Journal of Travel Research
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Exploring the Nature of Tourism and Quality of Life Perceptions among Residents
Kathleen L. Andereck and Gyan P. Nyaupane
Journal of Travel Research 2011 50: 248 originally published online 26 May 2010
DOI: 10.1177/0047287510362918
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Journal of Travel Research
50(3) 248­–260
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DOI: 10.1177/0047287510362918
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Exploring the Nature of
Tourism and Quality of Life
Perceptions among Residents
Kathleen L. Andereck1 and Gyan P. Nyaupane1
Abstract
Research on resident attitudes toward tourism has been under way for many years. Implicit in this research is the precept that
tourism influences people’s quality of life (QOL). Few studies, however, have directly investigated residents’ perception of the
impact tourism has on their QOL, and relationships between QOL perceptions and support for tourism in the community.
This study is an attempt to go beyond attitude research and explicitly consider tourism’s influence on QOL. A mail survey was
conducted with a random sample of residents throughout Arizona. The questionnaire included three sets of scales combined
into an index to measure perceived QOL impacts of tourism. Eight QOL domains were developed. In addition, further analysis
found that perceived personal benefit derived from tourism mediated the effect of the economic aspects of QOL, contact
with tourists, and employment in tourism on the perceptions of the role of tourism in the local economy.
Keywords
tourism, quality of life, measurement, residents, perceptions, mediator effect
Tourism has great potential to affect the lives of community
residents. Over the past several years, a number of studies
have considered residents’ attitudes toward tourism and the
impacts tourism can have on a community (Andereck et al.
2005; Andereck and Vogt 2000; Ap 1992; Dyer et al. 2007;
Gursoy, Jurowski, and Uysal 2002; Jurowski, Uysal, and
Williams 1997; Lankford and Howard 1994; Liu, Sheldon,
and Var 1987; McGehee and Andereck 2004; Perdue, Long,
and Allen 1990; Wang and Pfister 2008). While implicit in
this research is the precept that tourism influences people’s
quality of life (QOL) in a community, few studies have
directly investigated residents’ perceptions of the impact
tourism has on their QOL, and relationships between QOL
perceptions and support for tourism in the community. The
importance of a study on perceptions of tourism and QOL is
threefold: first, a study of this nature helps identify residents’
attitudes and perceptions toward tourism’s effect on QOL;
second, the study helps researchers examine resident support
for additional tourism development and specific development policies (Perdue, Long, and Allen 1990); and third, it
identifies the most salient aspects of QOL impacts from tourism to community residents.
QOL has become a topic of broad discussion in recent
years. The purpose of studying QOL is to show how an area
is doing not only from an objective physical design perspective but also from a subjective human response perspective.
At issue is how citizens perceive the community characteristics that contribute to their own QOL and how they
collectively think their region is doing (Morrison Institute
for Public Policy 1997). QOL can be loosely defined as “an
overall state of affairs in a particular society that people
evaluate positively” (Spradley 1976, p. 100). Although the
elements that are valued as contributing to QOL may fluctuate from culture to culture, QOL as a value is considered to
be universal.
Defining QOL is difficult because it is a subjective experience dependent on individuals’ perceptions and feelings.
There are more than 100 definitions and models of QOL,
though there is agreement in recent years that it is a multidimensional and interactive construct encompassing many
aspects of people’s lives and environments (Schalock 1996).
QOL refers to one’s satisfaction with life and feelings of contentment or fulfillment with one’s experience in the world. It
is how people view, or what they feel about, their lives. Similar situations and circumstances may be perceived differently
by different people. Therefore, many scholars feel QOL is
best studied from the perspective of the individual (Taylor
and Bogdan 1990).
Several researchers have developed broad domains or
dimensions of QOL that encompass many facets of an
1
Arizona State University, Phoenix
Corresponding Author:
Kathleen L. Andereck, School of Community Resources and Development,
Arizona State University, 411 North Central Avenue, Phoenix, AZ 85004
Email: kandereck@asu.edu
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249
Andereck and Nyaupane
individual’s life. Schalock (1996, pp. 126-27), when reviewing and synthesizing several years of QOL research, posited
that the following dimensions and indicators seem to capture the body of research on QOL:
1. Emotional and psychological well-being—safety,
spirituality, happiness, freedom from stress, selfconcept, contentment
2. Interpersonal and social relationships—intimacy,
affection, family, interactions, friendships, supports
3. Material well-being, including employment and
economic security—ownership, financial, security,
food, employment, possessions, social economic
status, shelter
4. Personal development, competence and goals—
education, skills, fulfillment, personal competence,
purposeful activity, advancement
5. Physical well-being, including wellness and
recreation/leisure—health, nutrition, recreation,
mobility, health care, health insurance, leisure,
activities of daily living
6. Self-determination, individual control and decisions—autonomy, choices, decisions, personal
control, self-direction, personal goals/values
7. Social inclusion, dignity, and worth—acceptance,
status, supports, work environment, community
activities, roles, volunteer activities, residential
environment
8. Rights, including privacy—privacy, voting, access,
due process, ownership, civic responsibilities
QOL
Tourism and QOL Studies
Few studies have specifically considered tourism’s impact
on QOL. However, resident attitudes toward tourism, and
more specifically perceptions of tourism impacts, have
been a subject of research for more than 30 years. The
difference between QOL and attitudes/impacts studies is
essentially one of measurement: attitude/impact studies
largely focus on the way people perceive tourism influences communities and the environment, whereas QOL
studies are typically concerned with the way these impacts
affect individual or family life satisfaction, including
satisfaction with community, neighborhood, and personal
circumstances (Allen 1990). Attitude and impact studies
are often concerned with tourism-related community changes
and the associated level of support for tourism development. There is an assumed connection between community
characteristics and life satisfaction. Attitude and impact
studies have generally asked residents to agree or disagree
with statements regarding tourism’s perceived impacts on
their community without specific questions linking these
impacts to perceived influences on individuals’ life satisfaction or QOL.
