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https://doi.org/10.20867/thm.27.1.7

THE EFFECT OF THE CONVENTION SPECIFIC DIMENSIONS ON UNIVERSITIES TEACHING STAFF BEHAVIORAL INTENTION

Daniela Gračan orcid id orcid.org/0000-0002-3847-7280 ; University of Rijeka, Faculty of Tourism and Hospitality Management Department of Tourism
Marina Barkiđija Sotošek orcid id orcid.org/0000-0003-2642-3960 ; University of Rijeka, Faculty of Tourism and Hospitality Management Department of Tourism
Matia Torbarina orcid id orcid.org/0000-0001-5756-7292 ; University of Rijeka, Faculty of Economics and Business Department of Marketing


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Sažetak

Purpose – The aim of this paper is to assess the influence of participation frequency at
the conventions on universities teaching staff’s behavioral intentions.
Design –The convention tourism attendees’ behavioral intentions evaluation was conducted
through the constructs of site-specific dimensions and convention-specific dimensions.
Methodology – In order to test proposed hypotheses, following establishment of
measurement invariance across groups, structural equation model was fitted to both groups
of participants.
Approach – The online questionnaire was conducted among the teaching staff of all
universities in the Republic of Croatia. The final sample consisted of 978 correctly
completed questionnaires.
Findings – Two groups differ in the effect of accessibility. It does not predict
behavioral intentions for those that visit one convention per year while it predicts
behavioral intentions of the attendees that visit more than one convention per year. Both
groups’ behavioral intentions are predicted by their rating of conventions’ social
networking and professional education opportunities.
Originality of the research – The research findings will help the convention organizers
to better understand the needs of both groups’ participants and thereby to encourage their
repeated participation and dissemination of positive recommendations.

Ključne riječi

Convention tourism; Participation frequency; Site-specific dimensions; Convention-specific dimensions; Behavioral intentions; Structural equation modeling

Hrčak ID:

253565

URI

https://hrcak.srce.hr/253565

Datum izdavanja:

3.5.2021.

Posjeta: 1.020 *




INTRODUCTION

Whilst tourism impacts from staging business events may be important, they are peripheral to the core outcomes that are being sought. In addition to financial income, according A Modern History of International Association Meetings – Update 1963-2017 (ICCA 2018, 49), there are a diverse range of outcomes and tourism impacts of the business event that are produced like: knowledge creation/innovation, knowledge dissemination, improved organization performance, personal development, increased productivity, increased sales, new skills and knowledge, awareness, investment in destination, business development in destination, enhanced destination profile/image. It can be concluded that conventions as a form of business meeting/event and as a significant segment of business tourism, make a meaningful tourism impact and contribution to the economy of host destinations (ETC/UNWTO 2015).

According the International Tourism Highlights, business and professional travel are making 13% of visit in all world regions (UNWTO 2019). It is a common case that a business meeting or event involves a business travel, making a total global economic contribution of 1.23 trillion U.S. dollars to the global economy during the year 2017 (Lock 2018). In the same year, the United Kingdom's business travel spending reached approximately 50.04 billion U.S. dollars (Lock 2019a). Just a year before, in 2016, business travel spending in the U.S. amounted to 283.62 billion U.S. dollars (Lock 2019b). According to theWorld Travel and Tourism Council (2018: 6) business travel spending is expected to grow by 3.2% until 2028 and rise from USD 1,276.8bn in 2018 to USD 1,756.1bn in 2028.

International Congress and Convention Association as a global meetings industry network is tracking meetings by the subject matter. From the last published report it is evident that Science meetings are third with 13,5% of share in all meetings held from 2013 till 2017, right after Medical Sciences (16,6%) and Technology meetings (14,4%) (ICCA 2019, 38). According to the same, most significant congress and convention source, in 2018 a total of 12,937 rotating association meetings were captured, indicating an increase of 379 meetings compared to the number registered at the same time in 2017 (ICCA, 2019). The number of meetings since 1963 has grown exponentially by approximately 10% each year. It can be concluded that the number of meetings has doubled each 10 years. In the period from 1963 to 1967, estimated total number of participants of all meetings has grown from just over 2 million to almost 25 million in the period from 2013 to 2017. But, in the same time, it is evident that meetings are getting smaller over the years. For instance, between the period of 1963 and 1967, the average number of participants was 1,263. Between the period of 2013 and 2017, the average number of participants was 409, marking a significant decrease of participants at international association meetings of 66% (ICCA 2018, 31).

