About the Author(s)

Alicia Fourie symbol
School of Economics, North-West University, South Africa

Tourism Research in Economic Environs and Society, North-West University, South Africa

Melville Saayman Email symbol
Tourism Research in Economic Environs and Society, North-West University, South Africa

Elmarie Slabbert symbol
Tourism Research in Economic Environs and Society, North-West University, South Africa

School of Tourism Management, North-West University, South Africa


Fourie, A., Saayman, M. & Slabbert, E., 2018, ‘Who are the big spending tourists travelling to South Africa?’, Journal of Economic and Financial Sciences 11(1), a205. https://doi.org/10.4102/jef.v11i1.205

Original Research

Who are the big spending tourists travelling to South Africa?

Alicia Fourie, Melville Saayman, Elmarie Slabbert

Received: 06 Apr. 2018; Accepted: 30 June 2018; Published: 14 Nov. 2018

Copyright: © 2018. The Author(s). Licensee: AOSIS.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Orientation: Tourism growth is not just about numbers anymore; it is about utilising the economic potential of every tourist visiting South Africa. This country needs to target the most lucrative markets to benefit economic growth.

Research purpose: This article aims to identify the big spenders with reference to demographic characteristics and tourist destination preferences.

Motivation for the study: The number of tourists to South Africa increases annually. However this is not evident in an increase in job opportunities or tourism products. The tourism industry also indicated that they receive less tourists. Therefore the increase in tourists do not necessarily lead to an increase in income which might relate to the type of tourist received.

Research design, approach and method: A quantitative survey was done amongst international visitors leaving South Africa at O.R. Tambo International Airport, to which a two-step clustering method was applied.

Main findings: Two spending groups were identified namely big spenders and average spenders. Big spenders are characterised by a specific demographic profile of being single, better qualified, in a professional occupation, and male. They tend to prefer visiting the iconic natural attractions where they spend significantly more than the average spenders.

Practical/managerial implications: The implication of this study is that tourism bodies should focus more direct marketing efforts on the big spenders and provide products that suit the needs of this target market.

Contribution/value-add: Effective market segmentation based on spending provide insight to markets that will create a high return on investment and this will directly contribute to the economic growth of the industry and alleviate poverty.



Tourism has the potential to be a modern-day engine of growth because tourism is the largest service industry globally. This is especially true for developing countries, where tourism plays a significant role in the generation of foreign-exchange earnings (Srihadi et al. 2016). South Africa is no different, and government has identified tourism as being a key sector with the potential to assist with the country’s economic growth (National Department of Tourism 2011). In this regard, the South African government aims to increase tourism’s contribution to economic growth from R189.4 billion in 2009 to R499 billion by 2020 (National Department of Tourism 2011).

More than 10 million international tourists visited South Africa in 2016, which was 13% more than in 2015 (Cape Argus 2017). Various efforts are made by destinations to accelerate growth, for example the implementation of creative marketing strategies, promotional efforts, upgrading of tourism products – all to grow this industry as efficiently as possible. It is the key role of destination marketers to influence and manage demand (Middleton et al. 2009), and they are continuously searching for new ways to do this. To be more effective and efficient in one’s marketing strategy, it is vital to understand the market.

It is, however, not just about numbers or arrivals anymore but about securing significant economic benefits from these tourists for the benefit of the country. In the past government agencies focused primarily on the number of tourists rather than spending. And in this regard Saayman and Saayman (2006a) state that it is better for destinations to attract 10 tourists who spend $100 than 100 tourists who spend $10. The amount that tourists spend has therefore become a better criterion for measuring success than just arrival figures.

Australia, for example, attracts far fewer tourists than a country such as South Africa. However, the average tourist in Australia spends far more than those in South Africa. This becomes even more apparent when one analyses visitor arrival figures and their spending in South Africa, where research confirmed that a tourist from Africa spends far less than tourists from Europe. However, the sheer number of African tourists makes up for their lack of spending (Saayman & Saayman 2008).

Research purpose

The latter prompted this research, which aimed to identify the big spending tourist markets in South Africa. This research differed from that found in the literature, where most other studies analysed only tourist and visitor expenditure (see Craggs & Schoffield 2006; Kruger, Saayman & Saayman 2010; Letho et al. 2004; Saayman & Saayman 2006b, 2008). This study also used a list of 12 key attractions in the analyses to determine if spending differed from attraction to attraction – an innovative approach that to the best of the authors’ knowledge has not been followed before.

