are getting used to the coronavirus. The progress in vaccination and easing of travel restrictions in different destinations contributed to people traveling using extra precautions than ordinary time. The progress in vaccination made people travel using extra precautions than ordinary time [2]. Specifically, masking, sanitizing, PCR adverse reports, and vaccination certificates are essential requirements to travel during COVID-19. Scholars from different countries investigated people’s willingness to travel. For instance, an analysis of online ticket sales for seven provinces in China found that people prefer to travel to nearby locations, especially local attractions, where they can feel safe [11]. American tourists were more inclined toward backpacking and camping trips in the wilderness areas because of the low level of fear of wilderness destinations [12]. Aebli et al. [13] found that multiple safety reasons determined tourists’ decision to book domestic tours in the COVID-19 pandemic. Tourists avoid highly infected areas, prefer the international tourists banned destinations, and choose the goal with a flexible cancellation policy [13]. Thus, people may like traveling even in a pandemic if they are assured of their travel safety.
COVID-19 pandemic has created and altered different trends in the tourism industry. For example, Polish people use virtual glasses and experience different destinations virtually [14]; real-time on-sight emotional experiences in China [15]. Many people travel in order to get COVID-19 vaccination where they can quickly get it in the early stage of vaccination [16,17]. However, some other tourism trends, like bleisure (businesss+ leisure) travelers, were demotivated, scared, and anxious [18]. Different tourism trends and travel motivations are somehow connected. Multiple factors contribute to determining travel motivation. Out of them, traveling purpose and destination selection and its determinants are considered more important than other factors to travel inspiration during COVID-19. Either people make travel decisions if they feel safe traveling or are forced to travel for work-related purposes [19]. The travel destination is already being fixed for those forced to travel to work. But, for those who travel for other purposes destination is to be selected. The reality is due to the travel restrictions throughout the world, people have fewer options to choose from. Out of the best availability, domestic tourist destinations have been preferred even in the COVID-19 pandemic than before in different countries because they do not need to follow any immigration restrictions on traveling within the country [3,13,20,21,22,23]. Because of the COVID-19, the same condition may not apply in different countries, and other destinations have various countermeasures. Thus, people’s travel motivation may have been affected differently in different destinations.
Travel motivation and related factors have been studied widely [4,24,25,26,27,28,29,30,31,32,33]. Travel motivation during COVID-19 for ordinary work in Bangladesh [19], travel motivation and psychological behavior in Australia [34], air travelers’ motivation in China [35], and the relation between school breaks and international travel motivation in Germany [36] were explored in different geographical locations. But the travel trends and motivation might be different on different geographical bases. In other words, the travel motivation for tourism purposes in developed and developing countries might be different due to the different levels of carrying capacity, level of infrastructure, organization of the services and mechanism, etc. Thus, the study on travel motivation and factors related to COVID-19 still demands further study because the muted virus and its short time affect people’s perception. Travel motivation and tourism movement in a pandemic are directly connected. Potential travel motivation is necessary to understand not only to prepare tourism strategies during and post-COVID situations but also to contribute to destination sustainability. Thus, this study aimed to explore (1) travel motivation and (2) its contributing factors to travel during COVID-19.
Within the literature review section, multiple contexts that deal with travel motivation in ordinary times will be presented. Regarding the travel motivation during COVID-19, Lin and Zhang [35] studied Taiwanese air travelers’ motivation and revealed that destination image and demographic features have a strong desire to travel. Similarly, Aebli et al. [13] revealed that socio-psychological needs for mental well-being and social connectedness are the major contributors to travel motivation among Western Australian people. Kim et al. [37] and Çolakoğlu et al. [38] studied the safety and travelers’ decisions and found that people feeling socially isolated motivated them to travel during the pandemic. Different scholars mentioned that consumer behaviors changed because of COVID-19 [39,40]. Therefore, we need additional confirmation on travel motivation, destination selection, and mode preferences because internal and external environments can influence people’s perceptions, and it changes with time being [13,27,39,40]. Based on the survey conducted in Nepal, this study discusses travel motivation and factors contributing to it during COVID-19. Based on the results, we present the policy implications.
In this study, we considered the Nepalese travel motivation during COVID-19 because tourism is regarded as one of the major industries in Nepal [41] and faced similar problems to other countries during COVID-19. Most of the tourism destinations in Nepal depend on international tourists [42], but due to the COVID-19, tourist arrival is almost negligent. Many international tourist-dependent tourism countries have no options but need to make new strategies for tourism mobility. Nobody can guess when COVID-19 allows people to travel freely everywhere and when it stops suddenly. China’s government imposed a lockdown in Shanghai even in early April 2022, although many people completed full vaccination [43]. Thus, the pandemic might not be over in a short period of time and exploring travel motivation is beneficial for making strategies during crises like COVID-19 and traveling with corona. Even though the data for this study is collected from Nepal, the implications can be implemented in Nepal and other countries, especially those with similar backgrounds in the tourism industry.

2. Nepalese Tourism Industry

Nepal’s border remained closed for tourism and is a comparatively new phenomenon compared to Western countries because the country was opened to the western world in the early 1960s [44]. However, in 1949 the first permission was given to an American doctor to lead a small party of mountaineers in the Everest region [45]. Then, from 1951 onwards, simultaneous permissions were given to mountaineers to different mountains like Mt. Everest 1951 (submitted in 1953) and other mountains in Nepal [44,45,46]. After the Everest successful summit, the interest of western visitors in visiting Nepal further increased. Now, the tourism industry is considered one of the Nepalese economy’s major industries, providing direct and indirect contributions.
Before the pandemic, the tourism industry contributed 7.8% to the national GDP in 2017; it is forecasted to contribute 8.2% in 2028 [47]. The tourism sector provided direct jobs to 3.2% in 2017 and is expected to rise by 2.1% per anum [47]. Due to the lack of official records of the Nepal government, we cannot present the tourism multiplier effect here. Thus, tourism can be considered a crucial industry for Nepal. However, like other countries, Nepal is also greatly affected by COVID-19, and international tourist arrival was almost nominal after March 2020 [48]. In this context, Nepalese tourism destinations have no option to depend only on domestic tourists. Even though Nepal is a tourist country, and its tourist history has over 70 years, many tourism activities are still untapped [42]. Because of the mountainous country, the major tourism activities in Nepal are mainly adventurous such as mountaineering, trekking, hiking, rafting, jungle safari, water-related activities, etc. [44,49]. Nepal Tourism Statistics [41] disclosed that more than 16% of the international tourists arrival were for trekking, and around 36% visited different conservation areas. Besides mountaineering, trekking and hiking in Nepal are mostly famous in four destinations such as Everest, Annapurna, Langtang, and Kanchanjunga regions [44]. Chitwan National Park and Bardiya National Park are attracting more tourists for jungle activities [49].
Due to the no official record of the domestic tourists in Nepal, we cannot present the data and economic contribution, but those who make travel plans mainly target adventures. Additionally, two famous homestay villages (Ghalegaun and Sirubari in the western part) are popular with domestic tourists, offering new tastes and services to the visitors [50]. Thus, a homestay signifies a tourism destination rather than just a cultural exchange center for a stereotyped Nepali. In other words, visiting a homestay for a common Nepali person signifies visiting either Ghalegaun or Sirubari. Pilgrimage and meditation are other popular types of tourism in Nepal. From the ancient period, Nepali land is considered a good place for meditation in the temples and caves in the hills, mountains, and the lower plain land in the Southern belt. Foreign tourist arrivals in Nepal cover almost 15% of pilgrimage in Nepal [41]; this data also includes the number of Yoga and meditation purposed tourists. Although due to the lack of data on the exact number of tourists visiting for health and wellness, the significant adventurers visit yoga and wellness centers during their visiting Nepal.