There are many ways in which tourism may influence an
individual’s QOL. An improved QOL can be seen through
the development of tourism products that can also be enjoyed
by residents, such as festivals, restaurants, natural and cultural attractions, and outdoor recreation opportunities. An
improved QOL can also be seen through a higher personal
standard of living through job creation and increased tax revenues that in turn result in services to residents, for example.
Alternatively, tourism can result in negative QOL impacts
such as crowding, traffic and parking problems, increased
crime, increased cost of living, friction between tourists and
residents, and changes in residents’ way of life, all of which
can be detrimental to life satisfaction (Ap and Crompton
1993; Bastias-Perez and Var 1995; McCool and Martin 1994;
Ross 1992; Tooman 1997). A number of studies have documented and thoroughly discussed these potential impacts of
tourism (Allen et al. 1993; Andereck 1995; Brunt and Courtney 1999; Dogan 1989; Haralambopoulos and Pizam 1996;
Hillery et al. 2001; Liu, Sheldon, and Var 1987; Liu and Var
1986; Thomason, Crompton, and Kamp 1979; Tosun 2002).
There have also been many authors who have developed
and/or tested conceptual models investigating the predictors
of attitudes toward tourism (e.g., Dyer et al. 2007; Gursoy,
Jurowski, and Uysal 2002; Ko and Stewart 2002; Perdue,
Long, and Allen 1990). Generally, no consistent relationships have emerged when testing the connection between
traditional demographic variables and tourism attitudes
(Lankford and Howard 1994; Liu and Var 1986; McGehee
and Andereck 2004; Perdue, Long, and Allen 1990; Sirakaya,
Teye, and Sönmez 2002; Tosun 2002). Additional demographic variables that have generally been labeled “community
attachment” and most often measured as length of time
living in a community and/or having been born in a community
have been investigated in some studies, with mixed results
(Davis, Allen, and Cosenza 1988; Deccio and Baloglu
2002; Gursoy, Jurowski, and Uysal 2002; Lankford and
Howard 1994; McCool and Martin 1994; McGehee and
Andereck 2004; Sheldon and Var 1984; Um and Crompton
1987). The only consistent demographic predictor of tourism attitudes has been employment in the tourism industry
with residents who are employed in, or otherwise dependent on, tourism having a more positive perception of
tourism than other residents (Brunt and Courtney 1999;
Deccio and Baloglu 2002; Haralambopoulos and Pizam
1996; Jurowski, Uysal, and Williams 1997; Lankford and
Howard 1994; Liu, Sheldon, and Var 1987; Sirakaya, Teye,
and Sönmez 2002).
Residents’ extent of contact with tourists and knowledge
regarding the tourism industry have shown some relationship to tourism attitudes. Variables such as involvement in
tourism decision making (Lankford and Howard 1994), level
of knowledge about tourism (Davis, Allen, and Cosenza
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250
Journal of Travel Research 50(3)
1988; Lankford and Howard 1994), and amount of contact
with tourists (Brougham and Butler 1981; Lankford and
Howard 1994) have all been examined as predictor variables.
The findings to date suggest that residents who are more
engaged with tourism and tourists are more positively
inclined toward tourism and express more positive attitudes
(Andereck et al. 2005).
Finally, and most importantly, the perceived benefit of
tourism to an individual and tourism’s relationship to attitudes has been previously explored (Jurowski, Uysal, and
Williams 1997; Lankford and Howard 1994; Liu and Var
1986; McGehee and Andereck 2004; Perdue, Long, and
Allen 1990; Wang and Pfister 2008). These studies have all
concluded that residents who perceive greater levels of personal benefit from tourism have more positive attitudes
toward tourism and are more supportive of tourism development than those who do not feel they receive tourism’s
benefit.
Measurement of QOL
As a general rule, resident attitudes toward tourism have
been measured using a number of items with a numerical
scale of responses, often an agreement scale. Most frequently, these items have been combined into multi-item
scales using confirmatory factor analysis in order to identify
specific domains (Andereck and Vogt 2000; Dyer et al. 2007;
Lankford and Howard 1994; Liu, Sheldon, and Var 1987;
Long, Perdue, and Allen 1990; McCool and Martin 1994).
Although the factors that emerged from each study were
slightly different, a few commonalities exist. All researchers
have discovered one or more positive impacts or benefits
dimension(s) and one or more negative impacts dimension(s).
The remaining factors have been partly dependent on the
questions asked. Some studies have found a community
development or related factor (Andereck and Vogt 2000; Liu,
Sheldon, and Var 1987; Long, Perdue, and Allen 1990;
McCool and Martin 1984), a tax levy factor (McCool and
Martin 1984; Perdue, Long, and Allen 1990), a social interaction factor (Sirakaya et al. 2002), and/or a QOL factor
(Andereck and Vogt 2000; Liu, Sheldon, and Var 1987).
Few tourism studies have measured QOL in the way it is
most often measured in sociological studies. To measure
QOL, two types of indicators have been used: (1) objective
circumstances of people’s lives, such as income and education attainment, and (2) subjective evaluation of life
circumstances, such as satisfaction with various aspects of
life (Heal and Sigelman 1996; Schalock 1996). Measures
can also be absolute or relative, indexing people’s QOL or
comparing it to some standard such as what they would
ideally want (Heal and Sigelman 1996). Studies can also
measure general aspects of QOL or specific aspects such as
community services and how these relate to satisfaction with
the community. As well, the unit of analysis for QOL studies
can range from the individual to the world with the individual, family, or community being common units of analysis
(Sirgy et al. 2000).
Many QOL measures, such as the Gross Domestic
Product, the Human Development Index, as well as other
measures, reveal information on only one of the two basic
dimensions of community-related QOL in that they calculate factors external to the individual that can be described
as facts of life or reality (Andereck and Jurowski 2006).
