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Tourism Management 36 (2013) 527e540

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Tourism Management

journal homepage: www.elsevier .com/locate/ tourman

How does tourism in a community impact the quality of lifeof community residents?

Kyungmi Kim a,*, Muzaffer Uysal b,1, M. Joseph Sirgy c,2

aDepartment of Nutrition, Dietetics and Hospitality Management, Auburn University, 362 Spidle Hall, Auburn, AL 36849, USAbDepartment of Hospitality and Tourism Management, Virginia Tech, 351 Wallace Hall, Blacksburg, VA 24061, USAcDepartment of Marketing Virginia Tech, 2025 Pamplin Hall Blacksburg, Virginia 24061, USA

h i g h l i g h t s

< A link is found between residents’ perceptions of tourism impact with residents’ life satisfaction.< Tourism impact dimensions are economic, social, cultural, and environmental in nature.< Residents possess life domains that are material, social, emotional, health and safety in nature.< Perceptions of those domains are moderated by the stage of tourism development in the community.< A model based on 321 respondents is provided and tested empirically.

a r t i c l e i n f o

Article history:Received 16 August 2011Accepted 4 September 2012

Keywords:Tourism impactQuality of lifeCommunity residentsLife satisfactionTourism development life cycle

* Corresponding author. Tel.: þ1 334 844 2211; faxE-mail addresses: kkim@auburn.edu (K. Kim), sam

vt.edu (M.J. Sirgy).1 Tel.: þ1 (540) 231 8426; fax: þ1 (540) 231 8313.2 Tel.: þ1 (540) 231 5110; fax: þ1 (540) 231 3076.

0261-5177/$ e see front matter � 2012 Elsevier Ltd.http://dx.doi.org/10.1016/j.tourman.2012.09.005

a b s t r a c t

The objective of this study is to test a theoretical model that links community residents’ perceptions oftourism impact (economic, social, cultural, and environmental) with residents’ satisfaction with partic-ular life domains (material well-being, community well-being, emotional well-being, and health andsafety well-being) and overall life satisfaction. The model also posits that the strength of these perceptualrelationships is moderated by the stage of tourism development in the community. The model was testedusing a survey of 321 respondents from communities varying in their level of tourism development. Theresults were mostly supportive of the overall model. Theoretical and managerial implications of thestudy findings are discussed.

� 2012 Elsevier Ltd. All rights reserved.

1. Introduction

Once a community becomes a tourist destination, the lives ofresidents in that community become affected by tourism activities(Jurowski, Uysal, & Williams, 1997). Over the past several decades,interest in tourism as a tool for regional economic development hasgrown dramatically. Community leaders and economic develop-ment specialists have increasingly treated tourism as an importantindustry that can enhance local employment opportunities, taxrevenues, and economic diversity. Tourism impact studies docu-mented positive and negative effects of tourism on economicwell-being of tourism communities (e.g., Allen, Hafer, Long, &

: þ1 334 844 3279.il@vt.edu (M. Uysal), sirgy@

All rights reserved.

Perdue, 1993; Belisle & Hoy, 1980; Liu, Sheldon, & Var, 1987;Lundberg, 1990; Perdue, Long, & Allen, 1987; Prentice, 1993;Sheldon & Var, 1984; Tosun, 2002; Um& Crompton,1990;Weaver &Lawton, 2001) and a range of other effects on tourism communitiessuch as social well-being (e.g., Ahmed & Krohn, 1992; Andereck,1995; Backman & Backman, 1997; Lankford & Howard, 1994; Liu& Var, 1986; Perdue, Long, & Gustke, 1991; Var & Kim, 1989),cultural well-being (e.g., Kousis, 1989; Pearce, 1996; Tosun, 2002;Wang, Fu, Cecil, & Avgoustis, 2006; Young,1973), and environmentalwell-being (e.g., Ahmed & Krohn, 1992; Andereck, 1995; Farrell &Runyan, 1991; Koenen, Chon, & Christianson, 1995; Var & Kim,1989). However, much of this research has captured the effects oftourism impact using objective indicators of community quality oflife such as poverty, per capita income, crime rates, and pollution(Crotts & Holland, 1993). The question remains: Is tourism impact(economic, social, cultural, and environmental) perceived bycommunity residents? If so, do these perceptions of tourism impactinfluence their sense of well-being in various life domains (e.g.,material life, community life, emotional life, and health and

K. Kim et al. / Tourism Management 36 (2013) 527e540528

safety)? And if so, does residents’ life satisfaction (overall sense ofwell-being) become influenced too? Answers to these questions arevery important to both community leaders and tourism officialsbecause these answers can guide successful planning policies intourism development. For example, if residents’ perception oftourism environmental impact is found to be a positive predictor ofresidents’ sense of health and safety well-being, which in turn isfound to be a positive predictor of life satisfaction, then environ-mental policies and programs should be formulated to encouragetourism development in ways that influence residents’ positiveperception of tourism impact on their sense of health and safetywell-being. Similar implications can be deduced in relation toeconomic, cultural, and social policies and programs.

Most importantly is the notion that tourism impact oncommunity residents’ well-being may vary significantly as a directfunction of the stage of the community in the tourism developmentlife cycle (introduction, growth, early maturity, late maturity, anddecline). For instance, social critics have argued that tourismbecomes unsustainable beyond a certain threshold (e.g., Butler,1980, 2004). This is commonly referred to as “carrying capacity”in the context of the tourist development life cycle. This researchbegs the following question: If tourism impact is indeed perceivedby community residents and these perceptions do influence theirsense of well-being in various life domains and overall life, thencould this influence vary depending on where the community is inthe tourism development life cycle (introduction, growth, earlymaturity, late maturity, and decline)? Again, answers to thesequestions are very important to both community leaders andtourism officials. This is due to the fact that tourism policies andprograms formulated to enhance residents sense of well-being inmaterial, community, emotional, and health/safety life may workmore effectively in certain stages of the tourism developmentlife cycle than others. Such information is vital to tourism devel-opment policy.

To answer these two main questions, we developed and testeda theoretical model that describes how residents’ perception oftourism affects their satisfaction with particular life domains andlife overall in the various stages of the tourism development cycle.The model reflects three major propositions: (1) residents’perception of tourism impact affects their sense of well-being invarious life domains (material, community, emotional, and health/safety well-being), (2) residents’ sense of well-being in those lifedomains affects their life satisfaction in general, and (3) the rela-tionship between residents’ perception of tourism impact and theirsense of well-being in those life domains is moderated by tourismdevelopment stages. The remainder part of the paper describes thebackground of this study, the conceptual development of thetheoretical model, the methods used in testing the model, and thestudy results and their implications.

2. Background

There is a plethora of studies that address tourism impact as animportant component of tourism development and destinationmanagement. Tourism planners typically consider the nature of theimpact and how it can be managed to ensure optimal outcomes(e.g., Beeton, 2006; Gunn & Var, 2002; McIntosh, Goeldner, &Ritchie, 2009; Murphy, 1983). Community planners have criti-cized tourism officials for failing to establish a clear framework todetermine what factors should be considered in their decision-making (e.g., de Kadt, 1979; Gunn & Var, 2002).

In their pioneering work, Mathieson and Wall (1982) and Walland Mathieson (2006) synthesized much of the research on theimpact of tourism. The literature review revealed that tourismimpact can be analyzed from different perspectives: economic,

social, cultural, and environmental. First, the economic impact oftourism has commonly been viewed as a positive economic force,both positively and negatively. With respect to the positiveeconomic impact of tourism, the evidence suggests tourism helpsimprove the standardof living (e.g., Belisle&Hoy,1980; Tosun, 2002;Um & Crompton, 1990), increases investment (e.g., Liu et al., 1987),increases business activity (e.g., Prentice, 1993). In regards to thenegative impact of tourism, the evidence suggests that propertytaxes increases as a result of tourism (e.g., Allen et al., 1993; Perdueet al.,1987), the price of goods and services increases (e.g.,Weaver &Lawton, 2001), and the price of land increases too (e.g., Lundberg,1990). Other studies found no economic effects. For example,Belisle and Hoy (1980) found that residents described the effect oftourism on the cost of land and housing as neutral. These mixedfindings suggest that the tourism impact may change over timebased on the developmental stages of tourism. Several studies (e.g.,Akis, Peristians, & Warner, 1996; Diedrich & Garcia-Buades, 2009;Johnson, Snepenger, & Akis, 1994; Ryan, Scotland, & Montgomery,1998; Upchurch & Teivance, 2000) have provided support for themoderating economic effects of tourism development cycle.