3. Literature Review

Willingness to travel (WT) or travel motivation determines whether an individual prefers visiting a particular destination. WT and travel motivation have been studied widely in the tourism literature. WT is defined as a tool that helps understand people’s travel choices and activities [51,52]. WT further pushes an individual to search for a destination where he/she can satisfy his own interests by taking a leisure trip [53,54,55]. Similarly, travel motivation has been studied from multiple perspectives. Travel motivation for determining individual satisfaction [38,56,57,58], leisure participation [59], tourist decision and consumption [60], and the role of safety-seeking and travel decision [37] are some of them. In this study, travel motivation signifies travelers’ willingness to choose destination and mode preferences to make their travel safe and pleasant while visiting a tourist destination. Perceptions and attitudes can be changed in different contexts and times [13,27,39,40]. Thus, this study picked up the travel motivation and factors related to COVID-19 for people’s travel planning.
Travel planning is a system that supports people and goods to manage systematically [61]. Many articles on the travel planning process are introduced to an ordinary situation in the destination because travel planning is done to avoid congestion spots, especially during peak times [61,62]. Similarly, destination choices are made based on a negotiation process between tourist attributes and destination characteristics [63]. In the context of risk of travel, tourists make their destination choices based on their perceptions [64]. People simply cancel their travel plans if they perceive physical risks in traveling to a destination [65]. Individual characteristics and preferences are crucial for travel motivation and destination selection. Consequently, one should be careful about risk factors while making a travel decision [64]. Traveling in the COVID-19 pandemic needs additional care to avoid the risks.
Travel motivation is a part of the travel decision-making process, which consists of determining where to go, why to go, how to go, with whom to go, and beyond. It additionally consists of a deeper understanding, summarizing growing actions, and confirming individual and collective activities at the destination [24]. Sociodemographic, psychological, travel aspects, and alternative destinations influence the travel decision-making process in ordinary times [26,27]. Nevertheless, during the current pandemic, people have limitations while selecting a specific destination. People need to choose a travel destination based on their health risks and psychological risks that suit their aims to visit the destination information on safety, pricing, and travel campaigns [28,29]. Based on the literature, we can say that tourists who want to travel during COVID-19 also select the destination to feel safer by minimizing the health and other risks. Because of the extended lockdowns, people might have more stress than in ordinary times. In this base, we set our first hypothesis (H1) for this study―travel motivation and the health and wellness purpose of traveling have a strong connection―.
Travel motivation is affected by different factors. Media reports and sensations significantly affect travel motivation in a specific destination [4,30,31]. Any negative news about a destination pushes travelers to cancel their trips or postpone them next time [32,33]. Oppositely, sometimes mass media plays an essential role in awareness creation which ultimately helps to motivate people to travel [25]. Therefore, we can say that personal risk perception and external factors like mainstream media and social media directly contribute to travel motivation.
Personal attributes and travel motivation also have a direct relationship. Specifically, demographic factors such as gender, age, family life cycle, income, country’s level of development, etc., greatly influence travel motivation [53,66,67,68]. Gender is a major influencing factor in travel motivation, and travel patterns also vary between males and females in ordinary times and pandemics [69]. For example, a study in Bangladesh found that male people travel more than females just because of the nature of the job during pandemics [19]. Anwari et al. [19] further revealed that the males reduced their recreation travel but continued the work-related trips recommended by their offices even during the COVID-19 pandemic. Generalizing these study results, people can freely choose the destination based on the destination attractiveness in normal conditions. However, during a crisis like the COVID-19 pandemic, they have limited or no choice of destination [3,70].
Age relates to travel motivation, destination selection, and travel mode preferences. For example, compared to younger people, people aged 65 and older are more likely to travel for health or educational purposes and more concerned about personal safety both getting to the destination and at the destination for automobile travel [71,72]. New York Times [73], published on 13 March 2020, mentioned that young people do not care about the virus, are confident, and fly within even in the pandemic. Forbes [74] (12 July 2020) also noted similar results that young adults like to travel during COVID-19. A survey conducted on 6121 respondents worldwide, 77% of them between 18 and 34, revealed that 64% have already started planning their next trip [75]. UNCTAD [76] mentioned that young people and backpackers are willing to travel more than old-aged people even in a pandemic. Based on this background, we set the hypothesis (H2)―young people prefer traveling during the COVID-19 pandemic as well―.
Travel motivation and means of travel have direct connections, but travel mode preferences during COVID-19 have changed before the pandemic. Tourists avoid large public transport and prefer using small vehicles made for limited people or family purposes not only for daily life but also for tourism purposes [70,77]. For instance, more than 30 million people used cruises in the year before COVID-19 [78]. After the pandemic, people less preferred cruises because of the closed environments and outbreaks of infectious diseases. Oppositely, small vehicle usage not only for daily life but also for tourism purposes is growing during pandemics [70,79]. For instance, more people use private cars to trip to Poland and the UK [70,80]. The bike-sharing option became more attractive and vital for the safety of COVID-19 in Greece [81]. In China, people avoid public vehicles and use bikes while visiting tourist destinations [82]. A study from Spain found that the willingness to use bike-sharing or kick scooter-sharing increased by more than two-thirds comparing the pre-COVID period [83]. Bike and public transport were explored as complementary to mobilizing tourists in the urban environment of the USA [79]. From these findings, we can say those small vehicles are critical and more preferred as a travel mode during COVID-19. In the case of Nepal, people may use small vehicles while traveling where possible.
To sum up, travel motivation and the connection between attributes are investigated in the tourism literature; however, it is not fully explored, particularly in the pandemic situation. Thus, we investigate the Nepalese travel motivation during the pandemic.

4. Research Methodology

4.1. Data Collection

As the main objective of this study is to explore the travel motivation of the potential tourist and its determinants, we conducted an internet-based questionnaire survey known as a convenience sampling technique for data collection. Due to the effects of COVID-19, convenience sampling was the best option for us because an in-person survey was not permitted. Therefore, we could not approach those who have no internet access. However, the authors gave utmost effort to prevent common method errors. We requested earlier respondents to recommend other potential participants for this survey to make more representative samples on age groups, professions, gender, etc. Then, we approached and follow-up them individually.
A questionnaire set was prepared in google forms. The link was sent through the emails, posted on different SNSs platforms like Facebook, and requested the participants to fill the survey sheet within 15 days starting from 29 January 2021. We gave a brief description at the beginning of the questionnaire and did not limit any quota based on age, gender, profession, location, etc. The responses were collected voluntarily and anonymously. We used SNSs as a survey tool to collect the data, which is quite useful for developing countries where SNSs are considered for both entertainment and mode of communication. Sample collection from different destinations is complex in developing countries due to weak infrastructure and underdeveloped systems; SNSs make it easier to reach the target audience. Further, participants were also requested to share the link with their friends as well. Thus, this survey adopted a convenience snowball sampling method for the data collection. An Internet-based questionnaire survey has been widely used in the tourism industry [70,84,85,86], especially with COVID-19; it is helpful to avoid the restrictions and quarantine requirements [34]. Moreover, it is cost-effective and can have diversified samples in a short period [84,85,86].
At the survey time, the COVID-19 infection peaked at the first wave on 21 October 2020 (5743 of seven days average and total active infection is 45,200), and it started falling [87]. On 25 January 2021, 339 new infections of COVID-19 on seven days average and 2324 total active cases. In the meantime, the COVID-19 infection in other western countries worsened [87]. From these data, we can say that Nepalese people were slowly getting used to coronavirus, and the government gradually removed restrictions.
Regarding the survey contents, we developed it based on the literature. Most of the contents are in Figure 1. Specifically, we asked whether the participants preferred traveling during COVID-19, what are their preferences on travel purpose, mode selection, destination choice, travel companions, lengths of stay, etc. (Table 1).

