Next Article in Journal
An Ideology of Sustainability under Technological Revolution: Striving towards Sustainable Development
Next Article in Special Issue
The Intervening Effects of Perceived Organizational Support on COVID-19 Pandemic Stress, Job Burnout and Occupational Turnover Intentions of Collegiate Sport Athlete-Facing Professionals
Previous Article in Journal
Using Forest Compensation Funds to Reverse Biodiversity Loss: A Case Study of Turin–Lyon High-Speed Railway Line
Previous Article in Special Issue
Estimating the Socio-Economic Value of Dance Curriculum as Public Education in Korea for Sustainable Development: Using Contingent Valuation Method
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 14
Issue 8
10.3390/su14084414
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Water Sport Tourists’ Hesitation in Decision-Making during the COVID-19 Pandemic: The Moderating Effect of Destination Image

by
Jeongmyeong Song
1,
Myungkyu Jung
2,
Kwangho Park
3 and
Ho Yeol Yu
4,*
1
Department of Sports Taekwondo, College of Physical Education, Kyung Hee University, Yongin-si 17104, Korea
2
Department of Taekwondo, Sehan University, Yeongam 1113, Korea
3
Dahl School of Business, Viterbo University, La Crosse, WI 54601, USA
4
Department of Health, Physical Education & Sport Sciences, Arkansas State University, Jonesboro, AR 72467, USA
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(8), 4414; https://doi.org/10.3390/su14084414
Submission received: 3 March 2022 / Revised: 30 March 2022 / Accepted: 1 April 2022 / Published: 7 April 2022
(This article belongs to the Special Issue Sustainability of Sport Management in the Post-COVID19 Era)
Browse Figure
Versions Notes

Abstract

:
Understanding the effect of risk factors on tourists’ hesitation in choosing a destination is vital for successful management in tourism, especially in the pandemic era. Based on protection motivation theory, this study investigated the impact of sport tourists’ perceived risk associated with COVID-19 on their hesitation to choose a tourist destination in the context of water sport tourism. Further, we examined whether the relationship changes according to the levels of tourists’ destination image. Data from a survey of water sport tourists (n = 312) were analyzed using structural equation modeling and Hayes PROCESS macro with bootstrapping procedures. Findings of this research empirically demonstrated that risk factors influence hesitation in choosing a destination. Furthermore, the moderating effect of destination image on the influences of perceived risks on hesitation was identified. The study’s theoretical and practical contributions to the sport tourism literature are also discussed.

1. Introduction

The global tourism industry has faced a period of unprecedented disarray and transformation due to the COVID-19 pandemic, which since emerging has adversely impacted the overwhelming majority of economic activity around the world [1]. In particular, in an era when hygiene and safety have become prioritized above all, the sport tourism industry has been significantly impacted as leisure activities have shifted to contact-free services [2]. Beyond that, because the sport tourism industry is labor-intensive due to relying on standardized manual operations (e.g., face-to-face interactions), the pandemic has caused additional difficulties for the industry [3]. In turn, local communities supporting the industry have been forced to adapt to the fundamental, often permanent transformations in the external environment caused by the pandemic—transformations that have simultaneously prompted changes in tourists’ behavior, including the delay, modification, and cancelation of travel plans and requests for alternative tourist destinations [4].
Those behavioral changes among tourists have largely stemmed from shifts in their risk perception, a frequently studied aspect of consumer behavior identified as a significant factor in consumers’ decision-making [5]. In tourism, an activity in which sudden changes and uncertainty abound, decision-making is an especially complex undertaking [6], particularly because the risk perception therein is subjective and distinct from the objective perception of stochastic risks. In such subjective decision-making, several factors (e.g., health, safety, time, cost, and distance for travel) may cause tourists to perceive various risks that impact their destination decision-making in particular [7]. In sport tourism, due to the standard of face-to-face interaction between consumers and businesses, the industry also considers risk perception to include the perception of inconvenience and threats that tourists may experience while selecting destinations to visit and activities to participate in [8]. Owing to all of those factors, sport tourists often hesitate while making final decisions about consuming travel products [9].
Despite the importance of understanding the effect of perceived risk on tourists’ hesitations, few studies have examined that relationship [10,11]. In adjacent work, researchers have examined tourists’ emotions and behavioral intentions in relation to potential risk perception created by the spread of COVID-19 [12] and have sought to forecast what the future holds for the tourism industry in the post-pandemic era [13]. Although such work has focused on the concept and measurement of risk perception in relation to destination selection, information searches, loyalty, and purchase intention, it has rarely investigated hesitation with regard to risk-reducing behaviors that surface under the influence of risk perception. To fill the gap in the literature and to better understand sport tourists’ behavior during the COVID-19 pandemic, this study examined the relationship between risk perception and hesitation, particularly perceived risk’s effect on hesitation in water sport tourism. Water sport tourism is regarded as one of the fastest-growing sectors of tourism in the world due to a growing preference for tourism activities that align with sustainable development [14]. At the same time, because tourist destination image plays a pivotal role in affecting tourists’ behavior [15,16], this study also aimed to examine how destination image moderates the relationship between risk perception and hesitation.
Consequently, the purpose of this research was twofold: (1) to investigate the relationship between the risk perception (e.g., health risk, physical risk, and social-psychology risk) and hesitation among water sport tourists as their needs and behaviors have changed due to the COVID-19 pandemic and (2) to examine whether the relationship changes according to the levels of tourist destination image amid the risk of COVID-19 infection. The current study aims to provide meaningful insights for new environmental and policy strategies for the sport tourism industry, as well as insights into coping with shifts in the consumption of water sports in the post-pandemic era as a means to revitalize the sport tourism industry.