However, the Covid-19 pandemic happened in the beginning of 2020. With borders closed, airlines grounded and citizens living in lockdown conditions in most of the world’s major travel source markets and destinations as well as business travel and the meeting industry have been hit hard. Cancellation and postponement of events become the new reality, which leads to irreversible financial losses. It should be noted that no reliable and publicly available data on the convention industry losses are available to date, but it should certainly take into account the fact that humans are social beings who wants to travel. So it is yet unlikely to see a short-term recovery in business travel. Business gatherings will certainly be held in person again and participants’ behavioral intentions will mater again.

An increasingly complex business environment creates more and more challenges. Considering the current trend of significant decrease of participants at individual conventions, understanding the evaluations of convention attendees becomes more important than ever. Though prior research has explored the concept of convention participants behavioral intentions (Carpenter and Lehmann 1985;Cronin and Taylor, 1992;Boulding et al. 1993;Zeithaml Berry and Parasuraman 1996;Oliver 1999;Bloemer and Odekerken-Schröder 2002;Kim et al. 2012), no research has been done to clarify how the frequency of participation per year effects convention participants behavioral intentions in order to attract them but also to encourage their repeated participation, spreading positive impressions and recommendations. Present study, using multi-group structural equation modeling approach, addresses such research gaps by exploring the proposed conceptual model (Fig. 3) from the perspective of both the attendees that attend one convention per year and attendees that attend more than one convention per year through several constructs: site-specific dimensions and convention-specific dimensions. At the same time, study investigated which dimensions of value affected attendees depending on the frequency of their attending conventions. The findings are expected to offer rich insight into how this frequency of attending moderates the relationship between convention specific dimensions and participants’ behavioral intentions.

1. CONVENTION TOURISM AS A PART OF BUSINESS TOURISM

Tags profitable and dynamic best describe business tourism. Its economic importance is linked to two important aspects: the purchasing power of a business tourist is considered higher than that of a leisure tourist, and at the international level, this type of tourism has reached high shares in overall tourism (Popşa 2018). Considering its characteristics, business tourism has multiple implications in the non-economic domain (progress and change of learned achievements, knowledge, as well as connecting and bringing people together), as well as in the economic domain (economic effects) (Štetić 2007, 15).

Every analysis of the business tourism structure inevitably faces terminology problems. Despite the rapid growth of this segment of tourism, or as a result of this rapid growth, there is a lack of universally accepted and standardized terminology (Davidson and Hyde 2014, 5). Even with the terms for meeting-related concepts in the English language, there are significant differences between terms defined in North American English and European English (Davidson and Hyde 2014: 5).

In case of business tourism, there are several terms used in different situations (Davidson and Hyde 2014, 6):

  • Business tourism is a well established term, but only in certain occasions. Problems with this term may emerge, for example, from the fact that the connection to tourism may be weak for some categories of meetings where very little travel takes place (for example, a corporate meeting held at a local hotel). The term is almost never used in North American English where business and tourism are clashing terms.

  • MICE is an acronym for Meetings, Incentives, Conferences/Conventions and Exhibitions/Events. The aforementioned acronym is widespread, however, the main problem with this term is that no one outside the meetings industry understands what the term means.

  • MEEC is an acronym for Meetings, Expositions, Events and Conventions. In recent literature this term replaces the current used term MICE. The reason for changing the name comes from the fact that most study programs which deal with business tourism dedicate insufficient attention to incentive travel. The incentive travel segment significantly changes its characteristics over time and from exclusive travel (employee reward) becomes an education and training based journey. This type of travel is increasingly represented in the form of sales training, motivational meetings or team building (Fenich 2016: 11).

  • Business events, an alternative term recently adopted in some of the major markets such as Australia and Canada, is based on the fact that meetings are very similar to other types of events (such as cultural or sports events) in terms of being planned, held in designated spaces or targeted at a specific audience.

  • Meetings industry. Recently, there was an initiative proposed by the International Congress and Convention Association, the Meeting Professionals International and the Reed Travel against the use of the term MICE wanting to introduce the term Meeting industry as an alternative. The success of the initiative was impeded by the fact that the term MICE seemed to be a preferred term in the world regions such as the Middle East and Southeast Asia where the industry is expanding significantly.