4.2. Descriptive Statistics

A total of 181 complete responses were received. Over half of the respondents were between 20 and 29 (50.8%), followed by 30–39 (29.8%). Regarding the profession, private company workers were 24.9%, and students were 21.1%. The female and male combination was 24.3% and 75.7%, respectively. More respondents were young in this survey because young people and students are more active in SNSs than older people in Nepal. Due to the lack of proper statistical records, it is hard to say how many young Nepali people travel in a year. However, international tourists’ arrival below 45 years of age was 58% in 2019 [41]. These statistics disclose that more tourists in Nepal are young. Regarding gender, equal opportunities and priorities were offered for both males and females during the survey, but male respondents were more. University graduates were 44.8%, but the national average as of 2011 is 10.2% junior high graduates, 6.4% are high school graduates, 2.8% are university graduates, and master’s graduates are only 0.9% of the total literate population [88]. The destination preferences, mountains (54.7%), and village/rural areas (57.9%) were the most targeted areas during COVID-19. Similarly, only 20% of respondents were planning to travel to big cities. It depicts that people target more to travel natural areas during COVID-19. A significant number of people’s travel purpose was to visit new destinations (69.5%). The majorly preferred travel mode is plane (49.5%) followed by private car and coach both were 36.8% each. A detailed description of the data is presented in Table 1.

4.3. Model Estimation and Data Analysis

We set the explained variable for this study as travel motivation based on the objective. Travel motivation was originally mapped into three categories, i.e., definitively willing to travel, not willing to travel, and not sure (maybe). However, we integrated ‘not willing to travel’ and ‘not sure’ at the analysis stage because we wanted to see the clear difference between straightforward travel motivations and otherwise. Thus, the explained binary variable for this study is travel motivation (yes = 1, otherwise = 0).
Next, we tested the significant connection between explained and explanatory variables using Chi-square/Fisher’s exact test. The details of the statistical relationship between the variables are presented in Table 2.
The data analysis was conducted from two perspectives. We used the whole sample (181) to explore the connection between travel motivation and other explanatory variables in Model A. However, we removed the number of students from the primary sample and analyzed the data in Model B. We tested the results by excluding students, assuming that Nepalese students’ travel behavior might also affect by limited income opportunities [89]. In model A, we incorporated factors related to individual travel motivation traveling either alone or with friends (excluding family members) perspectives. We included personal travel motivation (including family members) in Model B. Although the results were not so different, we kept both models to do meaningful discussion throughout the paper.
We use the probit regression model to analyze the data. The model for travel motivation can be written:
Travel motivation = f (vector of determinants factors of travel motivation during COVID-19)
In general, travel behavior is typical and varied based on its various characters. For example, who travels, why, with whom, how, where to travel, etc., make travel motivation different (Figure 1). We supposed that a travel motivation during the COVID-19 pandemic is affected by three vectors, i.e., attributes, travel purpose and destination location, duration of travel, and means of transport (Table 3). In each vector, different explanatory variables are included.
In attributes, we incorporated government employees’ travel with friends and families because we suppose that the regular income of government employees facilitates travel. People prefer to travel within their close circles and to whom they can feel secure from infection. For instance, people may feel safe while traveling with family members or friends in a closed circle. Similarly, the young generation (20–29) is also included in the model because popular international bodies and literature discovered that young people travel more during COVID-19 (See Section 3).
To travel purposes, we included health and wellness in the model based on the assumption that people focus on improving immunity to cope with the COVID-19 virus. We incorporated rural villages and homestay & agritourism in the model for the destination selection. We kept agritourism and homestay as tourist destinations because Nepalese people consider them as a destination. Since people were stacked at home due to extended lockdowns, they might search for open spaces in the rural villages. Further, community-based homestay/agritourism is growing in many destinations, and domestic tourists prefer to visit before COVID-19.
For the means of transport and duration of touring, we included bike and coach and travel around one week and around two weeks, respectively. We considered bike and coach in the model because many young people ride a bike in Nepal, and only two people can ride a single bike, reducing infection possibilities. The second option for traveling is using a coach in a group over two. Regarding the travel duration, hiking and trekking are more prevalent in Nepal, and most rural Nepal tour/trekking destinations consume time [90]. Thus, we incorporated around one week and more time into the model.
We tested the connection between travel motivation and other variables like gender, income, etc. However, in this study, we could not find a significant relationship. The data analysis was performed in Stata 16.1 SE.

