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A structural equation model of residents’ attitudes for tourism development
Tourism Management 23 (2002) 521–530
A structural equation model of residents’ attitudes for tourism development Dong-Wan Koa,*, William P. Stewartb b
a Division of Tourism Science, Kyonggi University, San 94-6, Yiui-Dong, Paldal-Gu, Suwon-Si, Kyonggi-Do 442-760, South Korea Department of Leisure Studies, University of Illinois at Urbana-Champaign, 104 Huff Hall, 1206 S. Fourth Street, Champaign, IL 61820, USA
Received 3 July 2001; accepted 4 January 2002
Abstract This study tests the structural equation model between residents’ perceived tourism impacts and attitudes toward host community. The model consisted of five latent constructs and nine path hypotheses and is based upon 732 mailback questionnaires returned by residents of Cheju Island, Korea, a major domestic tourism destination. It was found that residents’ ‘community satisfaction’ was closely related to ‘perceived positive’ and ‘perceived negative’ tourism impacts. These constructs were directly causing ‘attitudes toward additional tourism development’. But the hypothesized path relationships between ‘personal benefits from tourism development’ and the constructs of ‘perceived negative tourism impacts’ and ‘overall community satisfaction’ were rejected. In conclusion, community satisfaction was influenced by perception of tourism impacts, and may be useful in planning for additional tourism development. r 2002 Elsevier Science Ltd. All rights reserved. Keywords: Tourism impacts; Overall community satisfaction; Residents’ perception and attitudes
1. Introduction Tourism development is widely viewed as an important set of economic activities to enhance local economies. Many studies have suggested that development and promotion of tourism is a source of new employment, revenues, additional tax receipts, foreign exchange benefits, and enhances community infrastructure that will, in turn, attract other industries (Lankford & Howard, 1994). Until recently, the development and promotion of the tourism industry has been widely accepted as a positive economic step, especially in less developed countries (Cooke, 1982). The term ‘tourism impact’ has been gaining increasing attention in the tourism literature. A number of studies in recent years have examined host residents’ perception of the impact of tourism development on their community, and it continues to be an important issue. A major reason for rising interest has been the increasing evidence that tourism development leads not only to *Corresponding author. Tel.: +82-31-249-9509; fax: +82-31-2499503. E-mail addresses: [email protected] (D.-W. Ko), wstewart @uiuc.edu (W.P. Stewart).
positive, but also has the potential for negative, outcomes at the local level (Lankford & Howard, 1994). Liu and Var (1986) noted that tourism development is usually justified on the basis of economic benefits and challenged on the grounds of social, cultural, or environmental destruction. Furthermore, the economic benefits traditionally associated with tourism development are now being measured against its potential for social disruption (Cooke, 1982). Huang and Stewart (1996) indicated that tourism development may change residents’ relationships to one another and to their community. It is generally felt that the perception and attitudes of residents toward the impacts of tourism are likely to be an important planning and policy consideration for successful development, marketing, and operation of existing and future tourism programs (Ap, 1992). Although many studies have been performed to identify residents’ perception of tourism impacts and attitudes toward tourism, just a few have assessed relationships between tourism development and community satisfaction. To date, little research has examined the relationships between residents’ perceived impacts of tourism on their community and attitudes toward their own community. Residents must perceive
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tourism in overall positive terms to sustain development of tourism programs. In this context, relationships between residents’ perception of tourism impacts and community satisfaction are an important, yet not well understood, area of research. A significant portion of the social impact of tourism literature suggests that stakeholder involvement and community-based planning should be a part of the early stages of tourism development (Jamal & Getz, 1995). It has been argued that when residents are involved in the planning process, then tourism development will be socially responsible and social impacts will be perceived as appropriate by the host community (Robson & Robson, 1996). However most studies directed at residents’ perceptions of tourism and community-based planning have been conducted in the west: Canada (e.g., Ritchie, 1993), the US (e.g., Ap & Crompton, 1993), the UK (e.g., Robson & Robson, 1996), or Australia (e.g., Brown & Giles, 1994). Whether or not community involvement effects social impacts within Asian countries is still an open point that has yet to be fully examined. Currently, there is limited understanding of the relationships between residents’ perception of tourism impacts and community satisfaction. The lack of such research limits the current literature on understanding residents’ behavior toward the impacts of tourism (Ap, 1992). For a tourism-related economy to sustain itself, residents must be willing partners in the process. Because of the frequency of interaction between residents and tourists, their willingness to serve as gracious hosts is critical to the success of tourism. Therefore, residents must be involved in the planning and their attitudes toward tourism and perceptions of its impact on community life must be continually assessed (Allen, Long, Perdue, & Kieselbach, 1988). The purpose of this study is to demonstrate a structural model that explains the relationships between the residents’ perception of tourism impacts and attitudes toward host community.
2. Conceptual model integrating community satisfaction Although most of the studies of host community tourism attitudes and perceptions have focused on differences in the perceived impacts of tourism among different types of local residents, a few have discussed relationships between residents’ perception of tourism impacts and attitudes toward their own community. McCool and Martin (1994) found that Montana residents were concerned that increasing levels of tourism would crowd them out of local fishing, hunting, and other recreation areas. Allen et al. (1988) revealed that relationships between tourism development and satisfaction of various dimensions of community life
were generally nonlinear with citizen involvement, public services, and the environment being most sensitive to tourism development. They argued that negative attitudes about tourism appear to be confined to certain dimensions of community life related to public services and opportunities for civic involvement. Unfortunately, their study did not discuss relationships between residents’ perception of tourism impacts and community life satisfaction. Also, Allen, Haffer, Long, and Perdue (1993) found that residents agreed that their community should attract more tourists because this would lead to a higher quality of life. Although very little research has directly examined the influence of personal benefits from tourism on perception of impacts, numerous authors have interpreted the observed relationship between resident characteristics and perceptions of impact as supporting a positive relationship between personal benefits from tourism and favorable perceptions of tourism impacts (Perdue, Long, & Allen, 1990). However, most of these studies do not test the assertion that residents’ perception of tourism impacts influences attitudes toward community satisfaction. As a notable exception, Perdue et al. (1990) developed a model that examined relationships between resident’s perception of tourism impacts and their support for it. They tested a model that hypothesized relationships among rural resident perceptions of tourism impacts, support for additional tourism development, restrictions on tourism development, and support for special tourism taxes. They found that when controlling for personal benefits from tourism development, perception of impacts were unrelated to socio-demographic characteristics and that support for additional development was positively related to perceived positive impacts of tourism. Support for additional tourism development was negatively related to the perceived positive future of the community. Their conclusions were based on a multivariate regression analysis, however goodness-offit was not fully addressed in their reported process of model development. The hypothetical model (Fig. 1) is adapted from Perdue et al. (1990) whose model consisted of five latent constructs about tourism development and community satisfaction. Also, it has nine path hypotheses, which are the relationships among five latent constructs: personal benefits from tourism development, positive perceived tourism impacts, negative perceived tourism impacts, overall community satisfaction, and attitudes for additional tourism development. Each path represents an hypothesized relationship with the direction of effect identified as either positive (+) or negative (). Primary research questions are directed at the influence of perception of tourism impacts on overall community satisfaction, and the extent to which community satisfaction effects attitudes for additional
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Perceived Positive Tourism Impacts H5 + H1 +
H4 +
Personal Benefit from Tourism Development
Overall Community Satisfaction
H3 +
H2 -
Attitudes for 8Additional Tourism Development
H7 -
H6 -
Perceived Negative Tourism Impacts
H8 -
H9 +
Fig. 1. Relationships between residents’ perceived tourism and attitudes toward host community (Adapted from Perdue et al., 1990).
tourism development. The model also hypothesizes relationships among five latent constructs. This research tests the goodness-of-fit of the model and hypotheses with structural equation modeling.
