Content uploaded by Korawan Sangkakorn
Author content
All content in this area was uploaded by Korawan Sangkakorn on Feb 25, 2014
Content may be subject to copyright.
Factors Influencing Local Resident Support for Tourism
Development: A Structural Equation Model
1
Akarapong Untong
Student of Tourism Environmental Economics
The University of the Balearic Islands, Spain
Akarapong_un@hotmail.com
Mingsarn Kaosa-ard
Public Policy Studies Institute
Chiang Mai University, Thailand
mingsarn@chiangmai.ac.th
Vicente Ramos
Department of Applied Economics
The University of the Balearic Islands, Spain
Vicente.ramos@uib.es
Korawan Sangkakorn
Social Research Institute
Chiang Mai University, Thailand
korawana@hotmail.com
and
Javier Rey-Maquieira
Department of Applied Economics
The University of the Balearic Islands, Spain
Javier.rey@uib.es
ABSTRACT
The objective of this article is to study the causal relationship between a
destination’s tourism potential, the impact of tourism, and local resident support for
tourism development in four tourist destinations in Thailand: Phuket, Chiang Mai,
Pattaya, and Pai. A Structural Equation Model (SEM) was used to analyze the data
1
Best Paper Award in The APTA Conference 2010 at Macau, China between 13-16 July
2010.
2
(sample size of 1,367). The model contains 15 observable variables; four external
latent variables (destination potential, economic impact, social and cultural impact,
and environmental impact); and one internal latent variable (local resident support for
tourism development in their communities).
The study reveals that local residents see private cooperation as an important
factor in their support for local tourism development. Economic impact is the main
factor influencing local resident support for tourism development, but the magnitude
of influence varies by destination. Increase in investment and business opportunities are
important economic impacts for traditional tourist destinations such as Phuket and Pattaya.
Local residents in newer tourist destinations like Chiang Mai and Pai give more
importance to local employment opportunities. Regarding areas of development, local
residents in traditional destinations would like to see development in social and cultural
attractions, while in newer destinations local residents prefer to see continuous
development in the physical attractions and amenities. The results also show that
social and cultural as well as environmental impacts create only a low level of stress on
local resident support for tourism development. The results of the study suggest
different policy implications for local resident support for tourism development in
different destinations if sustainable development is to be achieved.
Keywords: local resident support, local tourism development, Structural Equation
Model.
3
INTRODUCTION
Tourism development is one of the important economic activities used to
promote economic growth in local communities (Ko and Stewart, 2002; Mingsarn, 2007).
The development or promotion of local tourism also creates employment, income, and tax
revenue, as well as an opportunity to develop community infrastructure (Lankford and
Howard, 1994; Akrapong, 2006). These benefits are often cited as successful outcomes of
local tourism development (Perdue, Long and Allen, 1990; Lawton, 2005; Leep, 2007).
In developing countries, the economic benefits of tourism development are often
regarded as of primary importance (Cook, 1982; Ko and Stewart, 2002), while its
social, cultural and environmental costs and impacts are of secondary importance (Liu
and Var, 1986; Bastias-Perez and Var, 1995). However, these tend to increase with
increasing levels of local tourism development (Butler, 1980; Akis, Peristanis and Warner,
1996; Dyer, et al., 2007). Therefore, the primary goal of local tourism development is
how to manage such development to achieve the highest level of benefits with least
costs.
Over the last decade, a wide range of studies on the impacts of tourism
development on local communities has been conducted (Akis, Peristanis and Warner,
1996; Dyer, et al., 2007). The success of local tourism development depends on the
destination’s attractions and other supporting factors within the communities.
Efficient local management is also important, whether it is the management to reduce
the negative impacts or the costs of development, or the management of its benefits so
these benefits can be distributed appropriately and just among local residents. Proper
management of these impacts will lead to sustainable development.
Not only can the impacts directly affect local residents but also they can directly
influence
the support for tourism development within the community (Yoon, Gursoy and Chen,
2001; Ko and Stewart, 2002; Dyer, et al., 2007).
Local resident support for tourism development is therefore dependent on
perceived benefits or anticipated costs of development (Perdue, Long and Allen, 1990;
Getz, 1994; Lindberg and Johnson, 1997; Yoon, Gursoy and Chen, 2001; Ko and
Stewart, 2002). The impacts of tourism development include economic, social and
cultural, and environmental (Yoon, Gursoy and Chen, 2001; Ko and Stewart, 2002;
Akarapong, 2006; Dyer, et al., 2007), as well as communal such as local residents’ pride in
their communities and their unity and cooperation (Akarapong, 2006). Moreover, the
relationship between local residents’ perceptions of the impacts from tourism development
and their support may be regarded as causal in nature. The perception of the impacts of
tourism development may affect local resident support directly or indirectly. The
perception of economic impacts normally produces a positive influence on local
4
resident support for tourism development (direct relationship), while social, cultural, and
environmental impacts normally have a negative influence on local resident support for
tourism development (inverse relationship) (Yoon, Gursoy and Chen, 2001; Ko and
Stewart, 2002; Akarapong, 2006; Dyer, et al., 2007).