Second, there is the social perspective of tourism impact, bothpositive and negative. Focusing on the negative impact of tourism,studies have shown that communities in the growth stage oftourism development cycle have traffic congestion problems,crowdedness in public areas, as well as other social problems (e.g.,Andereck, 1995; Backman & Backman, 1997). There is also evidencesuggesting that tourism contributes to social ills such as begging,gambling, drug trafficking, and prostitution, as well as uprootingtraditional society, and causing deterioration of the traditionalculture (e.g., Ahmed & Krohn, 1992; Andereck, Valentine, Knopf, &Vogt, 2005; Var & Kim, 1989). In contrast, evidence exists thatsupport the notion that tourism has positive social impact. Forexample, studies have shown that tourism brings more opportu-nities to upgrade facilities such as outdoor recreation facilities,parks, and roads, thus reducing crowdedness in theaters, movies,concerts, and athletic events (e.g., Lankford & Howard, 1994; Liu &Var, 1986; Perdue et al., 1991).

Third, there is the culture perspective of tourism impact, bothpositive and negative. Focusing on the negative impact, sometourism scholars have argued that tourism is a “culture exploiter”(e.g., Pearce, 1996; Young, 1973). Tourism has frequently beencriticized for the disruption of traditional cultural structures andbehavioral patterns (e.g., Kousis, 1989). Looking at the bright side,tourism has also been viewed as a means of revitalizing cultureswhen dying customs are rejuvenated for tourists (e.g., Wang et al.,2006). Tosun (2002) found that cultural impact varied based on theresidents’ social relationship with tourists and concluded that thedifference in the social relationship in regions may be related toresidents’ level of education, ability to communicate with tourist,and their image of international tourists.

Lastly, we have an environmental perspective of tourism impact,both positive and negative. Studies of the environmental impact oftourism focus on tourism development, stress, and preservation(e.g., Farrell & Runyan, 1991). With regard to the positive impact,some believe that tourism helps create a greater awareness of theneed to preserve the environment by capturing its natural beautyfor tourist purposes and increasing investments in the environ-mental infrastructure of the host country (e.g., Var & Kim, 1989).Tourism is also thought to be relatively a clean industry, with lesspollution problems compared to other types of industries (e.g.,manufacturing). This “clean” industry helps improve the physicalappearance of the community and its surroundings (e.g., Perdueet al., 1987; Ritchie, 1988). However, others believe that tourismcauses environmental pollution, the destruction of naturalresources, the degradation of vegetation, and the depletion of

K. Kim et al. / Tourism Management 36 (2013) 527e540 529

wildlife (e.g., Ahmed & Krohn, 1992; Andereck, 1995; Koenen et al.,1995; Var & Kim, 1989).

As previously stated, much of this research has captured theeffects of tourism impact using objective indicators of communityquality of life (Campbell, Converse, & Rodgers, 1976). One can arguethat tourism impact on the community affects many stakeholders.One of the most important stakeholder groups is the communityresidents. Much research is needed to better understand howtourism impact affects community residents’ overall sense of well-being (i.e., perceived quality of life. Specifically, we need to answerthe following questions: Is tourism impact (economic, social,cultural, and environmental) perceived by community residents? Ifso, do these perceptions of tourism impact influence their sense ofwell-being in various life domains (e.g., material life, communitylife, emotional life, and health and safety)? And if so, does residents’life satisfaction (overall sense of well-being) become influencedtoo? Do these perceptions of tourism impact affecting residents’sense of well-being in various life domains and overall life varydepending on the stage of tourism development of the communityin question?

More recently, Andereck and Nyaupane (2011) have developeda measure of perceived impact of tourism on community quality oflife by assembling a large set of items (38) from various publishedsources related to community aspects that have been shown to playa role in residents’ perceived quality of community life (e.g.,preserving peace and quiet, feeling safe, clean air and water, cityservices such as police and fire protection). Respondents(community residents) were asked three sets of questions relatedto the 38 community aspects: (1) their own satisfaction of thesecommunity aspects, (2) their perceptions of importance of thesecommunity aspects, and (3) the extent to which these communityaspects are impacted (increased or decreased) by tourism. A totalquality-of-life score was computed for each respondent by essen-tially multiplying these three sets of measures per communityaspect and averaging across all aspects to derive an index score.Some may argue that such an index serves to answer our firstquestion: Is tourism impact (economic, social, cultural, and environ-mental) perceived by community residents? In someways it does, butperhaps not fully. Such an index may capture the impact of tourismimpact on quality of life of community residents indirectly, notdirectly. A direct measure of tourism impact on quality of life has todemonstrate that this impact correlates highly with establishedmeasures of subjective well-being of community residents (e.g., lifesatisfaction, happiness, subjective well-being, psychological well-being, perceived quality of life, and positive/negative affect). Ourstudy is designed to capture perceptions of tourism impact andrelate these variables to well-established constructs and measuresof quality of life. The current study is also designed to address theremaining questions: do these perceptions of tourism impactinfluence their sense of well-being in various life domains (e.g.,material life, community life, emotional life, and health andsafety)? And if so, does residents’ life satisfaction (overall sense ofwell-being) become influenced too? Do these perceptions oftourism impact affecting residents’ sense of well-being in variouslife domains and overall life vary depending on the stage of tourismdevelopment of the community in question?

3. Conceptual development

To reiterate, our theoretical model that can be captured in termsof three major propositions: (1) residents’ perception of tourismimpact affects their sense of well-being in various life domains(material, community, emotional, and health/safety well-being), (2)residents’ sense of well-being in those life domains affects their lifesatisfaction in general, and (3) the relationship between residents’

perception of tourism impact and their sense of well-being in thoselife domains is moderated by tourism development stages. Seea graphic representation of the model in Fig. 1. We will describe themodel and the hypotheses that are deduced from the model basedon these three major theoretical propositions.

Few studies have addressed ways that tourism enhances theoverall life satisfaction of residents in a community (e.g., Andereck& Nyaupane, 2011). Several studies have supported this propositionby finding that residents view tourism as a benefit to increaserecreational opportunities e.g., (Keogh, 1989; Liu et al., 1987). Otherresearchers found a linear relationship between support fortourism and perceptions of tourism (e.g., Perdue et al., 1987). Still,other studies have inferred that there are varying levels of supportfor tourismwithin a community (e.g., Dogan, 1989; Doxey, 1975), aswell as different perceptions of tourism in the host community(e.g., Jurowski et al., 1997; Perdue, Long, & Kang, 1999; Williams &Shaw, 1988). However, there has not been a study that focused onlife satisfaction of residents as the ultimate dependent variable toestablish the link between perceived impact of tourism and satis-faction with life domains in the destination community.

How does perceived impact of tourism in the community affectresidents’ life satisfaction? To answer this question we will have tovisit the concept of bottom-up spillover theory of subjective well-being (Andrews & Withey, 1976; Campbell et al., 1976). The basicpremise of bottom-up spillover theory is that life satisfaction isfunctionally related to satisfaction with all of life’s domains andsub-domains. Life satisfaction is thought to be on top of an attitude(or satisfaction) hierarchy and therefore is influenced by satisfac-tion with life domains (e.g., satisfaction with community, family,work, social life, health, and so on). Satisfactionwith a particular lifedomain (e.g., social life), in turn, is influenced by lower levels of lifeconcerns within that domain (e.g., perceived impact of tourism onsocial events in the community). That is, residents’ life satisfactionis mostly influenced indirectly by evaluations of tourism impact inspecific life domains such as material life, community life,emotional life, and health and safety. The more positive theperception of tourism impact in community residents’ life domains,the greater the positive affect (and the less negative affect) theseperceptions contribute to those life domains housing those events(psychologically speaking). In other words, these perceptions oftourism impact contribute to positive or negative effects in variouslife domains (e.g., social life, leisure life, family life). In turn, changesin the positive or negative effect in life domains contribute tochanges in life satisfaction; that is, the greater the satisfaction withsocial life, family life, work life, spiritual life, etc., the greater thesatisfaction with life overall.

In sum, bottom-up spillover theory recognizes that satisfactionwith one’s life is mostly determined by satisfactionwith a variety oflife domains. The theory postulates that effects within a specific lifedomain accumulate and vertically spill over to super-ordinatedomains (e.g., life in general). From this discussion we can makea case for the effects of perceived tourism impact (i.e., economic,social, cultural, and environmental impact) on satisfaction of cor-responding life domains (sense of well-being in relation to materiallife, community life, emotional life, and health/safety, respectively),which in turn influences satisfaction with life overall. For example,the more residents perceive economic opportunity from tourism;the result may be that they may feel better in terms of theirmaterial well-being. Likewise, the more residents perceiveincreased recreational facilities because of tourism, the more likelythey feel satisfied with the sense of community well-being. Ifresidents see the community better preserving their own culturalheritage such as local arts and crafts because of tourism, this mayencourage residents to have more pride in their own culturalheritage, which may positively influence residents’ sense of

Fig. 1. The conceptual model and Empirical results.

