Original Research

The effect of income on the relationship between travel motives and destination choices

Jarè Struwig, Elizabeth A. du Preez

Received: 18 Aug. 2023; Accepted: 26 Feb. 2024; Published: 23 May 2024

Copyright: © 2024. 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.

Abstract

Background: Studies investigating the relationship between travel motivations and destination choice are often unidimensional and hierarchical, presenting limited perspectives on traveller groups with diverse socioeconomic backgrounds.

Aim: This study investigates the variations in travel motives versus destination choices given different income bands. It presents a nuanced profile of income group members based on socio-demographic variables and travel experience.

Setting: South African domestic tourism.

Method: Threshold regression was applied to determine whether 13 motivations changed toward six destinations given specific income levels. Data from the 2019 South African Social Attitudes Survey (SASAS) were used and the weighted sample represented 42 573 093 South Africans.

Results: The threshold regression materialised with between four to six breakpoints for most destinations. Fun dominated as a motive among lower income groups, as opposed to relationship building for higher income groups. Relaxation, as a known core travel motivation, did not lead to varied interest in specific destinations. Apart from motives, race and travel experience produced several significant differences.

Conclusion: Income thresholds meaningfully explain variations in the relationship between travel motivations and destination choice. More effective marketing strategies should be built around travellers within overlooked markets.

Contribution: The study provides novel empirical evidence that destination choice is non-linear and multifaceted. It applies threshold regression that has not been used in destination choice studies. Finer nuanced segments are identified and suggest an amendment to the travel career pattern (TCP) to accommodate developing and emergent travellers.

Keywords: push factors; threshold regression; travel career pattern; destination choice; travel motivations; socioeconomics.

Introduction

Tourist behaviour is a broad study field with decision-making and specifically destination choice being the most frequent topic of investigation. It has gained significant attention since its initial conceptualisation in the early 1990s (Pandey & Joshi 2021; Saito & Strehlau 2018), and the context in which motivations were investigated shifted from a focus on tourism attractions and ‘hardware’ to tourists’ destination choice decisions (Crompton & Petrick 2024). It is a complicated process with several variables at play (McKercher et al. 2021) and different theories and models have been used to explain destination, including the tourism consumption system, theory of planned behaviour, structure and process modelling, consumption value theory, and decision-making styles (Pandy & Joshi 2021). The most frequently applied theory is Decrop’s (2010) choice set theory (Saito & Strehlau 2018) and modelling (Pandey & Joshi 2021). This theory stipulates that destination choices are essentially narrowed down among various alternatives in a funnel-like manner, progressively eliminating destination choices during core stages (Karl, Reintinger & Schmude 2015; Saito & Strehlau 2018). Despite this topic being studied intensively, an area that is under-researched is the positioning of destinations relative to others (Pike 2017). Furthermore, it is often assumed that destination choice is hierarchical, sequential and multi-staged; and while investigating it as non-linear, multifaceted decision-making is lacking (Pandey & Joshi 2021).

One of the conceptual frameworks in tourism research offering a holistic approach to travel behaviour is the push and pull framework (Wangari 2017), and has been applied extensively to study destination choice (Pandy & Joshi 2021; Pestana, Parreira & Moutinho 2020). Dann (1977), Crompton (1979) and Plog (1974) were prominent scholars that linked push and pull factors and conceptualised the dual nature of travel motivation; namely that people are pushed to participate from internal imbalances and pulled by the offerings of a specific destination. Crompton’s (1979) study was specific in establishing that general, non-destination-specific push motives are often the major driving forces in a person’s selection of not only when, but also where to travel. This essentially concretised the link between push and pull factors and triggered a voluminous number of publications attempting to not only understand reasons and motives why people travel, but also why people travel to certain destinations (Pearce 2021; Pestana et al. 2020). As literature developed, push factors became known as personal intrinsic motivation factors, while pull factors were considered as extrinsic or external, linked to a destination or activity (Pereira & Gosling 2019). While the theory has been applied widely, it has been critiqued for limited measurement of the motivation dimensions and not clearly distinguishing between what constitutes ‘push’ and ‘pull’; where push factors are based on psychographic measures and pull factors are the ‘hardware’ (attractions, infrastructure, facilities) at the destination (Crompton & Petrick 2024).

The interdependence of push and pull factors has been investigated through a variety of methodologies (Katsikari et al. 2020; Pandey & Joshi 2021; Pestana et al. 2020) This article is therefore not unique in its attempt to study the relationship between travel motivations and destination choice. However, it attempts to determine how certain push motives change for specific destination choices considering income as a significant determinant of destination selection (Batabyal & Yoo 2020). Income has been cited as one of the most important barriers to travel, especially in developing countries (De Almeida & Kastenholz 2019; Rogerson 2020; Scott & Lee 2018; Stodolska, Shinew & Camarillo 2019). Studies by Dzikiti and Leonard (2016), Butler and Richardson (2015), and Ezeuduji and Dlomo (2020b) confirm the importance of financial constraint and identify it as the main constraint to travel patterns in developing countries such as South Africa and Kenya. Stodolska et al. (2019) showed that a lack of resources, specifically among marginalised ethnic and racial groups, leads to lower access to, and interest in certain leisure activities. Although travel motivation, destination choices and income are inevitably linked and important components of travel decision-making (Küçükergin et al. 2021), studies in tourism mostly tend to examine these factors on a unidimensional basis and do not explore nuances between shifts in motives per destination, given different income levels. Understanding how these components influence each other and impact travel intention is, however, critical if the aim is to grow tourism (Xie & Ritchie 2019).

