e-Review of Tourism Research (eRTR), Vol. 16, No. 6, 2019 http://ertr.tamu.edu 567 Tinashe Chuchu University of Pretoria Norman Chiliya University of the Witwatersrand, Johannesburg Richard Chinomona University of the Witwatersrand, Johannesburg Investigating the Impact of Destination Image on Travellers’ Intention to Revisit South Africa: A Case of International Tourists Destination image is widely accepted as an important aspect of successful tourism development and marketing of destinations. This research, therefore, seeks to investigate how experiences at a South African international airport influence travellers' image of South Africa as a tourist destination and their willingness to revisit the country. The study adopted the positivist philosophy, where it was quantitative nature. Participants were randomly selected through convenience sampling on-site at the airport. Findings of the study revealed that cognitive destination image, affective destination image, and conative destination image all have a direct and positive influence on a tourist’s intention to revisit a destination. The main contribution of the study was that cognitive destination image (pre-conceived ideas about a destination) had the most influence on a traveller’s intention to revisit that destination. This implies that tourism organisations and airport management companies in South Africa have to focus more on marketing the country as a travel destination in the home countries of those travellers before they visit South Africa. Keywords: destination, image, marketing, tourism, revisit intention, South Africa Dr. Tinashe Chuchu Department of Marketing Management Faculty of Economic and Management Sciences Lynwood Road, Hatfield, Pretoria, 0002 University of Pretoria Private bag X20, Hatfield, Hillcrest, Pretoria, South Africa, 0028 Phone: +27 12 420 4440 Email: tinashe.chuchu@up.ac.za Dr. Norman Chiliya Marketing Division School of Economic and Business Sciences Faculty of Commerce, Law and Management University of the Witwatersrand 1 Jan Smuts Ave, Johannesburg, 2000 Private Bag 3, Wits, 2050, Johannesburg, South Africa Phone: +27 11 717 8063 Email: norman.chiliya@wits.ac.za http://ertr.tamu.edu/ mailto:keith_brown@cbu.ca mailto:keith_brown@cbu.ca e-Review of Tourism Research (eRTR), Vol. 16, No. 6, 2019 http://ertr.tamu.edu 568 Prof Richard Chinomona Marketing Division School of Economic and Business Sciences Faculty of Commerce, Law, and Management University of the Witwatersrand 1 Jan Smuts Ave, Johannesburg, 2000 Private Bag 3, Wits, 2050, Johannesburg, South Africa Phone: +27 11 717 8085 Email: richard.chinomona@wits.ac.za Dr. Tinashe Chuchu Ph.D. is a senior lecturer in the Department of Marketing Management at the University of Pretoria. His research focuses on tourism, destination marketing and consumer behaviour. His work has been published and presented in numerous international journals and conferences respectively. Dr. Norman Chiliya Ph.D. is the head of the Marketing Division at the University of the Witwatersrand, Johannesburg. His current research focuses on adventure tourism and small business management. He has presented his research at academic conferences across the globe and has published in high impact international journals. Prof Richard Chinomona is an associate professor in Marketing Division at the University of the Witwatersrand, Johannesburg. His area of specialisation is in tourism marketing and consumer behaviour. http://ertr.tamu.edu/ mailto:keith_brown@cbu.ca e-Review of Tourism Research (eRTR), Vol. 16, No. 6, 2019 http://ertr.tamu.edu 569 Introduction Tourism images are essential to the success of any travel destination (Jeng, Snyder & Chen, 2019). This assertion is supported by Tasci and Gartner (2007) who suggested that destination image is widely regarded as a key aspect of successful tourism development and marketing of destinations (Tasci, & Gartner, 2007). The purpose of this study was, therefore, to explore servicescape, traveller perceived value, cognitive destination image, affective destination image, conative destination image, and the traveller’s intention to revisit a destination. ‘Servicescape’ is a term that was developed by Bitner (1992), and is broadly used to describe the physical environment of an organisation in which services are provided to customers (Balakrishnan, Muthaly & Leenders, 2016). Chivandi and Maziriri (2017) posited that operative problems solving and the potential of permanent improvement are hallmarks of efficient service organisations. Travellers’ expectations of an airport’s environmental surroundings can influence their perceptions of service quality (Fodness & Murray (2007). A traveller's perceived value is an important aspect of the tourism industry and is associated with the notion of visiting places being interesting (Yang, Liu, Jing & Li, 2014). Furthermore, Yang et al. (2014) state that perceived value influences a tourist's attitude and behaviour. Perceived value could be considered to be a low price, whatever the consumer wants in a product or service, and the quality the customer received for the price paid for the product (Bajs, 2015) Prior airport research, such as that of Halpern (2010), examined sources, capabilities, and consequences of marketing innovation at airports in Europe's