K. Kim et al. / Tourism Management 36 (2013) 527e540530

emotional well-being. Finally, if residents feel that tourism bring itair or water pollution or may destroy coral reefs or coastal dunes,this perception may negatively influence their sense of health andsafety. As such, our model of perceived tourism impact on resi-dents’ life satisfaction guided by bottom-up spillover theory isshown in Fig. 1. Based on the following discussion we propose totest the following hypotheses:

H1a. Community residents’ sense of material well-being isa positive function of the perception of the economic impact oftourism.

H1b. Community residents’ sense of community well-being isa positive function of the perception of the social impact of tourism.

H1c. Community residents’ sense of emotional well-being isa positive function of the perception of the cultural impact oftourism.

H1d. Community residents’ sense of health and safety is a positivefunction of the perception of the environmental impact of tourism.

H2a. Community residents’ life satisfaction is a positive functionof their sense of material well-being.

H2b. Community residents’ life satisfaction is a positive functionof their sense of community well-being.

H2c. Community residents’ life satisfaction is a positive functionof their sense of emotional well-being.

H2d. Community residents’ life satisfaction is a positive functionof their sense of health and safety.

The moderating effect of the tourism development life cycle hasbeen alluded to by past studies (e.g., Butler, 1980, 2004; Doxey,1975; Lundberg, 1990; Madrigal, 1993; Smith, 1992). The focus ofthese studies has been on social carrying capacity. The underlyingtheoretical premise of these studies is that residents’ quality of lifewill improve during the initial phases of tourism development, butwill diminish after tourism reaches a threshold or carrying capacity,which is the level of acceptable changes beyond which additionaldevelopment causes negative change. In other words, these studiessuggest that communities have a limited capacity to absorbtourists.

Butler (1980, 2004) explained that tourist areas go througha recognizable cycle of evolution illustrating different stages ofpopularity. This evolution is brought about by a variety of factors,including changes in preferences and needs of visitors, the gradualdeterioration and possible replacement of physical plant andfacilities, and the change of the original natural and culturalattractions. He concluded that the evolution reflects four stages: (1)exploration, (2) development, (3) stagnation, and (4) decline.Martin and Uysal (1990) investigated the relationship betweentourism life cycle and carrying capacity and found that eachdevelopment stage has its own carrying capacity. For instance, inthe beginning stage, the carrying capacity might be nearly infiniteon a social level, but, because of lack of facilities, few tourists canactually be accommodated. In this instance, the physical

K. Kim et al. / Tourism Management 36 (2013) 527e540 531

parameters may be the limiting factor. At the other extreme is thematurity stage, at which facility development has reached its peakand large numbers of tourists can be accommodated, but the hostcommunity is showing antagonism toward tourists. On the otherhand, O’Reilly (1986) claimed that carrying capacities can belimited not only by physical attributes but also by social attributes(crowding residents out of local activities), cultural attributes(damaging the local culture), and the economic subsystems of thedestination. Therefore, growth beyond this capacity may result innegative social and environmental impacts and diminishingreturns on tourism investments, which lead to negative economicimpact. If carrying capacity is determined, then economic, socialand environmental benefits can be optimized and negativeconsequences minimized (Allen, Long, Perdue, & Kieselbach, 1988).Based on this discussion, we propose to test the followinghypotheses:

H3a. The relationship between the perceived economic impact oftourism and the sense of material well-being is strongest in thegrowth stage of the tourism development cycle and weakest in thedecline stage.

H3b. The relationship between the perceived social impact oftourism and the sense of community well-being is strongest in thematurity stage of the tourism development cycle and weakest inthe beginning stage.

H3c. The relationship between the perceived cultural impact oftourism and the sense of emotional well-being is strongest in thematurity stage of the tourism development cycle and weakest inthe beginning stage.

H3d. The relationship between the perceived environmentalimpact of tourism and the sense of health and safety is strongest inthe decline stage of the tourism development cycle and weakest inthe beginning stage.

4. Method

The study population consisted of residents of Virginia. Thesample for this study was proportionally stratified from commu-nities representing each of the four tourism development stages,based on four different secondary indicators on counties and citiesin the state. Structural Equation Modeling and HierarchicalMultiple Regression were used to test the study hypotheses. Fig. 1shows the conceptual model, the various hypotheses, anda summary of the path effects. Specifically, the model shows rela-tionships among perceived tourism impact, the sense of well-beingin particular life domains, and life satisfaction. The moderating roleof tourism development stages between the perceived tourismimpact dimensions and the sense of well-being in particular lifedomains. In this model, the various dimensions of perceivedtourism impact are treated as exogenous variables, and the sense ofwell-being in particular life domains are treated as endogenousvariables. Life satisfaction is treated as the ultimate dependentvariable. Sense of well-being in particular life domains are medi-ating constructs between the various dimensions of perceivedtourism impact and life satisfaction. The relationships betweenperceived tourism impact dimensions and the sense of well-beingin particular life domains depend on the tourism developmentalstage (i.e., moderating variable).

4.1. The selection procedure of tourism developmental destinations

The sample for study included residents in selected regions ofVirginia who were at least 19 years of age. First, the areas for each

tourism development stage were selected by using four secondaryindicators followed by a stratified sampling method to determinethe number of respondents required from each county and city foreach development stage. The random sample (mailing list) for thisstudy was obtained from Reference USA data (http://www.referenceusa.com/) in the residential information section.

To select tourism areas to fit each tourism development stage,we used four indicators of the Virginia Tourism Bureau: PopulationGrowth Rate (PGR), Traveler Spending Growth Rate (TSGR), DirectTravel Employment Growth Rate (DTEGR), and State Travel TaxGrowth Rate (STTGR) (Perdue et al., 1991; Toh, Khan, & Koh, 2001).Based on Haywood’s (1986) and Toh et al. (2001) criteria, we wereable to classify all 135 counties and cities in Virginia into the fourtourism development stages: beginning, growth, maturity, anddecline.

Specifically, the selection process for each stage was as follows:The 95 counties and 40 cities in Virginia (135 regions total) werefirst screened using the population growth rate (PGR) from 1990to 2000. The PGR was calculated using the equation:(POP2000 � POP1990)/POP1990. Then, the PGR scores for each countyand city were summed up and divided by 135 to obtain the mean ofthe PGR for all 135 counties and cities. The standard of deviation(SD) of the PGR for all counties and cities was calculated, and thisSD of PGR was divided by two to obtain the 0.5 SD of the PGR. Allcounties and cities were sorted by PGR in ascending order. Thebeginning stage (B) was considered to be from the mean of minus0.5 standard deviation (M � 0.5SD) of the PGR during the availabledata periods to mean PGR (Mean). The growth stage (G) wasconsidered to be from the mean plus 0.5 standard deviation(M þ 0.5SD) of the PGR to the highest PGR (H). The maturity stage(M) was considered to be from the mean PGR (Mean) to the meanplus 0.5 standard deviation (M þ 0.5SD) of the PGR. Lastly, thedecline stage (D) was considered to be from the lowest PGR (L) tothe mean minus 0.5 standard deviation (M � 0.5SD) of the PGR.Three other indicators (tourist expenditure, direct tourismemployment and state travel tax growth rate) were also evaluatedby the same criteria. The criteria used for the developmental stageare shown in Table 1.

Using the PGR, thirty-nine counties and cities were identified asbeing in the beginning stage, ranging from a 4.6% PGR (ClarkeCounty) to 12.5% (Amherst County). The growth stage included 33counties and cities ranging from a 20.4% PGR (Henrico County) to96.8% (Loudoun County). The maturity stage included 23 countiesand cities ranging from a 12.6% PGR (Nelson County) to 20.3%(Augusta County). Lastly, the decline stage included a total of 40counties and cities ranging from a PGR of 4.6% (Halifax County) to�14.3% (Covington City).