A comprehensive study on tourism demand research by Song, Qiu and Park (2023) indicated that tourism demand warrants further investigation from a micro (individual level) and behavioural economic perspective to increase our understanding of demand determinants. The most important variables used include age, income, and previous visits (travel experience), while psychographic variables such as motivations feature minimally. Overall, demand studies popularly investigate relationships using econometric models and structural equation modelling (SEM) (Song et al. 2023) to test relationships. A great number of econometric tourism studies use threshold regression (TR) as a dynamic non-linear measurement at macro level, for example tourism and environmental performance (Lv & Xu 2023), the effect of a tourism niche market on economic growth (Tang 2021), the influence of globalisation on inbound tourism (Chiu, Zhang & Ding 2021), and tourism destination growth stage and economic growth (Sahni, Nsiah & Fayissa 2023). The authors of this study were not able to identify any studies at microeconomic level (behavioural) that apply this method. At the same time, studies on destination choice also include a wide range of popular methodologies to test relationships, including regression (simple; multiple; conditional, binomial, binary and multinomial logit), SEM, and correlations. A great number of studies use factor and principal component analyses along with group comparison analyses (analysis of variation [ANOVA], multivariate ANOVA [MANOVA], chi-square, t-test, cluster analyses) to identify different segments (review provided by Pandey & Joshi 2021). Considering the review (Pandy & Josh 2021) as well as the authors’ review of literature, to the authors’ best knowledge, no studies have used TR to measure destination choice.

Destination choices, as dependent variable of the study, consisted of interest in the beach, museums, art galleries or historical buildings, nature reserves, religious gatherings, and visiting friends and relatives (VFR). These destination choices were chosen for a variety of reasons. Firstly, they covered the inclusion of man-made, natural, and cultural features. Secondly, they eliminated spatial consideration and lastly, these destinations were sufficiently general for all people to understand and covered both popular and less popular destinations (McKercher et al. 2021). They also represented the four needs-family product taxonomies as specified by McKercher (2016); namely pleasure, personal quest, human endeavour and nature. Travel motives (independent variable) were based on Pearce and Lee’s (2005) widely applied travel career pattern (TCP) (McKercher 2021; Yoo, Yoon & Park 2018).

This study aims to determine whether and how income, as a key determinant of travel choices, may influence the relative importance of certain motivations in the destination choice process of travellers from different income groups. It moves away from studying these factors on a unidimensional basis. By applying a non-linear TR analysis, it provides finer nuances between shifts in motives per destination. It also incorporates socio-demographic variables and travel experience to describe the group members. It contributes to furthering of further academic work on the position of motivations in different destination settings (McKercher & Tolkach 2020). The next section presents an overview of travel motives as categorised by the travel career ladder (TCL) of Pearce and Lee (2005). This is followed by an outline of the research methods and presentation of results, focussing on the threshold analysis for each destination.

Travel motives and destination choice

Travel motivations are dynamic and subject to change depending on factors like life stage, psychographics, travel experience, and socio-demographic characteristics such as income and education (McKercher 2021; Pearce 2021; Yoo et al. 2018). Motivations feature at various levels within different segments (Pestana et al. 2020; Song & Bae 2018). Studies tend to focus on describing and modelling motives within a destination rather than determining the varying degrees of the significance of motives and which factors influence the weights of these motives (McKercher et al. 2021). A more nuanced approach to analysing the link between motive and changes in motives is warranted, as it may uncover subtle differences in behaviour patterns, thereby enabling destination management organisations to refine their marketing strategies more effectively. For this reason, McKercher et al. (2021) go so far as to state that in-destination research on motives might be flawed given that methodologies often involve tracking behaviour, making false assumptions about motives. They therefore make a plea for a more refined approach to understanding travel motives.

Most of the existing studies that attempted to study push factors alone or in combination with pull factors, use motives that are closely aligned with the motives identified in the TCP. The TCP of Pearce and Lee (2005) is derived from the work on the TCL (Pearce & Caltabiano 1983), which categorised travel motives according to Maslow (Pearce 2021). The TCP framework is a means to segment tourists (Song & Bae 2018; Yoo et al. 2018). This framework proposes to offer a comprehensive understanding of travel motives (McKercher et al. 2021) and identifies 14 major motive categories, grouping them into core, middle, and outer tiers.

The core motives are the most important or backbone and most common, regardless of travel experience. The middle layer motives are moderately important and change from inner directed to outer directed travel motives as people become more experienced travellers. The outer core consists of fairly common travel motives, which can be considered as less important. Because this study employed the TCP framework of motives as independent variables, it is critical to understand the different motives in more detail.

