Next Article in Journal
Assessing the Efficacy of a Virtual Assistant in the Remote Cardiac Rehabilitation of Heart Failure and Ischemic Heart Disease Patients: Case-Control Study of Romanian Adult Patients
Previous Article in Journal
Modulation of Heart Rate Variability following PAP Ion Magnetic Induction Intervention in Subjects with Chronic Musculoskeletal Pain: A Pilot Randomized Controlled Study
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJERPH
Volume 20
Issue 5
10.3390/ijerph20053936
ijerph-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

Understand Delegates Risk Attitudes and Behaviour: The Moderating Effect of Trust in COVID-19 Vaccination

by
Songhong Chen
1 and
Jian Ming Luo
2,*
1
Faculty of Hospitality and Tourism Management, Macau University of Science and Technology, Macau, China
2
Faculty of International Tourism and Management, City University of Macau, Macau, China
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2023, 20(5), 3936; https://doi.org/10.3390/ijerph20053936
Submission received: 10 January 2023 / Revised: 8 February 2023 / Accepted: 17 February 2023 / Published: 22 February 2023
(This article belongs to the Section Public Health Statistics and Risk Assessment)
Browse Figure
Review Reports Versions Notes

Abstract

:
The continuing COVID-19 pandemic has prompted many people to receive the needed vaccines. However, how trust in vaccination affects the attitude and behavior of delegates attending a convention in Macau has yet to be determined. Accordingly, we applied quantitative method in conducting a survey involving 514 participants and analysed the data using AMOS and SPSS. The results showed that trust in vaccines has a significant impact on moderating the relationship between risk attitude and satisfaction. Trust in vaccines has a significant positive effect on involvement. Risk attitude negatively affects involvement, satisfaction, and loyalty. The major contribution of this research is the introduction of a model based on trust in vaccination. To boost delegates’ confidence to attend convention activities, governments and organizations should deliver accurate information on vaccines and pandemic risks, and that delegates should obtain accurate information about it. Lastly, unbiased and professional operators of the MICE industry also can offer precise COVID-19 vaccination information to reduce misperception and increase the security.

1. Introduction

Trade and associated economic activities have been negatively affected by the global healthcare and economic crisis [1]. Globally and domestically in China, the meetings, incentives, conventions, and exhibitions (MICE) industry is growing faster in the tourism area [2,3,4]. Since the severe acute respiratory syndrome coronavirus (COVID-19) outbreaks globally, quarantine regulations and border closures hit the worldwide MICE industry [5]. According to the ICCA report, there were only 4843 events of MICE in 2020, the drop rate of which was 36.55% compared to 2019. In one of the largest MICE-hosting regions, Asia, the number of events has decreased by 17.85% compared to 2019. In Macau, over 500 exhibitions and conventions have been either cancelled or postponed [6]. The total revenue of the MICE sector in Macau has decreased to MOP 14.2 million from MOP 104.7 million in 2019 [7]. In the second quarter of 2022, only 91 MICE events were held in Macau, a decrease of 56 year-on-year; excluding financial support from government or organisations, these exhibitions recorded a loss of MOP 0.81 million [8].
According to the information from the Macau government, people wishing to attend selected Macau events should have completed their two-dose vaccination and present valid certification of nucleic acid test [9]. Currently, Macau has 12 medical facilities with the capacity to offer vaccination to 5000 people on a daily basis [10]. More importantly, the safety of COVID-19 vaccination, or the trust in COVID-19 vaccination, affects delegates’ physical and psychological hopes, inspiring them and ensuring security in open areas, especially when they take part in events or fairs. The annual Macau International Trade and Investment Fair (MIF) is one of the most representative international economic and trade events [11]. However, incorrect information about COVID-19 still misleads people, making the situation worse [11]. People might consider that taking part in any public activity will be more risky and dangerous, and what kind of issues will affect peoples’ attitude and behavior is becoming an interesting academic topic. Previous research has shown that trust in COVID-19 vaccines can affect people’s behavior [12]. Gursoy utilized monthly data collected from US consumers and examined the impact of consumers’ attitudes towards COVID-19 vaccination on their intentions to travel to a destination or stay in hotels [13]. The study found that people’s health related to COVID-19 has a positive impact on their ascribed responsibility to adapt emotionally (pride, guilt). Moreover, such pro-social behaviors acting on personal norms, impacted vaccination-friendly and altruistic behavior [14].
The theory of planned behavior (TPB) is the most comprehensive theory in social psychology in determining individual behavioural intention. The theory of planned behavior (TPB) is suitable to predict and explain potential behavior associated with energy use by identifying factors that impact behavior, the purpose of which is to develop behavior change programs in the tropical climate context [15,16,17,18]. Nevertheless, knowing the definition of trust remains a dynamic process [19,20,21,22,23,24,25]. The satisfaction–loyalty theory was constructed to investigate sources of customers’ loyalty to specific services, and has been extensively adapted and applied in a large area [26]. Shinyong Jung confirmed that there was a strong relationship between attendee satisfaction and loyalty in the convention sector [27]. Jinge Yao found that the attendees’ attitudes were positively impacted by the comparative advantage, perceived safety threat, outcome expectations and trialability regarding online MICE during the COVID-19 pandemic [28]. However, what constitutes value for convention attendees and how it influences outcomes is still undiscovered [29]. Furthermore, lacking a theory of planned behavior and trust theory to analyse the intention to attend online MICE events, the accurate identification of unique factors that impact intentions in the MICE sector under COVID-19 are still uninvestigated [28]. Placing greater importance on the theory of planned behavior (TPB) offers the possibility to make further distinctions among related dispositions and other kinds of beliefs. It is open to the inclusion of additional forecasters if a significant proportion of the captured variance in intention or behavior can be shown after the theory’s current variables have been explained [16]. Trust often manifests in dyadic relationships rather than across networks [29]. In festival tourism, the festival’s activities, sales concessions, environment, socialization throughout the event, authenticity, and uniqueness contribute to creating satisfaction and loyalty [27]. In spite of the speedy development and investment in the MICE industry, identifying the unique factors that create satisfaction and loyalty in the MICE sector has become meaningful under COVID-19. From a behavioural perspective, less attention has been paid to applying TPB to evaluate individual behavior based on the individual’s trust in COVID-19 vaccination. Most importantly, how the unique factor of trust under COVID-19 affects the individuals’ behavior, attitudes, satisfaction and decision to travel is still less discussed.
With the intention of discourse on these subjects, this article constructs a theoretical model to investigate the how attendees’ trust in vaccination affects attendees’ attitudes and behaviors when taking part in MICE events under the pandemic of COVID-19. The theory of planned behavior (TPB), standard satisfaction–loyalty theory, and trust theory are presented as the conceptual framework in the study. The standard satisfaction–loyalty theory identifies the relationship between delegates’ satisfaction and loyalty, trust theory identifies the delegate’s trust in vaccination, while TPB identifies the how the delegate’s trust in vaccination and the delegate’s risk attitude affect the delegate’s involvement in MICE events.
The structure of this study is as follows: Section 2 contains a literature review describing the fundamental theories that are applied, and the hypotheses that are made. Section 3 (Methodology) explains the methodology and data collection. Section 4 (Data Analysis) defines the testing hypothesis, and Section 5 (Discussion) describes the outcomes. Lastly, Section 6 (Conclusions) reviews the contributions and limits of this study.

2. Literature Review

2.1. Theoretical Background

The theory of planned behavior (TPB) is an addition which is based on the theory of reasoned action (TRA) [30]. The TPB is a framework to understand and predict consumers’ behavior. More performance will be created by a stronger intention to engage in a behavior. The assumption is that purposes determine the motivational factors that impact behavior [16]. The TPB is the most comprehensive theory in social psychology for determining behavioural intention. In this model of TPB, three basic determinants function to decide a person’s intention: perceived behavior control (PBC), subjective norms (SN), and attitudes (ATD) [15]. The TPB offers a robust theoretical basis for examining variables other than classical variables. For example, the variable “trust” is inherent in online transactions and has been studied frequently based on the TPB model [31,32,33,34,35].
Henning-Thurau and Klee studied solving the relationship between customer satisfaction and customer loyalty. Customer loyalty of is achieved through sustained customer satisfaction, and satisfaction of customer is complemented by an emotional component to the relationship formed with the service provider that creates consistency and willingness in patronage, premium and preference [36].
Trust is a complicated factor that concerns the relationship between individuals and organizations [37]. The different definitions of trust, including a psychological state, attitude, belief, confidence, expectation, feeling, willingness, or intention, have led to numerous misunderstandings, communication breakdowns, and confusion among researchers [38,39].
Based on the three theories above, the study offers a modified theoretical model which combines TPB, satisfaction–loyalty theory, and trust theory to investigate antecedents affecting delegates’ behavior in the convention sector.