Components of this objective and external dimension
include economic factors such as income, employment
opportunities, job security, social factors such as recreation
oppor­tunities, family structure, social networks, cultural
integrity, and historical infrastructure and environmental
factors such as crowding, noise, litter, traffic congestion,
driving hazards, and air or water pollution. However, when
individuals evaluate their QOL, they incorporate a subjective
dimension into their rating. Their evaluation incorporates
personal feelings and perceptions about their environment
(Dissart and Deller 2000). The subjective dimension of QOL
is emotional and value laden, encompassing factors such as
life satisfaction, happiness, feelings of well-being, and
beliefs about standard of living (Davidson and Cotter 1991;
Diener and Suh 1997; Dissart and Deller 2000; Grayson and
Young 1994). Cutter (1985) explains that the QOL in a
community is composed of the sum of individual community members’ feelings about and perceptions of the objective
conditions within the community (i.e., economic activity,
climate, social/cultural institution, and environmental
conditions).
Consequently, policy makers need information that demonstrates how an area is doing not only from a quantitative
perspective but also from the qualitative perspective that
incorporates how citizens perceive the factors that contribute
to their own QOL (Morrison Institute for Public Policy
1997). To that end, it is important to examine the perspective
of community residents in relation to how they experience
tourism; in other words, the extent to which residents feel
tourism influences aspects of community life that they deem
as personally valuable and contributing to life satisfaction.
Building on these findings from resident attitude and
impact studies and QOL studies to conceptualize the relationship between community characteristics and life satisfaction,
one purpose of this study is to develop a new measurement
approach to tourism and QOL. This article goes beyond the
results presented by Andereck and Jurowski (2006) and
Andereck et al. (2005) by further refining the calculation of
the Tourism and Quality of Life (TQOL) measure and investigating the way in which the items related to perceptions
about the role of tourism in the community. The measure
developed can be considered a subjective measure of life circumstances in that it is based on perceptions; relative in that
respondents compare the existing circumstance to their ideal
standard; and specific because respondents evaluate specific
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251
Andereck and Nyaupane
Demographics
Employment
Education
Income
Sex
Ethnicity
Age
Years in the community
Knowledge
Involvement
Contact
Personal
benefit from
tourism
Tourism’s
role in
community
economy
Tourism and Quality of Life
domains
Figure 1. Conceptual model of the mediating role of personal
benefit on perceptions of tourism’s role in the economy
characteristics of their communities. This measurement
instrument goes beyond the typical resident attitude study
approach to operationalization of variables by incorporating
measures of personal value (importance) and satisfaction
with a number of community characteristics in addition to
perceptions of the way tourism affects these characteristics.
A second purpose is to begin exploring residents’ perceptions of tourism’s impact on QOL and factors that may
influence these perceptions using this instrument. More specifically, the relationship between residents’ perception of
the role of tourism in the local economy and several variables, including demographics, knowledge about tourism,
contact with tourists, involvement in tourism, and tourism
and QOL domains, is explored. Furthermore, resident perception of personal benefit from tourism is tested as a
mediator variable (Figure 1).
Method
Sampling and Data Collection
To ensure a representative sample, the state population of
Arizona was stratified based on census data. Sample quotas
for each county in Arizona and for Hispanic respondents
were determined. Stratifying the sample allowed for
appropriate proportions of rural versus urban residents, a
geographically representative sample, and assurance of a
representative proportion of Hispanic respondents as this is
an important and often underrepresented ethnic group in the
southwestern United States. A telephone survey and a selfadministered mail survey were used to collect data for the
study. The telephone survey portion of the research was conducted by a survey company that used a computer-generated
random sample from a statewide voter registration list. Of
2,844 successful phone calls completed during one of three
tries, 1,003 interviews were completed for a telephone response
rate of 35%. The telephone survey was used only to identify
and enlist respondents and meet the quotas for the sample
strata. The person who answered the telephone was selected
as the interviewee, providing they met the age requirement
of 18 years or older. Names and addresses were confirmed
for the follow-up mail survey.
For the second portion of this study, a questionnaire was
administered to the respondents identified from the telephone portion of the project. The questionnaire was used to
determine the perceived effects of tourism-related economic,
sociocultural, and environmental factors on the QOL of
Arizona residents. After agreeing to participate in the survey,
each subject was mailed a questionnaire; a cover letter; a
stamped, preaddressed return envelope; and an Arizona
Council for Enhancing Recreation and Tourism (ACERT)
map of recreational and tourism sites in Arizona as incentive
to return the survey. In the cover letter, each person was
asked to complete the questionnaire and mail it back in the
enclosed stamped, preaddressed return envelope. In return
for their time and assistance, the potential respondents were
also notified that their names would be entered in a drawing
for a gift set from the clothing line “ArizonaGear.” The initial mailing was followed by a postcard reminder 1 week
later. As a final effort to increase the response rate, a second
survey packet was mailed to those prospective respondents
who had not yet returned their completed questionnaire 3 weeks
after the initial mailing. The response rate for the phone
survey was 35% and for the mail survey 70%, for an n of
695. A comparison of the sample with the state census data
indicated that the final sample was not significantly different
with respect to county of residence and ethnicity, though the
sample included more women, older people, and people with
somewhat higher education and income levels than the general population. These findings are similar to those reported
in other survey research papers (Krosnick 1999; Tolonen
et al. 2006) except for the better representation of ethnic
minorities in this sample and should be kept in mind when
reading the results.
Measurement
The questionnaire included several sections. Section 1 asked
respondents for opinions regarding the role of tourism in the
local economy (1 = no role, 2 = some role, 3 = dominant
role), self-reported knowledge about tourism (1 = not at all
knowledgeable to 4 = very knowledgeable), involvement
with tourism decision making in the community (1 = not at
all to 5 = a lot), amount of contact with tourists (1 = no contact at all to 4 = a large amount of contact), and perception
of personal benefit from tourism (1 = not at all to 5 = a lot).
