Regional Development and National Parks in South Africa: Lessons ...

Tourism Economics, 2010, 16 (4), 1037–1064 doi: 10.5367/te.2010.0007

Regional development and national parks in South Africa: lessons learned M. SAAYMAN AND A. SAAYMAN

Institute for Tourism, Wildlife Economics and Leisure Studies and School of Economics, North-West University, Private Bag X6001, Potchefstroom 2520, South Africa. E-mail: [email protected]. National parks are playing an important role in the South African tourism landscape – especially in their respective regional economies – since most foreign and many domestic tourists visit one or more of the 21 national parks annually. For the purpose of this article, socio-economic impact analyses were conducted at four national parks using similar methodology. These parks differ considerably and the results confirm that a variety of variables play a role in contributing to the magnitude of the socio-economic impact. From these case studies, a number of interesting lessons have been learned, which have implications for managing national parks. In terms of regional development, it is also shown that different parks play different roles in their regional economies. Keywords: socio-economic impacts; national parks; regional development; South Africa

‘Socio-economics’, according to Page (2007), can be defined as the study of the relationship between economic activity and social life. The goal of a socioeconomic study is generally to assess socio-economic development, usually in terms of improvements in metrics such as gross domestic product (GDP), life expectancy, literacy and levels of employment, with the aim of enhancing the benefits received by communities. A socio-economic impact study at a national park therefore goes beyond assessing the income generated by the park and also involves the contribution of the park to the quality of life of the community (Saayman and Saayman, 2006, p 3). Page (2007, p 394) has identified four economic benefits of tourism, which include the generation of income for the local community; creation of new employment opportunities; improvements to

This paper is based on work supported financially by the National Research Foundation (South Africa). Yet any opinions, findings and conclusions expressed in this paper are those of the authors and therefore the NRF does not accept any liability in regard thereto. The authors would also like to express their gratitude for the support received from SANParks, and especially Mr Glenn Phillips and the four park managers.

1038

TOURISM ECONOMICS

the structure and balance of economic activities within the locality; and the encouragement of entrepreneurial activity. The attitudes of residents towards tourism represent an important way in which participants contribute to policy and public support for, or dissent towards, tourism. What Page (2007) has proposed above supports at least one of the three fundamental objectives of national parks in South Africa, which are: firstly, to conserve the biodiversity of the country; secondly, to maintain a relationship of community upliftment and capacity building (entrepreneurial, improving quality of life, etc) among people living in the areas in and around the parks; and lastly, to provide a recreational outlet for people to experience and enjoy the wonders of the parks (Saayman and Saayman, 2006, p 1). In essence, it has to do with managing the natural, the social and the economic environment in the region where a particular park is situated. While the main emphasis of national parks traditionally has been on conservation, there has been a significant shift towards the economic sustainability and the upliftment of local communities (Myburgh and Saayman, 2002, p 259). It is the latter that has provided the rationale for determining the socioeconomic impact of selected national parks in South Africa. Added to this is the fact that South Africa has some of the greatest protected areas in the world, yet little is known about the socio-economic impact of these parks and, according to Eagles and McCool (2002, p 190), the link between communities and protected areas occurs at different temporal and social organizational scales and within differing functional areas. These areas include visitor expenditure, the protected area and its landscape that serve as a scenic backdrop (backdrops serve as a component of the local area’s quality of life) to adjacent communities, park expenditures and, lastly, employees’ spending on goods and services in the community (Crookes and Milner-Gulland, 2006, p 160). Based on the above, one could state that national parks can be seen as development tools with a greater aim than just conserving biodiversity. In this regard, Eadington and Redman (quoted by Walpole and Goodwin, 2000, p 559) state that tourism, as a development tool, holds many potential economic benefits for host communities. These include increased employment opportunities, improved socio-economic conditions and greater market stability than is provided by traditional commodity exports. In the South African context, parks are seen as development tools and, for this reason, it has become important to measure or evaluate this by means of a socio-economic impact analysis. To achieve this, the article is structured as follows: a literature review follows the introduction, which is followed by the method of research, the results, some regional implications and a conclusion.

Literature review Even though many socio-economic impact studies have been conducted internationally, especially in the field of event tourism and tourism from an economic point of view, few studies have been conducted in the area of national parks. Those that have been identified in the literature review include research by Loader (1994, p 43) and Pelser (2003, p 164), who argue that social involvement is an integral part of conservation in South Africa. Macleod (2001, p 221) and

Regional development and national parks in South Africa

Tourists

National park/ attraction

Businesses

Community

1039

Figure 1. Conceptual framework for the interaction between communities, national parks, businesses and tourists. Fauzi and Buchary (2002, p 167) suggest that the alleviation of poverty and marginality in the case of residents of the Kepulauan Seribu Marine Park in Indonesia and in Del Este in the Dominican Republic should be prioritized, and that park management should be based on consensus building and the participation of all stakeholders. These studies support the notion that still more has to be done in the context of socio-economic impacts and national parks. A conceptual framework of the interaction between national parks, tourists, the community and local businesses is indicated in Figure 1. Socio-economic studies are concerned mainly about the interaction between tourists and the national park and businesses (the economic side) and the interaction between the community, tourists and the national park (the social side). However, to create a framework that would contextualize a socio-economic impact study, Saarinen (2003) states that tourism is a highly polarized activity, the regional impacts of which are not evaluated easily without an understanding of the context and spatial scales. The latter implies, firstly, that tourism impacts are not distributed evenly, due to a variety of reasons including: seasonality, income generated, employment, growing competition and change in general. Both Saarinen (2003) and Saayman et al (2009) support the notion that a wide variety of aspects determine the magnitude of a socio-economic analysis. These researchers also state that it is easier to quantify economic benefits than social benefits. In support of this, Wilson (1984) indicated that economic analyses were influenced by four factors: length of stay, number of tourists, amount spent and the multiplier effect. However, from a developmental point of view, both economic and social impacts are regarded as important. In support of this notion, Streuders (2008) indicated that without community support, tourism could not be managed sustainably. Government policies such as the White

1040

TOURISM ECONOMICS

Paper on Tourism (1996) and Accredited Strategic Growth Initiative in South Africa (ASGISA, 2005) place emphasis on regional development and the important role that tourism plays in developing regions. Saarinen (2003) echoes this by stating that tourism should be integrated more closely with regional development to reduce uneven social development. According to Roehl (1998), tourism is commonly looked on as having a favourable economic and developmental impact at a regional level. However, Saayman and Saayman (2004b) have expressed a concern about leakages, since most national parks are situated in rural areas, which reduces the benefit to the local community. The regional economics of tourism consist of direct, indirect and induced effects brought to bear on income, employment, earnings and taxation. The process starts with tourists and visitors spending money whilst visiting a park or attraction. This generates direct income and employment effects, which in turn benefit the businesses that render a particular service or sell various products. This gives rise to indirect income and employment effects in other sectors of the economy. This cycle can continue for a few rounds, depending on the amount that ‘leaks’ from the cycle by means of imported goods and services. From a social impact point of view, higher spending and demand will lead to an increase in business activities. This, in turn, creates more employment and income for members in the community. Greater demand leads to more services and products to be supplied, which in turn leads to improved infrastructure including water, electricity, roads, shops and transport. Most parks in South Africa also introduce social upliftment and intervention programmes such as environmental education and training programmes for women, as well as various skill development programmes. These are done by the People in Conservation division of SANParks. Therefore, social upliftment is not just about job creation but also involves programmes that contribute to the improvement of quality of life. Based on the above, socio-economic studies at four selected national parks in South Africa were conducted: Addo Elephant (Saayman and Saayman, 2004), Karoo (Saayman et al, 2007), Wilderness (Saayman and Saayman, 2008a) and Tsitsikamma National Parks (Saayman and Saayman, 2008b). The results differed from park to park, which implied that various lessons were learned from these experiences. This leads to the purpose of this article, which is to compare the results of the four socio-economic studies conducted in national parks in South Africa and to place these results in a regional context. Therefore, it is imperative to start by giving a brief description of each of the four national parks investigated in this research and their regional settings.