We employed the traveler spending growth rate (TSGR) withrespect to the second screening process. Rappahannock County hadan increase of 325% (the highest) in tourist expenditure during theeleven-year period, and the TSGR of Manassas Park City declined by48.3% (the lowest) during the same years. The average TSGR for allcities and counties was plus 82%. Its SD was 71% and the half SD ofTSGR was 35.3%. Using the same criterion of SD, in the secondscreening process, the beginning stage consisted of the 36 countiesand cities ranging from a TSGR of 46% (Appomattox County) to81.6% (Staunton City) over eleven years. The growth stage included31 counties and cities ranging from a TSGR of 118% (ShenandoahCounty) to 325% (Rappahannock County). The maturity stageincluded the 25 counties and cities with a TSGR ranging from 82%(Warren County) to 117% (Essex County). Lastly, the decline stageconsisted of a total of 43 counties and cities ranging in TSGRfrom �48.3% (Manassas Park City) to 45.4% (Montgomery County).

The third screening process was conducted using the directtravel employment growth rate (DTEGR) for 11 years. Powhatan

Table 2Counties and cities in each stage and the number of stratified samples.

PGR(%)

TSGR(%) DTEGR(%) STTGR(%) POP NOS

BeginningLancaster

County6.2 55.0 21.2 65.34 11,567 5% 29

NewportNews City

5.1 67.7 31.2 101.99 180,150 76% 458

WestmorelandCounty

8.0 74.6 36.8 84.38 16,918 7% 43

Wythe County 8.4 76.3 44.7 82.29 27,599 12% 70(6.93) (68.40) (33.48) (83.50) 100% 600

GrowthChesapeake

City31.1 146.7 99.6 177.55 199,184 45% 272

FluvannaCounty

61.3 270.2 212.5 286.67 20,047 5% 27

GreeneCounty

48.0 161.6 177.5 172.50 15,244 3% 21

LoudounCounty

96.8 231.5 214.3 260.80 169,599 39% 231

New KentCounty

28.6 192.4 152.7 183.06 13,462 3% 18

PowhatanCounty

46.0 265.0 600.0 270.00 22,377 5% 31

(51.97) (211.23) (242.77) (225.10) 100% 600

MaturityGloucester

County15.4 114.0 55.0 140.96 34,780 50% 298

NelsonCounty

13.0 113.9 76.6 127.45 14,445 21% 124

RockbridgeCounty

13.4 105.2 66.6 129.19 20,803 30% 174

(13.93) (111.03) (66.07) (132.53) 100% 600

DeclineCovington

City�14.3 �13.3 �46.3 7.50 6303 16% 94

PetersburgCity

�9.0 �6.5 �21.1 3.70 33,743 84% 506

(-11.65) (-9.90) (-36.2) (5.60) 100% 600

Notes.PGR ¼ Population growth rate from 1990 to 2000.TSGR ¼ Traveler spending growth rate from 1990 to 2000.DTEGRG ¼ Direct travel employment growth rate from 1990 to 2000.STTGR ¼ State travel tax growth rate from 1990 to 2000.POP ¼ Populations estimated in 2000 NOS ¼ Number of stratified samples(�) ¼ mean value.

Table 1The criteria of the development stage associated with indicators.

criteria Beginning (B) Growth (G) Maturity (M) Decline (D)

M � 0.5SD < B < mean M þ 0.5SD < G < H Mean < M < M þ 0.5SD L < D < M � 0.5SD

PGR (%) 4.6 < B < 12.5 (39)a 20.4 < G < 96.8 (33) 12.6 < M < 20.3 (23) �14.3 < D < 4.6 (40)TSGR (%) 46 < B < 82 (36) 118 < G < 325 (31) 82 < M < 117 (25) �48.3 < D < 46 (43)DTEGR (%) 15.7 < B < 53.9 (43) 92.4 < G < 600 (27) 54 < M < 92.1 (24) �60 < D < 15.6 (41)STTGR(%) 65.3 < B < 103 (30) 142 < G < 358 (32) 103 < M < 141 (25) �44.3 < D < 65.2 (48)

NOTES.PGR ¼ Population growth rate from 1990 to 2000.TSGR ¼ Traveler spending growth rate from 1990 to 2000.DTEGRG ¼ Direct travel employment growth rate from 1990 to 2000.STTGR ¼ State travel tax growth rate from 1990 to 2000 SD ¼ Standard deviation of the growth rate M ¼ Mean of the growth rate from 1990 to 2000.

a (�) ¼ The number of Counties and Cities in each tourism development stage.

K. Kim et al. / Tourism Management 36 (2013) 527e540532

County increased 600% in DTEGR during eleven years, and Mana-ssas Park City declined by 60% during the same years. The meanDTEGR for all cities and counties was 54%. Its SD was 76.5% and thehalf SD of DTEGR was 38.3%. The beginning stage consisted of the43 counties and cities ranging from a 15.7% DTEGR (BotetourtCounty) to 51.9% (Bedford County) over eleven years. The growthstage included 27 counties and cities ranging from 94% (Mecklen-burg County) to 600% (Powhatan County). The maturity stageincluded 24 counties and cities which fell in the range from a 54.8%DTEGR (Spotsylvania County) to 92% (Northumberland County).Lastly, the decline stage consisted of a total of 41 counties and citiesranging in DTEGR from �60% (Manassas Park City) to 15.4% (Rich-mond City).

Lastly, the fourth screening was done using the state travel taxgrowth rate (STTGR) from 1990 to 2000. Rappahannock Countyincreased 358% in state travel tax during the last eleven years, whileManassas Park City declined by 44.3% during the same years. Themean STTGR for all cities and counties was 102.9%, and its standarddeviation was 75.5%. The half standard deviation of STTGR was37.8%. The beginning stage consisted of the 30 counties and citiesranging from a 65.3%STTGR (Lancaster County) to 103% (NewportNews City) over eleven years. The growth stage included 32counties and cities ranging from a 142% STTGR (Charles CityCounty) to 358% (Rappahannock County). The maturity stage con-tained the 25 counties and cities which fell in the range from 103%(Harrisonburg City) to 141% (Gloucester County). Lastly, the declinestage consisted of total of 48 counties and cities ranging in STTGRfrom �44.3% (Manassas Park City) to 65.1% (Arlington County).

Altogether, the counties and cities were screened and elimi-nated if a county or city did not fall into all four of the indicatorranges: PGR, TSGR, DTEGR, and STTGR. For example, during the lasteleven years, Buchanan County has decreased 13% in population;however, it has increased 8% in traveler spending and 13.8% indirect tourism employment. It is very ambiguous whether thiscounty should be categorized in the decline stage in the sense oftourism development. The final selected counties and cities areshown in Table 2.

The final areas selected for the beginning stage were LancasterCounty, Newport News City, Westmoreland County, and WytheCounty. The counties and cities in the beginning stage of tourismdevelopment increased around 7% of PGR during last eleven years.Also, these areas increased 68%, 34% and 84% in tourist expenditure,direct travel employment, and state travel tax for the same years,respectively. The areas selected for the growth stage were Ches-apeake City, Fluvanna County, Greene County, Loudoun County,New Kent County, and Powhatan County. These areas increasedaround 52% in population growth for the last eleven years. Also,these areas increased 211%, 243%, and 215% in tourist expendituregrowth, direct travel employment, and state travel tax for the sameyears, respectively. The areas selected for the maturity stage were

Gloucester County, Nelson County, and Rockbridge County. Theseareas increased around 13.9%, 111%, 66%, and 133% in populationgrowth, tourist expenditure growth, direct travel employment, andstate travel tax during the last eleven years, respectively. Sixteencounties and cities were identified as the areas for the decline stage

K. Kim et al. / Tourism Management 36 (2013) 527e540 533

for the last eleven years. Among 16 counties and cities, only Cov-ington City and Petersburg City have decreased in terms of pop-ulation growth, tourist spending, and direct tourism employmentfor the last 11 years. These areas have declined around 11.7% inpopulation growth during last eleven years, 9.9% in tourist expen-diture, and 36.2% in direct travel employment; however, the statetravel tax has increased slightly (5.6%) for the same years.

After all areas for each stage were screened, the number ofsubjects was stratified according to the proportion of the pop-ulation in each area, and the random samplingmethodwas applied.The survey questions were sent to the sample size for each desti-nation presented in Table 2. To crosscheck for the level of tourismdevelopment stages in the destinations selected by the secondaryindicators, the survey instrument included a question askingrespondents to assess their perception of the level of tourismdevelopment stages in their own community.