This type of research will assist tourism marketers and planners, because a new marketing paradigm is needed for South Africa. Such a paradigm should not focus on mass marketing but rather on targeted marketing for tourists to make a greater contribution to poverty-alleviation in this country. Research also confirms that the greater the economic impact, the greater the contribution to job creation (Saayman & Saayman 2006a, 2006b). Greater success follows from pursuing specific groups of tourists rather than from trying to appeal to the mass market (Morrison 2013).

Literature review

As part of a marketing strategy, market segmentation serves as the foundation for destination positioning and branding and can thus be seen as the starting point of marketing (Morrison 2013). This concept recognises that people differ and this knowledge enables the identification of similar groups whose needs and wants can be addressed by providing the most appropriate products and experiences (Middleton et al. 2009). One can then deal with the selected markets more profitably and effectively. Market segmentation is a dynamic process where segments are continuously changing because of shifts in the external environment as well as changes in consumers’ lifestyle. Their motivations, desires (Morrison 2013) and even spending patterns vary over time. As was indicated before, statistics on arrivals are not enough, and a more detailed understanding of the markets is necessary.

Market segmentation enables marketers to define groups of individuals according to one or several variables, including socio-economic demographics, motivations for travel, lifestyle, interest, values and personality (Galloway et al. 2008; Legoherel & Wong 2006; Morrison 2013). Specifically, the application of expenditure-based segmentation proves to be very efficient in dividing tourists into spending market segments. Legoherel (1998) regards expenditure-based segmentation as one of the superior segmentation approaches. The reasons for this are that expenditure-based segmentation:

  • identifies high-yielding markets
  • gives detailed information concerning the spending patterns and items of tourists
  • can assist in the cost-effectiveness of marketing
  • provides useful information for policy development
  • can assist in identifying niche markets
  • can assist in developing the right packages and products for the right markets (Saayman & Saayman 2006b; Wilton & Nicherson 2006).

Using market segmentation, Pizam and Reichel (1979) were among the first researchers to compare the socio-economic and demographic characteristics of big spenders and little spenders. The results indicated that residence, race, marital status, education and occupation were significantly different between these two groups (Pizam & Reichel 1979). A study compiled by Spotts and Mahoney (1991) found three key markets or clusters, namely high, medium and low spenders. Most studies conducted on expenditure-based segmentation use a combination of these three clusters.

Saayman and Saayman (2018) found six clusters or segments when they conducted a comprehensive study of scuba divers in Italy. This study showed that niche or specialised markets can have more than three clusters, for example, local rescue divers, international big spenders, intracontinental diver markets, new local divers, international advanced divers and local instructors. Spotts and Mahoney (1991) also found that big spenders were distinguishable from other spenders when one looks specifically at length of stay and party size. Agarwal and Yochum (1999), Downward and Lumsdon (2004), Leones, Colby and Crandall (1998), Mok and Iverson (2000), Saayman and Saayman (2009), Seiler et al. (2003) and Thrane (2002) concurred with the study by Spotts and Mahoney (1991) and found that people travelling with a larger group tend to spend more money, but they stay for a shorter period.

Studies conducted by Lee (2001), Mok and Iverson (2000), Perez and Juaneda (2000), Saayman and Saayman (2011) and Thrane (2002), looking at tourists visiting islands, festivals and tourism in general, found that age can contribute significantly to a tourist spending more money. Other factors influencing higher spending habits are profession, nationality, accommodation and transportation (Perez & Juaneda 2000), income (Agarwal & Yochum 1999; Taylor, Fletcher & Clabaugh 1993) and attraction type (Taylor et al. 1993).

Overall the literature review revealed that expenditure-based segmentation studies found that high spenders differ from low and medium spenders in six specific areas. Firstly, high spenders are better educated (Snowball & Willis 2006). Secondly, they earn more (Kruger & Saayman 2016; Saayman & Saayman 2006b, 2011; Thrane 2002). Thirdly, they are older (Kruger 2010). Fourthly, they travel larger distances (Cannon & Ford 2002; Pouta, Neuvonen & Sievänen 2006) and, fifthly, they stay longer (Mok & Iverson 2000; Thrane 2002). Lastly, they come from international or foreign markets (Saayman & Saayman 2006b, 2018). It is therefore important to capitalise on these high spenders because the tourism industry has the potential to create significant growth within a country, given its role in the service industry (Brida et al. 2010; Seiler et al. 2003).