3. Method 3.1. Study site The study was conducted in Cheju Island in Korea during November and early December 1997. Cheju Island is the largest and southernmost island of the Korean peninsula, is 1846 km2, oval-shaped, and in 1996 held a population of 524,000 people. The highest point is Halla Mountain at 1950 m in elevation; most of the residents live on the coastal plains at elevation of 300 m or less. Cheju Island is one of the most popular tourist destinations in Korea. The Korean government initiated tourism development on Cheju Island in the 1960s, and the local governments of the island made it a top priority in the 1970s. The main attractions of Cheju Island are its outstanding natural scenery of mountains rising from beautiful coastlines, the cultural heritage of the island people, the historic ambience of the rural villages, and opportunities for playing golf. According to the Cheju Statistical Yearbook (Cheju Do, 1997), there are 41 hotels with a collective capacity of 5168 rooms. In 1996, 4,140,000 visitors (209,000 were international) visited the island and spent the equivalent of US$ 1205 million that accounted for 28% of the gross income of Cheju Island. Tourism is the primary business sector of the Cheju economy, with the tangerinegrowing industry as second at US$ 720 million. In
1997, various local governments initiated the development of 23 additional tourism sites for the island. 3.2. Procedures The 1041 mailback questionnaires were delivered to a proportional stratified random sample of adults in each community of Cheju Island. A 70% response rate resulted from 732 usable questionnaires returned. Respondents consisted of 448 males (61%) and 284 females (39%). Their age ranged from 20 to 63 years with 61% being 40–49 years and 23% being 30–39 years old. Native residents of the island comprised 83% of respondents. The items of this study were originally derived from a comprehensive review of existing literature. The items for residents’ perception of tourism impacts were taken from seven existing empirical studies (e.g., Pizam, 1978; Belisle & Hoy, 1980; Liu & Var, 1986; Milman & Pizam, 1988; Perdue, Long, & Allen, 1987; Lankford & Howard, 1994; Haralambopoulos & Pizam, 1996). Although these combined studies reported 39 items about residents’ perception of tourism impacts, this study used 24 items due to exclusion of uncommon items (e.g., increases morality, honesty, politeness and manners, mutual confidence, and attitude toward work, increases exploitation of local natives) and redundant items. The items of community satisfaction were derived from studies related to Allen, Long, Perdue, and their colleagues. Allen and Beattie (1984) and Allen et al. (1988) developed 33 items that grouped into seven dimensions of community satisfaction: public services, economic, environment, medical services, citizen involvement, formal education, and recreation services and
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opportunities. This study employed all but two elements (adult education, dentists) that were not relevant in the case of Cheju Island. A 5-point Likert-type scale was utilized for most items in this study (5=strongly agreed or very satisfied; 1=strongly disagreed or very dissatisfied). Maddox (1985) recommended the use of a Likert-type scale in tourism impact research due to its superior validity (convergent and discriminant). An exception was the use of a binary scale (2=yes; 1=no) for ‘attitude for additional tourism development’. Data analysis was performed in two stages. In the first stage, reliability analysis was conducted using SPSS (ver. 7.5) to evaluate the stability and consistency for measured items. In the second stage, the evaluation of goodness-of-fit indices for the proposed structural equation model and testifying hypotheses were performed by using Analysis of MOment Structure (AMOS, ver. 3.6), and were estimated using asymptotically distribution free (ADF) method because the items of attitudes for additional tourism development were measured via binary scale. Standardized scores were used in the second stage of the analysis.
4. Results 4.1. Reliability analysis Reliability analysis was used to evaluate the stability and consistency for measured items of each latent
construct. The criteria used in deciding whether to delete an item were its corrected item-to-total correlation and whether the elimination improved the corresponding alpha values (Parasuraman, Zeithaml, & Berry, 1988). In general, items with corrected item-tototal correlations below 0.30 were eliminated. Reliability analysis was performed in two stages. The first stage of reliability analysis was directed at scales related to perceived tourism impact and overall community satisfaction. The variable of these latent constructs used summated rating scales comprised of many items. The corrected items-total correlation and Cronbach Alpha Coefficients for perceived tourism impacts are shown in Table 1 (positive tourism impact) and Table 2 (negative tourism impact). The items of positive perceived economic impacts (four items), positive perceived social and cultural impacts (six items), negative perceived social and cultural impacts (five items) and negative perceived environmental impacts (three items) in Table 1 had Cronbach Alpha Coefficients of over 0.74 with no increase resulting if any of the items were deleted. This Cronbach Coefficient Alpha exceeds Nunnally and Bernstein’s (1994) recommendation of 0.70, and supports the use of these items in each scale. The perceived positive environmental impacts scale (three items, Table 1) and perceived negative economic impacts scale (three items, Table 2) had Cronbach Alpha Coefficients under 0.70. Even though the three items for perceived positive environmental impact had a Cronbach Alpha Coefficient of 0.54, it would increase to
Table 1 Reliability of perceived positive tourism impact scales Variable name and description
Mean (SD)
Items-total correlation
Alpha if items deleted
Economic impacts Improves investment, development, and infrastructure in the economy Increases employment opportunities Contributes to income and standard of living Improves town’s overall tax revenue
3.3(0.9)
0.61
0.80 0.74
3.0(0.9) 3.1(0.9) 3.3(0.8)
0.66 0.64 0.53
0.72 0.73 0.78
Social and cultural impacts Improves quality of life Increases availability of recreational facilities and entertainment Improves understanding and image of different communities/cultures Increases demand for historical and cultural exhibits Encourages variety of cultural activities Improves quality of police and fire protection
3.2(0.9) 2.8(0.9) 3.0(0.8) 3.0(0.9) 3.0(0.9) 3.1(0.9)
0.51 0.50 0.55 0.48 0.49 0.37
0.74 0.70 0.70 0.69 0.71 0.71 0.74
3.0(0.9)
0.23
0.54 0.64
3.4(0.8)
0.41
0.34
3.6(0.8)
0.43
0.33
Environmental impacts Preserves environment and improves the appearance (and images) of an areas Improves living utilities infrastructure (supply of water, electric, and telephone, etc.) Improves public facilities (pavement, traffic network, and civic center)
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Table 2 Reliability of perceived negative tourism impact scales Variable name and description
Mean (SD)
Items-total correlation
Alpha if items deleted
Economic impacts Unfairly increased real estate cost and property taxes Increases cost of living Increases price of goods and services
3.3(0.9) 3.6(0.8) 3.6(0.9)
0.39 0.52 0.47
0.65 0.64 0.47 0.53
Social and cultural impacts Increases traffic accidents Increases crime/robberies/vandalism Increases alcoholism, prostitution, and sexual permissiveness Increases gambling/illegal games Increases exploitation of local natives
3.6(0.9) 3.5(0.9) 3.5(1.0) 3.4(1.0) 3.3(1.0)
0.44 0.64 0.70 0.65 0.59
0.81 0.82 0.77 0.75 0.76 0.78
Environmental impacts Damage natural environment and landscape Destroy local ecosystem Increases environmental pollution (litter, water, air, and noise)
3.4(1.0) 3.6(0.9) 3.7(0.9)
0.70 0.66 0.78
0.79 0.70 0.66 0.78