Differences among destinations’ resources and levels of development (Butler,
1980) as well as their varying sizes mean that the impacts from development and local
resident support are also different among these destinations (Yoon, Gursoy and Chen,
2001; Akarapong, 2006). This article therefore attempts to study the differences in
the structure of causal relationships between the development potential, tourism
impacts, and local resident support for tourism development in four important tourist
destinations in Thailand. The study will provide a better understanding of local
resident attitudes toward the development impacts of tourism and their support for
local tourism development under different conditions. The results of the study should
lead to better planning and policymaking in local tourism development to make it
more successful and sustainable in the future. The results of the study could also be
used as guidelines in policy implementation to make local tourism development more
suitable to local needs and help prevent any conflict that may occur among local
residents from such development in the future.
TOURISM DEVELOPMENT IN IMPORTANT TOURIST DESTINATIONS
OF THAILAND
Tourism development in Phuket
Before the 1997 economic crisis, the tourism industry in Phuket grew at an
average annual rate of 19.5%, despite a slight drop (-0.7%) in 1996. During the
periods 1998-2001 and 2002-03 (before SARS), the industry experienced decreasing
annual growth rates of 10.3% and 5.5%, respectively. SARS, which occurred in 2003,
did not have a significant impact on the number of tourist arrivals in Phuket. However the
Tsunami did have a direct impact on the tourism industry in Phuket. The number of
tourist arrivals in Phuket dropped significantly (-18.8%) the year after the Tsunami
before picking up at a very high rate one year later. The industry has expanded
continuously since then. This continuing growth is the result of the fact that Phuket is
a fully integrated destination for tourists. Many airlines fly direct and frequently to
Phuket from abroad, including Hong Kong, Sydney, and Guangzhou. Festivals/events are
organized throughout the year, including the Chinese New Year, Vegetarian Festival,
Phuket International Marathon, Johnny Walker Golf Classic, and Andaman Sea Rally.
5
Tourism development in Chiang Mai
Before the SEA Games, which were held in Chiang Mai in 1993, the tourism
industry in Chiang Mai grew at an average 9.9% per year. During the period 1997-2003
(before SARS) the growth rate slowed to an average annual rate of 2.5%. However,
after 2003, improvements in tourist attractions – including the addition of a panda at the
Chiang Mai Zoo, the Night Safari, and the Royal Flora Exhibition – all helped boost
tourism. The rate dropped again in 2007 (4.2%) when foreign tourists fell 14.4% and
Thai visitors only marginally increased (1.8%). The fall in tourist arrivals was seen as
normal after the large boost created by the temporary Royal Flora Exhibition, which
had closed. Abnormally bad air pollution in Chiang Mai that year was another
contributing factor. The recent arrival of a baby panda has provided a new tourist
attraction in Chiang Mai, boosting the number of weekend Thai tourists.
Tourism development in Pattaya
For Pattaya, the tourism industry has experienced continuous and stable growth.
The industry grew at an average annual rate of 11.4% before 1997, dropping only slightly
during the following periods 1998-2001 (9.8%) and 2002-2007 (9.7%). The year 2001
was an anomaly in this growth trend, with an oil spill contributing to an actual decline
in tourist numbers (-6.4%). Pollution, particularly from wastewater and oil spills, has
been a long-term problem for Pattaya tourism, although it has improved recently with
better control and management. Tourism in Pattaya has benefited from its image as a
place of great amusement, a wide range of tourist activities, proximity to Bangkok, a
convenient and fast transportation system, and cooperation between the private and
public sectors in organizing activities/events that promote tourism, including the
Pattaya International Music Festival, the Pattaya Marathon, and the New Year
Festival. Moreover, the opening of Bangkok’s new Suvannaphumi Airport has
benefitted the tourism industry in Pattaya as getting there is now shorter and more
convenient.
Tourism development in Pai
Currently, Pai is a popular nature-based tourism destination. In the past, this small
town served mostly as a stopover for transit visitors on their way to Mae Hong Son.
Before 1998, the tourism industry in Pai grew continuously. During this period, local
residents controlled and operated tourism developments, with backpackers the
primary target. The year 1999 saw a large contraction of tourism in Pai due to the
industry’s inability to cope with the fast growing number of visitors that put great
pressure on local amenities and other related infrastructure. Following this, outside
investors started to see opportunities for tourism businesses, based on Pai’s potential
6
and diverse attractions, not just as a transit point. Financial capital started to pour in,
with a large amount invested in accommodations, restaurants, and other tourist-related
businesses. The internet has provided a powerful medium for spreading the news
about Pai, helping tourism grow rapidly.
Current tourism statistics for the four destinations is presented in Table 1
below. The number of visitors to Phuket, Chiang Mai, and Pattaya is around 5-6
million. Foreign visitors account for most visitors to Phuket and Pattaya, while Thai
visitors account for most visitors to Chiang Mai. For Pai the number of visitors is
around 0.17 million. More than 50% of this number comprises foreign visitors.