Study areas The four national parks that form part of the research are the Karoo National Park, the Wilderness National Park – both situated in the Western Cape Province of South Africa – and the Addo Elephant National Park and Tsitsikamma National Park – both situated in the Eastern Cape Province of South Africa (see Figure 2). The descriptions that follow are based on information from SANParks and the Regional Economic Focus database (from Global Insight Southern Africa).


1041

Zimbabwe Mozambique

Botswana

Namibia

Karoo National Park

Tsitskamma National Park

Addo Elephant National Park

Wilderness National Park

Km

Figure 2. The national parks in South Africa.

Karoo National Park Karoo National Park was founded in 1979 to protect a sample of Karoo Biome, both the plain and the mountains. The park is currently 96,000 ha. It has a strategic location near the town of Beaufort West and is adjacent to the N1, about 460 km from Cape Town. In terms of tourism, the park has one rest camp of 38 units (138 beds) plus a 24-site camping area. There is a limited road network (116 km) to facilitate self-drive game and scenery viewing. Activities offered by the park include several short nature trails, swimming pools, an interpretive centre, fossil trail and a day-visitor area. Additional tourism products include 4×4 trail opportunities (either with own or with park vehicles). The town of Beaufort West is on the upper boundary of the Western Cape Province of South Africa. Since the Karoo is a very dry region, towns are located far from one another in this region, with the closest similar-sized towns being Laingsburg and Oudtshoorn (200 km away) and Colesberg (more than 300 km away). The town of Beaufort West has a population of between 42,000 and 43,000. Approximately 32% of the population have no formal schooling and only 13% have any after-school qualifications. The town also has one of the highest unemployment rates in the Western Cape at 38%. It is therefore not surprising that human development – based on the human development index (HDI) – is low (0.6). With a real GDP per capita of R14,000 per year (roughly £1,000) in constant 2000 prices, it is a very small contributor (0.1%) to the South African economy on all fronts.

1042

TOURISM ECONOMICS

Addo Elephant National Park (AENP) Addo Elephant National Park (AENP) consists of four rest camps that offer 296 beds and is situated close to the small town of Addo, approximately 75 km from the large metropolitan area of Port Elizabeth in the Eastern Cape. It is South Africa’s third largest national park and the only ‘Big 7’ (elephant, rhino, lion, buffalo, leopard, whale and shark) reserve in the world. Since 2000, the AENP has expanded greatly. The park is expected to grow to 356,000 ha, of which 236,000 ha will be a terrestrial area and 120,000 ha will be a Marine Protection Area (Anon, 2005, p 4). The park also includes Bird Island and St Croix Island. As such, the park offers a variety of activities and boasts a welldeveloped tourism infrastructure. The park falls between the Makana and Sunday’s River municipalities in the Eastern Cape, and approximately 112,000 people reside in these municipal districts. The university town of Grahamstown falls within the Makana district, leading to an increase in the percentage of people with after-school qualifications (18%) and a real GDP per capita of R21,000 (£1,500) per year. This can be compared to the 7% of people with post-school qualifications in the Sunday’s River district and an average real GDP per capita of R12,000 (less than £1,000). In this area, 56% of all people have no formal school education. It is therefore not surprising that the area’s level of human development (based on the HDI) is 0.53, while Makana’s is 0.62 – still below the South African average of 0.67. Both areas have unemployment rates above 40% and together they contribute roughly 0.3% to the GDP of South Africa.

Tsitsikamma National Park The Tsitsikamma National Park stretches for 80 km from the Krom River Forest Station to the Salt River and it lies between the Tsitsikamma Mountains and the coast in the Eastern and Western Cape Provinces of South Africa. It is well known for indigenous forests, its dramatic coastline and the Otter Hiking Trail. When the park was proclaimed in September 1964, it became the first marine national park to be proclaimed in Africa. The park protects a variety of intertidal and marine life and is one of the largest marine protected areas (MPA) in the world, conserving 11% of South Africa’s Temperate South Coast rocky shoreline. The park can accommodate 438 overnight visitors, with Storms River camp offering 251 beds and 90 camping sites, as well as a small conference venue. Recreational activities include boat rides, snorkelling, dolphin and whale watching, hiking, abseiling and mountain biking. The park borders two small towns: Storms River and Nature’s Valley. Both towns are extremely small – Nature’s Valley, for example, only has a general dealer and a small restaurant. Both fall within the same municipal district, Bitou, together with the well-known holiday town of Plettenberg Bay. The municipal area is home to roughly 39,000 people, of which almost 20% have after-school qualifications and 12% have no formal schooling. The area has an unemployment rate of 11%, well below the South African average unemployment rate, and real GDP per capita is approximately R19,000, while human development according to the HDI is estimated at 0.67. The area is a popular holiday destination and contributes a mere 0.1% to the South African GDP.


1043

Wilderness National Park Wilderness National Park is situated in the Wilderness area along the Garden Route, found in the Southern Cape of South Africa. The 2,500 ha park stretches from the Touw River mouth to the Swartvlei estuary and beyond, where it links with the Goukamma Nature Reserve. The series of lakes connected by the Touw River (Eilandvlei, Langvlei and Rondevlei) host a variety of aquatic species and is an internationally proclaimed Ramsar site. Furthermore, Wilderness National Park is one of the most integrated urban parks in South Africa and probably one of the most integrated urban parks in the world as its borders are intertwined with residential and farm lands to the extent that it becomes difficult to know when one is in the park and when not. Recreation activities include hiking, mountain biking, bird watching, dolphin and whale watching, paragliding and horse riding. The park offers 139 beds. The park forms part of the town of Wilderness, which is a small holiday town on the coast of South Africa. Other nearby coastal resorts includes Victoria Bay, Herold’s Bay and Groot Brak, and the town is a mere 13 km from the large town of George. All of these form the municipal area of George. Approximately 155,000 people reside in this area, of which 85% have a secondary school education or post-school education. Unemployment is approximately 20% and the real GDP per capita around R23,000 (almost £2,000). In the study area, the town has the highest level of human development – 0.68 according to the HDI – and it contributes a small 0.4% to the South African economy.

