Abstract
Purpose
This study aimed to determine the motivations of a select group of South Africans in terms of their potential engagement with cultural tourism; more specifically, the study set out to show whether these motivations influence the cultural activities that the tourists want to participate in and whether their interest in specific cultural activities determines their destination choices. Furthermore, the mediating role of activities in the relationship between cultural motivations and destination choice was also assessed.
Design/methodology/approach
An online panel survey collected responses from 1,530 potential cultural tourists across South Africa. Hypotheses were tested, using structural equation modelling.
Findings
The results show that tourists' motivations for cultural tourism influence their likelihood of participating in specific cultural activities. Cultural tourism is shown to be influenced by more than learning and includes entertainment, relaxation, novelty and escape dimensions. There also seems to be a difference in the activities engaged in by destination type. For example, tourists likely to take part in indigenous cultural tourism activities are more likely to do so at hedonic destinations.
Practical implications
This paper contributes to the understanding of cultural tourism activities, aiding destinations in attracting cultural tourists. Destinations need to develop activities that match visitor motivations, increase satisfaction and encourage visitors to return.
Originality/value
The paper increases the understanding of cultural tourism in South Africa and underlines the importance of communities in providing distinctive tourism activities. The study also has an important social dimension, highlighting the role of social status in cultural tourism consumption and destination selection.
Keywords
Citation
Douglas, A., Hoogendoorn, G. and Richards, G. (2024), "Activities as the critical link between motivation and destination choice in cultural tourism", Journal of Hospitality and Tourism Insights, Vol. 7 No. 1, pp. 249-271. https://doi.org/10.1108/JHTI-09-2022-0442
Publisher
:Emerald Publishing Limited
Copyright © 2023, Anneli Douglas, Gijsbert Hoogendoorn and Greg Richards
License
Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
Introduction
Since the 1990s, cultural tourism has become a mass phenomenon consisting of several broad sub-divisions such as heritage, arts, gastronomy, film and creativity (Dodds and Butler, 2019). As a result, Richards (2018) highlights the need to understand the practice of cultural tourism, which is directly influenced by available activities, the destinations they take place in and the motivations of the cultural tourists. For instance, typical examples of cultural tourism activities are: art galleries, sites of religious significance, visiting museums and cultural festivals. These have been segmented into different clusters depending on the location/destination (see McKercher et al., 2002). However, cultural tourism has increasingly become activity-driven, and tourists want to participate in dancing and arts and crafts (Richards, 2020). Indeed, Artal-Tur et al. (2018) showed that cultural tourism activities play a critical role in luring long-haul and first-time visitors to destinations. These activities will also vary between tourists primarily motivated by culture and those secondarily motivated (Du Cros and McKercher, 2014).
Given the different motivations present in cultural tourism, the choice of activities and destinations becomes a complex process that is influenced by a broad range of factors (Frías-Jamilena et al., 2019; Gómez et al., 2018; Pestana et al., 2020). In unravelling this complexity, McKercher (2002) foregrounded motives as key to the tourist destination choice and the desired depth of experience. Whereas Karl et al. (2015) see destination choice as based on the outcome of internal or external decision-making processes. Internal factors relate to the personal motivation of the tourists, and external factors involve aspects of the destination, such as which activities are available (Konu et al., 2011). Regarding internal factors, Qiu et al. (2018) refer to destination choice as a psychological process based on a complex interaction between subjective and objective factors when tourists, for example, evaluate and compare destinations. Indeed, Moscardo et al. (1996) state that motivation influences the choice of activities and that tourists will select a destination that provides their preferred activities. This emphasizes the importance of activities in guiding the destination choice and indicates a direct link between travel motivation and activity.
Nevertheless, only some studies have investigated how tourists' motives influence the cultural tourism activities they are likely to participate in and the role of these cultural activities in cultural tourism destination choice. Examples of research that hint at the intersections between motivations, activities and choice of destination include Kim and Lehto (2013) and Mehmetoglu and Normann (2013), these studies investigated the relationships between travel motives and activities, although not in the context of cultural tourism. In contrast, Kim et al. (2008) considered motivations and activities within cultural festival tourism, but not concerning destination choice, while Teye and Paris (2010) investigated all three aspects (activities, motivations and destinations) in the context of cruise tourism but not regarding the relationship between them. Only some studies have considered motivations, activities and destination choice together, making it difficult to establish the relationships between them (McKercher and Tolkach, 2020). Therefore, this paper responds to McKercher and Tolkach's (2020, p. 775) call for further research “to investigate the relationship between travel motives, destination choices and attraction visitation in different settings”.
The setting chosen for the current study of the relationships between motivations, activities and destination choices is South Africa. Cultural tourism is vital for South Africa's tourism economy, where it has been recognized as a vital economic development tool (Mokoena, 2020). Despite the importance of cultural tourism in the global tourism industry (Richards, 2018), it is currently a less prominent tourism product in South Africa, which has an external image as a nature-based or a “sun, sea and sand” destination (Van Dyk et al., 2019). The external image is despite the vast cultural resources spread across the country that are untapped in terms of tourism potential (Saarinen and Rogerson, 2015). Studies have yet to look at the motivations, activities and destination choices of cultural tourists in South Africa.
This study aims to determine the motivations of a select group of South Africans in terms of their potential engagement with cultural tourism; more specifically, the study set out to show whether these motivations influence the cultural activities of tourists and whether their interest in specific cultural activities determines their destination choices. In doing so, the study aims to make the following contributions: (1) to test the importance of Dann's push-and-pull theory in explaining the travel motivations of tourists and their destination decision-making behaviour, with specific reference to South Africans; (2) to provide practical implications to destinations in terms of strategies applicable to specific cultural tourism activities (pull factors) and cultural tourism motivations (push factors) for South Africans tourists; (3) to empirically analyze the relationship between travel motives, attraction visitation and destination choices. This paper is structured into four parts, reviewing the critical literature around cultural tourism in South Africa and the push and pull theory, followed by the methods used in this study, the results and then a discussion on the theoretical and practical implications.