5. Results and Discussions

We obtained adjusted R-square = 0.2690, Prob > F = 0.0000 in Model A and adjusted R-square = 0.3230, Prob > F = 0.0000 in Model B, which means the explained variable and explanatory variables included in both models are fitted well. We also checked the variance inflation factor using OLS and found nothing serious in both models. Further, the explanatory variables’ correlation was smaller than 0.8, meaning no problems. We also checked the robustness of both models to confirm if any concerns remain. However, neither in coefficients nor in significant levels in both models, there were no such big differences. Thus, the model we developed is fitted well. All the explanatory variables had significant connections with the travel motivation during COVID-19. In order to understand the effects of each variable on travel motivation, we also calculated the marginal effects in both models and presented them together with the results in Table 3. In this study, our 1st hypothesis (H1)―travel motivation and health and wellness purpose of traveling have a strong connection―and second hypothesis (H2)―young people prefer traveling during the COVID-19 pandemic as well―has been accepted at a 1% significant level in Model B and Model A, respectively (Table 3). The other individual results presented in Table 3 are discussed below.
Table 3. Estimation results of the travel during COVID-19 from a probit regression model.
Table 3. Estimation results of the travel during COVID-19 from a probit regression model.
VariablesModel A Model B
Coeff.Z-ValuesMarginal EffectsCoeff.Z-ValuesMarginal Effects
OrdinaryRobustOrdinaryRobust
Attributes (Who, with whom)
Government employee (yes = 1, no = 0)1.004 ***2.592.640.377 **0.7110 *1.721.720.291 *
Age between 20–29 years (yes = 1, no = 0) 0.7488 **5.502.800.285 ***
Travel with friends (yes = 1, no = 0)1.173 ***4.494.460.423 ***
With family member (yes = 1, no = 0) 0.6638 **2.052.220.135 *
Purpose and destination (Where, why)
Travel for health and wellness (yes = 1, no = 0)1.304 ***2.842.760.485 **
Agritourism as a tourism destination
(yes = 1, no = 0)−0.982 **−2.28−2.07−0.232 ***
Travel in rural destination including villages (yes = 1, no = 0) 0.7422 **2.462.500.227 **
Duration and means of transport (How, how long)
Use bike to travel (yes = 1, no = 0)0.608 *1.951.710.221
Public bus/tourist coach (yes = 1, no = 0) 0.9441 ***2.962.930.159 ***
Travel for around 1 week (yes = 1, no = 0)0.844 ***2.812.600.311 **
Travel for around two weeks (yes = 1, no = 0) 1.9807 ***2.852.660.285 *
Constant−1.200 ***−7.53−8.05 −1.7076 ***−6.03−8.43
Sample size181 141
Notes: *** p < 0.01, ** p < 0.05, * p < 0.1 significant level. Source: Authors’ survey, 2021.
Government employees and travel motivation during COVID-19 had a significant connection (1%). It is the highest contributor for Model B and 3rd contributor for Model A in marginal effect calculation. This result suggests that government employees will travel more during COVID-19. It has multiple reasons behind it. First, government employees have fixed incomes, which is a primary reason for traveling. The salary of government staff does not affect by a natural or artificial disaster. Second, the Nepal government introduced a policy to travel compulsorily for its employees. At the province level, they started in 2019, and throughout the country, the central government declared a ten-day complete paid travel holiday package for all employees in 2021 [91]. Based on these findings, we can say that the government policy on tourism movement during COVID-19 is on the way to its implementation.
Young people (20–29) and travel motivation were explored as significant (5%) and the second greatest contributor to marginal effects in Model B. Not surprisingly, this result discloses that young people prefer traveling more during COVID-19, which was our second hypothesis. There are multiple reasons behind this result. First, young people want to accept challenges, and even in the COVID-19, young and backpackers were explored as major travelers during COVID-19 [76]. Second, due to the border closers, people do not have the opportunity to travel to foreign countries during a pandemic. The trend of youth participation in the domestic tourism market in developing countries increased before the pandemic, which does not require a significant amount of money. For instance, Baniya & Paudel [20] studied Nepalese domestic tourists’ travel behavior and found that around 89% of the total domestic tourists were young (21–30). Bangladeshi young tourists (20–30) were explored as major contributors to the domestic tourism industry [22]. A similar trend was observed in Malaysia and India [21,23]. Thus, the young people who have no choice but to travel during COVID-19 prefer traveling to domestic tourism destinations.
Travel with friends and travel motivation was significantly connected at 1%, and it is the second contributor in terms of marginal effects in Model A. Similarly, travel with family members and travel motivation was significant at 5% and 6th contributor in Model B. These results suggests that those people who want to travel either with friends or family members will travel more during COVID-19. This may be because of the low risk of virus infection while traveling with the people of the closed circle than traveling with unknown people. Close friends and family members clearly know each other’s travel history, giving them peace of mind.
Travel purpose (health and wellness) and travel motivation are connected significantly at 1% and are the highest contributor to marginal effect calculation in Model A. This result suggests that our 1st hypothesis―travel motivation and health and wellness purpose of traveling have a strong connection―has been accepted and clarified that health is the tourists’ major concern to traveling during the pandemic. People are afraid of COVID-19 and want to increase their immunity power through traveling.
The destination preferences (homestay and agritourism) were connected at 1%, and 5th contributor in marginal effects calculation in Model A. These results suggest that those who travel with friends less prefer to visit agritourism and homestays during COVID-19. There are multiple reasons behind this finding. One of them is not having distributed agritourism in rural Nepal [42]. This result is opposite to Roman et al. [70], who found agritourism was the main attraction during COVID-19 in Poland. If community homestays are well prepared by bonding through social networks and conveying a message that they are ready and willing to host tourists, they can overcome such a crisis [92]. Rural destinations, including rural villages and travel motivation, had a significant connection (5%) and 4th contributor in marginal effects calculation. Specifically, those who want to travel with family members prefer more travel to rural destinations, including rural villages. UNWTO [2] predicted similar results as the new tourism trend in 2022 would be open-air, nature-based, and rural tourism in a nearby home. The cause behind this result is that most of the popular tourist destinations in Nepal lie in rural areas, and visiting rural destinations, including villages, helps to distance from the city crowds and gives them peace of mind from the virus contagion. Secondly, rural areas are peaceful, and people are more nostalgic while visiting those destinations.
Besides attributes, travel purpose, and destination selection, the next important step is to decide the travel mode. Regarding the means of transport to the Nepal people, while traveling during COVID-19, we statistically explored those bikes and coaches are the primary means of transportation in Nepal at 1% and 5% in model A and Model B, respectively. When people prefer to travel with friends, they love to use bikes (Model A). However, when people include family members as their travel companions, simply a bike is insufficient. Thus, they might have decided to use the coach to transport (Model B).
The selection of bikes to travel with friends has multiple reasons. First, using a bike to travel during the COVID-19 pandemic helps maintain social distancing and cheap and convenient means of transport to travel the rural destinations where the public vehicle is not readily available. Second, bikes are more preferred means of private vehicle in Nepal for daily life. Among the number of registered vehicles, bikes are much bigger in numbers than other types of vehicles. The latest data published by the Department of Transport Management [93] (as of February 2019) shows that 2530722 bikes were registered, whereas the number of car/jeep/vans ware 237,658 and buses was 49,318. Third, due to the COVID-19, people would like to travel within their close circle due to virus infection. A review study on family relationships and travel found that traveling with family members felt secure and increased travel bonding [94]. This result is consistent with the previous literature. Roman et al. [85] explored that people prefer traveling with family and friends during COVID-19 in Poland. Different scholars in different countries revealed similar results. Bike-sharing options became more attractive and important means of travel during the pandemic in Greece [81]; Chinese tourists also preferred bikes when possible to travel during the pandemic [82]; Bike-sharing was increased by two-thirds in Spain [83]. From this supporting literature, we can say those small vehicles are critical to travel during the COVID-19 pandemic. For the coach selection, people might have the second-best option of means of transport during COVID-19. Having a good car for an average-income person in Nepal is like a dream. Rental cars are available, but they are a bit expensive for ordinary people. People might have chosen the coach as a means of travel due to the cost-effectiveness. More people can travel using single vehicles, and relatively folding coaches are more comfortable traveling on Nepalese roads than small vehicles.
We found two different results connected with travel motivation at a 1% significant level (Table 1). Those who prefer to travel with a friend use bikes and travel for around one week at 1% (Model A), whereas those who travel with family members and use a coach as a means of transport prefer traveling for around two weeks at 1% (Model B). It reveals that people who want to travel for about one week will travel more during COVID-19. This result is directly linked with Nepalese infrastructural level, geography, peoples’ preferences, etc. Nepal is a mountainous country, and short trekking courses in rural areas are popular with young people. Due to the risk of traveling in the urban areas, people prefer traveling in less crowded areas like rural villages and mountains (Table 1). The popular trekking routes in Nepal are normally from 5 to 8 days long [90]. Because Nepali young people either go biking or trekking, it takes time to explore those destinations.
In summary, travel motivation and its determinants are different with whom to travel, where to go, and how to travel. Here, we found that Nepalese tourists who want to travel with friends use bikes, and the travel duration is shorter than those who plan to travel with family members. Those who wish to travel with family members and go to rural villages prefer using a coach as transportation.

6. Theoretical Contribution

We examined the travel motivation of Nepalese people during COVID-19 in the Asian context. Based on the data collected in January and February 2021, we conclude that people are motivated to travel even during the pandemic if they feel secure while traveling. Thus, this study adds value to the theory by exploring the travel motivation during COVID-19 and the research method by using the SNSs as a research tool in the tourism literature.
We created the travel motivation model based on the travel companions. Specifically, we supposed that the degrees of travel motivation and its determinants are based on the travel companions, i.e., traveling individually with friends or in groups with family members. This study statistically found significant differences in travel mode selection, destination preferences, and travel duration. The relationship between elements is related to who travels, why and where to travel, and how and how long to travel. Using the probit model, we could ground our hypotheses that travel during COVID-19, health-related factors have connections, and young people travel more during a pandemic. In other words, this study confirmed the relationship between attributes, travel purpose, and mode preferences with travel motivation.
Regarding the research methodology, we used SNSs as a survey tool to collect the data, which is important for developing countries because SNSs are for entertainment and communication. In developing countries where mainstream means of communication are expensive for the local people and hard to get contact numbers. However, using SNSs makes getting in touch at a low cost possible. Thus, the stakeholders can also use SNSs to promote their travel business.