The next section of the questionnaire included importance
and satisfaction scales with respect to tourism and QOL
items. Respondents were asked to first rate how important
(1 = not at all important to 5 = extremely important) each of
38 tourism-related QOL characteristics were to them personally, then to rate how satisfied they were with each QOL
characteristic in their community (1 = not at all satisfied to
5 = extremely satisfied). The next section included items
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252
Journal of Travel Research 50(3)
measuring perceived effects of tourism on QOL (1 = tourism
greatly decreases to 5 = tourism greatly increases). In this
section, the same 38 tourism-related QOL items used for the
importance and satisfaction scales were used with some
minor rewording to measure respondents’ opinions about
how much tourism decreases or increases each in their communities. The measurement items used for the three sets of
scales of the survey instrument are attributed to, and modified from, a combination of tourism attitude and QOL-related
studies, including Allen et al. (1993), Brown, Raphael, and
Renwick (1998), Inglehart and Rabier (1986), Martin (1995),
McCool and Martin (1994), Perdue, Long, and Allen (1990),
Ross (1992), and Schalock (1996). In addition, a series of
seven focus groups were conducted with diverse tourism professionals to confirm comprehensive inclusion of primary
tourism-related QOL indicators. The final section included
questions about demographic characteristics of respondents.
A series of calculations were used to develop a tourism
and QOL measure. To begin, a QOL score was computed for
each respondent using a method developed by Brown,
Raphael, and Renwick (1998) and further used by Massam
(2002) with some modifications. Their method uses importance and satisfaction ratings of items to determine a QOL
score ranging from –10 to +10. For example, an item rated as
extremely important with which a respondent is extremely
satisfied receives a score of +10. If the item is extremely
important and the respondent is not at all satisfied, an item is
given a score of –10. Items then range between the two end
points depending on the importance and satisfaction ratings
(see Brown, Raphael, and Renwick 1998 and Massam 2002
for more details). For the purpose of calculating a QOL
score, the measures have been modified so they range from
1 to 20 without any zeros and negative scores to facilitate
calculation (see Table 1).
A tourism and QOL index was then computed by using
the respondents’ perceptions of tourism’s effect on QOL in
conjunction with the 1-to-20 QOL indicators calculation.
First the items (with a 1-to-5 scale) were recoded into scores
ranging from –3 to +3, where 1 equals –3, 2 equals –2, 3
equals 1, 4 equals 2, and 5 equals 3. Six negative statements,
such as “tourism increases crime,” were recoded in a reverse
order. The perceptions scores were then multiplied by the
QOL scores. For example, an item with a QOL score of 20
(very important and very satisfied) and a perceptions rating
of +3 (tourism greatly increases) results in a Tourism and
Quality of Life (TQOL) score of +60. If the perceptions
rating was a –3 (tourism greatly decreases), however, the
TQOL score is a –60 (Table 2). Thus, the TQOL score not
only represents the extent to which tourism is perceived to
influence a QOL indicator, but it also denotes an individual’s
value judgment of the indicator by including a measure that
incorporates both importance of, and satisfaction with, that
indicator. Negative scores denote that tourism is playing a
negative role for the quality of the life. Next, the TQOL
scores were factor analyzed to develop TQOL domains.
Table 1. Calculation of Quality of Life Scores Using Importance
and Satisfactiona
Importance Satisfaction
5
4
3
2
1
Brown, Raphael, and
Renwick’s QOL
New Quality
of
Life Score
5 +10
20
4 +5
15
3 0
10
2 -5 5
1
-10 1
5 +8
18
4 +4
14
3 0
10
2 -4 6
1 -8 2
5 +6
16
4 +3
13
3 0
10
2 -3 7
1 -6 4
5 +4
14
4 +2
12
3 0
10
2 -2 8
1 -4 6
5 +2
12
4 +1
11
3 0
10
2 -1 9
1 -2 8
a. Adapted from Brown, Raphael, and Renwick 1998, p. 16.
To test the relationships of several variables as well as the
mediating effect of perceived personal benefit of tourism
(including demographic and various dimensions of QOL) on
the dependent variable of perception of tourism’s role in the
economy, a series of ordinal logistic regression analyses
were conducted. When dependent variables are not perfectly
continuous, ordinary least squared (OLS) regression cannot
be used as it violates the OLS regression assumptions
(Menard 1995). Binary and multinomial logistic regressions
are used when the dependent variable has two and more than
two categories, respectively. The predictor variable, in this
case, was measured neither on a continuous scale nor a nominal scale, but measured as successive categories. When the
dependent variable has an ordinal measurement scale,
ordinal logistic regression analysis is useful to estimate
regression coefficients. It is the best tool for estimating a set
of regression coefficients that predict the probability of the
outcome of interest that is measured on an ordinal scale
(O’Connell 2006).
The analysis follows the three-step mediator analysis outlined by Baron and Kenny (1986). To test if personal benefit
mediates the effect of predictor variables on perception of
tourism’s role in the economy, the following steps were used.