2.2. Hypothesis Construction

2.2.1. Trust

Cognitive-based trust increases when repeated interactions allow parties to understand, predict and know processes and routines of interaction [40]. Cognitive trust occurs when a conscious decision is made based on the best knowledge [41]. When the relationships are based on cognitive trust, people choose to accept evidence of trustworthiness.
Studies have considered that cognitive trust is often developed based on individuals’ proven reliability [41,42]. An example of a basis for building cognitive trust is a project manager’s ability in a client–project manager relationship. Confidence in vaccines relies on trust in many issues, such as science, the healthcare system, and the socio-political context. Trust is considered as an exchange for a reduction in decision complexity, a relationship between people and a system [43]. Given that trust also enhances science communication, enhancing general awareness of vaccines may be appropriate to control COVID-19 [40].
Degree of trust in vaccination is composed of two parts, namely, government and healthcare officials, both of which have been reported by interviewees using a five-point Likert scale (1 = Not at all, 5 = Completely) [44]. Trust is a possible factor that health officials identify as possibly reducing peoples’ perception of vaccination risks [45]. Another research indicated that due to a heterogeneous range of variables united with vaccine intention hesitancy, additional methods to resolve fears of vaccination are called for aside from campaigns of biased information. Government and health officials presenting promising approaches for controlling vaccination hesitation is a good response to affective reactions to community heads [46].

2.2.2. Risk Attitude

Human behavior is a stable psychological dimension that can be affected and predicted by attitude [47]. Risk attitude is a mindset on risk-taking behavior [48]. Under risky circumstances, people will make decisions rationally and consider risks carefully [49]. Completely avoiding risks is possible but only occasionally [49]. According to the nature of risks, people often formulate flexible or back-up plans [50]. Risk is a subjective assessment of the probability of incurring a loss [51,52].
Risk attitude was defined as consumers’ willingness to accept risks or different risk levels, and is a consistent tendency when consumers are faced with a choice [53]. Risk attitude is an intrinsic risk-selection attribute [54].

2.2.3. Involvement

An individuals’ involvement means the motivation and spirit to promote a specific object to a group of interest, such as an event [55]. Individuals’ involvement often relates to tourism sector research, among various involvement concepts [55,56]. Involvement is also defined as individual interests, needs, and values that urge people to participate in the pursuit of an object [57]. People who participate in the pursuit of special objects, such as products or services, will create an enhanced perception related to this object, thereby leading people to focus more on it. Therefore, people would often like to devote considerable time to acquire information about the product or service, thereby attracting people to buy it [58]. A consumer’s involvement relates to personal relevance; high-involvement purchases are very important for consumer products [59]. Although there are different definitions of involvement, some researchers have argued the importance of consumers relating with products or service offerings [59,60].
People who have received COVID-19 vaccines believe that they are effective and safe, particularly given that most of them even consider a third dose if it will enable them to travel. A positive relationship has been shown between the intention to receive vaccines for travel reasons and vaccine safety and effectiveness perceptions, travel intention, and taking significant precautions when traveling [61]. Hence, we formulate the hypothesis as below.
H1. 
Delegates’ trust in COVID-19 vaccines positively affects their involvement in venues.
Previous studies have explored how the COVID-19 pandemic has changed customer consumption attitudes and decision behavior based on their economic orientation [57].
H2. 
Delegates’ risk attitudes negatively affect their involvement in venues.

2.2.4. Satisfaction

Satisfaction is people’s feeling of pleasure or disappointment emerging after comparing the results of products with the expected outcome. If the outcome is below expectation, then customers’ satisfaction is considerably low. If the outcome meets their expectations, then their satisfaction is considerably high. Customers are highly satisfied and happy if outcomes exceed their expectations [62].
When performance differs from expectations, dissatisfaction results, and satisfaction represents a perceived bias, which is the difference between expectation and performance after consumption [63]. Satisfaction can also be considered as the level of people’s positive feelings about experiences [64]. In the tourism and hospitality sector, satisfaction first represents a function containing before- and after-travel experiences. Tourists are satisfied when their travelling experience outcomes are better than their expectations. However, they are dissatisfied when their travelling experience outcomes are not as good as their expectations [65]. The ordering of quality satisfaction is supported for events and festivals [66], and it has been confirmed in such fields as sports [67,68].
Previous studies have found that value and service quality perception impact satisfaction, and satisfaction impacts post-behaviors and loyalty [63,67,69,70,71,72,73,74,75]. The preceding studies have shown the contribution of satisfaction in their models. That is, attendees’ satisfaction, is a strong factor that impact attendees’ loyalty.
Research has reported that life satisfaction increased migration in OECD countries [76]. Individuals’ trust has also been reported to be an important factor because of increasing satisfaction of life in countries where they migrated [77]. Thus, the following hypothesis is formulated.
H3. 
Delegates’ trust in COVID-19 vaccines positively affects their satisfaction in venues.
Customer satisfaction and loyalty was explained by three theoretical foundations: customer involvement, satisfaction, and customer loyalty [78,79,80]. They suggested that involvement positively influences event quality perceptions and satisfaction [81]. Hence, the hypothesis is developed.
H4. 
Delegates’ involvement positively affects their satisfaction with venues.
Satisfaction is affected by attitude [82].
H5. 
Delegates’ risk attitude negatively affects their satisfaction in venues.

2.2.5. Loyalty

Loyalty represents attendees’ commitment in the convention industry and loyalty has already been expressed previously [83]. Loyal attendees create positive word-of-mouth (WOM) recommendations and revisit conventions in the future. Loyalty is also a frequently studied factor in event and tourism research that has explored the intention to take part in conferences in future, and the rate of prior attendance as two loyalty indicators [84,85,86].
Loyalty is an important factor based on measures of individuals’ attitude and behavior. A measure of individuals’ attitudes shows a unique relationship with service providers, exhibiting the idea of repeated patronage. In actual situations, actions involving individuals’ loyalty is difficult to determine, and many studies have used behavioural intentions, such as conative loyalty, to measure loyalty of action [87]. Tourists’ intentions to travel to destinations again and recommendation willingness often reflect the degree of destination loyalty [71,88].
Levels of satisfaction, evaluation of performance, and re-travel intention motivate normal involvement in the convention industry. Severt found numerous factors in examining WOM, such as satisfaction and re-travel intention following the first industry convention [89]. Severt found that attendees’ high satisfaction with experiences positively impacts their recommendation of and re-engagement with the conference [89]. Tanford explored attendees’ perspectives that impacted their loyalty to a large international convention and found that switching cost is the most significant factor that impacts the emotional commitment of attendees [90]. Locke explored the MICE literature in New Zealand using a content analysis method to develop a situational analysis framework that includes recommendation intentions, levels of satisfaction, and revisit intentions [86,91].
Trust engages the relationship between customers and service providers, particularly in terms of service quality [92]. Perceptions of government services and individual organizations will engage the attraction of tourists, including their understanding of destinations [93]. Hence, commitment, trust, and satisfaction influence tourist loyalty [94,95]. We formulate the following hypothesis based on the previous discussions.
H6. 
Delegates’ trust in COVID-19 vaccines positively affects their loyalty in venues.
Convention management studies have frequently reported the relationship between satisfaction and loyalty. From the marketing angle, attendee satisfaction is among the crucial strategies, and focusing on attendees’ requirements efficiently is important to convention industry success [89]. In most studies, attendees’ revisit intention decides their loyalty in the conventions sector [89,96], which is likewise considered attitudinal loyalty [97], behavioural intention [98], future intention [99], and willingness of stay [100]. Convention literature reviews have supported the relationship between satisfaction and loyalty. Hospitality management research has extensive documentation of the relationship between the two factors [101]. Therefore, the hypothesis is formulated [102].
H7. 
Delegates’ satisfaction positively affects their loyalty to venues.
Given that people have realized that going to public areas will increase the probability of COVID-19 infection, the pandemic has shown that the corresponding risk attitude is a significant factor that impacts clients [103]. Therefore, we formulate the following hypotheses.
H8. 
Delegates’ risk attitude negatively affects their loyalty to venues.