Cultural tourism in South Africa
Southern Africa is endowed with various and diverse indigenous languages, religions, communities, rock art, rural landscapes, ethnic groups, cuisine, museums and vineyards (Manwa et al., 2016). According to Saarinen and Rogerson (2015), the connections between local cultures and tourism and between cultural tourism and local economic growth have yet to be firmly established. This connection is slowly changing as tourists become more aware of the region's cultural resources, and policymakers recognize its importance in tourism development (Saarinen and Rogerson, 2015). In South Africa, several tourism strategies (Department of Tourism, 2011, 2012a, b) have aimed to facilitate the growth of cultural heritage tourism. Consequently, the country is an ideal destination for developing and promoting cultural tourism (Manwa et al., 2016). Indeed, cultural tourism development and marketing are also viable strategies to alleviate poverty and ensure inclusive growth and socio-economic development (Saarinen and Rogerson, 2015). To market cultural tourism effectively, it is important to have insight into the motivations of potential cultural tourists and how these motivations will influence their cultural tourism activities and ultimately determine their destination choice.
Push-and-pull theory
Researchers have used several theoretical frameworks to explain tourist motivation and destination choice, including the theory of planned behaviour and the travel career ladder. The push-and-pull theory is, however, the more widely used. In cultural tourism, the theory has been used to explore visitors' motivations and behaviours in various contexts, such as at pilgrimage centres (Liro, 2021), African villages (Lwoga and Mtura, 2020), indigenous tourism (Chen, 2021) and language tourism (Redondo-Carretero et al., 2017) to name a few. Push factors motivate or spark a desire to travel (Dann, 1977) and can include relaxation, prestige, adventure and self-exploration. Pull factors clarify why tourists want to travel and what type of activity or experience they desire (Ryan, 1991). For example, the specific attributes or features that draw tourists to particular destinations, such as historical monuments, sunshine and sports facilities. Therefore, according to Klenosky (2002), the push factors determine whether one will go, and the push factors determine where one will go. Dann (1977) states that push factors precede pull factors in travel decisions. Therefore, tourists first realize a need for a vacation and then proceed to decide where to go. In this study, the push-and-pull theory is used to explain the motivations of a select group of South Africans in terms of their potential engagement with cultural tourism. Also, whether these motivations influence the cultural activities the tourists want to participate in, and if their interest in specific cultural activities determines their destination choices (see Figure 1).
Hypothesis development
Motivations for engaging in cultural tourism and types of cultural activities
According to the decision-making literature in psychology, behaviour is interpreted in terms of plans and goals (Weber and Johnson, 2009). Motivations are high-level goals that proceed, direct and initiate decisions (Thiene et al., 2017). In tourism, motivation is vital in explaining travel behaviour (Xie and Ritchie, 2019). Various studies have investigated the effect of the tourists' respective motivations on their travel behaviour, yet much less is known about the influence of tourists' motivation on their chosen holiday activities. Uysal and Jurowski (1994) investigated the reciprocal association between pull-and-push factors and discovered that the appeal of pull attributes changes with motivation variations. Mehmetoglu and Normann (2013) found a strong link between travel motivations and activities in the context of nature-based tourism. More specifically, they found “novelty”, “prestige” and “physical activity” to be the primary sources of motivation for participating in safaris, fishing and hiking, respectively. In their study, McKercher et al. (2021) found motives to affect the behaviour of tourists once they arrive at the destination (including the activities they partake in). While Xiao et al. (2015) showed a significant relationship between the travel motivations of students and their activity preferences. For example, if a student is intellectually motivated, he/she will be more likely to participate in activities that provide learning opportunities. Yun et al. (2016) confirmed the links between the preferred activities and motivates of tourists visiting rural destinations. They found that tourists motivated by gaining knowledge and experiencing various ways of life, cultures and history were more probable to prefer activities such as experiencing local lifestyles and cultures and participating in cultural and historical activities. In a cultural tourism context, Kim et al. (2008) found that the motivations of attendees of a Korean cultural festival had a significant effect on the importance that they attached to activities at the festival, while Lee et al. (2002) showed a significant link between participation in cultural activity and two push factors, namely novelty and hedonism. The above discussion clarifies that tourists value activities at a destination, which aligns with the motives that influenced their decision to travel to that destination in the first place (Yun et al., 2016). Therefore, the first hypothesis is (see Figure 1):
Tourists' motivations for cultural tourism influence the cultural activities they are likely to partake.
Cultural activities and destination choice
According to Xiao et al. (2015), tourism activities are vital features of a destination and significant components of any leisure trip. The accessibility and variety of activities can act as a necessary “pull” factor in the destination choice process (Yun et al., 2016). According to Ritchie and Crouch (2003), activities and attractions can reinforce the unique nature of a destination's product appeal and act as the primary motivators for selecting one destination over another. Moscardo et al.’s (1996) activity-based model of destination choice states that tourists will select a destination that provides their preferred activities. For example, Jang and Cai (2002) found that the activities offered at a destination influenced the destination choices of British travellers. In addition, Yun et al. (2016) found that tourists, who were considering a leisure trip to a rural destination, were the least likely to play golf and most likely to be interested in viewing the beautiful scenery. Lee et al. (2002) found that tourists travelling to Asian countries were more inclined to participate in cultural activities than tourists travelling to the United States and Canada. Therefore, we hypothesize that (see Figure 1):
The cultural activities that tourists are likely to participate in influence their likelihood of visiting specific types of destinations.
Motivations for engaging in cultural tourism and destination choice
Travel motivation is a subjective factor that influences a tourist's choice of destination and behaviour (Qui et al., 2018). More specifically, the link between travel motivation and a tourist's choice of destination depends on the benefits a traveller seeks for in a destination (Chen et al., 2021). According to Song and Bae (2018), the travel decision making process could potentially be influenced by all motives, even though the importance placed on each motive might vary. Ward (2014), for instance showed that the seniors market had numerous interests and motives which affected their choice of destinations. Furthermore, Valea et al. (2022) found that outdoor activities, nature, landscape and relaxation are important motivators when selecting rural tourism destinations. In a cultural tourism context, Chang et al. (2020) showed that apart from the desire to experience new cultures, the chance to escape from the daily food routine and gain status among friends were two important motivations for culinary tourists to choose specific destinations. More formally, the following is posited (see Figure 1):
Tourists' motivations for cultural tourism influence their likelihood of visiting specific types of destinations.