2. Literature Review

2.1. Risk Perception

Because the risks involved in reaching tourist destinations directly affect the tourism industry, research has often empirically examined risk perception in the context of tourism. Arguably, due to various political and social crises (e.g., SARS, swine flu, and MERS), as well as the current COVID-19 pandemic, risk management in tourism has never been more important [17]. In the tourism literature, risk perception refers to tourists’ belief in the likelihood of being exposed to uncertain risks at tourist destinations [15]. Although identified as significantly impacting tourists’ decision-making and tourist activities in general, risk perception has different effects on tourists’ behavior according to their familiarity with or preference for destinations, the novelty of destinations, and destination image in general [18]. For example, if tourists prefer a destination with a high degree of novelty, then they seldom hesitate to travel there even if they perceive a potential danger. In such cases, risk perception has no significant effect on the choice of tourist destination [19].
The six elements of risk developed by Jacoby and Kaplan [20] have most often been used as criteria for measuring the perception of economic (i.e., monetary), physical (i.e., functional), psychological, social, and temporal risks. Drawing on those elements, factors for measuring risk perception have been classified and used in various ways according to the researchers’ varying purposes. For example, Chew and Jahari [15] classified risk perception as having four types of factors—physical, economic, functional, and psychological—whereas other researchers have categorized risk in the context of tourism as having two factors: disease risk and physical risk [21]. Based on such studies [21,22], in this study, we classified risk perception related to tourist destinations during the COVID-19 pandemic according to three factors: risk of COVID-19 (fear of getting infected with COVID-19), physical risk of problems that would jeopardize personal safety, physical injury and sickness, and social and psychological risks due to being in contact with people who may be infected with COVID-19.

2.2. Hesitation

Of the many obstacles in decision-making that people experience in their everyday lives, one obstacle affecting decision-making in the context of consumption is conceptualized as hesitation. A critical factor influencing consumers’ decision-making, hesitation is most broadly defined as procrastinating or delaying the act of making a purchase [10]. Hesitation is considered to be a more stable factor when consumers make their final decisions if combined with a habitual behavior [9]. Such postponement is intended to prevent negative emotions or evaluations resulting from the decision.
Hesitation in choosing destinations in water sport tourism, however, differs from hesitation in purchasing consumer goods in that it requires sacrificing time and space to travel to the destination. Research on hesitation in tourists’ decision-making has shown that tourists overcome the fear of risk and proceed to make final decisions only when they perceive that the situation is controllable [23]. In that light, it is conceivable that tourists are likely to hesitate in their decision-making about whether to travel to engage in water sport because it is difficult to prevent COVID-19 infection even if they take the routine precautions (e.g., washing hands and wearing masks). However, according to Pen and Chen [24], a tourist’s perceived risk of COVID-19 infection relates directly to their hesitation in decision-making. Thus, it is expected that hesitation in choosing a tourist destination would be influenced by the water sport tourist’s perceived risk.

2.3. Destination Image

All types of disasters and crises, including the COVID-19 pandemic, have a long-lasting impact on tourists’ behavior in relation to destination image. In tourism, destination image “consists of all that the destination evokes in the individual; any idea, belief, feeling or attitude that tourists associate with the place” [25] (p. 716). As such, destination image is recognized as a vital factor not only in the tourism industry overall but also in marketing and communication given its considerable influence on the choice of tourist destinations [26]. Moreover, destination image has been identified as a critical factor in affecting tourists’ behavior [16,27]. Decades earlier, scholars first classified the destination image into two dimensions concerning affective versus cognitive images [28,29]. Since then, factors of destination image have been measured and evaluated based on those two dimensions, and various constituent items for measuring each image factor have been extracted [30].
Meanwhile, in other research [15,16], destination image has been shown to significantly affect tourists’ behavior and their psychology (e.g., risk perception and satisfaction). In particular, Chew and Jahari [15] found that the greater the perceived risk of a tourist destination, the less reliable the entire region seems as a tourist destination. However, few studies have verified the moderating role of the destination image in the relationship between perceived risk and tourists’ behavior. In this study, we therefore sought to examine the moderating effect of the destination image on the relationship between risk perception and hesitation for water sport tourists during the COVID-19 pandemic.