A great deal of research has been conducted on the socio-demographic variables that influence tourists’ spending habits. Notwithstanding the aforementioned literature, little research has been conducted on big spenders from a destination perspective. This study looked specifically at the activities or destinations on which big spenders spend their money in South Africa. The next section focuses on the methodology and results of the spending habits of big spenders in South Africa.

Research design

Quantitative research was performed using a structured questionnaire among tourists at the O.R. Tambo International Airport in Johannesburg, South Africa. The O.R. Tambo International Airport is Africa’s biggest and busiest airport.

Research approach

The approach followed in this study was to target international tourists as they were waiting to board their respective flights back home. They were therefore in a favourable position to give a proper account of their spending during their stay and travels in South Africa.

Research method
Research participants

The target population was international tourists who were mostly at the departure terminals at O.R. Tambo International Airport in Johannesburg, South Africa. Krejcie and Morgan (1970) suggest that with a population size of 1 000 000, a sample size of 384 is acceptable. To ensure that a representative sample of international tourists departing from South Africa was acquired, experienced field workers were deployed to collect the data and 500 questionnaires were distributed. To furthermore ensure a representative sample, random sampling was used.

Measuring instrument

The questionnaire was divided into two sections. Section A captured the socio-demographic details of the respondents, including gender, date of birth, home language, the highest level of education, occupation and spending behaviour. Section B captured visitors’ travel behaviour, with specific reference to attraction preferences (Agarwal & Yochum 1999; Perez & Juaneda 2000; Saayman & Saayman 2011). Reliability and validity of the questionnaire were established.

Statistical analysis

The data were captured with Microsoft Excel®, and the statistical analysis was performed with the Statistical Package for Social Sciences (SPSS, 24.0). The statistical analysis was completed in two stages. Firstly, some analysis was done on the spending patterns of tourists by looking at who was spending money and on what the tourists were spending their money as seen in studies compiled by Galloway et al. (2008), Legoherel and Wong (2006) and Morrison (2013). Secondly, a two-step cluster analysis was carried out to identify two specific groups of tourists as seen by Kruger, Saayman and Saayman (2010). This classification was then used to identify how these two distinct groups of tourists spent their money, specifically looking at selected tourist destinations in South Africa.

Ethical considerations

Data for this study were collected by trained fieldworkers between 26 August and 01 September 2016. The research proposal was sent to the faculty’s ethical committee and was approved. The ethical code is EMS 15/10/15-02-01.


This section discusses the results of the descriptive statistics, expenditure patterns, two-step cluster analysis, independent sample t-tests and cross-tabulations.

Brief overview: Descriptive statistics

Table 1 presents the socio-demographic data that were collected from the survey at the O.R. Tambo International Airport. The majority of respondents were male (60.5%), had a tertiary-education background of either a diploma, degree or postgraduate qualification (85.7%), were married (54.2%) and had a professional qualification (22.8%). From the respondents, 49% indicated that the main purpose of their visit to South Africa was for holiday, 21% indicated it was for business, 19% indicated it was to visit family and friends, 2% indicated they had visited for medical reasons and 9% of visitors indicated they had visited for other purposes. Furthermore, 23% of respondents who visited South Africa for business also went on holiday to explore some of the sites South Africa has to offer.

TABLE 1: Socio-demographic indicators.

In order to better understand how many tourists visited different South African tourist destinations, Table 2 presents the percentage of tourists who visited the following attractions: national parks, the Garden Route, Cape Town Victoria & Alfred Waterfront, Johannesburg, Robben Island, the Winelands, Soweto, the Cradle of Humankind, Table Mountain, Durban beachfront, Sun City and the cultural villages. Websites such as Viator, TripAdvisor, Places South Africa, Travelstart and Safari Now ranked these attractions among the top-rated attractions to visit when visiting South Africa. The most popular destination with 63.6% was Johannesburg, followed by national parks (58.6%) and Cape Town V&A Waterfront (40.1%). The destination that attracted the fewest visitors was the Cradle of Humankind, with 8.1%.

TABLE 2: Tourist destination.

Because it was established which destinations attracted the most visitors, it would be meaningful to know, given a tourist’s socio-demographic information, which tourists are spending their money and on what. Table 3 reports the socio-demographic variables of marital status, level of education, occupation and gender, establishes the mean level of expenditure for each category in each variable and indicates whether the expenditure in each category in each variable differs significantly. The highest mean expenditure for the variable marital status was that of respondents who were engaged, with a mean level of expenditure of South African rand (R) 94 000.00, and respondents who were married, with a mean expenditure of R82 398.75.