0.64 if the item of ‘preserves environment and improves the appearance (and images) of an areas’ was deleted. This item is qualitatively distinct from the other two items that deal directly with community infrastructure, which explains the high alpha (0.64) if this item is deleted. The items of negative perceived economic impact had a Cronbach Alpha Coefficient of 0.65 with no increase resulting if any of the items were deleted. However, these two scales had items-total correlation of over 0.30, which is a general criterion for acceptable reliability. Therefore, this study used the two scales for perceived positive environmental impact (after the item of ‘preserves environment and improves the appearance (and images) of an areas’ was deleted) and the scale for perceived negative economic impact without any items deleted. The corrected items-total correlation and Cronbach Alpha Coefficient for community satisfaction are shown in Table 3. The latent construct of community satisfaction consisted of seven scales. Three of the scales had Cronbach Alpha Coefficient above 0.70, and three additional scales were above 0.60. Each of the scales whose coefficient was above 0.60 had items-total correlations greater than 0.30, and thus were retained for analysis. The economic satisfaction scale (five items) had a Cronbach Alpha Coefficient of 0.42, which would increase to 0.52 if the item ‘cost of living’ were deleted. Two items within this scale had items-total correlation lower than the general criterion of 0.30. The results of reliability analysis showed that the items of economic satisfaction have weak reliability. However, since the dimension of economic satisfaction is a very important factor in discussing community satisfaction, this study used the scale as part of community satisfaction after the item ‘cost of living’ was deleted. The weak reliability of
the economic satisfaction sub-scale remains as a limitation of the empirical portion of this study. 4.2. Evaluation of proposed model The proposed model hypothesized that there were significant causal relationships among five latent constructs of ‘personal benefits of tourism development’, ‘perceived tourism impacts (positive and negative)’, ‘overall community satisfaction’ and ‘attitudes for additional tourism development’. The causal relationships represented the nine hypotheses in the path model. Empirical evaluation of such hypotheses is complicated by the fact that latent constructs are not directly observable. Evaluation is based on sets of observed or measured variables that serve as indicators of latent variables, with the relationship between the observed and latent variables being estimated using factor analysis. The relationship among latent variables or among latent variables and surrogate latent variables (observed variables serving as single-item proxies for latent variables) is typically estimated using regression analysis. Structural equation modeling (SEM) is a technique for simultaneously estimating the relationships between observed and latent variables (the measurement model), and the relationships among latent variables (the structural model). SEM is a method that has gained popularity because it combines confirmatory factor analysis and regression analysis to model a variety of psychological, sociological, and other relationships (Lindberg & Johnson, 1997). The descriptions, corrected items-total correlation, and Cronbach Alpha Coefficients for five observed variables of the second stage of reliability analysis are
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Table 3 Reliability of community satisfaction scales Variable name and description
Mean (SD)
Items-total correlation
Alpha if items deleted
Public service satisfaction Fire protection Welfare and social services (public assistant) Public transportation to and from other community Police protection Local government Road and highway Public health services
3.5(0.9) 3.1(0.9) 2.5(1.1) 2.9(0.9) 3.1(0.9) 2.6(1.0) 2.8(1.0)
0.40 0.45 0.39 0.51 0.45 0.44 0.46
0.73 0.71 0.70 0.71 0.69 0.70 0.70 0.70
Formal education satisfaction Public schools (K through 12 programs) College university courses (for credit) Technical and/or vocation training for career
3.2(0.9) 2.8(0.8) 2.6(0.9)
0.39 0.57 0.35
0.63 0.59 0.32 0.63
Environment satisfaction Physical geography or terrain Environmental cleanliness (air, water, soil) Climate and weather General appearance of your living town General appearance of your region (Cheju Island)
3.5(1.1) 3.4(0.9) 3.8(0.8) 3.7(0.8) 4.0(0.8)
0.38 0.50 0.38 0.58 0.41
0.69 0.67 0.61 0.66 0.58 0.65
Recreation opportunities satisfaction Private/commercial recreation (health clubs, movies, etc) Publicly funded recreation (social, cultural, sports/fitness) Park and open space
2.7(1.0) 2.5(0.9) 2.6(0.9)
0.61 0.74 0.61
0.80 0.77 0.64 0.77
Economics satisfaction Shopping facilities Cost of living Housing (cost and availability) Utilities (water, gas, electricity, sewage) Job opportunities
2.7(1.1) 2.2(0.8) 2.7(0.9) 3.8(0.8) 2.3(0.9)
0.30 0.30 0.28 0.20 0.32
0.42 0.28 0.52 0.31 0.37 0.28
Citizen involvement and social opportunities Opportunities to be with friends and relatives Citizen input into community decisions Religious organizations (church/temple) Opportunities in civic and fraternal organizations Opportunities to become familiar with other residents
3.2(0.9) 2.8(0.9) 2.9(0.9) 3.0(1.1) 2.7(0.9)
0.47 0.46 0.31 0.41 0.42
0.66 0.58 0.59 0.65 0.61 0.60
Medical services satisfaction Hospital and medical facilities Medical doctors Emergency services
2.6(1.0) 2.6(0.9) 2.5(0.9)
0.57 0.67 0.65
0.79 0.78 0.67 0.69
presented in Table 4. The observed variables of ‘personal benefits of tourism development’ and ‘attitudes for additional tourism development’ were items measured directly. The observed variables of ‘positive perceived tourism impacts’, ‘negative perceived tourism impacts’, and ‘overall community satisfaction’ were the summated rating scales of the first stage of the reliability analysis (Tables 1–3). In Table 4, Cronbach Alpha Coefficient exceeds Nunnally and Bernstein’s (1994) recommendation of 0.70, and supports the use of these observed variables. There was one item, that if deleted would increase the scale’s Alpha Coefficient. If the item ‘positive environ-
mental tourism impacts’, or ‘PPTI’ was deleted, the Cronbach Alpha Coefficient would increase to 0.75. But, the marginal improvement in Alpha was not deemed significant enough compared to the items’ value in this study. Therefore, it was not deleted. Finally, the results of reliability for the latent constructs in this study support the use of these observed variables. Fig. 2 shows the standardized model as estimated by AMOS. Each of the observed variables is displayed in a rectangle, and each of the latent constructs is displayed in an oval. The evaluation of goodness-of-fit indices supported the model. The w2 test provides that the model generated w2 ¼ 376; df ¼ 110; po0:01; which
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527
Table 4 Reliability analysis of observed variables Latent constructs and description of observed variables
Corrected items-total correlation
Alpha if items deleted
PBTD pnjobrl fmjobrl
Personal benefits from Tourism Development Relationship with tourism of personal job Relationship with tourism of family job
0.57 0.57
0.73 — —
PPTI pecoimp pscimp penimp
Positive Positive Positive Positive
0.58 0.63 0.47
0.73 0.60 0.57 0.75
NPTI necoimp nscimp nenimp
Negative Negative Negative Negative
0.49 0.62 0.51
0.72 0.68 0.52 0.67
OCS satps sated satenv satrec sateco satci satms
Overall community satisfaction Public service satisfaction Formal education satisfaction Environmental satisfaction Recreation satisfaction Economic satisfaction Citizen involvement satisfaction Medical service satisfaction
0.57 0.55 0.32 0.48 0.58 0.50 0.52
0.77 0.73 0.74 0.77 0.75 0.73 0.75 0.74
AATD atdcheju atdcomn
Attitudes for additional Tourism Development Support level in Cheju regional contexts Support level in living community contexts
0.67 0.67
0.80 — —
perceived tourism impacts economic tourism impacts social and cultural tourism impacts environmental tourism impacts Perceived Tourism Impacts economic tourism impacts social and cultural tourism impacts environmental tourism impacts
pecoimp
pscimp
.69
nenimp .52
.81
PPTI .277 .360
satps
a
.634
pnjobrl .80
a
a
.080
sated
.66 .63 .41
satenv
PBTD
AATD .63
fmjobrl
.78
-.101
b
.96
-.121
OCS satrec
.66
.106
a
-.244
.74
atdcheju atdcomn
a
sateco -. 013
.62
satci .68
satms
PNTI .60
necoimp
.81
nscimp
.69
nenimp
Fig. 2. Standardized estimated hypothetical model (a) and (b) indicate significance at the 0.01 and 0.05 levels, respectively. Dashed lines indicate paths that are not significant at 0.05 or better.