In addition to the terms mentioned above, the authorsMarques and Santos (2017) list other acronyms that define activities correlated with business tourism: MECE (Meetings, Events, Conventions, Exhibitions); MCE (Meetings, Conventions, Exhibitions); CEMI (Conventions, Exhibitions, Meetings, Incentives); MC and IT (Meetings, Conventions and Incentive Travel); MI (Meetings Industry).

It is important to emphasize that conventions are the integral part of business tourism, comprising of two basic phenomena. The first group consists of business gatherings (MICE tourism) realized through the organization of associations/institutions conventions, business meetings and incentive trips by corporations, exhibitions and fairs as well as of government meetings. Another group of business tourism consists of individual business travel, realized through presentations, consultations, research and one-on-one meetings (Rogers 2008).

Figure 1: Business tourism structure according toMarques and Santos (2017)
THM-27-99-g1.png

Note: D = Discretionary, ND = Non-discretionary .

Source: Adapted fromDavidson and Cope (2003),Rogers (2008),Getz and Page (2016) andMarques and Santos (2017)

In the business tourism classification according toMarques and Santos (2017), non-discretionary travel implies that the destination is not willingly selected but imposed by the job requirements. The organization of events includes meetings, trade fairs/exhibitions, incentive travel and corporate hospitality, and is considered discretionary. Choosing a destination for such events is often flexible and associated with group travel (Davidson and Cope 2003;Rogers 2008;Getz and Page 2016;Marques and Santos 2017). This classification of business tourism is supported by the assumption that the attendees base their decision about participating in the conventions not only on convention program and its scientific expertise, but also on the convention host destination.

Previous research focused on answering the essential question: “Why do people attend conventions?” (Getz, 2013: 255)? Researchers have been discussing this issue for some time, and although there are always event-specific factors, it is generally accepted that there are four to six major motivators for attending conventions (Mair and Thompson 2009). In the same way that consumers would choose the product that best meets their needs, the potential attendees are likely to select a specific convention that gives them the most benefits and features they need. Since the main motivators have already been identified by the previous research, this paper introduces a new dimension to show that not all convention factors are equally relevant to a different group of attendees. The authors of this paper classify attendees into two groups determined by the frequency of convention participation per year (those attending one convention and those attending multiple conventions per year).

2. LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT

A long time ago researchers from various social science disciplines showed an interest in studying how individuals make decisions when buying. There is a general agreement that the understanding of customers’ decision making process is crucial for explaining and predicting their buying behavior. A significant number of researchers (Lee, Lee and Choi 2011;Rittichainuwat, Beck and LaLopa 2001;Severt et al. 2007) studied certain tourists’ decisions, especially focusing on vacation destination decision making process. Many of the mentioned studies were based on the consumer decision making models and provided considerable conceptual and empirical support for understanding tourists’ behavior when choosing the vacation destination. Similar concepts are also applied on convention tourism. The literature overview suggests that a lot of attention was dedicated to meeting planners’ perspectives, especially to the questions related to the choice of convention destination. On the other hand, there is a certain number of papers (Severt et al 2007;Opperman and Chon 1997;Lee, Petrick and Crompton 2007) which explore the convention attendee perspectives with questions related to making the decision about attending the convention.

2.1. Destination specific dimensions

Set out below is the analysis of papers which explore the factors crucial for choosing a convention, that is, factors which potential convention attendees consider when making the decision about participating in a particular convention or choosing another one. The analysis of convention themed literature was carried out in order to single out destination factors crucial for choosing the convention destination. AuthorsCrouch and Louviere (2004) conducted a research in 2004 and identified site factors important for choosing the convention destination: the desirability of the destination is strongly connected with the proximity of the convention destination. Also, desirability of the destination declines as the proportion of convention attendees who need to fly further to get to the convention destination increases. In terms of the general convention setting, opportunities for entertainment, shopping, sightseeing, recreation and organized tours were significant, as were physical destination attributes and the social and cultural environment. The results suggest that although the characteristics of the convention facilities are particularly important, an attractive convention destination must offer strengths across a broad range of other factors as well, if the destination is to be successful in an increasingly competitive environment. Accordingly, the hypotheses were formed:

Hypothesis 1: Accessibility of the convention destination has no effect on future behavioral intentions of the participants that attend one convention per year.