4.2. Sampling

Anderson and Gerbing (1988) suggest that a minimum samplesize should be at least 200 to ensure appropriate use of SEM and tominimize exaggerated goodness-of-fit indices due to small numberof observations. The targeted usable sample size for this study wasset at 480 (120 for each development stage). To achieve the tar-geted sample size, 2400 self-administered survey questionnaireswere sent via the U.S. Postal Service to randomly selected people incommunities representing each of the four developmental stages.Questionnaires were stamped with sequential numbers. Severalwaves of questionnaire mailings were conducted to increaseresponse rate (Dillman, 1978). A cover letter that was signed indi-vidually in blue ink and contained the name and address of therespondent was attached to each questionnaire to enhancepersonalization and thus increase response rate. A self-addressed,stamped envelope was included in the package being mailed.

4.3. The survey instrument

The survey instrument consisted of three sections. The first twosections captured perceptions of tourism impact and the sense ofwell-being in particular life domains using a 5-point rating scales:“strongly disagree” to “strongly agree,” and “very dissatisfied” to“very satisfied.” See exact measurement items in Table 4. The thirdpart of the questionnaire captured demographic information. Thesurvey questions represented the measurement items used tocapture each construct in the proposed model (Fig. 1).

The theoretical model (Fig. 1) for this study is represented byfour exogenous constructs (economic, social, cultural and envi-ronmental perceived impact dimensions) and five endogenousconstructs (sense of material, community, emotional and healthand safety well-being, and life satisfaction). Measurement itemsthat were previously used in tourism impact studies to assesssimilar constructs (e.g., Andereck, 1995; Ap & Crompton, 1998;Cicerchia, 1996; Crandall, 1994; Cummins, 1996; Liu & Var, 1986;Tosun, 2002) and quality-of-life studies (e.g., Andrews & Withey,1976; Duncan, 1969; Fisk, 1997; Liu & Var, 1986; Liu et al., 1987;Samli, 1995; Sirgy, 2001) were adapted for our study. The validityand reliability of measurement items were assessed througha pretest.

4.4. Pretest of the measures

A pretest of the measurement items was conducted in severalstages. First, the survey questionnaire was circulated to severalfaculty and graduate students; theywere asked to provide feedbackregarding the layout, wording, and ease of understanding of the

measurement items. The feedback was used in the revision of thequestionnaire. The revised questionnaire was pre-tested usinga convenience sample of undergraduates and residents of Blacks-burg, Virginia. The responses from the pretest were analyzed to testreliability and validity of the measurement items. The reliability ofthemeasurement instrumentwas assessed using Cronbach’s Alpha.Next, face validity of the measurement instrument was assessed byallowing four professionals to examine it and provide feedback.Convergent validity was assessed by deleting each indicator’sestimated pattern coefficient on its posited underlying constructfactor and determining if a Chi-square difference test betweena model with and without the estimated parameter is significant(greater than twice its standard error, Anderson & Gerbing, 1988).Discriminant validity was also assessed for every possible pair ofconstructs by constraining the estimated correlation parameterbetween them to 1.0 and then performing a Chi-square differencetest on the values obtained for the constrained and unconstrainedmodel (Anderson & Gerbing, 1988).

5. Results

The overall response rate was 13.76% (327 respondents out of2400). Six returned questionnaires were eliminated because theywere returned blank or were only partially completed. After elim-inating the unusable responses, 321 responses were coded andused for data analysis. The answers of the late respondents (thosewho returned completed questionnaires after the second surveyquestionnaire was mailed out) were compared with those of theearly respondents (those who returned the completed surveybefore the second survey questionnaire was mailed out) to test forlate response bias. c2 tests performed on these two groups indi-cated that no significant differences exist in demographic charac-teristics between the early and late responses.

The demographic characteristics of age, length of residency,education, gender, ethnic group, and income are summarized inTable 3. Survey respondents were asked their age in an open-endedquestion. About 48% of the respondents were 55 or older, around41% of the respondents were between the ages of 35 and 54, andthe average age of the respondents was 53.6 years old. More thanhalf of the respondents (53%) were men. The vast majority of thesurvey respondents were white (82.1%), with only 13.8% beingAfrican-American, 1% Hispanic and Asian, and 2.2% others. Lengthof residency in the study area averaged 22.34 years. The majority ofthe respondents (44.6%) had lived in their community for over 20years. Another 19.3% had resided in the same locality for 11e20years. About 20% reported a length of residency of 10 years orless. The largest percentage of households (44.3%) fell into thecategory “married couple living without children.” Around 32%were married with children living at home. Only 5.4% of therespondents described their household as a single parent withchildren, while 18.5% of the respondents reported that they livealone or with other single adults.

5.1. Confirmatory factor analysis

The next step in the analysis was to perform a confirmatoryfactor analysis to confirm the measurement scale properties anda separate confirmatory factor analysis on each dimension of thenine constructs to check the reliability and validity of the indicators.The reliability of the variables is defined as the square of thecorrelation between a latent factor and the indicators. Along withindividual indicator reliability, the composite reliability and vari-ance extracted estimate were calculated (Fornell & Larcker, 1981).Maximum likelihood confirmatory factor analysis requirescomplete data for every subject in order to preserve the integrity of

Table 3Demographic Profile of the respondents.

Category Frequencies Percentages(%)

Age (m ¼ 53.6)Under 25 4 1.325e34 28 9.235e44 60 19.745e54 66 21.755e64 78 25.7Over 65 68 22.4

The years you live in the community(m ¼ 22.34 years)

Less than 10 years 111 35.6From 10 to 20 years 62 19.9Over 20 years 139 44.6

GenderMale 170 53.3Female 149 46.7

Ethnic groupCaucasian 256 82.1Hispanic 3 1.0African-American 43 13.8Asian 3 1.0Other 7 2.2

EducationHigh School 128 39.9College 149 46.7Master or higher 58 18.2Professional 7 2.2

Marital statusSingle adult living alone 58 18.5Single adult with children 17 5.4Married couple living without children 139 44.3Married couple living with children 100 31.8

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the data set. The majority of the variables had four or five missingcases. Therefore, missing values were replaced with themean valueof that variable. After replacement of themissing variables, the totalof 321 samples was kept and this sample size was considered largeenough to satisfy the sample size requirements of confirmatoryfactor analysis. Another criterion requires that the correlationmatrix include multiple measures of each underlying construct(Byrne, 1988). All factors included in this study have at least twoobserved measures.

Before the overall measurement model was tested, measure-ment unidimensionality of each construct was assessed individu-ally (Sethi & King, 1994) because measures that are posited asalternate indicators of each construct must be acceptably unidi-mensional. Unidimensionality of constructs that was measured byat least four observed indicators were tested individually. Unidi-mensionality of constructs that were measured by fewer than fourindicators was tested by pairing the construct with anotherconstruct that also had fewer than four observed indicators.Constructs with unacceptable fit were respecified by deleting theindicators (Anderson & Gerbing, 1988).

First, the unidimensionality of exogenous variables and endog-enous variables was tested. The four exogenous variables wereperceived economic impact, perceived social impact, perceivedcultural impact, and perceived environmental impact, and the fiveendogenous variables were sense of material well-being, sense ofcommunity well-being, sense of emotional well-being, sense ofhealth and safety, and life satisfaction. One of the exogenous vari-ables, perceived economic impact of tourism, consisted of foursummated indicators: employment opportunity, revenue for local

business and government, standard of living, and cost of living. Allother exogenous and endogenous variables used summated scalesif they had sub-dimensions. Assessing each construct’s unidimen-sionality individually and deleting indicators that did not work outas planned decreased the number of indicators in the constructs.After making sure that each construct was unidimensional (Sethi &King, 1994), the overall measurement model fit was tested(Anderson & Gerbing,1988; Jöreskog, 1993; Sethi & King, 1994). Theproposed measurement model had a nine-factor structurecomposed of (1) perceived economic impact, (2) perceived socialimpact, (3) perceived cultural impact, (4) perceived environmentalimpact, (5) sense of material well-being, (6) sense of communitywell-being, (7) sense of emotional well-being, (8) sense of healthand safety, and (9) life satisfaction with 25 observed variables. Asshown in Table 4, four observed variables loaded onto culturalimpact of tourism; three observed variables each loaded ontoeconomic impact of tourism, social impact of tourism, environ-mental impact of tourism, emotional well-being, and life satisfac-tion; and two variables each loaded onto material well-being,community well-being, and health and safety.