2.2.6. Moderator of Trust

Koller argued that trust is a function of the degree of risk inherent in a situation [104]. Trust is significantly important with the presence of two situational factors: incomplete information asymmetry of product and risk [105]. Trust is the desire and willingness to rely on other parties in risk [106]. Prior studies have shown that the relationship between the definite behavior of consumers and intention is reliable, but using some moderators can support this relationship [107,108,109]. In the MICE industry, only limited research has measured how trust in COVID-19 vaccination impacts attendees’ attitude and behavior. Hence, the following hypotheses are developed.
H9a. 
Delegates’ trust in COVID-19 vaccines moderates risk attitude and involvement.
H9b. 
Delegates’ trust in COVID-19 vaccines moderates risk attitude and satisfaction.
H9c. 
Delegates’ trust in COVID-19 vaccines moderates risk attitude and loyalty.
Based on all the hypotheses above, the model is constructed as Figure 1:

3. Methodology

Survey Design and Data Collection

In this study, we used a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree) to construct a questionnaire based on existing research. Structural equation estimation and data were measured using SPSS (IBM Corp., Armonk, NY, USA) and Smart PLS (IBM Corp., Armonk, NY, USA). The scale is described as follows (See Appendix A):
Trust in vaccines is measured by three items [110]. A sample item is “I would take a COVID-19 vaccine if it were offered to me”.
Risk attitude is measured by three items [111]. The item is “I will not consider have meals with relatives and local friends after they took part in Macau MIF”.
Involvement is measured by six items adopted from Oppermann [112]. A sample item is “I feel Macau MIF is concern to me”.
Satisfaction is measured by five items adopted from Michelini and M. del C. de Rojas and Camarero [67,113]. A sample item is as follows: “MIF is one of the best places that I could have visited”.
Loyalty is measured by four items [86]. A sample item is “I would recommend the Macau MIF to my friends”.
All questionnaire items were back-translated to Chinese. The original questionnaire was part of a pilot test prior to the revision of the actual survey. In the pilot test, 136 individuals (most were students) were invited to participate online. The targets are typical MIF attendees in Macau, and 250 surveys are distributed in filed occupations of MIF, and 263 are from the online survey. Under the normalization of COVID-19, the field investigation that was applied for MIF only approving two days on 11 and 12 December. The original surveys were about 390, and 140 contained many mistakes in the filling out. The faulty surveys were removed. The online surveys were 300 which were distributed by friends and relatives who participated the MIF at Macau. A further 37 faulty surveys were removed.

4. Data Analysis

4.1. Demographic Information

Table 1 shows the demographic information of the convention delegates. More female delegates (57.12%) than male delegates (42.88%) completed the survey. Age ranges, namely, 18–25 (34.11%) and 26–35 (32.94%), were nearly equal. In the past year, 66.08% of the delegates came to Macau less than three times. The main local delegates and those from mainland China comprised 50.88% and 48.34%, respectively.

4.2. Measurement Model

This research performed confirmatory factor analysis (CFA) using SPSS, Amos, and Smart PLS. CFA showed convergent, reliability, and discriminant validities. Cronbach’s alpha values were between 0.846 and 0.929, as shown in Table 2. This outcome approaches the minimum requirement according to [63]. The validity of convergence is acceptable. Loadings of factors are dissimilar from zero in significance, and the range is from 0.646 to 0.986.
CFA (n = 513) is for the constructed model. Normed fit index (NFI), goodness-of-fit index (GFI), adjusted goodness-of-fit index (AGFI), root mean squared error approximation (RMSEA), minimum discrepancy per degree of freedom (CMIN/DF) and comparative fit index (CFI) are standard measurements to test the fitting in CFA. According to the general standard, values below 0.01, 0.05, and 0.08 are good, mediocre fit, and perfect, respectively, for RMSEA [114]. Moreover, the model indicates a poor situation if RMSEA > 0.1. The sample data and hypothetical model show acceptable fit if CMIN/DF < 3 [115], and reasonable fit if CMIN/DF < 5 [116].
When the standard values approach the good level of fit between the testing model and the data, AGFI, GFI, NFI, and CFI follow 0.8 < AGFI < 0.9, 0.85 < GFI, NFI < 0.9, CFI > 0.9, proving that the model is acceptable [117,118,119]. Table 3 shows the values of the empirical study: RMSEA = 0.06, AGFI = 0.886, NFI = 0.936, CFI = 0.958, and CMIN/DF = 2.827. That is, model fitting is generally acceptable. The Fornell–Larcker criterion shown in Table 4 indicates that the measurement model has been confirmed as reliable and valid.
Table 5 shows the routes of each dimension. Routes analysis shows that trust in vaccines has a significant moderating effect on the relationship between risk attitude and satisfaction. Thus, H9b is supported. Trust in vaccines has a significant positive effect on involvement. Therefore, H1 is supported.
Risk attitude negatively affects involvement, satisfaction, and loyalty significantly, which separately supports hypotheses H3, H4 and H5. Involvement positively affects satisfaction significantly, which supports hypothesis H7. Satisfaction positively affects loyalty significantly, which supports hypothesis H8.

5. Discussion

The main purpose of this article was to explore the moderating effect of trust in COVID-19 vaccination on delegates’ risk attitudes and behaviour in relation to conventions.
The trust in COVID-19 vaccination moderated the relationship between risk attitude and satisfaction. However, trust in vaccination was not significant in moderating the relationship between delegates’ risk attitude and involvement in convention activities. Risk attitude was found to negatively impact delegates’ involvement, satisfaction, and loyalty in convention activities. When risk attitude increases, delegates’ involvement, satisfaction and loyalty decrease. The results support the findings of previous studies [57,82,103]. Involvement positively impacts delegates’ satisfaction. Satisfaction positively impacts delegates’ loyalty. When the level of involvement increases, the satisfaction increases, and the revisit intention increases. The results support the findings of previous studies [81,102].
The above result may be explained as below.
When people’s trust in vaccination is higher, it reduces the peoples’ risk attitude to COVID-19, and lower risk attitude also causes people to more easily experience higher satisfaction when participating in the activities. For improving participation, the organizers can arrange special convention activities for the delegates who have received COVID-19 vaccination. In actual situations, delegates’ participation would be considered more about the attitude to the COVID-19-related environment (local anti-COVID-19 policy, local government warning information) than COVID-19 vaccination propaganda. Whether or not delegates would like to participate in convention activities again depends on their attitude to the COVID-19 environment. Delegates considered more of the risk under COVID-19 environment, and they would be more careful in participating in activities. The same reason also caused delegates to have lower passion with regard to convention satisfaction and loyalty. Delegates have good experiences in participating in convention activities, thereby creating higher satisfaction with the activities and making them come back to the activities again.

5.1. Theoretical Contributions

The main contribution is the construction of a model based on trust in COVID-19 vaccination. The trust factor construct is complex and focuses on the relationship between organizations and individuals [36].
From the psychological perspective, the outcome shows how trust factor moderates individuals’ decisions to travel. This study also explored several mediators of trust in vaccination, thereby affecting other factors indirectly: risk attitudes, involvement, satisfaction, and loyalty. The outcomes indicate that peoples’ involvement is affected by trust in COVID-19 vaccination, and the other three variables are also affected by moderating trust in vaccination. Risk attitudes and trust in vaccinations are two important factors explored in this research. Exploring delegates’ behavior contributes to the tourism literature.
Lastly, Macau enjoys strategic advantages in developing the MICE industry [120]. However, most previous studies on the MICE industry have focused on self-development, convenience, personal attraction, activities and educational benefits [121], or even on technical support, cultivation and development exhibition, and developing markets [122]. Only a few studies have concentrated on trust in vaccination affecting convention development in Macau during the COVID-19 pandemic.