Cultural activities as a mediator between motivations for engaging in cultural tourism and destination choice
Insofar we established that tourists' motivations for cultural tourism influence the cultural activities they are likely to partake in (H1) and in turn the cultural activities that tourists are likely to participate in influence their likelihood of visiting specific types of destinations (H2). Therefore, it can be argued that the motivation for cultural tourism is an antecedent of cultural tourism activities, which in turn is an antecedent of destination choice. According to Moscardo et al. (1996) there are several lines of research that propose that activities may offer the link between destinations and travellers. In other words, activities are vital features of a destination, which are assessed by travellers according to their potential to meet needs. Motives can thus be viewed as giving travellers expectations for activities, and destinations can be seen as presenting those activities. In other words, travel motives are related through activity preferences to destination choice (Moscardo et al., 1996). Consequently, the following is hypothesised (see Figure 1):
Cultural activities mediate the relationship between tourists' motivations for cultural tourism and their likelihood of visiting specific types of destinations.
Methods
Data collection
Recruitment of respondents was done using the consumer panel database of a South African market research company during September 2020. According to Cooper et al. (2006) a panel is a group of respondents who have indicated their commitment and willingness to participate in research studies. Approximately 40,000 individuals are included in the database. Specific requirements can be included to recruit respondents, including relationship status, population group, education level and age. The demographic composition of the panel is as follows: 54% female vs 46% male, 62% black African vs 38% non-black. Half are married (50%), and 87% are between 20 and 55. For this study, respondents were invited via email to complete a self-administered questionnaire hosted on the market research company's online server. Thus, a convenience sampling approach was followed. To encourage participation and ensure confidentiality, the email provided respondents with a direct link to the online questionnaire. Respondents could only complete the questionnaire once since each recipient's email address was encoded with a unique identifier. As a screening question respondents were asked whether they had travelled for holiday purposes in the previous 24 months, and if they answered “no”, they were not allowed to continue. In total, 1,530 fully completed questionnaires were collected for further analysis.
Instrument
The questionnaire was developed to identify the motivations of South Africans for engaging in cultural tourism, the cultural tourism activities they were most likely to participate in, their likelihood of engaging in cultural tourism experiences at certain destination types and their demographic characteristics. The scale of Kay (2009) was used to measure motivations for participating in cultural tourism and consisted of 31 items, with a five-point Likert scale ranging from “strongly disagree” (1) to “strongly agree” (5). The likelihood of engaging in specific cultural tourism activities scale (13 items) was developed from the literature (e.g. Croes and Semrad, 2015; Kline et al., 2016; Manwa et al., 2016) and measured on a five-point Likert scale from “very likely” (1) to “highly unlikely” (5). Similarly, the likelihood of visiting specific destination types (10 items) was measured on a scale developed from the literature (e.g. Byun and Jang, 2015; Loda and Amos, 2014), also with a five-point Likert scale from “very likely” (1) to “highly unlikely” (5). The demographic information collected from respondents included age, gender, relationship status and population group. Before distributing the questionnaire, a pilot study was conducted with ten individuals from the target population. According to Leedy and Ormrod (2015) a pilot test should include at least 6 participants. Several tourism related studies (e.g. Kim and Hall, 2022; Labanauskaitė et al., 2020) have used between 10 and 20 participants in their pilot studies. The ten individuals in our study were requested to complete the questionnaire, and a short interview was held with each to assess the questionnaire in terms of readability, clarity, flow and ambiguity. The pilot respondents raised no significant issues.
Data analysis
After measuring the descriptive statistics, three exploratory factor analyses (EFA) were carried out on the motivations, activities and destination-type scales to determine their dimensions. Then, the reliability and validity of the newly identified factors were assessed. Lastly, structural equation modelling was used to evaluate the measurement model in two phases: (1) assessing the validity and reliability of the factors and (2) evaluating structural relationships between the latent constructs (Chin, 2010).
Results
Profile of respondents
Table 1 shows that the sample consisted of 51% females and 49% males. The average age of respondents was 29 years. The population groups were as follows: 67% were black Africans, and 33% were non-black. Respondents were single (65%), and 33% were married or living together. The 2018 domestic tourism survey indicated that 32.5% of adults taking overnight trips were married, 53.5% of adults taking overnight trips were female, 46.5% were male, and 60% were Black Africans (StatsSA, 2020). The responses indicate that our sample broadly reflects the South African travelling population.
Given that cultural tourism is contextual and built on a destination's unique features and activities, the dimensions of cultural tourism motivations adopted from Kay (2009) were investigated by performing EFA. Since the scales measuring cultural tourism activities and destination types were developed from the literature, they were also subjected to EFA. Principal axis factoring as the extraction method with Promax rotation was used, with the criterion of factor extraction based on the eigenvalue exceeding 1.0 (Hair et al., 2010). Based on the eigenvalue criterion, five factors were extracted from the motivation scale that together explained 57.1% of the total variance in the data. The five cultural tourism motivation factors were labelled: learning about the local culture, relaxation and entertainment, social status and recognition, escape and curiosity and experience. Learning about the local culture is an essential motivation for cultural tourism, as highlighted by Falk et al. (2012) as well as Packer and Ballantyne (2016). Relaxation and entertainment are also consistent with other studies (Lwoga and Maturo, 2020). Travel bragging/self-esteem is consistent with our status and social recognition factor and has been identified as an essential motivator for cultural tourism (Özel and Kozak, 2012). Escape and curiosity are additional factors identified before (Chiang et al., 2015; Correia et al., 2013). The fifth factor, experience, is also similar to the existing literature (Chiang and Jogaratnam, 2006). Three factors were extracted from the cultural tourism activities scale, explaining 62.3% of the variance of the data. These factors were labelled: intangible cultural tourism activities, tangible cultural tourism activities and indigenous cultural tourism activities. Two factors were extracted from the cultural tourism destination scale, explaining 52.3% of the data's variance and labelled utilitarian and hedonic destinations, following Byun and Jang (2015). At a hedonic destination, the consumption of the tourism product can be described as fun and sensorial. In contrast, tourism consumption is described as functional, practical and valuable at a utilitarian destination. Per EFA results, several items (namely CTM 9, CTM 14, CTM 28, CTA3 and CTA13) were removed from further analysis owing to either cross-loadings or low factor loading values. The four main hypotheses were divided into sub-hypotheses based on the results of the exploratory factor analysis. The proposed conceptual model, based on the sub-hypotheses, is given in Figure 2.