The core or dominant travel motives identified by the TCP are novelty, relaxation and/or escape (these are considered as one motive in the TCP) and relationships. The core motive of novelty includes statements such as having fun and experiencing something different; feeling the special atmosphere of the vacation destination; and visiting places related to personal interests. The dominant motive under novelty is fun, and Dann (1977) initially identified this as critical using the term ‘anomie’, implying the need to get away from ultimate boredom. The importance of novelty as a motive has been confirmed as a central travel motive (Song & Bae 2018; Katsikari et al. 2020; McKercher et al. 2021). Another core motive initially identified by Pearce and Lee (2005) was the relaxation and/or escape motive, implying the need for resting and relaxing, getting away from everyday physical and psychological stress/pressure, being away from daily routine, and not worrying about time. In particular, sunny weather, warm temperatures, quality of the beaches, and water-based activities seem to be major pull factors associated with escape and relaxation (Kassean & Gassita 2013; Khuong & Ha 2014; McKercher et al. 2021). A third element identified by Pearce and Lee (2005) as core was building relationships. People travel to build new and strengthen current relationships. Statements included doing things with my companion(s) or doing something with my family/friend(s). Researchers agreed with Pearce and similarly identified relationships as a key motive (Ezeuduji & Diomo 2020a: Song & Bae 2018). Building relationships has been closely linked as a motive for VFR (McKercher et al. 2021). In addition, Wu et al. (2019) and Pestana et al. (2020) found that despite changes across life stages (getting older), building relationships remains important as a push factor. This corroborates the TCP which states that relationship building remains a core motive, despite travel experience.

Turning to middle layer motives, a motive considered as important was self-development, which was classified into two categories, namely personal development and host-site involvement. Both of these constructs belong to perceived meaningfulness which forms a key component of memorable tourism experiences (Chandralal & Valenzuela 2015). Personal development includes being able to enhance intellectual capacity and broaden perspectives. Relationship development includes not only existing bonds, but also new friendships through interaction with locals. Personal development tends to be emphasised more by people with low travel experience (Wu et al. 2019) and involves statements such as developing personal interests; gaining a sense of accomplishment; gaining a sense of self-confidence; and developing skills and abilities. The motive of self-development has also been attached to beach visits (McKercher et al. 2021). Travel motives reflecting self-development through host-site involvement, such as experiencing different cultures and meeting the locals, as well as feeling secure in terms of being among hosts, form part of the middle layer motive associated with highly experienced travellers. These high order motives were also seen as important by other authors (Wangari 2017; Yousaf, Amin & Santos 2018). The motive of self-actualisation consists of motives such as gaining a new perspective on life, doing things that are important, as well as feeling inner harmony and peace. Self-actualisation is attached to various destination choices in the literature. Nikjoo and Ketabi (2015) and Kassean and Gassita (2013) showed that this motive was closely related to a need to visit cultural destinations, while it has also been linked to an interest in nature reserves (Khuong & Ha 2014; Kruger & Saayman 2010; Song & Bae 2018). Kassean and Gassita (2013) and McKercher et al. (2021) found this motive associated with a preference for beach activities. The middle layer motive of nature, which includes the motives of being close to nature and appreciating the scenery was associated with more experienced travellers. As could be expected, the motive of seeking solitude in nature was associated with wanting to visit nature destinations (Carvache-Franco, Segarra-Oña & Carrascosa López 2019; Ma et al. 2018). Nature was also associated with beach and cultural activities (McKercher et al. 2021).

Autonomy, stimulation, isolation, recognition/self-esteem, nostalgia, and romance are outer layer motives that were less frequently mentioned. Autonomy includes motives such as being independent; being obligated to no one; and doing things my own way. It was especially applicable to young travellers (Sparks & Pan 2009) and less experienced travellers (Huang & Hsu 2009). Stimulation was expressed as a travel motive by low experience travellers and included exploring the unknown; feeling excitement; having unpredictable experiences; having daring/adventuresome experiences; experiencing thrills; and experiencing the risks involved. This motive was linked to first time travellers and linked to beach activities and culture (McKercher et al. 2021). Isolation covered statements such as experiencing peace and calm; avoiding interpersonal stress and pressure; and experiencing open spaces. This motive is also deemed as an important motive by Kassean and Gassita (2013), Song and Bae (2018) and Wangari (2017), and has been associated with beach (McKercher et al. 2021). Recognition or ego enhancement included sharing skills and knowledge with others, as well as being recognised by other people. It has been associated with natural and historic environments (Mohammad & Som 2010), culture (Yousefi & Marzuki 2012), beaches and culture (Kassean & Gassita 2013), and beaches, culture, nature and historical sites (McKercher et al. 2021). The motive of nostalgia included thinking about past good times, and romance included statements pertaining to having romantic relationships (McKercher et al. 2021; Song & Bae 2018).

From the description above, studies have been undertaken that link motives and specific destinations. These studies are useful to gain insight into the relationship between push and pull factors. Although the research examined whether and to what degree particular sets of destinations are associated with push motivation, no research has been done which explores the nuances between change in motives, given certain structural changes, such as income. As McKercher et al. (2021) rightly maintain, all motives might play a role in the travel decision process, but the weight of each motive for different destinations and trips varies. Recent critique by Crompton and Petrick (2024) similarly argues that the motive construct is so diverse and variable that it cannot be generalised through hierarchies.