Method of research From the above, it can be seen that most of the national parks of South Africa are situated in rural areas with relatively low economic activity and low levels of schooled labour. The research therefore aimed to assess both the economic and social value of each park to the communities that were in the immediate vicinity of the parks. In order to achieve this, three surveys were conducted: a visitor survey, a business survey and a community survey.1

The surveys The visitor questionnaire intends to determine the magnitude of visitor spending while at the national park. To obtain accurate spending attributes, visitors not only indicate their total spending, but a breakdown of spending as well. The questionnaire also includes questions on the size of the travel party, the number of people the respondent is paying for while at the national park, and the nights spent at the park, to enable determination of spending per visitor per day. Note that no day visitor spending is included. For the purpose of analysis, the questionnaires of people holidaying in chalets are distinguished from those that camp. Since the national parks are situated in rural areas, very little information is available on businesses and their linkages and leakages. Therefore, a business survey was conducted with the aim of determining the various linkages between the different businesses in the vicinity of the park, as well as the extent of job

1044

TOURISM ECONOMICS

creation for locals. The questionnaire also aims to determine the dependence of the businesses on the national park. All businesses that were clearly marked as a business were included in the survey. The community questionnaire is based on the social impact-measuring instrument developed by Fredline (2000) and Fredline et al (2003, p 29). Its design is based on previous events and the tourism literature, as well as from the social capital literature. Slightly different versions of this questionnaire had already been tested by these authors at the Australian Formula One Grand Prix (2002), the 2002 Melbourne Moomba Festival and the Horsham Art Festival in 2002. In South Africa, the questionnaire was also used at the Klein Karoo National Arts Festival (2006). The questionnaire was adapted slightly to focus on the needs of national parks. The residents’ perceptions of the impacts of the national park were measured using a Likert scale. Respondents were asked to indicate their degree of agreement or disagreement on 35 statements, referring to the positive and negative social impacts of the park. These statements included participation, community attachment and demographics (Fredline et al, 2003, p 29).

The timeframe and samples The research was conducted first at the Addo Elephant National Park during December 2004. Part of the business survey was formed of 114 tourism-related businesses, and 82 visitor groups to the park were surveyed during the month. No community survey was undertaken. This was identified as a shortcoming of the research and served as inspiration to include community surveys in subsequent research. During March 2007, the surveys were conducted at the Karoo National Park and 101 overnight visitor groups and 85 businesses in Beaufort West were surveyed. Additionally, 240 households in Beaufort West were also surveyed and care was taken to include households from all the cultural groups living in the area. The surveys for Tsitsikamma and Wilderness National Parks both took place during March 2008. At Wilderness National Park, 101 community surveys, 85 visitor group surveys and 22 business surveys were received. The businesses surveyed were only those in Wilderness, and did not include any businesses in the neighbouring town of George, or the coastal towns of Herolds Bay and Victoria Bay. At Tsitiskamma National Park, 132 community surveys were received and 156 visitor group surveys and 11 business surveys. As mentioned previously, there are very few businesses in the towns of Storms River and Nature’s Valley. A statistical analysis of the visitor, community and business survey results can be found in Appendices A–C.

Method Walpole and Goodwin (2000) conclude that large-scale techniques are often inappropriate to determine the local economic impacts of national parks and protected areas where significant data are often unavailable. They proposed the use of direct estimation from primary sources, obtained through surveys of


1045

businesses (supply-side) and tourists (demand-side) to determine the magnitude and distribution of revenue and employment generated by tourism activity. This is also the approach proposed by Vaughan et al (2000). To determine the economic impact, the method followed is similar to that proposed by Vaughan et al (2000). Since the areas are rural and small, it entails determining a proportional multiplier. Although the analysis is based on input– output modelling, it contains normally only a reduced set or partial input– output analysis. For rural areas, this is especially relevant, since no complete firm-level data are readily available and the modelling process is based on information received from business surveys. The proportional multipliers derived are based on a number of assumptions, which can be summarized as follows (see Vaughan et al, 2000, pp 97–98): • Average values are used, since it is extremely difficult to measure coefficients at the margin. • The analysis gives an instantaneous multiplying effect, while the actual effect of the spending is more long term. • The models are static. • The cost of data collection places constraints on the extent of the model and its nature – that is, static. Given the expenditure information obtained from the visitor surveys (direct impact), and the purchasing decisions of firms obtained from the business survey, two methods can be employed to estimate the indirect and induced impacts of this spending. Firstly, a process of iteration can be used, where the expenditure is tracked as it finds its way through the local economy. Secondly, matrix inversion can be used, which is based on the Leontief procedure used in normal input–output models, and the models are then used to derive multipliers (Vaughan et al, 2000, p 97). Since the first procedure was very time-consuming when using large data sets, a proportional input–output model was built for both Addo Elephant National Park and Karoo National Park. The models are much smaller than normal input–output models and consist of an 8×8 and 9×9 matrix, respectively. The businesses around Wilderness and Tsitsikamma National Parks were so few, however, that a process of iteration was used in preference. The partial input–output model for Addo Elephant National Park is an 8×8 transaction matrix (transposed into a technical coefficient matrix, or A-matrix), with the eight sectors included in the model: (i) accommodation; (ii) curios; (iii) restaurants; (iv) tourism services; (v) retail; (vi) transport; (vii) wholesale; and (viii) manufacturing. For Karoo National Park it is a 9×9 matrix, with the following nine sectors included in the model: (i) accommodation; (ii) restaurants and food; (iii) curios; (iv) tourism services; (v) municipal services; (vi) transport; (vii) retail; (viii) wholesale; and (ix) manufacturing. The proportional output multipliers are calculated by determining the additional output that one additional visitor to the national park in question creates for the sectors in the partial input–output model – with the value of the proportional multiplier equalling the change in output divided by the change in expenditure. To obtain a clearer picture of the economy of the area, the remuneration for labour, profits, indirect taxes and each sector’s intermediate imports was also

1046

TOURISM ECONOMICS

included in the model. This gave an indication of the income distribution within the local economy, as well as the leakages (imports and taxes) to neighbouring regions. Again, the effect of one additional visitor on additional income generated in the area is measured, and the proportional income multiplier indicates the change in income in the sectors in the model due to the change in expenditure. Both the technical conditions pertaining to input–output analysis were satisfied by the models. The first is the non-singular condition, which must be valid before the inverse of a matrix can be determined; and the second is the ‘Hawkins–Simon Stability Condition’, which tests the economic validity of the technical coefficients. Note that Wang (1997) proposes the inclusion of expenditure by the park to get a true reflection of the financial contribution made to the economy of an area. Therefore, the park expenditure is also included, as well as the indirect and induced effect of park expenditure. The social impact analysis entails an analysis of the role that the park plays and the impact that the park has on the community, based on the questions in the community survey.

Results The results are discussed in terms of both the economic and the social impact of the relevant park. A brief synopsis of the results of the various national parks is presented in each section.

Economic impact Based on the visitor surveys as well as the park expenditure information provided by SANParks, the total direct impact of the park can be estimated. Since the magnitude of direct impact depends not only on spending per visitor group but also on the number of visitors, Table 1 gives an exposition of the visitors that every park attracts. It can be seen clearly that Tsitsikamma attracts the most visitors, while Karoo National Park attracts the least. Addo Elephant National Park has grown into second place, in terms of overnight visitors, while Wilderness has actually declined in terms of visitor numbers.