indicates a marginal fit (normed w2 ¼ 3:42). Because this w2 test is sensitive to sample size (n ¼ 732 in this study), supplementary measures have been developed. The
other goodness-of-fit indices indicated a good fit within accepted exhortation levels. The goodness-of-fit index (GFI) is acceptable at 0.926, the root mean square error
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of approximation (RMSEA) is acceptable at 0.058, and also the root mean square residual (RMR) is acceptable at 0.044. Path hypothesis 1 (i.e., ‘personal benefits from tourism development’ are positively related to ‘positive perceived tourism impacts’) was supported with an optimal level at t ¼ 6:168 (po0:001) and b ¼ 0:36: But path hypothesis 2 (i.e., ‘personal benefits from tourism development’ are negatively related to ‘perceived negative tourism impacts’) was rejected at t ¼ 0:026 and b ¼ 0:013: Many studies have supported a causal relationship between ‘personal benefits from tourism development’ and ‘perception of tourism impacts’ (e.g., Lindberg & Johnson, 1997; Madrigal, 1993; Perdue et al., 1990). Support for this relationship aligns with common sense that residents (or their relatives, friend, and neighbors) who depend upon tourism-based employment would be more favorable toward tourism (e.g., Liu & Var, 1986; Milman & Pizam, 1988; Murphy, 1983; Pizam, 1978). Although the related hypothesis between ‘personal benefits from tourism development’ and ‘perceived negative tourism impacts’ was supported at t ¼ 27:9 (po0:001) and b ¼ 0:157 by Perdue et al. (1990), this study did not find a significant relationship. It could be that the relationship between ‘personal benefits from tourism development’ and ‘perceived negative tourism impacts’ was strongly dependent upon the level of tourism development or residents’ education level. An important finding of these results is the lack of a significant relationship between benefits from tourism and perceived negative impacts. Path hypothesis 3 (i.e., ‘personal benefits from tourism development’ are positively related to ‘overall community satisfaction’) was rejected at a significant level of 95% (two tailed test, t > 1:96), but supported with a marginal level at t ¼ 1:625 (po0:05) and b of 0.08. If the path relationship between ‘personal benefits from tourism development’ and ‘perceived negative tourism impacts’ was deleted (due to rejection of hypothesis), the t-value decreased to t ¼ 1:587 (p > 0:10). These results suggest that ‘personal benefits from tourism development’ does not contribute to attitude toward ‘overall community satisfaction’. Tourism development is widely perceived as an important community development strategy. It converges with intuition that ‘overall community satisfaction’ would be positively related to ‘personal benefits from tourism development’. However, this relationship was not significant at po0:05: Path hypothesis 4 (i.e., ‘perceived positive tourism impacts’ are positively related to ‘overall community satisfaction’) was supported with an optimal level at t ¼ 10:10 (po0:001) and b ¼ 0:634: Also, path hypothesis 5 (i.e., ‘perceived positive tourism impacts’ are positively related to ‘attitude for additional tourism development’) was supported with an optimal level at t ¼ 4:142
(po0:001) and b ¼ 0:291: Path hypothesis 6 (i.e., ‘perceived negative tourism impacts’ are negatively related to ‘overall community satisfaction’) was supported with an optimal level at t ¼ 2:319 (po0:05) and b ¼ 0:101: Path hypothesis 7 (i.e., ‘perceived negative tourism impacts’ are negatively related to ‘attitude for additional tourism development’) was supported with an optimal level at t ¼ 5:923 (po0:001) and b ¼ 0:244: These results generally converge with those of previous research. Perdue et al. (1990) have reported that this relationship (hypothesis 7) was supported at b ¼ 27 (po0:001). Finally, path hypothesis 8 (i.e., ‘overall community satisfaction’ is negatively related to ‘attitude for additional tourism development’), although negative, was not statistically significant at po0:05 (the t ¼ 1:895 (po0:10) and b ¼ 0:121). Many researchers have suggested that residents’ attitudes toward tourism may be related directly to the degree and/or stage of development within the host community (e.g., Doxey, 1975; Williams, 1979; Butler, 1980; Cooke, 1982; Getz, 1983; Haywood, 1986). These studies suggest that communities have a certain capacity to absorb tourists (Allen et al., 1988). Therefore, the lack of a significant negative relationship between ‘community satisfaction’ and ‘attitude toward additional tourism development’ may be due to the long history of tourism development at Cheju Island. Path hypothesis 9 (i.e., ‘personal benefits from tourism development’ are positively related to ‘attitude for additional tourism development’) was supported with an optimal level at t ¼ 2:635 (po0:01) and b ¼ 0:106: Many studies have found that residents who are economically dependent on tourism tend to favor tourist activity (e.g., Pizam, 1978; Brougham & Butler, 1981). Perdue et al. (1990) also found a strong positive relationship between personal benefits from tourism and attitudes for additional tourism development.
5. Conclusions The purpose of this research was to test a model of residents’ perceptions and attitudes of tourism, examining not only perceptions of tourism impacts, attitudes toward community satisfaction, and additional tourism development, but also the path relationships between perceptions of benefits from tourism development, positive and negative tourism impacts, community satisfaction, and attitudes for additional tourism development. The results support six hypotheses from previous studies, but three of the hypotheses were not supported at po0:05 level. This study found that ‘residents’ community satisfaction’ was closely related to ‘perceived positive tourism impacts’ and ‘perceived negative tourism impacts’. Both perceived positive and negative impacts were directly
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causing ‘attitudes toward additional tourism development’. Perdue et al. (1990) found that resident support for additional tourism was negatively associated with a positive future for the community. Tourism development is viewed not as a goal but as a tool or means of community development. Community satisfaction may be a useful concept for evaluation of residents’ perception 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. But, the hypothesis that ‘personal benefits from tourism development’ would be negatively related to ‘perceptions of negative tourism impacts’ was rejected, and contrasts to findings of past research (e.g., Perdue et al., 1990). The implications suggest that personal benefits from tourism are relevant to understanding perceptions of positive impacts but, in this case, irrelevant to understand perceptions of negative impacts. This may be due to the level of development on Cheju Island, which has a longstanding history of tourism as an integral part of its economy. In other words, the length of time and history of tourism development within a host community may be relevant to understanding residents’ perceptions of tourism (see also Brown & Giles, 1994; Ryan, Scotland, & Montgomery, 1998), and should be addressed as part of future research efforts. Although this study supported some important relationships between residents’ perceptions of tourism impacts and community satisfaction, the limitations include a weak reliability on community economic satisfaction sub-scale along with a sample that may not be representative of the population (e.g., 84% of respondents were between 30 and 49 years of age). Many investigations have suggested that residents’ attitudes toward tourism may be directly related to the degree or stage of development within the host community, which may partially explain the findings. Further research needs to address community satisfaction, level of tourism development, and attitude toward additional tourism development.
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Ap, J., & Crompton, J. (1993). Respondents’ strategies for responding to tourism impacts. Journal of Travel Research, 32(1), 47–50. Belisle, F. J., & Hoy, D. R. (1980). The perceived impact of tourism by residents: a case study in Marta Colombia. Annals of Tourism Research, 7(1), 83–101. Brougham, J. E., & Butler, R. W. (1981). A segmentation analysis of resident attitudes to social impact of tourism. Annals of Tourism Research, 7(4), 569–590. Brown, G., & Giles, R. (1994). Resident responses to the social impact of tourism. In A. Seaton, et al. (Ed.), Tourism: A state of the art (pp. 755–764). Chichester: Wiley. Butler, R. W. (1980). The concept of a tourism areas cycle of evaluation: implications for management of resources. Canadian Geographer, 24(1), 5–12. Cheju, DO. (1997). Cheju Statistical Yearbook, Cheju: Cheju Province Government. Cooke, K. (1982). Guidelines for socially appropriate tourism development in British Columbia. Journal of Travel Research, 21(1), 22–28. Doxey, G. V. (1975). A causation theory of visitor-resident irritants’ methodology and research inferences. Proceedings of the Sixth Annual Conference of the Travel Research Association (pp. 195–198), San Diego CA: Travel and Tourism Research Association. Getz, D. (1983). Capacity to absorb tourism: concepts and implications for strategic planning. Annals of Tourism Research, 10(2), 239–263. Haralambopoulos, N., & Pizam, A. (1996). Perceived impacts of tourism: the case of Samos. Annals of Tourism Research, 23(3), 503–526. Haywood, K. M. (1986). Can the tourist area life cycle be made operational? Tourism Management, 7(3), 154–167. Huang, Y., & Stewart, W. P. (1996). Rural tourism development: shifting basis of community solidarity. Journal of Travel Research, 36(4), 26–31. Jamal, T., & Getz, D. (1995). Collaboration theory and community tourism planning. Annals of Tourism Research, 22(1), 186–204. Lankford, S. V., & Howard, D. R. (1994). Developing a tourism impacts attitude scale. Annals of Tourism Research, 21(1), 121–139. Lindberg, K., & Johnson, R. L. (1997). Modeling resident attitudes toward tourism. Annals of Tourism Research, 24(2), 402–427. Liu, J. C., & Var, T. (1986). Resident attitudes toward tourism impacts in Hawaii. Annals of Tourism Research, 13(2), 193–214. Maddox, R. N. (1985). Measuring satisfaction with tourism. Journal of Travel Research, 23(3), 2–5. Madrigal, R. (1993). A tale of tourism in two cities. Annals of Tourism Research, 20(2), 336–353. McCool, S. F., & Martin, S. R. (1994). Community attachment and attitudes toward tourism development. Journal of Travel Research, 32(3), 29–34. Milman, A., & Pizam, A. (1988). Social impacts of tourism on Central Florida. Annals of Tourism Research, 15(2), 191–204. Murphy, P. E. (1983). Perceptions and attitudes of decision making groups in tourist centers. Journal of Travel Research, 21(3), 8–12. Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed). New York: McGraw-Hill. Parasuraman, A., Zeithaml, V., & Berry, L. L. (1988). Servqual: a multiple-item scale for measuring consumer perceptions of services quality. Journal of Retailing, 64, 12–40. Perdue, R. R., Long, P. T., & Allen, L. R. (1990). Resident support for tourism development. Annals of Tourism Research, 17(4), 586–599.
