2013), understanding of residents' perceptions throughout a mega-event's full life cycle (Li, Hsu ... In the case of Tour de France Cycle Race 2007 event.
2014 FIFA World Cup in Brazil: Local residents’ perceptions of impacts, emotions, attachment, and their support for the event
Dogan GURSOY Taco Bell Distinguished Professor Washington State University, College of Business School of Hospitality Business Management 340G Todd Hall, PO Box 644736 Pullman, WA 99164-4736, USA
Bishnu SHARMA Senior Lecturer in Management School of Business, Faculty of Arts & Business, University of the Sunshine Coast Maroochydore DC QLD 4558, Australia
Alexandre PANOSSO NETTO Lecturer in leisure and tourism Universidade de São Paulo, São Paulo, Brazil
And
Manuel Alector RIBEIRO Ph.D. Candidate in Tourism, Research Centre for Spatial and Organizational Dynamics Faculty of Economics, University of Algarve Campus de Gambelas 8005-139 - FARO - Portugal
ABSTRACT This study investigates the relationships between local residents’ attachment and their emotions ‘positive and negative’ towards the World Cup, residents’ emotions and their perceptions of impact from the FIFA 2014 World Cup Games, and residents’ perceptions of impact and their support for the event. For conducting this study, data collection was carried out using a stratified random sampling approach from a sample of residents (n=3770) located in 12 cities in Brazil that hosted the World Cup games during the spring of 2014. The LISREL 8.7 structural equation analysis package was used to analyse the data. The results suggest that there is a direct relationship between residents’ attachment and both positive and negative emotions towards the event; between positive emotions and both the perceptions of positive impacts and the perceptions of
negative impacts and so forth. The study also identified a direct significant impact between positive impact perceptions and support for mega-event and between positive negative perceptions and support for mega-event. Key words: FIFA 2014 World Cup, positive and negative emotions, impacts of and support for the event
INTRODUCTION Mega-events such as FIFA World Cup, Olympic Games, Rugby World Cup etc. have an impact on long term tourism and are one of the major contributors of tourism growth. They also act as a catalyst in stimulating economy and also contribute to social and cultural change to the host nations (Pappas, 2014; Fourie & Gallego, 2011; Hiller, 2000; Hiller, 1998). Such events are also expected to provide massive opportunity and challenges for tourism service providers and local communities. While mega-events give an impetus for local development, revenue generation, city branding, innovation and enterprise; they also involve substantial capital and lead to negative environmental impacts. In spite of possible negative impacts, prospective host communities invest significant amounts of time and resources in preparing the bids and winning the competition to host such mega-events (Gursoy et al., 2011; Ritchie & Aitken, 1985) as some countries consider such successes as a means of global image creation to make the destination more attractive to future tourists (Lee et al., 2005), their international publicity, recognition and an opportunity to showcase their economic maturity (Smith, 2005). Pre-event process e.g. bid preparation, submission and award processing can be complex, time consuming and costly. Such events can lead to the forward linkage e.g. short or long-term employment generation and enhanced tourism infrastructure through improved transport, backward linkage such as mega-event idea generation and development of background objectives, and parallel linkages e.g. side-effects of the mega-event (Hiller, 1998). Studies related to residents’ perceptions of tourism generally suggest that tourism’s positive influence on social and environmental impacts might enhance resident’s support for tourism and negative influence might lead to resident’s withdrawal of support for tourism activities (Long & Kayat, 2011). Events such as sports, business, and festivals are some of the important motivators of tourism and they play a major role in the development and marketing of tourist destinations (Getz 2008). However, the research on the impact of mega-events on local communities and the extent of community support for those events is still limited (Kim & Petrick, 2005). Organising such events involves the construction of facilities and infrastructure