Hypothesis 1.1: Accessibility of the convention destination positively affects future behavioral intentions of the participants that attend more than one convention per year.

Oppermann and Chon (1997) claim that extra-convention opportunities, including shopping, local attractions and recreational activities (in this research termed as integral destination product), attract participants. Considering the fact that most participants are financed by their organizations, the attendees and/or their spouses rather participate in conventions which offer more extra-convention opportunities besides the convention itself.Lee and Back (2008) used destination-specific factors as dimensions crucial for measuring convention quality when testing the participants on brand market value. They used accessibility, extra-convention opportunities, safety and costs for assessing the destination-specific factors and concluded that the mentioned factors impact positively on the attendees’ satisfaction, that is, if accessibility is on a satisfactory level and the destination offers enough extra-convention opportunities while also being safe, the participants perceived it positively. Accordingly, the hypotheses were formed:

Hypothesis 2: Integral destination product positively affects behavioral intentions of the attendees that visit one convention per year.

Hypothesis 2.2: Integral destination product has no effect on behavioral intentions of the attendees that attend more than one convention per year.

Yoo and Chon (2008) developed a measurement scale to examine factors affecting convention participation decision-making and identified three destination-specific factors: destination opportunities, safety and health situation, and travelability. All of these factors are connected with the accessibility, extra-convention opportunities and destination environment.

Usually, there is a number of conventions and meetings related to different areas which are held all over the world at the same or approximately the same time. If the convention takes place at a renowned destination, the attendance would significantly increase. The participants take into consideration destination’s accessibility because it is highly related to the travel costs. Destination factors, such as the climate, local population and safety, are worrying because the participants are aware of natural disasters’ effects, virus infections, terrorism threats and local violence. The mentioned destination attributes affect the destination image itself (Yoo and Chon 2008). Accordingly, three hypotheses were formed:

Hypothesis 3: Site environment is positively related to behavioral intentions for the attendees that visit one convention per year.

Hypothesis 3.3: Site environment is positively related to behavioral intentions for the attendees that attend more than one convention per year.

Following the analysis of relevant research on convention destination factors and their influence on the decision-making process regarding the participation in a convention, for the purpose of this research three convention destination dimensions are used: accessibility, integral destination products and site environment with related variables.

2.2. Convention specific dimensions

Professional education and social networking are considered as key dimensions in the convention tourism literature because they are influential motivational factors for convention attendees. The studies analyzed below have demonstrated that the attendees’ motivation for participating in a convention comes mainly from the opportunity to expand their social network, make business contacts, keep up with the trends, acquiring new knowledge and ideas.

The following studies (Oppermann 1998;Severt, et. al. 2007;Yoo and Chon 2008;Lee and Back 2008;Lee, Kim and Lee 2012) have shown that the attendees’ motivation for attending the convention came from the opportunities to develop professional and social networks, expand professional contacts, keep up with the changes in the profession and acquire new knowledge and ideas. People have an inherent goal of acquiring skills and knowledge which strongly motivates them to participate in conventions. The attendees don’t want to feel isolated or excluded which motivates them to maintain interactions and networking (Rittichainuwat, Beck and LaLopa 2001). Individuals choose conventions which best serve their education and social networking goals. Accordingly, authors suggests hypotheses as follows:

Hypothesis 4: Social networking positively affects intentions for the attendees that visit one convention per year.

Hypothesis 4.1: Social networking positively affects intentions for the attendees that attend more than one convention per year.

There is an extensive amount of research conducted in the convention literature regarding education and social networking. According toOppermann (1998), when assessing the convention participation factors, education and networking were highly ranked among participation decision-making variables.Severt et al. (2007) determined that the fundamental dimensions of convention performance are convention activities, extra-convention opportunities and education benefits. It was affirmed that education benefits have a dominant effect on the satisfaction.Yoo and Chon (2008) conducted a study which proved that besides the destination-specific dimensions, the opportunities for education and social networking are also important for convention participation decision-making. This study was designed as the first step towards developing a measurement scale which could be used by future researchers and practitioners to understand the decision-making process affecting attendees’ convention participation. Accordingly, authors suggests hypotheses as follows:

Hypothesis 5: Professional education positively affects intentions for the attendees that visit one convention per year.