Next, the squared multiple correlation (R2) values generated bythe LISREL 8 were used to determine whether the measurementmodel was adequately represented by the observed variables. Thesquared multiple correlation also represents the indicator reli-ability (Bollen, 1989). Examination of the R2 values reported inTable 4 reveals that measures were moderately strong, and most ofthe composite reliabilities were above 0.7. Table 4 also indicatesthat the strongest indicators were three measures of the economicimpact of tourism; three measures of the cultural impact of tourismconstructs and most of the variance extracted estimates were alsoabove 0.50, with the exception of the material well-being andhealth and safety constructs. However, composite reliability scoresbetween 0.60 and 0.70 represent the lower limit of acceptability(Hair, Black, Babin, & Anderson, 2010). Therefore, these values wereaccepted as marginally reliable measurement scales.

Next, overall measurement fit was assessed. The most commonindex of fit is the c2 goodness-of-fit test. The sample size was 321and the c2 value for the saturated model was 452.23, indicating anacceptable fit. With the c2 (and associated p values), various typesof absolute and incremental fit indices were selected to measurethe fit of the tested model. Three absolute goodness-of-fit indiceswere generated: the Goodness of Fit Index (GFI ¼ 0.90), theAdjusted Goodness of Fit Index (AGFI ¼ 0.86), and the ParsimonyGoodness of Fit Index (PGFI ¼ 0.66), indicating that the proposedmeasurement model fits the sample data marginally well. Fiveincremental goodness-of-fit indices were also generated: theNormed Fit Index (NFI ¼ 0.88), the Non-Normed Fit Index(NNFI ¼ 0.92), the Parsimony Normed Fit Index (PNFI ¼ 0.70), theComparative Fit Index (CFI ¼ 0.94), and the Incremental Fit Index(IFI ¼ 0.94), indicating a good fit of the proposed measurementmodel to the data. A cut-off of 200 or greater is suggested as anindication of adequate model fit for the critical N statistic (Bollen,1989). The CN value for the proposed model was 202.68, forwhich the c2 is significant. In addition, the value of the Root MeanSquare Residual (RMR) and standardized RMR (0.047 for both)represents the average discrepancy between samples observed andproposed variance-covariance matrices and indicates a well fittingmodel. Similar to RMSR, the value of the Root Mean Square Error ofApproximation (RMSEA ¼ 0.53) shows that the proposed model isacceptable.

5.2. Testing the main hypotheses

Structural equationmodeling (used by LISREL 8) was used to testthe hypothesized model statistically in a simultaneous analysis of

Table 4Composite reliability and validity of overall measurement model.

Constructs and indicators SL (Li) Reliability (Li)2 VEE

Economic impact variable 0.85 a 0.66b

X1 0.81 0.66 0.34X2 0.80 0.65 0.35X3 0.83 0.68 0.32

Social impact variable 0.79a 0.56b

X4 0.71 0.50 0.50X5 0.77 0.60 0.40X6 0.76 0.58 0.42

Cultural impact variable 0.88 a 0.64b

X7 0.78 0.61 0.39X8 0.89 0.79 0.21X9 0.82 0.67 0.33X10 0.71 0.50 0.50

Environmental impact variable 0.81 a 0.58b

X11 0.86 0.75 0.25X12 0.78 0.60 0.40X13 0.64 0.40 0.60

Material well-being 0.61a 0.43b

X14 0.69 0.47 0.53X15 0.63 0.40 0.60

Community well-being 0.84a 0.72b

X16 0.84 0.71 0.29X17 0.86 0.73 0.27

Emotional well-being 0.82a 0.61b

X18 0.65 0.42 0.58X19 0.92 0.86 0.14X20 0.74 0.55 0.45

Health and safety 0.63a 0.48a

X21 0.65 0.45 0.55X22 0.70 0.50 0.50

Life satisfaction 0.78 0.55b

X23 0.84 0.70 0.30X24 0.86 0.74 0.26X25 0.46 0.21 0.79

Notes: SL ¼ standardized loading.X1 ¼ Employment opportunity.X2 ¼ Revenue from tourist for local business and government.X3 ¼ Standard of living.X4 ¼ Tourism is a major reason for the variety of entertainment in the community.X5 ¼ Because of tourism, roads and other local services are well maintained.X6¼ Increased tourism provides more recreational opportunities for local residents.X7 ¼ Meeting tourists from all over the world is definitely a life-enriching experi-ence.X8 ¼ The cultural exchange between residents and tourists is valuable for residents.X9 ¼ The cultural exchange between residents and tourists is pleasant for residents.X10 ¼ I would like to meet tourists from as many countries as possible in order tolearn about their culture.X11 ¼ Tourism produces large quintiles of waste products.X12 ¼ Tourism businesses that serve tourists throw away tons of garbage a year.X13 ¼ Tourists’ littering destroys the beauty of the landscape.X14 ¼ Income and employment of material well-being.X15 ¼ cost of living of material well-being.X16 ¼ Facilities you get in this community.X17 ¼ People who live in this community.X18 ¼ Spare time.X19 ¼ Your leisure life.X20 ¼ Your cultural life.X21 ¼ Health well-being.X22 ¼ Safety well-being.X23 ¼ Your life as a whole.X24 ¼ The way you spend your life.X22 ¼ The feeling about life compared to others.

a Composite reliability.b VEE ¼ Variance extracted estimate.

K. Kim et al. / Tourism Management 36 (2013) 527e540 535

the entire construct to determine the extent to which it is consis-tent with the data. Fig.1 shows the hypothesized tourism impact onthe quality of life model. The model suggests that tourism impactdimensions influence the particular life domains (H1a, H1b, H1c,and H1d). The results are shown in Table 5.

Positive perceptions of the economic impact of tourism signifi-cantly influenced sense of material well-being (H1a: gamma¼ 0.37,p < 0.01). Then, sense of material well-being significantly influ-enced life satisfaction (H2a: beta ¼ 0.36, p < 0.01). Results indicatethat as the residents’ perception of the benefits of the economicimpact of tourism increases, their satisfaction with material lifeincreases. Consequently, as satisfaction with material life increaseslife satisfaction increases.

Positive perceptions of the social impact of tourism significantlyinfluenced satisfaction with community life (H1b: gamma ¼ 0.40,p < 0.01). However, satisfaction with community life did notsignificantly influence life satisfaction (H2b: beta¼�0.08, p< 0.01).

Positive perceptions of the cultural impact had a statisticallysignificant influence on the sense of emotional well-being (e.g.,satisfaction with leisure life and cultural life) (H1c: gamma ¼ 0.17,p < 0.05). Consequently, the sense of emotional well-being (aspredicted by perceptions of cultural impact of tourism) was relatedsignificantly to life satisfaction (H2c: beta ¼ 0.58, p < 0.01).

With respect to H1d, negative perceptions of environmentalimpact of tourism (e.g., tourists producing large quantities of wasteproducts or destroying the beauty of the landscape by littering)were found to be a significant predictor of satisfaction with healthand safety (H1d: gamma ¼ �0.24 p < 0.05). However, satisfactionwith health and safety did not have a statistically significant effecton life satisfaction (H2d: beta ¼ 0.12 p > 0.05).

5.3. Testing of the moderating effect of tourism development cycle

The basic premise of these moderating effects is that variationsin satisfaction with particular life domains are affected by thelevel of tourism development. This study used hierarchicalmultiple regression/correlation (HMRC) to examine thesemoderating effects. The following procedures were described byCohen and Cohen (1983). Each dependent variable (i.e., a partic-ular well-being domain such as material, community, emotional,and health and safety) was regressed on an independent variable(i.e., tourism impact dimensions such as economic, social, culturaland environmental) and a moderator, the tourism developmentstage recoded as dummy variables. Thus, H3a to H3d wereexamined using the Hierarchical MRC procedure in analyzing thedata. For a sample of 321 responses, the dependent variable (Y)was sense of material well-being and the independent variableswere the perception of the economic impact of tourism (repre-sented by X1). Four groups reflected the four different tourismdevelopment stages. By recoding the nominal scale (tourismdevelopment stages) to dummy variable coding, the decline stagewas set as the reference group, with D1, D2, D3 (X2, X3, X4) codedas 0,0,0; beginning stage coded as 1,0,0; growth stage coded as0,1,0; and maturity stage coded as 0,0,1. Next, interaction vari-ables were formed by multiplying the independent variable ofeconomic impact by three dummy variables of tourism develop-ment stages, resulting in the following three independentvariables:

X5 ¼ X1X2 ¼ eco*D1;X6 ¼ X1X3 ¼ eco*D2;X7 ¼ X1X4¼ eco*D3: ð1ÞBecause perception of tourism impact assesses enduring traits

and is antecedent to the tourism development stages, it was

Table 5Estimated standardized coefficients for the hypothesized model.