Research methodology

Sampling and data collection

The study is based on quantitative data. A module of questions on travel motivations and travel destination preferences was included in the South African Social Attitude Survey (SASAS) in 2019. The SASAS is a cross-sectional survey which is conducted annually by the Human Sciences Research Council (HSRC). The SASAS infrastructure allows for the inclusion of modules of question on different topics in its annual survey rounds. It is based on a nationally representative sample of 3500 adults aged 16 years and older, living in private residences. In 2019, a total of 2844 people, 16 years and older (81% response rate) completed the survey and when weighted, this total represents 42 573 093 South Africans. The sample uses small area layers (SALs) as primary sampling units and the estimated number of dwelling units (households) is the secondary sampling units. In the first sampling stage, the primary sampling units are drawn with probability proportion to size. In the second sampling stage, a predetermined number of households are drawn with equal probability. Finally, in the third sampling stage, a person is drawn with equal probability from all persons 16 years and older in the drawn dwelling units.

Prior to a module being included in the survey, it is piloted and tested to ensure the validity of the instrument. The questionnaire is translated into the country’s major official languages and the surveys are administered in the preferred language of the respondent. The method of data collection is face-to-face interviews. The research project was approved by the HSRC’s Research Ethics Committee (REC 5/17/08/11) which is registered with the South African National Health Research Ethics Council of the South Africa National Department of Health (NHREC No 290808-015) and has US Office for Human Research Protections Federal-wide Assurance (FWA) accreditation (FWA 00006347, IRB No. 00003962). All participants provided verbal consent to be involved in the study.

Dependent variables: Destination choice

The dependent variables included in the study were five destination choices, which are the beach, VFR, religious gathering, museums, art gallery or historical building, and nature reserves. This study attempted to be inclusive by determining travel motives across a broad range of income categories, including those belonging to lower income categories. The questions were also designed to ask about interest in destinations rather than actual travel to destinations. This allowed for lower income earners to also participate, given that they might never have travelled to certain destinations. Respondents were asked to indicate how interested they were in each of the stated destination choices. The specific questions were phrased as: ‘How interested are you in the following activities’? The activities were listed, and respondents had to indicate on a scale from 1 = ‘Very interested’; 2 = ‘Fairly interested’; and 3 = ‘Not interested’. In the analysis, the scales were reversed for a high score to denote high interest. ‘Don’t know’ responses were recoded as missing. The destination choices included were the beach, visiting friends and family, both part of the pleasure domain as per the taxonomy of McKercher (2016). Religious sites was included because it is part of the personal quest domain of McKercher (2016). Museum, art gallery or historical building formed part of the human endeavour domain and nature reserves represented the nature domain of McKercher (2016).

Independent variables: Motives, socio-economics and travel experience

The threshold variable used was a banded income variable and respondents had to indicate which category best described their total monthly income before tax and other deductions. They were asked to consider all sources of income, i.e. salaries, pensions, income from investments, and other relevant sources.

The income categories were as follows: No income = 1; R1–R500 = 2; R501–R750 = 3; R751–R1000 = 4; R1001–R1500 = 5; R1501–R2000 = 6; R2001–R3000 = 7; R3001–R5000 = 8; R5001–R7500 = 9; R7501–R10 000 = 10; R10 001–R15 000 = 11; R15 001–R20 000 = 12; R20 001–R30 000 = 13; R30 001–R50 000 = 14; R50 000+ = 15. For the analysis, the midpoint of the categories was used as a scale variable.

Motives for travelling (independent variables) were based on the TCP motives (Pearce & Lee 2005). A list of motives as per the TCP was given to the respondents and they were asked the following question: ‘Are any of the following important reasons why you go on holiday?’ This was a multiple response question, and they could indicate more than one motive. The motives included having fun; relaxing; building relationships; being in nature; self-development (host-site); self-development (personal); self-actualisation; stimulation; isolation; nostalgia; romance and recognition. In order to test these motives in a questionnaire, a statement testing each motive had to be included. Pearce and Lee (2005) had a few statements measuring each motive, but for this study only one statement per motive could be included. The statements that were selected were those that were most popular at measuring the specific motive in the TCP. For this study, more colloquial terminology was used to describe the various motives of the TCP. Table 1 specifies the terminology used in this article.

To juxtapose socio-demographics against these motives, selected socio-demographics were included, because it is well-known that they are important variables that impact destination choice (Karl et al 2015; Kasim et al. 2013; Uvinha et al. 2017). These were gender, age (continuous), education level (no or primary school, secondary school, Grade 12, tertiary), race (Black African, Coloured, Indian/Asian), labour market status (employed/have worked/never worked), and travel experience (number of trips as continuous variable). Education level influences travel motivations and tourists’ evaluation of destinations (Ma et al. 2018). Age is a discriminating demographic variable, influencing tourism preferences (Tomić, Leković & Tadić 2019; Wangari 2017). Travel experience might lead to a preference for more specific destinations (McKercher & Tolkach 2020; Song et al. 2023) and increases the intention to travel among existing travellers more than it does among non-travellers (Karl et al. 2020). Neglecting distinctions between racial and ethnic groups hampers efforts to understand more refined patterns of participation in tourism, including how members evaluate, avoid, and decide on host destinations (Benjamin, Dillette & Robinson 2022; Liu et al. 2018).