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Perdue, R. R., Long, P. T., & Allen, L. R. (1987). Rural resident of tourism perceptions and attitudes. Annals of Tourism Research, 14(3), 420–429. Pizam, A. (1978). Tourism impacts: the social costs to the destination community as perceived by its residents. Journal of Travel Research, 16(4), 8–12. Ritchie, J. (1993). Crafting a destination vision: putting the concept of resident-responsive tourism into practice. Tourism Management, 14(5), 379–389.
Robson, J., & Robson, I. (1996). From shareholders to stakeholders: critical issues for tourism marketers. Tourism Management, 17(7), 533–540. Ryan, C., Scotland, A., & Montgomery, D. (1998). Resident attitudes to tourism development: a comparative study between the Rangitikei, New Zealand and Bakewell, United Kingdom. Progress in Tourism and Hospitality Research, 4(2), 115–130. Williams, T. A. (1979). Impact of domestic tourism on host population the evolution of a model. Tourism Recreation Research, 14(1), 15–21.
A structural equation model of residents’ attitudes for tourism development Dong-Wan Koa,*, William P. Stewartb b
a Division of Tourism Science, Kyonggi University, San 94-6, Yiui-Dong, Paldal-Gu, Suwon-Si, Kyonggi-Do 442-760, South Korea Department of Leisure Studies, University of Illinois at Urbana-Champaign, 104 Huff Hall, 1206 S. Fourth Street, Champaign, IL 61820, USA
Received 3 July 2001; accepted 4 January 2002
Abstract This study tests the structural equation model between residents’ perceived tourism impacts and attitudes toward host community. The model consisted of five latent constructs and nine path hypotheses and is based upon 732 mailback questionnaires returned by residents of Cheju Island, Korea, a major domestic tourism destination. It was found that residents’ ‘community satisfaction’ was closely related to ‘perceived positive’ and ‘perceived negative’ tourism impacts. These constructs were directly causing ‘attitudes toward additional tourism development’. But the hypothesized path relationships between ‘personal benefits from tourism development’ and the constructs of ‘perceived negative tourism impacts’ and ‘overall community satisfaction’ were rejected. In conclusion, community satisfaction was influenced by perception of tourism impacts, and may be useful in planning for additional tourism development. r 2002 Elsevier Science Ltd. All rights reserved. Keywords: Tourism impacts; Overall community satisfaction; Residents’ perception and attitudes
1. Introduction Tourism development is widely viewed as an important set of economic activities to enhance local economies. Many studies have suggested that development and promotion of tourism is a source of new employment, revenues, additional tax receipts, foreign exchange benefits, and enhances community infrastructure that will, in turn, attract other industries (Lankford & Howard, 1994). Until recently, the development and promotion of the tourism industry has been widely accepted as a positive economic step, especially in less developed countries (Cooke, 1982). The term ‘tourism impact’ has been gaining increasing attention in the tourism literature. A number of studies in recent years have examined host residents’ perception of the impact of tourism development on their community, and it continues to be an important issue. A major reason for rising interest has been the increasing evidence that tourism development leads not only to *Corresponding author. Tel.: +82-31-249-9509; fax: +82-31-2499503. E-mail addresses: [email protected] (D.-W. Ko), wstewart @uiuc.edu (W.P. Stewart).
positive, but also has the potential for negative, outcomes at the local level (Lankford & Howard, 1994). Liu and Var (1986) noted that tourism development is usually justified on the basis of economic benefits and challenged on the grounds of social, cultural, or environmental destruction. Furthermore, the economic benefits traditionally associated with tourism development are now being measured against its potential for social disruption (Cooke, 1982). Huang and Stewart (1996) indicated that tourism development may change residents’ relationships to one another and to their community. It is generally felt that the perception and attitudes of residents toward the impacts of tourism are likely to be an important planning and policy consideration for successful development, marketing, and operation of existing and future tourism programs (Ap, 1992). Although many studies have been performed to identify residents’ perception of tourism impacts and attitudes toward tourism, just a few have assessed relationships between tourism development and community satisfaction. To date, little research has examined the relationships between residents’ perceived impacts of tourism on their community and attitudes toward their own community. Residents must perceive
0261-5177/02/$ - see front matter r 2002 Elsevier Science Ltd. All rights reserved. PII: S 0 2 6 1 - 5 1 7 7 ( 0 2 ) 0 0 0 0 6 - 7
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tourism in overall positive terms to sustain development of tourism programs. In this context, relationships between residents’ perception of tourism impacts and community satisfaction are an important, yet not well understood, area of research. A significant portion of the social impact of tourism literature suggests that stakeholder involvement and community-based planning should be a part of the early stages of tourism development (Jamal & Getz, 1995). It has been argued that when residents are involved in the planning process, then tourism development will be socially responsible and social impacts will be perceived as appropriate by the host community (Robson & Robson, 1996). However most studies directed at residents’ perceptions of tourism and community-based planning have been conducted in the west: Canada (e.g., Ritchie, 1993), the US (e.g., Ap & Crompton, 1993), the UK (e.g., Robson & Robson, 1996), or Australia (e.g., Brown & Giles, 1994). Whether or not community involvement effects social impacts within Asian countries is still an open point that has yet to be fully examined. Currently, there is limited understanding of the relationships between residents’ perception of tourism impacts and community satisfaction. The lack of such research limits the current literature on understanding residents’ behavior toward the impacts of tourism (Ap, 1992). For a tourism-related economy to sustain itself, residents must be willing partners in the process. Because of the frequency of interaction between residents and tourists, their willingness to serve as gracious hosts is critical to the success of tourism. Therefore, residents must be involved in the planning and their attitudes toward tourism and perceptions of its impact on community life must be continually assessed (Allen, Long, Perdue, & Kieselbach, 1988). The purpose of this study is to demonstrate a structural model that explains the relationships between the residents’ perception of tourism impacts and attitudes toward host community.