Visitors to Phuket have the longest average period of stay as well as the highest
average spending per day. In 2007, Phuket had the highest earnings from tourism
among the four destinations of approximately US$2.73 billion. Next are Pattaya and
Chiang Mai with US$1.72 and 1.13 billion, respectively. The average period of stay and
average spending per day for these two destinations are similar. Since visitors to Pai
are mainly backpackers, their average spending is US$47.60/person/day, with the
period of stay averaging 2-3 days. Therefore for Pai, total earnings from tourism in
2007 were only US$22.48 million. For accommodation, Phuket has the highest
number of accommodation establishments and the highest number of rooms as well.
Phuket’s room occupancy rate of 65.8% is the highest. Pattaya has a higher number of
rooms and higher occupancy rate than Chiang Mai but fewer accommodation
establishments. Pai has slightly over 1,000 rooms for accommodation and a relatively
low occupancy rate of only 27.5%. The average length of stay in Chiang Mai
accommodations is two nights, which is less than in Phuket and Pattaya, but similar to
Pai. This may indicate that visitors to Chiang Mai are mainly Thai who come to visit
during weekends, or are visitors who use Chiang Mai as hub of travel to visit other
provinces in the north such as Chiang Rai, Mae Hong Son, and Pai.
7
Table 1. Tourism in major destinations in 2007
Item
Phuket
Chiang
Mai
Pattaya
Pai
Number of visitors (million
persons)1
5.01 (66%)
5.36 (33%)
6.68 (67%)
0.17 (53%)
- Tourists
4.73
4.18
6.22
0.16
Average length of stay (days)
4.71
3.13
3.13
2.84
Average spending
(US$/day/person)
121.14
78.97
86.15
47.60
- Tourists
121.82
81.25
87.27
47.90
Earnings (million. US$)
2,726.84
1,125.41
1,717.23
22.48
- Tourists
2,708.18
1,062.41
1,699.76
22.33
Number of accommodation
establishments
628
418
357
141
Number of rooms
37,543
20,816
38,085
1,518
Room occupancy rate (%)
65.82
42.02
57.48
27.50
Number of tourists (million
persons)
4.01
3.07
5.83
0.15
Average length of stay (days)
3.7
1.9
2.7
2.2
Note: 1 Figures in parentheses are foreign visitors.
: Exchange rate at 34.56 baht/US$.
Source: Tourism Authority of Thailand, 2008.
RESEARCH METHODOLOGY
Conceptual framework and model
Most studies on the relationship between the perception of impact and support
for tourism development refer to the Social Exchange Theory (Yoon, Gursoy and
Chen, 2001). The theory explains that local residents are willing to exchange with
tourists if they think that the benefits that they will receive will be greater than the
costs. Most studies on local residents’ attitudes about the impact and support of
tourism development refer to the Theory of Reasoned Action (Dyer, et al., 2007).
This theory stipulates that local residents will support tourism development in their
communities if they can expect the benefits to be greater than the costs. However, these
two theories have also been used to explain the influence of the differences between
anticipated benefits and costs on local resident support/opposition of tourism
development in their communities (Ap, 1990; Lindberg and Johnson, 1997; Yoon,
Gursoy and Chen, 2001; Ko and Stewart, 2002; Akarapong, 2006; Dyer, et al., 2007). It
is often explained that the magnitude of support/opposition of local residents for
8
tourism development in their communities varies with the difference between the
anticipated benefits and costs of that development (Perdue, Long and Chen, 1990;
Lindberg and Johnson, 1997; Jurowski, Uysal and Williams, 1997; Ko and Stewart,
2002; Akarapong, 2006).
Past studies also show four groups of impacts resulting from local tourism
development: economic, social, cultural, and environmental. The economic benefits
from local tourism development are important to local people (Ritchie, 1988; Akis,
Peristianis and Warner, 1996) while social, cultural and environmental impacts are
major costs to the whole community (Kreage, 2001; Yoon, Gursoy and Chen, 2001;
Dyer, et al., 2007). Economic impacts cited by most studies in the past include
employment opportunities and income generation (Akarapong, 2006; Mingsarn,
2007). Moreover, tourism also helps to raise the standard of living of local residents
(Allen, et al., 1988; Ko and Stewart, 2002). It also increases local government revenue as
well as opportunities to develop local community infrastructure (Kreage, 2001; Dyer,
et al., 2007). These are often cited as positive impacts of local tourism development
while overlooking the negative economic impacts such as higher prices, higher costs of
living, inequality of income distribution, and higher competition for employment from
nonresidents (Akarapong, et al., 2006; Akarapong, 2006; Mingsarn, 2007).
Generally, local residents perceive more negative impacts such as rising
problems associated with congestion of the community, crime, and drugs (Akarapong,
2006; Dyer, et al., 2007; Mingsarn, 2007) while positive social and cultural impacts
such as increasing opportunities for cultural exchanges, revival and preservation of folk
arts, and better quality of life (Akarapong, 2006; Mingsarn, 2007) are often overlooked.