2.4. Theoretical Framework and Hypotheses Development

According to protection motivation theory [31], individuals are likely to exhibit protective behavior when the choices before them involve potential risks [9], and such behavior influences their decisions to, for instance, quit or delay their plans. When making decisions involving risks, individuals’ motivation for engaging in protective behavior is based on three cognitive processes: “the likelihood the risk will occur, the severity of the risk, and the potential that protective behavior will reduce” [24] (p. 4). In this study, the primary goal of applying protection motivation theory was to elucidate the likelihood of engaging in protective behavior when decision-making is associated with risks or uncertainty related to a destination as the perception of greater risk would result in reduced intention to choose the destination.
Based on protection motivation theory and our review of the literature, this study proposed that water sport tourists’ perceived risks associated with COVID-19 affects their hesitation in making a decision to travel to engage in water sport. Prior studies have revealed a positive, direct relationship between tourists’ perceived risks and their cognitive hesitation [9]. In terms of perceived risks, this study considered three factors to be pivotal in whether tourists choose a destination during the COVID-19 pandemic: physical health, infections, and psychological safety. Given increased concerns about risks associated with COVID-19 during the pandemic, we expected that when making decisions about choosing destinations, water sport tourists would be concerned about whether the destination provides a safe environment and would compare several destinations offering the same opportunities for engaging in water sport. Accordingly, in three hypotheses, the current study proposes that water sport tourists would delay their decisions to choose destinations if they perceived that risks associated with COVID-19 would be present at those destinations.
Hypothesis 1:
There is a significant relationship between perceived physical risk and tourists’ hesitation in traveling to destinations.
Hypothesis 2:
There is a significant relationship between perceived risk of disease and tourists’ hesitation in traveling to destinations.
Hypothesis 3:
There is a significant relationship between perceived social-psychological risk and tourists’ hesitation in traveling to destinations.
In addition, it is believed that destination image may moderate the relationship between perceived risk associated with COVID-19 and perceived hesitation—put differently, a favorable destination image would attenuate the relationship between some risk factors and tourists’ hesitation to choose. Little research has investigated destination image as a moderator of the relationship between perceived risk and hesitation. Nevertheless, following empirical research showing that the association between perceived risk and behavioral intention is positively influenced depending on the individual’s image of a destination [15], we also hypothesized that tourists holding more favorable destination images would have lower perceived risk and, thus, hesitate less in their decisions to choose the destination:
Hypothesis 4:
Destination image moderates the relationship between water sport tourists’ perceived risk and hesitation.

3. Methodology

3.1. Measurement

The questionnaire was comprised of three content areas: risk, hesitation, and destination image. Existing scales were adapted to fit the context. Specifically, to measure perceived risk associated with COVID-19, a series of scale items measuring perceived risk were adapted from existing research [21,22]. Perceived risk was a second-order construct comprising three sub-dimensions: physical risk (four items), disease risk (four items), and psychological risk (four items). Hesitation was measured with six items adapted from the previous research [9]. Last, destination image was adapted from the previous research [32,33] and comprised two sub-dimensions: (a) four items of infrastructure risk and (b) three items of natural environment.
All items utilized a five-point Likert scale ranging from 1 = strongly disagree to 5 = strongly agree. The survey measurement was first validated by sport tourism professors and leisure sport experts for face validity and content validity (i.e., wording and appropriateness to the context).

3.2. Sample and Procedure

The target group of this study was water sport tourists. Thus, it was necessary to include only those potential tourists who have traveled for participating in water sport. Given that scuba diving is one of the highly attractive water-based activities for tourists [34], we considered scuba diving as the focal water sport. To screen qualified participants, the three questions were given to respondents: (a) Have you ever traveled for water-based activities? (b) Have you ever traveled to participate in scuba diving? and (c) How many years have you participated in scuba diving? Those who did not have any experience in scuba diving were excluded.
The data collection was carried for two months between 20 July and 30 September in 2021 in South Korea. Due to a strict regulation associated with COVID-19 for data collection limiting contacting participants in person, we utilized the snowball sampling approach, a non-probability sampling method. An initial group of potential participants was chosen, and subsequent participants were referred by the initial group of participants [35]. Participants were given the online survey link via messages and SNS and were given information about the purpose of the study, the background of the study, and the duration of participation in the survey. Respondents received an informed consent form in the online survey. We collected a total of 350 questionnaires and 38 questionnaires were eliminated due to incomplete responses. The final sample size was 312. G*Power 3.1.9.6 software was utilized to calculate a minimum sample size for the current study with a statistical power of 0.95, effect size of 0.15, and significance level of 0.05. According to the G*Power calculation, the minimum total sample size required was 199. The present study’s sample size exceeded the minimum sample size.
From the sample, 57.1% were male and 42.9% were female. Nearly 50.6% of the respondents were between 30 and 40 years old. Respondents reported the number of years that they had participated in leisure sport. The majority of respondents had at least 5 years of experience in scuba diving (72.4%).

3.3. Data Analysis

Descriptive statistics for the demographic and measured variables were carried out using SPSS version 23.0. Exploratory factor analysis (EFA) was performed to verify the validity of the scale. In addition, using AMOS version 7.0, this study followed Anderson and Gerbing’s two-step approach [36]. Specifically, a confirmatory factor analysis (CFA) was performed to test the measurement model, and structural equation modeling (SEM) was utilized to test the hypothesized structural model. Lastly, the Hayes PROCESS macro [37] was performed to examine the moderating effect of destination image in the relationship between perceived risk and hesitation. In particular, the bootstrapping method was used to test the significance of the effects to acquire robust standard errors for parameter estimation [37].
The reliability of the scales was measured using Cronbach’s alpha, CR, and average variance extracted (AVE). The suggested value of 0.70 was adopted to assess the reliability of the scales [38]. The cutoff values for AVE were greater than 0.50 [39]. Following the recommendation of Hair, Black, Babin, and Anderson [39], a goodness of fit measure was adopted as follows: chi-square statistic, normed chi-square (χ2/df), root mean square error of approximation (RMSEA), comparative fit index (CFI), and standardized root mean residual (SRMR). The cutoff value of χ2/df was less than 3.0 [40]. Hu and Bentler [41] suggested that RMSEA value between 0.06 and 0.08 indicates an acceptable fit. Values of SRMR that are less than 0.10 indicate a good fit [38]. In addition, it is suggested that recommended values of CFI should be larger than 0.90.