bordering regions, whereby a form-based feedback survey was administered to airport executives (Halpern, 2010). It was then established that independently run airports demonstrated more innovation in comparison to regional or national airports (Halpern, 2010). According to Halpern (2010), big airports http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 6, 2019 http://ertr.tamu.edu 570 were seen to have a greater deal of innovation in comparison to the relatively smaller airports. As stated by Ucler and Martin-Domingo (2015), air travel has been on an upward trajectory for decades, increasing by 5.9 % on average in terms of passenger-kilometre performed, and by 6.1 % in terms of ton-kilometre performed. According to Ucler and Martin-Domingo (2015), there has been an increase in air traffic supported by world trade and tourism, due to airport congestion that has ultimately lead to travellers spending more time at airports. Transit time spent at airports together with the waiting time at check-in, security control, or baggage claims are all activities that are of no particular use to the traveller, as they do not bring commercial value to the airport (Ucler & Martin-Domingo, 2015). Air travellers are from a higher socio-economic group that manages their journeys, and in recent years they have expressed the need for enhanced airport experiences, such as increasing transparency, corporate responsibility, and efficiency at airports (Ucler & Martin-Domingo, 2015). There is limited published academic research on destination marketing within a South African context regarding how tourists’ service experience at an airport would help influence their image of a destination and potential revisits based on those images. Few studies such as Du Plessis Saayman and Potgieter (2014) and Giampiccoli, Lee, and Nauright (2015) focused on South African destination marketing. However, these studies did not investigate revisit intention of the travellers. The former investigated visitor’s experience at an airport while the later investigated the impact of the 2010 FIFA World Cup in South Africa. This study seeks to investigate how experiences at a South African international airport would influence travellers’ image of South Africa as a tourist destination and their willingness to revisit the country. Since the airport utilised for this research was a South African airport, the research context was thus presented from a South African perspective. In 2016 the South African http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 6, 2019 http://ertr.tamu.edu 571 domestic tourism market generated R6,4 billion for the second quarter (Q2) of the year (South African Tourism, 2016). Furthermore, South African Tourism (2016) indicated that holiday travel to South Africa had increased considerably in comparison to 2015, and accounts for 25% of the total tourism revenue (South African Tourism, 2016). Literature Review Destination image The study was based on the theory of destination image in which cognitive, affective, and conative elements of destination image were extensively reviewed. Destination image refers to an attitudinal theory comprising of the beliefs, ideas, and perceptions that a tourist holds of a destination (Hosany, Ekinci & Uysal, 2006; Chuchu, Chiliya & Chinomona, 2018). It comprises of three elements, namely cognitive, affective, and conative images. These elements are discussed later in this paper. Destination image is essential for tourism organisations/businesses and influences the content and material that they post for promotional purposes (Zhou, 2014). According to Stylidis, Shani and Belhassen (2017) destination image has been one of the most investigated topics tourism scholarship and marketing research (Cherifi, Smith, Maitland, & Stevenson, 2014; Fu, Ye, & Xiang, 2016; Stepchenkova & Li, 2013; Sun, Ryan, & Pan, 2015). This then shows the relevance and importance of investigating destination image. Destination image development is made from cognitive, affective/ emotional and conative, offline and web travel information thereby having a significant impact on tourist's destination choice processes and is a crucial method of differentiating destinations among competitors (Hyun et al., 2012). The sections that follow discuss cognitive, conative, and affective destination image. Lastly, traveller intention to revisit a destination is explored. http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 6, 2019 http://ertr.tamu.edu 572 Cognitive image was defined by Chen et al. (2016) as the probable knowledge of a destination that a tourist might hold. Cognitive destination image in a key component of destination image. Destination image is primarily made of cognitive image components (Rajesh, 2013). Cognitive destination image was described by Hosany, Ekinci, and Uysal (2006) as the beliefs and knowledge that tourists hold about the physical qualities of a destination. According to King, Chen, and Funk (2015). Cognitive image component is defined as the known features of the destination in reference to information or beliefs (King et al., 2015). Gerdes and Stromwall (2008) described conative destination image as the nature in which an individual with any degree of motivation goes about acting on that motivation. Cognitive component positively influences