Residents’ impact on their visitors’ experience: A host–guest dyadic approach in student-generated VFR travel

Abstract

Visiting friends and relatives (VFR) is one of the largest but most neglected segments in tourism research. Little is known about the way hosts affect their visitors’ experience, although it is crucial for the understanding and marketing of VFR. To fill this gap the study first identified three key constructs (hosts’ destination knowledge, destination image and motivation to host) and developed a theoretical model to measure hosts’ influence on their visitors’ experience. The model was then tested on 458 pairs/dyads of hosts and their visitors, which provides a unique methodological perspective, rare in tourism research where most constructs’ relationships are normally measured in single individuals. The model's measurement suggests that to improve visitors’ experience, destination marketers should focus on educating residents about the local attractions (increase hosts’ destination knowledge). However, to increase visitation, marketing should target residents’ emotional connections with potential visitors (increase motivation to host).

Keywords

VFR marketing dyads residents’ impacts destination knowledge visitors’ experience

Introduction

Visiting friends and relatives (VFR) has been considered the oldest, largest and one of the most reliable and resilient travel segments, representing around a quarter of all international travel and often an even larger proportion of domestic travel (Backer, 2012; Backer and King, 2015). VFR travellers tend to return regularly to the same destination, travel during off-season periods and are less affected by economic fluctuations making them more profitable and reliable in the long term (Backer and King, 2015). Accordingly, even during the COVID-19 pandemic VFR remained one of the few tourism segments allowed to travel (commonly returning citizens who wanted to be closer to their loved ones), and it was one of the leading segments starting the recovery of the tourism industry (Bakri et al., 2024; Zentveld et al., 2022).

VFR travellers tend to have more prolonged visits and include their hosts in the activities increasing the group expenditure, which they also spread more evenly throughout the local economy (Backer and King, 2015). Moreover, VFR has been identified as ‘less intrusive’ for local communities, less harmful for the environment and overall more ‘sustainable’ than other types of tourism (Stylidis et al., 2022; Zentveld, 2025). However, despite its large size and benefits, VFR remains as one of the most neglected topics in tourism research (Backer and King, 2015). Zentveld et al. (2022) identified only 94 articles published between 1990 and 2021, which is an extremely small body of research for a segment that represents at least a quarter of all travel. To put this into perspective, Dinç et al. (2023) identified 1387 ‘ecotourism’ studies during a similar period.

The lack of research in VFR is even more concerning when it comes to the marketing of VFR and the role of the host in the VFR experience, although hosts play a crucial part having a strong influence on their visitors (Bakri et al., 2024; Choi and Fu, 2018; Humbracht et al., 2022; Yousuf and Backer, 2015). Hosts, for example, have been described as: local guides, tourism mediators, destination experience brokers and destination ambassadors (Dutt and Ninov, 2017; Morrison et al., 2000; Humbracht, 2015). Consequently, Zátori et al. (2017, p. 18) stated that ‘the local knowledge and passion for the given place of the hosts are seen as crucial factors of involving VFR travellers in local tourism; however, little empirical evidence is available’. Similarly, Bischoff and Koenig-Lewis (2007, p. 480) argued that ‘more research is needed into the role of hosts in VFR tourism’ and stated that ‘perhaps hosting friends and relatives or “HFR” would be a more appropriate label for this type of research’.

This study aims to fill this gap by proposing a model that identifies the key elements in this relationship and can measure hosts’ influence on their visitors’ experience, which is crucial for the understanding and marketing of VFR. Hence, the study first recognised three hosts’ constructs (destination knowledge, destination image and motivation to host) to develop a theoretical model and a measurement instrument. The model was then tested on 458 host–guest pairs or ‘dyads’ using structure equation modelling (SEM). Methodologically, the study provides a distinct view by analysing construct relationships between related individuals (458 host–guest dyads), which generally involves many more difficulties than measuring construct's relationships within single individuals, which is largely the most common approach in tourism and hospitality.

Literature review

At first glance defining VFR appears to be a simple question, however, when a more specific definition is needed for practical purposes, such as conducting marketing or research, it can become a complex issue (Munoz et al., 2017). Most VFR studies rarely discuss this question, implying that VFR is defined based on the categorisation used to collect the data in tourism statistics, which most of the time is as ‘main purpose of travel’, a term that includes business, leisure, VFR or other purposes (Backer, 2009). Yet VFR has also been described by the accommodation type: commercial versus friends or relatives, as well as the activities performed at the destination and the motivation to travel (Morrison et al., 2000).

These different ways to define VFR travellers provide different measurements of the market, with some visitors just qualifying in one category while others overlap throughout several categories, creating confusion and underrepresentation of the VFR market (Munoz et al., 2017). Backer and Hay (2015) argued that VFR is often just one of many different reasons for travel or one of the many different activities undertaken by travellers. Consequently, VFR could be seen as one element of a ‘hybrid trip’.

Backer (2007) acknowledged this problem and proposed a definition that combines both travellers ‘main purpose of travel’ and their ‘accommodation type’ in a ‘definitional typology’. Hence Backer (2007, p. 369) argued that VFR ‘is a form of travel involving a visit whereby either (or both) the purpose of the trip or the type of accommodation involves visiting friends and/or relatives’. This is illustrated in Figure 1.

Figure 1.

Backer's (2009) definitional typology.

Backer (2007) named travellers in the top left corner ‘pure VFRs’ because both their purpose and their accommodation are VFR. Travellers in the top right corner were named ‘commercial VFRs’ and the bottom left corner were called Exploiting Friends and Relatives (EFRs), because they use the host's accommodation, but their main purpose is to see the destination and not their hosts, which was further explored by Backer (2008, 2009).