4. Results

Data normality was assessed through skewness and kurtosis. All values of skewness and kurtosis were within the recommended criteria [42]. In particular, values of skewness ranged from −1.008 to −0.268, and values of kurtosis ranged from −0.539 to 0.775. The skewness and kurtosis values were within ±2 and ±4, respectively. Thereby, the normality assumption was met.

4.1. Exploratory Factor Analysis

EFA was carried out using principal component analysis and the varimax method. Initially, EFA yielded 5 latent factors with 25 items, which explained a total variance of 77.0%. The percentage of total variance exceeded the minimum cutoff point of 60% [38]. The Kaiser–Meyer–Olkin measure of sampling adequacy was 0.917, which was greater than 0.700, and Barrlett’s test of sphericity was statistically significant (χ2 = 6048.367, df = 300, p = 0.000). The scree plots also indicated that a six-factor model is appropriate for this data. Additionally, all Cronbach’s alphas were greater than the suggested value of 0.70, indicating good evidence of reliability.

4.2. Measurement Model

CFA was performed to test the psychometric properties of the measured scales (see Table 1). The goodness of fit indices revealed an acceptable model fit (χ2 = 660.170, df = 260, χ2/df = 2.53, RMSEA = 0.07, CFI = 0.93, SRMR = 0.06). In addition, all factor loadings were statistically significant and greater than 0.50, exceeding the minimum criteria [38]. All constructs revealed satisfactory scale reliability as construct reliability and Cronbach’s alpha exceeded the threshold of 0.70. Convergent validity was established as follows: (a) factor loadings were significantly loaded on the respective construct and (b) the average variance extracted (AVE) values were larger than the suggested value of 0.50 [38]. Correlations among measured constructs were less than 0.85, indicating the establishment of discriminant validity (see Table 2).

4.3. Hypotheses Testing

We tested the hypotheses of the study using a structural equation modeling with a maximum-likelihood approach. The results showed an acceptable model fit to the data: χ2 = 323.563, df = 129, χ2/df = 2.50, RMSEA = 0.07, CFI = 0.95, SRMR = 0.05. As shown in Figure 1, physical risk (β = 0.179, t = 3.60, p < 0.001), disease risk (β = 0.603, t = 7.17, p < 0.001), and social-psychological risk (β = 0.136, t = 2.062, p < 0.05) had a significant positive direct effect on participants’ hesitation, supporting H1, H2, and H3.

4.4. The Moderating Effect of Destination Image

Hayes’ PROCESS macro was performed to test H3 [37]. Model 1 of the PROCESS macro with 5000 bootstrap resampling was used. In addition, a simple slope analysis (Model 1) was used [37]. The mean score of destination image for the less identified group (−1 standard deviation below the mean) was 3.00, while it was 4.833 for the highly identified group (+1 standard deviation above the mean). The results indicated that the main effects of perceived risk (β = 0.37, t = 2.59, p < 0.05) and destination image (β = −0.45, t = −4.79, p < 0.01) as well as the interaction effects between the perceived risk and destination image (β = 0.08, t = 2.29, p < 0.05) were all significant. Overall, 64.9% of the variance was explained by the model. In addition, the results of conditional effects showed both moderator values of −1 SD and +1 SD. It was found that the effects were significant at all levels. However, the coefficient value of highly identified group (β = 0.76, t = 12.93, p = 0.000) was larger than the lowly identified group (β = 0.62, t = 10.824, p = 0.000), which indicates that the relationship between perceived risk and hesitation may be stronger for the highly identified group. Moreover, the results indicated that the effect of perceived risk about the destination on how much water sport tourists hesitate to choose the destination depends on the image of destination. Overall, H4 was partially supported.

5. Discussion

The aim of this research was to investigate how water sport tourists perceive risk factors associated with COVID-19 amid the pandemic and how such perceptions impact their hesitation to choose a tourist destination. Water sport is considered to be an active, eco-friendly type of leisure activity in which tourists can participate in local communities and communicate with residents. However, due to the pandemic, social distancing has been strongly enforced in everyday life in order to prevent the spread of COVID-19 across communities. Such restrictions associated with COVID-19—another is the total closure of communities—have limited physical contact between individuals and prevented tourists from traveling, which may have had profound psychological and economic consequences. Paradoxically, in interactions during the pandemic, individuals and communities have had to disperse in order to engage together, and ways of participating in water sport have also been modified due to the pandemic. In that regard, understanding perceptions of water sport tourists’ risk factors and hesitation can provide tourism managers with important insights into designing effective practices of managing their businesses.

5.1. Theoretical Implications

The current study explored the relationship between factors of perceived risk among water sport tourists and their behavior, especially their hesitation, in deciding to choose tourist destinations. Furthermore, the moderating effect of destination image within the relationship between perceived risk factors at destinations and tourists’ decision-making was investigated. As a result, this study was able to provide a comprehensive understanding of tourists’ perceptions of risk factors related to COVID-19 and water sport tourists’ behavior.