Moreover, local residents tend to believe that tourism has destroyed their communal
natural resources and has generated negative, rather than positive, impacts on their
environment (Jurowski, Uysal and Williams, 1997; Yoon, Gursoy and Chen, 2001;
Akarapong, 2006; Mingsarn, 2007). Negative environmental impacts from tourism,
such as pollution (waste, noise, water, and air) and destruction of natural resources,
are often mentioned (Kreage, 2001; Akarapong, 2006; Mingsarn, 2007). At the same
time, positive impacts on the environment, such as greater awareness on issues
relating to natural resources and the environment among local residents and greater
opportunities to protect their natural resources, are often not mentioned as
environmental impacts. At present, there have been attempts to find other alternatives
for local tourism development with minimal negative impacts on the environment.
Ecotourism has been proposed as one alternative as it promotes not only a learning
process for local residents but also provides participatory management and leads local
tourism development to be sustainable.
9
Finally, previous studies also show that there is a causal relationship between
local residents’ perception of these impacts and their support for tourism
development, both directly and indirectly (Yoon, Gursoy and Chen, 2001; Chen,
2001; Gursoy, Jurowski and Uysal, 2002; Ko and Stewart, 2002; Akarapong, 2006;
Dyer, et al., 2007). According to the Social Exchange Theory and the Theory of
Reasoned Action as applied to the study of the perception of potential development of
a tourist destination and its impacts, economic, social, cultural, and environmental,
these will directly influence local resident support for tourism development in their
communities. A model of hypotheses of these causal relationships can be written as
follows:
Figure 1. Model of factors influencing local resident support for tourism development
From the above model, four hypotheses can be derived:
Hypothesis 1 H1: Development of destination’s potential has direct influence
on local support for tourism development
Hypothesis 2 H2: Economic impact has direct influence on local support for
tourism development
Hypothesis 3 H3: Social and cultural impact has direct influence on local
support for tourism development
Hypothesis 4 H4: Environmental impact has direct influence on local support
for tourism development
Because different destinations are of different sizes, developmental levels, as
well as environs, the impacts from development are also different (Yoon, Gursoy and
Chen, 2001; Akarapong, 2006). Therefore, differences in the potential of individual
Potential of
destination
Economic
impact
Social and Cultural
impact
Environmental
impact
Support for tourism
development
H1
H2
H3
H4
10
destinations and differences in impacts from development should have different
magnitudes of influence on local residents’ support as well. The objective of this
study is to focus on this issue, i.e. to study whether the differences in the potential of
individual tourist destinations affect local residents’ support for tourism differently or
not. The model with the four hypotheses mentioned above is then used to test four
major tourist destinations in Thailand – Phuket, Chiang Mai, Pattaya, and Pai –
considering that the differences in development levels and place-specific characteristics
of these four destinations are very distinct.
Data used in the study
Data for the study were obtained from interviewing a sample of 1,367 local
residents in Phuket (362 persons), Chiang Mai (347 persons), Pattaya (282 persons),
and Pai (367 persons) using questionnaires. The sample covered local residents who
were employed in tourism related business as well as those who were not, with the
focus on those who were 18 years old or older and had lived in their respective
communities at least 10 years. Local residents were defined here as those who live
and support social and economic activities in tourist destinations (Jackson, 2008) and
are affected by tourism development in their communities. The interviews were
conducted in February-May 2009. The questionnaires used were designed with the
help of experts and were pretested before using.
Variables of the model
For this article, a model of causal relationships between potential, impact, and
support of local tourism development was developed to be used for hypothesis testing
of four tourist destinations that have different sizes as well as different levels of
development. The variables included in the model were chosen from questions in the
questionnaire (on the criterion that their correlation coefficients must be greater than
0.30) and primary Factor Analysis. Fifteen observable variables, 12 independent and 3
dependent, were used in the model. Five latent variables were used in the model: four
independent variables (destination’s potential, economic impact, social and cultural
impact, and environmental impact) and one dependent variable (support for local
tourism development) (See Table 2 for details).
11
Table 2. Variables and sources of variables under study
Latent Variables
Observable Variables
Questions in questionnaire
Dependent Variables
Support for local
tourism development
(SUP)
Support from local government
(Sup1)
7. Support from local government
organization
Cooperation from private sector
(Sup2)
8. Cooperation from private business
Participation of local residents
(Sup3)
9. Participation of local residents
Independent Variables
Potential of tourist
destination (POTEN)
Physical attractions (Att_P)
1. Natural, such as sea, mountain, and
waterfall
2. Temples/historical sites/pre-historic
marks
Social and cultural attractions
(Att_S_C)
3. Culture/way of living
4. Ethnic diversity
10. Local residents’ manners and their
service mindedness
Facilities and amenities (Fac)
5. service sector
6. public facilities/utilities
12. restaurants, local food, well known
recipe
Economic impact
(ECON)
Higher employment for local
residents (Econ1)
1. Higher employment for local residents
Higher income earnings for
local residents (Econ2)
4. Higher income earnings for local
residents
Greater opportunities for
investment and business
(Econ3)
2. Attract more investment into the local
community
6. Creation of new business opportunities
Social and cultural
impact (S_C)
Creation of unity and
cooperation in community
(S_C1)
2. Create pride in community among local
residents
3. Revival and conservation of
traditional culture and rites
6. Cooperation among local residents to
make their community a nicer place to
reside
Creation of social problems
(S_C2)
7. Increasing crime problems in
community
10. Bringing the use of drugs into
community
11. Prostitution
14. Attract more criminals into the
community
12
Impact on local culture,
tradition, and behavior
(S_C3)
3. Transfer of inappropriate behavior
4. Increasing use of traditional rites and
culture commercially
7. Neglect of local dialect
8. Bad use of language
9. Value and norms in living
10. Loss or distortion of traditional art
Environmental impact
(ENV)
Pollution problems (Env1)
4. Solid waste
5. Water pollution
7. Dust and air pollution
8. Crowded roads/traffic jam
Problems related to use of
public space (Env2)
10. More use of public space for
commercial purposes
13. Higher encroachment of public space
Degradation of environment
and natural resources (Env3)
14. Environmental destruction
15. Natural resources destruction
STUDY RESULTS
The analysis of the model of factors influencing local resident support for
tourism development was conducted using a Structural Equation Model (SEM).