Validity and reliability
First, the validity and reliability of the factors were tested. Convergent validity was evaluated using composite reliability (CR) and average variance extracted (AVE), while internal consistency (reliability) was assessed using Cronbach's alpha. As is evident in Table 2, the factor loadings for were between 0.321 and 0.916. Tabachnick and Fidell (2014) suggest that factor loadings with an absolute value of less than 0.32 (representing 10% of the shared variance) should be ignored. Cronbach's alpha scores for most factors exceeded 0.70, and the construct CR values were above 0.7. The Cronbach's alpha value for the entertainment and recreation destination factor was 0.676, which according to Nunnally and Bernstein (1994), is still an adequate reliability coefficient for exploratory research. Some AVE values were smaller than the 0.5 benchmarks (Hair et al., 2010), but Malhotra and Dash (2011) argue that AVE is often too strict, and reliability can be established through CR alone. Therefore, the internal consistency and convergent validity of the factors were established. Discriminant validity was evaluated using the heterotrait–monotrait (HTMT) ratio of correlations (Henseler et al., 2015). Table 3 shows that none of the values violated the HTMT 0.85 threshold; therefore, it is clear that discriminant validity is not an issue between the constructs. This study used Harman's single-factor test to detect common method variance (Harman, 1976). A single factor should not account for more than 50% of the variance. Harman's one-factor test found ten factors, with 24.6% of the total variance explained by a single factor, indicating no serious common method bias.
Hypothesis testing
Second, the structural model and hypotheses were examined. The structural model had to be evaluated before testing the hypotheses. We considered a set of fit indices to determine if the data fit the conceptual model to test the research hypotheses. The structural model results indicated standardized weights larger than one between some constructs, often resulting in high multicollinearity between two or more constructs. In this study's model, the constructs “intangible cultural tourism activities” and “tangible cultural tourism activities” displayed the presence of multicollinearity (correlation of 0.92). The model is, however, still acceptable since neither standard regression coefficients nor correlation coefficients are bound by ± 1 (Deegan, 1978, p. 882). One option in such a case is to merge the constructs and treat them as a single construct if theoretically sound, statistically reliable and valid. The researchers decided to do this, with the single construct being “intangible and tangible cultural tourism activities”. The absolute fit of the model was established by calculating the root mean square error of approximation (RMSEA) and the standardized root mean square residual (as it considers discrepancies in approximation).
The Chi-square goodness-of-fit index (CMIN) was also determined (as it is the foundation of most fit indices); however, as CMIN is affected by sample size, the comparative fit index (CFI) and the incremental fit index (IFI) were applied to assess the model's incremental fit (Zeka, 2020). Threshold values suggested by Hair et al. (2010) and Kline (2010) were used to assess the model. The RMSEA value of 0.049 is adequate (Blunch, 2008). The standardized root means squared residual was 0.0464, below the cut-off value of 0.08. The CFI was 0.916, and the IFI 0.916, more than the threshold value of 0.9. Furthermore, it is advised for the CMIN/df to range between 3 and 5. Thus, the value of 4.599 is adequate. In essence, the set of fit indices showed an adequate fit of the data to the model.
Next, the hypothesized relationships in the structural model were assessed (see Table 4) and showed that 16 of the 24 paths were statistically significant (p < 0.05). In terms of the first hypothesis, the results show that learning about the local culture (β = 0.394, p < 0.001), relaxation and entertainment (β = 0.157, p < 0.05) and experience (β = 0.189, p < 0.05) had a statistically significant positive influence on tourists' likelihood of engaging in tangible and intangible cultural tourism activities, whereas status and social recognition (β = −0.130, p < 0.05) had a statistically significant negative influence on tourists' likelihood to engage in tangible and intangible cultural tourism activities. In addition, learning about the local culture (β = 0.510, p < 0.05), relaxation and entertainment (β = 0.131, p < 0.001) and status and social recognition (β = 0.304, p < 0.001) had a statistically significant positive influence on tourists' likelihood to engage in indigenous cultural tourism activities. Regarding the second hypothesis, the results indicate that tourists' likelihood of engaging in tangible and intangible cultural tourism activities influences their likelihood of engaging in cultural tourism experiences when visiting utilitarian destinations (β = 0.558, p < 0.001) and hedonic destinations (β = 0.227, p < 0.001). In addition, tourists' likelihood of engaging in indigenous cultural tourism activities (β = 0.323, p < 0.001) influences their likelihood of engaging in cultural tourism experiences when visiting hedonic destinations. For the third hypothesis the results show that learning about the local culture (β = 0.303, p < 0.001), experience (β = 0.363, p < 0.001) and escape and curiosity (β = 0.121, p < 0.10), had a statistically significant positive influence on tourists' likelihood of engaging in cultural tourism experiences when visiting utilitarian destinations while status and social recognition (β = −0.185, p < 0.001) had a statistically significant negative effect on tourists' likelihood of engaging in cultural tourism experiences when visiting utilitarian destinations. What is more, relaxation and entertainment (β = 0.259, p < 0.001) and experience (β = 0.393, p < 0.001) had a statistically significant positive influence on tourists' likelihood of engaging in cultural tourism experiences when visiting hedonic destinations.