Step 1: regress the mediator (personal benefit received from
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253
Andereck and Nyaupane
Table 2. Means for Quality of Life Indicators
Items
Preserving (peace and quiet)
Feeling safe
Clean air and water
City services like police and fire protection
A stable political environment
Good public transportation
The beauty of my community
Quality of roads, bridges, and utility services
The prevention of (crowding and congestion)
Controlled (traffic)
Controlled (urban sprawl and population growth)
(Litter) control
Proper (zoning/land use)
My personal life quality
The preservation of my way of life
A feeling of belonging in my community
A stable political environment
Having tourists who respect my way of life
The image of my community to others
An understanding of different cultures
Awareness of natural and cultural heritage
Community pride
Opportunities to participate in local culture
Preservation of wildlife habitats
Preservation of natural areas
Preservation of cultural/historical sites
Strong and diverse economy
Stores and restaurants owned by local residents
The value of my house and/or land
Enough good jobs for residents
Plenty of retail shops and restaurants
Fair prices for good and services
Plenty of festivals, fairs, museums
Having live sports to watch in my community
Quality recreation opportunities
The prevention of crime and vandalism
The prevention of drug and alcohol abuse
Tax revenue (sales tax/bed tax)
Importancea
Satisfactionb
QOL Scorec
Tourism Effectsd
TQOL Scoree
4.48
4.66
4.75
4.56
4.01
3.60
4.36
4.41
4.41
4.42
4.34
4.47
4.28
4.66
4.32
3.99
3.79
3.86
3.98
3.81
3.74
4.12
3.36
4.22
4.35
4.16
4.12
3.58
4.41
4.28
3.62
4.28
3.48
3.17
4.10
4.71
4.54
3.89
3.23
3.41
3.04
3.77
2.99
2.41
3.42
3.09
2.72
2.70
2.56
2.93
2.85
3.83
3.42
3.37
3.07
3.23
3.43
3.22
3.36
3.36
3.30
3.09
3.11
3.24
3.15
3.13
3.67
2.92
3.49
3.20
3.28
3.34
3.30
3.13
2.91
2.97
11.07
12.03
10.22
13.72
10.06
7.74
11.95
10.46
8.75
8.65
8.01
9.79
9.37
14.00
11.97
11.77
10.33
10.97
11.81
10.95
11.51
11.66
11.20
10.42
10.53
11.06
10.74
10.51
13.11
9.71
11.88
10.95
11.11
11.40
11.31
10.66
9.65
10.00
0.38
1.09
0.60
1.46
1.15
1.50
1.34
1.45
-1.01
-1.23
-0.48
–0.46
0.00
0.90
0.72
1.05
1.05
0.95
1.79
1.40
1.69
1.50
1.33
1.15
1.28
1.57
1.75
1.26
1.36
1.52
2.02
1.07
2.02
1.81
1.67
–0.30
0.16
1.61
4.79
12.76
7.39
20.09
12.06
12.11
16.27
16.24
-8.62
-11.30
-3.98
–5.56
0.05
13.07
9.21
13.41
11.12
11.72
21.59
15.88
19.88
17.86
15.33
13.19
14.98
18.44
19.27
13.97
18.36
15.83
24.44
11.94
22.86
21.16
19.53
–4.04
1.46
16.81
Note: TQOL = Tourism and Quality of Life measure.
a. Scale: 1 = not at all important to 5 = extremely important.
b. Scale: 1 = not at all satisfied to 5 = extremely satisfied.
c. Range: 1 to 20 (please see Table 1).
d. Scale: for positive items, –3 = tourism greatly decreases to +3 = tourism greatly increases; for negative items, +3 = tourism greatly decreases to –3 = greatly
increases; revised wording in parentheses.
e. TQOL score = QOL × Tourism Effects; range: –60 to 60.
tourism) on the predictors; Step 2: regress the criterion variable (tourism’s role in the economy) on the mediator; Steps 3a
and 3b: regress the criterion on both the predictors alone (a),
and the combination of predictors and mediator (b). To demonstrate the mediation effect, the following conditions must
be met: (1) the predictor must be shown to affect the mediator
(Step 1); (2) the mediator must affect the criterion (Step 2);
and (3) the predictor variables must affect the criterion variable, and the effect of predictor variables on the criterion
variable must be smaller when the mediator is included
(Step 3b) than when it is not included (Step 3a).
Results
Principal components factor analysis with varimax rotation
of TQOL items resulted in eight factors with items that
loaded reasonably well and have fairly strong reliability
(Table 3). Although one domain, recreation amenities, has a
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Journal of Travel Research 50(3)
Table 3. Factor Analysis of Tourism and Quality of Life Domains
Domains
Factor Loadings
Community well-being (TQOLWELL)
Preserving peace and quiet
Feeling safe
Clean air and water
City services like police and fire protection
A stable political environment
Good public transportation
The beauty of my community
Quality of roads, bridges, and utility services
α = .79
Urban issues (TQOLURBAN)
The prevention of crowding and congestion
Controlled traffic
Controlled urban sprawl and population growth
Litter control
Proper zoning/land use
α = .77
Way of life (TQOLLIFE)
My personal life quality
The preservation of my way of life
A feeling of belonging in my community
Resident participation in local government
Having tourists who respect my way of life
α = .73
Community pride and awareness (TQOLPRIDE)
The image of my community to others
An understanding of different cultures
Awareness of natural and cultural heritage
Community pride
Opportunities to participate in local culture
α = .75
Natural/cultural preservation (TQOLPRES)
Preservation of wildlife habitats
Preservation of natural areas
Preservation of cultural/historical sites
α = .87
Economic strength (TQOLECON)
Strong and diverse economy
Stores and restaurants owned by local residents
The value of my house and/or land
Enough good jobs for residents
Plenty of retail shops and restaurants
Fair prices for good and services
α = .66
Recreation amenities (TQOLREC)
Plenty of festivals, fairs, museums
Having live sports to watch in my community
Quality recreation opportunities
α = .59
Crime and substance abuse (TQOLCRIME)
The prevention of crime and vandalism
The prevention of drug and alcohol abuse
α = .66
Excluded variables
Tax revenue (sales tax/bed tax)
Eigenvalue
Variance Explained
8.68
22.83
3.87
10.19
1.73
4.55
1.54
4.06
1.44
3.78
1.28
3.38
1.22
3.20
1.14
3.01
.642
.619
.616
.606
.537
.459
.408
.397
.775
.766
.725
.592
.576
.705
.649
.626
.502
.453
.611
.600
.588
.525
.425
.853
.839
.606
.689
.571
.559
.545
.442
.393
.536
.705
.509
.633
.626
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Andereck and Nyaupane
Table 4. Tourism and Quality of Life Domain Scores
Mean
Recreation amenities
(TQOLREC)
Community pride and
awareness (TQOLPRIDE)
Economic strength
(TQOLECON)
Natural/cultural preservation
(TQOLPRES)
Community well-being
(TQOLWELL)
Way of life (TQOLLIFE)
Crime and substance abuse
(TQOLCRIME)
Urban issues
(TQOLURBAN)
21.18
Standard
Deviation
10.07
18.03 9.28
17.39 9.42
15.55
14.57
12.79
11.58
11.71
-1.47
10.67
17.92
-5.89
14.10
marginally acceptable alpha coefficient, the domain makes
conceptual sense and was retained. Only one item (tax revenue) was excluded after the factor analysis as this item did
not load very well with any of the domains. The eight
domains are (1) community well-being, which includes eight
items related to safety and cleanliness; (2) urban issues,
which includes five items typically considered negative
impacts of tourism and often associated with urban areas;
(3) way of life, which includes five items related to an individual’s way of life; (4) community pride and awareness,
which includes five items related to community image, pride,
and cultural awareness; (5) natural/cultural preservation,
which includes the three preservation-oriented items; (6) economic strength, which includes six items related to economic
impacts; (7) recreation amenities, consisting of three items
related to recreation, sport, and cultural opportunities; and
(8) crime and substance abuse, which is made up of the two
crime-oriented items.