TABLE 3: Mean expenditure – Socio-demographic factors.

Results further indicated that the mean expenditures of the different marital status categories differed significantly from one another (p < 0.05). Respondents who had a postgraduate qualification spent R40 299.57 on average, and the mean expenditures for the different levels of education differed significantly (p < 0.05). Furthermore, self-employed respondents spent R61 009.79 on average, followed by professionals, with a mean expenditure level of R41 743.35. The mean expenditure levels for the different occupations differed significantly (p < 0.05). The mean expenditures for males and females differed significantly, with males spending more than females (p < 0.05).

To elaborate on expenditure, Table 4 contains the mean expenditure per person on selected items, including airplane tickets, accommodation, activities, souvenirs, other transport, retail shopping, food and drink, other and spending per person in general. The mean expenditure per person visiting South Africa was calculated to be R31 297.25.

TABLE 4: Mean expenditure on selected items.

Table 5, on the other hand, presents the results from an independent sample t-test to determine whether there was a statistically significant difference in the mean scores for two groups (in this case tourists who had visited certain destinations or took part in certain activities, and those who had not). Table 5 shows that tourists visiting national parks, the Garden Route, Cape Town V&A Waterfront, Robben Island, the Winelands, the Cradle of Humankind and Table Mountain spent significantly more than visitors who had not visited these attractions and destinations.

TABLE 5: Mean differences in expenditure-based on activities and destinations.

Two-step cluster analysis

The two-step cluster analysis procedure is an exploratory tool designed to reveal natural groupings (or clusters) within a data set that would otherwise not be apparent. The TwoStep Clustering Component is a scalable cluster analysis algorithm designed to handle large data sets. Capable of handling both continuous variables and attributes, it requires only one data pass in the procedure. The objective of this section is to gain a better understanding of how specific tourists spend their money. One would be particularly interested in seeing how big spending tourists spend more than the average tourist.

To distinguish between tourists, a two-step cluster analysis was applied to identify clusters of tourists on the basis of their expenditure. Variables used to calculate expenditure were the cost of accommodation, transport, activities, food and beverage, retail shopping and souvenirs. Respondents were asked to indicate how much they spent towards each of the mentioned categories (in South African rands). In this case, two clusters were identified on the basis of the respondents’ expenditure patterns. In Table 6 two distinct clusters are indicated. Hereafter, the two clusters will be referred to as the ‘average spender’ and the ‘big spender’. The average spender recorded a mean expenditure of R17 537.55, and the big spender recorded a mean expenditure of R109 521.17. It was determined that the mean expenditures of these two types of spenders differed significantly (p < 0.05).

TABLE 6: Cluster distribution.

The specific activities and destinations at which big spenders and average spenders spent their money are presented in Table 7 using cross-tabulation. Cross-tabulations are used to indicate whether there is a statistical relationship between the type of spender (big or average) and the type of tourist activity or destination. To test the relationship between two categorical variables, the Pearson chi-squared test can be used.

TABLE 7: Cross-tabulation of spending habits.

With regard to national parks, 71.2% of big spenders indicated that they had gone to a national park. Furthermore, 26.9% of big spenders indicated that they had visited the Garden Route, 48.1% had visited Cape Town V&A Waterfront, 30.8% had visited the Winelands and 15.4% had visited the Cradle of Humankind. The Pearson chi-squared test results for these activities and destinations indicated that there was a significant difference between the spending habits of the big and the average spenders, whether or not they had visited these destinations.


Outline of the results

Firstly, the research highlighted specific attraction preferences, the fact that all attractions were not equally important to tourists (confirming research by Morrison 2013) and that tourist spending per attraction differed significantly. It confirmed the popularity of attractions such as national parks, the Cape Town V&A Waterfront and Johannesburg. These attractions all form part of the list of top 10 things to see and experience in South Africa (www.southafrica.net) and are therefore well marketed, leading to optimal visitation.

The value of iconic, well-known attractions for big spenders should not be underestimated by the government and the tourism industry. To sustain the popularity of these attractions, it is important to constantly modify these products to serve the needs of potential, current and returning visitors. It is also evident that attractions such as the cultural villages and Robben Island are not favoured by the big spenders, even though they still spend significantly more at these attractions than the average spenders.

It would be interesting to determine the reasons for this. It could be that these big spenders have experienced these attractions before, or that these attractions do not interest them at all. From an economic point of view this is an interesting finding, because we need to understand the reasons why specific attractions are preferred and why tourists spend more at them compared to other top or well-known attractions.

