v
4.1.3. Challenges 44
4.2. Recommendations 45
4.2.1. The choice of mutual development 45
4.2.2. Investment in infrastructure 46
4.2.3. Consideration of the proposed An Giang airport 46
4.2.4. Investment in education 47
4.2.5. Creation of tourism business associations 47
4.2.6. Creation of heritage tours 48
4.2.7. Less investment on spiritual tourism projects 48
4.2.8. Promotional campaigns 48
4.3. Conclusions 50
REFERENCES 51
APPENDICES 56
vi
ABBREVIATIONS
2009 Census 2009 Population and Housing Census
AGPC People Committee of An Giang province
AGU An Giang University
An Giang An Giang province
ATIPC An Giang Trade and Investment Promotion Center
FDI Foreign Direct Investment
GSO General Statistics Office
HCMC Ho Chi Minh City
ICAO International Civil Aviation Organization
MDTA Mekong Delta Tourism Association
PCI Provincial Competitiveness Index
SME Small and medium size enterprise
vii
LIST OF TABLES
Table 1.1: South Carolina industries’ dependence on tourism 6
Table 3.1: Tourism destinations in An Giang (listed by district) 16
Table 3.2: Airports in the Mekong Delta 30
Table 3.3: Structure of An Giang’s enterprises (2004 – 2009) 33
Table 3.4: Structure of An Giang’s enterprises (divided by size of capital and number of employees)
(2004 – 2009) 34
viii
LIST OF CHARTS
Chart 3.1: An Giang’s demographic structure in 2010 12
Chart 3.2: Total retail sales of goods and services – current prices (1995 – 2010) 12
Chart 3.3: Composition of An Giang’s economy from 2000 to 2010 13
Chart 3.4: Number of tourists served by the hotels in An Giang (2001 – 2010) 18
Chart 3.5: Structure of domestic tourism in 2009 18
Chart 3.6: Average expenditures per day of domestic tourists in 2009 19
Chart 3.7: Tourists’ average daily expenditures in An Giang from 2000 to 2010 19
Chart 3.8: Number of tourists served by the accommodation units and length of stay 20
Chart 3.9: Revenue from tourism activities (2009 – 2011) 20
Chart 3.10: Revenue per tourist in 2011 21
Chart 3.11: GDP per capita (constant prices) of An Giang, Can Tho, Kien Giang, Tien Giang and Tay
Ninh from 2000 - 2010 24
Chart 3.12: Volume of passengers in An Giang, Can Tho and Tay Ninh (2001 – 2010) 25
Chart 3.13: Percentage of drop – out students from 5 to 18 years old in 2009 26
Chart 3.14: Proportion of development investment expenditure of An Giang from 2000 – 2010 28
Chart 3.15: PCI of An Giang province in 2010 and 2011 33
Chart 3.16: Revenue of the enterprises in tourism sector in An Giang (2001 – 2010) 37
Chart 3.17: Increase of foreign tourists from 1996 – 2011 39
ix
LIST OF FIGURES
Figure 1.1: Determinants of regional competitiveness 3
Figure 1.2: Diamond model of competitiveness 4
Figure 1.3: Cluster development ladder 6
Figure 3.2: Map of the transport network from An Giang to larger Mekong Delta 13
Figure 3.3: An Giang tourism’s cluster map 15
Figure 3.4: Determinants of regional competitiveness in tourism in An Giang 22
Figure 3.5: Distances from An Giang and Tay Ninh to HCMC and Phnom Penh 22
Figure 3.6: Percentage of high school graduates 26
Figure 3.7: Locations of An Giang, Can Tho, Ca Mau, Rach Gia and Phu Quoc airports 29
Figure 3.8:Location of industrial zones and tourist sites in An Giang province 32
Figure 3.9: Diamond model of competitiveness in An Giang 36
Figure 4.1: Promotional campaigns targeting at tourists 49
1
1. INTRODUCTION
1.1. Background of the problem
1.1.1. Clusters & the competitiveness of clusters
Clusters as a new economic concept
“Cluster” is an emerging term in today’s economics. Michael E. Porter (1998) claims that
clusters have a prominent role in maintaining the competitiveness of nations. He defines a
cluster as a “geographic concentration of interconnected companies and institutions in a
particular field,” which includes suppliers of specific inputs, providers of specialized
infrastructure, manufacturers of complementary products and companies in related industries
(Porter 1998, 199). He also states that when the companies and institutions get together in
clusters, their whole value is greater than the sum of each separate part, and “clusters, broader
than industries, capture important linkages, complementarities, and spillovers of technology,
skills, information, marketing, and customer needs that cut across firms and industries”
(Porter 1998, 205).