and the analysis of events includes the cost of building infrastructure and event associated facilities, revenue generation from visitor spending, receipts from event, media exposure, capital accumulation through corporate sponsorships and the commodification of entertainment (Hiller, 2000; Whitson & Macintosh, 1996). Hosting mega-events such as World Cup, Olympics, Winter Olympics involves host region’s/country’s commitment of resources e.g. financial, physical, managerial and technical in a significant way (Jeong & Faulkner, 1996). The planners and architects of such events normally make decisions for such investments in the hope that successful implementation of mega-events can led to positive outcomes such as enhancement of the profile of the city/region ‘image’ in the international arena, development of infrastructure, unity within the host community, increased opportunities to meet foreign travellers and enjoy sports, and the promotion of tourism globally (Kim & Petrick, 2005; Jeong & Faulkner, 1996). Generally it has been reported that such events have a long-term tourism and urban development benefits including community building, urban renewal, and cultural development in fostering national identity (Getz, 2008). However, such events also cause considerable inconvenience to the local community resulting in short-term economic costs (Jeong & Faulkner, 1996). Some of the recent studies that have focused on mega-events include impact of the 2010 FIFA World Cup on urban development (Pillay & Bass, 2008; Bob & Swart, 2009), impacts of the Beijing 2008 Olympic games (Zhou & Ap, 2009; Gursoy, Chi & Chen, 2011; Jin, et al., 2011), impacts of the ICC Cricket World Cup 2007 on Barbados (Lorde, Greenidge & Devonish, 2011), hosting mega-events and Londoners’ support for the 2012 Olympic games (Pappas, 2014; Prayag et al., 2013), understanding of residents’ perceptions throughout a mega-event’s full life cycle (Li, Hsu & Lawton, 2014), examination of the residents’ perceptions of psychic income and social capital before and after the 2010 FIFA World Cup in South Africa (Gibson et al., 2014) and so forth.
Based on the perceptions of residents past studies have generally reported positive impacts of mega events (Jones, 2012). However, the residents’ perceptions of impacts before and after the games can change (Kim & Petrick, 2005). For example, based on a study of the 2008 Beijing Olympic Games, changes in local residents’ perceptions of impacts suggested that benefits generated were less than they had expected and the costs associated were higher than they had anticipated (Gursoy et al., 2011). Contrary to these findings, Lorde et al. (2011) reported that in Barbados the perceived benefits after the ICC Cricket World Cup 2007 had outweighed the costs although pre-games expectations were that the costs would outweigh the cost of hosting the event. In terms of psychic income measured as event related pride for hosting the 2010 FIFA World Cup in South Africa, there was a significant increase in the perceptions of residents of five host cities which, however, was not the case with social capital dimension (Gibson et al., 2014). In the case of Tour de France Cycle Race 2007 event organised in the city of Canterbury, residents’ support for the decision to host the event was remarkable despite the potential for various negative impacts as the City Council launched a very successful campaign for the event (Bull & Lovell, 2007). Pre- and post- games perceptions of Barbadian residents on the direct and indirect impacts of hosting the ICC Cricket World Cup 2007 found significant statistical differences between their pre- and post-games perceptions for various impact factors including benefits of cultural exchange, social problems, economic benefits, natural resource and cultural development, traffic congestion and pollution, price increases, and construction costs (Lorde et al., 2011). Although there are several studies dealing with mega-events, there is not much available that deals with the residents’ emotions regarding such events. Therefore, this study has the objective of advancing theoretical understanding of local residents’ support for mega events incorporating their emotions both positive ‘loving, caring, glad, inspired’ and negative ‘increased littering, destruction of natural environment, increased noise, pollution and crime’. This study examines these relationships using data from the 2014 FIFA World Cup event in Brazil.