7. Policy Discussion

We found that government employees and young people are motivated to travel more during COVID-19 in Nepal. The government already has a travel vacation policy for its employees, and government employees are motivated to travel even in COVID-19. The different destinations can grab this opportunity to host government employees as tourists. However, the government should not only offer the policy to their employees; they should monitor the procedure by developing guidelines for travel destination selection. For instance, we found homestay and agritourism were less favored to visit. The government should encourage employees to stay in the homestay and agritourism during their visits. Furthermore, most government employees may also choose popular tourism destinations that ultimately are less productive for tourism diversification and expanding destinations. There should be a limited quota for each popular destination, and more number employees should promote to travel to less popular tourism destinations. Government offices can use lots or a rolling basis to decide when an employee can choose a destination for their visit. The government subsidies to ordinary travelers can contribute significantly to tourism destination selection in the less favored destination [95]. Countries that do not have travel packages for their employees can also encourage their employees to visit less popular tourist destinations in multiple ways like paid vacation, discounted coupons, etc. The method may contribute to reviving the tourism industry in different crises.
Concerning the purpose of traveling, people who want to visit with friends travel for health and wellness purposes. These people less preferred agritourism or community-based homestays during COVID-19, which is inconsistent with [70], who found agritourism was the main priority of Polish travelers. Oppositely, those who travel with the family members travel for around two weeks and like to visit rural destinations, including rural villages. This result is consistent with the UNWTO [2] projections. We can say that people in closed circles want to travel to different rural destinations in this base. The news analysis of eight countries showed similar results, including France [96]. Tourists who like to spend a long time may choose trekking and Yoga centers in Nepali contexts. Therefore, combined packages of wellness centers located in different rural destinations and tour/trekking trails can develop family/friends targeted travel packages. Those packages may include adventure and health-wellness packages of one to two weeks, focusing on young people and government employees.
Regarding the transport mode preferences, those who want to travel with friends are interested in using bikes and prefer spending around one week. These are fully consistent with the previous literature explored in different countries [70,79,80,81,82]. In contrast, those who select their family members as travel companions will choose public transport, specifically coach, and spend around two weeks in the travel destinations. If the travel company or tourism destination can make a combined package with public transport company like in the developed countries would be beneficial [97]. However, the low-risk travel environment should be ensured.
In this study, we found young travelers are motivated to travel more in the hills and mountains during COVID-19, which is beneficial for developing countries like Nepal, where adventure tourism is the main tourist attraction. Youths are important for tourism resilience in Nepal during and post COVID-19 era. This finding also confirmed the literature [20,21,23,76]. We can say that nature-based and adventure tourism in developing countries will revive earlier from this base. Thus, the policymakers should give the first target to promote nature-based tourism in developing countries.

8. Limitations and Further Direction

This study has some limitations as well. A limited sample size was collected through convenience sampling techniques, and only those who have access to the internet and SNSs are incorporated. This study failed to accommodate the opinions of comparatively old-aged people with no access to SNSs and compare the different opinions between urban-originated vs. rural-originated. Further, it is the fact that more respondents in this survey were young which might bring biased results. These limitations should be eliminated in further studies. To address these issues, future studies should be based on on-site interviews captured by professionally trained interviewers taken at random during different days/sites/times over several peaks and non-peak tourism seasons. The quota sampling technique can be used to generate diversified samples. Then, comparing the results with this study would be interesting. Although different variants of novel coronavirus have been detected, the COVID-19 vaccination might affect travel motivation during COVID-19. These factors should also be considered in future studies.