the intention to recommend the destination (Stylidis et al., 2017). Affective destination image influences intention to revisit a destination but overall image of the destination mediates the relationship (Stylidis et al., 2017). Affective destination refers to the feelings that potential tourists hold about a destination (Chen et al. 2016). Affective destination image influences intention to revisit a destination but overall image of the destination mediates the relationship (Stylidis et al., 2017). Furthermore, it was proposed that affective destination image is impacted directly by cognitive destination image (Stylidis et al., 2017). Revisit intention is defined as an individual's willingness to make a repeat visit to the same destination (Stylos, Vassiliadis, Bellou & Andronikidis, 2016). In addition, it was postulated by Stylidis et al. (2017) that revisit intention was a result of cognitive destination image and that the overall image of a destination had a direct impact on revisit intention. The following section looks at the hypotheses development and the study's conceptual framework. This is then followed by the remainder of the paper, which includes the analysis of data and the interpretation of the study's findings. The model of destination image is presented in figure 1 below. Figure 1: Model of the Formation of Destination Image http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 6, 2019 http://ertr.tamu.edu 573 Source: Beerli and Martin (2004) The present research adapted the model of destination image proposed by Beerli and Martin (2004). However, some aspects of their model, such as personal factors and information sources were not examined as this research was mainly concerned with the interrelatedness of cognitive image, affective image, and conative image. Conative image was an additional construct added for this study’s purposes. This model, therefore, formed the basis of the following model, figure 2, which became the proposed conceptual model for this study. http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 6, 2019 http://ertr.tamu.edu 574 Figure 2: Destination Image Conceptual Framework Source: author’s own work 3.1 Cognitive destination image and affective destination image According to Chen et al. (2016), both destination quality and destination uniqueness directly and positively influence affective destination image. Liu et al. (2015) argued that tourists’ overall image is significantly and positively related to their affective image. Affective destination image influences a holistic image (overall image), which in turn influences a traveller's intention to revisit a tourist destination (Stylos et al., 2016). This assertion was then supported by Qu, Kim, and Im (2011), who suggested that cognitive images have a positive effect on a visitor’s image of that destination. It was then postulated by Banki Ismail, Dalil and Kawu (2014) that affective destination image directly and positively influences tourist behavioural intention. Affective destination image is, therefore, necessary for tourist revisit intention to occur (Banki et al., 2014). H1: Cognitive destination image is directly and positively related to affective destination image http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 6, 2019 http://ertr.tamu.edu 575 3.2 Affective destination image and conative destination image It is imperative to consider that emotions are associated with a traveller's intention to revisit a destination. This notion was supported by Qu, Kim, and Im (2011) stated that destination image relies greatly on the ability of that destination to attract traveller revisits or recommendations which are crucial for tourism development. Tourists’ emotional experiences play a function in influencing satisfaction levels and intention to recommend (Hosany & Gilbert, 2010). Therefore, inferring from the literature and the empirical evidence mentioned above, the study hypothesised the following statements: H2: affective destination image is directly and positively related to conative destination image 3.3 Affective destination image and traveller intention to revisit In a study that investigated the relationship between affective destination image and traveller intention to revisit (Stylos et al., 2016) found a link between these two constructs. Affective image positively influences traveller intention according to (Chen, Lai, Petrick & Lin, 2016). Stylos et al. (2016) posited that affective image directly and positively influences a tourist's intention to revisit a destination. Affective image is positively related to the intention to recommend the destination to other travellers (Qu et al., 2011). However, this is not a direct relationship as it is mediated through the overall image that the traveller has of the destination. Therefore, inferring from the literature and the empirical evidence mentioned above, the study hypothesised that: H3: Affective destination image is directly and positively related to traveller intention to revisit a destination http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 6, 2019 http://ertr.tamu.edu 576 3.4 Conative destination image and traveller intention to revisit According to Stylos et al. (2016), conative destination image influences traveller intention to revisit significantly in