Data analysis

One of the most interesting forms of non-regular regression models is the TR model – a technique widely used in economics, econometrics, and biomedical fields. The attractiveness of this model stems from the fact that it treats the sample split value (threshold parameter) as unknown. That is, it internally sorts the data, based on some threshold determinant, into groups of observations, each of which obeys the same model (Fong et al. 2017).

Threshold regression models are thus a class of regression models, where the predictors or independent variables are associated with the outcome in a threshold-dependent way. By introducing such a threshold parameter (or change point), different kinds of non-linear relationships between the outcome and a predictor can be modelled. The discrete TR model includes a simple form of non-linear regression, featuring piecewise linear specifications and regime switching that occur when an observed variable crosses unknown thresholds or change points (Bai & Perron 2003; Hansen 2001; Perron 2006). These TRs are popular because they are easy to interpret and provide an interesting way to model non-linear relationships between an outcome and a predictor (Fong et al. 2017). EViews (IHS Global Inc, Irvine, CA, USA) was the software used to undertake this analysis and does not make use of the fixed regressor bootstrap testing proposed by Hansen (1999). It uses the methods proposed by Bai and Perron (1998) to test for the presence of multiple structural changes and to determine the number of thresholds, the R-square, the F-statistic, and the corresponding probability which are all based on a comparison with the fully restricted, no threshold, constant only model.

Results

The results of the TR for each of the destinations are provided in Table 2 (beach, VFR, religious gatherings) and Table 3 (museums, art gallery or historical buildings; nature reserves). The columns within each destination choice indicated the thresholds (change points) as determined by the threshold analysis. The rows are the motives for travel as per the TCP (Pearce & Lee 2005). The regression coefficients are indicated in the cells, as well as the statistical significance, indicated by p values.

Interest in the beach

Interest in going to the beach was investigated and five income breakpoints were found, based on the TR, namely less than R875 per month, R875–R2499 per month, R2500–R6249 per month, R6250–R17 499 per month and those earning R17 500 and more per month (refer to Table 2 and Figure 1). Given that different breakpoints were identified, it is evident that income plays a role in the relationship between the independent variables (motivation and demographical characteristics) and their interest in the beach.

FIGURE 1: Interest in beach by income threshold.

When investigating the differences in core motivations per threshold grouping, it is noted that for the lowest threshold group, in other words those earning less than R875 per month (15% of the sample), fun and self-development (personal) were two statistically significant motives in increasing interest in going to the beach. For the next income threshold group (R875–R2499) (26%), being independent, thus ‘doing things my own way’ (autonomy), having fun and exploring the unknown (stimulation), were statistically significant. A further quarter of the sample (24%) formed part of the next income threshold group (R2500–R6249) and revealed that the motives of being in nature, sharing skills and knowledge (recognition), having fun, experiencing peace (isolation) and exploring the unknown (stimulation), were statistically significant. The next income threshold group (R6250–R17 499) (20%) showed that nature and experiencing peace (isolation) were statistically significant. Among the highest earning group (more than R17 500) (16%), being in nature and the relationship motives were statistically significant.

In terms of socio-demographic variables, education was a significant predictor of interest. This association was positive, implying that those with a primary, secondary, or tertiary education were more interested in the beach than those with no or primary schooling. In terms of variation in race groups, it was found that the coloured ethnic grouping showed a significantly higher interest in going to the beach than other race groups, among those earning less than R875 per month and those earning between R6250 and R17 499 per month. Among those earning R875–R2499 per month, the number of times a person had been on holiday was positively associated with being interested in visiting the beach.

Interest in visiting friends and relatives

Interest in VFR found four income breakpoints based on the TR, namely less than R875 per month (15%), R875–R2499 per month (26%), R2500–R17 499 per month (44%) and R17 500 and more per month (16%) (refer to Table 2 and Figure 2). Given that these breakpoints were identified, it is evident that income plays a role in the relationship between motivation and demographics, as well as an interest in VFR.

FIGURE 2: Interest in visiting friends and relatives by income threshold.

When investigating the differences in core motivations per threshold grouping on interest in VFR, it is noted that for the lowest threshold group, in other words those earning less than R875 per month, reminiscing about the past (nostalgia) was negatively associated with VFR. For this income group, the motive of reminiscing about the past therefore decreased the desire for VFR. For the second income TR (R875–R2499), building relationships, nature and sharing skills and knowledge (recognition) were motives that were statistically significantly associated with an interest in VFR. In this income group, the motive of seeking romance was negatively associated with interest in VFR. The third income TR (R2500–R17 499) constituted the largest contingent of people (44%) and the motives of being in nature and having fun, appealed to this group and were statistically significant in predicting interest in VFR. For the fourth income TR (R17 500 and more), having fun and building relationships were statistically significant and positively associated with an interest in VFR. In sum, the fun motive, relationship building, and nature were dominant in terms of predicting a preference for VFR.