The descriptive statistics show that among eight tourism
and QOL domains, six domains have positive scores, suggesting that tourism enhances perceived QOL (Table 4). The role
of tourism in providing recreation amenities (M = 21.18) was
rated the highest, followed by community pride and awareness (M = 18.03), economic strength (M = 17.39), natural and
cultural preservation (M = 15.55), community well-being
(M = 12.79), and way of life (M = 11.71). However, two
domains, urban issues (M = –5.89) and crime and substance
abuse (M = –1.47), have negative scores, suggesting that tourism plays slightly negative roles on these domains.
In response to the question on the role of tourism in the
local economy, three quarters (74.9%) of the respondents
thought that tourism should play some role in the economy,
and about one quarter (22.9%) thought that tourism should
play a dominant role. Only a small percentage (2.3%) of
respondents perceived that tourism should play no role in
the economy. Of the respondents, 90.5% of respondents
reported that they were knowledgeable about the tourism
industry. As a response to the question on their contact with
tourists visiting their community, 81.9% responded that
they had at least some contact with tourists. In terms of
personal benefit from tourism, on a 5-point scale, the
mean score was 2.7. The mean score (M = 1.6) on involvement in tourism suggests that the respondents did not have
much involvement in the tourism decision making in their
community.
A series of ordinal logistic regression analyses were conducted to test whether personal benefit mediates the role of
TQOL and other predictor variables on the perception of
tourism’s role in the economy. Three different sets of predictor variables, including demographic variables; tourism
knowledge, involvement, and contact; and the QOL domains
were selected for analysis (Figure 1). Personal benefit from
tourism was selected as a mediator variable. Descriptive statistics of these variables are provided in Table 5. Demographic
variables include employment (three categories—directly,
indirectly, and not employed in tourism), education (four categories), income (six categories), sex (dummy variable),
ethnicity (dummy variable—non-Hispanic and Hispanic),
age, and years in the community. Knowledge and contact
were measured as dummy variables, involvement was measured as a continuous variable, and personal benefit was
measured as five categories.
When the above-mentioned steps were followed to test
the mediator effect of personal benefit of tourism on perceptions of the role of tourism in the economy, the following
results were observed.
Step 1: The mediator variable (personal benefit of
tourism) was significantly related to two domains
of QOL, way of life (TQOLLIFE) and community pride and awareness (TQOLPRIDE); as well
as, age, involvement, income, knowledge, contact,
employment, and ethnicity (Table 6). Among the
demographic variables, employment was the strongest
predictor of personal benefit from tourism. The results
revealed that those individuals whose jobs were directly related to tourism were 17.83 times more likely
to perceive benefit from tourism than those whose jobs
were not related to tourism (e2.88 =17.83). Furthermore, income and personal benefit were positively
related. Age, however, has a negative influence on
perception of personal benefit (b = –0.02). As age
increases, perceptions of personal benefit slightly
decrease. There is also a strong association between
race/ethnicity and perception of personal benefit.
When all other demographic variables were controlled, non-Hispanic whites were two times more
likely to perceive the next level of benefit of tourism
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Journal of Travel Research 50(3)
Table 5. Descriptive Table of the Other Variables Included in the Analysis
Variable
Categories
Employment (EMPLOY)
Education (EDU)
Income (INCOME)
Sex (SEX)
Ethnicity (ETHNY)
Age (AGE) Years in AZ (YEARSAZ) Knowledge about tourism industry (KNOW)
Contact with tourists (CONTACT)
Involvement in tourism decision makinga (INVOLVE) Personal Benefit from tourisma (BENEFIT) Role of tourism (ROLE)
n
%
Directly 13
Indirectly 85
Not employed 568
High school or less 137
Some college or technical degree 299
College degree 158
Advance degree 94
>$20K 75
$20K to $39,999 161
$40K to $59,999 185
$60K to $79,999 95
$80K to $99,999 52
$100,000 or more 73
Female 372
Male 307
Caucasian 531
Hispanic 127
M = 54.4, SD = 15.4
M = 27.9, SD = 18.4
Knowledgeable 600
Not Knowledgeable 63
Contact 546
No contact 121
M = 1.62, SD = 0.88
M = 2.70, SD = 1.07
No role
15
Some role 498
Dominant role 152
2.0
12.8
85.3
19.9
43.5
23.0
13.7
11.7
25.1
28.9
14.8
8.1
11.4
54.8
45.2
80.7
19.3
90.5
9.5
81.9
18.1
2.2
74.9
22.9
a. Scale: 1 = Not at all to 5 = A lot.