Table 1. Overnight visitor numbers for the various parks (March 2003–March 2008). Year

Addo Camp Chalet

Karoo Camp Chalet

Wilderness Camp Chalet

Tsitsikamma Camp Chalet

2003 2004 2005 2006 2007 2008

12,179 13,293 18,033 22,059 22,870 23,025

10,434 9,674 12,742 10,716 13,449 11,491

19,226 15,560 17,060 19,076 20,274 17,508

43,562 42,001 50,876 38,890 49,354 60,236

Source: SANParks.

14,247 18,728 19,331 21,339 22,879 23,521

8,127 9,528 8,913 9,161 9,373 9,165

12,311 11,298 9,084 8,591 8,494 7,570

24,580 23,972 22,655 23,038 24,568 24,655


1047

Table 2. Total direct impact of the various parks (in constant 2000 rand). Expenditure item Chalet visitor expenditure Campers expenditure Total visitor expenditure Park expenditure Total direct impact

Addo

Karoo

Wilderness

Tsitsikamma

26,977,533 4,858,474 31,836,006 18,800,512 50,636,519

3,855,565 815,589 4,671,153 2,907,902 7,579,055

3,717,972 1,527,041 5,245,013 8,008,566 13,253,579

13,900,001 5,831,335 19,731,336 9,723,070 29,454,406

Source: Calculated from information obtained from SANParks and the visitor surveys.

Table 3. Proportional output and income multipliers of the various parks.

Output multiplier – camp Output multiplier – chalet Output multiplier – management Income multiplier – camp Income multiplier – chalet Income multiplier – management

Addo

Karoo

Wilderness

Tsitsikamma

1.200 1.180 1.110 0.300 0.404 0.430

1.43 1.47 1.26 0.40 0.39 0.88

1.143 1.139 1.085 0.300 0.310 0.260

1.110 1.105 1.100 0.320 0.300 0.270

For the various parks that formed part of this study, total expenditure by campers, chalet holidaymakers and the park management, which together constitute the total direct impact, is listed in Table 2. It is evident that the smaller parks in terms of visitor numbers also have the smallest direct impact, which can be expected. In terms of visitor expenditure, Karoo and Wilderness National Parks are very comparable, while spending at Addo Elephant National Park far exceeds those of the other parks. Based on the partial input–output models compiled for Addo and Karoo National Parks from the business surveys, as well as the iteration process for Wilderness and Tsitsikamma National Parks also based on these surveys, output and income multipliers were derived. The output multipliers range between 1.1 and almost 1.5 and indicate the change in production in the regions, due to a change in expenditure caused by tourists and the park management. The income multiplier captures only the indirect and induced income effect due to tourist and park management expenditure and ranges between 0.26 and 0.88 (Table 3). The total value of each park to its immediate local economy can be estimated by multiplying the relevant multipliers with the expenditure items. These estimates are indicated in Table 4. Again, it is evident that the contribution of the most popular parks to their local economies exceeds those of the other parks, which might be expected. Table 4. Total impact of the various parks (in constant 2000 rand). Expenditure item Output effect Income effect

Addo

Karoo

Wilderness

Tsitsikamma

58,532,226 24,641,350

10,497,928 6,098,620

15,107,733 8,547,943

32,527,660 12,228,487

1048

TOURISM ECONOMICS

In terms of the various parks’ contribution to employment and business development in their respective local economies, the results from the business surveys were used. As such, it is estimated that Addo Elephant National Park has led to 434 additional job opportunities (7.2% of households) in the local economy, Tsitsikamma National Park to 244 additional jobs (46.7% of households), Wilderness National Park to 288 job opportunities (11.25% of households) and Karoo National Park to 244 job opportunities (3.34% of households). Given the high unemployment rates in most of these local economies, the existence of the national park has contributed towards job creation for locals. It is also interesting that all the economies are very reliant on tourists for income and that 25% of all businesses around Tsitsikamma owe their existence to the national park. For Addo, this percentage is 33% of all businesses, for Wilderness 24% of all businesses and only 4% of businesses in Beaufort West exist because of the Karoo National Park. Yet, when one examines the percentage of turnover that businesses ascribe to the national park being in their vicinity, it gives another indication of the importance of these parks to their local economies. Around Tsitsikamma, accommodation establishments indicated that they owed 35% of their turnover to the park, while 12% of retail turnover was due to the park. In Wilderness, guest houses and bed-and-breakfast establishments indicated that they owed 62.1% of their turnover to the park. Restaurants indicated a percentage of 7.5, and tourism and recreation services estimated this contribution at a third. Guest houses and bed-and-breakfast establishments around Addo Elephant National indicated that they owed 65% of their turnover to the park, while lodges and the hotel indicated that 39% and 10% of their turnover, respectively, could be ascribed to the park. Curio shops indicated that 26% of their business was due the park, with restaurants indicating a percentage of 33%. Retailers and service stations indicated that they owed 11% of their turnover to the park, and tourism and recreation services estimated this contribution at 19%. The percentages are again lower for businesses around the Karoo National Park, with accommodation units owing 12% of their turnover to the park, curio shops 9%, restaurants and recreation services 15% and retailers and service stations owing, respectively, 8% and 20% of their turnover to the park.

Social impact The effect of the various national parks on the society surrounding the park were measured by various statements pertaining to the effect of the park on the quality of life, the community and various other social indicators (see Table 6). The responses of the communities to these statements are documented in Tables 5 and 6. According to the results of the questionnaire, all the national parks have a very positive impact on their communities. The parks also affect the communities’ personal quality of life positively, indicating the positive perception that the communities have of the relevant national parks. The social indicators are listed in Table 6 and it is evident that all the national parks have a positive effect on the appearance and perception of the


1049

Table 5. Effect of the various national parks on the quality of life and the community. Statement Effect on personal quality of life

Effect on the community

Karoo

Wilderness

Tsitsikamma

Very positive (67%) Very positive (72%)



Table 6. Social indicators of the various national parks. Social indicators

Karoo

The appearance of the area has improved Employment opportunities in the local economy have increased The range of things to do in the local region has increased The number of people in the area has increased Property values in the area have increased Crime levels have increased

Agree (70%) Agree (80%)

Agree (74%)


Agree (73%)

Agree (55%) Agree (46%) Agree (49%) Neither agree nor disagree (36%)

Agree (67%) Agree (79%) Agree (65%) Disagree (54%)

Participation in community activities has increased Opportunities to relax have increased Prices of some goods and services have increased The pride that the residents have in their town has improved The overall cost of living has increased The opportunities to meet new people have increased Opportunities for local business have increased The number of tourists visiting the town at other times of the year has increased Public funding for community activities has increased The rights and civil liberties of local residents have increased Interaction between locals and tourists has increased Facilities available to local residents have improved Social and moral values have improved The turnover for local businesses has increased

Wilderness

Agree (70%) Agree (76%) Agree (72%) Disagree (64%)

Tsitsikamma

Agree (45%) Disagree (62%) Agree (65%) Agree (41%) Agree (72%) Agree (65%) Agree (35%) Agree (68%)

Agree (76%)

Agree (65%) Agree (78%) Agree (37%) Agree (64%)


Agree (54%) Agree (67%) Agree (55%) Agree (73%)



Agree (81%)

Agree (35%) Disagree (74%) Agree (54%) Agree (37%) Disagree (68%) Disagree (55%) Agree (41%) Agree (55%)

Agree (65%)

Agree (46%) Disagree (56%) Agree (52%) Agree (37%) Disagree (68%) Disagree (52%) Agree (45%) Agree (76%) Agree (70%)

Note: The scale used at Karoo National Park was ‘Agree/Disagree/Uncertain/Do not know’. The scales for the other parks ranged from ‘strongly disagree’ to ‘strongly agree’.