two ways, first directly and second indirectly through the holistic image. As suggested by Sylos et al. (2016), the destination image theory provides the foundation of the relationship between conative destination image and traveller intention to revisit a destination. Pike & Ryan (2004) argued that conation is to be measured based on stated intent to visit. Li, Petrick & Zhou (2008) pointed out that conative images positively and significantly affect destination overall image. Han, Kim, and Kim (2011) argued that the conative image is directly related to both loyalty and revisit intention. Therefore, inferring from the literature and the empirical evidence mentioned above, the study hypothesised the following statements: H4: Conative destination image is directly and positively related to traveller intention to revisit a destination 3.5 Cognitive destination image and traveller intention to revisit The cognitive or perceptual components are concerned with the beliefs or knowledge about a destination's features evaluations (Stepchenkova & Mills, 2010). The present study hypothesised that cognitive destination image was directly and positively associated with traveller intention to revisit a destination. Additionally Park Hsieh and Lee (2017) also observed that there was an alternate option in which destination image and traveller intention were mediated by traveller constraints in which this became a negative linkage. The likelihood of tourists to make future visits then ultimately leads to the likelihood of recommendation for that destination (Eusébio & Vieira, 2013). H5: Cognitive destination image is directly and positively related to traveller intention to revisit a destination http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 6, 2019 http://ertr.tamu.edu 577 4. Research Methodology The study was quantitative in nature and utilised the survey methodology approach. Following the positivist, philosophy was imperative in order to obtain objective results. Due to the absence of a known population, which made it impossible to obtain a sampling frame, non-probability sampling was adopted for selecting research participants. Travellers were intercepted at the departures section of the airport. Data collection was conducted in 2016 over a one month period at various times of the day to allow for an even spread of the sample. Trained research aids administered surveys to willing tourists at a busy South African Airport, where 503 surveys were returned and later used for data analysis. After research data was collected from the participants, it was analysed using SPSS24 for descriptive and reliability results while AMOS 24 was used for testing the study’s hypotheses through structural equation modeling. 4.1 Measurement Instrument Design Survey questions were based on constructs of the proposed conceptual model. Measurement items for cognitive destination image were adapted from Tan and Wu (2016), while those for affective destination image were adapted from Stylos et al. (2016). Conative destination image measurement items were taken from (Stylos et al. 2016) while those for traveller intention to revisit a destination were taken were based on Gallarza and Saura (2006). 5. Results of the Study 5.1 Measurement Model Assessment Reliability and validity were assessed using the Cronbach's alpha, composite reliability, average variance extracted, respectively. In the following section, the confirmatory factor analysis model is presented to check whether constructs such as cognitive destination image, affective destination image, and conative destination image as well as traveller http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 6, 2019 http://ertr.tamu.edu 578 intention to revisit a destination are still valid and appropriate for use in the present study. Table 1 and 2 present reliability and validity tests, respectively. Table 1: Reliability and Validity Tests CONSTRUCT MEAN (α) ALPHA CR AVE Cognitive destination image 1,537 0.888 0.892 0.457 Affective destination image 1, 405 0.914 0.913 0.600 Conative destination image 1, 445 0.913 0.910 0.563 Traveller intention to revisit a destination 1,595 0.917 0.910 0.659 Key: (α) Alpha: Cronbach’s alpha, CR: Composite reliability, AVE: Average variance extracted 5.2 Sample Profile Gender Characteristics The majority of the participants were males, as indicated by 58% of the total sample. This was significantly larger than the number of women who participated in the study accounting for only 39% of the total sample. Some tourists decided to remain anonymous and declined to provide their gender affiliation. These accounted for a mere 3% of all the tourists surveyed at the airport. Age of Travellers The largest age group was that of 36 years and older, which accounted for 38% of all the tourists surveyed at the airport. This was then followed by the 26 to 35 age group representing 32% of all the participants. The third-largest age group that participated was represented by 22% of the entire sample. The smallest age groups were that of the 18 to 19 and 20 to 25 and years of age. It could be inferred that the younger tourists probably travel less due to having less disposable income in comparison to the much older tourists. The least represented age group was also the youngest, and this was between