In terms of socio-demographic variables, among the lowest threshold group, namely those earning less than R875 per month, age was negatively associated with interest in VFR. Youngsters were therefore less inclined to be interested in VFR and white people were also less likely to be interested in VFR than black Africans in this income group. In the R2500–R17 500 group, Indians/Asians showed a statistically significantly higher interest in VFR than the black African majority. Among those earning R875–R2499 per month, the number of times a person had been on holiday was positively associated with being interested in VFR. Travelling for VFR is associated with relationship building, and the need for social interaction and kinship. As a result of migratory patterns instilled during apartheid, many families remain spatially dispersed and VFR continues to be popular especially among the lower income groups.

Interest in religious sites

Interest in religious sites was interrogated and two income breakpoints (thresholds), based on the TR, were found, namely those earning less than R6250 per month (64%) and those earning R6250 and more per month (36%) (refer to Table 2 and Figure 3). Given that these breakpoints were identified, it is evident that income plays a role in the relationship between these identified motivations, demographics, and an interest in religious sites.

FIGURE 3: Interest in religious sites by income threshold.

For those earning less than R6250, the motive of recognition and autonomy was statistically significant and positively associated with an interest in religious gatherings. In the high-income threshold group (those earning R6250 and more), the motive of relationship building significantly increased an interest in religious gatherings.

In terms of socio-demographic variables, gender was statistically significant in both the lower and higher income groups, with females statistically significantly more interested in religious gatherings than males. In the high-income group, age was positively associated with interest in religious gatherings, implying that older people were more interested in religious gatherings. The race variable was statistically significant among the low-income group, with Indians or Asians more interested and white people less interested in religious gatherings than the reference group, namely black Africans. Among those earning R6250 and more, travel experience increased the likelihood of being interested in religious gatherings.

Interest in visiting a museum, art gallery or historical building

Interest in visiting a museum, art gallery or historical building was interrogated, and six income breakpoints (thresholds) based on the TR were established, namely less than R875 per month (15%), R875–R1749 per month (9%), R1750–R3999 per month (26%), R4000–R6249 (14%), R6250–R17 499 per month (20%), and those earning R17 500 and more per month (16%) (refer to Table 3 and Figure 4). Given that these different breakpoints emerged, it is evident that income plays a role in the relationship between the independent variables (motivation and demographical characteristics) and an interest in visiting museums, art galleries and historical buildings.

FIGURE 4: Interest in museum, art gallery or historical building by income threshold.

When investigating the differences in core motivations per threshold grouping on interest in museums, art galleries and historical buildings, it is noted that for the two lowest threshold groups, in other words those earning less than R1750 per month, being close to nature was the motive that discriminated between those interested and those not interested in visiting a museum, art gallery or historical building. Outer layer motives, namely being independent (autonomy), exploring the unknown (stimulation), and sharing skills and knowledge with others (recognition) were the motives associated with greater interest in visiting museums, art galleries or historical buildings in the R1750–R3999 income group. In the R4000–R6249 income group, the motive of sharing skills and knowledge (recognition) was statistically significant and heightened interest in visiting a museum, art gallery or historical building.

Those in the R6250-R17 499 income group who considered middle core motives as important (being in nature, discovering new cultures, gaining a new perspective on life), were significantly more likely to show interest in going to a museum, art gallery or historical building. Among the highest earning group (R17 500 and more), the motive of relationship building was statistically significantly associated with the dependent variables, namely visiting a museum, art gallery or historical building.

Among those earning less than R875 per month, a higher education impacted positively on an interest in visiting a museum, art gallery or historical building. Interestingly, among the highest income group, being a member of the Indian/Asian or white race group was negatively associated with an interest in visiting a museum, art gallery or historical building when compared with the African black majority. Except for the highest income threshold group, travel experience was positively associated with being interested in going to a museum.

Interest in visiting a nature reserve

Interest in visiting a nature reserve was interrogated and four income breakpoints (thresholds), based on the TR, were noted, namely less than R875 per month (15%), R875–R1749 per month (9%), R1750–R12 499 (53%), and those earning more than R12 500 (22%) (refer to Table 3 and Figure 5). Given that different breakpoints were identified, it is evident that income played a role in the relationship between the independent variables (motives and demographical characteristics) and interest in visiting a nature reserve.

FIGURE 5: Interest in nature reserves by income threshold.

When investigating the differences in core motivations per threshold grouping on interest in visiting a nature reserve, it was noted that for the lowest threshold group, in other words those earning less than R875 per month, the motive to be independent and do things my own way (autonomy) was the motive that discriminated between those interested in visiting a nature reserve and those not interested. To view the scenery and be close to nature was the motive associated with greater interest in visiting a nature reserve in the R875–R1749 income group.

In the R1750–R12 499 income group, the motives of being in nature, learning new things and discovering new cultures (self-development: host-site), being independent (autonomy), exploring the unknown (stimulation), and sharing skills and knowledge with others (recognition) were statistically significantly higher among those interested in visiting a nature reserve. This group represents more than a third of the subject and when attempting to grow this market, these motives should be considered in campaigns. Among the highest earning group (more than R12 500), the motives of being in nature and VFR were statistically significantly associated with the dependent variables. Similar motives such as escaping in nature and kinship development, self-actualisation and self-enhancement were also confirmed in literature as to be associated with an interest in nature reserves. As could be expected, the motive to view the scenery and be close to nature was positively associated with interest in nature reserves among most income threshold groups. Relationship building and being close to nature were motivators that were central and statistically significant in predicting interest among specifically, the high-income threshold earners.