To analyse the mediating effect, the bias-corrected percentile method (with bootstrapping) for the standardised indirect effect was used. A mediation effect is observed when the confidence interval for the standardized indirect effect does not include 0, indicating statistical significance. A complete mediation effect is evident if the confidence interval for the standardized direct effect includes 0, if not partial mediation is evident. Table 5 shows the mediation effect analysis of activities on all motivation paths related to utilitarian and hedonic destinations. First, we observe the complete mediation effect of indigenous cultural tourism activities on the relationships between learning about the local culture and hedonic destinations; status and recognition and hedonic destinations as well as between learning about the local culture and utilitarian destinations and partial mediator between status and recognition and utilitarian destinations. In addition, tangible and intangible cultural tourism activities are complete mediation variables between learning about the local culture and hedonic destinations; status and recognition and hedonic destinations; learning about the local culture and utilitarian destinations as well as relaxation and entertainment and utilitarian destinations. Tangible and intangible cultural tourism activities are partial mediators between relaxation and entertainment and hedonic destinations as well as learning about the local culture and utilitarian destinations.
Discussion and conclusions
Conclusions
Understanding the relationship between activity preference, tourist motivation, and destination choice is critical because, with this understanding, destinations and tour operators can develop products that best meet tourist needs (Xiao et al., 2015). Even so, research on motivations, activities and destination choice is still in its infancy in Africa (Filimonau and Perez, 2018). The purpose of this paper was thus to investigate how the motives of cultural tourists influence the types of activity they are likely to participate in; and how the cultural tourism activities, in turn, influence these tourists' choice of destination. A link was also established between cultural tourism motivations and destination choice, and the mediating role of cultural tourism activities was assessed.
The structural equation modelling results found support for the four main research hypotheses. Regarding the first central hypothesis, the results show that tourists' motivations to participate in cultural tourism influence the cultural activities they are likely to undertake. Three of the five motivators (learning about the local culture, relaxation and entertainment and experience) significantly influenced tourists' likelihood of engaging in tangible and intangible cultural tourism activities. In contrast, social status and recognition showed a negative influence. Therefore, the more important social status and recognition is as a motivator, the less likely tourists are to engage in tangible and intangible cultural tourism activities. Three of the five motivators (learning about the local culture, relaxation and entertainment and social status and recognition) indicated a significant favourable influence on tourists' likelihood of engaging in indigenous cultural tourism activities. According to Smith et al. (2022), the importance of educational experiences has declined for most age groups, while escapism and entertainment have become more critical in cultural tourism experiences. Our study showed the contrary, where escapism and entertainment showed no relationship with tourists' likelihood of engaging in cultural tourism activities.
Interestingly, the more critical social status and recognition are as a motivator, the more likely tourists are to engage in indigenous cultural tourism activities. According to Correia et al. (2016) the choices tourists make may be influenced by the level of status they seek. Just as indigenous cultures worldwide have gained more attention as distinctive cultural entities, tourists who engage with indigenous communities may also feel a sense of distinction. This links to Abascal et al. (2016), who found that tourists engaging in indigenous tourism activities were particularly likely to emphasize learning, authenticity and uniqueness in these experiences (also see Genc and Genc, 2022). More specifically, destinations or attractions that are seen as exotic, uncommon or different offer considerably more chances for travel bragging, which allows travellers to display their perceived social status (Liu and Li, 2021). Indeed, this speaks to indigenous cultural tourism experiences, which allows tourists to display their quest for experiences that are exotic, different or considered unique (Wu et al., 2020). Therefore, seeking status as a motivator for engaging in indigenous tourism activities makes sense.
Related to the second main hypothesis, the results show that the cultural activities tourists are likely to participate in influence their likelihood of engaging in cultural tourism experiences when visiting specific destinations. More specifically, the results show that tourists likely to participate in tangible and intangible cultural tourism activities are likely to do so at any destination. In contrast, tourists who are likely to partake in indigenous cultural tourism activities are more likely to do so at hedonic destinations. In terms of the third main hypothesis, the results indicate that tourists' motivations for cultural tourism influence their likelihood of visiting specific types of destinations, supporting the results of Valea et al. (2022), Ward (2014) and others. More specifically, our results show that experience as a motivator had a significant influence on tourists' likelihood to visit both utilitarian and hedonic destinations. The fourth main hypothesis is also supported, the results show that cultural activities mediate the relationship between tourists' motivations for cultural tourism and their likelihood of visiting specific types of destinations, thereby confirming Moscardo et al. (1996) who postulated that activities offer the link between destinations and travellers. These results have important theoretical and practical implications for cultural tourism research and the development of the cultural tourism industry.
Theoretical implications
Using Dann's (1977) push and pull theory, the study developed a conceptual model exploring the relationships between cultural tourism motivations, cultural tourism activities and types of destinations and more specifically the mediating effect of cultural tourism activities on these relationships. The connection between motivations and activities has received scant attention in the literature. Indeed, according to McKercher et al. (2021) many studies have considered the link between motives and behaviour. However, few have examined the association between travellers' motives and their in-destination behaviour and activities. Our study found five cultural tourism motivations (learning about the local culture, relaxation and entertainment, social status and recognition, escape and curiosity and experience). Theoretically, the study thus improves our understanding of the dimensional nature of tourists' cultural tourism motivations and how they inform tourists' behaviour. Indeed, the results suggest that of the five motivators, “learning about the local culture” is the strongest predictor of the likelihood of engaging in cultural tourism activities (tangible and intangible cultural tourism activities and indigenous cultural tourism activities). Therefore, our study adds to the body of knowledge by confirming the influence of potential cultural tourists' motivations on their likelihood of participating in specific cultural tourism activities.
The limited literature (McKercher and Tolkach, 2020) has opposing findings regarding the relationship between activities and destination choice. On the one hand, Crompton (1979) argued that destination features might have little to no influence on tourists' decision to visit, while Leiper (1990) opined that visitors might be pushed towards attractions by their motivations rather than by the nature of the attraction. More recently, McKercher and Tolkach (2020) began to analyze whether attractions (as the places where activities are undertaken) attract tourists. If so, what role do they play in enticing tourists to visit a destination? Their results suggested that attractions play a role in tourists' destination choices. In line with McKercher and Tolkach's (2020) work, our research provides more evidence of the relationship between activities and destination choice—specifically in cultural tourism. Our results showed that there seems to be a difference in terms of the activities engaged in by destination type. For example, respondents who were likely to participate in tangible and intangible cultural tourism activities were more likely to do so at utilitarian destinations than hedonic destinations. Interestingly, respondents were more likely to engage in indigenous cultural tourism activities at hedonic destinations than utilitarian destinations.