5.1.1. The Impact of Risk Factors on Hesitation

The present research identified underlying factors of tourists’ perceived risk regarding COVID-19—namely, physical risk, risk of disease, and social-psychological risk. The results indicate that, among water sport tourists, those factors significantly impacted hesitation. In particular, tourists seem likely to delay making decisions about whether to travel to destinations if they perceive risky outcomes from choosing those places. That delay occurs because tourists are concerned that destinations may not be able to offer sufficient safety regarding physical risk, risk of disease, and social-psychological risk due to COVID-19. In line with this study, Kozak, Crotts, and Law [43] found that 83% of tourists either canceled or changed their plans due to the potential risks. Generally, perceived risk is considered to be a vital factor of tourists’ behavior in a wide range of fields (e.g., hotel management) [24].
Based on the aforementioned findings, the current study reaffirms Floyd, Gibson, Pennington-Gray, and Thapa’s [44] argument that social-psychological risk is crucial for tourists when it comes to making a decision regarding their travel. Previous studies on tourism have identified that, of various risk factors, social-psychological risk has the most significant and negative effect on tourists’ decisions to choose destinations [44,45,46]. Due to COVID-19, individuals have become concerned about visiting unsafe locations, which causes an increase in an individual’s perceived social-psychological risk. Such concerns may arise from the incompatibility of the destination that may be affected by others’ opinions [15]. Hence, the social-psychological risk is particularly salient, and this risk factor directly affects tourists’ hesitation.
Contrary to Chew and Jahari’s [15] findings that examined the effect of several risk factors associated with a natural disaster on tourists’ behavior, this study found that the physical risk factor impacted tourists’ hesitation. Given that physical risk indicates the likelihood of encountering physical injury or sickness in the context of tourism [15], tourists’ hesitation should be influenced by perceived physical risk.
Furthermore, Quintal, Lee, and Soutar [47] have identified that perceived risk, which includes disease risk, not only directly affects tourists’ behavior but also indirectly impacts their intention to choose destinations in a negative way. Those results suggest that perceived risk of disease is an important factor when it comes to the hesitation of water sport tourists’ in deciding whether to choose destinations.

5.1.2. Moderating Role of Destination Image

Destination image moderated the relationship between perceived risk and hesitation. However, contrary to our expectations, the findings of this research indicate that the more positive a destination’s image to a tourist, the greater their hesitation in choosing the destination, and vice versa. In general, according to research on destination image, the more positive the destination image, the more likely tourists are to choose [48,49]. Likewise, previous research on tourism has identified that destination image, including affective image and cognitive image, has a positive relationship with tourists’ behavioral intention and choice of destination [16,27,50,51]. Unlike past findings, this study’s results suggest that tourists who have a more positive destination image tend to hesitate more due to the influence of risk factors. Such results may have partly stemmed from the fact that our respondents were likely to be patrons. In fact, of all respondents, 72.4% had at least 5 years’ experience with water sport (e.g., scuba diving) and were, thus, likely familiar with the destinations. According to familiarity bias, people are biased in their judgments of objects and events depending on their familiarity with those [52]. For example, consumers are likely to favorably judge particular car models that are familiar to them when asked about which car to purchase [52]. By extension, individuals may also have more opinions about objects and places that are more familiar to them. It is, therefore, conceivable that tourists holding a more positive image of a destination are more likely to perceive risky elements and, therefore, hesitate to choose the destination to a greater degree.

5.2. Practical Implications

The importance of recognizing risk perceptions should not be understated. In the context of water sport tourism, governments need to establish an overall safety manual, including measures for facility and security inspection within the water sport areas. Due to the pandemic, various COVID-19 prevention measures and repetitive drills for prompt emergency rescue are also needed to reduce the perceived risk held by water sport tourists. At the same time, it is essential to mitigate water sport tourists’ concerns regarding COVID-19 by operating facilities by reservation only in order to manage the flow of tourists and maintain social distancing by dispersing them. Because risk factors related to infection have demonstrated a relatively high influence on tourists’ hesitation to choose destinations, maintaining preventive measures on-site may relieve their anxiety. In that sense, promoting and marketing managers should stress the safety and hygiene of tourist activities above all.
Research on sport tourism suggests the need to actively support tourists’ activities in order to overcome the crisis that the industry is facing due to the pandemic and to revitalize sport tourism for the post-pandemic era. To those ends, there is a need to preemptively strengthen water sport infrastructure and even engage in the underwater imaging of the water sport area. The paradigm of tourist content is currently in transition in accordance with changes in tourism conditions due to the pandemic and demand among tourists. For example, water sport tourists have a stronger demand for safety than in the past and that demand naturally connects with well-being and wellness tourism to drive participation in water sport. Thus, it seems that developing new tourism content based on changing paradigms (e.g., COVID-19-preventive water sport and the observance of health care protocols) can be an effective means of strengthening the image of destinations and restoring tourists’ faith in them following the pandemic.
Last, the influence of the perceived risk among water sport tourists on their hesitation to choose destinations varies depending on the macroscopic environment (e.g., political, economic, and social circumstances), the time and situation of dangerous incidents, and/or the way in which an individual interprets danger [53,54]. Thus, strategic development is required to induce positive behavior among water sport tourists based on an empirical understanding of the physical and social-psychological risk factors that could occur at water sport destinations. In particular, local governments in water sport areas should prepare practical guidelines for differentiated marketing (e.g., ensuring the impression of safety and publicizing the cleanliness of areas) and risk management policy (e.g., an industry-wide hygiene and safety certification system and mandatory quarantines) to minimize tourists’ anxiety over dangerous tourism conditions and environments and, in turn, to revitalize the market for sport tourism.