1050

TOURISM ECONOMICS

local towns, as well as on the local economy. They have improved the pride of the local community and its interaction with other people. Yet the parks have also contributed to an increase in the price of goods and services and the cost of living in the area. The influences on crime and social and moral values are also not as positive as one would expect. Wilderness National Park has not been able to improve community participation in activities, public funding for community activities, or facilities available to local residents. The evidence from the other two parks is more positive in this regard.

A regional perspective From the results of the four studies, it is evident that not only do the parks differ, but also their impact on the economy and community in which they operate differs. As such, the regional influence of the various parks is unique, as is evident from the following. First, the Karoo National Park has the highest multipliers, which is an indication that more linkages have been established with local businesses. Possible reasons why more linkages were established might be sought in the remoteness of the park and the town of Beaufort West (with the nearest town approximately 200 km away) and the nature of economic activity in the town. The town also has a well-established business and industrial area. Even though it is rather remote, it is situated on an important national road linking Cape Town with Johannesburg, causing a constant flow of traffic. Since the park borders the town, it contributes towards a positive social impact. Second, the Addo Elephant National Park has the greatest impact on the local economy. It is also the park which has the best-developed tourism infrastructure, with various types of accommodation units and tourist activities (game drives, hiking, horse riding, etc) available, a comprehensive road infrastructure and the greatest variety of species that includes the Big 7. It is a park that shows huge potential in terms of growing tourist numbers. The park has a great impact on businesses in the area and has also contributed to an increase in economic activity in the area – as can be seen from the fact that a third of all businesses owe their existence to the park and large percentages of their income are ascribed to the park’s existence. Third, it is evident that both marine parks (Tsitsikamma and Wilderness) are situated in small holiday towns and coastal resorts, in a well-established tourism region known as the Garden Route. These parks show the lowest multiplying effects, although Tsitsikamma National Park has a relatively large economic impact due to more tourists and better-developed tourism infrastructure compared to Wilderness National Park. Since the main activities in this region are based on tourism, farming and forestry, the absence of other industries leads to higher leakages, and thus lower multipliers. Fourth, from a social point of view, parks that are adjacent to communities with high unemployment rates (such as Karoo and Tsitsikamma National Parks) are viewed by the relevant communities as having a greater impact, with better facilities for local residents, more community participation and an increase in public funding for these areas. Fifth, an urban park in a more affluent area, such as Wilderness, has higher


1051

social value than economic value. The high social value is fuelled by a large proportion of the community that perceive the benefits they derive from the park to be extremely important. This includes access to the park, improved property values and a high level of conservation that impacts positively on the quality of their environment in general. Hence, they perceive their personal quality of life to be very high. The location of the park (that is, urban) also leads to high employment of locals in park activities. Although there are many differences in the parks and their socio-economic impacts, there are also some aspects that are constant. On the positive side, the establishment of a national park in all the regions has had a positive social impact in terms of the community’s perception of their area, their life and the quality of their life. It has contributed towards building pride – an important aspect in improving both development and quality of life. Added to this, these parks also have positive economic spin-offs and they make a positive contribution to conservation. As such, these parks are all addressing the three core mandates of national parks in South Africa: the conservation of national assets and biodiversity, a contribution to the regional economy and a contribution to their local communities. However, the level at which these objectives are addressed differ from park to park. This is influenced by what the park has to offer in terms of both conservation value and tourism infrastructure. On the negative side, all communities indicate that the increased tourist numbers has put pressure on the price of goods and services and has increased their cost of living. The ‘imported’ inflation caused by additional economic activity is an indication that the capacity to supply products that tourists need and demand is not always available in the region of these national parks.

Conclusion This article compares the local socio-economic impact of four national parks, using similar methodology, and thereby contributes towards the understanding of how national parks interact with their regional economies and communities. The lessons that have been learned from this research could be useful in the decision-making process when it comes to the location and development of national parks and regional development. The results of this research show clearly that different levels of regional development have an influence on the economic impact of these parks. Added to this, it became evident that communities, in general, supported these parks and perceived them as very positive contributors to their quality of life. The research therefore also confirms the research by Eagles and McCool (2002) and Crookes and Milner-Gulland (2006), which indicates that the link between the community and protected areas occurs at different levels, which include the positive economic effect of tourist and park spending on employment and business opportunities, as well as the scenic backdrop, which improve quality of life. Added to this, the research indicates that other links between the community and the national park include the improvement of community pride, recreational activities, interaction with locals and tourists and, in the more impoverished areas, improved participation in and funding of community

1052

TOURISM ECONOMICS

activities. However, there is very little evidence to suggest that national parks have a positive effect on social problems in the surrounding communities (that is, crime levels and low social and moral values). From the results, one can ascertain that, over and above the four aspects identified in the literature that contribute towards the economic impact (that is, number of tourists, length of stay, amount spent by tourists and the multiplying effect of spending), socio-economic impacts are influenced by additional factors. These factors include: the levels of unemployment and development in the adjacent communities; the level of development of the tourism infrastructure (accommodation, road infrastructure, number and variety of species and activities); the location of the park; the level of business and industrial development, as well as the size of the neighbouring town(s); and the level of community participation in the park. The results also suggest that the economic impact, in terms of output and income multipliers, is greater in more diversified economies (such as the Karoo National Park case study) compared to pure tourist economies (such as the Tsitsikamma and Wilderness National Parks). However, since tourism is a relatively labour-intensive industry, a greater percentage of households are involved, in terms of employment, in pure tourism economies. The research shows that in order for SANParks to improve their socioeconomic value for their local economies, better tourism infrastructure and variety of activities are paramount, together with high levels of community participation. The latter includes having park forums, the hosting of community events – either inside or outside the park borders – and to be visible in the community. It would also be beneficial for SANParks to establish and maintain good relations with local businesses to create more linkages between the parks and local businesses. Endnotes 1. The community survey was not conducted at the Addo Elephant National Park

References Anon (2005), Addo Elephant Park: Expansion (http://www.addoelephantpark.com/expansion.hp, accessed 17 January 2005). ASGISA (2005), Accelerated and Shared Growth Initiative of South Africa, Government Press, Pretoria. Crookes, D.J., and Milner-Gulland, E.J. (2006), ‘Wildlife and economic policies affecting the bushmeat trade: a framework for analysis’, South African Journal Of Wildlife Research, Vol 36, No 2, pp 15–165. Eagles, P., and McCool, S. (2002), Tourism In National Parks And Protected Areas; Planning And Management, University of Montana Press, Missoula, MT. Fauzi, A., and Buchary, E.S. (2002), ‘A socio-economic perspective of environmental degradation at Kepulauan Seribu Marine National Park, Indonesia’, Coastal Management, Vol 30, pp 167–181. Fredline, E. (2000), Host Community Reactions to Major Sporting Events: The Golden Coast Indy And The Australian Formula One Grand Prix In Melbourne, PhD dissertation, Griffith University, Brisbane. Fredline, L., Jago, L., and Deery, M. (2003), ‘The development of a generic scale to measure the social impact of events’, Event Management, Vol 8, pp 23–37. Loader, J.A. (1994), ‘National parks and social involvement – an argument’, Koedoe, Vol 37, No 1, pp 137–148. Macleod, D.V.L. (2001), ‘Parks or people: national parks and the case of Del Este, Dominican Republic’, Progress In Development Studies, Vol 1, No 3, pp 221–235. Myburgh, E., and Saayman, M. (2002), Ecotourism In Action: Guidelines And Principals, 2nd edn, Leisure C Publications, Potchefstroom.