Clusters promote both competition and cooperation (Porter 1998). Clusters will affect
productivity growth, with “productivity” defined as “the value created per day of work and
unit of capital or physical resources employed” (Porter 1998, 209). Porter states that clusters
are of foremost importance since they provide better access to employees, suppliers,
specialized information, complementarities, institutions and public goods. Clusters also
encourage improved measurement and motivation. Besides, clusters also help drive the
direction and pace of innovation as well as stimulate the formation of new businesses (Porter
1998). Ferreira and Estevão (2009) believe that clusters generate static externalities (cheaper
access to product factors) and dynamic externalities (enhanced learning and motivation).
The tourism cluster
Tourism has recently been considered an “economic growth engine with particular focus at
the regional level” (Ferreira and Estevão 2009, 1). Botti et al. (2008) prove that the industry is
a prodigious source of value creation and employment, especially in places with no other
alternative economic advantages.
2
Ferreira and Estevão (2009, 5) define the tourism cluster as a “geographic concentration of
companies and institutions interconnected in tourism activities”. Generally, tourism clusters
are associated with tourism products and destinations.
Tourism achieves positive economic outcomes through clustering (Roberts 2000). The
industry is extremely suitable to the application of the cluster concept because the satisfaction
of the customers (tourists) comes from both the attraction of the destination and the quality of
related businesses such as hotels, restaurants, shopping centers and transportation (Ferreira
and Estevão 2009). Nordin (2003) observes that the experience of tourists is based on the
overall impression of the destination visited, and every single factor needs systematic
development.
In general, destinations like clusters are formed naturally. However, to achieve their full
potential, they need support (Nordin 2003). Braun (2005) says that tourism clusters’ growth
needs a critical mass of firms and also the important elements of strategic infrastructure such
as hard, financial and human resource infrastructure.
The competitiveness of tourism clusters
Dominguez (2001, as cited in Ferreira and Estevão 2009, 9) states that the competitiveness of
a tourism cluster depends on the tourism businesses’ capacity to attract visitors who “offset
the costs of business development, and reward the capital invested, in an equal or above
manner of the opportunity cost.” Some elements of tourism cluster competitiveness are
invisible and immeasurable (Dwyer and Kim 2003). Objectively measured elements of the
competitiveness of a tourism destination (tourism cluster) are visitor numbers, market share,
tourist expenditure, employment and value added by the tourism industry, and the
subjectively measured ones are “richness of culture and heritage” and “quality of tourism
experience” (Dwyer and Kim 2003, 375). There are models that can be applied to measure
the competitiveness of a destination and a specific cluster.
Determinants of regional competitiveness
Adjusting Porter’s framework to a regional scale to analyze national competitiveness, Vu
Thanh Tu Anh et al. (2011) mention three factors that affect the productivity of a region,
namely: (i) regional natural endowments; (ii) competitiveness at the regional level; and, (iii)
competitiveness at the firm level.
3
Source: Porter, E. (1990), adjusted by Vu Thanh Tu Anh et al. (2011)
Natural endowments refer to the factors naturally owned by the regions such as natural
resources, geographic position and scale of the local economy. It is not always true that
favorable natural endowments will lead to a high degree of competitiveness of a region and
vice versa (Vu Thanh Tu Anh et al. 2011). Facing pressure from unfavorable conditions, such
as lacking natural resources or having an adverse climate, necessary strategies and innovation
will be generated, thus enhancing competitiveness. For example, Japan and Korea have
proved that countries can create and maintain high competitiveness without the support of
natural resources, while many countries blessed by nature such as Nigeria and many other
African countries seem to suffer from the “curse of natural resources” (Sach and Warener
1995).