Table 6. Ordinal Logistic Regression Analysis for Predicting Personal Benefit of Tourism
Variable
TQOLLIFE
TQOLPRIDE
AGE
INVOLVE
INCOME (1) Ref (6)
INCOME (2)
INCOME (3)
INCOME (4)
INCOME (5)
KNOW CONTACT
EMPLOY (1) Reference (3)
EMPLOY (2)
ETHNY Hispanic
Estimate (b)
Standard Error
eb
p
0.03
0.03
-0.02
0.24
-1.14
-0.56
-0.21
-0.42
-0.50
0.74
1.12
2.88
1.17
0.69
0.01
0.01
0.01
0.10
0.40
0.32
0.30
0.33
0.38
0.32
0.24
0.70
0.25
0.23
1.03
1.03
0.98
1.28
0.32
0.57
0.81
0.66
0.61
2.10
3.08
17.83
3.22
2.00
.008
.039
.001
.016
.004
.076
.476
.206
.186
.022
.000
.000
.000
.003
Note: model chi-square (df = 25) = 232.95; -2 log likelihood = 1305.96; Nagelkerke R-square = .375.
than Hispanics. Other variables including involvement in tourism decision making in the community
(b = 0.24), knowledge about the tourism industry
(b = 0.74), and contact with tourists (b = 1.12)
positively influenced the perception of personal
benefit of tourism.
Step 2: The mediator variable (personal benefit) significantly affected the criterion variable (role of
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Andereck and Nyaupane
Table 7. Ordinal Logistic Regression Analysis of Predicting
Perceptions of Role of Tourism in the Economy (without
Mediating Variable)
Variable
Estimate (b)
TQOLECON
CONTACT
EMPLOY (1) Reference (3)
EMPLOY (2)
Table 8. Ordinal Logistic Regression Analysis of Predicting
Perceptions of Role of Tourism in the Economy (Including
Mediating Variable)
Standard
Error
eb
p
0.034
1.240
0.714
0.01
0.39
0.70
1.035
3.456
2.042
0.016
0.001
0.305
0.617
0.29
1.853
0.033
Note: model chi-square (df = 25) = 59.27; –2 log likelihood = 586.35;
Nagelkerke R-square = .15.
tourism in the economy), suggesting that local residents tend to perceive that tourism can play a more
important economic role in the community if they
perceive more personal benefit from tourism.
Step 3a: When examining the effect of predictor variables on the criterion variable (tourism’s role in the
economy), three predictor variables were found to
be significant (Table 7). These variables include
economic strength (TQOLECON), personal benefit
of employment in tourism (EMPLOY), and contact with tourists (CONTACT). The results indicate
that perception of the role of tourism in the local
economy is positively associated with the economic
domain of tourism and QOL, employment in tourism, and level of contact with tourists. The estimated scores indicated that for a one unit increase
in TQOLECON, the probability that the resident’s
positive perception moves to the next category (no
role to some role, or some role to dominant role)
is 4% (e0.03 = 1.04). Although 4% seems low, as
TQOLECON is measured in a scale ranging from
+60 to –60, a small change in TQOL can change
the perception of role of tourism in the economy
significantly. The results also suggested that contact
with tourists plays a significant role. Those residents
who have contact with tourists are 3.46 (e1.24 = 3.46)
times more likely to go to the next level of the role
of tourism than those who do not have contact with
tourists. The results also reveal that residents whose
jobs are indirectly related to tourism are (e0.62 =
1.85) 1.85 times more likely to go on the next level
of the role of tourism in the economy.
Step 3b: When personal benefit (BENEFIT) was included in the model, the effect of predictor variables
(TQOLECON, CONTACT, and EMPLOY) was
less than the previous model (Table 8). The effect
of TQOLECON and CONTACT was reduced, and
the effect of EMPLOY was not significant. The
mediator variable, personal benefit, however, was
Variable
Estimate (b)
TQOLECON
CONTACT
EMPLOY (1) Reference (3)
EMPLOY (2)
BENEFIT (1) Reference (5)
BENEFIT (2)
BENEFIT (3)
BENEFIT (4)
Standard
Error
eb
p
0.030
1.003
-0.336
0.02
0.40
0.79
1.030
2.726
0.715
0.044
0.013
0.671
0.308
-2.513
0.31
0.71
1.361
0.081
0.321
0.000
-2.228
-2.161
-1.350
0.63
0.61
0.60
0.108
0.115
0.259
0.000
0.000
0.025
Note: model chi-square (df = 29) = 80.94; –2 log likelihood = 562.46;
Nagelkerke R-square = .20.
significant as expected with a (e–2.513 = 0.081, 1/.081)
12.35 times increase in the role of tourism to the next
level when local residents receive a lot of personal
benefit compared to not at all. These models clearly
revealed that when personal benefit (BENEFIT) is
controlled, the predictor variables had a smaller effect, suggesting that personal benefit mediated the
relationship between the predictor variables and perception of role of tourism in the economy.
Discussion and Conclusions
This article has proposed a new measurement method for
investigating residents’ perceptions of the manner in which
tourism affects their QOL. Following Brown, Raphael, and
Renwick (1998) and Massam (2002), as well as resident attitude studies, several indicators that have been associated
with tourism were used to develop a measure of how residents view these indicators in the context of life satisfaction.
Then, their perceptions of the way tourism influences these
indicators was included to develop a Tourism and Quality of
Life measure. The TQOL measure presented here provides
an easier calculation method than that introduced by
Andereck and Jurowski (2006). The major contribution of
this study therefore is advancing a QOL measure based on a
subjective approach consistent with that developed in sociology. Existing research has generally considered only a form
of this last measure when explicitly investigating resident
attitudes toward tourism with an implicit assumption of the
QOL connection. It is hoped that this new measurement
method will provide a more accurate assessment of the
manner in which residents view tourism in their communities and the way it affects their lives. The assumption is that
even if an individual feels tourism influences a certain aspect
of her or his community, unless that characteristic is deemed
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Journal of Travel Research 50(3)
personally important, the individual is unlikely to attribute
any meaning to whether tourism positively or negatively
affects that attribute. For example, a resident may feel tourism contributes to more festivals and fairs in the community.
This will positively influence that person’s QOL only if she
or he thinks having such events is important, there are currently not enough, and that tourism will result in more events.