5.3. Conclusions

As the importance of understanding effective management and marketing strategies has been recognized, research pertaining to the impact of COVID-19 is inevitable. Thus, the present research explored the relationships between sport tourists’ perceived risk and hesitation, and further, the moderating effect of destination image was investigated. The above discussion explained a role in the response to COVID-19 in the interface of sport and tourism. This study identified that the delay (hesitation) occurs when sport tourists worry about risks that a tourist destination’s government and politicians may not be able to control. Moreover, sport tourists who have a more positive destination image are more likely to hesitate (due to the familiarity bias). Based on the study’s findings, it is suggested that policy-makers, local governments, and sport tourist managers should have appropriate rules, policies, and guidelines in order to reduce sport tourists’ perceptions of risk and their hesitation.

Author Contributions

Conceptualization, J.S. and M.J.; methodology, J.S. and H.Y.Y.; software, J.S.; validation, J.S. and M.J.; formal analysis, J.S.; investigation, J.S. and M.J.; resources, J.S. and M.J.; data curation, J.S.; writing—original draft preparation, K.P. and H.Y.Y.; writing—review and editing, K.P. and H.Y.Y.; visualization, K.P. and H.Y.Y.; supervision, K.P. and H.Y.Y.; project administration, J.S. and M.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Schiopu, A.F.; Hornoiu, R.I.; Padurean, M.A.; Nica, A.M. Virus tinged? Exploring the facets of virtual reality use in tourism as a result of the COVID-19 pandemic. Telemat. Inform. 2021, 60, 1–20. [Google Scholar] [CrossRef]
  2. UNWTO. Reopening Tourism for Travelers with Disabilities: How to Provide Safety without Imposing Unnecessary Obstacles. 2022. Available online: https://webunwto.s3.eu-west-1.amazonaws.com/s3fs-public/2020-08/REOPENING.pdf (accessed on 22 February 2022).
  3. Sobaih, A.E.E.; Elshaer, I.; Hasanein, A.M.; Abdelaziz, A.S. Responses to COVID-19: The role of performance in the relationship between small hospitality enterprises’ resilience and sustainable tourism development. Int. J. Hosp. Manag. 2021, 94, 1–11. [Google Scholar] [CrossRef] [PubMed]
  4. Hall, C.M.; Scott, D.; Gössling, S. Pandemics, transformations and tourism: Becareful what you wish for. Tour. Geogr. 2020, 22, 577–598. [Google Scholar] [CrossRef]
  5. Musleh, J.S.A.; Marthandan, G. The effects of risk and attitude on online shopping intention. Int. J. Manag. Res. Bus. Strategy 2014, 3, 23–39. [Google Scholar]
  6. Pappas, N. UK outbound travel and Brexit complexity. Tour. Manag. 2019, 72, 12–22. [Google Scholar] [CrossRef]
  7. Bansal, H.; Eiselt, H.A. Exploratory research of tourist motivations and planning. Tour. Manag. 2004, 25, 387–396. [Google Scholar] [CrossRef]
  8. Mayo, E.J.; Jarvis, L.P. The Psychology of Leisure Travel: Effective Marketing and Selling of Travel Services; CBI Publishing Company: Boston, MA, USA, 1981. [Google Scholar]
  9. Wong, J.Y.; Yeh, C. Tourist hesitation in destination decision making. Ann. Tour. Res. 2009, 36, 6–23. [Google Scholar] [CrossRef]
  10. Li, L.L. A study of the relationship between risk communication and tourist hesitation. Financ. Manag. Strategy 2013, 8, 23–48. [Google Scholar]
  11. Lin, J.H.; Lee, S.J.; Yeh, C.; Lee, W.H.; Wong, J.Y. Identifying gender differences in destination decision making. J. Tour. Recreat. 2014, 1, 1–11. [Google Scholar] [CrossRef] [Green Version]
  12. Kock, F.; Nørfelt, A.; Josiassen, A.; Assaf, A.G.; Tsionas, M.G. Understanding the COVID-19 tourist psyche: The evolutionary tourism paradigm. Ann. Tour. Res. 2020, 85, 1–13. [Google Scholar] [CrossRef]
  13. Brouder, P.; Teoh, S.; Salazar, N.B.; Mostafanezhad, M.; Pung, J.M.; Lapointe, D.; Desbiolles, F.H.; Haywood, M.; Hall, C.M.; Clausen, H.B. Reflections and discussions: Tourism matters in the new normal post COVID-19. Int. J. Tour. Place Space Environ. 2020, 22, 735–746. [Google Scholar] [CrossRef]
  14. Hall, C.M. Tourism Planning: Policies, Processes and Relationships; Prentice Hall: Hoboken, NJ, USA, 2000. [Google Scholar]
  15. Chew, E.Y.T.; Jahari, S.A. Destination image as a mediator between perceived risks and revisit intention: A case of post-disaster Japan. Tour. Manag. 2014, 40, 382–393. [Google Scholar] [CrossRef]
  16. Parameswaran, R.; Pisharodi, M.R. Assimilation effects in country image research. Int. Mark. Rev. 2002, 19, 259–278. [Google Scholar] [CrossRef]