Before analyzing with the SEM, the internal consistency is measured by Cronbash
Alpha. This value must be at least 0.70 (Nunnally and Bernstein, 1994) for the
variables used for creating the factors to have a high degree of reliability. In addition,
the item-to-total correlation should be at least 0.30 (Parasuraman et al., 1988) if
adding these variables into the factor are to increase the value of Alpha.
The Cronbash Alpha values are presented in Table 3. Nearly all of the
Cronbash Alpha values are either higher or close to 0.70, except the economic impact
variable for Phuket and Pattaya with values equal to 0.49 and 0.45, respectively. The
results thus indicate that most variables included in the equation are of a high level of
reliability, while the values of item-to-total correlation have similar results. Only the
variables representing higher employment for local residents and higher earnings for
local residents in the economic impact group of Phuket and Pattaya have item-to-total
correlation values less than 0.30. This means that adding these variables into the
factor do not increase the value of Alpha. Therefore, the variables used to evaluate the
economic impact in Phuket and Pattaya are of a lower reliability level.
13
Table 3. Results of reliability testing (Cronbach’s Alpha) of variables in the model.
Item
Symbol
Phuket
Chiang
Mai
Pattaya
Pai
C.A.
Corr.
C.A.
Corr.
C.A.
Corr.
C.A.
Corr.
A. Potential of Tourist Destination.
POTE
N
0.65
-
0.80
-
0.60
-
0.68
-
- Physical attractions.
Att_P
0.511
0.49
0.701
0.68
0.39
0.48
0.46
0.59
- Social and cultural attractions.
Att_S_
C
0.481
0.52
0.721
0.65
0.45
0.44
0.54
0.55
- Facilities and amenities.
Fac
0.651
0.38
0.751
0.20
0.63
0.31
0.72
0.38
B. Economic Impact.
ECON
0.49
-
0.68
-
0.45
-
0.71
-
- Higher employment for local residents.
Econ1
0.521
0.22
0.531
0.55
0.37
0.27
0.58
0.56
- Higher income earnings for local
residents.
Econ2
0.551
0.27
0.621
0.48
0.51
0.21
0.69
0.46
- Greater opportunities for investment and
business.
Econ3
0.121
0.53
0.601
0.53
0.22
0.40
0.58
0.56
C. Social and Cultural Impact.
S_C
0.78
-
0.87
-
0.82
-
0.73
-
- Creation of unity and cooperation in
community.
S_C1
0.611
0.69
0.781
0.79
0.71
0.71
0.62
0.57
- Creation of social problems.
S_C2
0.791
0.53
0.811
0.77
0.76
0.66
0.61
0.59
- Impact on local culture, tradition, and
behavior.
S_C3
0.691
0.63
0.861
0.71
0.77
0.65
0.69
0.51
D. Environmental Impact.
ENV
0.87
-
0.92
-
0.83
-
0.81
-
- Pollution problems.
Env1
0.801
0.76
0.901
0.80
0.84
0.61
0.77
0.62
- Problems related to use of public space.
Env2
0.821
0.73
0.871
0.85
0.71
0.74
0.71
0.68
- Degradation of environment and natural
resources.
Env3
0.811
0.75
0.871
0.84
0.73
0.73
0.72
0.67
E. Support for Local Tourism
Development.
SUP
0.73
-
0.82
-
0.80
-
0.81
-
- Support from local government.
Sup1
0.641
0.56
0.751
0.66
0.74
0.62
0.69
0.69
- Cooperation from private sector.
Sup2
0.561
0.62
0.701
0.72
0.66
0.70
0.72
0.66
- Participation of local residents.
Sup3
0.721
0.48
0.791
0.93
0.76
0.61
0.78
0.61
Note: C.A. = Cronbach’s Alpha; Corr. = Item-to-total correlation; 1 = Cronbach’s Alpha if item
deleted.
Source: Author's calculation.
In order to ensure internal consistency under appropriate conditions, the
model was then adjusted by adding into the model the relationship between
measurement errors of internal and external variables (Table 4). This should also help
make empirical data derived from local resident attitudes truly reflect the influence of
the tourist destinations’ potential on support for local tourist development.