Even though the constructs of motivation, activities and destination choice have been studied before, the relationships between the three constructs still need to be determined. The only study that to date had attempted to understand the relationship between the three constructs was that of Moscardo et al. (1996). Our study contributes to the limited literature on the link between motivation, activities and destination choice by showing significant relationships between cultural tourism motivations and cultural tourism activities. At the same time, significant relationships were evident between cultural tourism activities and types of destinations as well as between cultural tourism motivations and types of destinations. The mediation results also showed that activities are indeed the critical link between motivation and destination choice in cultural tourism. Most of the existing studies on cultural tourism have been site-specific, which makes it hard to generalize the findings to wider areas (Chen and Rahman, 2018). Our study investigates the potential demand for cultural tourism in South Africa nationally by examining the relationships between push-and-pull factors and destination choice and therefore has implications for the broader cultural tourism industry beyond a specific site.
Practical implications
Our results show that motivations influence the activities tourists are likely to engage in; we therefore propose that destination managers collect more information on the motives of their visitors. Most destination managers know the popular attractions/activities at their destinations. However, they often need clarification about tourists' motivations for visiting these attractions/engaging in the activities. According to McKercher et al. (2021) departing visitor surveys conducted by national destination marketing organizations often need more questions on travellers' motives. Adding visitor motivations to such surveys could yield valuable insights into visitor behaviour (McKercher et al., 2021). This finding is in line with Srihadi et al. (2016) and others (Handler and Kawaminami, 2022; Stylidis et al., 2018) in that our study supports the value of market segmentation based on psychographic variables instead of solely relying on demographics. In addition, knowledge about potential cultural tourists' motives is vital in product development and marketing. Managers must understand the motives of their visitors so that they can develop activities that are aligned with these motives. Promotional material should also be developed that links activities with motives. Since our results also demonstrate that activities significantly influence destination choice, the inclusion of specific activities in advertising campaigns should aid in attracting more visitors to a destination.
The results showed five distinct motivations for engaging in cultural tourism activities, of which “learning about the local culture” was the strongest predictor of tourists' likelihood to engage in tangible and intangible and indigenous cultural tourism activities. According to Chen and Rahman (2018), cultural tourists naturally tend to be inquisitive about other cultures. Therefore, cultural destinations/sites should focus on increasing and improving tourists' learning experiences. Learning could be done through the practical interpretation of sites, guided tours, educational sessions and even live entertainment.
The finding that indigenous cultural tourism activities are a distinct type of experience is significant. It has often been noted that indigenous cultures are viewed as a key attraction for tourists and as an essential point of distinction for tourism destinations in an international environment that is becoming increasingly competitive and homogenous (e.g. Fletcher et al., 2016; Richards, 2021). While indigenous cultural tourism is a recognized segment in the tourism industry in South Africa, in light of our findings, more should be done to make domestic and international tourists aware of this segment. To develop a destination's indigenous cultural tourism offering, Pabel et al. (2017) make several suggestions, including making indigenous experiences and artefacts more accessible and available to tourists, creating effective promotional strategies and raising awareness of the diversity of indigenous offerings and including some cultural content in nature-based experiences. Tourists should be actively engaged to improve the learning experience when engaging in indigenous cultural tourism activities. Tourists could participate in workshops where they are taught how to make artefacts, cook traditional meals and learn traditional dances (Fan et al., 2020). Related to this, an interesting result was that respondents were more likely to engage in indigenous cultural tourism activities in hedonic destinations than in utilitarian destinations. Destinations classified as hedonic, thus providing fun and sensorial consumption experiences, should take note of this finding and develop more opportunities for engaging in indigenous cultural tourism activities. The Sun City resort is an excellent example of a hedonic destination in a South African context that has capitalized on this opportunity. Visitors to Sun City Resort are allowed to learn about the diverse heritage and history of the area at Segaetsho Cultural Village – which means “Our Heritage” in Setswana. The village gives tourists an authentic African experience by exploring Batswana culture through traditional dance, food and art, music, fashion and photography (Sun International, 2022).
Our results indicate that cultural tourists are motivated by more than just learning about the local culture. Cultural tourism products should be developed to provide a complex travel experience for visitors, including entertainment, relaxation, novelty and escape. Therefore, cultural tourism providers should combine learning and hedonic-entertainment dimensions, also known as “edutainment” (Geissler et al., 2006). ICTs, such as augmented reality, can assist in personalizing the experience to satisfy the needs of various visitor segments (Etxeberria et al., 2012) and make edutainment possible. As a result, ICTs can enhance the attractiveness of cultural landmarks by helping visitors understand heritage better and enriching the experience (Tscheu and Buhalis, 2016).
Limitations and directions for future research
There are some limitations related to this research. First, we included 13 cultural tourism activities in our study. Even though these 13 items provide a good representation of cultural tourism activities and an excellent foundation to work from, adding a more comprehensive and exhaustive list of activities could yield more variance in the data, which could provide richer results. Second, even though we expressly set out to survey potential cultural tourists, it could be seen as a limitation of the study. Previous studies have shown that intention does not necessarily end in behaviour. As such, it will be valuable for future studies to include actual cultural tourists and their activities in the destination, not only potential tourists. Third, is the use of an online survey. Pan (2010) notes three methodological issues with online surveys, including a declining response rate, the representativeness of online surveys and technological uncertainty. Despite these limitations, an online survey still provides several advantages such as speed of responses, lower costs and interface advantages and was deemed the most appropriate data collection method for this study. The study showed some interesting results regarding the link between cultural tourism activities and destination types. Future research could investigate whether different types of tourists are attracted to different destinations to undertake different activities, which could hold some significant implications for destination marketers.