METHOD In achieving the above research objectives, a structural modeling approach was employed on a data set collected from a sample of the residents located in 12 cities that hosted the 2014 World Cup games in Brazil during the spring of 2014. The sample population consisted of individuals who reside in the cities that hosted the 2014 World Cup games in Brazil. The 12 cities that hosted at least one World Cup game included Rio de Janeiro, São Paulo, Belo Horizonte, Porto Alegre, Brasília, Cuiabá, Curitiba, Fortaleza, Manaus, Natal, Recife, Salvador. First, the number of usable responses was determined from each city based on the margin of error estimations. Researchers aimed to collect at least 250 usable responses from each city. The number of targeted usable responses was higher in cities with larger populations. Afterwards, a stratified random sampling approach was utilized to determine the sample from each city. Gender, age and location of the principal residents were used to determine the number of responses from each population strata. The usable number of responses were 3770 from the 12 cities. Survey instrument used in this study was developed following the procedures recommended by Churchill (1979) and DeVellis (1991). A number of items to measure each construct were identified from the literature. Using a back translation approach, items were translated into Portuguese. Afterwards, a group of tourism experts assessed the content validity of these items. They were asked to provide comments on content and understandability of those items. They were then asked to edit and improve those items to enhance their clarity and readability. They were also asked to identify any of those scale items that are redundant and to offer suggestions for improving the proposed scale. After checking the content validity of the survey instrument, two pretests were conducted on local residents in Sao Paulo, Brazil. Based on the outcome of the pretests, the survey instrument was finalized. The survey instrument consisted of eight sections. This study, however, utilized data from four sections that focused on community attachment to the event, residents’ emotions toward the event, residents’ perceptions of the event and their support for the event. A total of five items were used to measure community attachment to the event. Local residents’ emotions towards the 2014 World Cup were measured with 13 items; seven measuring positive emotions and six measuring
negative emotions. A total of eleven items were used to measure local residents perceptions of mega event impacts and three items were used to measure support for mega events. Items for measuring perceptions of mega event impacts and support for mega events were adopted from Prayag et al. (2013), Gursoy & Kendall (2006) and Kim, Gursoy & Lee (2006). All of the items were measured on a five-point Likert type scale with “strongly disagree” at the low end and “strongly agree” at the high end. Data for this study were collected using personal interviews from the residents of the 12 selected cities in Brazil utilizing an intercept approach. A professional data collection company was contracted to collect data from each of the selected cities. Sample frame included residents who reside in those 12 cities. The interviewers were properly identified with the badge of the company and tablets were used for data collection. Interviewers were asked to approach every tenth person passing through. They were instructed to ask the person if s/he was interested in participating in a survey that measures local residents’ perceptions of the 2014 World Cup. If the answer was a no, interviewers were instructed to intercept the next person and ask the same questions until they identified an individual who agreed to participate in the survey. After the individual agreed, the purpose of the study was explained in detail by the interviewer and a personal interview using a structured survey instrument was conducted. Each question was asked to the respondent by the interviewer and his/her responses were recorded on a tablet. The survey company called back around 20 percent of respondents from each city to confirm the validity of the responses after each interviewer submitted the data they collected. A total of 3,770 valid questionnaires were obtained from the residents of 12 cities that hosted at least one 2014 World Cup game.
RESULTS The fit of the measurement model and the fit of the structural model were tested using the LISREL 8.7 structural equation analysis package. The maximum likelihood (ML) method of estimation in combination with the two-stage process was utilized to analyze the data (Nunkoo, Gursoy & Ramkissoon, 2013). As fit indices, the chi-square statistics (and associated ‘p’ values) were examined first. However, because of the large effect of sample size on the chi-square values (and associated ‘p’ values), other fit indices were also selected to assess the fit of the models (Nunkoo, Ramkissoon, & Gursoy, 2013). These fit indices were the goodness-of-fit index (GFI), adjusted goodness-of-fit index (AGFI); the normed-fit index (NFI), the nonnormed-fit index (NNFI), the comparative fit index (CFI), the incremental Fit Index (IFI) and the relative fit index (RFI). Two indices that are proposed to measure the parsimony of the model were also reported: parsimony goodness of fit index (PGFI) and parsimony normed fit index (PNFI). All of the composite reliabilities were found to be above 0.70, indicating that each construct had acceptable reliability. The overall fit indices of the measurement model were as follows: χ2 (446) = 1,712.05 (p = 0.0); goodness-of-fit index = 0.97; adjusted goodness-of-fit index = 0.97; the normed-fit index = 0.99; the non-normed-fit index = 0.99; the comparative fit index = 1.00; the incremental fit index = 1.00; the relative fit index = 0.99; the parsimonious goodness-of-fit index = 0.82; and the parsimonious normed-fit index = 0.89. Further, the indicators of two residuals, root mean square residual (RMR) and standardized root mean square residual (standardized RMR), and root mean square error of approximation (RMSEA) were 0.070, 0.030, and 0.027 respectively. Two types of validity measures, convergent and discriminant validity, were examined. Convergent validity was tested by examining ‘t’ values of each item’s factor loading on its underlying construct (Anderson & Gerbing, 1988). All tvalues associated with each completely standardized factor loading for each indicator were found to be higher than 1.96; suggesting significance at 0.05 significance level, which indicated that convergent validity of all the indictors were established. Discriminant validity was tested by comparing intercorrelations of factors with the square root of the average variance (i.e. variance extracted estimate) for each factor (Hatcher, 1994). Since the estimate for variance extracted for each factor was at least 0.50 and exceeded any of the intercorrelations of the factors, discriminant validity of all constructs were established (Fornell & Larcker, 1981).