14
Table 4. Goodness of fitted statistics of the model for the four tourist destinations.
Goodness of fitted
statistics
Conditions
Phuket
Chiang
Mai
Pattaya
Pai
1.2
Low 2 and not
Sig.
62.84 (P. =
0.14)
82.70 (P. =
0.14)
72.13 (P. =
0.18)
67.06 (P. =
0.15)
2.2 / d.f.
< 2.00
1.208
1.181
1.163
1.198
3.RMSEA
< 0.05
0.024
0.023
0.024
0.023
4.RMR
Close to 0
0.035
0.036
0.031
0.026
5.GFI
Close to 1
0.98
0.97
0.97
0.98
6.AGFI
> 0.90
0.95
0.95
0.94
0.95
Note: 2= Chi-square; RMSEA = Root mean square error of approximation; RMR = Root
mean square residual; GFI = Goodness of fit index; AGFI = Adjusted goodness of fit index.
Source: Author's calculation.
Results of hypotheses testing as presented in Table 6 show that, for all four
tourist destinations, economic impact is found to have direct influence on local
support for tourism development with a statistical significance at the 95% level of
confidence. Local residents in Phuket, Chiang Mai, and Pai also think that the
destination’s potential is another factor that directly influences local support for
tourism development with a statistical significance at the 95 % level of confidence.
Social and cultural, as well as environmental impacts are not found to have direct
influence on local resident support for tourism development with a statistical
significance at the 95% level of confidence. The results, therefore, reveal that the
economic impact and potential of destination are main factors influencing local
support for tourism development in their communities, while costs of development as
reflected through social, cultural, and environmental impacts do not have a
statistically significant influence on local support for tourism development.
The factor analysis results, as presented in Table 5, show that local residents in
Phuket and Pattaya see that social and cultural development is important to increasing the
potential of tourism development in their own communities, while those in Chiang
Mai and Pai would like to see more development of tourist amenities and physical
attractions in their own communities. On the analysis of local residents’ perception of
impacts from local tourism development, the study shows that Phuket and Pattaya residents
see the economic impact of attracting more investment and business opportunities into their
communities as important, while people in Chiang Mai and Pai see higher employment for
local residents as important. On the study of local residents’ perception of social and
cultural impacts, residents of Phuket and Chiang Mai think that local tourism development
leads to social unity and better cooperation, while their counterparts in Pattaya and Pai think
that local tourism development leads to social problems such as those relating to crime,
15
drugs, and prostitution. For environmental impacts, only local residents in Pai think that
local tourism development would bring into their communities problems relating to the use
of public space, such as encroachment of public space or increasing use of public areas for
commercial purposes. Those in the other three tourist destinations think similarly that local
tourism development would lead to higher destruction of the environment and natural
resources.
Table 5. Coefficient of factor loading of the model for the four tourist destinations
Item
Symbol
Phuket
Chiang
Mai
Pattaya
Pai
A. Potential of Tourist Destination
POTEN
- Physical attractions
Att_P
0.44
0.62
0.23
0.43
- Social and cultural attractions
Att_S_C
0.47
0.47
0.35
0.30
- Facilities and amenities
Fac
0.31
0.60
0.31
0.44
B. Economic Impact
ECON
- Higher employment for local residents
Econ1
0.32
0.69
0.41
0.58
- Higher income earnings for local
residents
Econ2
0.39
0.49
0.28
0.39
- Greater opportunities for investment and
business
Econ3
0.64
0.57
0.42
0.53
C. Social and Cultural Impact
S_C
- Creation of unity and cooperation in
community
S_C1
0.72
0.89
0.60
0.47
- Creation of social problems
S_C2
0.47
0.82
0.62
0.69
- Impact on local culture, tradition, and
behavior
S_C3
0.58
0.68
0.59
0.49
D. Environmental Impact
ENV
- Pollution problems
Env1
0.78
0.83
0.56
0.57
- Problems related to use of public space
Env2
0.70
0.94
0.60
0.76
- Degradation of environment and natural
resources
Env3
0.81
0.96
0.69
0.68
E. Support for Local Tourism
Development
SUP
- Support from local government.
Sup1
0.67
0.65
0.57
0.64
- Cooperation from private sector
Sup2
0.66
0.78
0.68
0.63
- Participation of local residents
Sup3
0.43
0.58
0.59
0.53
Source: Author's calculation.
The results of the study also reveal that local residents in all the four tourist
destinations think that support from local government and cooperation from the
private sector are important factors in local tourism development. They also see
participation of local residents as secondary in importance. Therefore, the main factor
supporting local tourism development is cooperation from the private sector in
16
developing various amenities to meet demands from tourists, such as
accommodations, restaurants, and shops. However, cooperation from the private
sector may not be sufficient without support from local government organizations.