Figures
Profile of respondents
| Demographic variable | Percentage |
|---|---|
| Population group | |
| Black African | 67 |
| Non-black | 33 |
| Gender | |
| Female | 51 |
| Male | 49 |
| Marital status | |
| Single | 65 |
| Married/living together | 33 |
| Divorced/widowed/separated | 2 |
Source(s): Author's own creation/work
Validity and reliability results
| Measurement and items | Factor loadings | Cronbach's alphas | CR | AVE |
|---|---|---|---|---|
| Cultural tourism motivations | ||||
| Learning about the local culture | 0.850 | 0.844 | 0.521 | |
| CTM 10_To meet locals | 0.547 | |||
| CTM 11_To learn about local culture | 0.842 | |||
| CTM 12_To learn about local history | 0.822 | |||
| CTM 13_To learn about local performing arts | 0.645 | |||
| CTM 15_To enjoy something unique to the destination | 0.407 | |||
| Relaxation and entertainment | 0.839 | 0.836 | 0.391 | |
| CTM 1_To have fun | 0.491 | |||
| CTM 2_To be entertained by others | 0.425 | |||
| CTM 3_To relax physically | 0.858 | |||
| CTM 4_To relax mentally | 0.884 | |||
| CTM 5_To have thrills and excitement | 0.652 | |||
| CTM 7_To do something I want to do | 0.475 | |||
| CTM 8_To do something with my family and friends | 0.426 | |||
| Status and social recognition | 0.821 | 0.817 | 0.530 | |
| CTM 20_To tell my friends and relatives about it | 0.335 | |||
| CTM 21_To enhance my social position | 0.618 | |||
| CTM 25_To gain the respect of others | 0.835 | |||
| CTM 26_To demonstrate my ability to travel | 0.768 | |||
| Escape and curiosity | 0.810 | 0.848 | 0.526 | |
| CTM 16_To have a change from my daily routine | 0.559 | |||
| CTM 17_To forget about the demands of daily life | 0.896 | |||
| CTM 18_To escape into another world | 0.855 | |||
| CTM 19_To satisfy my curiosity | 0.472 | |||
| Experience | 0.859 | 0.815 | 0.411 | |
| CTM 22_To see famous cultural places | 0.595 | |||
| CTM 23_To hear famous local performers/entertainers | 0.750 | |||
| CTM 24_To see famous local shows performed | 0.694 | |||
| CTM 27_To go somewhere safe | 0.444 | |||
| CTM 29_To have a high-quality experience | 0.495 | |||
| CTM 30_To buy goods and souvenirs | 0.502 | |||
| CTM 31_To buy food and drinks to consume at the cultural experience | 0.504 | |||
| Cultural tourism activities | ||||
| Intangible cultural tourism activities | 0.827 | 0.813 | 0.521 | |
| CTA 1_Guided cultural-focused walking tours | 0.499 | |||
| CTA 4_Cultural tours | 0.737 | |||
| CTA 5_Visiting arts and crafts stores | 0.478 | |||
| CTA 6_Attending cultural festivals or events | 0.648 | |||
| Indigenous cultural tourism activities | 0.750 | 0.753 | 0.435 | |
| CTA 2_Township/slum/favela tourism | 0.415 | |||
| CTA 8_Visiting traditional villages | 0.351 | |||
| CTA 9_Homestays | 0.780 | |||
| CTA 10_Medicinal plant tours | 0.424 | |||
| Tangible cultural tourism activities | 0.788 | 0.786 | 0.552 | |
| CTA 7_Visiting museums | 0.483 | |||
| CTA 11_Visiting architectural and archaeological sites | 0.916 | |||
| CTA 12_Visiting historic or heritage sites, and landmarks | 0.673 | |||
| Types of destinations | ||||
| Utilitarian destinations | 0.795 | 0.804 | 0.409 | |
| CTD 1_Adventure | 0.321 | |||
| CTD 4_Countryside | 0.592 | |||
| CTD 5_Cultural | 0.738 | |||
| CTD 7_Mountains | 0.692 | |||
| CTD 8_Nature | 0.773 | |||
| CTD 8_ Wildlife | 0.411 | |||
| Hedonic destinations | 0.676 | 0.700 | 0.411 | |
| CTD 2_City | 0.712 | |||
| CTD 3_Coast | 0.689 | |||
| CTD 8_Sport and recreation | 0.430 | |||
| CTD 9_Resort | 0.583 | |||
Source(s): Author's own creation/work
Discriminant validity of the correlations among constructs
| Learning about the local culture | Relaxation and entertainment | Status and social recognition | Escape and curiosity | Experience | Intangible cultural tourism activities | Indigenous cultural tourism activities | Tangible cultural tourism activities | Utilitarian destinations | Hedonic destinations | |
|---|---|---|---|---|---|---|---|---|---|---|
| Learning about the local culture | – | – | – | – | – | – | – | – | – | – |
| Relaxation and entertainment | 0.719 | – | – | – | – | – | – | – | – | – |
| Status and social recognition | 0.545 | 0.617 | – | – | – | – | – | – | – | – |
| Escape and curiosity | 0.613 | 0.677 | 0.542 | – | – | – | – | – | – | – |
| Experience | 0.705 | 0.758 | 0.743 | 0.732 | – | – | – | – | – | – |
| Intangible cultural tourism activities | 0.536 | 0.484 | 0.306 | 0.378 | 0.448 | – | – | – | – | – |
| Indigenous cultural tourism activities | 0.560 | 0.500 | 0.497 | 0.348 | 0.459 | 0.813 | – | – | – | – |
| Tangible cultural tourism activities | 0.500 | 0.413 | 0.282 | 0.386 | 0.433 | 0.849 | 0.734 | – | – | – |
| Utilitarian destination | 0.609 | 0.563 | 0.379 | 0.511 | 0.590 | 0.566 | 0.539 | 0.595 | – | – |
| Hedonic destination | 0.509 | 0.570 | 0.478 | 0.433 | 0.575 | 0.566 | 0.520 | 0.433 | 0.771 | – |
Source(s): Author's own creation/work
Standardised regression weights and p-values for model
| Hypothesis# | Factors | Standardised regression weights | Decision |