Hypothesis 5.1: Professional education positively affects intentions for the attendees that attend more than one convention per year.

Apart from choosing the destination,Lee and Back (2008) also consider education and social networking to be quality dimensions in the conceptual model while establishing the convention staff service as a new dimension which contributes to the attendees’ satisfaction.Kim et al. (2012) explored the differential convention evaluation by first-time and repeat convention attendees. The quality evaluation of the convention was divided into convention-specific factors (professional training, social networking) and destination-specific dimensions (accessibility, extra-convention opportunities, environment). Their research indicates the following: although convention-specific dimensions remain crucial for both the first-time convention attendees and the repeat ones, the first-time attendees pay more attention to the destination compared to the repeat attendees considering the lack of information about a particular convention.

Figure 2: Conceptual presentation of the proposed hypotheses for each group of attendees(upper Figure: Attendees that attend one convention per year; lower Figure: Attendees that attend more than one convention per year)
THM-27-99-g2.png

Based on prior research, this paper uses the dimension of convention quality which consists of convention-specific and destination-specific factors. Professional training and professional networking constitute quality dimensions related to the convention specific factors. These prominent dimensions are used for understanding the convention evaluation by the two groups of attendees. Hypotheses are conceptually presented in theFigure 2.

2.3. Behavioral intentions of convention attendees

Behavioral intention is defined as the willingness to pay a price premium (Zeithaml, Berry and Parasuraman, 1996) and the intention of spreading positive word of mouth (Boulding et al. 1993). In this research, behavioral intentions are explored through the intentions of repeated participation and of spreading positive word of mouth/recommendations, excluding the willingness to pay a price premium because the employers cover the participation of most attendees so the willingness to pay a premium price doesn’t serve as an adequate dimension of behavioral intentions in the convention context.

AuthorOliver (1999) put behavioral loyalty as the last stage so as to explain the transition from behavioral intentions and loyalty to behavior. Behavioral intention is the stage in which the intention turns into a willingness to act. In the convention context, the frequency of attending and the intention of spreading positive word of mouth serve the purpose of measuring behavioral intentions of convention attendees. AuthorNeal (1999) claims that the value explains behavioral intentions better than satisfaction because the satisfaction doesn’t always predict behavioral intentions.

Stimulated by this claim, authorsChen and Hu (2010),Lee, Lee and Yoon (2009) andLee, Lee and Choi (2011) as well as the authorOh (2000), dedicated their research to investigating the direct relationship between the perceived value and behavioral intention.Lee, Lee and Choi (2011) explored the role of emotional and functional values in evaluating the festivals and determined that both values have a positive effect on behavioral intentions. Also,Chen and Hu (2010) examined the structural relationship between relational benefits, perceived value and behavioral intentions in the coffee industry. Their results showed that the multidimensional value contributed to behavioral intentions. The positive correlation between values and behavioral intentions is explained by the theory of goals and action identification (Carver and Scheier 1990). Individuals have the tendency to arrange their goals from the lowest to the highest and act accordingly. A similar situation can be observed when it comes to convention attendees. The higher they perceive the value of the convention and its destination, the more they are willing to spread positive recommendations and to participate in the convention again in the future.

3. METHODOLOGY

3.1. Data collection

For the purpose of identifying the convention tourism attendees’ behavioral intentions depending on the frequency of their annual participation, university teaching staff (employees elected to the scientific title) were surveyed since they have the obligation to participate in conventions, conferences and symposiums which gives them the opportunity for additional education, but also to make professional progress by publishing papers in conference proceedings. Accordingly, teaching staff of the following public universities in the Republic of Croatia are included in the sample of this research: Josip Juraj Strossmayer University of Osijek, Juraj Dobrila University of Pula, the University of Dubrovnik, the University of Rijeka, the University of Split, the University of Zadar and the University of Zagreb.

Personalized e-mails were sent on all publicly accessible mail addresses (7 581) collected by researching every single constituent of the mentioned universities. The survey was conducted in May 2018. Participants were asked to rate their experience of the last convention they had attended that took place outside of their place of residence and where they stayed for at least 24 hours. The questionnaire could be accessed via the SurveyMonkey online tool where a link was available for each of the subjects. The possibility to access the questionnaire lasted for 20 days. Out of a total of 1 228 responses gathered, after the detailed analysis and elimination of incomplete questionnaires, the final sample consisted of 978 correctly completed questionnaires which forms the return rate of 75.85 %. The questionnaires were analyzed with the help of R Studio program, specifically using the lavaan package (Rosseel 2012) for creating and testing the structural model. Following recommendations byAdelson et al. (2019) for transparent research, the entire code for data analysis along with the example of the dataset is accessible in the following link:https://osf.io/zwc2x/.