5.2. Practical Contributions

From a practical point of view, this study offers an empirical investigation of how trust in COVID-19 vaccination moderates delegates’ involvement, satisfaction, and loyalty via risk attitude. The findings of this study are that trust in vaccination moderates the connection between risk attitude and satisfaction, and trust in COVID-19 vaccination directly affects involvement.
Based on above, the government should offer detailed information on vaccination safety to enable people to understand; in particular, those belonging to the low-risk-tolerance group should be prioritized [123]. Social media, health information centres, and advertisements on public transportation can be channels to disseminate safety information on COVID-19 vaccination. Individuals’ perception of risk will be improved by enhancing public safety. The level of local safety will cause high exaggeration among local guides and operators. To reduce some unnecessary information on high-risk activities or attractions, they can advertise products by repackaging [124]. Meanwhile, delegates should actively obtain pandemic risk and vaccination information from other channels. Unbiased and professional operators can offer precise information to reduce misperception and increase security. The government ought to make a long-term plan for supporting the introduction or cultivation of MICE industry experts and talents [125].

6. Conclusions

Although conventions may still be limited owing to the COVID-19 pandemic, trust in vaccines appears to be an important factor to boost Macau tourism industry confidence. Unbiased and professional operators can offer precise information to reduce misperception and increase the security of the Macau MICE industry. This research focused on exploring the dimensions that could impact the involvement, satisfaction, and loyalty to the Macau convention industry. The COVID-19 pandemic has resulted in considerable fear in society. In this research, young delegates were interested in this investigation, including most of those aged 18–25 years (34.11%) and 26–35 years (32.94%). The satisfaction and loyalty relied considerably on their participation and COVID-19 risk attitude. They are active participants in convention activities, and not sensitive about COVID-19.
Trust theory, TPB, and standard satisfaction–loyalty theory provided bases for the research model used in this study. This paper hypothesized that trust in vaccination and risk attitude influence delegates’ involvement in convention venues, and also hypothesized that trust in vaccination moderates each relationship of two factors (risk attitude–involvement, risk attitude–satisfaction, risk attitude–loyalty). The outcomes show that delegates in Macau appeared to be more concerned with participation, which would influence their satisfaction of convention experience and whether or not they would come to the convention again. Trust in vaccination influences their behavior in the convention but would not influence their satisfaction and loyalty in convention activities. This research provides theoretical and practical contributions as follows.
In future study, we should investigate factors such as motivation, lifestyle, and personality. Different attitudes to participation in convention activities exist in the West and East, and performing the related comparative study would have been meaningful. Lastly, increasing the sample size should also be considered in the future for representativeness.

Author Contributions

Writing—original draft, S.C.; Writing—review and editing, J.M.L. All authors have read and agreed to the published version of the manuscript.

Funding

Research and Technology Administration Office, Macau University of Science and Technology, FRG-22-008-FHTM.

Informed Consent Statement

Not applicable.

Data Availability Statement

This research data is the first hand data which is survied from The 26th Macao International Trade and Investment Fair.

Acknowledgments

I would like to thank all the people who offered me great support for this article, especially to acknowledge Elizabeth Agyeiwaah who offered me all kinds of help in model design and data processing.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Questionnaire for the Macau MICE Industry on the Normalization of the COVID-19 Pandemic
Trust in vaccinesStrongly agreeAgreeNormalDisagreeStrongly
disagree
1. I will vaccinate the COVID-19 vaccine provided by the government.□□□□□
2. I believe the vaccine for the COVID-19 is effective.□□□□□
3. I can trust what healthcare providers tell me about the risks and benefits associated with the COVID-19.□□□□□
Risk attitudeStrongly agreeAgreeNormalDisagreeStrongly
disagree
1. With the normalization of the COVID-19, I cannot accept attending MICE events with my family.□□□□□
2. With the normalization of the COVID-19, that is not acceptable for me to attend MICE events with local friends or relatives. □□□□□
3. I cannot accept to have meals with local friends or relatives after attending MICE events under COVID-19 conditions□□□□□
InvolvementStrongly agreeAgreeNormalDisagreeStrongly
disagree
1. I consider MICE events to be relevant to me.□□□□□
2. I consider the MICE events to be good for me.□□□□□
3. I feel that the MICE events is very attractive.□□□□□
4. I consider MICE events to be very important to me.□□□□□
5. I am very interested in the MICE events.□□□□□
6. I am very excited about the MICE events.□□□□□
SatisfactionStrongly agreeAgreeNormalDisagreeStrongly
disagree
1. The MICE events venue is one of the best options I have available to visit.□□□□□
2. I would be delighted to attend the MICE events.□□□□□
3. I had a great time and had a lot of fun at the MICE events.□□□□□
4. High attendance at MICE events despite the normalization of the epidemic.□□□□□
5. I am reassured by the outbreak control measures at the MICE events.□□□□□
LoyaltyStrongly agreeAgreeNormalDisagreeStrongly
disagree
1. I would recommend my friends to attend MICE events.□□□□□
2. I will encourage my friends to attend MICE events. □□□□□
3. I will promote the positive aspects of MICE events to others.□□□□□
4. Even if there is COVID-19 epidemic, I will be happy to attend MICE events.□□□□□

References

  1. Nagurney, A. Supply Chain Game Theory Network Modeling under Labor Constraints: Applications to the Covid-19 Pandemic. Eur. J. Oper. Res. 2021, 293, 880–891. [Google Scholar] [CrossRef]
  2. He, H.; Lin, Z.; Li, H. Key Survival Factors in the Exhibition Industry. Int. J. Hosp. Manag. 2020, 89, 102561. [Google Scholar] [CrossRef]
  3. Huang, H.-C. How Does Meetings, Incentives, Conventions, and Exhibitions Industry Attract Exhibitors? Asia Pac. J. Tour. Res. 2016, 21, 73–93. [Google Scholar] [CrossRef]
  4. Kim, S.S.; Chon, K.; Chung, K.Y. Convention Industry in South Korea: An Economic Impact Analysis. Tour. Manag. 2003, 24, 533–541. [Google Scholar] [CrossRef]
  5. Bakar, N.A.; Rosbi, S. Effect of Coronavirus Disease (COVID-19) to Tourism Industry. Int. J. Adv. Eng. Res. Sci. 2020, 7, 189–193. [Google Scholar] [CrossRef] [Green Version]
  6. Wong, J.K.C. Half of Macau’s 2020 MICE Events Impacted by COVID-19; IAG: Hong Kong, China, 2020. [Google Scholar]
  7. Available online: https://www.dsec.gov.mo/en-US/ (accessed on 1 July 2022).
  8. MICE Exhibitions Lose MOP810,000 in Q2. MACAU Dly. TIMES 2022. Available online: https://macaudailytimes.com.mo/mice-exhibitions-lose-mop810000-in-q2.html#:~:text=After%20excluding%20financial%20support%20from,dropped%20by%204.0%25%20to%20306%2C000 (accessed on 1 July 2022).
  9. Government Information Bureau. Available online: https://www.gov.mo/en/entity-page/entity-51/ (accessed on 22 December 2022).
  10. COVID-19 Vaccination Programme Opens to Non-Resident Workers. Available online: https://www.gov.mo/en/news/133078/ (accessed on 22 December 2022).
  11. Weir, K. Grief and COVID-19: Mourning Our Bygone Lives; American Psychological Association: Washington, DC, USA, 2020. [Google Scholar]
  12. Han, H. The Norm Activation Model and Theory-Broadening: Individuals’ Decision-Making on Environmentally-Responsible Convention Attendance. J. Environ. Psychol. 2014, 40, 462–471. [Google Scholar] [CrossRef]
  13. Gursoy, D.; Can, A.S.; Williams, N.; Ekinci, Y. Evolving Impacts of COVID-19 Vaccination Intentions on Travel Intentions. Serv. Ind. J. 2021, 41, 719–733. [Google Scholar] [CrossRef]
  14. Radic, A.; Koo, B.; Gil-Cordero, E.; Cabrera-Sánchez, J.P.; Han, H. Intention to Take COVID-19 Vaccine as a Precondition for International Travel: Application of Extended Norm-Activation Model. Int. J. Environ. Res. Public. Health 2021, 18, 3104. [Google Scholar] [CrossRef]
  15. Ajzen, I. From Intentions to Actions: A Theory of Planned Behavior. In Action Control; Kuhl, J., Beckmann, J., Eds.; Springer: Berlin/Heidelberg, Germany, 1985; pp. 11–39. [Google Scholar] [CrossRef]
  16. Ajzen, I. The Theory of Planned Behavior. Organ. Behav. Hum. Decis. Process. 1991, 50, 179–211. [Google Scholar] [CrossRef]
  17. Ajzen, I.; Madden, T.J. Prediction of Goal-Directed Behavior: Attitudes, Intentions, and Perceived Behavioral Control. J. Exp. Soc. Psychol. 1986, 22, 453–474. [Google Scholar] [CrossRef]
  18. Obaidellah, U.H.; Danaee, M.; Mamun, M.A.A.; Hasanuzzaman, M.; Rahim, N.A. An Application of TPB Constructs on Energy-Saving Behavioural Intention among University Office Building Occupants: A Pilot Study in Malaysian Tropical Climate. J. Hous. Built Environ. 2019, 34, 533–569. [Google Scholar] [CrossRef]
  19. Audrey Korsgaard, M.; Kautz, J.; Bliese, P.; Samson, K.; Kostyszyn, P. Conceptualising Time as a Level of Analysis: New Directions in the Analysis of Trust Dynamics. J. Trust Res. 2018, 8, 142–165. [Google Scholar] [CrossRef]
  20. Castaldo, S.; Premazzi, K.; Zerbini, F. The Meaning(s) of Trust. A Content Analysis on the Diverse Conceptualizations of Trust in Scholarly Research on Business Relationships. J. Bus. Ethics 2010, 96, 657–668. [Google Scholar] [CrossRef]
  21. Geiger, J.L.; Steg, L.; van der Werff, E.; Ünal, A.B. A Meta-Analysis of Factors Related to Recycling. J. Environ. Psychol. 2019, 64, 78–97. [Google Scholar] [CrossRef]
  22. Isaeva, N.; Gruenewald, K.; Saunders, M.N.K. Trust Theory and Customer Services Research: Theoretical Review and Synthesis. Serv. Ind. J. 2020, 40, 1031–1063. [Google Scholar] [CrossRef]
  23. Lewis, J.D.; Weigert, A.J. The Social Dynamics of Trust: Theoretical and Empirical Research, 1985–2012. Soc. Forces 2012, 91, 25–31. [Google Scholar] [CrossRef] [Green Version]
  24. Mayer, R.C.; Davis, J.H.; Schoorman, F.D. An Integrative Model Of Organizational Trust. Acad. Manage. Rev. 1995, 20, 709–734. [Google Scholar] [CrossRef]
  25. Rousseau, D.M.; Sitkin, S.B.; Burt, R.S.; Camerer, C. Not So Different After All: A Cross-Discipline View Of Trust. Acad. Manag. Rev. 1998, 23, 393–404. [Google Scholar] [CrossRef] [Green Version]
  26. Jen, W.; Tu, R.; Lu, T. Managing Passenger Behavioral Intention: An Integrated Framework for Service Quality, Satisfaction, Perceived Value, and Switching Barriers. Transportation 2011, 38, 321–342. [Google Scholar] [CrossRef]
  27. Tanford, S.; Jung, S. Festival Attributes and Perceptions: A Meta-Analysis of Relationships with Satisfaction and Loyalty. Tour. Manag. 2017, 61, 209–220. [Google Scholar] [CrossRef]
  28. Yao, J.; Pang, Q.; Zhang, B.; Wang, L.; Huang, Y. Public Health and Online MICE Technology During the COVID-19 Pandemic: The Role of Health Beliefs and Technology Innovation. Front. Public Health 2021, 9, 756987. [Google Scholar] [CrossRef]
  29. McGregor, A.; Robinson, R.N.S. Wine Industry and Wine Tourism Industry Collaboration: A Typology and Analysis. In Wine Tourism Destination Management and Marketing; Palgrave Macmillan: Cham, Switzerland, 2019; pp. 381–397. [Google Scholar] [CrossRef]
  30. Fishbein, M.; Ajzen, I. Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Philos. Rhetor. 1977, 6, 244–245. [Google Scholar] [CrossRef]
  31. Dennis, C.; Merrilees, B.; Jayawardhena, C.; Tiu Wright, L. E-consumer Behaviour. Eur. J. Mark. 2009, 43, 1121–1139. [Google Scholar] [CrossRef] [Green Version]
  32. George, J.F. The Theory of Planned Behavior and Internet Purchasing. Internet Res. 2004, 14, 198–212. [Google Scholar] [CrossRef] [Green Version]
  33. Kamarulzaman, Y. Adoption of Travel E-shopping in the UK. Int. J. Retail Distrib. Manag. 2007, 35, 703–719. [Google Scholar] [CrossRef] [Green Version]
  34. Pavlou, P.A. What Drives Electronic Commerce? A Theory of Planned Behavior Perspective. Acad. Manag. Proc. 2002, 2002, A1–A6. [Google Scholar] [CrossRef]
  35. Wen, I. Factors Affecting the Online Travel Buying Decision: A Review. Int. J. Contemp. Hosp. Manag. 2009, 21, 752–765. [Google Scholar] [CrossRef]
  36. Vallerand, R.; Deshaies, P.; Cuerrier, J.-P.; Pelletier, L.; Mongeau, C. Ajzen and Fishbein’s Theory of Reasoned Action as Applied to Moral Behavior: A Confirmatory Analysis. J. Pers. Soc. Psychol. 1992, 62, 98–109. [Google Scholar] [CrossRef]
  37. Fulmer, A.; Dirks, K. Multilevel Trust: A Theoretical and Practical Imperative. J. Trust Res. 2018, 8, 137–141. [Google Scholar] [CrossRef]
  38. Harrison McKnight, D.; Chervany, N.L. Trust and Distrust Definitions: One Bite at a Time. In Trust in Cyber-societies; Springer: Berlin/Heidelberg, Germany, 2001; pp. 27–54. [Google Scholar] [CrossRef]
  39. Khodyakov, D. Trust as a Process: A Three-Dimensional Approach. Sociol.-J. Br. Sociol. Assoc.-Sociol. 2007, 41, 115–132. [Google Scholar] [CrossRef]
  40. Rzymski, P.; Zeyland, J.; Poniedziałek, B.; Małecka, I.; Wysocki, J. The Perception and Attitudes toward COVID-19 Vaccines: A Cross-Sectional Study in Poland. Vaccines 2021, 9, 382. [Google Scholar] [CrossRef]
  41. McAllister, D.J. Affect- and Cognition-Based Trust as Foundations for Interpersonal Cooperation in Organizations. Acad. Manag. J. 1995, 38, 24–59. [Google Scholar] [CrossRef]
  42. Lewis, J.D.; Weigert, A. Trust as a Social Reality. Soc. Forces 1985, 63, 967–985. [Google Scholar] [CrossRef]
  43. Larson, H.J.; Clarke, R.M.; Jarrett, C.; Eckersberger, E.; Levine, Z.; Schulz, W.S.; Paterson, P. Measuring Trust in Vaccination: A Systematic Review. Hum. Vaccines Immunother. 2018, 14, 1599–1609. [Google Scholar] [CrossRef] [Green Version]
  44. Sturgis, P.; Brunton-Smith, I.; Jackson, J. Trust in Science, Social Consensus and Vaccine Confidence. Nat. Hum. Behav. 2021, 5, 1528–1534. [Google Scholar] [CrossRef]
  45. Marlow, L.A.V.; Waller, J.; Wardle, J. Trust and Experience as Predictors of HPV Vaccine Acceptance. Hum. Vaccin. 2007, 3, 171–175. [Google Scholar] [CrossRef] [Green Version]
  46. Ebrahimi, O.V.; Johnson, M.S.; Ebling, S.; Amundsen, O.M.; Halsøy, Ø.; Hoffart, A.; Skjerdingstad, N.; Johnson, S.U. Risk, Trust, and Flawed Assumptions: Vaccine Hesitancy During the COVID-19 Pandemic. Front. Public Health 2021, 9, 700213. [Google Scholar] [CrossRef]
  47. Ajzen, I.; Gilbert Cote, N. Attitudes and the Prediction of Behavior. In Attitudes and Persuasion; Psychology Press: New York, NY, USA, 2008; pp. 289–311. [Google Scholar]
  48. Hillson, D.; Murray-Webster, R. Understanding and Managing Risk Attitude; Routledge: England, UK, 2017; ISBN 978-1-315-23544-8. [Google Scholar]
  49. Maser, B.; Weiermair, K. Travel Decision-Making: From the Vantage Point of Perceived Risk and Information Preferences. J. Travel Tour. Mark. 1998, 7, 107–121. [Google Scholar] [CrossRef]
  50. Kozak, M.; Crotts, J.C.; Law, R. The Impact of the Perception of Risk on International Travellers. Int. J. Tour. Res. 2007, 9, 233–242. [Google Scholar] [CrossRef]
  51. Lu, H.; Hsu, C.; Hsu, H. An Empirical Study of the Effect of Perceived Risk upon Intention to Use Online Applications. Inf. Manag. Comput. Secur. 2005, 13, 106–120. [Google Scholar] [CrossRef]
  52. Pires, G.; Stanton, J.; Eckford, A. Influences on the Perceived Risk of Purchasing Online. J. Consum. Behav. 2004, 4, 118–131. [Google Scholar] [CrossRef]
  53. Schroeder, T.C.; Tonsor, G.T.; Pennings, J.M.E.; Mintert, J. Consumer Food Safety Risk Perceptions and Attitudes: Impacts on Beef Consumption across Countries. BE J. Econ. Anal. Policy 2007, 7, 1–29. [Google Scholar] [CrossRef] [Green Version]
  54. Weber, E.U.; Blais, A.-R.; Betz, N.E. A Domain-Specific Risk-Attitude Scale: Measuring Risk Perceptions and Risk Behaviors. J. Behav. Decis. Mak. 2002, 15, 263–290. [Google Scholar] [CrossRef]
  55. Havitz, M.E.; Dimanche, F. Leisure Involvement Revisited: Conceptual Conundrums and Measurement Advances. J. Leis. Res. 1997, 29, 245–278. [Google Scholar] [CrossRef]
  56. Prayag, G.; Ryan, C. Antecedents of Tourists’ Loyalty to Mauritius: The Role and Influence of Destination Image, Place Attachment, Personal Involvement, and Satisfaction. J. Travel Res. 2012, 51, 342–356. [Google Scholar] [CrossRef]
  57. Zaichkowsky, J.L. Measuring the Involvement Construct. J. Consum. Res. 1985, 12, 341–352. [Google Scholar] [CrossRef]
  58. Beatty, S.E.; Smith, S.M. External Search Effort: An Investigation Across Several Product Categories. J. Consum. Res. 1987, 14, 83–95. [Google Scholar] [CrossRef]
  59. Schiffman, L.G.; Kanuk, L.L. Consumer Behavior, 8th ed.; Prentice-Hall: Hoboken, NJ, USA, 2004. [Google Scholar]
  60. Bloch, P.H.; Richins, M.L. A Theoretical Model for the Study of Product Importance Perceptions. J. Mark. 1983, 47, 69–81. [Google Scholar] [CrossRef]
  61. Morar, C.; Tiba, A.; Jovanovic, T.; Valjarević, A.; Ripp, M.; Vujičić, M.D.; Stankov, U.; Basarin, B.; Ratković, R.; Popović, M.; et al. Supporting Tourism by Assessing the Predictors of COVID-19 Vaccination for Travel Reasons. Int. J. Environ. Res. Public. Health 2022, 19, 918. [Google Scholar] [CrossRef]
  62. Armstrong, G.; Kotler, P.; Harker, M.; Brennan, R. Marketing an Introduction, 1st ed.; Prentice Hall: Hoboken, NJ, USA, 2009. [Google Scholar]
  63. Oliver, R.L. A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions: A Suggested Framework and Research Propositions. J. Mark. Res. 1980, 17, 460–469. [Google Scholar] [CrossRef]
  64. Rust, R.T.; Oliver, R.L. (Eds.) Service Quality: New Directions in Theory and Practice; Sage Publications: Thousand Oaks, CA, USA, 1994; ISBN 978-0-8039-4919-5. [Google Scholar]
  65. Long, P. Cross-Cultural Behaviour in Tourism: Concepts and Analysis, by Y. Reisinger and L. W. Turner. Butterworth Heinemann, Oxford, 2003. No. of Pages: 337. ISBN 0-7506-56689. Int. J. Tour. Res. 2003, 6, 54. [Google Scholar] [CrossRef]
  66. Baker, D.A.; Crompton, J.L. Quality, Satisfaction and Behavioral Intentions. Ann. Tour. Res. 2000, 27, 785–804. [Google Scholar] [CrossRef]
  67. De Rojas, C.; Camarero, C. Visitors’ Experience, Mood and Satisfaction in a Heritage Context: Evidence from an Interpretation Center. Tour. Manag. 2008, 29, 525–537. [Google Scholar] [CrossRef]
  68. Murray, D.; Howat, G. The Relationships among Service Quality, Value, Satisfaction, and Future Intentions of Customers at an Australian Sports and Leisure Centre. Sport Manag. Rev. 2002, 5, 25–43. [Google Scholar] [CrossRef]
  69. Bigné, J.E.; Sánchez, M.I.; Sánchez, J. Tourism Image, Evaluation Variables and after Purchase Behaviour: Inter-Relationship. Tour. Manag. 2001, 22, 607–616. [Google Scholar] [CrossRef]
  70. Chen, C.-F. Investigating Structural Relationships between Service Quality, Perceived Value, Satisfaction, and Behavioral Intentions for Air Passengers: Evidence from Taiwan. Transp. Res. Part Policy Pract. 2008, 42, 709–717. [Google Scholar] [CrossRef]
  71. Chen, C.-F.; Tsai, D. How Destination Image and Evaluative Factors Affect Behavioral Intentions? Tour. Manag. 2007, 28, 1115–1122. [Google Scholar] [CrossRef]
  72. Choi, T.Y.; Chu, R. Determinants of Hotel Guests’ Satisfaction and Repeat Patronage in the Hong Kong Hotel Industry. Int. J. Hosp. Manag. 2001, 20, 277–297. [Google Scholar] [CrossRef]
  73. Cronin, J.J., Jr.; Taylor, S.A. Measuring Service Quality—A Reexamination And Extension. J. Mark. 1992, 56, 55–68. [Google Scholar] [CrossRef]
  74. Petrick, J.F.; Backman, S.J. An Examination of the Construct of Perceived Value for the Prediction of Golf Travelers’ Intentions to Revisit. J. Travel Res. 2002, 41, 38–45. [Google Scholar] [CrossRef]
  75. Tarn, J.L.M. The Effects of Service Quality, Perceived Value and Customer Satisfaction on Behavioral Intentions. J. Hosp. Leis. Mark. 1999, 6, 31–43. [Google Scholar] [CrossRef]
  76. Helliwell, J.F.; Huang, H. New Measures of the Costs of Unemployment: Evidence from the Subjective Well-Being of 3.3 Million Americans. Econ. Inq. 2014, 52, 1485–1502. [Google Scholar] [CrossRef] [Green Version]
  77. Habibov, N.; Afandi, E. Pre- and Post-Crisis Life-Satisfaction and Social Trust in Transitional Countries: An Initial Assessment. Soc. Indic. Res. 2015, 121, 503–524. [Google Scholar] [CrossRef] [Green Version]
  78. Brown, J.J.; Reingen, P.H. Social Ties and Word-of-Mouth Referral Behavior. J. Consum. Res. 1987, 14, 350–362. [Google Scholar] [CrossRef]
  79. Skogland, I.; Siguaw, J. Are Your Satisfied Customers Loyal? Cornell Hotel Restaur. Adm. Q. 2004, 45, 221–234. [Google Scholar] [CrossRef]
  80. Kim, Y.-S.; Lee, Y.-Y.; Love, C. A Case Study Examining the Influence of Conference Food Function on Attendee Satisfaction and Return Intention at a Corporate Conference. J. Conv. Event Tour. 2009, 10, 211–230. [Google Scholar] [CrossRef] [Green Version]
  81. Jae Ko, Y.; Kyoum Kim, Y.; Kil Kim, M.; Hak Lee, J. The Role of Involvement and Identification on Event Quality Perceptions and Satisfaction: A Case of US Taekwondo Open. Asia Pac. J. Mark. Logist. 2010, 22, 25–39. [Google Scholar] [CrossRef]
  82. Chon, K. Understanding Recreational Traveler’s Motivation, Attitude and Satisfaction. Tour. Rev. 1989, 44, 3–7. [Google Scholar] [CrossRef]
  83. Tanford, S.; Raab, C.; Kim, Y.-S. Determinants of Customer Loyalty and Purchasing Behavior for Full-Service and Limited-Service Hotels. Int. J. Hosp. Manag. 2012, 31, 319–328. [Google Scholar] [CrossRef]
  84. Mair, J.; Thompson, K. The UK Association Conference Attendance Decision-Making Process. Tour. Manag. 2009, 30, 400–409. [Google Scholar] [CrossRef] [Green Version]
  85. Yoo, J.J.-E.; Chon, K. Temporal Changes in Factors Affecting Convention Participation Decision. Int. J. Contemp. Hosp. Manag. 2010, 22, 103–120. [Google Scholar] [CrossRef]
  86. Kim, W.; Malek, K. Understanding the Relationship among Motivation to Attend, Satisfaction, and Loyalty of Medical Convention Attendees. J. Conv. Event Tour. 2017, 18, 282–300. [Google Scholar] [CrossRef]
  87. Yang, Z.; Peterson, R.T. Customer Perceived Value, Satisfaction, and Loyalty: The Role of Switching Costs. Psychol. Mark. 2004, 21, 799–822. [Google Scholar] [CrossRef] [Green Version]
  88. Oppermann, M. Tourism Destination Loyalty. J. Travel Res. 2000, 39, 78–84. [Google Scholar] [CrossRef]
  89. Severt, D.; Wang, Y.; Chen, P.-J.; Breiter, D. Examining the Motivation, Perceived Performance, and Behavioral Intentions of Convention Attendees: Evidence from a Regional Conference. Tour. Manag. 2007, 28, 399–408. [Google Scholar] [CrossRef]
  90. Tanford, S.; Montgomery, R.; Nelson, K.B. Factors That Influence Attendance, Satisfaction, and Loyalty for Conventions. J. Conv. Event Tour. 2012, 13, 290–318. [Google Scholar] [CrossRef]
  91. Locke, M. A Framework for Conducting a Situational Analysis of the Meetings, Incentives, Conventions, and Exhibitions Sector. J. Conv. Event Tour. 2010, 11, 209–233. [Google Scholar] [CrossRef]
  92. Rauyruen, P.; Miller, K.E. Relationship Quality as a Predictor of B2B Customer Loyalty. J. Bus. Res. 2007, 60, 21–31. [Google Scholar] [CrossRef]
  93. Marinao Artigas, E.; Yrigoyen, C.C.; Moraga, E.T.; Villalón, C.B. Determinants of Trust towards Tourist Destinations. J. Destin. Mark. Manag. 2017, 6, 327–334. [Google Scholar] [CrossRef]
  94. Cheunkamon, E.; Jomnonkwao, S.; Ratanavaraha, V. Impacts of Tourist Loyalty on Service Providers: Examining the Role of the Service Quality of Tourism Supply Chains, Tourism Logistics, Commitment, Satisfaction, and Trust. J. Qual. Assur. Hosp. Tour. 2021, 23, 1397–1429. [Google Scholar] [CrossRef]
  95. Nadeem, S.R. Does Emotional Intelligence Matters? The Study of Emotional Intelligence and Its Implications on Job Satisfaction, Job Performance and Work Engagement of Employees in Pakistan. Middle East J. Appl. Sci. Technol. 2020, 3, 35–48. [Google Scholar]
  96. Sangpikul, A.; Kim (Samuel), S. An Overview and Identification of Barriers Affecting the Meeting and Convention Industry in Thailand. J. Conv. Event Tour. 2009, 10, 185–210. [Google Scholar] [CrossRef]
  97. Lu, Y.; Cai, L. Analysis of Image and Loyalty for Exhibitions and Host Destinations. In Proceedings of the 2009 ICHRIE Conference, San Francisco, CA, USA, 29 July–1 August 2009. [Google Scholar]
  98. Jago, L.K.; Deery, M. Relationships and Factors Influencing Convention Decision-Making. J. Conv. Event Tour. 2005, 7, 23–41. [Google Scholar] [CrossRef]
  99. Hahm, J.; Breiter, D.; Severt, K.; Wang, Y.; Fjelstul, J. The Relationship between Sense of Community and Satisfaction on Future Intentions to Attend an Association’s Annual Meeting. Tour. Manag. 2016, 52, 151–160. [Google Scholar] [CrossRef]
  100. Siu, N.; Wan, P.; Dong, P. The Impact of the Servicescape on the Desire to Stay in Convention and Exhibition Centers: The Case of Macao. Int. J. Hosp. Manag. 2012, 31, 236–246. [Google Scholar] [CrossRef]
  101. Tanford, S. Antecedents and Outcomes of Hospitality Loyalty: A Meta-Analysis. Cornell Hosp. Q. 2016, 57, 122–137. [Google Scholar] [CrossRef]
  102. Jung, S.; Tanford, S. What Contributes to Convention Attendee Satisfaction and Loyalty? A Meta-Analysis. J. Conv. Event Tour. 2017, 18, 118–134. [Google Scholar] [CrossRef]
  103. Orden-Mejía, M.; Carvache-Franco, M.; Huertas, A.; Carvache-Franco, W.; Landeta-Bejarano, N.; Carvache-Franco, O. Post-COVID-19 Tourists’ Preferences, Attitudes and Travel Expectations: A Study in Guayaquil, Ecuador. Int. J. Environ. Res. Public. Health 2022, 19, 4822. [Google Scholar] [CrossRef]
  104. Kotler, P.; Keller, K.L. Marketing Management, 15 ed.; Pearson Education: New York, NY, USA, 2015. [Google Scholar]
  105. Ba, S.; Pavlou, P.A. Evidence of the Effect of Trust Building Technology in Electronic Markets: Price Premiums and Buyer Behavior. MIS Q. 2002, 26, 243–268. [Google Scholar] [CrossRef] [Green Version]
  106. Rahmi, D.T.; Nizam, A. Pengaruh citra merek terhadap niat pembelian tiket pesawat secara online pada konsumen traveloka.com dengan kepercayaan sebagai variabel mediasi. J. Ilm. Mhs. Ekon. Manaj. 2017, 2, 70–85. [Google Scholar] [CrossRef]
  107. Elliott, M.A.; Armitage, C.J.; Baughan, C.J. Drivers’ Compliance with Speed Limits: An Application of the Theory of Planned Behavior. J. Appl. Psychol. 2003, 88, 964–972. [Google Scholar] [CrossRef] [Green Version]
  108. Hagger, M.; Chatzisarantis, N.; Biddle, S. A Meta-Analytic Review of the Theories of Reasoned Action and Planned Behavior in Physical Activity: Predictive Validity and the Contribution of Additional Variables. J. Sport Exerc. Psychol. 2002, 24, 3–32. [Google Scholar] [CrossRef]
  109. Rehman, S.U.; Bhatti, A.; Mohamed, R.; Ayoup, H. The Moderating Role of Trust and Commitment between Consumer Purchase Intention and Online Shopping Behavior in the Context of Pakistan. J. Glob. Entrep. Res. 2019, 9, 43. [Google Scholar] [CrossRef] [Green Version]
  110. Cobos Muñoz, D.; Monzón Llamas, L.; Bosch-Capblanch, X. Exposing Concerns about Vaccination in Low- and Middle-Income Countries: A Systematic Review. Int. J. Public Health 2015, 60, 767–780. [Google Scholar] [CrossRef] [Green Version]
  111. Zhu, H.; Deng, F. How to Influence Rural Tourism Intention by Risk Knowledge during COVID-19 Containment in China: Mediating Role of Risk Perception and Attitude. Int. J. Environ. Res. Public. Health 2020, 17, 3514. [Google Scholar] [CrossRef]
  112. Oppermann, M. Association Involvement and Convention Participation. J. Hosp. Tour. Res. 1998, 21, 17–30. [Google Scholar] [CrossRef]
  113. Michelini, L.; Iasevoli, G.; Theodoraki, E. Event Venue Satisfaction and Its Impact On Sponsorship Outcomes. Event Manag. 2017, 21, 319–331. [Google Scholar] [CrossRef] [Green Version]
  114. MacCallum, R.C.; Browne, M.W.; Sugawara, H.M. Power Analysis and Determination of Sample Size for Covariance Structure Modeling. Psychol. Methods 1996, 1, 130–149. [Google Scholar] [CrossRef]
  115. Kline, R. Principles and Practice of Structural Equation Modeling, 4th ed.; The Guilford Press: New York, NY, USA, 2018. [Google Scholar]
  116. Marsh, H.W.; Hocevar, D. Application of Confirmatory Factor Analysis to the Study of Self-Concept: First- and Higher Order Factor Models and Their Invariance across Groups. Psychol. Bull. 1985, 97, 562–582. [Google Scholar] [CrossRef]
  117. Bentler, P.M. Comparative Fit Indexes in Structural Models. Psychol. Bull. 1990, 107, 238–246. [Google Scholar] [CrossRef]
  118. Cole, D.A. Utility of Confirmatory Factor Analysis in Test Validation Research. J. Consult. Clin. Psychol. 1987, 55, 584–594. [Google Scholar] [CrossRef]
  119. Marsh, H.W.; Balla, J.R.; McDonald, R.P. Goodness-of-Fit Indexes in Confirmatory Factor Analysis: The Effect of Sample Size. Psychol. Bull. 1988, 103, 391–410. [Google Scholar] [CrossRef]
  120. Tingyue, K. A Study of Evaluation of Two-Dimensional Quality Elements of Convention Tourism Based on Kano Model-A Case Study on Macao. E3S Web Conf. 2021, 251, 03012. [Google Scholar] [CrossRef]
  121. Zhang, T. A Study on Motivation of Meeting and Exhibition Attendees in Macao. In Proceedings of the 2010 International Conference on Management and Service Science, Wuhan, China, 24–26 August 2010; pp. 1–4. [Google Scholar]
  122. Lu, P. Study on the Moderate Diversification of Industrial Structure in Macao. Am. J. Ind. Bus. Manag. 2016, 6, 176. [Google Scholar] [CrossRef] [Green Version]
  123. 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]
  124. Reisinger, Y. Travel Anxiety and Intentions to Travel Internationally: Implications of Travel Risk Perception. J. Travel Res. 2005, 43, 212–225. [Google Scholar] [CrossRef]
  125. Chen, S.; Luo, J.M. Assessing Barriers to the Development of Convention Tourism in Macau. Cogent Soc. Sci. 2021, 7, 1928978. [Google Scholar] [CrossRef]
Ijerph 20 03936 g001 550
Figure 1. The Research Model.
Figure 1. The Research Model.
Ijerph 20 03936 g001
Table
Table 1. Demographic Profile of Visitor.
Table 1. Demographic Profile of Visitor.
Variable Frequency (n = 513)Percentage (%)
Gender Male22042.88
Female29357.12
Age 18–2517534.11
26–3516932.94
36–458616.76
46–55499.55
above 56346.63
Visit times in past 1 year less 3 times33966.08
3–5 times17433.92
From Macau26150.88
Hongkong40.78
Mainland China24848.34
Table
Table 2. Reliability, CR, and AVE.
Table 2. Reliability, CR, and AVE.
VariableItemFactor LoadingCronbach’s AlphaComponent Reliability (CR)Average Variance Extracted (AVE)
Trust of VaccinesI would take a COVID19 vaccine if it were offered to me0.6510.860.8660.689
I believe it works 0.819
I believe healthcare provider about the risks and benefits with coronavirus vaccines0.986
Risk AttitudeUnder the normal circumstances of the epidemic, I cannot accept participating in exhibition activities with my family0.9320.9290.9550.875
Under the normal circumstances of the epidemic, I cannot accept participating in exhibition activities with local friends or relatives0.950
After participating in exhibition activities, I cannot accept dining with local friends or relatives0.925
InvolvementI feel the MIF is concern to me0.6600.9030.9250.676
The MIF activity is beneficial to me0.802
The MIF activity is appealing to me 0.848
It is very significant to me0.875
I am very interested in MIF activity0.875
I feel exciting in MIF activity0.852
SatisfactionMICE venues are one of the best options I can visit0.8040.8460.8910.625
I am very happy to be able to participate in the exhibition activities0.887
I had a good time and had a lot of fun at the exhibition0.875
Under the normalization of the epidemic, many people still participate in exhibition activities0.646
I am very reassured by the measures to control the epidemic during the exhibition activities0.713
LoyaltyI will recommend my friends to participate in exhibition activities0.9190.9030.9330.777
I will encourage my friends to participate in exhibition activities0.919
I will promote the positive meaning of the exhibition to others0.867
Even if there is an epidemic, I am happy to participate in exhibition activities0.816
Table
Table 3. CFA standard values.
Table 3. CFA standard values.
ModelRMSEACFIAGFIGFIAGFICMIN/DF
Default model0.060.9580.8860.9130.8862.827
Saturated model 1 1
Independence model0.26700.1530.230.15337.508
Table
Table 4. Fornell-Larcker criterion.
Table 4. Fornell-Larcker criterion.
Trust of VaccinesRisk AttitudeInvolvement SatisfactionLoyalty
Trust in Vaccines0.83
Risk Attitude0.1810.935
Involvement0.067−0.0450.822
Satisfaction0.052−1.560.7330.791
Loyalty0.01−0.2640.6410.7830.881
Table
Table 5. Route Analysis.
Table 5. Route Analysis.
Initiative Sample (O)Mean of Sample (M)Standard Deviation (STDEV)t-Test (O/STDEV)p Value
Involvement-> Satisfaction0.7430.7430.02332.2420.000
Risk Attitude-> Involvement−0.100−0.0990.0482.0930.036
Risk Attitude->Loyalty−0.155−0.1570.0315.0680.000
Risk Attitude-> Satisfaction−0.106−0.1070.0333.2670.001
Satisfaction->Loyalty0.7250.7250.02826.1690.000
Trust of Vaccines -> Involvement0.1520.1540.0652.3440.019
Trust Of Vaccines ->Loyalty−0.013−0.0120.0320.3910.696
Trust of Vaccines -> Satisfaction0.0130.0170.0350.3820.702
Moderator a-> Involvement−0.005−0.0020.0490.1030.918
Moderator b -> Satisfaction0.0700.0670.0332.1040.035
Moderator c ->Loyalty0.0510.0480.0321.5810.114
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Chen, S.; Luo, J.M. Understand Delegates Risk Attitudes and Behaviour: The Moderating Effect of Trust in COVID-19 Vaccination. Int. J. Environ. Res. Public Health 2023, 20, 3936. https://doi.org/10.3390/ijerph20053936

AMA Style

Chen S, Luo JM. Understand Delegates Risk Attitudes and Behaviour: The Moderating Effect of Trust in COVID-19 Vaccination. International Journal of Environmental Research and Public Health. 2023; 20(5):3936. https://doi.org/10.3390/ijerph20053936

Chicago/Turabian Style

Chen, Songhong, and Jian Ming Luo. 2023. "Understand Delegates Risk Attitudes and Behaviour: The Moderating Effect of Trust in COVID-19 Vaccination" International Journal of Environmental Research and Public Health 20, no. 5: 3936. https://doi.org/10.3390/ijerph20053936

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