In terms of socio-demographic variables, age was negatively associated with interest in nature reserves among the low-income group (earning less than R875) and the group earning between R1750–R12 500, implying that younger people were less interested in nature reserves. This finding is not unexpected, because an interest in nature reserves tends to increase with age, but it is an area that should be focussed on. For most income thresholds, travel experience was positively associated with being interested in visiting a nature reserve.

Discussion

This study determined whether and how income, as a key determinant of travel choices, may influence the relative importance of certain motivations in the destination choice process of travellers from different income groups. By applying a non-linear TR analysis, it provides finer nuances between shifts in motives per destination. It also incorporates socio-demographic variables and travel experience to describe the group members. Table 4 provides a summary of the motives and socio-demographics per destination choice.

For all types of destinations included in the study, the TR analysis materialised, implying that differential income thresholds discriminated when considering motives and socio-demographics for the various destinations. Based on the regression results from this study, the impact coefficients of tourism motivation on destination choice varied between different levels of income, indicating the tourism motives’ changes along with the different incomes. The study provides empirical evidence that tourism motivations are not static for different destination choices but differ for different income thresholds across the board.

Destination preferences differed in the number of breakpoints identified. These breakpoints indicate a change in interest in these destination choices, given the various motives. Not only are the number of breakpoints insightful, but the sizes of these breakpoints are important from a marketing perspective. Marketers can focus on certain income bands which pertain the highest proportion of travellers for that specific destination and concentrate marketing messages on the motives pertinent to that group. Another observation evident from the TR was that between four to six breakpoints were identified for all the destination choices, except for religion. Religious travels are typically associated with novice or low experience travellers, and it seems plausible that destination choices that are enticing to emergent travellers have not been disaggregated into segmented income bands, as a result of universal mass appeal to lower income groups with similar motives.

The first destination choice that was analysed was the beach. This activity falls under the pleasure domain of McKercher (2016), and has proven to be an important motivation for beach destinations (McKercher et al. 2021). At the same time, the threshold analysis revealed that the fun motive was applicable to the lower threshold income earners and not the high threshold income earners. Despite being a core motive as per the TCL, this study showed that the fun motive for beach as a destination did not increase interest universally among all income groups. Among the middle-income threshold groups, the outer core motives, namely seeking peace (isolation) and exploring the unknown (stimulation) were significant. Among the higher income threshold groups, relationship building and being in nature were statistically significant. From these results, it therefore seems that a transition from the fun or pleasure motive to motives associated with autonomy, nature and relationship building is possible with an increase in income. The possibility of a transition of motives as income increases can therefore exist for a specific destination – much like the overall progression of motives on a TCL or TCP. The heightened interest in the beach as a destination among the coloured race group was noted and is potentially a function of cultural proximity and habitus formation, given the group’s geographical proximity to the seaside, as well as close and historical connection with beach areas (Humphreys 2021).

A second destination choice under the pleasure domain was VFR. Visiting friends and relatives is motivated by the need for social interaction and kinship, and it is therefore not surprising that relationship building as a push factor is closely linked to VFR as a pull factor (McKercher et al. 2021; Prayag & Ryan 2011). This study confirmed the importance of strengthening relationships as an important motive for VFR, together with being in nature and having fun. Interestingly, the fun motive, contrary to interest in the beach, was a motive associated with the high-income thresholds.

Turning to religious sites, a destination that was included under the personal quest domain on the taxonomy, two income thresholds were formed. For the lower income threshold group, the motives of seeking independence (autonomy) and sharing knowledge (recognition) were associated with an increase in interest; while in the higher income group, the motive of building relationships was significantly associated with religious travel. The motives for undertaking religious travel therefore differed from the motives associated with travel for pleasure and were directed towards motives associated with autonomy, sharing knowledge and relationship building. Gender was significant in predicting an interest in religious travel, with females more interested in this kind of travel for both income thresholds.

Interest in museums, art galleries or historical buildings represented the human endeavour domain on the taxonomy. Visiting museums has been identified as a higher order need (Pearce & Lee 2005) and in line with this argument, this study showed that motives of self-actualisation, autonomy and sharing knowledge (recognition) were also motives expressed at various income levels for an increasing interest in museums (Nikjoo & Ketabi 2015). The motive of nature was significant in almost all income thresholds pertaining to human endeavour products. The central role that nature plays in motives for these types of destinations in a developing context was also found by Oktadiana et al. (2017). In terms of socio-demographic variables, travel experience was found to positively influence interest in the human endeavour activity of visiting museums, art galleries or historical buildings.

The nature domain on the taxonomy of McKercher (2016) was represented by an interest in visiting a nature reserve. It was not unexpected that the motive of seeking solitude in nature was associated with wanting to visit nature destinations as confirmed by Carvache-Franco et al. (2019) and Ma et al. (2018). Interestingly, as is the case with other destination choices, relationship building was again a significant motive under the highest income group. Given South Africa’s history of discriminatory policies, which precluded the black majority from accessing and visiting nature reserves (Kruger & Douglas 2015), it was interesting to note that race was not found to be a significant predictor of interest in nature reserves in any of the income groups.