1053

Page, S.J. (2007), Tourism Management: Managing For Change, 2nd edn, Butterworth-Heinemann, Oxford. Pelser, A. (2003), ‘Omgewingsbewaring in ‘n nuwe era: ‘n nis vir die geestes- en sosiale wetenskappe’, Tydskrif Vir Geesteswetenskappe, Vol 43, No 3&4, pp 164–176. Roehl, W. (1998), ‘The tourism production system: the logic of industrial classification’, in Ioannides, D., and Debbage, K.G., eds, The Economic Geography Of The Tourism Industry, Routledge, London. Saarinen, J. (2003), ‘The regional economics of tourism in northern Finland: the socio-economic implications of recent tourism development and future possibilities for regional development’, Scandinavian Journal of Hospitality and Tourism, Vol 3, No 2, pp 91–113. Saayman, M., and Saayman, A. (2004a), An Economic Impact Analysis of Addo Elephant National Park: Desk Top Study, Institute For Tourism and Leisure Studies, Potchefstroom. Saayman, M., and Saayman, A. (2004b), ‘Economic impact of cultural events’, South African Journal for Economic and Management Sciences, Vol 7, No 4, pp 629–642. Saayman, M., and Saayman, A. (2006), ‘Creating a framework to assess the economic contribution of national parks in South Africa: the case of the Addo Elephant National Park’, Tourism Economics, Vol 12, No 4, pp 619–633. Saayman, M., and Saayman, A. (2008a), Socio-Economic Impact of Wilderness National Park, Institute for Tourism and Leisure Studies, Potchefstroom. Saayman, M., and Saayman, A. (2008b), Socio-Economic Impact of Tsitsikamma National Park, Institute for Tourism and Leisure Studies, Potchefstroom. Saayman, M., Saayman, A., and Ferreira, M. (2007), Socio-Economic Impact of the Karoo National Park, Institute for Tourism and Leisure Studies, Potchefstroom. Saayman, M., Saayman, A., and Ferreira, M. (2009), ‘The socio-economic impact of the Karoo National Park’, Koedoe, Vol 51, No 1, pp 1–10. South Africa, Department of Environmental Affairs and Tourism (1996), Guidelines For Implementing the White Paper on The Development and Promotion of Tourism in South Africa, Government Printer, Pretoria. Streuders, C. (2008), Communication Efficacy of Karoo National Park, North West University, Potchefstroom (dissertation, MCom). Vaughan, D.R., Farr, H., and Slee, R.W. (2000), ‘Estimating and interpreting the local economic benefits of visitor spending: an explanation’, Leisure Studies, Vol 19, pp 95–118. Walpole, M.J., and Goodwin, H.J. (2000), ‘Local economic impacts of dragon tourism in Indonesia’, Annals of Tourism Research, Vol 27, No 3, pp 559–576. Wang, P.C.M. (1997), ‘Economic impact assessment of recreation services and the use of multipliers: a comparative examination’, Journal of Park and Recreation Administration, Vol 15, No 2, pp 32– 43. White Paper on Tourism (1996), see South Africa. Wilson, G.D.H. (1984), ‘n Ekonomies-Geografiese Analise Van Die Toerisme In Die Thabazimbi-Omgewing, PU vir CHO, Potchefstroom (dissertation, MCom).

1054

TOURISM ECONOMICS

Appendix 1 Descriptive statistics of the visitor surveys

Table A1. Addo Elephant National Park. N Language Age Marital status Province Qualification People Visits Nights Entrance Accommodation Restaurants Food Beverages Tobacco Clothing Transport to the park Transport at the park Recreation Medicine Toiletries Souvenirs Telecommunications Other Visit shops Valid N (list-wise)

67 65 66 28 64 58 61 63 66 67 67 67 67 67 67 67 67 67 67 67 67 67 67 63 23

Frequency Valid

7 Australia 3 France 2 Germany 23 New Zealand 1 RSA 33 Sweden 1 Switzerland 1 UK 2 USA 1 Total 74

Descriptive statistics Minimum Maximum Mean 1 3 1 1 2 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

9 6 5 9 5 12 36 12 1,500 4,000 3,000 2,100 1,000 250 500 1,000 500 6,000 150 100 2,000 200 20 2

Country Percentage Valid percentage 9.5 4.1 2.7 31.1 1.4 44.6 1.4 1.4 2.7 1.4 100.0

9.5 4.1 2.7 31.1 1.4 44.6 1.4 1.4 2.7 1.4 100.0

4.52 4.37 1.71 3.25 3.19 2.43 4.97 3.22 125.26 603.18 183.19 184.70 83.48 4.03 20.90 171.79 33.58 175.07 3.73 1.49 46.27 8.10 0.30 1.38

Std deviation 3.839 1.039 1.134 1.878 0.924 1.708 5.980 1.923 241.727 926.571 476.049 445.121 187.912 30.603 84.616 290.553 92.682 742.713 21.870 12.217 256.183 35.293 2.443 0.490

Cumulative percentage 9.5 13.5 16.2 47.3 48.6 93.2 94.6 95.9 98.6 100.0


1055

Table A2. Karoo National Park. N Language Age Marital status Province Qualification People Visits Nights Entrance Accommodation Restaurants Food Beverages Tobacco Clothes Transport to the park Transport at the park Game drives Medicine Toiletries Souvenirs Telecommunications Other Total Shops visited Wild card Valid N (list-wise)

100 90 101 88 99 94 94 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 96 98 69

Frequency Valid Austria 1 Botswana 1 Germany 1 Korea 1 New Zealand 1 RSA 85 Spain 1 UK 9 Zimbabwe 1 Total 101

Descriptive statistics Minimum Maximum Mean 1 18 1 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1

3 79 5 9 5 18 30 10 1,000 3,250 580 500 500 0 160 3,000 1,220 480 60 150 144 200 350 7,450 2 2

1.57 48.29 1.37 3.68 3.41 3.14 4.93 1.71 41.73 501.99 51.39 36.49 25.55 0.00 3.63 376.05 36.04 9.21 0.59 3.27 6.57 5.10 6.73 1,104.35 1.29 1.51

Country Percentage Valid percentage 1.0 1.0 1.0 1.0 1.0 84.2 1.0 8.9 1.0 100.0

1.0 1.0 1.0 1.0 1.0 84.2 1.0 8.9 1.0 100.0

Std deviation 0.537 15.062 0.902 2.761 1.050 2.270 4.238 1.178 116.412 582.117 120.709 92.289 62.258 0.000 21.437 453.251 141.493 52.568 5.970 17.153 24.284 28.107 45.697 1,084.009 0.457 0.502

