Annals of Tourism Research, Vol. 38, No. 3, pp. 964–988, 2011 0160-7383/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. Printed in Great Britain

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doi:10.1016/j.annals.2011.01.017

DEVELOPING A COMMUNITY SUPPORT MODEL FOR TOURISM Robin Nunkoo University of Waterloo, Canada Haywantee Ramkissoon Monash University, Australia

Abstract: This study developed a model of community support based on the social exchange theory. The model contained fourteen hypothesized relationships and was tested using the LISREL package from responses collected from residents of Grand-Baie, Mauritius. Results indicated that support was influenced by perceived benefits, perceived costs, and community satisfaction. Perceived benefits were affected by community satisfaction, institutional trust, power to influence tourism, and neighborhood conditions. Community satisfaction and neighborhood conditions did not exert a significant influence on perceived costs. Power to influence tourism was also not found to affect community satisfaction. Policy implications and limitations of the study are discussed. Keywords: community support, trust, power, neighborhood conditions, overall community satisfaction. Ó 2011 Elsevier Ltd. All rights reserved.

INTRODUCTION Tourism development results in several economic and social benefits for destinations (Andereck, Valentine, Knopf, & Vogt, 2005; Kwon & Vogt, 2010). However, growth of the industry is also accompanied by several costs, affecting the lives of the host community (Andereck & Nyaupane, in press). The success of tourism depends on the active support of the local population (Gursoy & Rutherford, 2004), without which the sustainability of the industry is threatened. Residents should be the focal point of the tourism decision making process (Choi & Sirakaya, 2005). It is important for planners to consider information about the impacts of tourism from the local community’s perspective when planning for the industry. Recognizing the active participation of the local community as an integral part of sustainable tourism (Hung, Sirakaya, & Ingram, in press), scholars and researchers pay a great deal of attention to understand residents’ perceptions and their Robin Nunkoo is a doctoral candidate in the Department of Recreation and Leisure Studies, University of Waterloo (200 University Ave. W. Waterloo, ON N2L 3G1, Canada. Email ). He is also a Senior Lecturer at the University of Mauritius. Haywantee Ramkissoon is conducting doctoral research at the Tourism Research Unit, Monash University, Australia (Email ). She is also a Lecturer at the University of Technology, Mauritius. Both authors have research interests in sustainable tourism and tourist behavior. 964

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support for the industry, resulting in numerous studies on the topic (e.g., Byrd, Bosley, & Dronberger, 2009; Gursoy, Chi, & Dyer, 2010; Lee, Kang, Long, & Reisinger, 2010; Nunkoo & Ramkissoon, 2010; Yu, Chancellor, & Cole, 2011). While the majority of studies on residents’ attitudes is atheoretical (Gursoy & Rutherford, 2004), researchers also systematically study the reactions of the host community by making use of a theoretical framework (e.g., Andereck & Nyaupane, in press; Gursoy et al., 2010; Ko & Stewart, 2002; Kwon & Vogt, 2010; Nunkoo & Ramkissoon, 2010; Vargas-Sanchez, Plaza-Mejia, & Porras-Bueno, 2009). Social Exchange Theory (SET) remains one of the most widely used frameworks by researchers attempting to study community attitudes (Byrd et al., 2009; Gursoy et al., 2010; Lee et al., 2010). Ap (1992, p. 668) describes SET as ‘‘a general sociological theory concerned with understanding the exchange of resources between individuals and groups in an interaction situation.’’ From a tourism perspective, SET implies that residents’ support is based on their evaluations of the benefits and costs resulting from the industry (Andereck et al., 2005). Residents are willing to enter an exchange with the industry if they believe that the gains are higher than the costs. Accordingly, a community is likely to support tourism if the perceived positive impacts outweigh the negative consequences (Allen, Hafer, Long, & Perdue, 1993; Gursoy & Kendall, 2006; Gursoy et al., 2010). The usefulness of the theory is confirmed by several studies (e.g., Gursoy, Jurowski, & Uysal, 2002; Gursoy & Rutherford, 2004; Lee et al., 2010; Nunkoo & Ramkissoon, 2010). While research on residents’ attitude continues to gain popularity, other scholars investigate the determinants of residents’ support by developing theoretical models based on the SET (Gursoy et al., 2002; Nunkoo, Gursoy, & Juwaheer, 2010). Jurowski, Uysal, and Williams (1997) developed a framework which proposed that community attachment, economic gain, utilization of tourism resource base, and environmental attitudes are determinants of the residents’ perceived social, economic, and environmental impacts. The model postulated that these variables had a direct and indirect impact on support. Later, Gursoy et al. (2002) criticized the model for aggregating the benefits and costs into three categories. They proposed a new model which segregated the impacts into benefits and costs and investigated their effects on support. The model also incorporated two new determinants of attitudes: the state of the local economy and community concern. Gursoy and Rutherford (2004) further expanded on the above models and delineated the impacts into five categories: economic benefits; social benefits; social costs; cultural benefits; and cultural costs. More recently, Gursoy et al. (2010) further built upon the model developed by Gursoy and Rutherford (2004) and proposed that the perceived economic, social, and cultural benefits, the perceived social, socioeconomic costs and state of the local economy are determinants of residents’ support for mass and alternative forms of tourism. Other researchers (e.g., Ko & Stewart, 2002; Nunkoo & Ramkissoon, 2010; Vargas-Sanchez et al., 2009), though few in numbers, incorporate community satisfaction in their theoretical models to investigate