  17. Yang, C.L.; Nair, V. Risk perception study in tourism: Are we really measuring perceived risk? Procedia Soc. Behav. Sci. 2014, 144, 322–327. [Google Scholar] [CrossRef] [Green Version]
  18. Lepp, A.; Gibson, H. Tourists roles, perceived risk and international tourism. Ann. Tour. Res. 2003, 30, 606–624. [Google Scholar] [CrossRef]
  19. Pinhey, T.K.; Iverson, T.J. Safety concerns of Japanese visitors to Guam. J. Travel Tour. Mark. 1994, 3, 87–94. [Google Scholar] [CrossRef]
  20. Jacoby, J.; Kaplan, B.L. The components of perceived risk. In Proceedings of the Third Annual Conference of the Association for Consumer Research, Chicago, IL, USA, 3–5 November 1972; Venkatesan, M., Ed.; Association for Consumer Research: Chicago, IL, USA; pp. 382–393. [Google Scholar]
  21. Luo, J.M.; Lam, C.F. Travel anxiety, risk attitude and travel intentions towards ’travel bubble’ destinations in Hong Kong: Effect of the fear of COVID-19. Int. J. Environ. Res. Public Health 2020, 17, 7859. [Google Scholar] [CrossRef]
  22. Moutinho, L. Consumer behaviour in tourism. Eur. J. Mark. 1987, 21, 5–44. [Google Scholar] [CrossRef]
  23. Saadat, S.; Naseripour, M.; Karbakhsh, M.; Rahimi-Movaghar, V. Perceived risk and risk-taking behavior during the festival firework. Am. J. Health Behav. 2010, 34, 525–531. [Google Scholar] [CrossRef]
  24. Pen, N.; Chen, A. Luxury hotels going green-the antecedents and consequences of consumer hesitation. J. Sustain. Tour. 2019, 27, 1374–1392. [Google Scholar]
  25. Alcañiz, E.B.; García, I.S.; Blas, S.S. The functional-psychological continuum in the cognitive image of a destination: A confirmatory analysis. Tour. Manag. 2009, 30, 715–723. [Google Scholar] [CrossRef]
  26. Pike, S.; Ryan, C. Destination positioning analysis through a comparison of cognitive, affective, and conative perceptions. J. Travel Res. 2004, 42, 333–342. [Google Scholar] [CrossRef] [Green Version]
  27. Barsky, J.D. Customer satisfaction in the hotel industry: Meaning and measurement. Hosp. Res. J. 1992, 16, 51–73. [Google Scholar] [CrossRef]
  28. Baloglu, S.; Brinberg, D. Affective images of tourism destinations. J. Travel Res. 1997, 35, 11–15. [Google Scholar] [CrossRef]
  29. Gartner, W.C. Image formation process. J. Travel Tour. Mark. 1994, 2, 191–215. [Google Scholar] [CrossRef]
  30. Baloglu, S.; McCleary, K.W. A model of destination image formation. Ann. Tour. Res. 1999, 26, 868–897. [Google Scholar] [CrossRef]
  31. Rogers, R.W. A protection motivation theory of fear appeals and attitude change. J. Psychol. 1975, 91, 93–114. [Google Scholar] [CrossRef]
  32. Chalip, L.; Green, B.C.; Hill, B. Effects of sport event media on destination image and intention to visit. J. Sport Manag. 2003, 17, 214–234. [Google Scholar] [CrossRef]
  33. Gibson, H.J.; Qi, C.X.; Zhang, J.J. Destination image and intent to visit China and the 2008 Beijing Olympic Games. J. Sport Manag. 2008, 22, 427–450. [Google Scholar] [CrossRef] [Green Version]
  34. Hallmann, K.; Feiler, S.; Breuer, C. Sport motivation as driver for segmenting sport tourists in coastal regions. Tour. Review 2012, 67, 4–12. [Google Scholar] [CrossRef]
  35. Birks, D.F.; Malhotra, N.K. Marketing Research: An Applied Approach; Pearson Education: London, UK, 2006. [Google Scholar]
  36. Anderson, J.C.; Gerbing, D.W. Structural equation modeling in practice: A review and recommended two-step approach. Psychol. Bull. 1988, 103, 411–423. [Google Scholar] [CrossRef]
  37. Hayes, A.F. Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach; Guilford Publications: New York, NY, USA, 2017. [Google Scholar]
  38. Fornell, C.; Larcker, D.F. Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 1981, 18, 39–50. [Google Scholar] [CrossRef]
  39. Hair, J.F.; Black, W.C.; Babin, B.J.; Anderson, R.E. Multivariate Data Analysis, 7th ed.; Pearson: New York, NY, USA, 2010. [Google Scholar]
  40. Bollen, K.A. A new incremental fit index for general structural equation models. Sociol. Methods Res. 1989, 17, 303–316. [Google Scholar] [CrossRef]
  41. Hu, L.T.; Bentler, P.M. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct. Equ. Model. A Multidiscip. J. 1999, 6, 1–55. [Google Scholar] [CrossRef]
  42. West, S.G.; Finch, J.F.; Curran, P.J. Structural equation models with nonnormal variables: Problems and remedies. In Structural Equation Modeling: Concepts, Issues and Applications; Hoyle, R., Ed.; Sage: Newbury Park, CA, USA, 1995; pp. 56–75. [Google Scholar]
  43. Kozak, M.; Crotts, J.C.; Law, R. The impact of the perception of risk on international travelers. Int. J. Tour. Res. 2007, 9, 233–242. [Google Scholar] [CrossRef]