Cumulative percentage 1.0 2.0 3.0 4.0 5.0 89.1 90.1 99.0 100.0

1056

TOURISM ECONOMICS

Table A3. Wilderness National Park. N Language Year of birth Marital status Province Education People Visits Nights Entrance Accommodation Restaurant Food Beverages Tobacco Clothes Transport to the park Transport at the park Activities Medicine Toiletries Souvenirs Telecommunications Other Total Visit shops Wild card Valid N (list-wise)

73 72 73 72 71 68 73 73 73 73 73 73 73 73 73 73 73 73 73 73 73 73 73 73 72 70 60

Frequency Valid Germany RSA Taiwan UK Total

1 70 1 1 73

Descriptive statistics Minimum Maximum Mean 1 1,932 1 1 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 170.00 1 1

3 1,984 5 9 6 11 30 45 2,200 5,000 2,000 2,000 1,500 500 2,600 3,000 600 400 100 200 65 180 1,000 13,960 2 2

1.55 1,963.14 1.47 3.68 3.31 3.50 4.70 4.44 197.39 1,068.79 257.67 439.17 203.83 23.16 83.21 516.30 53.42 15.20 5.10 18.90 0.89 5.44 19.28 2,907.82 1.10 1.46

Country Percentage Valid percentage 1.4 95.9 1.4 1.4 100.0

1.4 95.9 1.4 1.4 100.0

Std deviation 0.554 10.762 1.107 1.287 1.077 1.791 4.912 5.545 391.217 910.716 450.868 450.196 308.678 72.215 362.668 500.567 114.117 61.601 19.135 46.713 7.607 28.128 119.535 2,211.502 0.298 0.502

Cumulative percentage 1.4 97.3 98.6 100.0


1057

Table A4. Tsitsikamma National Park. N Language Year of birth Marital status Province Education People Visits Nights Entrance Accommodation Restaurants Food Beverages Tobacco Clothes Transport to the park Transport at the park Activities Medicine Toiletries Souvenirs Telecommunications Other Visit shops Wild card Valid N (list-wise)

154 153 156 135 152 150 153 153 156 155 156 156 156 155 156 156 156 156 156 156 156 156 156 154 152 110

Frequency Valid

Australia 2 Belgium 1 Bulgaria 1 Germany 5 Namibia 1 Netherlands 3 Norway 1 RSA 129 Saudi Arabia 1 Scotland 1 Sweden 1 Switzerland 1 UK 5 USA 2 Zimbabwe 1 Total 155 Missing –9 1 Total 156

Descriptive statistics Minimum Maximum Mean 1 1,924 1 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1

3 1,990 5 9 9 27 60 15 1,500 14,000 3,500 3,000 2,000 200 3,500 4,500 1,000 2,500 200 800 530 1,000 2,160 2 6

1.75 1,962.54 1.38 3.19 3.75 3.53 4.12 4.40 160.06 1,314.05 212.30 340.87 116.79 4.97 127.40 683.22 82.62 54.61 7.50 22.94 27.21 13.07 24.28 1.26 1.39

Country Percentage Valid percentage 1.3 0.6 0.6 3.2 0.6 1.9 0.6 82.7 0.6 0.6 0.6 0.6 3.2 1.3 0.6 99.4 0.6 100.0

1.3 0.6 0.6 3.2 0.6 1.9 0.6 83.2 0.6 0.6 0.6 0.6 3.2 1.3 0.6 100.0

Std deviation 0.622 11.133 0.986 2.217 1.164 2.551 5.598 3.285 245.834 1,792.308 379.923 578.338 247.813 27.386 429.464 892.575 207.286 254.135 34.165 87.440 88.773 88.322 185.950 0.440 0.652

Cumulative percentage 1.3 1.9 2.6 5.8 6.5 8.4 9.0 92.3 92.9 93.5 94.2 94.8 98.1 99.4 100.0

1058

TOURISM ECONOMICS

Appendix 2 Descriptive statistics of the business surveys Table A5. Addo Elephant National Park. N Location Number of beds Bed occupancy (%) Conference capacity Years of existence Tourists (%) Locals (%) Number of workers Permanent employment (%) Temporary employment (%) Live in the area Stock (%) Goods and services (%) Tax (%) Salaries (%) Local purchases (%) Existence due to park Turnover due to park (%) Valid N (list-wise) Classa Valid

A A, G A, H, B B C D E F G H Total Missing –9 Total

Std deviation

83 48 41 20 81 79 77 66

1 0 0 0 0 0 0 0

2 240 90 100 986 100 99 350

1.95 20.81 50.02 29.15 22.80 51.95 46.27 15.45

0.215 36.966 26.607 28.359 109.803 37.274 36.521 47.245

77

0

100

78.96

32.325

45 78 81 80 79 82 78 81 83 8

0 1 0 0 0 0 0 0 0

100 2 100 100 40 100 100 2 100

29.64 1.04 23.75 17.46 6.03 13.71 28.64 1.36 34.07

31.804 0.194 33.913 26.097 8.911 21.983 34.370 0.508 36.185

Frequency 39 3 1 7 4 16 2 1 1 6 80 3 83

Descriptive statistics Minimum Maximum Mean

Classification Percentage Valid percentage 47.0 3.6 1.2 8.4 4.8 19.3 2.4 1.2 1.2 7.2 96.4 3.6 100.0

48.8 3.8 1.2 8.8 5.0 20.0 2.5 1.2 1.2 7.5 100.0

Cumulative percentage 48.8 52.5 53.8 62.5 67.5 87.5 90.0 91.2 92.5 100.0

Note: aA = accommodation; B = curios; C = food and restaurants; D = transport; E = retail; F = wholesale; G = manufacturing; H = recreation/tourism services.


1059

Table A6. Karoo National Park. N Beds available Bed occupancy Years of existence Tourists (%) Locals (%) Permanent employment Temporary employment Total employment Live in the area Stock (%) Municipal (%) Other (%) Operational (%) Wages (%) Stock purchases local Service purchases local Operational purchases local Existence due to park Turnover due to park Valid N (list-wise) Classa Valid

A A, B B C D E E, F E, G E, H F G H Total Missing –9 Total

Std deviation

6 6 85 75 74 83 41 84 84 46 42 30 38 44 53 54

6 50 1 0 0 1 1 1 1 5 1 1 0 0 0 0

50 100 100 100 100 41 150 182 2 80 20 35 40 70 100 100

23.67 63.33 15.62 27.59 68.76 7.52 8.83 11.74 1.02 50.91 8.60 9.60 12.76 19.43 44.72 59.57

15.513 19.745 19.196 27.135 28.102 8.928 25.827 23.564 0.153 19.874 5.583 8.203 9.263 14.699 36.340 42.132

44 84 67 1

0 1 0

100 2 90

62.05 1.04 9.37

42.961 0.187 14.003

Frequency 5 1 4 11 2 52 1 1 1 3 2 2 85 1 86


Classification Percentage Valid percentage 5.8 1.2 4.7 12.8 2.3 60.5 1.2 1.2 1.2 3.5 2.3 2.3 98.8 1.2 100.0

5.9 1.2 4.7 12.9 2.4 61.2 1.2 1.2 1.2 3.5 2.4 2.4 100.0

Cumulative percentage 5.9 7.1 11.8 24.7 27.1 88.2 89.4 90.6 91.8 95.3 97.6 100.0

Note: aA = accommodation; B = curios; C = food and restaurants; D = tourism services; E = retail; F = transport; G = wholesale; H = manufacturing.