Author Contributions

Conceptualization, K.B. and T.T.; Data curation, K.B. and P.G.; Formal analysis, K.B.; Funding acquisition, K.B. and T.T.; Investigation, K.B., P.G.; Methodology, K.B.; Project administration, K.B., P.G.; Resources, K.B. and P.G.; Supervision, T.T.; Visualization, K.B.,T.T.; Writing—original draft, K.B. and P.G.; Writing—review & editing, K.B., P.G. and T.T. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Japan Society for the Promotion of Science under Grant-in-Aid for JSPS fellows no JP20J11833, JSPS KAKENHI no 18K11748 and 22K18103.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Available on request to the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. UNWTO. Global Economy Could Lose Over $4 Trillion Due To COVID-19 Impact on Tourism. Available online: https://www.unwto.org/news/global-economy-could-lose-over-4-trillion-due-to-covid-19-impact-on-tourism (accessed on 17 January 2022).
  2. UNWTO. Tourism Grows 4% in 2021 But Remains Far Below Pre-Pandemic Levels. Available online: https://www.unwto.org/news/tourism-grows-4-in-2021-but-remains-far-below-pre-pandemic-levels?fbclid=IwAR2sendRRdcLQcHI1IJsxHKNb1nbF3DLS632LttHnJnO5nbJBVRui9ZXFRs (accessed on 25 January 2022).
  3. Arbulú, I.; Razumova, M.; Rey-Maquieira, J.; Sastre, F. Measuring Risks and Vulnerability of Tourism to the COVID-19 Crisis in the Context of Extreme Uncertainty: The Case of the Balearic Islands. Tour. Manag. Perspect. 2021, 39, 100857. [Google Scholar] [CrossRef] [PubMed]
  4. Zheng, Y.; Goh, E.; Wen, J. The Effects of Misleading Media Reports about COVID-19 on Chinese Tourists’ Mental Health: A Perspective Article. Anatolia 2020, 31, 337–340. [Google Scholar] [CrossRef]
  5. Gössling, S.; Scott, D.; Hall, C.M. Pandemics, Tourism and Global Change: A Rapid Assessment of COVID-19. J. Sustain. Tour. 2021, 29, 1–20. [Google Scholar] [CrossRef]
  6. Basnyat, S.; Sharma, S. Effects of COVID-19 Crisis on Small and Medium-Sized Hotel Operators: Insights from Nepal. Anatolia 2021, 32, 106–120. [Google Scholar] [CrossRef]
  7. UNWTO. Restrictions on Tourism Travel Starting to Ease but Caution Remains, UNWTO Reports. Available online: https://www.unwto.org/news/covid-19-restrictions-on-tourism-travel (accessed on 17 January 2022).
  8. UNWTO. UNWTO World Tourism Barometer, May 2020–Special Focus on the Impact of COVID-19; World Tourism Organization (UNWTO): Geneva, Switzerland, 2020; ISBN 9789284421930. [Google Scholar]
  9. Twining Ward, L.; McComb, J.F. COVID-19 and Tourism in South Asia; World Bank: Washington, DC, USA, 2020. [Google Scholar]
  10. UNWTO. Covid-19 Related Travel Restrictions—A Globel Review For Tourism; UNWTO: Madrid, Spain, 2021. [Google Scholar]
  11. Li, X.; Gong, J.; Gao, B.; Yuan, P. Impacts of COVID-19 on Tourists’ Destination Preferences: Evidence from China. Ann. Tour. Res. 2021, 90, 103258. [Google Scholar] [CrossRef]
  12. Humagain, P.; Singleton, P.A. Exploring Tourists’ Motivations, Constraints, and Negotiations Regarding Outdoor Recreation Trips during COVID-19 through a Focus Group Study. J. Outdoor Recreat. Tour. 2021, 36, 100447. [Google Scholar] [CrossRef]
  13. Aebli, A.; Volgger, M.; Taplin, R. A Two-Dimensional Approach to Travel Motivation in the Context of the COVID-19 Pandemic. Curr. Issues Tour. 2022, 25, 60–75. [Google Scholar] [CrossRef]
  14. Roman, M.; Kosi, R.; Bhatta, K.; Niedziółka, A.; Krasnod, A. Virtual and Space Tourism as New Trends in Travelling at the Time of the COVID-19 Pandemic. Sustainability 2022, 14, 628. [Google Scholar] [CrossRef]
  15. Yang, Y.; Ruan, Q.; Huang, S.; Lan, T.; Wang, Y. Impact of the COVID-19 Outbreak on Tourists’ Real-Time on-Site Emotional Experience in Reopened Tourism Destinations. J. Hosp. Tour. Manag. 2021, 48, 390–394. [Google Scholar] [CrossRef]
  16. Gulati, S. Decoding the Global Trend of "Vaccine Tourism" through Public Sentiments and Emotions: Does It Get a Nod on Twitter? Glob. Knowl. Mem. Commun. 2021. ahead of print. [Google Scholar] [CrossRef]
  17. Kaewkitipong, L.; Chen, C.; Ractham, P. Examining Factors Influencing COVID-19 Vaccine Tourism for International Tourists. Sustainability 2021, 13, 12867. [Google Scholar] [CrossRef]
  18. Walia, S.; Kour, P.; Choudhary, P.; Jasrotia, A. COVID-19 and the Bleisure Travellers: An Investigation on the Aftermaths and Future Implications. Tour. Recreat. Res. 2021. [Google Scholar] [CrossRef]
  19. Anwari, N.; Tawkir Ahmed, M.; Rakibul Islam, M.; Hadiuzzaman, M.; Amin, S. Exploring the Travel Behavior Changes Caused by the COVID-19 Crisis: A Case Study for a Developing Country. Transp. Res. Interdiscip. Perspect. 2021, 9, 100334. [Google Scholar] [CrossRef]
  20. Baniya, R.; Paudel, K. An Analysis of Push and Pull Travel Motivations of Domestic Tourists in Nepal. J. Manag. Dev. Stud. 2016, 27, 16–30. [Google Scholar] [CrossRef]
  21. Chiu, L.K.; Ramli, K.I.; Yusof, N.S.; Ting, C.S. Examining Young Malaysians Travel Behaviour and Expenditure Patterns in Domestic Tourism. Asian Soc. Sci. 2015, 11, 77–88. [Google Scholar] [CrossRef]
  22. Parvez, M.; Kashem, J. Bin Young Tourists’ Attitude towards Domestic Tourism: A Study on Bangladesh. Probl. Perspect. Manag. 2018, 16, 117–129. [Google Scholar] [CrossRef]
  23. Sharma, T.; Sehrawat, A.; Chauhan, A. Domestic Tourism Destination Preferences of Indian Youth. Himal. J. Contemp. Res. 2014, 3, 747–753. [Google Scholar]
  24. Smallman, C.; Moore, K. Process Studies of Tourists’ Decision-Making. Ann. Tour. Res. 2010, 37, 397–422. [Google Scholar] [CrossRef]
  25. Kaushal, V.; Srivastava, S. Hospitality and Tourism Industry amid COVID-19 Pandemic: Perspectives on Challenges and Learnings from India. Int. J. Hosp. Manag. 2021, 92, 102707. [Google Scholar] [CrossRef] [PubMed]
  26. Karl, M.; Muskat, B.; Ritchie, B.W. Which Travel Risks are More Salient for Destination Choice? An Examination of the Tourist’s Decision-Making Process. J. Destin. Mark. Manag. 2020, 18, 100487. [Google Scholar] [CrossRef]
  27. Zhou, S.; Han, L.; Liu, P.; Zheng, Z.-J. Global Health Governance for Travel Health: Lessons Learned from the Coronavirus Disease 2019 (COVID-19) Outbreaks in Large Cruise Ships. Glob. Health J. 2020, 4, 133–138. [Google Scholar] [CrossRef] [PubMed]
  28. Gautam, P. The Effects and Challenges of COVID-19 in the Hospitality and Tourism Sector in India. J. Tour. Hosp. Educ. 2021, 11, 43–63. [Google Scholar] [CrossRef]
  29. Volgger, M.; Taplin, R.; Aebli, A. Recovery of Domestic Tourism during the COVID-19 Pandemic: An Experimental Comparison of Interventions. J. Hosp. Tour. Manag. 2021, 48, 428–440. [Google Scholar] [CrossRef]
  30. Sönmez, S.F.; Graefe, A.R. Influence of Terrorism Risk on Foreign Tourism Decisions. Ann. Tour. Res. 1998, 25, 112–144. [Google Scholar] [CrossRef]
  31. Pizam, A.; Fleischer, A. Severity versus Frequency of Acts of Terrorism: Which Has a Larger Impact on Tourism Demand? J. Travel Res. 2002, 40, 337–339. [Google Scholar] [CrossRef]
  32. Uğur, N.G.; Akbıyık, A. Impacts of COVID-19 on Global Tourism Industry: A Cross-Regional Comparison. Tour. Manag. Perspect. 2020, 36, 100744. [Google Scholar] [CrossRef]
  33. Mair, J.; Ritchie, B.W.; Walters, G. Towards a Research Agenda for Post-Disaster and Post-Crisis Recovery Strategies for Tourist Destinations: A Narrative Review. Curr. Issues Tour. 2016, 19, 1–26. [Google Scholar] [CrossRef]
  34. Zheng, D.; Luo, Q.; Ritchie, B.W. Afraid to Travel after COVID-19? Self-Protection, Coping and Resilience against Pandemic ‘Travel Fear’. Tour. Manag. 2021, 83, 104261. [Google Scholar] [CrossRef]