2. Conceptual model integrating community satisfaction Although most of the studies of host community tourism attitudes and perceptions have focused on differences in the perceived impacts of tourism among different types of local residents, a few have discussed relationships between residents’ perception of tourism impacts and attitudes toward their own community. McCool and Martin (1994) found that Montana residents were concerned that increasing levels of tourism would crowd them out of local fishing, hunting, and other recreation areas. Allen et al. (1988) revealed that relationships between tourism development and satisfaction of various dimensions of community life
were generally nonlinear with citizen involvement, public services, and the environment being most sensitive to tourism development. They argued that negative attitudes about tourism appear to be confined to certain dimensions of community life related to public services and opportunities for civic involvement. Unfortunately, their study did not discuss relationships between residents’ perception of tourism impacts and community life satisfaction. Also, Allen, Haffer, Long, and Perdue (1993) found that residents agreed that their community should attract more tourists because this would lead to a higher quality of life. Although very little research has directly examined the influence of personal benefits from tourism on perception of impacts, numerous authors have interpreted the observed relationship between resident characteristics and perceptions of impact as supporting a positive relationship between personal benefits from tourism and favorable perceptions of tourism impacts (Perdue, Long, & Allen, 1990). However, most of these studies do not test the assertion that residents’ perception of tourism impacts influences attitudes toward community satisfaction. As a notable exception, Perdue et al. (1990) developed a model that examined relationships between resident’s perception of tourism impacts and their support for it. They tested a model that hypothesized relationships among rural resident perceptions of tourism impacts, support for additional tourism development, restrictions on tourism development, and support for special tourism taxes. They found that when controlling for personal benefits from tourism development, perception of impacts were unrelated to socio-demographic characteristics and that support for additional development was positively related to perceived positive impacts of tourism. Support for additional tourism development was negatively related to the perceived positive future of the community. Their conclusions were based on a multivariate regression analysis, however goodness-offit was not fully addressed in their reported process of model development. The hypothetical model (Fig. 1) is adapted from Perdue et al. (1990) whose model consisted of five latent constructs about tourism development and community satisfaction. Also, it has nine path hypotheses, which are the relationships among five latent constructs: personal benefits from tourism development, positive perceived tourism impacts, negative perceived tourism impacts, overall community satisfaction, and attitudes for additional tourism development. Each path represents an hypothesized relationship with the direction of effect identified as either positive (+) or negative (). Primary research questions are directed at the influence of perception of tourism impacts on overall community satisfaction, and the extent to which community satisfaction effects attitudes for additional
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Perceived Positive Tourism Impacts H5 + H1 +
H4 +
Personal Benefit from Tourism Development
Overall Community Satisfaction
H3 +
H2 -
Attitudes for 8Additional Tourism Development
H7 -
H6 -
Perceived Negative Tourism Impacts
H8 -
H9 +
Fig. 1. Relationships between residents’ perceived tourism and attitudes toward host community (Adapted from Perdue et al., 1990).
tourism development. The model also hypothesizes relationships among five latent constructs. This research tests the goodness-of-fit of the model and hypotheses with structural equation modeling.
3. Method 3.1. Study site The study was conducted in Cheju Island in Korea during November and early December 1997. Cheju Island is the largest and southernmost island of the Korean peninsula, is 1846 km2, oval-shaped, and in 1996 held a population of 524,000 people. The highest point is Halla Mountain at 1950 m in elevation; most of the residents live on the coastal plains at elevation of 300 m or less. Cheju Island is one of the most popular tourist destinations in Korea. The Korean government initiated tourism development on Cheju Island in the 1960s, and the local governments of the island made it a top priority in the 1970s. The main attractions of Cheju Island are its outstanding natural scenery of mountains rising from beautiful coastlines, the cultural heritage of the island people, the historic ambience of the rural villages, and opportunities for playing golf. According to the Cheju Statistical Yearbook (Cheju Do, 1997), there are 41 hotels with a collective capacity of 5168 rooms. In 1996, 4,140,000 visitors (209,000 were international) visited the island and spent the equivalent of US$ 1205 million that accounted for 28% of the gross income of Cheju Island. Tourism is the primary business sector of the Cheju economy, with the tangerinegrowing industry as second at US$ 720 million. In
1997, various local governments initiated the development of 23 additional tourism sites for the island. 3.2. Procedures The 1041 mailback questionnaires were delivered to a proportional stratified random sample of adults in each community of Cheju Island. A 70% response rate resulted from 732 usable questionnaires returned. Respondents consisted of 448 males (61%) and 284 females (39%). Their age ranged from 20 to 63 years with 61% being 40–49 years and 23% being 30–39 years old. Native residents of the island comprised 83% of respondents. The items of this study were originally derived from a comprehensive review of existing literature. The items for residents’ perception of tourism impacts were taken from seven existing empirical studies (e.g., Pizam, 1978; Belisle & Hoy, 1980; Liu & Var, 1986; Milman & Pizam, 1988; Perdue, Long, & Allen, 1987; Lankford & Howard, 1994; Haralambopoulos & Pizam, 1996). Although these combined studies reported 39 items about residents’ perception of tourism impacts, this study used 24 items due to exclusion of uncommon items (e.g., increases morality, honesty, politeness and manners, mutual confidence, and attitude toward work, increases exploitation of local natives) and redundant items. The items of community satisfaction were derived from studies related to Allen, Long, Perdue, and their colleagues. Allen and Beattie (1984) and Allen et al. (1988) developed 33 items that grouped into seven dimensions of community satisfaction: public services, economic, environment, medical services, citizen involvement, formal education, and recreation services and
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opportunities. This study employed all but two elements (adult education, dentists) that were not relevant in the case of Cheju Island. A 5-point Likert-type scale was utilized for most items in this study (5=strongly agreed or very satisfied; 1=strongly disagreed or very dissatisfied). Maddox (1985) recommended the use of a Likert-type scale in tourism impact research due to its superior validity (convergent and discriminant). An exception was the use of a binary scale (2=yes; 1=no) for ‘attitude for additional tourism development’. Data analysis was performed in two stages. In the first stage, reliability analysis was conducted using SPSS (ver. 7.5) to evaluate the stability and consistency for measured items. In the second stage, the evaluation of goodness-of-fit indices for the proposed structural equation model and testifying hypotheses were performed by using Analysis of MOment Structure (AMOS, ver. 3.6), and were estimated using asymptotically distribution free (ADF) method because the items of attitudes for additional tourism development were measured via binary scale. Standardized scores were used in the second stage of the analysis.
4. Results 4.1. Reliability analysis Reliability analysis was used to evaluate the stability and consistency for measured items of each latent
construct. The criteria used in deciding whether to delete an item were its corrected item-to-total correlation and whether the elimination improved the corresponding alpha values (Parasuraman, Zeithaml, & Berry, 1988). In general, items with corrected item-tototal correlations below 0.30 were eliminated. Reliability analysis was performed in two stages. The first stage of reliability analysis was directed at scales related to perceived tourism impact and overall community satisfaction. The variable of these latent constructs used summated rating scales comprised of many items. The corrected items-total correlation and Cronbach Alpha Coefficients for perceived tourism impacts are shown in Table 1 (positive tourism impact) and Table 2 (negative tourism impact). The items of positive perceived economic impacts (four items), positive perceived social and cultural impacts (six items), negative perceived social and cultural impacts (five items) and negative perceived environmental impacts (three items) in Table 1 had Cronbach Alpha Coefficients of over 0.74 with no increase resulting if any of the items were deleted. This Cronbach Coefficient Alpha exceeds Nunnally and Bernstein’s (1994) recommendation of 0.70, and supports the use of these items in each scale. The perceived positive environmental impacts scale (three items, Table 1) and perceived negative economic impacts scale (three items, Table 2) had Cronbach Alpha Coefficients under 0.70. Even though the three items for perceived positive environmental impact had a Cronbach Alpha Coefficient of 0.54, it would increase to
Table 1 Reliability of perceived positive tourism impact scales Variable name and description
Mean (SD)
Items-total correlation
Alpha if items deleted
Economic impacts Improves investment, development, and infrastructure in the economy Increases employment opportunities Contributes to income and standard of living Improves town’s overall tax revenue
3.3(0.9)
0.61
0.80 0.74
3.0(0.9) 3.1(0.9) 3.3(0.8)
0.66 0.64 0.53
0.72 0.73 0.78