the ages of 18 to 19. http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 6, 2019 http://ertr.tamu.edu 579 Frequency of Travels As shown in figure 4 above in terms of frequency of travels it could be noted that 52% of all the tourists surveyed travelled at least once a year while 23% of them travelled more than once a month. Some of the tourists decided to choose the "other option" since there was no category that matched their specific travel habits. The fourth-largest as far as frequency of travel is concerned was that of those who travelled often in a week. This group represented 5%. This group was then followed by tourists who mentioned that they only travel once a week. 1% of all tourists did not provide any response concerning their frequency of travels. The last group was that of tourists who stated that the statement of "frequency of travels" was not applicable to them. Figure 2: Purpose of Trip As indicated in figure 57, the purpose of the trip is presented. Leisure travellers represented 35%, while business travellers represented 33%. These two groups of travellers were very similar in representations and contributed to more than half of all travellers intercepted at the airport. Educational purpose travellers represented 17% of all the tourists. Tourists who decided to state that their trip to South Africa was for reasons other than those http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 6, 2019 http://ertr.tamu.edu 580 stated were 12% of total sample. Travellers who came to South Africa for medical reasons accounted for 12% of all tourists while those who did not elected to decline answering the statement concerning their purpose of travel were 1% of the sample. This study was not immune to respondents that thought the purpose of travelling was not applicable to them. This group of tourists represented less than 0% of all travellers. Figure 3: Frequency of Holidays Figure 6 presents the frequency of holidays. Tourists that stated that they go on holiday every few years were 15% while those that stated going on holiday once a week were 6%. Additionally, 36% of all travellers indicated that they went on holiday once a year while those that mentioned going to holiday twice a year were 15%. Tourists that stated that they would go on holiday more than twice a year and for any "other" duration were 19% to 8% respectively. Some tourists decided to choose the "other" option regarding their frequency of holidays. Lastly, 1% of the tourists did not provide a response concerning their frequency of holidays, and 0% of the tourists stated that the frequency of holidays was not applicable to them. http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 6, 2019 http://ertr.tamu.edu 581 Measured Model Fit Table 2 below presents the model fit indicators where all indices met the recommended thresholds. Chi-square (CMIN/DF) was below 3 while GFI, NFI, RFI, IFI, TLI, CFI, were all above recommended thresholds of 0.900. The root mean standard error approximation (RMSEA) was 0.051 also below recommended thresholds. Table 2: Model Fit CMIN/DF GFI NFI RFI IFI TLI CFI RMSEA 2,315 0,900 0,916 0,901 0,950 0,941 0,950 0,051 CFA Model: Confirmatory factor analysis model; CMIN/DF: Chi-square; GFI: Goodness of fit index; NFI: Normed Fit index; RFI; Relative Fit Index; IFI: Incremental Fit Index; TLI: Tucker Lewis Index; CFI: Comparative Fit Index. RMSEA: Root Measure Standard Error Approximation After the model fit was confirmed, the research proceeded to the structural model presented in figure 4. Figure 4: Structural Model Key: β=Estimate http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 6, 2019 http://ertr.tamu.edu 582 The Structural model presented in figure 4 presents the results from hypotheses testing. A table with further details of the analysis is presented in the following section. Furthermore, discussions that explore findings, as well as implications of those findings, are provided. Table 3: Hypotheses Results Hypothesised Relationship Estimate P-Value Result Cognitive destination image & Affective destination image H1 0.72 *** Supported and Significant Affective destination image & Conative Destination Image H2 0.67 *** Supported and Significant Affective destination image & Traveller Intention to Revisit H3 0.34 *** Supported and Significant Conative destination image & Traveller Intention to Revisit H4 0.62 *** Supported and Significant Cognitive destination image & Traveller Intention to Revisit H5 0.11 *** Supported and Significant P-value level of significance: p<0.01; p<0.05; p<0.1 Discussion of hypothesis results Table 3 above presents the findings of the hypothesis testing. All proposed relationships were both supported and significant at p<0.001, ranging from 0.11 to 0.72. It is observed that cognitive destination image and affective destination image (H1) are positively and directly related at an estimate of 0.72. This implied that the image that tourists have of South Africa as a destination influence the emotions they associated with that destination. This relationship was also the strongest of all relationships. http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 6, 2019 http://ertr.tamu.edu 583 Based on the results, it is established that affective destination image and conative destination image (H2) are