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support. Ko and Stewart (2002, p. 529) note that ‘‘community satisfaction may be a useful concept for evaluation of residents’ perceptions of tourism impacts and attitudes for additional tourism development. Therefore, further research in this field is needed to discuss integrating community satisfaction with tourism development.’’ However, existing studies on community satisfaction and residents’ support provide researchers with a limited understanding on the relationships between the two constructs. Results are contradictory and still far from conclusive (Vargas-Sanchez et al., 2009), probably because the community satisfaction construct is treated as a unitary variable, when in fact existing research suggests that community satisfaction is multidimensional in nature, comprising of several sub-constructs such as satisfaction with neighborhood conditions, perceived power to influence policy-making and trust in local institutions (Filkins, Allen, & Cordes, 2000; Grzeskowiak, Sirgy, & Widgery, 2003; Sirgy & Cornwell, 2001; Sirgy, Rahtz, Cicic, & Underwood, 2000; Widgery, 1982). The concepts of trust and power between the parties in an exchange relationship are inherent to the SET. ‘‘Social exchange requires trusting others to reciprocate’’ (Kayat, 2002, p. 175) and is characterized by unspecified personal obligations and trust, alongside with intrinsic and extrinsic rewards (Blau, 1994). Researchers agree that social exchanges are based not only on obligations, but also on trust between the partners in the exchange process (Cropanzano & Mitchell, 2005; Hwang, 1987; Kipnis, 2002; Redding, 1990; Xin & Pearce, 1996). Cook (2000) notes that social exchange is based on enduring long-term social relations (e.g., between the host community and the tourism industry) as opposed to one-shot transactions in a market context. Unlike economic transactions which are conditioned by impersonal markets and the legal framework, the persistence and extension of social exchanges are dependent on personal trust (Zafirovski, 2005). The value of SET is also recognized in areas such as social power (Molm, Peterson, & Takahashi, 1999). Alongside with trust, power plays an important role in any exchange (Kayat, 2002). Power relation between stakeholders in the tourism industry is considered to be an important component of the SET (Ap, 1992; Hernandez, Cohen, & Garcia, 1996; Lindberg & Johnson, 1997; Madrigal, 1993). The core ideas of trust and power that comprise the SET have yet to be adequately integrated in a single framework in research on community responses to tourism. Tests of the SET, as well as its application by researchers investigating residents’ attitudes have been based on an incomplete specified set of ideas, leaving out important theoretical constructs relevant to the theory. Integrating these concepts together, Figure 1 presents the model being tested. It proposes that residents’ level of trust in tourism institutions, their perceived level of power to influence development, and their satisfaction with neighborhood conditions are antecedents of the perceived benefits and costs, and their overall satisfaction with the community. Overall satisfaction is further considered to influence the perceived costs and benefits. The model also suggests that the perceived benefits and costs and overall community satisfaction influence support. The following section presents

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X10

X11

X12

X13

X18

X19 X20

Trust in tourism institutions

Perceived benefits of tourism

H3a

X21 X22

H5a H2a

H1a

X23 X1

H3c H4a X24

Power to influence tourism

H4c

Overall community satisfaction

Support for tourism development

H2c

X25

X2 X3

H4b

H5c X5 X4 X6

H2b X26

H3b X7 X27

Neighborhood conditions

H1b

Perceived costs of tourism

H5b

X28

X8

X29 X14

X15

X16

X17

X30

Figure 1. The Proposed Model of Community Support for Tourism

support for the inclusion of each construct in the model. The discussion works backward beginning with the ultimate dependent variable and ends with the exogenous variables. COMMUNITY SUPPORT FOR TOURISM Hypothetical Constructs Perceived Benefits of Tourism. Research on residents’ attitudes toward tourism suggests that a host population is influenced by the perceived positive benefits of the industry. Tourism increases employment opportunities for the local people (Dyer, Gursoy, Sharma, & Carter, 2007; Gu & Ryan, 2008), improves the local economy (Gursoy & Rutherford, 2004; Perdue, Long, & Allen, 1990), contributes to income and standard of living (Belisle & Hoy, 1980; Liu & Var, 1986; Pizam, 1978), brings in new businesses and improves investment opportunities (Dyer et al., 2007; Kwan & McCartney, 2005). Previous studies reported a positive relationship between economic benefits and attitudes (Andereck & Vogt, 2000). Tourism also increases recreational facilities and opportunities (Belisle & Hoy, 1980; Dyer et al., 2007; Liu & Var, 1986), enriches the community fabrics, cultural values, leads to heightened self esteem (Stronza & Gordillo, 2008), and improves quality of life of the residents (Milman & Pizam, 1988; Tovar & Lockwood, 2008). In general, existing studies suggest a positive relationship between residents’ perceptions of the positive impacts and support (Gursoy & Rutherford, 2004; Lee et al., 2010; Nunkoo & Ramkissoon, 2010; Ovie-

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do-Garcia, Castellanos-Verdugo, & Martin-Ruiz, 2008). Based on the conceptual and empirical discussion from the literature, the following hypothesis is proposed: Hypothesis 1a. A direct positive relationship exists between the perceived benefits of tourism and local residents’ support for its development.

Perceived Costs of Tourism. Although many studies reveal that residents tend to view economic impacts positively (Andereck et al., 2005; Gursoy et al., 2002), tourism increases costs of living (Kwan & McCartney, 2005; Liu & Var, 1986; Perdue et al., 1990), increases the price of land and housing (Belisle & Hoy, 1980; Lord, Greenidge, & Devonish, 2011; Pizam, 1978) and creates shortage of goods (Belisle & Hoy, 1980; Pizam, 1978). Other studies report that residents view the social and cultural impacts of tourism negatively (Ap & Crompton, 1998; Jurowski et al., 1997; Perdue, Long, & Allen, 1987; Pizam, 1978). Crime and congestion are the most frequently cited negative impacts of the industry on the local community (Gursoy & Rutherford, 2004). Previous studies report that perceived crime influences support for the industry (Belisle & Hoy, 1980; Lankford, 1996; Milman & Pizam, 1988; Pizam & Pokela, 1985). Overall, studies indicate that higher perception of the negative impacts leads to lower support (Gursoy & Rutherford 2004; Gursoy et al., 2002, 2010; Nunkoo & Ramkissoon, 2010). Based on the prior theoretical and empirical discussion, the following hypothesis is proposed: Hypothesis 1b. A direct negative relationship exists between the perceived costs of tourism and local residents’ support for its development.

Overall Community Satisfaction. Community satisfaction is considered to be an important component of community development and planning (Sirgy & Cornwell, 2001; Sirgy et al., 2000; van Es & Schneider, 1983). Research investigating the relationship between residents’ level of community satisfaction and support is limited in the literature (Ko & Stewart, 2002; Vargas-Sanchez et al., 2009). Vargas-Sanchez et al.’s (2009) study reveals a direct correlation between residents’ satisfaction with their community and perceived impacts. The study by Nunkoo and Ramkissoon (2010) which integrated community satisfaction as a determinant of residents’ attitudes also reveals the former to be a good predictor of community responses to development. Residents who were satisfied with their community were more likely to perceive tourism as having positive impacts. A direct negative relationship was also noted between community satisfaction and perceived costs of development, indicating that less satisfied residents were more likely to perceive tourism as having negative consequences. Based on the empirical findings from the literature, the following hypotheses are developed: Hypothesis 2a. A direct positive relationship exists between residents’ overall community satisfaction and the perceived benefits of tourism.

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Hypothesis 2b. A direct negative relationship exists between residents’ overall community satisfaction and the perceived costs of tourism. Hypothesis 2c. A direct positive relationship exists between residents’ overall community satisfaction and their level of support for tourism.

Existing studies which investigate the effects of community satisfaction on perceptions of impacts (e.g., Ko & Stewart, 2002; Nunkoo & Ramkissoon, 2010; Vargas-Sanchez et al., 2009) consider community satisfaction as a single construct. Scholars argue that community satisfaction is a multidimensional construct comprising of several variables (Allen, Long, & Perdue, 1991; Filkins et al., 2000; Grzeskowiak et al., 2003; O’Brien and Ayidiya, 1991; Sirgy & Cornwell 2001; Sirgy et al., 2000). While some researchers consider community services as an appropriate indicator of community satisfaction (Christenson, 1976; Murdock & Schriner, 1979), others argue that social and environmental factors of a community are the best indicators of community satisfaction (Flanagan, 1978; Goudy, 1977; Wilkinson, 1979). Still others consider neighborhood conditions (Grzeskowiak et al., 2003; O’Brien and Ayidiya, 1991), trust in local institution (Grzeskowiak et al., 2003; Widgery, 1982) and power to influence decisions (Diener, 1984; Grzeskowiak et al., 2003) as important determinants of community satisfaction. Trust in Tourism Institutions. Trust has emerged as a major issue in a number of institutional spheres in contemporary society (Fukuyama, 1995). It is considered as a part of political culture (Lovell, 2001). Trust builds relationships that underline economic development, legitimacy of governance institutions and promotes outcome which are in the best interest of society (Gilson, 2003). Public trust in institutions, commonly referred to as institution trust, is deeply embedded in the debate about the role of government in society and its relationship with the citizenry (Zussman, 1997). Luhiste (2006, p. 478) defines institutional trust as ‘‘confidence that political institutions would not misuse power.’’ Public trust in institutions is important for gaining political support for development (Klingemann, 1999; Norris, 1999). Trust in government institutions also affects the level of trust in other domains of life (Lovell, 2001). It affects a community’s attitudes toward political actors, as well as with government outputs (Easton, 1965). Institutional trust is a basic preconditioned for cooperation between two parties and is important to liberal democracy and civil society as it lays the foundations for people’s confidence in government decisions (Lovell, 2001). Sustained and low trust in public institutions challenges regime legitimacy (Hetherington, 1998; Miller & Listhaug, 1999) and may hinder the acceptability of tourism in a region. Past studies demonstrate that trust in regulatory institutions affects the general acceptability of an activity (Bronfman, Vazquez, & Dorantes, 2009; Earle, Siegrist, & Gutscher, 2007). Bronfman et al.’s (2009) study findings reveal that people rely on their trust in institutions before making judgments about the acceptability of a project. Lack of trust in institutions can

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make an activity unacceptable to people and make them more prone to influence from opponents (Bronfman et al., 2009). Researchers consider trust as an identifying outcome to social exchange (Blau, 1964; Cropanzano & Mitchell, 2005; Holmes, 1981). By extrapolation, it can reasonably be argued that residents’ trust in tourism planning institutions is likely to be a factor influencing attitudes toward the industry. Based on the above discussion, the following hypotheses are proposed: Hypothesis 3a. A direct positive relationship exists between residents’ level of trust in tourism institutions and their perceived benefits of tourism. Hypothesis 3b. A direct negative relationship exists between residents’ level of trust in tourism institutions and their perceived costs of tourism.

Grzeskowiak et al. (2003) consider trust in local institutions as an important component of community satisfaction and argue that the construct contributes significantly to residents’ attitude toward their community. Their study on residents of Genesee County, Michigan indicates that the residents’ level of institutional trust was a good determinant of their overall satisfaction with the community. A direct positive correlation between trust and overall community satisfaction was noted in the study. Likewise, Widgery’s (1982) research on Flint, Michigan community also reveals that residents’ trust in government and the political system are significant predictors of community-wide satisfaction. Residents with high level of trust were found to be more satisfied with their community than residents with low levels of trust. Based on the preceding discussion the following hypothesis is developed: Hypothesis 3c. A direct positive relationship exists between residents’ level of trust in tourism institutions and their overall community satisfaction.

Power to Influence Tourism. ‘‘The politics of tourism is a struggle for power’’ (Yasarata, Altinay, Burns, & Okumus, 2010, p. 345). Power refers to the ability of one actor to influence policy decisions that affect others (Thibaut & Kelley, 1959; Wrong, 1979). Power governs the interactions among stakeholders influencing or trying to influence the formulation of tourism policy and the ways in which it is implemented (Hall, 1994) and is influenced by resource distribution and competition (Bramwell, 2006). Power relations can be extended beyond individuals to include community groups (Emerson, 1962). Community power is often undistributed among groups within the local community. Ap (1992, p. 683) notes that ‘‘when the form of relation involves an imbalance and is asymmetrical, the disadvantaged host actors’ perceptions will be negative.’’ Previous research confirms Ap’s (1992) proposition and indicates that residents’ perception of impacts is dependent on their perceived level of power in relation to the tourism industry or the level of personal influence over tourism (Hernandez et al., 1996; Lindberg & Johnson, 1997).

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Kayat’s (2002) research indicates that powerful residents had favorable attitudes and were supportive of future development. Madrigal (1993) also notes that positive attitudes was positively related to perceived personal influence over tourism development, but negatively related to perceived business influence over tourism. Based on this discussion, the following hypotheses are developed: Hypothesis 4a. A direct positive relationship exists between residents’ perceived level of power to influence tourism and the perceived benefits of the industry. Hypothesis 4b. A direct negative relationship exists between residents’ perceived level of power to influence tourism and the perceived costs of the industry.

The concept of power is considered to be an important construct influencing overall satisfaction with one’s community. It is akin to the psychological concept of locus of control. Researchers argue that people who perceive themselves as having more control over aspects which affect their lives are most satisfied with their lives (Diener, 1984). Grzeskowiak et al. (2003) suggest that residents’ power to influence institutions is an important determinant of their satisfaction with their community. Their study on the residents of Genesse County, Michigan, confirms that the residents’ perceived power to influence decision-making has an effect on their level of community satisfaction. Powerful residents were found to be more satisfied with their community than less powerful ones. Based on the preceding theoretical and empirical discussion from the literature, the following hypothesis is proposed: Hypothesis 4c. A direct positive relationship exists between residents’ perceived level of power to influence tourism and their overall satisfaction with the community.

Neighborhood Conditions. Satisfaction with one’s neighborhood is a function of one’s satisfaction with the physical, social and economic aspects of neighborhood (Grzeskowiak et al., 2003), including satisfaction with crowding and noise level (Cook, 1988; Miller, Tsemberis, Malia, & Grega, 1980), quality of environment (Lee & Guest, 1983), landscape (Miller et al., 1980), crime level (Lansing, Marans, & Zehner, 1970; Lee & Guest, 1983), street lightning (Dahmann, 1985), and outdoor play spaces (Lansing et al., 1970). Tourism impacts positively as well as negatively on these aspects of neighborhood (Andereck et al., 2005; Lepp, 2007). Huning and Novy (2006, p. 2) note that ‘‘despite its risks and pitfalls, tourism has not only the potential to encourage economic development and physical improvement within a community, but can under certain circumstances, also contribute to neighborhoods’ long term and sustainable regeneration in several ways.’’ Based on the preceding discussion, the following hypotheses are proposed:

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Hypothesis 5a. A direct positive relationship exists between residents’ level of satisfaction with neighborhood conditions and the perceived benefits of tourism. Hypothesis 5b. A direct negative relationship exists between residents’ level of satisfaction with neighborhood conditions and the perceived costs of tourism.

Overall community satisfaction is considered to be a function of residents’ satisfaction with neighborhood conditions (Grzeskowiak et al., 2003). Research suggests that absence of decent neighborhood conditions may have severe consequences on overall quality of life in a community (O’Brien and Ayidiya, 1991). Other researchers (e.g. Campbell, Converse, & Rodgers, 1976) argue that satisfaction with one’s neighborhood conditions is good predictor of overall community satisfaction. The study findings of Grzeskowiak et al. (2003) reveal that satisfaction with neighborhood conditions is positively related to overall satisfaction with one’s community. O’Brien et al. (1989) study confirms that neighborhood conditions have significant effects on the overall quality of a community. Downs (1981) also notes that the quality of neighborhood has important consequences for home owners. Based on the above discussion, the following hypothesis is developed: Hypothesis 5c. A direct positive relationship exists between residents’ level of satisfaction with neighborhood conditions and their overall community satisfaction.

Study Method Study Location. The sample population of the study consisted of residents of Grand-Baie, a tourist resort situated in the north-west coastline of Mauritius. Traditionally a fishing and agricultural village, the place has been able to develop itself into a major tourist hub of the island. Growth of tourism has resulted in development of the region’s infrastructure and services such as road network, drainage and sewage systems, waste water management systems, parking spaces, communication, banking, and other financial services. Corporate social responsibility initiatives by hotels and other tourism-related businesses in the region have also meant that the general environment has been enhanced and recreational opportunities for the local people improved. However, development has also been accompanied by several costs for the region and the local community. Contributing to the negative consequences of tourism is the construction of integrated resorts which are owned and managed by foreigners. Such development has placed severe pressure on existing resources in the region and is known to exclude the residents from the planning and development process (Andriotis, 2008; Freitag, 1994; Wall, 1997).

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The United Nations Environment Program (2006) notes that tourism development in Grand-Baie is poorly controlled and this has led to the deterioration of the natural environment and alteration of the coastline. Bungalows and recreational second homes in the region are often constructed close to beach frontage, restricting residents’ access to beaches (Institute of Environment and Legal Studies, 1998). Alongside with planning authorities, tourism businesses have a major influence on policy-making in the region, often leading to the marginalization of the community. Commercial gains from tourism development in the region tend to go foreign enterprises and local elites and local residents seem to participate only through wage employment and small businesses, reflecting the typical nature of tourism development in island economies like Mauritius (Buhalis, 1999). Traffic congestion, pollution, crime, prostitution, and lack of public and green spaces are other adverse consequences of tourism and related development in the region (Nunkoo & Ramkissoon, in press). These have given rise to conflicts between the industry and residents. Local media often reports on residents’ opposition against hotel development and expansion, construction of recreational second homes, and private bungalows. Sample. Data was collected using a random sampling approach, where every second house in each street of Grand-Baie was chosen. A structured self-administered questionnaire was used to collect data from 800 households in 2008 through to early 2009. Response rate was around 77%, resulting in 616 respondents who completed the survey. Questionnaires with missing data were eliminated from the survey to avoid biased statistical results (Hair, Anderson, Tathman, & Black, 1998). After this process, a total of 559 complete questionnaires were used for further analysis, satisfying the minimum sample requirement of 200 for effective use of structural equation modeling (Anderson & Gerbing, 1988). Structural equation model is designed to evaluate how well a proposed model that contains observed indicators and hypothetical constructs explains or fits the data (Bollen, 1989a, 1989b; Hoyle, 1995). The LISREL 8.72 structural equation analysis package was used for data analysis. Measurement of Constructs. All items were measured on a 1–5 Likert scale. Support for tourism development was measured using four items (X1-X4) borrowed from Oviedo-Garcia et al. (2008) and measured on a scale where 1 represented ‘strongly disagree’ and 5 ‘strongly agree’. Items to measure overall community satisfaction (X5–X8) were adopted from Grzeskowiak et al. (2003). X5 was measured on a scale, where 1 represented ‘very dissatisfied’ and 5 represented ‘very satisfied’. X6 was measured on a scale, where 1 represented ‘very much worsened’ and 5 represented ‘very much improved’. X7 was measured on a scale, where 1 represented ‘much worse than today’ and 5 represented ‘much better than today’. X8 was measured on a scale where 1 represented ‘not desirable at all’ and 5 represented ‘very desirable’.

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Perceived benefits (X9–X13) and costs (X14–X17) were taken from the study by Gursoy and Rutherford (2004) and Gursoy et al. (2002). These items were measured on a scale where 1 represented ‘strongly disagree’ and 5 represented ‘strongly agree’. Trust in tourism institutions was measured by six items (X18–X23) adopted from Grzeskowiak et al. (2003) and Luhiste (2006). Respondents were asked about the extent to which they trust that tourism planning institutions in Grand-Baie look after the interests of the community on a scale where 1 represented ‘no trust at all’ and 5 represented ‘complete trust’. Perceived power to influence tourism development was measured by two items (X24–X25). X24 was measured on a scale where 1 represented ‘no influence at all’ and 5 represented ‘very high influence’. X25 was measured on a scale where 1 represented ‘strongly agree’ and 5 represented ‘strongly disagree’. These items were borrowed from Madrigal (1993). Items to measure satisfaction with neighborhood conditions (X26–X30) were adopted from Grzeskowiak et al. (2003) and Allen et al. (1991) and were measured on a scale with ‘strongly dissatisfied’ at the low end and ‘strongly satisfied’ at the high end of the scale. RESULTS Sample Characteristics A total of 559 responses were analyzed. Three hundred and twenty seven (59%) respondents were male while the rest were female (n = 232, 41%). The age distribution of the sample was as follows: 18–25 (n = 84, 15%), 26–34 (n = 136, 25%), 35–44 (n = 97, 17%), 45– 54 (n = 115, 20%), and 55 years or more (n = 127, 23%). The sample was dominated by those who studied up to secondary level (n = 374, 67%), followed by respondents who benefitted from tertiary education (n = 123, 22%), while the rest studied up to primary level (n = 62, 11%). Three hundred and ninety two respondents were married (70%) while the rest were single (n = 157, 28%) and divorced/separated (n = 10, 2%). The majority of the respondents were employed/ self-employed (n = 436, 78%) while the rest were either retired (n = 53, 9%), unemployed (n = 32, 6%) or were in full time education (n = 38, 7%). Modeling Process and Model Evaluation The analysis was done with the maximum likelihood method of estimation, together with the two-staged process as recommended by Anderson and Gerbing (1988). The measurement model is that component of the general model in which latent variables are prescribed. The measurement model was evaluated and re-specified before the final measurement and structural equation models were examined (Anderson & Gerbing, 1988), implying that before the measurement model was tested each construct in the model was separately analyzed.

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All constructs were paired with one another. Following this step, each construct’s fit was measured separately to ensure that indicators for each construct do not load on another construct. Constructs with unacceptable fits were respecified by deleting indicators that failed to preserve unidimensionality (Anderson & Gerbing, 1988). Afterwards, items that had a coefficient alpha below 0.3 was deleted and omitted from further analysis (Joreskog, 1993). These resulted in the deletion of two items, namely X22 and X30. Table 1 presents the remaining items after the above two steps were performed. A closer examination of the table reveals that item X24’s loading is 1.00, suggesting that it is a perfect match with the factor and explains the factor on its own. Nevertheless, from a scale reliability perspective, it was decided to include item X25 in the measurement scale. The resulting measurement model was tested using confirmatory factor analysis (Anderson & Gerbing, 1988). After this process, the structural model was tested. This model is known as that component of a general model that relates the constructs to the other constructs by providing path coefficients for each of the proposed hypothesis to determine their relative significance. Each parameter value can be evaluated for its respective statistical significance for the hypothesized relationship, while including standard errors and calculated t-values (Bollen, 1989a; Hair et al., 1998). Researchers recommend several indices to evaluate the overall model fit. These are: the chi-square (v2) statistics, the goodness-of-fit index (GFI) (Joreskog & Sorbom, 1989), non-normed-fit-index (NNFI) (Hu & Bentler, 1995), comparative-fit-index (CFI) (Bentler, 1990), incremental-fit-index (IFI) (Mulaik et al., 1989) and the critical N statistic (Hoelter, 1983). Values of GFI, NNFI, CFI, and IFI range from 0 to 1 with a value close to one indicating a good model fit. The parsimony goodness of fit index (PGFI) and the parsimony normed fit index (PNFI) were also used to measure the parsimony of the model. Value of the PGFI and PNFI ranges from 0 to 1 with a value greater than 0.7 indicating a good model fit (Joreskog & Sorbom, 1989). A value of 200 or greater is also suggested as an indication for adequate model fit for the critical N statistics (Hoelter, 1983). In the overall measurement model, the adequacy of the individual items and the composites were assessed by measures of reliability and validity. Three types of reliability measures were used: composite reliability, indicator reliability, and estimated percentage of variance extracted by each construct. Composite reliability is synonymous to a coefficient alpha (Fornell & Larcker, 1981) which indicates the internal consistency of the indicators used to measure a construct. Hair et al. (1998) suggest that a value greater than 0.70 is acceptable for composite reliability. As indicated in Table 1, the composite reliability scores for all the constructs exceeded the recommended level of 0.70. Table 1 also shows that the variance extracted estimate for each construct meets the desirable level of 50% or higher (Fornell & Larcker, 1981). To assess validity, discriminant and convergent validity measures were used. In order to test the discriminant validity of each construct, two models were tested for every possible pair of estimated constructs. The first

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Table 1. Measurement Scale Properties Constructs and indicators

Mean

Support for tourism (SFT) X1 Most important industries for my community X2 Help my community grow in the right direction X3 Continue to play an important economic role X4 Proud that tourist are coming in my community

4.03a 4.03 4.01

Indicator reliability & composite reliability

Variance extracted & error variance

0.71 0.78

0.87b 0.57 0.67

0.62c 0.43 0.33

4.12 3.98

0.95 0.70

0.87 0.55

0.13 0.45

Overall community satisfaction (OCS) X5 Overall satisfaction with quality of life X6 Overall conditions of Grand-Baie X7 Future conditions of Grand-Baie in the years to come X8 Grand-Baie as a desirable place to live

3.86a 3.94 3.67 3.71

0.81 0.92 0.83

0.85b 0.70 0.82 0.72

0.61c 0.30 0.18 0.28

4.13

0.51

0.34

0.66

Perceived benefits of tourism (PBT) X9 Employment opportunities X10 More business for local people X11 Better infrastructure X12 Increase in standard of living X13 Investment opportunities

4.00a 4.25 4.01 3.72 4.07 3.95

0.86 0.93 0.95 0.83 0.85

0.94b 0.76 0.85 0.87 0.72 0.74

0.63c 0.24 0.15 0.13 0.28 0.26

Perceived costs of tourism (PCT) X14 Increase in environmental pollution X15 Increase in alcoholism and prostitution X16 Increase in prices of good and services X17 Increase in the price of land and property

3.82a 4.32 3.07 4.15 3.64

0.82 0.75 0.85 0.77

0.87b 0.70 0.63 0.74 0.65

0.63c 0.30 0.37 0.26 0.35

Trust in tourism institutions (IT) X18 Ministry of Tourism & Leisure X19 Ministry of Environ. & Sustainable Development X20 Ministry of Housing & Lands X21 District Council X22 Village Council X23 Beach Authority

3.79a 3.65 4.21

0.89 0.67

0.90b 0.78 0.49

0.67c 0.22 0.51

0.55 0.87

0.45 0.13

0.70

0.30

Power to influence tourism (PT) X24 Personal influence over decisions related to community tourism development X25 Extent to which tourism businesses had political influence in the area’s decision making process Neighborhood conditions (NC) X26 Behavior of children in your neighborhood X27 Your personal safety in your neighborhood X28 Security against break ins to your home X29 Number of trees in your neighborhood X30 Amount of traffic in your neighborhood a

Construct mean;

b

Composite reliability;

Completely standardized loadings

3.32 0.70 4.19 0.95 Deleted 3.59 0.81 2.91 2.89 2.93

a

b

1.00

0.91 1.00

0.83c 0.00

0.82

0.70

0.30

0.82b 0.74 0.67 0.41 0.49

0.54c 0.26 0.33 0.59 0.51

3.50a 3.76 0.85 3.32 0.78 4.00 0.63 2.95 0.67 Deleted c

Variance extracted.

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model was the constrained model where the correlation parameter was constrained between each pair of constructs to 1.0. The second model was the unconstrained model where the correlation parameter between two constructs was not manipulated (not fixed at 1.00). Afterward, a v2 difference test on the values obtained for the constrained and unconstrained models was performed (Anderson & Gerbing, 1988). Results indicated a significantly lower v2 value for the unconstrained (free) model and this demonstrated that discriminant validity had been achieved (Anderson & Gerbing, 1988; Bogazzi & Phillips, 1982). Convergent validity was assessed from the measurement model by determining whether each indicator’s estimated pattern coefficient on its posited underlying construct factor is significant. Statistically significant large factor loadings indicate convergent validity. Results indicated that all of the estimated pattern coefficients on their posited underlying construct factors were significant at the 0.05 significance level (i.e., each had a t value > ±1.96), indicating that convergent validity has been achieved. The overall fit of the measurement model was as follows: v2(184) = 295.42 (p < 0.001); GFI = 0.96; AGFI = 0.95; NFI = 0.96; NNFI = 0.95; CFI = 0.97; PGFI = 0.73; PNFI = 0. 75; RMR (root mean square) = 0.035; standardized RMR = 0.038; root mean square error of approximation (RMSEA) = 0.030 and the critical N = 373.84. After ensuring the measurement model was acceptable, the proposed structural model illustrated in Figure 1 was tested. The overall fit of the structural model was as follow: v2(192) = 315.42 (p < 0.001); GFI = 0.96; AGFI = 0.94; NFI; 0.95; NNFI = 0.96; CFI = 0.96; PGFI = 0.74; PNFI = 0. 76; RMR = 0.036; SRMR = 0.047; RMSEA = 0.038 and critical N = 352.56. These fit indices suggested that the structural model was acceptable and that the data fits the model well. DISCUSSION Rejected Hypotheses Results indicate support for eleven of the fourteen hypotheses proposed (Table 2). Overall satisfaction with the community was not significant in its effect on the perceived costs (b = 0.02; t = 0.52). Consequently, Hypothesis 2b which proposed a negative relationship between overall community satisfaction and perceived costs was rejected. This finding contradicts the results of Nunkoo and Ramkissoon’s (2010) study which suggest the existence of a direct negative relationship between community satisfaction and perceived negative impacts. Ko and Stewart (2002) and Vargas-Sanchez et al. (2009) also note that community satisfaction is closely related to the perceived negative impacts of the industry. One plausible explanation which can be put forward to explain this contradictory finding is that it is possible that residents of Grand-Baie have developed coping mechanisms. The latter comprise of a set of cognitive and behavioral processes initiated by residents in response to the adverse consequences of tourism

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Table 2. Path Coefficient SFT PBT PCT OCS IT PT NC

b = 0.32; t = 4.52* b = 0.27; t = 3.41* b = 0.38; t = 5.63*

PBT

b = 0.31; b = 0.24; b = 0.33; b = 0.37;

PCT

t = 4.63* t = 3.11* t = 4.53* t = 4.95*

b= b= b= b=

OCS

0.02; 0.22; 0.28; 0.05;

t= t= t= t=

0.52 3.15* 3.29* 0.75

b = 0.45; t = 5.54* b = 0.04; t = 0.63 b = 0.35; t = 4.58*

* Supported hypothesis at p < 0.05; PBT—Perceived benefits of tourism; PCT—Perceived costs of tourism; OCS—Overall community satisfaction; IT—Trust in tourism institutions; PT—Power to influence tourism; NC—Neighborhood conditions; SFT—Support for tourism.

development on the community with the aim reducing the levels of stress and bringing forth desirable emotional states (Duhachek, 2005). Faulkner and Tideswell (1997) argue that in communities with a long history of tourism development (e.g., Grand-Baie), residents can adapt by developing coping strategies. Hypothesis 4c which proposed a direct positive relationship between level of power to influence development and overall community satisfaction was also rejected (b = 0.04; t = 0.63), contradicting the research of Diener (1984) and Grzeskowiak et al. (2003). This contradictory finding can be explained the way the ‘power’ construct has been operationalize in the present study. The latter two research measured power by asking residents about their level of influence on a wider range of community decisions made by the local government, thus, taking a more generic approach to its measurement. However in the present study, power was measured by asking respondents about their level of influence and that of tourism businesses over tourism related decisions only. Consequently, previous studies were able to capture a greater number of nuances related to residents’ power. The issue of power is complicated by the fact that it is often present without being formally and visibility exercised (Stone, 1980). It is possible that if additional measures of power were included in this study, the results could have changed. Hypothesis 5b which proposed a direct negative relationship between satisfaction with neighborhood conditions and perceived cost was also rejected (b = 0.05; t = 0.75). This finding can be explained by the fact that absence of proper neighborhood conditions in a community may not necessarily create psychological problems or impede psychological functioning of community members (Fischer, 1982; O’Brien and Ayidiya, 1991). Supported Hypotheses Hypothesis 1a which proposed a direct positive relationship between perceived benefit and support and hypothesis 1b which proposed a direct negative relationship between perceived cost and support were both supported (b = 0.32; t = 4.52; b = 0.27; t = 3.41). These results

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suggest that residents engage in behaviors congruent with their attitudes. Perceived benefit was found to have a higher influence on support than perceived costs. This confirms the argument of VargasSanchez et al. (2009, p. 384) who note that ‘‘among the perceived effects, those that are positive have a greater influence on attitude toward more tourism development than the negative effects. . .’’ Results support existing research in the field (e.g., Gursoy et al., 2010; Lee et al., 2010; Nunkoo & Ramkissoon, 2010; Oviedo-Garcia et al., 2008). However, these findings contradict the research of Gursoy and Kendall (2006) and Deccio and Baloglu (2002) whose study results indicate an insignificant relationship between perceived cost and support. Two plausible explanations can be put forward to explain the contradictory findings. Firstly, the latter studies considered a host’s support for mega events, suggesting that community responses is dependent on the type and nature of tourism development taking place in an area (Andereck & Vogt, 2000). Secondly, Deccio and Baloglu’s (2002) study focused on nonhost community residents who may have experienced the negative impact to a lesser extent compared to the host residents. A closer examination of Table 1 reveals that the mean scores of the individual items used to measure the ‘perceived benefits’ and ‘perceived costs’ constructs range from 3.72–4.25 to 3.07–4.32 respectively. These findings suggest that Grand-Baie residents perceive tourism as resulting in both benefits as well as costs. The study findings confirm Hypotheses 2a and 2b which proposed a direct positive relationship between overall community satisfaction and benefits (b = 0.31; t = 4.63) and a direct positive relationship between community satisfaction and support (b = 0.38; t = 5.63) respectively. These results contradict those of Ko and Stewart (2002) who note an insignificant relationship between community satisfaction and attitudes to additional tourism development. It also contradicts VargasSanchez et al.’s (2009) study results which suggest that community satisfaction does not influence the perceived benefits. The findings however, support that of Nunkoo and Ramkissoon (2010) who found a statistically significant relationship between community satisfaction and perceptions of positive impacts. The supported path relationship between community satisfaction and perceived benefits and support reinforce the notion that community satisfaction is an important variable in understanding residents’ support and that the construct should be investigated further in future studies. Trust in tourism institutions was found to influence the perceived benefits and cost as well as overall community satisfaction. Consequently, Hypotheses 3a, 3b, and 3c were supported (b = 0.24; t = 3.11; b = 0.22; t = 3.15; b = 0.45; t = 5.54). These findings suggest the importance of institutional trust in influencing attitude and confirm its importance in understanding the exchange between residents and the tourism industry. The findings support the view of other researchers who suggest that the level of trust influence the risks and benefits associated with an activity (Bronfman et al., 2009; Siegrist, 2000; Siegrist & Cvetkovich, 2000). Therefore, further research by other scholars on this concept is recommended since to-date, this has not

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been systematically documented in the literature. The effect of institutional trust on overall community satisfaction was also statistically significant, suggesting that the level of trust residents have in their institution is a good determinant of their overall satisfaction with the community. This finding is in line with those of Grzeskowiak et al. (2003) and Widgery’s (1982). Hypotheses 4a which proposed a direct positive relationship between power to influence tourism and perceived benefits and 4b which proposed a direct negative relationship between the two variables, were both supported (b = 0.33; t = 4.53; b = 0.28; t = 3.29). Residents who perceived themselves as having enough power to influence development viewed the impacts positively. Less powerful residents viewed the industry as resulting in several costs. The findings confirm those of other researchers (Kayat, 2002; Madrigal, 1993). Satisfaction with neighborhood conditions was also found to be a determinant of perceived benefits and overall community satisfaction. Consequently, Hypotheses 5a (b = 0.37; t = 4.95) and 5c (b = 0.35; t = 4.58) were accepted. These findings suggest that residents satisfaction with neighborhood conditions influence the perceived benefits of tourism. Results also suggest that neighborhood conditions remain an important aspect of overall community satisfaction as confirmed by several researchers (Andrews & Whitney 1976; Campbell et al., 1976; Grzeskowiak et al., 2003). Policy Implications The study confirms the importance of understanding the antecedents of support and its complex nature. Results can be useful for policy-makers, developers, and local authorities of the region attempting to gain residents’ support. Findings suggest that the residents’ level of trust in tourism institutions is a determinant of perceived benefits and costs as well as the overall community satisfaction, suggesting its importance in sustaining development. Authorities should segment the community based on their level of trust in tourism planning institutions and conduct an internal marketing program for those with low levels of trust. Research suggests that institutional trust is a complex variable comprising of honesty, integrity, transparency, and competence (Johnson, 1999; Lang & Hallman, 2005). These aspects need to be dealt with openly and promoted in all planning institutions attempting to gain and sustain public trust. Planning institutions in the region should show consideration and sensitivity to the residents’ needs and interests to gain their support. They should refrain from engaging in policy decisions which are in their own interests and benefits but at the detriment of the community. Effective communication, provision of accurate information, and explanations of decisions taken are other effective strategies that tourism authorities and businesses in the region can implement for gaining public institutional trust (Baron & Markman, 2003; Cullen, Johnson, & Sakano, 2000). Authorities should also understand that trust develops

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through reliable performance and gradual expansion of exchanges between the parties (Blau, 1964). Findings also indicate that the perceived level of power by residents influences their perceptions of benefits and costs. Residents who believed that they were able to influence policy decision and that tourism business did not have much influence over decision making had more favorable perceptions than less powerful residents. Therefore, community power is an important tool to assist in the sustainable development of the industry. Empowering the local residents in decision making can be an effective strategy to influence their perceptions and gain their support. Residents should be allowed to participate actively in the decision making process and give a voice in issues affecting their lives. Authorities should adopt a participatory approach to development with the aim of making ‘‘people central to development by encouraging beneficiary involvement in interventions that affect them and over which they previously had limited control and influence’’ (Cooke & Kothari, 2000, p. 5). Providing residents with complete and important information about the benefits and costs of development will allow them to make informed decisions and have more control over the industry. This further empowers them to make meaningful inputs into decision-making processes (Keogh, 1990; Madrigal, 1993). Public participation can also be encouraged by organizing tourism advisory committees, holding public hearings and conducting residents’ surveys (Spencer, 2010). Tourism businesses in Grand-Baie should give priority of employment to residents living within their catchment area. Hiring people from the local work force and providing them with training and marketable skills can also lead to community empowerment. Residents’ satisfaction with their neighborhood conditions was found to have a positive influence on perception of benefits and overall satisfaction with the community. Planners should therefore be sensitive to the impacts of tourism on neighborhood conditions. As part of tourism development strategies, they should invest in improving the physical, social, and economic dimensions of neighborhood in an attempt to improve the overall satisfaction of residents. Policies should be directed at minimizing the adverse socio-cultural and environmental impacts of development on neighborhood conditions. Planning institutions and tourism related businesses in the region can adopt strategies to build a sense of community at the local neighborhood level. To improve residents’ overall satisfaction with the community, the Government of Mauritius can also encourage businesses to engage in corporate social responsibility initiatives to improve the overall community in Grand-Baie. Positive steps toward such initiatives have already been started. The Government of Mauritius requires selected profitable businesses, including hotels to contribute 2% of their profits to corporate social responsibility programs. However, corporate social responsibility initiatives by tourism businesses in Grand-Baie should be based on a ‘bottom-up’ approach rather than a ‘top-down’ approach, where community members are actively involved in deciding the nature and forms of

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such programs. The Government of Mauritius can also consider issuing permits to tourism investors not only based on the market value of their projects, but also based on their proposed corporate social responsibility initiatives. Tourism projects should not only be seen only as an economic development tool, but also as a means of community development. Support for development was found to be influenced by the perceived costs and benefits. This suggests that planners may consider conducting an educational program informing residents about the benefits of development to gain their support. Authorities involved in tourism planning in Grand-Baie should attempt to find out about those residents who view tourism negatively and attempt to change their opinions favorably. It is likely that these residents will oppose any development should they perceive that it results in more costs than benefits. Tourism businesses should also adopt strategies to mitigate the costs of development on the environment, society and the economy. Businesses and public authorities should ensure that development in the area results in more benefits than costs to the local community. Authorities should ensure that the community benefits of development are shared not only by those residing within the borders of development but also to the majority of the residents. CONCLUSION Drawing from the existing literature, a community support model with a series of hypotheses involving fourteen paths was proposed. The model was based on the SET and examined the determinants of support and was tested using the structural equation modeling. Data was collected from the residents of Grand-Baie, Mauritius. The most notable theoretical contribution of the study is that unlike previous research, it delineates the community satisfaction construct in three categories: residents’ trust in local institutions, their level of power to influence development and neighborhood conditions and investigates their effects on overall community satisfaction and attitude in a single model. While previous research did consider the role of residents’ power (e.g., Kayat, 2002; Madrigal, 1993) and community satisfaction (e.g., Ko & Stewart, 2002; Nunkoo & Ramkissoon, 2010; Vargas-Sanchez et al., 2009) on community responses, no model has yet incorporated all these variables simultaneously in an integrative theoretical framework. Another noteworthy contribution of this study is that it extends the use of the SET to include a variable set measuring residents’ level of trust in planning institutions. Existing tourism support models in the literature has failed to consider the role of trust in the exchange between residents and the tourism industry. The supported path relationships between trust and perceived benefits and costs imply that residents do not evaluate an exchange basing themselves only on economic or social rewards, but also on the level of trust they place on the

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partners’ benevolence, ability and integrity (Nguyen & Rose, 2009). Results confirm that trust is a promising relational construct in understanding residents’ attitudes, demanding further investigation by other researchers. Given the paucity of research on this construct in the tourism literature, it is recommended that other scholars researching on community behavior towards the industry incorporate the concept of trust in their theoretical frameworks. The limitations of the study are also evident. The study aggregated the impacts in two categories: benefits and costs. Existing research (e.g., Nunkoo & Ramkissoon, 2009; Pizam, 1978) suggests that impacts can be delineated into perceived positive and negative environmental, social, cultural and economic ones. The model also included only three determinants of perceived benefits and costs. Other community dimensions such as community services, social and family life, and work life could also be included in the model to improve on its predictive power. The model also misses on a variable which researchers consider one of the most important in influencing attitude: the state of the local economy (Gursoy et al., 2002). Given that the focus of this study was to analyze the sub-dimensions of the community satisfaction construct (as established by the literature) and its influence on community support, it was outside the scope of this study to include an economic variable such as the state of the local economy in the model. However, it is possible that if this variable was included, the explained variance in the ‘support for tourism’ construct would have increased. Furthermore, the study did not investigate how trust between the community and institutions develops over time. Finally, the model was tested using data collected from residents of a highly developed destination. This might limit the external validity of the findings. Researchers should attempt to test the model in other destinations positioned at different stages in the tourist area life cycle and experiencing different forms of tourism. It is possible that the direction and magnitude of the relationships might change if it is applied to other destinations. REFERENCES Allen, L. R., Hafer, H. R., Long, P. T., & Perdue, R. R. (1993). Rural residents’ attitudes toward recreation and tourism development. Journal of Travel Research, 31, 27–33. Allen, L. R., Long, P. T., & Perdue, R. (1991). Relational patterns between community dimensions and global measures of community satisfaction. Journal of Rural Studies, 7(3), 331–338. Andereck, K. L., & Nyaupane, G. P. (in press). Exploring the nature of tourism and quality of life perceptions among resident. Journal of Travel Research. doi:10.1177/0047287510362918. Andereck, K. L., Valentine, K. M., Knopf, R. C., & Vogt, C. A. (2005). Residents’ perceptions of community tourism impacts. Annals of Tourism Research, 32(4), 1056–1076. Andereck, K. L., & Vogt, C. (2000). The relationship between residents’ attitudes towards tourism and tourism development options. Journal of Travel Research, 39, 27–36.

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