Material well-being Community well-being Emotional well-being Health and safety Life satisfaction

Economic impact 0.37** (4.60) �0.12 (�0.71)Social impact 0.40** (4.85) 0.01 (0.07)Cultural impact 0.17** (2.66) 0.10 (1.04)Environmental impact �0.24** (�2.63) 0.11 (1.76)Material well-beingCommunity well-beingEmotional well-beingHealth and safetyLife satis. 0.36** (4.35) �0.08 (�1.17) 0.58** (7.85) 0.12 (1.55)R2 0.13 0.16 0.03 0.06 0.49

Notes.t-value in parentheses.**significant at 0.01 probability level.

K. Kim et al. / Tourism Management 36 (2013) 527e540536

entered first as X1. Then, the tourism development stage (X2, X3,and X4) was added, and finally the interaction set, which consists ofX5, X6 and X7 was added to the main effect independent variable.In Table 6, Eq. (1) shows the results of the hierarchical MRC analysis.In the same table, the complete regression equation with thecomposite coefficient for each stage was restated. In Eq. (1), the firstvalue (2.365) is a constant, the second value (0.230E) is a functionof tourism impacts (E-economic, S-social, C-cultural and E-envi-ronmental), and the third value (�0.225D1 þ 0.507D2 � 0.740D3)represents developmental stage, and the fourth value(0.087ED1 �0.08ED2 þ 0.243ED3) is a combination of develop-mental stage and tourism.

Even though the statistical analysis did not indicate markedlydifferent relationships between level of the perception of thetourism impact and satisfactionwith the life domains, in a practical

Table 6Results of a hierarchical MRC analysis for tourism impact and development stages.

Notes: D1, D2, and D3-dummy coding, Eco-economic impact of tourism; I-increment of

sense, an increase of one point of economic impact of tourism isassociated with an average increase of 0.473 points in sense ofmaterial well-being in the tourism maturity development stage.This increase is three times as great as that for the residents in thegrowth stage. Table 7 and Fig. 1 show a summary of the hypothesestesting results.

6. Discussion

We conducted this study to answer a set of questions. These are:Is tourism impact (economic, social, cultural, and environmental)perceived by community residents? If so, do these perceptions oftourism impact influence their sense of well-being in various lifedomains (e.g., material life, community life, emotional life, andhealth and safety)? And if so, does residents’ life satisfaction

R2; and df-degrees of freedom *significant at 0.05; **-significant at 0.01 levels.

Table 7The summary of hypotheses testing results.

Hypotheses Results

H1a: Sense of material well-being is a positive functionof the perception of the economic impact of tourism

Supported

H1b: Sense of community well-being is a positive functionof the perception of social impact of tourism

Supported

H1c: Sense of emotional well-being is a positive functionof the perception of cultural impact of tourism

Supported

H1d: Sense of health and safety is a positive function of theperception of environmental impact of tourism

Supported

H2a: Life satisfaction is a positive function of sense ofmaterial well-being.

Supported

H2b: Life satisfaction is a positive function of sense ofcommunity well-being.

Notsupported

H2c: Life satisfaction is a positive function of sense ofemotional well-being.

Supported

H2d: Life satisfaction is a positive function of sense of healthand safety.

Notsupported

H3a: The relationship between economic impact of tourismand material well-being is strongest in the growth stageof the tourism developmentcycle and weakest in the decline stage

Notsupported

H3b: The relationship between social impact of tourismand community well-being is strongest in the maturitystage of the tourism development cycle and weakestin the beginning stage.

Partiallysupported

H3c: The relationship between cultural impact of tourismand emotional well-being is strongest in the maturitystage of the tourism development cycle and weakestin the beginning stage

Notsupported

H3d: The relationship between environmental impactof tourism and health and safety is strongest in thedecline stage of the tourism development cycle andweakest in the beginning stage.

Partiallysupported

Notes.S ¼ statistical sense.P ¼ practical sense.

K. Kim et al. / Tourism Management 36 (2013) 527e540 537

(overall sense of well-being) become influenced too? Do theseperceptions of tourism impact affecting residents’ sense of well-being in various life domains and overall life vary depending onthe stage of tourism development of the community in question?

The results of the study provided the following answers. Yes,community residents do have perceptions of tourism impact interms of the four aforementioned dimensions: economic, social,cultural, and environmental. And yes, these perceptions of impactdo influence their sense of well-being in corresponding lifedomains. Specifically, positive perceptions of economic impactwere found to significantly predict residents’ sense of materialwell-being; positive perceptions of social impact were found tosignificantly predict residents’ sense of community well-being;positive perceptions of cultural impact were found to significantlypredict residents’ sense of emotional well-being; and negativeperceptions of environmental impact were found to significantlypredict residents’ sense of health and safety.

As Jurowski et al. (1997) argued, once a community becomesa tourist destination the lives of residents in the community areaffected by the tourism in better or worse ways. Therefore, satis-faction or dissatisfaction with living conditions (e.g., employmentand income), influenced by the perception of tourism, spill oververtically to satisfaction with life domains. Consequently, satisfac-tion with a particular life condition influences the overall lifesatisfaction of residents. Like other studies, this study founda positive relationship between the economic impact of tourismand residents’ sense of material well-being. Tourism is perceived toincrease the standard of living of community residents, helpsgenerate employment, and increases revenues to local business(e.g., Backman & Backman, 1997; Gursoy, Jurowski, & Uysal, 2002;Jurowski, Daniels, & Pennington-Gray, 2006).

This study finding was also consistent with previous studies indemonstrating a positive relationship between the social impact oftourism and residents’ sense of community well-being, meaningthat as residents increasingly perceive the positive social impact oftourism, their satisfaction with the community well-beingincreases. In the study of Backman and Backman (1997) and Varand Kim (1989) residents in the community agreed that shoppingfacilities built to serve tourists also serve residents, that services ofall kinds offered to tourists in turn serve local residents, and thattourism generates the impetus to improve and further developcommunity infrastructure.

In addition, our study found that the relationship between theperceived cultural impact of tourism and residents’ sense ofemotional well-being is significantly positive. When residentsagree with statements such as “I would like to meet tourists fromas many countries as possible in order to learn about their culture”and “the cultural exchange between residents and tourists isvaluable for the residents,” residents develop an increased senseof emotional well-being related to spare time, leisure life, andcultural life. As Var and Kim (1989) reported, tourism contributesto the renaissance of traditional arts and crafts, and helps promoteunderstanding of different people through cultural exchange.Tourism also helps keep culture alive, helps preserve traditionalart forms, and maintains cultural identity and the transmission ofcultural beliefs and rituals to the next generation (e.g., Chen,2000).

Lastly, our study found that there is a negative relationshipbetween the environmental impact of tourism and residents senseof health and safety. Researchers have found that tourism helpscreate greater awareness and appreciation of the need to preservethe environment to preserve its natural beauty for tourist purposes(Var & Kim,1989). As Bubloz, Eicher, Evers, and Sontag (1980) notedthe environment is the place that provides sustenance. Thus, theenvironment should be preserved and enhanced to provide suffi-cient resources to meet the needs of community residents. If resi-dents perceive the positive environmental impact of tourism, theyare likely to develop an increased sense of health and safety.However, tourism has often been considered as a negative influ-ence on the environmentdcontributing to the destruction ofnatural resources, the deterioration of cultural and historical sites,and the proliferation of litter, garbage, and waste (Andereck et al.,2005; Tosun, 2002). In conclusion, when residents perceive thepositive economic, social, and cultural impact of tourism, satisfac-tion with related life domains (sense of material, community, andemotional well-being) increases too. However, when residentsperceive the negative environmental impact of tourism, their senseof health and safety decreases as a result.

With respect to the question about whether residents’ sense ofwell-being in material life, community life, emotional life, andhealth and safety contribute significantly to their satisfaction withlife overall, the answer seems to be mixed. Yes, residents’ sense ofmaterial well-being and emotional well-being were found tosignificantly predict their life satisfaction. However, contrary toexpectations, residents’ sense of community well-being and healthand safety failed to predict their life satisfaction.

The latter findings may be explained as follows: Andrews andWithey (1976) and Argyle and Lu (1990) asserted that social funand family contribute more to happiness than to life satisfaction.Life satisfaction may be interpreted by respondents as satisfactiontoward overall living conditions and life accomplishments. There-fore, the sense of community well-being (e.g., satisfaction withvariety of entertainment opportunities in the community, well-maintained roads and other local services) may contribute to resi-dents’ happiness more than life satisfaction. The distinctionbetween life satisfaction and happiness may explain why the sense

K. Kim et al. / Tourism Management 36 (2013) 527e540538

of community well-being did not have a statistically significanteffect on residents’ overall life satisfaction.