Social and cultural impacts Improves quality of life Increases availability of recreational facilities and entertainment Improves understanding and image of different communities/cultures Increases demand for historical and cultural exhibits Encourages variety of cultural activities Improves quality of police and fire protection
3.2(0.9) 2.8(0.9) 3.0(0.8) 3.0(0.9) 3.0(0.9) 3.1(0.9)
0.51 0.50 0.55 0.48 0.49 0.37
0.74 0.70 0.70 0.69 0.71 0.71 0.74
3.0(0.9)
0.23
0.54 0.64
3.4(0.8)
0.41
0.34
3.6(0.8)
0.43
0.33
Environmental impacts Preserves environment and improves the appearance (and images) of an areas Improves living utilities infrastructure (supply of water, electric, and telephone, etc.) Improves public facilities (pavement, traffic network, and civic center)
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Table 2 Reliability of perceived negative tourism impact scales Variable name and description
Mean (SD)
Items-total correlation
Alpha if items deleted
Economic impacts Unfairly increased real estate cost and property taxes Increases cost of living Increases price of goods and services
3.3(0.9) 3.6(0.8) 3.6(0.9)
0.39 0.52 0.47
0.65 0.64 0.47 0.53
Social and cultural impacts Increases traffic accidents Increases crime/robberies/vandalism Increases alcoholism, prostitution, and sexual permissiveness Increases gambling/illegal games Increases exploitation of local natives
3.6(0.9) 3.5(0.9) 3.5(1.0) 3.4(1.0) 3.3(1.0)
0.44 0.64 0.70 0.65 0.59
0.81 0.82 0.77 0.75 0.76 0.78
Environmental impacts Damage natural environment and landscape Destroy local ecosystem Increases environmental pollution (litter, water, air, and noise)
3.4(1.0) 3.6(0.9) 3.7(0.9)
0.70 0.66 0.78
0.79 0.70 0.66 0.78
0.64 if the item of ‘preserves environment and improves the appearance (and images) of an areas’ was deleted. This item is qualitatively distinct from the other two items that deal directly with community infrastructure, which explains the high alpha (0.64) if this item is deleted. The items of negative perceived economic impact had a Cronbach Alpha Coefficient of 0.65 with no increase resulting if any of the items were deleted. However, these two scales had items-total correlation of over 0.30, which is a general criterion for acceptable reliability. Therefore, this study used the two scales for perceived positive environmental impact (after the item of ‘preserves environment and improves the appearance (and images) of an areas’ was deleted) and the scale for perceived negative economic impact without any items deleted. The corrected items-total correlation and Cronbach Alpha Coefficient for community satisfaction are shown in Table 3. The latent construct of community satisfaction consisted of seven scales. Three of the scales had Cronbach Alpha Coefficient above 0.70, and three additional scales were above 0.60. Each of the scales whose coefficient was above 0.60 had items-total correlations greater than 0.30, and thus were retained for analysis. The economic satisfaction scale (five items) had a Cronbach Alpha Coefficient of 0.42, which would increase to 0.52 if the item ‘cost of living’ were deleted. Two items within this scale had items-total correlation lower than the general criterion of 0.30. The results of reliability analysis showed that the items of economic satisfaction have weak reliability. However, since the dimension of economic satisfaction is a very important factor in discussing community satisfaction, this study used the scale as part of community satisfaction after the item ‘cost of living’ was deleted. The weak reliability of
the economic satisfaction sub-scale remains as a limitation of the empirical portion of this study. 4.2. Evaluation of proposed model The proposed model hypothesized that there were significant causal relationships among five latent constructs of ‘personal benefits of tourism development’, ‘perceived tourism impacts (positive and negative)’, ‘overall community satisfaction’ and ‘attitudes for additional tourism development’. The causal relationships represented the nine hypotheses in the path model. Empirical evaluation of such hypotheses is complicated by the fact that latent constructs are not directly observable. Evaluation is based on sets of observed or measured variables that serve as indicators of latent variables, with the relationship between the observed and latent variables being estimated using factor analysis. The relationship among latent variables or among latent variables and surrogate latent variables (observed variables serving as single-item proxies for latent variables) is typically estimated using regression analysis. Structural equation modeling (SEM) is a technique for simultaneously estimating the relationships between observed and latent variables (the measurement model), and the relationships among latent variables (the structural model). SEM is a method that has gained popularity because it combines confirmatory factor analysis and regression analysis to model a variety of psychological, sociological, and other relationships (Lindberg & Johnson, 1997). The descriptions, corrected items-total correlation, and Cronbach Alpha Coefficients for five observed variables of the second stage of reliability analysis are
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Table 3 Reliability of community satisfaction scales Variable name and description
Mean (SD)
Items-total correlation
Alpha if items deleted
Public service satisfaction Fire protection Welfare and social services (public assistant) Public transportation to and from other community Police protection Local government Road and highway Public health services
3.5(0.9) 3.1(0.9) 2.5(1.1) 2.9(0.9) 3.1(0.9) 2.6(1.0) 2.8(1.0)
0.40 0.45 0.39 0.51 0.45 0.44 0.46
0.73 0.71 0.70 0.71 0.69 0.70 0.70 0.70
Formal education satisfaction Public schools (K through 12 programs) College university courses (for credit) Technical and/or vocation training for career
3.2(0.9) 2.8(0.8) 2.6(0.9)
0.39 0.57 0.35
0.63 0.59 0.32 0.63
Environment satisfaction Physical geography or terrain Environmental cleanliness (air, water, soil) Climate and weather General appearance of your living town General appearance of your region (Cheju Island)
3.5(1.1) 3.4(0.9) 3.8(0.8) 3.7(0.8) 4.0(0.8)
0.38 0.50 0.38 0.58 0.41
0.69 0.67 0.61 0.66 0.58 0.65
Recreation opportunities satisfaction Private/commercial recreation (health clubs, movies, etc) Publicly funded recreation (social, cultural, sports/fitness) Park and open space
2.7(1.0) 2.5(0.9) 2.6(0.9)
0.61 0.74 0.61
0.80 0.77 0.64 0.77
Economics satisfaction Shopping facilities Cost of living Housing (cost and availability) Utilities (water, gas, electricity, sewage) Job opportunities
2.7(1.1) 2.2(0.8) 2.7(0.9) 3.8(0.8) 2.3(0.9)
0.30 0.30 0.28 0.20 0.32
0.42 0.28 0.52 0.31 0.37 0.28
Citizen involvement and social opportunities Opportunities to be with friends and relatives Citizen input into community decisions Religious organizations (church/temple) Opportunities in civic and fraternal organizations Opportunities to become familiar with other residents
3.2(0.9) 2.8(0.9) 2.9(0.9) 3.0(1.1) 2.7(0.9)
0.47 0.46 0.31 0.41 0.42
0.66 0.58 0.59 0.65 0.61 0.60
Medical services satisfaction Hospital and medical facilities Medical doctors Emergency services
2.6(1.0) 2.6(0.9) 2.5(0.9)
0.57 0.67 0.65
0.79 0.78 0.67 0.69
presented in Table 4. The observed variables of ‘personal benefits of tourism development’ and ‘attitudes for additional tourism development’ were items measured directly. The observed variables of ‘positive perceived tourism impacts’, ‘negative perceived tourism impacts’, and ‘overall community satisfaction’ were the summated rating scales of the first stage of the reliability analysis (Tables 1–3). In Table 4, Cronbach Alpha Coefficient exceeds Nunnally and Bernstein’s (1994) recommendation of 0.70, and supports the use of these observed variables. There was one item, that if deleted would increase the scale’s Alpha Coefficient. If the item ‘positive environ-
mental tourism impacts’, or ‘PPTI’ was deleted, the Cronbach Alpha Coefficient would increase to 0.75. But, the marginal improvement in Alpha was not deemed significant enough compared to the items’ value in this study. Therefore, it was not deleted. Finally, the results of reliability for the latent constructs in this study support the use of these observed variables. Fig. 2 shows the standardized model as estimated by AMOS. Each of the observed variables is displayed in a rectangle, and each of the latent constructs is displayed in an oval. The evaluation of goodness-of-fit indices supported the model. The w2 test provides that the model generated w2 ¼ 376; df ¼ 110; po0:01; which
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527
Table 4 Reliability analysis of observed variables Latent constructs and description of observed variables
Corrected items-total correlation
Alpha if items deleted
PBTD pnjobrl fmjobrl
Personal benefits from Tourism Development Relationship with tourism of personal job Relationship with tourism of family job
0.57 0.57
0.73 — —
PPTI pecoimp pscimp penimp
Positive Positive Positive Positive
0.58 0.63 0.47
0.73 0.60 0.57 0.75
NPTI necoimp nscimp nenimp
Negative Negative Negative Negative
0.49 0.62 0.51
0.72 0.68 0.52 0.67
OCS satps sated satenv satrec sateco satci satms
Overall community satisfaction Public service satisfaction Formal education satisfaction Environmental satisfaction Recreation satisfaction Economic satisfaction Citizen involvement satisfaction Medical service satisfaction
0.57 0.55 0.32 0.48 0.58 0.50 0.52
0.77 0.73 0.74 0.77 0.75 0.73 0.75 0.74
AATD atdcheju atdcomn
Attitudes for additional Tourism Development Support level in Cheju regional contexts Support level in living community contexts
0.67 0.67
0.80 — —
perceived tourism impacts economic tourism impacts social and cultural tourism impacts environmental tourism impacts Perceived Tourism Impacts economic tourism impacts social and cultural tourism impacts environmental tourism impacts
pecoimp
pscimp
.69
nenimp .52
.81
PPTI .277 .360
satps
a
.634
pnjobrl .80
a
a
.080
sated
.66 .63 .41
satenv
PBTD
AATD .63
fmjobrl
.78
-.101
b
.96
-.121
OCS satrec
.66
.106
a
-.244
.74
atdcheju atdcomn
a
sateco -. 013
.62
satci .68
satms
PNTI .60
necoimp
.81
nscimp
.69
nenimp
Fig. 2. Standardized estimated hypothetical model (a) and (b) indicate significance at the 0.01 and 0.05 levels, respectively. Dashed lines indicate paths that are not significant at 0.05 or better.