Secondly, it was evident that socio-demographic characteristics influenced spending patterns significantly, confirming the notion that, in general, education (Snowball & Willis 2006), income (Saayman & Saayman 2006b; 2011), age (Kruger 2010), travelling distances (Pouta et al. 2006), length of stay (Thrane 2002) and being a foreign tourist (Saayman & Saayman 2006b) influence bigger spending, as indicated in the literature review. This research found that big spenders were neither engaged nor married, were better qualified, self-employed or in a professional occupation (earned more) and were male. The latter finding contradicts the research of Craggs and Schoffield (2006), who indicated that females were bigger spenders. These characteristics in themselves represent a specific group of tourists with particular preferences.

Thirdly, and significant to this research, spending was directly related to the type of attraction visited. Significantly more money was spent by those who visited national parks, the Garden Route, the Winelands and the Cradle of Humankind. The unique selling point of South Africa remains the natural attractions. It might also be that these attractions offer opportunities to spend and tourists are then willing to do so. One of the reasons why nature-based tourists spend more is because of the cost involved in staying at some of the lodges, which are extremely expensive but offer very unique experiences. Results on the motives of visitors and tourists also showed that 49% travel primarily for holiday purposes.

Fourthly, as the key finding of this research, two distinct markets were identified. This confirmed the notion that a combination of three markets exists, namely high, medium or low spenders (Spotts & Mahoney 1991). In this case, they were labelled average and big spenders. The importance of big spenders, as well as the relationship between this group of tourists and their attraction preferences, is evident. Big spenders spend significantly more (52.4%) than the average spenders, thereby increasing their appeal as a lucrative market for South Africa. An increase in the number of big spenders can have a significant economic impact, which from a poverty-alleviation point of view would be extremely beneficial to the country’s economic growth plan.

Practical implications

The first implication is that the big spenders have been identified and they should be the key target market if the South African tourism industry is focusing on generating more income from fewer tourists as indicated in the literature review.

The second implication is that marketing efforts should be directed at the high end of this market through direct and personal strategies showcasing these popular attractions and added value and changes or modifications to the attractions that will encourage first-time and/or repeat visitation. Marketing using Twitter and LinkedIn is therefore advised, with personalised messages and loyalty options.

The third implication is that tourism development should follow an ‘all-in-one’ approach providing for accommodation, restaurants, entertainment, souvenirs and unique elements that tourists want to experience and that provide the opportunity to spend money. In addition it remains paramount that tourism products need to ensure that they fulfil the needs of their visitors.

Lastly, for a country battling with high unemployment and high levels of poverty, it has become paramount to follow a more focused marketing approach. A two-pronged approach is therefore advised. In the first instance, a marketing focus on the big spenders is important, as their value lies in spending, and in the second instance the average spenders should be maintained, as their value lies in volume (number of average spenders).

Limitations and recommendations

The greatest limitation to this research is the fact that because of financial constraints only one survey could be conducted. A few such surveys over a period of a year might give different markets. It is recommended that one survey per quarter be conducted in order to get a comprehensive view of the spending behaviour of international tourists.


It was the aim of this innovative study to apply expenditure segmentation to international visitors to South Africa, focusing on the key attractions that these tourists visited. The analysis revealed two significant groups, namely big spenders and average spenders. Big spenders spend significantly more than average spenders, which makes them a lucrative market, even though they are few in numbers. Opportunities for growing this group of tourists are evident, and tourism destination marketers should make an effort to focus on this segment. The average spenders create a demand stream to South Africa that should be nurtured, as they carry the industry with a constant income stream. Big spenders preferred nature-based attractions where there were opportunities to spend money.

This article makes an important contribution, as it is one of the first to use key attractions as variables in expenditure-based segmentation. It is also the first time that such a study has been undertaken in South Africa, focusing on international tourists and their spending behaviour using primary data. Not only are spending markets identified, but the importance of attractions and how this influences spending behaviour are also highlighted. From a management and marketing point of view, this type of analysis is extremely useful and gives researchers and managers greater insight into the economic significance of different attractions and tourists’ spending patterns or behaviour.


The views and opinions expressed in the article are those of the authors and not of any of the reviewers or of any specific institution.

Competing interests

The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this manuscript.

Authors’ contributions

A.F. contributed to the literature review and statistical analysis. M.S. contributed to the introduction, literature review, findings and implications. E.S. contributed to the literature review, developed the questionnaire and managed the survey.


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