|---|---|---|---|
| H1ab | Tangible and intangible cultural tourism activities ← learning about the local culture | 0.394*** | Supported |
| H1de | Tangible and intangible cultural tourism activities ← relaxation and entertainment | 0.157*** | Supported |
| H1gh | Tangible and intangible cultural tourism activities ← social status and recognition | −0.130*** | Supported |
| H1jk | Tangible and intangible cultural tourism activities ← escape and curiosity | −0.004 | Rejected |
| H1mn | Tangible and intangible cultural tourism activities ← experience | 0.189** | Supported |
| H1c | Indigenous cultural tourism activities ←learning about the local culture | 0.510*** | Supported |
| H1f | Indigenous cultural tourism activities ← relaxation and entertainment | 0.131** | Supported |
| H1i | Indigenous cultural tourism activities ← social status and recognition | 0.304*** | Supported |
| H1l | Indigenous cultural tourism activities ← escape and curiosity | −0.092 | Rejected |
| H1o | Indigenous cultural tourism activities ← experience | −0.157 | Rejected |
| H2ac | Utilitarian destinations ← Tangible and intangible cultural tourism activities | 0.558*** | Supported |
| H2bd | Hedonic destinations ← Tangible and intangible cultural tourism activities | 0.227*** | Supported |
| H2e | Utilitarian destinations ←Indigenous cultural tourism activities | 0.067 | Rejected |
| H2f | Hedonic destinations ←Indigenous cultural tourism activities | 0.323*** | Supported |
Note(s): *Statistically significant: p ≤ 0.10; **Statistically significant: p ≤ 0.05; ***Statistically significant: p ≤ 0.01
#As a result of multicollinearity, the factors “intangible cultural tourism activities” and “tangible cultural tourism activities” were merged and treated as a single construct (tangible and intangible cultural tourism activities) and the hypotheses related to these constructs were consequently restated
Source(s): Author's own creation/work
Mediation effect analysis
| Point estimate | Bias corrected 95% CI | Outcome | ||||
|---|---|---|---|---|---|---|
| Lower | Upper | p | ||||
| Learning→Indigenous CA →Hedonic | Indirect effect | 0.140 | 0.067 | 0.207 | 0.018* | CM |
| Direct effect | −0.060 | −0.240 | 0.084 | 0.391 | ||
| Relaxation | Indirect effect | 0.031 | −0.010 | 0.084 | 0.129 | No mediation |
| Status→Indigenous CA → Hedonic | Indirect effect | 0.092 | 0.051 | 0.170 | 0.006** | CM |
| Direct effect | −0.072 | −0.230 | 0.059 | 0.263 | ||
| Escape→Indigenous CA → Hedonic | Indirect effect | −0.024 | −0.068 | 0.014 | 0.260 | No mediation |
| Experience→Indigenous CA → Hedonic | Indirect effect | −0.053 | −0.149 | 0.007 | 0.080 | No mediation |
| Learning→T&I CA → Hedonic | Indirect effect | 0.085 | 0.048 | 0.147 | 0.007** | CM |
| Direct effect | −0.007 | −0.167 | 0.112 | 0.842 | ||
| Relaxation | Indirect effect | 0.035 | 0.009 | 0.081 | 0.007** | PM |
| Direct effect | 0.225 | 0.062 | 0.399 | 0.008** | ||
| Status→ T&I CA → Hedonic | Indirect effect | −0.025 | −0.049 | 0.000 | 0.044* | CM |
| Direct effect | 0.043 | −0.079 | 0.184 | 0.469 | ||
| Escape→ T&I CA → Hedonic | Indirect effect | −0.004 | −0.036 | 0.039 | 0.995 | No mediation |
| Experience→ T&I CA → Hedonic | Indirect effect | 0.036 | −0.017 | 0.096 | 0.242 | No mediation |
| Learning→Indigenous CA →Utilitarian | Indirect effect | 0.156 | 0.096 | 0.239 | 0.006** | CM |
| Direct effect | 0.148 | −0.014 | 0.315 | 0.066 | ||
| Relaxation | Indirect effect | 0.034 | −0.004 | 0.095 | 0.081 | No mediation |
| Status→Indigenous CA →Utilitarian | Indirect effect | 0.103 | 0.058 | 0.192 | 0.003** | PM |
| Direct effect | −0.288 | −0.452 | −0.186 | 0.005** | ||
| Escape→Indigenous CA →Utilitarian | Indirect effect | −0.027 | −0.079 | 0.016 | 0.317 | No mediation |
| Experience→Indigenous CA →Utilitarian | Indirect effect | −0.059 | −0.155 | 0.006 | 0.072 | No mediation |
| Learning→T&I CA →Utilitarian | Indirect effect | 0.125 | 0.068 | 0.187 | 0.012* | PM |
| Direct effect | 0.179 | 0.048 | 0.328 | 0.010* | ||
| Relaxation | Indirect effect | 0.052 | 0.015 | 0.128 | 0.010* | CM |
| Direct effect | −0.005 | −0.134 | 0.127 | 0.964 | ||
| Status→ T&I CA →Utilitarian | Indirect effect | −0.037 | −0.068 | 0.000 | 0.045* | PM |
| Direct effect | −0.147 | −0.263 | −0.043 | 0.006** | ||
| Escape→ T&I CA →Utilitarian | Indirect effect | −0.006 | −0.049 | 0.048 | 0.995 | No mediation |
| Experience→ T&I CA →Utilitarian | Indirect effect | 0.053 | −0.025 | 0.130 | 0.275 | No mediation |
Note(s): Indigenous CA: Indigenous cultural activities; T&I CA: Tangible and Intangible cultural activities; CM: Complete mediation; PM: Partial mediation; CI: Confidence interval
Source(s): Author's own creation/work
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Further reading
Alegre, J., Cladera, M. and Sard, M. (2011), “Analyzing the influence of tourist motivations on tourist expenditure at a sun-and-sand destination”, Tourism Economics, Vol. 17 No. 4, pp. 813-832.