3.2. Measures

The survey instrument (seeTable 1) is the adapted and translated version ofKim et al.’s (2012) one. Throughout the 21 items, participants indicated their rating of six latent variables: accessibility, integral destination product, site environment, social networking, professional education and behavioral intentions. UnlikeKim et al. (2012) authors were interested in the direct relationship between convention rating and behavioral intention relationship that is why the model did not contain multidimensional value items. Question that grouped participants into two distinct groups was how many conventions, on average, they attend annually. Every measure was operationalized on a seven-point Likert-type scale where higher rating corresponds to higher agreement.

Table 1: Results of confirmatory factor analysis
Factor loadingZ - ValueM (sd)
Factor 1: Accessibility
ACC 1: The convention was held in a venue easily accessible.1NA5.64 (1.39)
ACC 2: Local public transportation was easily accessed.1.0914.825.75 (1.22)
Factor 2: Integral destination product
IDP 1: The convention sites offered an opportunity for enjoying amusing attractions.1NA4.95 (1.45)
IDP 2: The convention sites offered an opportunity for a variety of restaurants.0.9623.995.33 (1.35)
IDP 3:The convention sites had cultural attractions.1.0323.725.19 (1.47)
Factor 3: Site environment
SE 1: The convention destination's climate was desirable.1NA5.64 (1.26)
SE 2: Local people were friendly.0.9617.055.59 (1.18)
SE 3: The convention sites were safe.0.6814.676.00 (1.07)
Factor 4: Social networking
SN 1: Attending the convention developed my professional social networking.1NA5.73 (1.17)
SN 2: Social functions (e.g., banquets, receptions) at the convention contributed to expanding my networking with others.1.0127.545.76 (1.14)
SN 3: Attending the convention was helpful in gaining recognition from peers.0.9220.035.04 (1.41)
Factor 5: Professional education
PE 1: Session programs and topics at the convention were informative.1NA5.65 (1.08)
PE 2: Session program was interesting.1.0533.515.50 (1.11)
PE 3: Attending the convention was helpful in exchanging knowledge and ideas.1.0734.435.71 (1.11)
PE 4: Attending the convention was helpful in keeping up with changes in my profession.1.1433.115.55 (1.22)
PE 5: Attending the convention was useful as I got the chance to listen experts' research.1.1030.845.63 (1.22)
Factor 6: Behavioral intentions
BI 1: I encourage my colleagues to attend the convention.1NA5.26 (1.27)
BI 2: If someone is looking for good conventions, I advise him/her to attend the convention.1.0351.445.24 (1.27)
BI 3: I say positive things about the convention.0.9443.955.38 (1.31)
BI 4: I am willing to attend the convention continuously in the future.0.9538.695.43 (1.31)
BI 5: I will keep attending the convention in the future.0.9536.105.25 (1.34)

Note: All factor loadings are significant at p<0.000. Parameters are fixed at 1 for the maximum-likelihood estimation, thus, z-values were not obtained (NA) for those fixed at 1 for identification purposes.

3.3. Results

Testing for reliability and validity

Confirmatory factor analysis was conducted in order to check whether the questionnaire structure remained the same after the scale translation. For the purposes of the model identification and factor scaling, marker variable approach of fixing the regression coefficient from the factor to one of the measured variable to one thus giving the factor the same variance as the measured variable (Tabachnik and Fidell, 2007). The model showed satisfactory fit to the data (χ2 = 756.49; df = 173; CFI = .96; TLI = .95; RMSEA = .06).

Table 2 presents the Cronbach’s alpha used to estimate reliability of each construct: accessibility (.79), integrated destination product (.84), site environment (.72), social networking (.79), professional education (.92) and behavioral intentions (.80). All of the alpha coefficients were above theNunnally’s (1978) cut-off of 0.7. As for the convergent validity of the scale, it was supported by all average variance extracted (AVE) exceeded 0.5(Fornell and Larcker 1981) except for the site environment which is close enough to be regarded as not being problematic (0.47). Except for the AVEs, all factor loading for all indicators were significant at p<0.05 which further lends the support for convergent validity (Anderson and Gerbin 1988).Fornell and Larcker (1981) state that the AVE size for each construct should be greater than the squared correlation coefficients for the corresponding inter-constructs which is the case in this data and supports discriminant validity of the scale.