  44. Floyd, M.F.; Gibson, H.; Pennington-Gray, L.; Thapa, B. The effect of risk perceptions on intentions to travel in the aftermath of September 11, 2001. J. Travel Tour. Mark. 2001, 15, 19–38. [Google Scholar] [CrossRef]
  45. Qi, C.X.; Gibson, H.J.; Zhang, J.J. Perceptions of risk and travel intentions: The case of China and the Beijing Olympic games. J. Sport Tour. 2009, 14, 43–67. [Google Scholar] [CrossRef] [Green Version]
  46. Sönmez, S.F.; Graefe, A.R. Determining future travel behavior from past travel experience and perceptions of risk and safety. J. Travel Res. 1998, 37, 171–177. [Google Scholar] [CrossRef]
  47. Quintal, V.A.; Lee, J.A.; Soutar, G.N. Risk, uncertainty and the theory of planned behavior: A tourism example. Tour. Manag. 2010, 31, 797–805. [Google Scholar] [CrossRef]
  48. Lee, W.G.; Shin, L.; Jung, C. Effect of airport service quality on destination image and tourist behavior: International airport as destination and its service as tourist experience. J. Tour. Stud. 2020, 32, 75–100. [Google Scholar] [CrossRef]
  49. Bong, M.H.; Chung, D.Y.; Seo, W. A study on the influence of cognitive image on overall image and behavioral intention: Focused on Kangwon land. Korean J. Hosp. Tour. 2018, 27, 21–38. [Google Scholar] [CrossRef]
  50. Alden, D.L.; Hoyer, W.D.; Crowley, A.E. Country of origin, perceived risk and evaluation strategy. Adv. Consum. Res. 1993, 20, 678–683. [Google Scholar]
  51. Hampton, G.M. Perceived risk in buying products made abroad by American firms. Bayl. Bus. Stud. 1977, 8, 53–64. [Google Scholar] [CrossRef]
  52. Fox, C.R.; Levav, J. Familiarity bias and belief reversal in relative likelihood judgment. Organ. Behav. Hum. Decis. Process. 2000, 82, 268–292. [Google Scholar] [CrossRef] [PubMed]
  53. Dillard, A.J.; Ferrer, R.A.; Ubel, P.A.; Fagerlin, A. Risk perception measures’ associations with behavior intentions, affect, and cognition following colon cancer screening messages. Health Psychol. 2012, 31, 106–113. [Google Scholar] [CrossRef]
  54. Gerrard, M.; Gibbons, F.X.; Houlihan, A.E.; Stock, M.L.; Pomery, E.A. A dual-process approach to health risk decision making: The prototype willingness model. Dev. Rev. 2008, 28, 29–61. [Google Scholar] [CrossRef]
Sustainability 14 04414 g001 550
Figure 1. The results of the structural model.
Figure 1. The results of the structural model.
Sustainability 14 04414 g001
Table
Table 1. Measurement properties of first-order latent constructs.
Table 1. Measurement properties of first-order latent constructs.
Construct and ItemλαC.R.AVE
Hesitation (HT) 0.8940.9140.639
HT10.773
HT20.727
HT30.810
HT40.740
HT50.737
HT60.796
Physical Risk (PR) 0.9240.9190.740
PR10.817
PR20.903
PR30.876
PR40.877
Social-Psychological Risk (SPR) 0.8630.8910.673
SPR10.856
SPR 20.757
SPR 30.680
SPR 40.839
Disease Risk (DR) 0.8490.8940.679
DR10.683
DR20.801
DR30.820
DR40.752
Destination Image (DI)
Infrastructure Image (IFI) 0.9350.9620.784
IFI_DI10.885
IFI_DI20.818
IFI_DI30.806
IFI_DI40.800
Environmental Image (EVI) 0.9350.9210.795
EVI_DI10.861
EVI _DI20.843
EVI _DI30.808
Note: λ = factor loading; α = Cronbach’s alpha; CR = composite reliability; AVE = average variance extracted.
Table
Table 2. Means, standard deviations, and bivariate correlations.
Table 2. Means, standard deviations, and bivariate correlations.
123456
1. PR1
2. DR0.332 **1
3. SPR0.366 **0.541 **1
4. HT0.419 **0.655 **0.510 **1
5. IFI−0.247 **−0.487 **−0.323 **−0.537 **1
6. EVI−0.397 **−0.405 **−0.271 **−0.423 **0.628 **1
Mean3.493.883.843.773.973.63
SD0.930.670.750.720.941.05
Note: PR = physical risk; DR = disease risk; SPR = social-psychological risk; HT = hesitation; IFI = infrastructure image; EVI = environmental image; ** p < 0.05.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Song, J.; Jung, M.; Park, K.; Yu, H.Y. Water Sport Tourists’ Hesitation in Decision-Making during the COVID-19 Pandemic: The Moderating Effect of Destination Image. Sustainability 2022, 14, 4414. https://doi.org/10.3390/su14084414

AMA Style

Song J, Jung M, Park K, Yu HY. Water Sport Tourists’ Hesitation in Decision-Making during the COVID-19 Pandemic: The Moderating Effect of Destination Image. Sustainability. 2022; 14(8):4414. https://doi.org/10.3390/su14084414

Chicago/Turabian Style

Song, Jeongmyeong, Myungkyu Jung, Kwangho Park, and Ho Yeol Yu. 2022. "Water Sport Tourists’ Hesitation in Decision-Making during the COVID-19 Pandemic: The Moderating Effect of Destination Image" Sustainability 14, no. 8: 4414. https://doi.org/10.3390/su14084414

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop