Week 3 Discussion Sustainability and Government

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Tourism Management 36 (2013) 120e132

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Tourism Management

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Political economy of tourism: Trust in government actors, political support, and their determinants

Robin Nunkoo a,c,*, Stephen L.J. Smith b,1

aDepartment of Management, Faculty of Law and Management, University of Mauritius, Reduit, Mauritius bDepartment of Recreation and Leisure Studies, University of Waterloo, Burt Matthews Hall, 200 University Ave. W. Waterloo ON N2L 3G1, Canada c Faculty of Management, University of Johannesburg, South Africa

h i g h l i g h t s

< Trust in government is a good determinant of political support. < Political performance of government is the strongest predictor of trust. < Social exchange theory is partially supported. < No empirical support for cultural theory of political trust. < Strong empirical support for institutional theory of political trust.

a r t i c l e i n f o

Article history: Received 2 September 2012 Accepted 26 November 2012

Keywords: Political support Trust in government actors Institutional theory of political trust Cultural theory of political trust Social exchange theory Political economy

* Corresponding author. Department of Manage Management, University of Mauritius, Reduit, Maurit

E-mail addresses: [email protected], rnunkoo [email protected] (S.L.J. Smith).

1 Tel.: þ1 519 888 4567; fax: þ1 519 747 1141.

0261-5177/$ e see front matter � 2012 Elsevier Ltd. http://dx.doi.org/10.1016/j.tourman.2012.11.018

a b s t r a c t

This study developed a comprehensive model of residents’ trust in government actors and political support for tourism based on social exchange theory, institutional theory of political trust, and cultural theory of political trust. The model was tested on a sample of 391 residents of Niagara Region, Ontario, Canada, using confirmatory factor analysis and structural equation modelling. Findings suggested that residents’ perceptions of the benefits and costs of tourism and their trust in government actors were significant determinants of political support. Their perceptions of the political and economic perfor- mance of government actors significantly predicted trust in government actors. Interpersonal trust, perceived costs of tourism, and perceived power in tourism decision-making were insignificant deter- minants of trust. The study found partial support for social exchange theory. Cultural theory of political trust was not found to be relevant, while strong support was found for institutional theory of political trust.

� 2012 Elsevier Ltd. All rights reserved.

1. Introduction

The negative consequences of tourism development on local communities have led researchers emphasise on the sustainability of the sector (Choi & Sirakaya, 2006). It is now widely accepted among scholars and destination practitioners that sustainable tourism requires that residents are involved in the planning process of and actively support the sector (Diedrich & Garcia-Buades, 2009; Dyer, Gursoy, Sharma, & Carter, 2007; Latkova & Vogt, 2012; Nunkoo & Ramkissoon, 2011, 2012). Recognizing communities’ central role in tourism, researchers have widely investigated

ment, Faculty of Law and ius. Tel.: þ230 403 7400. @uwaterloo.ca (R. Nunkoo),

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residents’ perceptions of tourism impacts and their support for the sector’s development (e.g. Nunkoo & Ramkissoon, 2011, 2012; Nunkoo & Gursoy, 2012). The premise of these studies rests on the assumption that residents’ perceptions of tourism are at least as important as the actual benefits and costs of the sector, if not more so (McGehee & Andereck, 2004).

Various theories have been used to explain the ways in which residents react to tourism development. While each theory has contributed in its own ways to this area of investigation, social exchange theory (SET) has been the most widely utilized and has made significant contributions to studies on residents’ support for tourism (Gursoy, Chi, & Dyer, 2010). AP (1992) described SET as “a general sociological theory concerned with understanding the exchange of resources between individuals and groups in an interaction situation” (p. 668). Applied to a tourism context, SET posits that residents’ support is determined by their perceptions of the benefits and costs of tourism development. A key concept of

R. Nunkoo, S.L.J. Smith / Tourism Management 36 (2013) 120e132 121

SET is trust among the actors involved in a social exchange rela- tionship (Blau, 1964; Cropanzano & Mitchell, 2005). The funda- mental role of trust in social exchanges is reinforced because exchange of benefits is a voluntary action and entails unspecified future obligations (Konovsky & Pugh, 1994). The persistence and extension of social exchange are based on implicit trust among the actors involved in an exchange relationship (Blau, 1964). In the absence of trust, opportunities for mutually beneficial co- operations among social actors would have to be forgone (Arrow, 1971; Bowles & Gintis, 2002).

The studies by Beritelli (2011) and Beritelli, Bieger, and Laesser (2007) reinforce the need for researchers to consider trust as an important ingredient for cooperation among tourism actors and effective destination management. One of the lacunae of existing studies on community support for tourism is that the majority of them have omitted trust as a key component of SET. This omission needs to be addressed by future studies to ensure that the full potential of SET in explaining community support for tourism is achieved. Also, notwithstanding the contributions of SET to this research area, the theory has been criticized by some researchers (Pearce, Moscardo, & Ross, 1996; Ward & Berno, 2011). SET assumes that individuals are rationale decision-makers, processing informa- tion systematically. However, research from psychology suggests that humans are more likely to be cognitive misers who use mental shortcuts that result in quick but inaccurate solutions instead of engaging in an effortful mental processing (Fredline & Faulkner, 2000; Nunkoo & Ramkissoon, 2009; Pearce et al., 1996). SET is also based on the premise that a person’s knowledge is derived from direct experiences with tourism, when in reality such knowledge is socially derived (Fredline & Faulkner, 2000). Given these limitations, it is important that SET is complemented with other theoretical approaches to investigate community support for tourism to provide new perspectives to this scientific area of investigation.

This paper develops a comprehensive model that predicts resi- dents’ trust in government actors and political support for tourism based on three different theories: SET, institutional theory of political trust (ITPT), and cultural theory of political trust (CTPT). Grounded in a political economy perspective, the study investigates the concept of trust in the context of a social exchange relationship between residents and local government actors involved in tourism development. Political economy suggests that government has a central role in tourism planning and regulation of the sector

Notes: PST: political support for tourism; PBT: perceived benefits o in government actors; PPT: perceived power in tourism; P actors; PPP: perceived political performance of government a

PPT

PEP

PPP

IPT

TGA

PBT

PCT

H8

H7

H4

H3

H5

H9

H10

H11

H12

Fig. 1. The propo

(Bramwell, 2011). Thus, trust is conceptualized as residents’ trust in government actors (also referred to as political trust or citizens’ trust in institutions) involved in tourism development. Addition- ally, the study uses ITPTand CTPT to investigate the determinants of residents’ trust in government actors. Fig. 1 shows the proposed model of the study which was tested on a sample of 391 residents of Niagara Region, Ontario, Canada, using structural equation modelling (SEM).

This paper makes some valuable contributions to existing literature. Despite the centrality of trust in social exchanges (Cropanzano & Mitchell, 2005) and its importance for good governance of the tourism sector (Beritelli, 2011; Beritelli et al., 2007), very little is known about its role in tourism planning and development. Few researchers have considered trust in the context of community support for tourism (e.g. Nunkoo & Ramkissoon, 2011, 2012; Nunkoo, Ramkissoon, & Gursoy, 2012), yet these studies contain some theoretical limitations that need to be addressed. Although Nunkoo and Ramkissoon (2011, 2012) provide valuable insights on the role of trust in fostering community support, the studies are limited because the models tested were developed solely on the postulates of SET. These studies do not provide any insights on the determinants of residents’ trust in government actors in tourism. Nunkoo et al.’s (2012) used ITPT and CTPT to investigate the antecedents of residents’ trust in govern- ment actors. However, the study considered trust as the only determinant of community support for tourism and failed to take into account two important variables of SET (residents’ perceptions of the benefits and costs of tourism) that have been found to be strong predictors of residents’ support in many previous studies (e.g. Ko & Stewart, 2002; Nunkoo & Gursoy, 2012).

The implications of these are that existing research on this topic is based on incomplete theoretical propositions and may be lacking in predictive power. It is therefore important that these studies are enhanced and made theoretically more robust so that a more accurate analysis of residents’ support for tourism is achieved. It is also important thatmore research is carried out on residents’ trust in government actors and its determinants given the paucity of research on this topic in tourism. The study of trust in tourism is more than ever important because several recent studies alert us of declining societal trust and citizens’ trust in government institutions (e.g. Scheidegger & Staerkle, 2011), including those of tourism (Bramwell, 2011). By empirically testing the model illustrated in

f tourism; PCT: perceived costs of tourism; TGA: trust EP: perceived economic performance of government ctors; IPT: interpersonal trust.

PST

H1

H2

H6

sed model.

R. Nunkoo, S.L.J. Smith / Tourism Management 36 (2013) 120e132122

Fig. 1, the study provides new theoretical perspectives on residents’ trust in government actors and their support for tourism. Findings from this study may also have significant influence on the gover- nance and management of tourism. Policy-makers could benefit from a better understanding of residents’ trust in government actors in tourism and their support for the sector’s development.

2. Political economy of government intervention

Political economy is concerned with the political nature of decision-making and with how politics affects choices in a society. It provides an understanding of structures and social relations that form societies in order to evoke social change towards more equitable and democratic conditions (Mosedale, 2011). Political economy offers a useful perspective to study tourism development and government processes (Bramwell, 2011). This approach considers that the state has an influential role in managing and promoting tourism (Wang & Bramwell, 2012; Webster, Ivanov, & Illum, 2011). Government is the principal actor in the political process of tourism development (Bramwell, 2011) and has usually adopted a more interventionist approach in tourism development than in other sectors (Ruhanen, 2013). Government controls the industry through formal ministries, other institutions, legislations, and various programs and funding initiatives (Elliot, 1997), and intervenes in tourism for environmental, political, and economic reasons (Nyaupane & Timothy, 2010). According to Hall (2005), government has seven functions in tourism development: coordi- nation, planning, legislation and regulation, entrepreneurship, stimulation, social tourism, and public interest protection roles.

Traditionally, economic concerns were the principal reasons for governments to intervene in tourism (Bramwell, 1994). Overtime, the negative effects of tourism and local residents’ reluctance to accept development have meant that governments’ roles in the sector have extended beyond economic considerations to address the environmental and social consequences of development. The diffusion of the sustainable development concept in the 1980s has also led governments to assume greater roles and responsibilities in tourism planning (Ruhanen, 2013). Governments now usually attempt to secure a balance between economic priorities, the environment, and the local society in order to gain political support for tourism development (Bramwell, 2011). Political economy suggests that a politically stable relationship between the state and the citizens is important to maintain political legitimacy and effective authority (Purcell & Nevins, 2005) and to ensure the state’s ability to reflect the popular will (Bramwell, 2011). Political legitimacy cannot be achieved without residents’ trust in govern- ment and their support for tourism development.

While political economy is a broad social perspective that scholars and analysts can use to study the motivations, roles, and effects of a state’s activities in tourism development, distribution of tourism benefits among society members, citizens’ trust in government actors, and political support for tourism (Bramwell, 2011; Dredge & Jenkins, 2007; Mosedale, 2011), SET, ITPT, and CTPTenable an empirical testing of the relationships among the key concepts of political economy. More specifically, these theories provide an understanding of the determinants of political trust and how residents’ perceptions of the benefits and costs of tourism and their trust in government actors interact to influence political support for tourism development.

2.1. Political support for tourism

Support is an “attitude by which a person orients himself to an object either favourably or unfavourably, positively or negatively” (Easton, 1965, p. 436). Government requires a certain amount of

political support for its policies to persist or flourish (Gregory & Gibson, 1992). In a tourism context, political economy suggests that it is important for government to maintain legitimacy and influence on governance processes by ensuring that the local pop- ulation supports its policies (Wang & Bramwell, 2012). Residents’ support for tourism is influenced by their perceptions of the benefits and costs of the sector. Tourism development results in investment opportunities, better infrastructure, employment opportunities, more public development, and improvement in the local economy (Latkova & Vogt, 2012; Nunkoo & Ramkissoon, 2011). Tourism also provides opportunities for cultural exchanges (Besculides, Lee, & McCormick, 2002) and increases entertainment opportunities for local people (Andereck & Nyaupane, 2011; Latkova & Vogt, 2012). Several studies report a positive relationship between perceived benefits and support for tourism (Latkova & Vogt, 2012; Nunkoo & Gursoy, 2012; Nunkoo & Ramkissoon, 2011). Based on the preceding discussion, the following hypothesis is proposed:

Hypothesis 1 (H1): There is a direct positive relationship between residents’ perceptions of the benefits of tourism and their political support for the sector’s development.

Development of tourism also results in several costs to local communities that may threaten the legitimacy of government and its political support (Wang & Bramwell, 2012). Tourism increases costs of living and the price of land and housing (Latkova & Vogt, 2012; Liu & Var, 1986); leads to a lack of economic diversification (Jackson & Inbarakan, 2006); and negatively affects a community’s traditional employment patterns (Nunkoo & Gursoy, 2012). Tourism may also destroy the natural environment; increase environmental pollution (Dyer et al., 2007; Nunkoo & Ramkissoon, 2011); cause litter; create traffic congestion (Latkova & Vogt, 2012); increase prostitution in a destination area (Nunkoo & Ramkissoon, 2011): increase vandalism; and change local culture (Dyer et al., 2007). In support of SET, a number of studies empirically demon- strate that a negative relationship exists between residents’ perceptions of the costs of tourism and their support for the sector’s development (e.g. Gursoy et al., 2010; Ko & Stewart, 2002; Nunkoo & Gursoy, 2012; Nunkoo & Ramkissoon, 2011). This discussion led to the following hypothesis:

Hypothesis 2 (H2): There is a direct negative relationship between residents’ perceptions of the costs of tourism and their political support for the sector’s development.

Residents’ perceptions of tourism impacts are not held in isola- tion. A change in the perceptions of one type of impact is likely to influence other types of impacts. Gursoy and Kendall (2006) argued that “themost salient impact is likely to influence the perceptions of all other impacts” (p. 610). Although the relationship between perceived benefits and costs is notwell established in the literature, there is some evidence confirming that interactions exist among residents’ perceptions of the different impacts of tourism. For example, Gursoy and Kendall’s (2006) and Gursoy and Rutherford’s (2004) studies revealed a significant negative relationship between perceived benefits and costs of tourism. Based on the above empirical evidence, the following hypothesis is developed:

Hypothesis 3 (H3): There is a direct negative relationship between residents’ perceptions of the benefits of tourism and their perceptions of the costs of tourism.

2.2. Residents’ perceived level of power

Power is a central concept of SET (Emerson, 1962) and is an underlying theme of political economy (Mosedale, 2011). It is defined as the capacity of individuals to make decisions that affect their day-to-day lives (Johnson & Wilson, 2000). Existing tourism literature considers power as key issue in destination management

R. Nunkoo, S.L.J. Smith / Tourism Management 36 (2013) 120e132 123

and governance (e.g. Beritelli & Laesser, 2011; Beritelli et al., 2007; Reed, 1997). Power gains additional significance because destina- tions comprised of diverse stakeholders influencing or trying to influence the formulation of tourism policy and the ways in which it is implemented (Beritelli & Laesser, 2011; Hall, 1994). All deci- sions affecting tourism development, the nature of government intervention, management of tourism, and community tourism issues emerge from a political process, all of which involve actors in a struggle for power, reflecting different values and priorities (Hall, 2003). Power issues among stakeholders also explain inherent imbalances in destination governance (Beritelli et al., 2007). Usually, the less influential groups are marginalized in tourism development because power relationships among stakeholders are inherent to society, both within local communities and with actors affecting those communities (Holland, 2000; Reed, 1997).

SET posits that the level of power of an actor has a considerable influence on the social exchange process because power deter- mines the ability of the actor to take advantage of the outcomes of tourism development (AP, 1992; Cook & Emerson, 1978). An actor with low level of power is usually negatively disposed towards the exchange relationship AP (1992). Local communities usually have the least influence on tourism planning and governance processes (Moscardo, 2011). Their level of power influences their disposition towards tourism development. For example, a number of studies have demonstrated empirically that residents’ perceived level of power in tourism planning is positively related to their perceptions of the benefits and negatively related to their perceptions of the costs of tourism (Madrigal, 1993; Nunkoo & Ramkissoon, 2011). Contrary to these studies, Latkova and Vogt (2012) did not report any significant relationship between residents’ perceived level of power and their perceptions of tourism. This discussion led to the following hypotheses:

Hypothesis 4 (H4): There is a direct positive relationship between residents’ perceptions of their level of power in tourism development and their perceptions of the benefits of tourism.

Hypothesis 5 (H5): There is a direct negative relationship between residents’ perceptions of their level of power in tourism development and their perceptions of the costs of tourism.

2.3. Trust in government actors

Trust is a relational construct (Markova & Gillespie, 2008) that is inherent to SET (Blau, 1964). Trust between actors (e.g. residents and government) is fundamental in the emergence and mainte- nance of social exchanges between two parties (Cropanzano & Mitchell, 2005). Political trust (i.e. residents’ trust in government) is the belief that the political system or some of it will produce preferred outcomes (in tourism development) even in the absence of constant scrutiny (Miller & Listhaug, 1990). Studies on political trust are driven by the importance of linking citizens to institutions, the desire to achieve good governance, and the need to gain public support for development (Scheidegger & Staerkle, 2011). Political trust is important because it conveys a message to the governing elite whether or not their policy decisions conform to the norma- tive expectations of the governed (Citrin & Luks, 2001).

In any model of destination governance, trust is a key compo- nent of the relationship between individuals and government institutions and is important for consensual decision-making and actions in tourism development (Beritelli et al., 2007). Discussing the importance of public trust in government for a democratic society, Nye, Zelikow, and King (1997) noted that:

If people believe that government is incompetent and cannot be trusted, they are less likely to provide [critical] resources. Without critical resources, government cannot perform well,

and if government cannot perform, people will become more dissatisfied and distrustful of it. Such a cumulative downward spiral could erode support for democracy as a form of gover- nance (p. 4).

A number of studies confirm the significant influence of trust on people’s support for government policies. Nunkoo and Ramkissoon (2012) and Nunkoo et al. (2012) found that residents’ trust in tourism institutions positively influenced their level of support for tourism development. A number of other studies have validated the relationship between trust in government and political support for government policies (e.g. Gabriel & Trudinger, 2011; Hetherington, 2004; Hetherington & Globetti, 2002; Rudolph & Evans, 2005). Based on this discussion, the following hypothesis is developed:

Hypothesis 6 (H6): There is a direct positive relationship between residents’ trust in government actors in tourism and their political support for the sector’s development.

SET postulates that the benefits and costs resulting from a social exchange relationship influence the trust of one actor on the other (Blau, 1964). These benefits/costs can be of either an economic or non-economic nature (Farrell, 2004). In a political context, the outcomes of a social exchange relationship between the govern- ment and citizens influence political trust. Government institutions create policies and in return, they receive trust from those indi- viduals who are satisfied of these policies, and cynicism and mistrust from those who are dissatisfied (Citrin, 1974). Nunkoo and Ramkissoon’s (2012) study demonstrated that residents’ percep- tions of the benefits of tourism positively influenced their trust in government actors while perceptions of the costs adversely influ- enced trust. Hence, the following hypotheses are formulated:

Hypothesis 7 (H7): There is a direct positive relationship between residents’ perceptions of the benefits of tourism and their trust in government actors.

Hypothesis 8 (H8): There is a direct negative relationship between residents’ perceptions of the costs of tourism and their trust in government actors.

3. Institutional determinants of trust in government actors

Researchers have made use of two competing theories to explain the origins of citizens’ trust in government institutions: ITPT and CTPT. ITPT is based on the assumption that trust stems from the extent to which people perceive political institutions to work effectively (Hetherington, 1998). Here, trust is dependent on how people evaluate the performance of institutions with respect to their expectations (Luhiste, 2006; Mishler & Rose, 2001). In tourism development, citizens often hold the government responsible for policy decisions and call upon the state to improve sustainability practices that affect their daily lives (Bramwell, 2011). The performance of government actors in tourism has a direct bearing on how citizens view the government.

3.1. Economic performance of government actors in tourism

Political economy suggests that a key role for the government is intervention to encourage the conditions for capital accumulation and economic expansion (Bevir, 2009). In the context of tourism, government often gives priority to economic growth over envi- ronmental and social concerns (Wang & Bramwell, 2012). Institu- tionalists argue that the economic performance of government institutions is one of the strongest determinants of citizens’ trust (Mishler & Rose, 2001, 2005). Citizens trust government to the extent that its institutions produced desired economic outcomes and meet their expectations in the economic domain (Luhiste, 2006). Government’s inability to deal with economic challenges

R. Nunkoo, S.L.J. Smith / Tourism Management 36 (2013) 120e132124

such as unemployment and poverty impinge on citizens’ trust. Nunkoo et al. (2012) reported that residents’ perceptions of the economic performance of tourism institutions positively influenced political trust. Such a relationship has been validated by several studies in political science (e.g. Mishler & Rose, 2001, 2005; Wang, 2005; Wong, Wan, & Hsiao, 2011). Based on this discussion, the following hypothesis is developed:

Hypothesis 9 (H9)e There is a direct positive relationship between residents’ perceptions of the economic performance of government actors and their trust in those actors.

3.2. Political performance of government actors in tourism

The political performance of government actors covers issues such as extent of corruption among public officials, fair treatment of citizens and protection of their rights in development, and a democratic form of governance (Wong et al., 2011). These dimensions of development are crucial for sustainable and good governance of tourism. Although political economy suggests that government intervenes in tourism to protect societal interests, government is often criticised for being politically unfair to communities because of its undue influence on the tourism policy process (Bramwell, 2011; Ruhanen, 2013), for imposing tourism planning on and marginalising local communities (Moscardo, 2011), and for having hidden agendas (Nyaupane & Timothy, 2010). These factors results in citizens’ poor evaluation of the political performance of government and impinge on their trust (Freitag & Buhlmann, 2009). Nunkoo et al.’s (2012) recent study demonstrated that residents who evaluated the political perfor- mance of government actors in tourism more positively were more likely to trust those actors. Several other studies have validated such a relationship (e.g. Luhiste, 2006; Wong et al., 2011). Hence, the following hypothesis is developed:

Hypothesis 10 (H10) - There is a direct positive relationship between residents’ perceptions of the political performance of government actors and their trust in those actors.

3.3. Power and trust in government actors

Power and trust are inherent to social exchanges and should be considered jointly in any theory that deals with social relations (Cook, Hardin, & Levi, 2005). Power is an important dimension of the political arrangements of institutions. Institutions which are universally oriented and share power in decision-making with citizens generate political trust (Freitag & Buhlmann, 2009). Power inequalities create ground for distrust and block the possibility of trust (Cook et al., 2005; Farrell, 2004). In a tourism context, Nunkoo and Ramkissoon (2012) and Nunkoo et al. (2012) demonstrated empirically that residents’ perceived level of power in tourism positively influenced their trust in government actors. Similar conclusion can be drawn from the research of Oberg and Svensson (2010) and Oskarsson, Svensson, and Oberg (2009). Hence, the following hypothesis is proposed:

Hypothesis 11 (H11): There is a direct positive relationship between residents’ perceptions of their level of power in tourism development and their trust in government actors.

4. Cultural determinants of trust in government actors

4.1. Interpersonal trust

CTPT posits that trust does not originate from within the polit- ical spheres, but outside of it, in the long standing and deeply seeded beliefs about people that are rooted in cultural norms and values in a society (Wong et al., 2011). Cultural theorists assume

that trust is a phenomenon linked to basic forms of social rela- tionships and are shaped by cultural orientations that assign meanings and values to events (Mishler & Rose, 2001; Shi, 2001). Culturalists argue that trust is generated by non-political factors such as interpersonal trust which is the general disposition to trust or distrust in others (Luhiste, 2006). They note that political trust is an extension of interpersonal trust learnt in life, and later projected onto political institutions. Trust starts within the immediate family and eventually extends to include friends, colleagues, neighbours, and political institutions. Nunkoo et al. (2012) reported that inter- personal trust was positively related to residents’ trust in govern- ment actors in tourism. Many other studies in political science validate such an empirical relationship (e.g. Dowley & Silver, 2002; Luhiste, 2006). Based on the preceding discussion, the following hypothesis is developed:

Hypothesis 12 (H12): There is a direct positive relationship between interpersonal trust and residents’ trust in government actors.

5. Research design

5.1. Study location and context

This studywas conducted in Niagara Region, located in Southern Ontario, Canada. The Region is one of the fastest growing areas of Canada. Tourism is a major sector of the regional economy and a major player in the provincial tourism sectore contributing more than 40% of total revenues to Ontario’s overall tourism perfor- mance. A review of existing policy documents and published studies on Niagara Region indicates that although tourism makes significant contributions the local economy, development of the sector also leads to a number of adverse consequences such as conflicts between tourism developers and residents, environmental destruction, marginalization of local people, inadequate public consultation, and opposition to tourism development. Planning authorities in Niagara Region recognize the need for community involvement in the sustainable development of the region and this has been expressed in a number of policy documents (e.g. Regional Municipality of Niagara, 2006, 2009).

5.2. Data collection: online panel

Data were collected from residents of Niagara Region using an online panel provided by TNS Global Marketing Research, Canada. An online panel “consists of people who have registered to occa- sionally take part in web surveys” (Goritz, 2004, p. 411). Online panels are increasingly being used as a mode of data collection for social science research (e.g. Dolnicar, Yanamandram, & Cliff, 2012; Vocino & Polonsky, 2011). Although researchers report some limi- tations with online panels such as under-coverage of the target population, high non-response within the panel, and self-selection bias, online panel data generally do not suffer from higher levels of sample bias than traditional mail surveys and usually display higher reliability than those collected by telephone surveys (Braunsberger, Wybenga, & Gates, 2007). The data requirements in terms of sample frame and size were provided to TNS. The sample frame was the residents of Niagara Region who were at least 18 years of age or older. TNS online panel consists of 3271 residents of Niagara Region. The minimum sample size for this study was determined based on recommendations for SEM.

5.3. Scale development and statistical procedures

Items to measure political support for tourism were derived from Andereck and Vogt (2000). Themeasurement scale for trust in government actors were borrowed from Luhiste (2006) and Shi

Table 1 Exploratory factor analysis (N ¼ 130).

Scale items Factor loadings

Eigen value

% Of variance explained

aPolitical support 1.92 47.89 Hotel development 0.81 Convention and meeting facilities 0.73 Attractions designed to

attract large number of tourists 0.67

Casino development 0.54

bTrust in government actors 2.45 61.21 Trust in tourism decisions

made by local government (LG) 0.85

Trust in local elected officials 0.83 Trust in LG to do what is right in

tourism 0.75

Trust in LG to look after the interests of the community in tourism

0.70

cPerceived benefits 2.70 53.98 Employment opportunities 0.84 Opportunities for local businesses 0.84 More investment 0.75 Development of nature parks 0.65 Preservation of cultural identity 0.55

cPerceived costs 2.56 42.58 Environmental pollution 0.79 Traffic problems 0.75 Litter 0.72 Increase in prices of goods and services 0.61

cPerceived economic performance 2.75 55.04 LG effectively uses tourism to deal

with current economic problems. 0.76

LG effectively uses tourism to deal with future economic problems.

0.76

LG effectively uses tourism to reduce unemployment.

0.76

LG effectively uses tourism to reduce poverty.

0.73

LG effectively uses tourism to take advantage of current economic opportunities.

0.70

cPerceived political performance 2.25 57.27 LG treats residents fairly in the

tourism development process. 0.82

LG ensures that there is an adequate representation of residents in the tourism development process.

0.78

LG is responsive to the needs of the residents in tourism development.

0.72

Corruption and bribe-taking are uncommon among LG officials.

0.67

cPerceived power 1.36 68.22 Personal influence in tourism

planning and development 0.83

Opportunity to participate in tourism planning and development

0.83

bInterpersonal trust: 2.09 52.23 Trust in people you meet for the first time 0.85 Trust in people in general

whom you do not know 0.81

Trust in friends 0.60 Trust in people of a different ethnicity 0.60

a 1 ¼ strongly oppose, 5 ¼ strongly support. b 1 ¼ do not trust them at all, 5 ¼ trust them very much. c 1 ¼ strongly disagree, 5 ¼ strongly agree.

R. Nunkoo, S.L.J. Smith / Tourism Management 36 (2013) 120e132 125

(2001). Measures of perceived benefits and costs of tourism were borrowed from Latkova and Vogt (2012) and Nunkoo and Ramkissoon (2011). Items to measure perceived level of power were based on the study of Hung, Sirakaya-Turk, and Ingram (2011), Latkova and Vogt (2012), and Madrigal (1993). Perceived economic and political performance were measured using items adopted from Luhiste (2006), Mishler and Rose (2001), and Wong et al. (2011). The scale to measure interpersonal trust was borrowed from Delhey, Newton, and Welzel (2011). Many of the measure- ment items were slightly modified to suit the context of the study. Such modifications were contextual rather than conceptual.

To purify the scale items, they were tested empirically using a pilot study sample of one hundred and thirty respondents to whom the survey was administered face-to-face. The criterion used in deciding whether to delete an item from the scale was the item’s corrected item-to-total correlation. Items with an item-to-item correlation score lower than 0.30 were discarded (Churchill, 1979). This process resulted in the deletion of several items from the scales. Then, a separate exploratory factor analysis (EFA) using a principal component methods with varimax rotation was per- formed on each construct. In each EFA, attributes that had factor loadings of lower than 0.40 and attributes that loaded onmore than one factor were eliminated from the analysis as recommended by Chen and Hsu (2001). The items that remained after these steps and the results of the EFA are presented in Table 1. The measurement scales were revised based on these results and the survey was sent to TNS for administration to the residents of Niagara Region. The survey was opened to residents for a period of ten days, between 28th May and 6th June 2012. The data obtained were then sub- jected to a confirmatory factor analysis (CFA) and the model was tested using SEM.

6. Results

6.1. Sample profile and representativeness

Four hundred and eight responses from residents of Niagara Region were obtained from the online panel survey. Seventeen questionnaires were eliminated from the analysis because they contained missing responses. This resulted in a final sample size of 391 respondents. Table 2 presents the profile of the sample. Of the 391 respondents, 65.7% were females and 34.3% were males. Respondents between the age of 55 and 64 represented a slight majority. The sample was dominated by non-minorities (95.6%). Respondents were generally educated; only 4.9% of respondents had less than high school education. The majority of respondents were married (53.7%). To verify the sample representativeness, the sample data were compared to the census data of Niagara Region using chi- square difference test. Although chi-square is mostly used for frequency data, in some cases it can be used on percentage data as explainedbyNesbitt (1966) andWilliams (1974). Results fromTable 2 suggested that the sample data did not differ significantly from the census data in terms of age, ethnicity, level of education, and marital status. However, a significant difference was noted between the gender profile of the sample data and the census data. Nevertheless, taken together, these findings suggested that the survey sample was representative of the population with respect to the majority of variables. However, the gender difference suggests that readers should take this into account when reviewing the results.

6.2. Confirmatory factor analysis

SEM involves the testing of a confirmatory measurement model and a structural equation model. Before testing the overall measurement model, the unidimensionality of each construct was

assessed by CFA using AMOS package (Version 9) with maximum likelihood estimation method. Constructs with unacceptable fits were re-specified by deleting indictors that failed to preserve unidimensionality. The items that remained after this process are

Table 3 Confirmatory factor model (N ¼ 391).

Construct and indicators Standardized loadings

Composite reliability

AVE

Political support for tourism 0.75 0.51 Convention and meeting facilities 0.59 Hotel development 0.77 Casino development 0.78

Trust in government actors 0.83 0.82 Trust in tourism decisions made by LG 0.88 Trust in LG to look after the interests

of the community in tourism 0.92

Trust in local elected officials 0.91 Trust in LG to look after the interests

of the community in tourism 0.91

Perceived benefits 0.89 0.66 Employment opportunities 0.88 Opportunities for local businesses 0.89 More investment 0.76 Development of nature parks 0.70 Preservation of cultural identity 0.85

Perceived costs Traffic problems 0.73 0.86 0.60 Litter 0.87 Increases in prices of goods and 0services 0.64 Environmental pollution 0.85

Perceived economic performance 0.70 0.65 LG effectively uses tourism to take

advantage of current economic opportunities

0.90

LG effectively uses tourism to reduce unemployment

0.88

LG effectively uses tourism to deal with current economic problems

0.73

LG effectively uses tourism to deal with future economic problems.

0.69

Local government effectively uses tourism to reduce poverty

0.81

Perceived political performance 0.87 0.72 LG treats residents fairly in the tourism

development process 0.86

LG ensures that there is an adequate representation of residents in the tourism development process

0.84

LG is responsive to the needs of the residents in tourism development

0.85

Perceived power 0.84 0.72 Opportunity to participate in tourism

planning and development 0.81

Personal influence in tourism planning and development

0.88

Interpersonal trust 0.84 0.65 Trust in your friends 0.83 Trust in people of an ethnicity

different to your own 0.92

Trust in people in general whom you do not know

0.64

Table 2 Sample profile and representativeness.

Variables Sample data

Census data

Chi-square difference

Gendera (N ¼ 391) Male 34.3% 48.39% c2 (1) ¼ 4.09; p ¼ 0.04* Female 65.7% 51.61%

Agea (N ¼ 391) 18e24 years old 4.3% 9.01% c2 (6) ¼ 8.91; p ¼ 0.18 (ns.) 25e34 years old 8.2% 10.58% 35e44 years old 16.6% 12.21% 45e54 years old 19.7% 15.84% 55e64 years old 32.2% 14.18% 65e74 years old 14.6% 9.68% 75e84 years old 4.3% 6.45%

Ethnicityb (N ¼ 383) Non-minorities 95.6% 93.74% c2 (1) ¼ 0.34; p ¼ 0.56 (ns.) Visible minorities 4.4% 6.26%

Level of educationb (N ¼ 391) Less than high school 4.9% NA c2 (3) ¼ 2.51; p ¼ 0.47 (ns.) High school 37.1% 29.93% Apprenticeship 6.6% 9.85% College 33.0% 20.34 University 18.4% 15.96

Marital statusb (N ¼ 391) Widowed 4.9% 7.73% c2 (4) ¼ 3.73; p ¼ 0.44 (ns.) Single 17.6% 28.76% Common-law 9.2% 7.07% Married 53.7% 51.89 Divorced/separated 14.6% 11.62%

*Significant at p < 0.05; NA: Data not available. a Based on 2011 census figures provided by Statistics Canada (2012). b Based on 2006 census figures provided by Statistics Canada (2007). More recent

statistics were not available for this category.

Table 4 Fit indices of the measurement model.

Fit indices c2 RMSEA TLI GFI AGFI CFI NFI IFI

Values 780 (349) p < 0.001 0.05 0.93 0.97 0.94 0.94 0.90 0.94

R. Nunkoo, S.L.J. Smith / Tourism Management 36 (2013) 120e132126

presented in Table 3. The resulting measurement model was tested using CFA and evaluated based on a number of fit indices. c2 was used as the first fit index. However, because c2 is very sensitive to sample size (Bagozzi & Yi, 2012), other fit indices were used. These included root mean square error of approximation (RMSEA), goodness of fit index (GFI) comparative fit index (CFI), normed fit index (NFI), incremental fit index (IFI), and TuckereLewis index (TLI). Values for GFI, CFI, NFI, TLI, and IFI range from 0 to 1, with values greater than 0.90 indicating a good model fit (Hair, Black, Babin, & Anderson, 2010). Value of RMSEA should be less than 0.06 for a model to have a good fit (Bagozzi & Yi, 2012). Results of the measurement model evaluation are presented in Table 3 and indicated that the model was a good fit to the data: c2(349) ¼ 780 (p < 0.001); RMSEA ¼ 0.05; TLI ¼ 0.93; GFI ¼ 0.97; AGFI ¼ 0.94; CFI ¼ 0.094; NFI ¼ 0.90; IFI ¼ 0.94 (Table 4).

The measurement model was further evaluated for its reliability and validity. Reliability of measurement models should also be assessed by the composite reliability and average variance extrac- ted (AVE) of each construct. Values of composite reliability and AVE should be 0.70 or greater and 0.50 or greater, respectively. In addition, an indicator is considered to be reliable if its loading score is at least 0.50 or above (Bagozzi & Yi, 2012). As indicated in Table 3, the composite reliability and AVE scores for each construct were above the recommended threshold of 0.70 and 0.50 respectively. Also, the loading scores of each indicator were well beyond the recommended value of 0.50. These results suggested that the measurement model was reliable.

The validity of the measurement model is usually assessed by convergent validity and discriminant validity. Convergent validity is determined by examining the AVE value which should be 0.50 or

Table 6 Fit indices of the structural model.

Fit indices c2 RMSEA TLI GFI AGFI CFI NFI IFI

Values 844.94 (359) p < 0.001 0.05 0.93 0.96 0.93 0.94 0.90 0.94

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higher (Hair, Sarstedt, Ringle, & Mena, 2012). As shown in Table 3, the AVE scores for all constructs were greater than 0.50. Discrimi- nant validity is assessed by comparing the squared correlation between a pair of constructs against the AVE for each of the two constructs (Fornell & Larcker, 1981). Table 5 shows that discrimi- nant validity was achieved because the AVE for each construct was higher than the squared correlations between the construct and other constructs in the model (Fornell & Larcker, 1981).

6.3. Structural model and hypotheses testing

Once it was ensured that the measurement model had good fit and was reliable and valid, the structural model was tested and evaluated. Results are presented in Table 6 and suggested that the structural model was a good fit to the data: c2(359) ¼ 844.94 (p < 0.001); RMSEA ¼ 0.05; TLI ¼ 0.93; GFI ¼ 0.96; AGFI ¼ 0.94; CFI ¼ 0.94; NFI ¼ 0.90; IFI ¼ 0.94. Fig. 2 shows the tested SEM with beta coefficients and explained variance in the dependent vari- ables. As illustrated in the figure, eight of the 12 proposed hypotheses were supported by the SEM results. The model explained 54% and 41% of the variance in trust in government actors and in political support for tourism respectively. Therefore, the proposed model can be assumed to sufficiently predict residents’ trust in government actors and their political support for tourism.

7. Discussion of results

This study tested a model that predicted residents’ trust in government actors and their political support for tourism. H1 that proposed a direct positive relationship between perceived benefits and political support and H2 that proposed a direct negative relationship between perceived costs and political support were both supported (b ¼ 0.53, t ¼ 7.58; b ¼ �0.17, t ¼ �3.05). From a theoretical perspective, these results provide support for SET. Findings are also congruent with those of Gursoy and Rutherford (2004), Latkova and Vogt (2012), Nunkoo and Ramkissoon (2011), Nunkoo and Gursoy (2012). A closer look at the beta coefficients in Fig. 2 suggested that perceived benefits of tourism had the strongest influence on political support (0.53 vs. �0.17). This finding provides support to Vargas-Sanchez, Plaza-Mejia, and Porras-Bueno (2009) who noted that “perceptions of the positive effects of tourism is the variable that most strongly and with a direct relationship, conditions the attitudes towards the devel- opment of tourism” (p. 466).

H3 that postulated a direct negative relationship between perceived benefits and perceived costs was supported (b ¼ �0.21, t ¼ �3.62). This result suggests that residents’ perceptions of the different categories of impact are not mutually exclusive. Themost salient impact is likely to influence perceptions of all other impacts. In the context of the present study, the more Niagara’s residents perceived tourism to result in benefits, the less they were likely to perceive the sector to result in costs. This finding is

Table 5 Discriminant validity results.

PST TGA PBT PCT PPT PEP PPP IPT

PST 0.51 0.35 0.61 �0.29 0.16 0.09 0.16 0.21 TGA 0.82 0.35 �0.07 0.35 0.63 0.35 0.08 PBT 0.66 �0.22 0.12 0.17 0.12 0.26 PCT 0.60 �0.08 0.07 �0.16 �0.15 PPT 0.72 0.34 0.47 0.21 PEP 0.65 0.34 0.02 PPP 0.72 0.05 IPT 0.65

consistent with Gursoy and Kendall (2006), Gursoy and Rutherford (2004), and Gursoy et al. (2010) whose study results suggested the existence of interactions among perceived benefits and perceived costs of tourism.

H4 that proposed a direct positive relationship between residents’ perceptions of their level of power and their percep- tions of the benefits of tourism was supported (b ¼ 0.15, t ¼ 2.67). This result is consistent with those of Madrigal (1993) and Nunkoo and Ramkissoon (2011, 2012) whose findings suggested that residents who perceived that they had strong influence in tourism decision-making were more likely to view tourism positively compared to those who had less power. The positive relationship between perceived level of power and perceived benefits of tourism may be explained by the fact power deter- mines an individual’s ability to benefit from an exchange (Ap, 1992). H5 that proposed a direct negative relationship between residents’ perceived level of power in tourism and their perceptions of the costs of tourism was rejected (b ¼ �0.07, t ¼ �1.26). This finding supports the results of Latkova and Vogt (2012), but contradicts those of Nunkoo and Ramkissoon (2011, 2012) who reported a significant negative relationship between the two constructs.

Results provided support for H6 that proposed a positive relationship between residents’ trust in government actors and political support (b ¼ 0.15, t ¼ 2.85). This finding is consistent with the results of recent studies of Nunkoo and Ramkissoon (2012) and Nunkoo et al. (2012). The results also lend support to Beritelli’s (2011) assertion that cooperative behaviour is not solely based on economic considerations, but also on relation- based items such as trust among tourism actors in a destina- tion. Our results suggest that Niagara residents who trust local government are convinced that government leaders will act in the interests of the community and will behave honestly and fairly even if they are not continually scrutinized. For local government leaders, political trust contributes to reducing transaction costs because they need to make lower efforts to induce a trusting than distrusting public to conform to political decisions related to tourism development. However, the down- side of this is that local government actors may easily gain political support from residents who trust them even if they choose to implement unpopular tourism policy options, although they are also likely to meet with opposition from distrusting citizens. In general, the result suggests that people need to trust local government to support its policies and strategies as confirmed by several empirical studies (e.g. Gabriel & Trudinger, 2011; Hetherington & Globetti, 2002; Hetherington & Husser, 2012; Rudolph & Evans, 2005).

H7 that proposed a direct positive relationship between resi- dents’ perceptions of the benefits of tourism and their trust in government actors was supported (b ¼ 0.21, t ¼ 5.05). Local government actors in Niagara Region discharge their political obligations to local communities by providing them with tourism benefits that in turn help to foster trust among residents. Our results suggest that political trust can develop when government actors offer incentives and benefits that encourage people to act in collaboration (Freitag & Buhlmann, 2009). The finding confirms the study of Nunkoo and Ramkissoon (2012) that suggested perceived benefits of tourism positively influenced residents’ trust in government actors. The result is also consistent with the arguments

Notes: PST: political support for tourism; PBT: perceived benefits of tourism; PCT: perceived costs of tourism; TGA: trust in government actors; PPT: perceived power in tourism; PEP: perceived economic performance of government actors; PPP: perceived political performance of government actors; IPT: interpersonal trust. * p < .01; ** p < .001; Broken arrow indicates an insignificant path

PPT

TGA

PCT

PBT

PST

PPP

IPT

PEP

= .53**

= .17*

= .15*

= .21**

= .03

= .00

= .47**

= .27**

= .02

= -.21**

= - .07

= .15*

R2 = .41R2 = .54

R2 = .02

R2 = .05

Fig. 2. The tested structural equation model with b coefficients and R2 values.

R. Nunkoo, S.L.J. Smith / Tourism Management 36 (2013) 120e132128

of social exchange theorists who note that when social exchange results in positive economic and social outcomes, these increase the partner’s trust in each other (Blau, 1964).

H8 that postulated a direct negative relationship between resi- dents’ perceptions of the costs of tourism and their trust in government actors was rejected (b ¼ 0.03, t ¼ 0.62). This result contradicts that of Nunkoo and Ramkissoon (2012) who reported a significant negative relationship between perceived costs of tourism and residents’ trust in government actors. While contextual differences may explain the contradictory findings, the non- significant relationship between perceived costs and trust can be theoretically explained. Social exchange theorists note that the presence of risks and costs in an exchange relationship may not necessarily impede trust (Ekeh, 1974). Researchers argue that in some cases, risks and costs resulting from a social exchange rela- tionship are essential to development of trust. Institutional policies and their conflict resolution mechanisms that minimize these costs act as catalysts for development of political trust (Freitag & Buhlmann, 2009). Thus, it may be possible that residents of Niagara Region based their trust on the extent to which local government is able to effectively dealwith the adverse consequences of tourism development. The costs of tourism on local communities serve as a basis for residents’ judgement rather than impede on their trust, explaining the insignificant result noted in this study.

Results indicated support for H9 that proposed a positive rela- tionship between residents’ perceived economic performance of government actors and their trust in those actors (b ¼ 0.26, t ¼ 3.93) and for H10 that postulated a positive relationship between perceived political performance of government actors and trust (b ¼ 0.47, t ¼ 6.38). These results suggest that the extent to which local government actors is perceived to be effective in using tourism to deal with economic problems and enshrines fairness, justice, incorruptibility, and transparency in tourism development as core norms of communal living has a strong bearing on trust (Delhey & Newton, 2005). Findings from this study corroborate those of Nunkoo et al. (2012) and those reported by political scientists (e.g. Luhiste, 2006; Mishler & Rose, 2001, 2005; Wong et al., 2011). While the general agreement among political scien- tists is that economic and political performance of government are

the primary sources of political trust (Mishler & Rose, 2001; Wong et al., 2011), economic performance is viewed as a stronger predictor of trust (Mishler & Rose, 2005). However, interestingly, our results suggest otherwise. A closer look at the beta values indicates that residents’ perceptions of the political performance of government actors in tourism have the strongest effect on trust.

The difference in findings may be attributed to the specific characteristics of the tourism sector in general as well as to the politics of tourism in Niagara Region. Governments have usually been criticized for adopting top-down tourism planning and decision-making (Dredge & Jenkins, 2007), for achieving self- serving outcomes that are against the interests of local people (Bramwell, 2004), and for undermining and marginalizing resi- dents in tourism development (Moscardo, 2011). Existing tourism policy documents on Niagara Region suggest that these challenges are inherent to tourism development in the region. Given that political performance of government measures the extent of universalism in decision-making and the extent to which local government enshrines fairness in tourism, it is not surprising to note that residents’ perceptions of the political performance of government actors have a very strong bearing on political trust.

H11 that proposed a direct positive relationship between perceived power and trust was rejected (b ¼ 0.02, t ¼ 0.40). This finding contradicts those of Nunkoo and Ramkissoon (2012), Nunkoo et al. (2012), and Oberg and Svensson (2010) who re- ported a significant relationship between power and trust. The contradictory findings can be theoretically justified. Some researchers note that the effect of power on trust is context specific (Olekalns & Smith, 2006). This is probably why Oberg and Svensson (2010) argued that the relationship between power and trust is expressed with more nuances than just an obvious positive relationship in existing literature. While disparities in power may influence the way in which the proceeds of trust-based coopera- tion are distributed, they will not necessarily prevent trust from arising (Farrell, 2004). Supporting the argument of Farrell (2004), Oberg and Svensson (2010) noted that when an actor (e.g. resi- dents) has relatively low or no power at all vis-à-vis another actor (e.g. government), there is no need for trust to engage in cooperation.

R. Nunkoo, S.L.J. Smith / Tourism Management 36 (2013) 120e132 129

H12 that proposed a direct positive relationship between interpersonal trust and political trust was rejected (b ¼ 0.00, t ¼ 0.11). This finding is not surprising as it is consistent with several studies that found interpersonal trust to be a weak deter- minant of political trust (e.g. Mishler & Rose, 2001). However, the result goes against Putnam (1993) who conceived a positive rela- tionship between interpersonal trust and political trust and Luhiste (2006) who demonstrated empirically a significant positive rela- tionship between the two constructs. There are a number of well- rehearsed arguments that explain the insignificant relationship and inconsistent findings. Fukuyama (1999) argued that interper- sonal trust is culturally determined. He noted that while a degree of trust among individuals is common in all societies and cultures, the radius of trust (i.e. the extent to which individuals extend their interpersonal trust to institutions) varies widely across cultures. While in some cultures citizens trust only people who they know well, in others, trust extends beyond the immediate family to include fellow citizens, but exclude political institutions. In still other societies, the radius of trust is extended to the political domain as well. In other instances, interpersonal trust has been found to negatively influence political trust (Campbell, 2004). Thus, it appears that interpersonal trust influences political trust only in certain circumstances, and in the present research, interpersonal trust among Niagara residents does not have a spill-over effect on the political context. This is probably because in post-industrial societies (e.g. Canada) the “thick” trust previously present among individuals or groups, has now been transformed into “thin” trust that is not extended to political institutions (Mishler & Rose, 2001).

7.1. Implications

Findings from this study have important implications for local government attempting to promote the sustainability of the tourism sector in Niagara Region and for officials to better under- stand the influences on public support for tourism initiatives or potential “hot buttons” with taxpayers. Results suggest that polit- ical support for tourism is positively related to residents’ percep- tions of the benefits of tourism and negatively related to their perception of the costs that they as taxpayers must bear. Thus, it is important that local government ensures that tourism develop- ment results in more benefits than costs for local communities in Niagara Region. The benefits of tourism should also be distributed more equally across residents of different social spectrum and municipalities of Niagara Region. Education, awareness, and internal marketing campaigns that advocate the community benefits of tourism fuel greater support for tourism and generate positive views towards the sector among local residents.

Policy-makers should also recognise that residents should trust government actors in tourism to support their policies. Trust facilitates cooperation among tourism actors in a destina- tion (Beritelli, 2011; Beritelli et al., 2007). Our findings suggest that trust can be developed if government actors improve their political performance in tourism development. This can be ach- ieved if local government shows sensitivity and consideration to residents’ needs in tourism planning and development. They should refrain from engaging in policy decisions that are in the interests of powerful stakeholders at the expense of local communities. Residents are likely to trust government actors if they are treated fairly in tourism development (Rothstein, 2000). There should also be a high standard of tourism leadership by local government designed to create and reinforce the centrality of public interests in tourism above the self-interest of politicians and societal elites. Trust can also be promoted through proper exchange of information between local communities and government actors. Information exchange does not only relate to

intensity or contact ease, but should also include explanations about tourism policy decisions and other issues in the tourism sector (Beritelli, 2011).

Residents’ perception of the economic performance of govern- ment actors was also a good predictor of trust. Local government should be viewed by residents as being effective in delivering economic benefits to local communities and in dealing with current and future economic challenges facing Niagara Region. At present, local government lacks a clear mandate for tourism development in the Region (Graveline, 2011). Thus, local government should rede- fine its roles and responsibilities in tourism planning and devel- opment to be able to deal effectively with current and future economic challenges. This can be achieved if local government works in collaboration with other stakeholders such as Niagara Economic Development Corporation and The Niagara Parks Commission, and utilizes all means and support that are available at the provincial level, including the recently established Niagara Regional Tourism Organization model. These players are likely to strengthen the ability of local government to take full advantage economic opportunities in tourism and deal with emerging challenges.

7.2. Limitations and direction for future research

Like any other research, this study is not without caveats. Although the study sample was generally representative of the census population, the survey method employed (online panel) may introduce some element of bias in the findings. Some studies found considerable differences in sample characteristics and statistical results when analysing data collected by mail and web- based surveys such as online panels (e.g. Cole’s, 2005; Duffy, Smith, Terhanian, & Bremer, 2005). On-line respondents are also usually more politically active than mail survey respondents (Duffy et al., 2005). These differences mean that future researchers should test the study’smodel using responses collected from other types of survey methods to validate the research findings and to note similarities and differences in results.

There are also some limitations with measuring citizens’ perceived performance of government institutions that readers should take into account. Nye et al. (1997) noted that:

People say they are dissatisfied with the performance of government, and in a democracy that is one important measure. But performance is more complicated than it first appears. Performance compared with what? Expectations? The past? Other countries? Other institutions such as business or nonprofit organizations? And what are people willing to pay for government efficiency, either in dollars or other values? A federal systemwith separated institutions sharing powers is not designed to optimize performance. Do peoplewant this change? Probably not. Would they if new problems like terrorism produced a “domestic Pearl Harbor”? Perhaps (p. 8).

Also, citizens’ knowledge about the roles and functioning of institutions may not always be reliable (Van de Walle, Van Roosbroek, & Bouckaert, 2008). Poor knowledge and lack of familiarity with government may result in low standard of judge- ments as to the achievements and the abilities of its institutions to deal with economic and political problems. In the particular context of tourism development, some researchers note that local communities are not able to fully understand the sector and its role in economic development (Timothy, 1999). This may in turn adversely influence residents’ general attitudes towards govern- ment actors involved in tourism development and planning and may result in poor evaluation of the economic and political performance of those actors in tourism. Thus, it is important that

R. Nunkoo, S.L.J. Smith / Tourism Management 36 (2013) 120e132130

future studies attempt to develop and usemore objective indicators to evaluate performance of government institutions.

The research investigated trust and power issues in the context of a tourism social exchange relationship between residents and government actors only. In reality, the tourism sector comprises several other actors such as private stakeholders (e.g. accommo- dation businesses, transport operators, attractions, hotels, inves- tors, etc.) and successful implementation of sustainable tourism and good governance requires the cooperation of all those actors (Vernon, Essex, Pinder, & Curry, 2005). These various stakeholders have varying levels of power on tourism planning decisions and on governance processes affecting tourism development, with some groups in society having relatively more influence than others (Dredge & Jenkins, 2007; Hill, 1997). Power asymmetries among stakeholders may result in conflicts around tourism development and governance (Bramwell & Lane, 2011; Beritelli & Laesser, 2011). Residents may also exhibit different levels of trust in private tourism actors in comparison to government institutions involved in tourism development (Nunkoo et al., 2012). Thus, it is important for future researchers to expand the scope of this study and consider investigating trust and power among a wider range of tourism stakeholders.

Finally, because the study has been carried out in a society located in an established democracy, its findings may have limited applicability to other economies. Webster et al. (2011) adopted O’Neil’s (2007) view that there are four fundamental types of political economy (liberalism, social democracy, communism, and mercantilism), each based on a different assumption of the rela- tionship between the market and the state, to explain tourism development policies and processes in different economies. Corroborating Webster’s et al. (2011) distinction among different economic systems that govern tourism development, Bramwell and Lane (2011) noted that roles of government in tourism develop- ment and tourism governance processes are context specific and vary across different political contexts. Such differences mean findings from this study may not be entirely relevant to other political economies, for examples those operating under commu- nism or mercantilism regimes. Future research should be con- ducted in other societies that operate under different political economy systems to validate the results of this study.

8. Conclusion

This study tested a political support model based on three different theories: SET, ITPT, and CTPT. Some of the study’s findings reinforce the results of previous research. The study also provides new theoretical perspectives on the determinants of residents’ trust in government actors and their political support for tourism. The study found SET to be partially relevant because level of power was not found to be a significant predictor of perceived costs, while the latter had an insignificant relationship with trust. CTPT was also not relevant in this research because interpersonal trust was found to be an insignificant determinant of residents’ trust in government actors. In contrast, ITPT was found to be very relevant in explaining trust. An important lesson for researchers and tourism planners is that trust in government actors in tourism is primarily influenced by the political and economic performance of those actors. Furthermore, destination managers should also recognize that residents are likely to support policies related to tourism if they trust government.

The research suggests that residents’ trust in government actors and their level of political support for tourism are complex issues that are determined by several factors. A single theory is unlikely to provide a comprehensive understanding of residents’ trust and political support for tourism development. Based on the results of

this research, future researchers are urged to avoid using a single theoretical perspectivewhen investigating public trust and support for tourism development and planning. Adopting more than one theoretical perspective in such studies is likely to provide a broader and deeper analysis of findings, prevent premature acceptance of plausible explanations, increase confidence in developing concepts or constructs in theory development, and reduce potential biases in and improve credibility of research findings. Overall, the findings suggest trust is a key ingredient of a democratic and sustainable development of tourism and the concept should be investigated further by tourism researchers.

Acknowledgement

The authors would like to thank TNS Global Marketing Research, Canada, for collecting the data used for this study using its online panel.

Appendix A. Supplementary data

Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.tourman.2012.11.018.

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Robin Nunkoo, Ph.D is a Senior Lecturer in the Depart- ment of Management at the University of Mauritius and a visiting Senior Research Fellow in the Faculty of Management at the University of Johannesburg, South Africa. He obtained his PhD from University of Waterloo, Canada. He also holds an M.Phil from University of Mauritius; an MA Tourism Management and an MA Development Administration, both from University of Westminster, UK; and a BA Economics from University of Mumbai, India. He has research interests in political economy, public trust in government institutions, and community support for tourism. He has articles in such journals as Annals of Tourism Research, Tourism Management, Journal of Sustainable Tourism, and Journal

of Hospitality and Tourism Research.

Stephen Smith, Ph.D is a Professor in the Department of Recreation and Leisure Studies at the University of Waterloo. His research interests include methodology, philosophy of science, and knowledge management in tourism. He has published widely in Annals of Tourism Research, Journal of Travel Research, and Tourism Management. He serves as a consultant for numerous local, provincial, and national agencies, particularly in the area of tourism product development and destination management.