Table 2: Correlations, reliability, AVE and mean.
ACCIDPSESNPEBI
ACC1
IDP0.381
SE0.350.451
SN0.230.230.291
PE0.210.170.210.631
BI0.240.230.260.590.641
CR0.790.840.720.790.920.80
AVE0.660.630.470.580.710.77
Mean5.695.165.755.515.615.31
Std.Dev1.191.240.931.051.011.17

Note: ACC = accessibility, IDP = integrated destination product, SE = site environment, SN = social networking, PE = professional education, BI = behavioral intentions, CR = construct reliability (Cronbach’s alpha), AVE = average variance extracted. Mean values are based on 7-point scales. All correlations are significant at p<0.05.

Before testing for the differences between two groups of participants, the proposed model was fitted across the entire sample in order to show its validity. The model’s fit was satisfactory (χ2 = 756.49; df = 173; CFI = .96, TLI = .95, RMSEA = .06) thus providing further support for its validity. The model is presented in theFigure 2. Next step was to test the model fit separately on participants who attend one convention per year and on those who attend more than one convention per year.

Figure 3: The structural model
THM-27-99-g3.png

Testing for measurement invariance across participants that attend one convention per year and those who attend more than one convention per year

Authors of this research divided participants in two groups depending on the average number of conventions they visit in a given year. There were 366 participants that attend one convention per year and 612 participants that attend more than one convention each year. Two groups do not differ in age (t = 0.66; df = 942.39; p=0.50) but slightly differ in the number of males and females that attend one or more conventions per year (χ2 = 6.22; df = 1; p<0.05). Authors observed a higher percentage of men than women who attend more than one convention per year and vice-versa. Both of these findings indicate that the two groups were homogenuous and that observed differences cannot be attributed to neither the age nor sex differences between groups. In order to compare the effect of conventiondestination rating on behavioral intentions it was necessary to establish that the studied phenomena yield measures of the same attribute (Horn and McArdle 1992) or measurement invariance. Both configural and metric invariance have been established for both groups (Table 3).

Table 3: Testing for measurement invariance across attendees that visit one and those who visit more than one convention per year.
Chi-squaredfCFITLIRMSEA
Nonrestricted measurement model1039.49346.95.94.06
Full metric invariance (L(X)Y=IN)1051.22361.95.94.06

Hypothesis testing

Once the assumption of invariance has been met, the full-metric invariant model has been fitted into the both groups and the structural relationships between them have been compared (seeFigures 2 and 3). The model showed a good fit to the data (χ2 = 1051.22; df = 361; CFI = .95; TLI = .94; RMSEA = .06). Structural parameters were estimated freely for each group. There were not many differences between the two groups. Authors observed statistically significant effect of integral destination product, social networking and professional education on behavioral intentions while accessibility and site environment do not predict future behavioral intentions for those who attend one convention per year (on average). On the other hand, accessibility, social networking and professional education are significant predictors of behavioral intentions for those who visit more than one convention per year while integral destination product nor site environment cannot predict one’s behavioral intentions of visiting specific convention again. The main differences between two studied groups are the effect of accessibility on behavioral intentions (significant for attendees that visit more than one convention per year) and integral destination product (significant for those who visit one convention per year).

Authors tested whether different convention characteristics differently affect those attendees that are “more selective” to the convention they visit and those that are “less selective” i.e. visit more convention on average. A non-restricted measurement model and a full-metric invariance model for “once-a-year” attendees and “more-than-once-a-year” attendees were tested first. The results show that full metric invariance was supported since the Chi-square difference between those two models was not significant (Δχ2 = 11.72; p>.05). Meaning of the result is that this model is invariant across the two groups.