indicates a marginal fit (normed w2 ¼ 3:42). Because this w2 test is sensitive to sample size (n ¼ 732 in this study), supplementary measures have been developed. The
other goodness-of-fit indices indicated a good fit within accepted exhortation levels. The goodness-of-fit index (GFI) is acceptable at 0.926, the root mean square error
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of approximation (RMSEA) is acceptable at 0.058, and also the root mean square residual (RMR) is acceptable at 0.044. Path hypothesis 1 (i.e., ‘personal benefits from tourism development’ are positively related to ‘positive perceived tourism impacts’) was supported with an optimal level at t ¼ 6:168 (po0:001) and b ¼ 0:36: But path hypothesis 2 (i.e., ‘personal benefits from tourism development’ are negatively related to ‘perceived negative tourism impacts’) was rejected at t ¼ 0:026 and b ¼ 0:013: Many studies have supported a causal relationship between ‘personal benefits from tourism development’ and ‘perception of tourism impacts’ (e.g., Lindberg & Johnson, 1997; Madrigal, 1993; Perdue et al., 1990). Support for this relationship aligns with common sense that residents (or their relatives, friend, and neighbors) who depend upon tourism-based employment would be more favorable toward tourism (e.g., Liu & Var, 1986; Milman & Pizam, 1988; Murphy, 1983; Pizam, 1978). Although the related hypothesis between ‘personal benefits from tourism development’ and ‘perceived negative tourism impacts’ was supported at t ¼ 27:9 (po0:001) and b ¼ 0:157 by Perdue et al. (1990), this study did not find a significant relationship. It could be that the relationship between ‘personal benefits from tourism development’ and ‘perceived negative tourism impacts’ was strongly dependent upon the level of tourism development or residents’ education level. An important finding of these results is the lack of a significant relationship between benefits from tourism and perceived negative impacts. Path hypothesis 3 (i.e., ‘personal benefits from tourism development’ are positively related to ‘overall community satisfaction’) was rejected at a significant level of 95% (two tailed test, t > 1:96), but supported with a marginal level at t ¼ 1:625 (po0:05) and b of 0.08. If the path relationship between ‘personal benefits from tourism development’ and ‘perceived negative tourism impacts’ was deleted (due to rejection of hypothesis), the t-value decreased to t ¼ 1:587 (p > 0:10). These results suggest that ‘personal benefits from tourism development’ does not contribute to attitude toward ‘overall community satisfaction’. Tourism development is widely perceived as an important community development strategy. It converges with intuition that ‘overall community satisfaction’ would be positively related to ‘personal benefits from tourism development’. However, this relationship was not significant at po0:05: Path hypothesis 4 (i.e., ‘perceived positive tourism impacts’ are positively related to ‘overall community satisfaction’) was supported with an optimal level at t ¼ 10:10 (po0:001) and b ¼ 0:634: Also, path hypothesis 5 (i.e., ‘perceived positive tourism impacts’ are positively related to ‘attitude for additional tourism development’) was supported with an optimal level at t ¼ 4:142
(po0:001) and b ¼ 0:291: Path hypothesis 6 (i.e., ‘perceived negative tourism impacts’ are negatively related to ‘overall community satisfaction’) was supported with an optimal level at t ¼ 2:319 (po0:05) and b ¼ 0:101: Path hypothesis 7 (i.e., ‘perceived negative tourism impacts’ are negatively related to ‘attitude for additional tourism development’) was supported with an optimal level at t ¼ 5:923 (po0:001) and b ¼ 0:244: These results generally converge with those of previous research. Perdue et al. (1990) have reported that this relationship (hypothesis 7) was supported at b ¼ 27 (po0:001). Finally, path hypothesis 8 (i.e., ‘overall community satisfaction’ is negatively related to ‘attitude for additional tourism development’), although negative, was not statistically significant at po0:05 (the t ¼ 1:895 (po0:10) and b ¼ 0:121). Many researchers have suggested that residents’ attitudes toward tourism may be related directly to the degree and/or stage of development within the host community (e.g., Doxey, 1975; Williams, 1979; Butler, 1980; Cooke, 1982; Getz, 1983; Haywood, 1986). These studies suggest that communities have a certain capacity to absorb tourists (Allen et al., 1988). Therefore, the lack of a significant negative relationship between ‘community satisfaction’ and ‘attitude toward additional tourism development’ may be due to the long history of tourism development at Cheju Island. Path hypothesis 9 (i.e., ‘personal benefits from tourism development’ are positively related to ‘attitude for additional tourism development’) was supported with an optimal level at t ¼ 2:635 (po0:01) and b ¼ 0:106: Many studies have found that residents who are economically dependent on tourism tend to favor tourist activity (e.g., Pizam, 1978; Brougham & Butler, 1981). Perdue et al. (1990) also found a strong positive relationship between personal benefits from tourism and attitudes for additional tourism development.
5. Conclusions The purpose of this research was to test a model of residents’ perceptions and attitudes of tourism, examining not only perceptions of tourism impacts, attitudes toward community satisfaction, and additional tourism development, but also the path relationships between perceptions of benefits from tourism development, positive and negative tourism impacts, community satisfaction, and attitudes for additional tourism development. The results support six hypotheses from previous studies, but three of the hypotheses were not supported at po0:05 level. This study found that ‘residents’ community satisfaction’ was closely related to ‘perceived positive tourism impacts’ and ‘perceived negative tourism impacts’. Both perceived positive and negative impacts were directly
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causing ‘attitudes toward additional tourism development’. Perdue et al. (1990) found that resident support for additional tourism was negatively associated with a positive future for the community. Tourism development is viewed not as a goal but as a tool or means of community development. Community satisfaction may be a useful concept for evaluation of residents’ perception 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. But, the hypothesis that ‘personal benefits from tourism development’ would be negatively related to ‘perceptions of negative tourism impacts’ was rejected, and contrasts to findings of past research (e.g., Perdue et al., 1990). The implications suggest that personal benefits from tourism are relevant to understanding perceptions of positive impacts but, in this case, irrelevant to understand perceptions of negative impacts. This may be due to the level of development on Cheju Island, which has a longstanding history of tourism as an integral part of its economy. In other words, the length of time and history of tourism development within a host community may be relevant to understanding residents’ perceptions of tourism (see also Brown & Giles, 1994; Ryan, Scotland, & Montgomery, 1998), and should be addressed as part of future research efforts. Although this study supported some important relationships between residents’ perceptions of tourism impacts and community satisfaction, the limitations include a weak reliability on community economic satisfaction sub-scale along with a sample that may not be representative of the population (e.g., 84% of respondents were between 30 and 49 years of age). Many investigations have suggested that residents’ attitudes toward tourism may be directly related to the degree or stage of development within the host community, which may partially explain the findings. Further research needs to address community satisfaction, level of tourism development, and attitude toward additional tourism development.
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