Cleary, more research is needed to further document the utility of this proposed measurement method.
Some aspects of this analysis are similar to that of traditional resident attitudes research, while other aspects differ.
As compared to resident attitude studies, the domains found
in this analysis are somewhat different. There are positive
and negative impact types of factors, including items such as
more jobs, better shopping, more recreation opportunities,
and more crime and traffic, respectively, similar to Andereck
and Vogt (2000), Dyer et al. (2007), and Perdue, Long, and
Allen (1990). There are also QOL-related factors with items
such as cultural exchange, better public services, and more
parks as is the case with other work (Andereck and Vogt
2000; Liu, Sheldon, and Var 1987; Teye, Sönmez, and Sirakaya 2002). The primary difference found in this study with
respect to others, however, is that the domains such as urban
issues, community well-being, economic strength, and
community pride tend to differ with respect to specificity.
Frequently, composite attitude variables have tended to be
more general in nature with more items, whereas the TQOL
factors are more focused (Andereck and Vogt 2000; McCool
and Martin 1984; McGehee and Andereck 2004; Perdue,
Long, and Allen 1990; Sirakaya, Teye, and Sönmez 2002).
The more precisely defined domains allow for an improved
understanding of the way in which residents perceive that
tourism influences their QOL. They do perceive that tourism
has a positive influence on their QOL, especially with respect
to the availability of recreation amenities and feelings of
community pride. They also perceive that tourism positively
influences the economy, facilitates preservation of natural
and cultural resources, can enhance community well-being,
and has an overall positive influence on their way of life. On
the other hand, residents also recognize that tourism can
have negative QOL consequences, such as more crime and
urban issues, though these are not perceived as highly problematic. The analysis is an indication that the TQOL indicators
are measuring perceptions with somewhat more clarity than
existing resident attitude research.
Looking at the variables that help to predict residents’
opinions about the role of tourism in the local economy, the
TQOL domains along with several variables often used in
resident attitudes research were used. Similar to a few earlier
studies, this analysis tested whether personal benefit
mediates the influence of predictor variables (including
demographic and TQOL domains) on the perception of the
role of tourism in the economy (Perdue, Long, and Allen
1990; McGehee and Andereck 2004). Nearly every study
that has included a measure of personal benefit of tourism
has demonstrated the importance of this variable as a predictor of support for tourism. Again, many differences as well
as some similarities to this existing research emerged. As is
often the case, demographic variables, including age, income,
ethnicity, and employment; involvement in tourism decision
making in the community; level of knowledge about the
tourism industry; and contact with tourists emerged as predictors of personal benefit of tourism. In addition, two TQOL
domains, TQOLLIFE and TQOLPRIDE, were predictors of
personal benefit. Although this relationship is often tested in
the opposite direction, with personal benefit predicting attitudes (Ko and Stewart 2002; McGehee and Andereck 2004;
Perdue, Long, and Allen 1990), others have included attitudes as predictors of benefit (Deccio and Baloglu 2002;
Gursoy, Jurowski, and Uysal 2002). To date, there is no
compelling theoretical reason suggesting causality of this
relationship.
When predicting the perceptions of tourism’s role in
the economy, personal benefit mediated the effect of demographic variables and TQOL domains. In the mediator
analysis, personal benefit of tourism mediated the effect of
economic strength (TQOLECON), contact with tourists, and
employment on perception of role of tourism in the economy. Researchers have tended to find that those who have
tourism jobs are likely to perceive that tourism has a more
important role in the economy than those who do not have tourism jobs. In this study, when personal benefit was included
in the model, employment related to tourism was dropped
from the predictors of opinions about tourism’s role in the
economy. Benefit from tourism has been measured in a
number of ways in attitude studies including employment in
tourism. It seems to make sense that those employed in tourism benefit more than those who are not, but this analysis
intimates it is the perception of benefit that is the more powerful measure.
The amount of contact residents have with tourists substantially influences the perception of tourism’s role in the
economy. This suggests that those who have contact with
tourists on a frequent basis view tourism in a much more
positive light than those who do not, as other studies have
also found. However, this relationship is again mediated by
personal benefit. It is becoming increasingly clear that logically, those who gain the most from tourism are the most
supportive of existing and additional tourism development.
The one TQOL domain that emerged as a predictor of tourism’s role is economic strength. Those who feel tourism
effects their QOL from an economic perspective are more
likely to be supportive of tourism in the community than
those who do not feel it is an economic contributor. This is
consistent with the relationship between personal benefit and
tourism’s role in the economy in the sense that personal benefit may be viewed as economic benefit. This finding is
somewhat consistent with the social exchange theory, which
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Andereck and Nyaupane
has often been used as a framework within which to view
resident attitudes. It is also consistent with the emphasis of
tourism providers who tend to build their advocacy messages
to the public and government officials around the economic
impact of tourism rather than other positive QOL effects.
This study has extended traditional resident attitudes
research which has implicitly connected attitude perceptions
to QOL effects’ by developing QOL indicators rather than
only considering attitudes. This includes not only measures of
how residents feel tourism affects aspects of their lives
and communities but whether these attributes are personally
important and their opinions about the current state of their
communities with respect to these indicators. Although the
indicators require further development, testing, and refinement, this is a first step toward more precise measurement
and understanding of the way tourism is perceived as influencing QOL in a community by its residents. Future research
on the relationship between tourism and QOL should consider going beyond the resident attitude approach and consider
not only assessments of agreement with impact items but the
personal importance and satisfaction of such items.
Declaration of Conflicting Interests
The authors declared no conflicts of interests with respect to the
authorship and/or publication of this article.
Funding
The authors received no financial support for the research and/or
authorship of this article.
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Bios
Kathleen L. Andereck, PhD, is the director and a professor, School
of Community Resources and Development, Arizona State University, Phoenix, Arizona.
Gyan P. Nyaupane, PhD, is an assistant professor, School of
Community Resources and Development, Arizona State University, Phoenix.
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