  35. Lin, Y.-H.; Zhang, C. Investigating Air Travellers’ Travel Motivation during a Pandemic Crisis. J. Air Transp. Manag. 2021, 97, 102138. [Google Scholar] [CrossRef]
  36. Backhaus, A. International Travel in Times of the COVID-19 Pandemic: The Case of German School Breaks. Econ. Hum. Biol. 2022, 44, 101090. [Google Scholar] [CrossRef]
  37. Kim, J.; Park, J.; Lee, J.; Kim, S.; Gonzalez-Jimenez, H.; Lee, J.; Choi, Y.K.; Lee, J.C.; Jang, S.; Franklin, D.; et al. COVID-19 and Extremeness Aversion: The Role of Safety Seeking in Travel Decision Making. J. Travel Res. 2022, 61, 837–854. [Google Scholar] [CrossRef]
  38. Çolakoğlu, Ü.; Yurcu, G.; Avşar, M. Social Isolation, Anxiety, Mental Well-Being and Push Travel Motivation: The Case of COVID-19 in Turkey. Asia Pac. J. Tour. Res. 2021, 26, 1173–1188. [Google Scholar] [CrossRef]
  39. Arens, E. How COVID-19 Has Changed Social Media Engagement. Available online: https://sproutsocial.com/insights/covid19-social-media-changes/ (accessed on 9 April 2022).
  40. Sheth, J. Impact of Covid-19 on Consumer Behavior: Will the Old Habits Return or Die? J. Bus. Res. 2020, 117, 280–283. [Google Scholar] [CrossRef]
  41. Government of Nepal. Nepal Tourism Statistics 2019; Government of Nepal: Kathmandu, Nepal, 2020.
  42. Bhatta, K.; Itagaki, K.; Ohe, Y. Determinant Factors of Farmers’ Willingness to Start Agritourism in Rural Nepal. Open Agric. 2019, 4, 431–445. [Google Scholar] [CrossRef]
  43. Stanway, D. Whole of Shanghai Enters COVID Lockdown despite Lower Symptomatic Cases. Available online: https://www.reuters.com/world/china/shanghai-lockdown-deepens-after-new-surge-asymptomatic-cases-2022-04-05/ (accessed on 9 April 2022).
  44. Thapa, B. Tourism in Nepal. J. Travel Tour. Mark. 2004, 15, 117–138. [Google Scholar] [CrossRef]
  45. Marks, T.A.; Rowell, G. Many People Come, Looking, Looking. Mt. Res. Dev. 1981, 1, 85. [Google Scholar] [CrossRef]
  46. Stevens, S.M. Tourism and Development in Nepal. Kroeber Anthropol. Soc. Pap. 1988, 67, 67–80. [Google Scholar]
  47. WTTC. Travel & Tourism Economic Impact 2018 Nepal; Southwark Street: London, UK, 2018. [Google Scholar]
  48. NTB. Nepal Tourism Statistics. Available online: https://trade.welcomenepal.com/downloads-cat/nepal-tourism-statistics/ (accessed on 10 April 2022).
  49. Bhatta, K. What Is Agritourism in Nepal? J. Tour. Hosp. Educ. 2020, 10, 170–178. [Google Scholar] [CrossRef]
  50. Walter, P.; Regmi, K.D.; Khanal, P.R. Host Learning in Community-Based Ecotourism in Nepal: The Case of Sirubari and Ghalegaun Homestays. Tour. Manag. Perspect. 2018, 26, 49–58. [Google Scholar] [CrossRef]
  51. Hanemann, W.M. Willingness to Pay and Willingness to Accept: How Much Can They Differ? Reply. Am. Econ. Rev. 2003, 93, 464. [Google Scholar] [CrossRef]
  52. Smith, S.L.J. U.S. Vacation Travel Patterns: Correlates of Distance Decay and the Willingness to Travel. Leis. Sci. 1985, 7, 151–174. [Google Scholar] [CrossRef]
  53. Kara, N.S.; Mkwizu, K.H. Demographic Factors and Travel Motivation among Leisure Tourists in Tanzania. Int. Hosp. Rev. 2020, 34, 81–103. [Google Scholar] [CrossRef]
  54. Pyo, S.; Mihalik, B.J.; Uysal, M. Attraction Attributes and Motivations: A Canonical Correlation Analysis. Ann. Tour. Res. 1989, 16, 277–282. [Google Scholar] [CrossRef]
  55. Yoon, Y.; Uysal, M. An Examination of the Effects of Motivation and Satisfaction on Destination Loyalty: A Structural Model. Tour. Manag. 2005, 26, 45–56. [Google Scholar] [CrossRef]
  56. Khan, M.J.; Chelliah, S.; Ahmed, S. Factors Influencing Destination Image and Visit Intention among Young Women Travellers: Role of Travel Motivation, Perceived Risks, and Travel Constraints. Asia Pac. J. Tour. Res. 2017, 22, 1139–1155. [Google Scholar] [CrossRef]
  57. Çelik, S.; Dedeoğlu, B.B. Psychological Factors Affecting the Behavioral Intention of the Tourist Visiting Southeastern Anatolia. J. Hosp. Tour. Insights 2019, 2, 425–450. [Google Scholar] [CrossRef]
  58. Preko, A.; Doe, F.; Dadzie, S.A. The Future of Youth Tourism in Ghana: Motives, Satisfaction and Behavioural Intentions. J. Tour. Futur. 2019, 5, 5–21. [Google Scholar] [CrossRef]
  59. Yan, N.; Halpenny, E. The Role of Cultural Difference and Travel Motivation in Event Participation: A Cross-Cultural Perspective. Int. J. Event Festiv. Manag. 2019, 10, 155–173. [Google Scholar] [CrossRef]
  60. Chen, C.-H.; Nguyen, B.; Klaus, P.; Wu, M.-S. Exploring Electronic Word-of-Mouth (EWOM) in The Consumer Purchase Decision-Making Process: The Case of Online Holidays–Evidence from United Kingdom (UK) Consumers. J. Travel Tour. Mark. 2015, 32, 953–970. [Google Scholar] [CrossRef]
  61. National Business Travel Network (NBTN). The Essential Guide to Travel Planning; National Business Travel Network (NBTN): London, UK, 2008. [Google Scholar]
  62. Garcia, J.; Juaneda, C.; Raya, J.M.; Sastre, F. A Study of Traveller Decision-Making Determinants: Prioritizing Destination or Travel Mode? Tour. Econ. 2015, 21, 1149–1167. [Google Scholar] [CrossRef]
  63. Ankomah, P.K.; Crompton, J.L.; Baker, D. Influence of Cognitive Distance in Vacation Choice. Ann. Tour. Res. 1996, 23, 138–150. [Google Scholar] [CrossRef]
  64. Mansfeld, Y. The Role of Security Information in Tourism Crisis Management: The Missing Link. In Tourism, Security and Safety; Elsevier: Amsterdam, The Netherlands, 2006; pp. 271–290. [Google Scholar]
  65. Wang, Y.S. The Impact of Crisis Events and Macroeconomic Activity on Taiwan’s International Inbound Tourism Demand. Tour. Manag. 2009, 30, 75–82. [Google Scholar] [CrossRef]
  66. Liao, H.-H.; Su, C.-J.; Lorgnier, N.; Lan, Y.-F.; Oh, S. Adolescents’ Motivation for Family Travels: Cross-Culture/Cross-Country Evidence. Asia Pac. J. Tour. Res. 2022, 27, 103–134. [Google Scholar] [CrossRef]
  67. Ma, A.T.H.; Chow, A.S.Y.; Cheung, L.T.O.; Lee, K.M.Y.; Liu, S. Impacts of Tourists’ Sociodemographic Characteristics on the Travel Motivation and Satisfaction: The Case of Protected Areas in South China. Sustainability 2018, 10, 3388. [Google Scholar] [CrossRef]
  68. Mkwizu, K.H.M. Media and Source Markets for Domestic Tourism in Tanzania: Study of Kitulo National Park. Int. J. Innov. Res. Dev. 2018, 7, 107–112. [Google Scholar] [CrossRef]
  69. Moriarty, P.; Honnery, D. Determinants of Urban Travel in Australia. In Proceedings of the 28th Australasian Transport Research Forum (ATRF), Sydney, Australia, 28 September 2005. [Google Scholar]
  70. Roman, M.; Niedziółka, A.; Krasnodębski, A. Respondents’ Involvement in Tourist Activities at the Time of the COVID-19 Pandemic. Sustainability 2020, 12, 9610. [Google Scholar] [CrossRef]
  71. Eby, D.W.; Molnar, L.J.; Zhang, L.; St. Louis, R.M.; Zanier, N.; Kostyniuk, L.P.; Stanciu, S. Use, Perceptions, and Benefits of Automotive Technologies among Aging Drivers. Inj. Epidemiol. 2016, 3, 1–20. [Google Scholar] [CrossRef]
  72. Eby, D.W.; Molnar, L.J. Age-Related Decision Factors in Destination Choice for United States Driving Tourists. J. Hosp. Leis. Mark. 2002, 9, 97–111. [Google Scholar] [CrossRef]
  73. New York Times Young, Confident and Flying, Virus Be Damned. Available online: https://www.nytimes.com/2020/03/13/travel/coronavirus-travel-deals.html (accessed on 18 January 2022).
  74. Forbes Despite The Delta Variant, Are Some American Generations Still Eager to Travel? Available online: https://www.forbes.com/sites/lealane/2021/08/31/new-survey-despite-the-delta-variant-american-generations-still-eager-to-travel/?sh=785cc8b431eb (accessed on 24 January 2022).