1060

TOURISM ECONOMICS

Table A7. Wilderness National Park. N Available beds 21 Bed occupancy 21 Conference capacity 21 Years 19 Tourists (%) 22 Locals (%) 20 Permanent employment 18 Temporary employment 12 Live in area 20 Stock (%) 14 Municipal (%) 14 Other services (%) 14 Operational costs (%) 14 Wages (%) 14 Stock purchases local 16 Stock purchases outside 16 Services purchases local 15 Services purchases outside 15 Operational purchases local 15 Operational purchases outside 15 Existence due to park 21 Turnover due to park 12 Valid N (list-wise) 5 Classa

Frequency

A C G H Total

1 14 1 3 4 23

Valid


Std deviation

0 0 0 1 20 3 1 1 1 0 2 0 5 10 0 0 0 0

369 100 510 131 100 80 27 45 1 65 27 35 40 60 100 100 100 100

26.76 26.33 28.76 14.37 69.27 33.80 6.94 7.75 1.00 26.31 9.69 16.02 16.79 31.19 36.88 63.12 39.33 60.67

79.571 31.571 111.401 28.644 25.030 24.148 7.166 12.099 0.000 20.809 5.592 10.169 9.561 13.562 38.073 38.073 41.139 41.139

0

100

41.73

42.410

0 1 5

100 2 90

58.27 1.24 45.83

42.410 0.436 29.759

Classification Percentage Valid percentage 4.3 60.9 4.3 13.0 17.4 100.0

4.3 60.9 4.3 13.0 17.4 100.0

Cumulative percentage 4.3 65.2 69.6 82.6 100.0

Note: aA = accommodation; C = retail; G = tourism services; H = food and restaurants.


1061

Table A8. Tsitsikamma National Park. N Available beds 7 Bed occupancy 6 Conference capacity 1 Years 11 Tourists (%) 11 Locals (%) 11 Permanent employment 11 Temporary employment 11 Live in area 10 Stock (%) 6 Municipal (%) 6 Other services (%) 6 Operational costs (%) 6 Wages (%) 6 Stock purchases local 7 Stock purchases outside 7 Services purchases local 7 Services purchases outside 7 Operational purchases local 7 Operational purchases outside 7 Valid N (list-wise) 1 Classa

Frequency

A C G Total

1 6 4 1 12

Valid


Std deviation

4 7.0 84.0 0.1 10.0 0.0 0.0 0.0 1.0 0.0 5.0 5.0 5.0 30.0 0.0 0.0 0.0 0.0

78 75 84 30 100 90 40 54 2 40 20 20 30 40 100 100 100 100

23.14 54.00 84.00 8.79 65.00 35.00 6.09 6.63 1.10 23.66 10.00 11.50 22.33 32.50 37.28 62.71 47.71 52.28

26.028 25.502 0.000 10.115 30.565 30.565 11.717 16.057 0.316 16.268 5.477 5.244 11.604 04.183 39.305 39.305 44.683 44.683

0.0

100

47.42

45.014

0.0

100

52.57

45.014

Classification Percentage Valid percentage 8.3 50.0 33.3 8.3 100.0

8.3 50.0 33.3 8.3 100.0

Note: aA = accommodation; C = retail; G = tourism services.

Cumulative percentage 8.3 58.3 91.7 100.0

1062

TOURISM ECONOMICS

Appendix 3 Descriptive statistics of the social surveys Table A9. Karoo National Park. N Year Gender Occupation Education Appearance Employment opportunities Things to do Number of people Property values Crime levels Participation in community activities Entertainment opportunities Prices Pride Cost of living Meet new people Local business Number of tourists Public funding Liberties of local residents Interactions Facilities available Social and moral values Turnover for local businesses


232 235 233 228 199

1923 1 1 1 1

202 199 200 200 197

Std deviation

1998 2 14 9 4

1965.28 1.37 7.19 3.17 2.40

15.857 0.484 5.275 1.485 0.797

1 1 1 1 1

4 4 4 4 4

2.34 2.41 2.79 2.64 2.60

0.820 0.823 0.911 0.898 1.003

199

1

4

2.62

0.896

199 203 198 201 201 200 199 203

1 1 1 1 1 1 1 1

4 4 4 2 4 4 4 4

2.48 2.60 2.36 2.59 2.45 2.52 2.36 2.77

0.963 0.962 0.824 0.967 0.812 0.874 0.859 1.034

202 200 198 202

1 1 1 1

4 4 4 4

2.67 2.68 2.48 2.61

0.984 .992 0.911 0.992

198

1

4

2.69

0.973


1063

Table A10. Wilderness National Park. N Year of birth Gender Occupation Education Quality of life Community Favour of location Asset to community Where born Years Appearance Employment Things to do Number of people Property values Crime Community activities To relax Prices Pride Cost of living Meet new people Local business Number of tourists Public funding Civil liberties Interaction Facilities Social values Turnover

101 101 101 101 100 99 96 100 95 94 96 96 97 97 96 94 84 93 96 91 95 91 94 96 86 88 89 89 88 95

Descriptive statistics Minimum Maximum Mean 1922 1 1 2 -3 -3 1 1 1 0 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2

1991 2 14 6 3 3 2 2 5 37 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 4 4 4 4 4

1955.71 1.53 6.10 3.18 1.50 1.80 1.89 1.95 2.92 8.36 2.94 2.68 2.78 2.93 2.95 2.32 2.36 2.80 2.85 2.87 2.81 2.74 2.83 2.93 2.16 2.16 2.51 2.36 2.23 3.14

Std deviation 16.497 0.501 4.621 1.062 1.508 1.400 0.320 0.219 0.846 8.021 0.792 0.641 0.680 0.696 0.716 0.722 0.614 0.700 0.882 0.653 0.789 0.612 0.666 0.669 0.571 0.709 0.659 0.727 0.638 0.612

1064

TOURISM ECONOMICS

Table A11. Tsitsikamma National Park. N Year of birth Gender Occupation Education Quality of life Community Favour of location Asset to community Wild card Where born Appearance Employment Things to do Number of people Property values Crime Community activities To relax Prices Pride Cost of living Meet new people Local business Number of tourists Public funding Civil liberties Interaction Facilities Social values Turnover

130 130 119 122 118 118 113 119 105 121 126 128 128 127 126 127 123 126 125 126 126 124 122 127 121 121 123 123 118 124

Descriptive statistics Minimum Maximum Mean 1,927 1 1 1 –3 –3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1,996 2 14 6 3 3 2 2 2 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4

1,969.65 1.34 8.72 3.25 1.58 1.69 1.83 1.83 1.17 2.43 2.85 2.79 2.73 2.94 2.71 2.38 2.63 2.60 2.91 2.63 2.73 2.77 2.66 2.98 2.50 2.37 2.58 2.43 2.38 2.80

Std deviation 15.980 0.475 4.794 1.609 1.746 1.771 0.376 0.376 0.379 0.911 0.780 0.820 0.828 0.770 0.866 0.908 0.792 0.802 0.843 0.910 0.916 0.787 0.821 0.766 0.818 0.838 0.820 0.790 0.826 0.846