Turning to broad observations, a finding that was unexpected was the absence of the motive of relaxation. Relaxation, a core activity according to the TCL, did not significantly increase interest in any of the 12 destination choices included in the study. This is a finding that was also found by Oktadiana et al. (2017), where Western, Malaysian and Indonesian tourists were compared. For the non-Western sample, building relationships, nature and fun were core as opposed to the Western tourist where fun, relaxation and building relationships were most important. Oktadiana et al. (2017) ascribed the absence of the escape motive to being absorbed in the relationship factor, implying wanting to be with others who hold similar views. In the current study, a similar trend was noted, with fun, nature and relationship building being the most popular motives and escape being absent. In the South African case, the absence of escape might be explained by the demographic profile of the population and employment statistics. The motive of escape seems to be associated with a Westernised stressful lifestyle, typically experienced by employed people in careers. In a developing context such as South Africa, the demography reflects a youthful society. In addition, unemployment rates are extremely high, which might explain the absence of the motive of relaxing in generating interest in any of the destination choices. This finding contradicts the TCP which states that the motive of escape or relaxation is a core motive to all travel. Given that this finding seems to resonate with non-Western and developing nations (Oktadiana et al. 2017), it is a finding that needs to be investigated with a view of possibly suggesting an amendment to the TCP to accommodate developing and emergent travellers.

Conclusion

Results from this study pointed to the fact that tourism push and pull factors are complex phenomena. It confirmed that a different set of push factors or motives is at play, given different income thresholds for destinations. The number and magnitude of these thresholds or breakpoints also differ from destination to destination. These breakpoints indicate a change in the weight or significance of motives thus providing a finer segmentation of the homogenous population. Not only are the number of breakpoints insightful, but the sizes of these breakpoints are important from a marketing perspective. Marketers can focus on certain income bands which pertain the highest proportion of travellers for that specific destination and concentrate marketing messages on the motives pertinent to that group.

Apart from showing that the different destinations have different segments, the study also shed light on the fact that different motives are prioritised per income threshold. The motive of being in nature was the motive that was most cited in positively impacting interest in destination choices researched in this study. Promoting this motive generally, is therefore likely to yield the most impact in terms of increasing interest in a variety of destination choices. The motive of having fun was the second highest in discriminating between those interested and those not interested in any destination. It was noted that the motive of fun was especially a significant predictor of interest among lower income groups, eliciting the conclusion that the fun motive should be promoted in marketing campaigns to encourage interest among lower income groups. Interestingly, the motive of relationship building was an important predictor of interest among all high-income groups for all destination choices, except for religious sites.

Despite recognising that prioritisation in motives might exist, studies have primarily focussed on describing and modelling motives within destinations rather than determining the varying significance of motives and the factors influencing their weights (McKercher 2021). This study contributes to understanding the relative importance of motives and how income, for instance, alters the emphasis placed on each motive. It is hoped that this study furthered the body of knowledge around travel motivations in that it illustrated that motives and combinations of motives differ for different income thresholds, and that the relative importance of motives forms distinct groupings considering income. This study also alerted to a possible amendment of the TCP when considering developing or emergent travellers. The absence of the relaxation motive is something that should be investigated in future research, to understand if this motive is absorbed in relationship building or is a feature of a developing society. As stated, it may not be possible to validate the TCP as motives can hardly be placed in hierarchies and be generalisable across individuals (Crompton & Petrick 2024).

To date, the application of a TR methodology in tourism journals on motive and income has not been undertaken, suggesting a unique opportunity for similar investigations to be undertaken in different contexts. Employing this methodology presents a unique opportunity to further explore the dynamics between motives and destination choices across various contexts, countries, and tourist destinations. Such endeavours could shed light on whether the observed findings are context-dependent or universally applicable.

Acknowledgements

The authors will like to extend their thanks to Dr Marthi Pohl for statistical support. They would also like to acknowledge the Human Sciences Research Council for collaboration on the research and making the data available for the research.

This article is partially based on, J.S., the first author’s thesis of the degree of PhD in Tourism Management at the University of Pretoria, South Africa, with supervisor Prof. Du Preez, June 2022, available here: https://repository.up.ac.za/handle/2263/89288.

The authors declare that they have no financial or personal relationship(s) that may have inappropriately influenced them in writing this article.

J.S. was responsible for conceptualisation of the research, developing the methodology, carrying out the research, and writing up the results. E.D.P. acted as supervisor of the study and assisted in this position to conceptualise the study, design the methodology, reviewing and editing.

Data from the South African Social Attitudes Survey (SASAS) were used to complete the first author’s PhD’s studies in Tourism Management at the University of Pretoria. This survey is conducted annually by the Human Sciences Research Council (REC 5/17/08/11).

The authors received no financial support for the research, authorship, and/or publication of this article.

Data that were used for this study form part of the South African Social Attitudes Survey (SASAS). The data are curated and available on the HSRC website https://hsrc.ac.za/special-projects/sasas/

The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of any affiliated agency of the authors, and the publisher.

References