  75. World Hostels. Post COVID-19 Reopening Survey June 2020. Available online: https://www.st-christophers.co.uk/world-hostels-survey/STC-SurveyFindings-Web.pdf (accessed on 10 April 2022).
  76. UNCTAD. COVID-19 and Tourism an Update. Available online: https://unctad.org/webflyer/covid-19-and-tourism-update (accessed on 10 April 2022).
  77. Li, J.; Nguyen, T.H.H.; Coca-Stefaniak, J.A. Coronavirus Impacts on Post-Pandemic Planned Travel Behaviours. Ann. Tour. Res. 2021, 86, 102964. [Google Scholar] [CrossRef]
  78. Moriarty, L.F.; Plucinski, M.M.; Marston, B.J.; Kurbatova, E.V.; Knust, B.; Murray, E.L.; Pesik, N.; Rose, D.; Fitter, D.; Kobayashi, M.; et al. Public Health Responses to COVID-19 Outbreaks on Cruise Ships—Worldwide, February–March 2020. MMWR. Morb. Mortal. Wkly. Rep. 2020, 69, 347–352. [Google Scholar] [CrossRef]
  79. Yang, Y.; Jiang, L.; Zhang, Z. Tourists on Shared Bikes: Can Bike-Sharing Boost Attraction Demand? Tour. Manag. 2021, 86, 104328. [Google Scholar] [CrossRef]
  80. Harrington, D.M.; Hadjiconstantinou, M. Changes in Commuting Behaviours in Response to the COVID-19 Pandemic in the UK. J. Transp. Health 2022, 24, 101313. [Google Scholar] [CrossRef]
  81. Nikiforiadis, A.; Roukouni, A.; Basbas, S.; Chrysostomou, K. Do Businesses Expect Benefits from the Existence of Metro Stations in Their Area? A Case Study in Thessaloniki, Greece. Transp. Res. Procedia 2020, 47, 259–266. [Google Scholar] [CrossRef]
  82. Wen, J.; Kozak, M.; Yang, S.; Liu, F. COVID-19: Potential Effects on Chinese Citizens′ Lifestyle and Travel. Tour. Rev. 2021, 76, 74–87. [Google Scholar] [CrossRef]
  83. Awad-Núñez, S.; Julio, R.; Gomez, J.; Moya-Gómez, B.; González, J.S. Post-COVID-19 Travel Behaviour Patterns: Impact on the Willingness to Pay of Users of Public Transport and Shared Mobility Services in Spain. Eur. Transp. Res. Rev. 2021, 13, 20. [Google Scholar] [CrossRef]
  84. Li, Z.; Zhang, S.; Liu, X.; Kozak, M.; Wen, J. Seeing the Invisible Hand: Underlying Effects of COVID-19 on Tourists’ Behavioral Patterns. J. Destin. Mark. Manag. 2020, 18, 100502. [Google Scholar] [CrossRef]
  85. Roman, M.; Bhatta, K.; Roman, M.; Gautam, P. Socio-Economic Factors Influencing Travel Decision-Making of Poles and Nepalis during the Covid-19 Pandemic. Sustainability 2021, 13, 11468. [Google Scholar] [CrossRef]
  86. Joo, D.; Xu, W.; Lee, J.; Lee, C.-K.; Woosnam, K.M. Residents’ Perceived Risk, Emotional Solidarity, and Support for Tourism amidst the COVID-19 Pandemic. J. Destin. Mark. Manag. 2021, 19, 100553. [Google Scholar] [CrossRef]
  87. Worldometer Daily New Cases in Nepal. Available online: https://www.worldometers.info/coronavirus/country/nepal/ (accessed on 24 January 2021).
  88. Ministry of Education (MOE). Education in Figures 2017 (At A Glance); Singhdurbar: Kathmandu, Nepal, 2018.
  89. Gardiner, S.; King, B.; Wilkins, H. The Travel Behaviours of International Students. J. Vacat. Mark. 2013, 19, 287–299. [Google Scholar] [CrossRef]
  90. Dérioz, P.; Upadhayaya, P.; Bachimon, P.; Loireau, M. Development of Mountain Domestic Tourism Close to the Major Urban Areas of Nepal: South Side of the Annapurna Massif and Helambu. Via Tour. Rev. 2020, 17. [Google Scholar] [CrossRef]
  91. Ministry of Finance (MOF). Economic Survey 2020–21; Singh Durbar: Kathmandu, Nepal, 2020.
  92. Gabriel-Campos, E.; Werner-Masters, K.; Cordova-Buiza, F.; Paucar-Caceres, A. Community Eco-Tourism in Rural Peru: Resilience and Adaptive Capacities to the COVID-19 Pandemic and Climate Change. J. Hosp. Tour. Manag. 2021, 48, 416–427. [Google Scholar] [CrossRef]
  93. Department of Transport Management (DTM). Total Number of Vehicles Registered till Fiscal Year 2018/19; DTM: Kathmandu, Nepal, 2019. [Google Scholar]
  94. Durko, A.M.; Petrick, J.F. Family and Relationship Benefits of Travel Experiences. J. Travel Res. 2013, 52, 720–730. [Google Scholar] [CrossRef]
  95. Ministry of Land Infrastructure, Transport and Tourism (MLIT). White Paper on Land, Infrastructure, Transport and Tourism in Japan, 2015. Available online: https://www.mlit.go.jp/common/001157851.pdf (accessed on 10 April 2022).
  96. Seraphin, H.; Dosquet, F. Mountain Tourism and Second Home Tourism as Post COVID-19 Lockdown Placebo? Worldw. Hosp. Tour. Themes 2020, 12, 485–500. [Google Scholar] [CrossRef]
  97. OECD. The Impact of Culture on Tourism; OECD: Paris, France, 2008; ISBN 9789264056480. [Google Scholar]
Figure 1. Factors related to travel motivation.
Figure 1. Factors related to travel motivation.
Sustainability 14 07165 g001
Table 1. Attributes of the respondents.
Table 1. Attributes of the respondents.
ItemSamples % (Frequency)
GenderMale = 75.7% (137), Female = 24.3% (44)
Age>19 = 1.1% (2), 20–29 = 50.8% (92), 30–39 = 29.8% (54), 40–49 = 12.2% (22), 50< = 6.1% (11)
Education backgroundJunior high school = 5% (9), high school = 21% (38), university graduates = 44.8% (81), Postgraduates = 29.3% (53)
Travel during pandemicYes = 30.4% (55), no = 47.5% (86), maybe = 22.1% (40)
ProfessionPrivate company worker = 24.9% (45), government employees = 8.8% (16), part-timers = 6.1% (11), students = 22.1% (40), retired = 2.8% (5), temporary working in foreign countries = 12.2% (22), unemployment = 4.4% (8), housewife = 2.2% (4), entrepreneur = 13.3% (24), others = 3.5% (6)
Purpose of visit *Visiting new destinations = 69.5% (66), because of work = 23.2% (22), wellness = 10.5% (10), VFR = 37.9% (36), relaxation = 26.3% (25), event participations = 28.4% (27), to play game = 4.2% (6), pilgrimage = 15.9% (15), others = 3.3% (3)
Types of vehicles *Private care = 36.8% (35), rental car = 30.5% (29), Coach/bus = 36.8% (35), plane = 49.5% (47), motorcycle = 28.4% (27), others = 8.5% (8)
Place to visit/destinations *Mountains = 54.7% (52), village/rural areas = 57.9% (55), big cities = 20% (19), lakes = 8.4% (8), others = 23.3% (22)
AccommodationHotel = 51.6% (49), guesthouse/airbnb = 30.5% (29), homestay/agritourism = 15.98% (15), VFR homes = 35.8% (34), campsites = 15.8% (15), others = 10.5% (10)
Travel companionsAlone = 16.8% (16), with lover = 7.4% (7), with friends = 46.3% (44), with family members = 65.3% (62), with co-workers = 20% (19)
Source: Authors’ survey, 2021. VFR = visiting friends and relatives. * Multiple selections. Sample size: 181.
Table 2. Relationship between travel motivation and other variables (Chi-squared/Fisher’s exact test undertaken).
Table 2. Relationship between travel motivation and other variables (Chi-squared/Fisher’s exact test undertaken).
VariablesTravel Motivation
YesNoTR
Government employee (yes = 1, no = 0)62.5027.27***
Travel with friends (yes = 1, no = 0)59.0921.17***
With family member (yes = 1, no = 0)58.0615.97***
Age between 20–29 years (yes = 1, no = 0)31.5229.21ns
Use bike to travel (yes = 1, no = 0)59.2625.32***
Public bus/tourist coach (yes = 1, no = 0)60.0023.29***
Travel for around 1 week (yes = 1, no = 0)60.7124.84***
Travel for around two weeks (yes = 1, no = 0)63.6428.24**
Travel for health and wellness (yes = 1, no = 0)60.0028.65**
Homestay/agritourism as a tourism destination (yes = 1, no = 0)20.0031.33ns
Travel in rural destination including villages (yes = 1, no = 0)59.6516.94***
Source: Authors survey 2021. Notes: *** and ** are 1% and 5% significant level, ns = not significant. Sample size: 181.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Back to TopTop