The coefficients of the structural equation model as presented in Table 6 show that
the economic impacts are most important and they have positive influence on support for
local tourism development. This means that an incremental increase in economic impact
will have the greatest effect on generating additional local support. The magnitude of
influence varies by destination. For those that have been developed as tourist destinations
for a long time, with a good supply of amenities, and where the majority of local residents
are non-native, like Phuket and Pattaya, the magnitude of economic impact factors is higher
than those destinations where local residents constitute mainly native people, like Chiang
Mai or Pai. On the influence of a destination’s potential development on local resident
support, the study shows that potential development of traditional destinations with good
physical attractions and tourist amenities, such as Phuket and Pattaya, means less support
from local residents, -0.62 and -0.04, respectively (Table 6). For those destinations with
strong social and cultural attractions, such as Chiang Mai and Pai, the findings show
that development of destination potential results in greater support from local residents.
For the social and cultural as well as environmental impacts from local tourism
development, these impacts were seen by local residents as having only slight influence on
their support for local tourism development. An increase in these impacts leads to less
support from local residents with the exception of local residents in Phuket who see that an
increase in environmental impacts lead to more support for tourism development. For
Phuket, the important environmental impact is the encroachment/destruction of natural
resources for tourism purposes and their local residents see this as creating economic
benefits for their communities rather than as a negative impact on natural resources. This
could be due to the fact that the majority of local residents in Phuket are not native to the
locality but originally from other regions who went there to seek opportunities from tourism
and, therefore, are less interested in environmental problems than the economic benefits
received from tourism development. Pattaya has more or less the same picture as Phuket in
the sense that the majority of local residents in Pattaya are not local natives and went there
to reap economic benefits from tourism development and therefore think less about the
costs of development. Therefore, an increase in social and cultural impacts is still related to
local support for tourism development as the tourism industry in Pattaya relies significantly
on these impacts, such as prostitution and inappropriate social behavior. On the other hand,
environmental impact is seen as an important factor influencing local support for tourism
development in Pattaya. This could be due to the fact that Pattaya residents have had bad
experiences with the environmental impact on the tourism industry. An oil spill in 2001
resulted in a 6.4% drop in tourists visiting Pattaya.
17
Table 6. Coefficients of the structural equation model of the four tourist destinations
Independent Variables
Symbol
Phuket
Chiang
Mai
Pattaya
Pai
Destination potential
POTEN
-0.62
0.21
-0.04NS
0.19
Economic impact
ECON
1.29
0.56
0.81
0.45
Social and cultural
impact
S_C
-0.20NS
-0.02NS
0.35NS
-0.07NS
Environmental impact
ENV
0.08NS
-0.16NS
-0.32NS
-0.14NS
Squared Multiple
Correlations
R2
0.24
0.57
0.55
0.54
Note: NS = not statistically significant at 95 % level of confidence.
Source: Author's calculation.
CONCLUSION
The objective of this article is to study the causal relationships between
destination potential, tourism impacts, and local support for tourism development in four
important Thai tourist destinations that have different sizes, development levels, and
environments. The summary of the study as presented in Table 7 shows that local
residents view cooperation of the private sector as more important than cooperation
from local government organizations. Although economic impact is the main factor
influencing local resident support for tourism development, the magnitude of
influence varies by destination. In tourist destinations like Phuket and Pattaya, where
most local residents are originally from other localities, the level of influence of the
economic factor is greater than in those destinations where the majority of local
residents are native to the area, like Chiang Mai and Pai. Increases in investment and
business opportunities constitute important economic impacts for the tourist
destinations of Phuket and Pattaya, while an increase in local employment
opportunities is considered important for residents of Chiang Mai and Pai.
To develop traditional destinations’ potential (Phuket and Pattaya), qualitative
development (e.g., service quality, cleanliness, and the quality of the public
transportation system) are important factors, as well as developing social and cultural
attractions (e.g., social and cultural festivals). For the newer destinations (Chiang Mai
and Pai), more development is still needed in the areas of physical attractions and
integrated public amenities (e.g., mass transit system, theme parks, and public
parks/rest areas). Based on experience, development of physical attractions in both
Chiang Mai and Pai has been quite successful in attracting tourists to these two
destinations. For the costs of tourism development, whether social, cultural, or
18
environmental, these impacts have little influence on local support for tourism
development.
The study has proven clearly that differences in the levels of development,
destination size, and the environment of tourist destination influence the destination
potential and the impact of tourism development on local support for tourism
development differently. Moreover, the cost and benefits from tourism development
as well as the potential development requirements vary as well.
Table 7. Summary of study results using Structural Equation Model for the four tourist
destinations
Item
Phuket
Chiang Mai
Pattaya
Pai
Important factors of
local tourism
development
Support from
local
government and
private sector
Cooperation of
the private
sector
Cooperation of
the private
sector
Support from
local
government and
private sector
Main factors
influencing local
support for tourism
development
Economic
impact
Economic
impact
Economic
impact
Economic
impact
Potential of
destination which
should be
improved
Social and
cultural
attractions
Physical
attractions and
tourist amenities
Social and
cultural
attractions
Physical
attractions and
tourist amenities
Negative impact
on local
residents’ stress
Social and
cultural
Social and
cultural, and
environmental
Environmental
Social and
cultural, and
environmental
The results reflect different policy implications of tourism development for
different local communities. Individual communities, especially important tourist
destinations of Thailand, should be encouraged to develop their own tourism
development plans (consistent with the national tourism development plan). Since
individual tourist destinations differ from each other in terms of levels of development,
size, and the environment; they, therefore, may have different tourism development aims
and objectives. However, sustainable development can only result if those involved,
whether from the public or private sector or local residents, must join hands to participate
in and/or support such development. Planning or policy implementation must be
determined or decided jointly by involved individuals so to achieve the highest benefits
for local communities at the least cost. Only this will lead to sustainability of local
development.