With respect to the lack of significant effect of sense of healthand safety on life satisfaction, this finding is not consistent withprevious research. Past studies have demonstrated that feelingsabout personal health spill over to overall life satisfaction, becausepersonal health is considered important in one’s evaluation of life(Andrews &Withey, 1976). One explanation of this anomaly may bethe fact that the sense of health and safety in a community contextmay not play a significant role in one’s overall evaluation of one’slife. Given the community setting as a backdrop of the survey,respondents may have felt threats from environmental degradationand refuse problems that are not directly related to them.

The last research question that our study addresses is: Do theseperceptions of tourism impact affecting residents’ sense of well-being in various life domains vary depending on the stage oftourism development of the community in question? The answer tothis question turned out to be complex.

We hypothesized that residents in the community usually startto perceive the economic impact of tourism in the beginning stageof tourism development, and feel the most benefit of tourism in thegrowth stage. Afterwards, residents develop perceptions of thesocial, cultural, and environmental impact of tourism in thematurity stage, and perhaps may feel these tourism impacts moststrongly in the decline stage. The results of our study did notindicate the statistically significant results but showed somemeaningful moderating effects of the tourism development stage.

This study results showed that the relationship between theeconomic and social impact of tourism and the satisfaction with itscorrespondent life domains (material well-being and communitywell-being) initially decreased in the growth stage of tourismdevelopment and peaked in maturity stage of tourism develop-ment. However, when a community enters the decline stage oftourism development, the strength of the relationship between theeconomic and social impact of tourism and the satisfaction withcorrespondent life domains decreases. This finding is consistentwith the theoretical foundation of carrying capacity–the destina-tion maximizes its capacity to absorb tourists, and after the hostpopulation feels negative impacts, community residents lose theirsense of economic and social benefits from tourism; and thosefeelings become increasingly negative as a function of over-crowded conditions and rising living costs. However, the relation-ship between the cultural impact of tourism and the satisfactionwith emotional well-being decreased in the growth stage oftourism development, increased in the maturity stage, and peakedin the decline. The theory of social carrying capacity did not offermuch to explain this result. This result may be evidenced withButler’s (1980, p 9) argument that “in the decline stage, moretourist facilities disappear as the area becomes less attractive totourists and the viability of existing tourist facilities becomes moreavailable to residents in the destination community.” Residentsmay come to realize that tourism provides and preserves theircultural legacy even after the community experience a decline intourism. The relationship between the environmental impact oftourism and the satisfaction with health and safety well-beingincreased in the growth, decreased in the maturity, and peaked inthe decline stage. This result confirms Butler’s (1980, 2004) conceptof the tourist area cycle of evolution: as residents’ perception ofnegative environmental impacts increases, their satisfaction withhealth and safety well being decreases in the decline stage oftourism development unless the area as a destination providesrejuvenating or alternative planning options. When a communityenters into the decline stage, community residents becomeincreasingly aware of environmental deterioration, which in turnmay adversely influence their sense of health and safety.

6.1. Implications of the study

Findings of this study are important to tourism developers in thehost community. Tourism planners need to develop not onlya short-term perspective of tourism benefits, but also a long-termperspective of residents’ QOL and sustainable tourism. This studyshowed that as residents’ perception of the tourism impactincreases, their life satisfaction with various life conditionsincreases, and that this effect finally influences their overall lifesatisfaction. Tourism development strategists need to consider thestrength of this relationship, and focus on maintaining the resi-dents’ highest life satisfaction derived from various tourismdimensions.

This finding also suggests that tourism developers andmarketers should know how residents perceive tourism impactsand how it affects their life satisfaction according to tourismdevelopment stages. For example, this study revealed that therelationship between the economic impact of tourism and materialwell-being was strongest in the maturity stage but the relationshipdecreased in the decline state. Therefore, even though residentsperceive tourism as positively associated with their life satisfactionin the maturity stage, this feeling may quickly turn into a negativeperception. For this reason, tourism developers should plana strategy that emphasizes residents to perceive a positiveeconomic impact of tourism in the beginning stage of the devel-opment and to fully recognize it in the growth stage, and toperceive a positive cultural impact of tourism in the decline stage,and feel more satisfaction in emotional well-being.

The local involvement in tourism is likely to increase at thisstage, as employees and other residents are able to purchasefacilities at significantly lower prices as the market declines.However, residents’ positive perceptions may again quickly becomenegative when they perceive the negative environmental impact oftourism. Therefore, tourism developers should try to rejuvenate thetourism destination before that community reaches a maximumcarrying capacity and a decline stage.

Individuals seeking to gather support from the community foran already established tourism industry may find the results of thisstudy useful. The research demonstrates that perception of thepositive social impact of tourism was an important determinant insatisfaction with community well-being, suggesting that internalmarketing techniques designed to inform residents of the socialbenefits they receive from tourism may be helpful in gaining theresidents’ support for the development, successful operation, andsustainability of tourism. Promotion of the positive social andeconomic benefits of tourism may serve to sway the opinion ofresidents who perceive that they have little to gain economicallyfrom tourism. Further, support from otherwise neutral residentsmay be gained by the dissemination of information concerningsecondary economic benefits received by community memberswhose household income is not directly tied to tourism. Conser-vation and preservation programs for the community may serve toease the concerns of residents who are skeptical about the envi-ronmental impact of tourism.

In addition, the measurement instrument refined and tested inthis study could be used via a mail survey to appraise how theresidents in the community perceive tourism impact and whetherthey perceive it as enhancing the QOL of the residents in thecommunity. Also, the data generated by periodically administeringthe survey to residents, tourism developers, and managers (CBVdirectors or persons related to tourism industry) can be examinedand compared with the mean score of the perceptions of tourismimpact and life satisfaction. It should be noted that these conclu-sions may not be appropriate for all rural communities which donot have any tourism establishments. However, the tools developed

K. Kim et al. / Tourism Management 36 (2013) 527e540 539

for this research might be useful in other communities. Throughapplication of the principles determined by this research, tourismdevelopers in a variety of tourism settings may be able to ascertainthe strength of each factor in determining support for alternativeplans.

In assessing the implications of this paper it needs to be alsonoted that the purpose of the paper in one of hypothesis testing,and not simply description. From the latter perspective it could beargued that the research suffers from a sample that consisted ofresidents residing in pre-selected cities and counties of Virginiabased on four secondary indicators in 2002. It is recognized thattime and place associated with data gathering is extremelyimportant in descriptive research because descriptive researchfocuses on identifying and describing the parameters of certainconstructs and providing external validity. However, in hypothesis-testing research, the emphasis is placed on internal validity (i.e., thetheoretical relationships among the constructs). From thisperspective the fact that the data were gathered in 2002 does notdiminish the overall contribution of the study to the tourismliterature.

6.2. Limitation of the study

One limitation of the study was that the sample population ofthe study consisted of residents residing in pre-selected cities andcounties of Virginia based on four secondary indicators. Thismethodology means that the areas selected for tourism develop-ment stages did not fully coincide with the tourism developmentstages from the literature. Butler (1980) and Haywood (1986)divided the areas into different stages by using tourist arrivals. Ifthe areas had been selected by using the number of visitors toa community, the results might have been different. However, itwas difficult to count the exact number of visitors for a community.One solution to this problemmay be to divide the area according toits CVB (Convention and Visitors’ Bureau) territory, not by itspolitical territory, because CVB counts roughly the number ofvisitors. In addition, this study focused only on residents in Virginia.If the study were conducted on residents of other states andcounties, the magnitude and direction of the relationship betweentourism impact and overall life satisfaction might be different. Also,if the survey were extended to include business people, tourismplanners, or other stakeholders in the tourism community, theremight be different levels of perception of tourism impacts onoverall life satisfaction. Including many residents in other sectorsmay help us better understand the relationship between tourismimpacts and life satisfaction and the role of tourism developmentstages.

This study examined the influence of four tourism impactdimensions on four specific well-being domains. One limitation isrelated to testing only the influences of one tourism impactdimension on one particular life domain. Future research shouldinvestigate dynamic interactions among impact dimensions andparticular life domains. Among those, further research may findsome spillover effects. For example, the satisfaction with commu-nity well-being might influence the satisfaction with emotionalwell-being; this influence may be the reason that satisfaction withcommunity well-did not has a statistically significant effect onoverall life satisfaction. In addition, future research should test therole that positive and negative impacts of tourism might havebefore they are divided into various dimensions of tourism impacts.

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