Figure 4: The conceptual model for attendees that visit more than one convention per year
THM-27-99-g4.png

4. DISCUSSION AND RESULTS

Convention tourism, as a part of business tourism, is increasing its presence in the global tourism trends and as such significantly contributes to the total tourist traffic, based on the meetings which cover both business and tourist aspects. Its particularities manifest in characteristics such as convention attendees’ increased spending, the interaction of numerous economic activities and the creation of convention tourism destination image. Based on the research model, the correlation was established between the frequency of annual participation and the evaluation of convention and destination variables as well as the behavioral intentions of convention tourism attendees. After the measurements are made, it is possible to conclude that the measurement instrument is valid and reliable, with extended usability in the Croatia sample, followingKim et al.’s (2012). Regardless of the number of convention participants visit each year, social networking and professional education are the most important determinants in selecting a convention to attend while the site environment is not an important predictor of future behavior. Possible explanation is that they are academic staff that are guests to other academic staff high in SES (socio economic status) and maybe the area in which convention is held is safe. Behavioral intentions of attendees that visit one convention per year (we might call them more selective ones) are affected by the integral destination product (i.e. extra convention content) and not by accessibility of the destination unlike attendees that visit more than one convention per year. Their future intentions are not affected with integral destination product (the assumption is they attend so many conventions that they are fed up with them) but by destination’s accessibility (again, plausible because if they are constantly visiting conventions, they will try to pick those that are easily assessed compared to those that are far away or ones that require changing couple of means of transport).

Figure 5: The conceptual model for attendees that visit one convention per year
THM-27-99-g5.png

Attendees that visit more than one convention per year have a higher average rating of attitudes toward convention’ social networking opportunities (as expected, since they are exposed more to various colleagues and have more opportunity to network – which leads to more positive attitudes toward it).

CONCLUSION

The availability of a convention destination is positively related to behavioral intentions, but only for those convention participants who attend more than one convention per year. Integral destination product assessment (the convention sites offer an opportunity for enjoying amusing attractions, opportunity for a variety of restaurants and cultural attractions) is positively related to behavioral intentions, only to those convention attendees who attend one convention a year. Given that they attend only one convention per year, the convention sites offered in the destination is very significant for them. In addition to what is a key result, the site environment is not related to any group's behavioral intentions (they may know from experience that this does not pose a risk since they are academics who have a full convention programmed and aren’t many situations for interacting with the locals and opportunities for endanger their safety are minimized in more or less every convention). Social networking and professional education are both positively related to behavioral intentions in both groups (which is also expected and logical given that this is actually the most common goal of scientific conventions).

As pointed in the literature review, previous research focused on answering the question why people attend conventions. This research revealed that universities teaching staff are not resilient to the convention destination. Convention organizers and destination tourist boards can take these kind of research into account when organizing conventions or business meetings and start to organize kind of business events that previously had lower attendance in different destinations to enhance the probability of more participants coming to them.

After the Covid-19, for sure the most desirable business tourism destinations will be the one that can convince participants in the destination safety. This is a great opportunity for the destination marketing to start promoting the destination as a safety environment for the business gathering that are unthinkable without onsite participation in the long turn. The ultimate goal is to use this information to move attendees to a higher frequency of attendance.

One of the research limitations is certainly the target group. The survey was conducted in terms of university teaching staff employees, but it should be taken into consideration that the private sector employees who also attend the conventions were not included in this study. Also, the subjects were evaluating their most recent convention experience which means that not all of them participated in the same convention nor they were necessarily at the same destination. The survey was conducted in May when most of the conventions are organized. The subjects’ responses to the questions were based on their evaluation of the convention they most recently attended provided that they stayed at the convention destination for at least 24 hours. At the same time, it should be taken into account that some of the subjects evaluated the convention which they attended in the last couple of days so their recollection of the convention was fresh and more realistic, while some of the other subjects evaluated the convention which they attended a couple of months ago which considerably affects the evaluation credibility. A significant limitation also lies in the fact that the subjects didn’t evaluate one (the same) convention nor the same convention destination which considerably affects the difference between their answers and their perception of observed variables.

At the same time, the mentioned limitations can serve as guidelines for further research. In that context, the following suggestions are set out below. A better validity and generalization of the results could be achieved by increasing the number of subjects in the research which would ensure that the obtained results are representative. The same research should be conducted upon the completion of the convention so the subjects could give more credible answers.

Future research could identify the trend of changing convention attendees’ habits. Also, the existing body of work would be enriched by taking into consideration new factors such as the attendees’ cultural or life standards. Conducting parallel research in other countries of the world would be a great contribution to future research.

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