positively and directly related at an estimate of 0.67. This implies that tourists’ emotions influence their behaviour and reactions to situations. The third hypothesis, confirms that affective destination image has a positive and direct influence on traveller intention to revisit a destination (H3). This hypothesis has an estimate of 0.34, implying that tourists' emotions towards a destination generally lead them to return for future visits. Conative destination image had a positive and direct impact on traveller intention to revisit a destination (H4). This hypothesis had an estimate of 0.62. This, therefore, suggested that tourists' behaviour and motivations are related to their intention to revisit a destination. Lastly, results show that cognitive destination image has a positive and direct impact on traveller intention to revisit a destination (H5). This hypothesis had an estimate of 0.11. This finding was quite interesting as it suggested that tourists' belief and knowledge about a place did not play a major role in their decision to revisit that place. Policymakers and tourism operators in South Africa could take advantage of knowing that there is an opportunity to change tourists’ beliefs towards the country since this study confirms that tourists are open- minded to other beliefs and acquiring new knowledge. Conclusions and Recommendations The present research had cognitive destination image, affective destination image, and conative destination image as predictors of intention to revisit a destination. It would be interesting to find out how cognitive destination image and conative destination would influence traveller intention to revisit a destination if affective destination image (emotions and feelings) was removed from the model. Possibly emotions could have created biases due to their subjective nature. In addition, future research could utilise the same conceptual model as of this study to establish whether similar results will be obtained for comparison reasons? http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 6, 2019 http://ertr.tamu.edu 584 Questions regarding the use of airport experience as an objective assessment for destination image and revisit intention will continue to be raised. Managerial Implications and Contribution The study’s findings imply that managers of tourism organisations should try to understand tourists’ emotions and their pre-conceived beliefs better as these factors influence their intention to revisit a destination. This would in-turn inform them of the best methodologies to adopt when providing services to these tourists. Additionally, the research contributed to the comprehension of the relationship between cognitive destination image, affective destination, conative destination image, and ultimately, how these constructs affect traveller intention to revisit a destination? The main contribution of the study was that cognitive destination image (pre-conceived ideas about a destination) had the most influence on a traveller’s intention to revisit that destination. This implied that tourism organisations and airport management companies in South Africa have to focus more on marketing the country as a travel destination in the home countries of those travellers before they visited South Africa. This would influence travellers before they enter South Africa rather than waiting for the travellers to reach the country and then try to promote the country to them. Limitations of the Research The research study could have been compromised by the fact that it was only conducted at a single airport. This could have resulted in some respondent and sample bias since all participants were exposed to exactly the same environment. Another limitation was that the antecedents of destination image were not empirically investigated, and this could have limited this study’s explanation of how destination image affects revisit intention? http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 6, 2019 http://ertr.tamu.edu 585 Suggestions for Future Research Findings of this study left room for future researchers to explore. This study did not categorise international tourists by nationality, which meant that differences based on tourists' countries of origin could not be measured and evaluated empirically. Future research could include “nationality” as a demographic factor. Also highlighted in the study’s limitations, antecedence of destination image should be measured as this would help explain destination image and its eventual influence on revisit intention. Furthermore, it could also be recommended that future researchers use different potential predictors of revisit intention as that would potentially reveal interesting insights that were potentially left-out by this research. Future research can involve local tourists surveyed at multiple airports in South Africa. This is because relying only on international travellers intercepted at a single airport possibly led to responses that were not very diverse since all participants were exposed to the same environment. On the other hand, surveying, tourists at an airport could have resulted in receiving feedback from individuals who were anxious, tired, possibly frustrated due to the stress of travelling. 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