Most of the goodness-of-fit statistics of the proposed theoretical model were found to be above the recommended threshold values. The χ2 value with 452 degrees of freedom was 2,546.97 (p = 0.0), which was lower than the acceptable level. However, all other fit indices indicated that the proposed hypothesized structural model fits well to the data: goodnessof-fit index = 0.96; adjusted goodness-of-fit index = 0.95; the normed-fit index = 0.99; the non-normed-fit index = 0.99; the comparative fit index = 0.99; the incremental fit index = 0.99; the relative fit index = 0.99; the parsimony goodness-of-fit index = 0.82; and the parsimony normed-fit index = 0.90. Further, the indicators of two residuals, root mean square residual (RMR) and standardized root mean square residual (standardized RMR), and root mean square error of approximation (RMSEA) were 0.088, 0.037, 0.035 respectively. Both the direct and indirect estimated standardized path coefficients for the proposed model were also determined. The results indicated direct relationships between attachment and both positive (direct effect = 0.39, t-value = 10.04, p < .05) and negative emotions (direct effect = 0.84, t-value = 48.04, p < .05); between positive emotions and both the perceptions of positive impacts (direct effect = 0.69, t-value = 31.32, p < .05) and the perceptions of negative impacts (direct effect = -0.37, t-value = -6.97, p < .05); between negative emotions and both the perceptions of positive impacts (direct effect = -0.33, tvalue = -20.23, p < .05) and the perceptions of negative impacts (direct effect = 0.32, t-value = 3.14, p < .05). As expected, a direct significant impact was identified between positive impact perceptions and support for mega events (direct effect = 0.88, t-value = 35.38, p < .05) and between positive negative perceptions and support for mega events (direct effect = -0.09, t-value = -5.16, p < .05). A direct negative relationship between positive impact perceptions and negative impact perceptions was also identified (direct effect = -0.21, t-value = -3.14, p < .05).
CONCLUSIONS This study investigated the relationships between local residents’ attachment and their emotions ‘positive and negative’ towards the FIFA 2014 World Cup Games, along with their emotions and perceptions of impact from the Games, and their support for the event. The aim of this study was to advance theoretical understanding of local residents’ support for mega events by developing a mega-event support model using data from a sample of residents located in 12 cities in Brazil that hosted the World Cup games during the spring of 2014. The analysis was carried out using the LISREL 8.7 structural equation analysis package. The results from this analysis indicated that there is a direct relationship between residents’ attachment and both positive and negative emotions towards the event; between positive emotions and both the perceptions of positive impacts and the perceptions of negative impacts; between negative emotions and both the perceptions of positive impacts and the perceptions of negative impacts. The study also identified a direct significant impact between positive impact perceptions and support for mega-event and between positive negative perceptions and support for mega-event. The results also indicate an evidence of direct negative relationship between positive impact perceptions and negative impact perceptions. To get further insights into these relationships and determine why different people perceive the impact of such events in different ways, it will be interesting to extend this study in other mega-events such as the Olympics or the World Cup Cricket. Funding acknowledgement: This project was funded by the "CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico", Brasil (National Council for Scientific and Technological Development", Brazil).
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