19
REFERENCES
Akarapong Untong, Sasipen Phuangsaichai, Nattdhida Taweelertkunthon and Jakkree
Tejawaree. (2006). Income distribution and community based tourism: Three case
studies in Thailand. The Journal of GMS Development Studies, 3(1), 69-81.
Akarapong Untong. (2006). Attitude of local residents on tourism impacts: A case study of
Chiang Mai and Chiang Rai. Proceeding 12th Asia Pacific Tourism Association and
4th APacCHRIE Joint Conference, June 26-29 2006, Hualien, Taiwan.
Akis, S., Peristianis, N. and Warner, J. (1996). Residents’ attitudes to tourism development:
The case of Cyprus. Tourism Management, 17(7), 481-494.
Allen, L.R., Long, P.T., Perdue, R.R. and Kieselbach, S. (1988). The impacts of tourism
development on residents’ perceptions of community life. Journal of Travel
Research, 27 (1), 16-21.
Ap, J. (1990). Residents’ perceptions research on the social impacts of tourism.
Annals of Tourism Research, 17(4), 610-616.
Bastias-Perez, P. and Var, T. (1995). Perceived impacts of tourism by residents. Annals of
Tourism Research, 22(1), 208-210.
Butler, R.W. (1980). The concept of a tourism areas cycle of evaluation: Implication
for management of resources. Canadian Geographer, 24(1), 5-12.
Chen, J.S. (2001). Assessing and visualizing tourism impacts from urban residents’
perspectives. Journal of Hospitality & Tourism Research, 25(3), 235-250.
Cooke, K. (1982). Guidelines for socially appropriate tourism development in British
Columbia. Journal of Travel Research, 21(1), 22-28.
Dyer, P., Gursoy, D., Sharma, B. and Carter, J. (2007). Structural modeling of
resident perceptions of tourism and associated development on the Sunshine
Coast, Australia. Tourism Management, 28(2), 409-422.
Getz, D. (1994). Residents' attitudes toward tourism: A longitudinal study in Spey Valley,
Scotland. Tourism Management, 15(4), 247-258.
Gursoy, D., Jurowski, C. and Uysal, M. (2002). Resident attitudes: A structural modeling
approach. Annals of Tourism Research, 29(1), 79-105.
20
Jackson, L.A. (2008). Residents’ preceptions of the impacts of special event
tourism.
Journal of Place Mangement and Development, 1(3), 240-255.
Jurowski, C., Uysal, M. and Williams, D.R. (1997). A theoretical analysis of host
community resident reactions to tourism. Journal of Travel Research, 36(2),
3-11.
Ko D.-W. and Stewart W.P. (2002). A structural equation model of residents’
attitudes for tourism development. Tourism Management, 23(5), 521-530.
Kreage, G. (2001). The Impacts of Tourism. www.seagrant.umn.edu, October, 10
2008.
Lankford, S.V. and Howard, D.R. (1994). Developing a tourism impacts attitude
scale. Annals of Tourism Research, 21(1), 121-139.
Lawton, L. (2005). Resident perceptions of tourism attractions on the Gold Coast of
Australia. Journal of Travel Research, 44(2), 188-200.
Leep, A. (2007). Residents’ attitudes towards tourism in Bigodi village, Uganda. Tourism
Management, 28(3), 876-885.
Lindberg, K. and Johnson, R.L. (1997). Modeling resident’s attitude toward tourism.
Annals of Tourism Research, 24(2), 402-424.
Liu, J.C. and Var, T. (1986). Resident attitudes toward tourism impacts in Hawaii.
Annals of Tourism Research, 13(2), 193-214.
Mingsarn Kaosa-ard. (2007). Mekong Tourism: Blessings for All?, White Lotus: Bangkok.
Nunnally, J.C. and Bernstein, I.H. (1994). Psychometric theory. (3rd ed), New York:
McGraw-Hill.
Parasuraman, A., Zeithaml, V. and Berry, L. (1988). SERVQUAL: A multiple-item
scale for measuring consumer perceptions of services quality. Journal of
Retailing, 64(1), 12-40.
Perdue, R.R., Long, P.T. and Allen, L. (1990). Resident support for tourism
development. Annals of Tourism Research, 17(4), 586-599.
21
Ritchie, J.R.B. (1988). Consensus policy formulation in tourism: Measuring resident
views via survey research. Tourism Management, 9(3), 199-212.
Yoon, Y., Gursoy, D. and Chen, J.S. (2001). Validating a tourism development theory
with structural equation modeling. Tourism Management, 22(4), 363-373.
ACKNOWLEDGEMENT
This article is a part of “Integrated Development of Sustainable Tourism in the
Mekong Region Phase IV” which supported by the Office of National Research
Council of Thailand.