Competitiveness at the regional level includes the infrastructure of culture, society, health and
education, which is usually called “soft infrastructure,” together with fiscal and credit policies
and the economic structure of the region. The last determinant of regional competitiveness
refers to competitiveness at the firm level. This determinant includes the business
environment and infrastructure, the capacity of the clusters and the strategies and business
practices in the region.
Business
environment &
infrastructure
Cultural, social,
medical & education
infrastructure
Fiscal, credit
policies &
Economic structure
Business’s practice
& strategies
Cluster
development
Geographic
position
Scale of regional
economy
Natural resources
Competitiveness at the firm level
Competitiveness at the regional level
Given local natural endowments
Figure 1.1: Determinants of regional competitiveness
4
A local context that encourages
investment and sustained upgrading,
e.g. intellectual property protection
Open vigorous competition among
local based rival
A core of sophisticated and
demanding local customer(s)
Unusual local demand in
specialized segments that can
be served nationally or
globally
Customer needs that
anticipate those elsewhere
High quality, specialized inputs
available to firms:
• Human resource
• Capital resources
• Physical infrastructure
• Information infrastructure
• Scientific & technological
infrastructure
• Natural resources
Film Strategy
Structure &
Rivalry
Related &
Supporting
Industries
Factor
conditions
Demand
conditions
Government
Availability of capable,
locally based suppliers and
firms in related industry
Presence of clusters instead
of isolated industry
Diamond model of competitiveness
Porter (1990) believes that the success of every company that competes in the market comes
from the economic environment, institutions and government’s policies. He also emphasizes
that the main indicator of competitiveness is productivity. He proposes a framework of
competitive performance, depicted as a “diamond model”, consisting of (i) factor conditions;
(ii) firm strategy, structure and rivalry; (iii) demand conditions; and (iv) related and
supporting industries. Porter later adds (v) government and (vi) change/chance as “events out
of control of the company”.
Source: Porter, E. (1990)
Figure 1.2: Diamond model of competitiveness
5
The first facet of the model is about factor conditions, which Porter and many other authors
place much emphasis on. Factor conditions are also called “input conditions” – or raw
materials. In tourism, factor conditions play such an important role that Nordin (2003) even
claims that without these conditions, there would be no tourism activity. Factor conditions are
usually classified as “basic production factors” such as land, labor, capital, natural and
cultural resources and “specialized factors” (Nordin 2003, 21). Among these, specialized
factors – things that are not inherited but created – are vital to competitiveness. The
specialized factors of the tourism industry include human resources trained in tourism,
infrastructure to access natural resources, capital markets to finance long-term tourism
projects and wide coverage of public services (Inman 2002 – as cited in Nordin 2003).
Demand conditions refer to the needs and wants of consumers. Local demand is very
important since the proximity of companies to their customers increases their responsiveness
and shortens communication channels (Nordin, 2003). Nordin (2003) also states that both
domestic and foreign visitors contribute to local demand of tourism. Porter (1998) believes
that the sophistication of consumers is crucial. Smeral (1998) says that sophisticated tourists’
needs require recognizing new trends and new production possibilities early on. Therefore,
anticipating consumers’ wants are vital to developing tourism activities.
Porter (1990) insists that in an intensively competitive environment among local companies,
the pressure to innovate and constantly improve is created. Therefore, long-term competition
should be considered as a driver of innovation. In the tourism industry, destinations compete
in terms of services, prestige and market share (Nordin, 2003), and it is not surprising that the
high degree of rivalry may lead to improved standards and new products.
Nordin (2003) concludes that the competitiveness of a destination is defined by “the degree of
specialization, by its diversity, the quality of suppliers and operating network” (Nordin 2003,
23). The term “related and supporting industry” is related to the development of all factors in
a cluster. There is no general agreement about the dependence of each single related industry
depends on tourism, but Flowers and Easterling (2005) propose a grid, ranking industries by
their dependence on tourism for the tourism cluster in South Carolina. The grid can be more
or less applied to other tourism clusters.
Không có nhận xét nào:
Đăng nhận xét