Later Munoz et al. (2017) extended Backer's model to include other aspects used in previous definitions, such as Morrison et al. (2000) activities and motivations, to argue that all the elements used in previous definitions are based on how hosts affect common aspects of all trips, such as accommodation, purpose or activities. However, no element alone or in groups can fully explain what the VFR phenomenon is, because the most essential characteristic of the VFR concept and all the previous definitions, is the influence that hosts have on all aspects of the VFR experience. Hence, Munoz et al. (2017, p. 483) use the ‘influence of the host’ as the most fundamental characteristic to define VFR as ‘a specific type of mobility influenced by a host that includes a prior personal relationship between host and visitor and some face-to-face interaction or co-presence between them during the act of mobility’.

Students in VFR research

Traditionally, students have also been neglected in tourism research because they have been seen as a less profitable segment (Bischoff and Koenig-Lewis, 2007). Most studies looking at students in the context of tourism have explored their experiences as travellers backpacking but less frequently as hosts and generators of VFR trips. The few studies that have explored students’ VFR experiences as hosts have mainly looked at the VFR trips generated by specific cultural groups of international students (Munoz, 2020). Nevertheless, domestic students’ migration to undertake tertiary studies is one of the largest emigrational movements in western societies, generating substantially more VFR visits than international students in total and per student (Bischoff and Koenig-Lewis, 2007).

Bischoff and Koenig-Lewis (2007), one of the few studies that have looked at the whole student population including domestic and international students, found that in Swansea, UK, most domestic students received on average eight visits a year (3.8 from relatives and 4.2 visits from friends) while international students received less than two visits. The authors also noted that relatives used more commercial accommodation than friends, and that younger students received more visits from relatives than older students who received more visits from friends. Consequently, students attract a substantial amount of VFR trips to university cities, and the market follow a predictable pattern of visits closely related with the academic year offering commercial opportunities. Tourism authorities can take advantage of these dates to retain visitors for longer periods, as well as potentially building long-term relationships with alumni.

Marketing to VFR

From the perspective of most Destination Marketing Organisations (DMOs), the VFR market has traditionally been seen as a segment that is less profitable, hard to reach, influence, and has been taken less into consideration (Backer, 2009; Backer and Morrison, 2015; Morrison et al., 2000). Pearce et al. (1995) for example, found that only 40 out of the 56 DMOs interviewed in Australia recognised VFR in their campaigns and only seven of them (12%) implemented specific programmes to target it. Later, Morrison et al. (2000) surveyed 221 DMOs in Australia, Canada, New Zealand and the United States, obtaining similar findings and noted that, although DMOs in Australia and New Zealand had a better attitude towards the VFR market, in general DMOs did not believe in the importance of the segment. This was confirmed by Backer (2009) who conducted 47 interviews with DMOs in Australia and later by Backer and Morrison (2015) who replicated that study's protocol with 22 DMOs. These authors also observed that DMOs did not normally include VFR in their marketing, they did not have specific marketing strategies towards VFR, had difficulties defining it, and had little data and knowledge about the segment.

This lack of understanding about VFR has been pointed out as one of the reasons for its neglected status (Munoz et al., 2017). VFR travellers are not harder to influence but are different from the stereotypical tourism segments where tourists’ main purpose is associated with the destinations’ attractions. The VFR phenomenon is a unique mix of tourism and human relationships, and thus, it is necessary to adjust the marketing approaches to its particular needs. Better understanding VFR's unique characteristics is important to develop the best marketing approaches for the segment and especially to decide why and how to use the hosts when conducting marketing to VFR travellers.

There are two important questions DMOs need to answer when targeting VFR travellers: (1) how to reach them and (2) how to motivate them. How to reach them initially can be seen as difficult because VFR travellers are heterogeneous and come from various locations. DMOs however, can easily reach VFR travellers through their hosts, because they are the main and most trusted source of information for their visitors and they live permanently at the destination. Morrison et al. (2000) added that targeting the hosts is generally simpler, more effective and requires less investment than using traditional strategies. Moreover, by reaching the hosts it is possible to successfully target subgroups within the VFR market, such as students or pensioners (Bischoff and Koenig-Lewis, 2007).

In terms of motivation to travel, it was originally believed that VFR travellers’ only motivation was to see their friends and relatives, and thus, it was not possible to persuade them to consume commercial tourism products. Backer (2008, 2009) however, claimed that VFR traveller can have multiple motivations to travel and can be strongly influenced by the appeal of the destination. Therefore, DMOs should tailor their strategies to target different groups within the VFR market, which Yousuf and Backer (2017), and Zentveld and Yousuf (2022) noted that can also include hosts and visitors’ origin (local versus immigrant) and their relationship (visiting friends or relatives).

According to Morrison et al. (2000) DMOs use mainly two strategies to attract VFR travellers: (1) encouraging residents to learn about the destination by using the local attractions and (2) to persuade hosts to attract their friends and family to visit. Later Munoz (2020) expanded this to three key strategies based on the analysis of 12 VFR marketing campaigns previously reported by Morgan et al. (2003), Morrison and Hay (2010), Backer (2014) and Backer and Hay (2015). Therefore, according to Munoz (2020) DMOs generally attract VFR travellers using one or more of the following strategies: (1) improving residents’ destination image and attitude towards the destination; (2) educating residents about the local attractions (providing destination knowledge); and (3) motivating residents to attract visitors (use them as pull factors) and becoming local ambassadors.

Munoz (2020) analysis suggests that the marketeers behind these 12 VFR campaigns have a strong belief that these strategies are the most effective way to influence VFR travellers. Nonetheless, despite the extensive application of these approaches, none of the studies analysed by Munoz (2020) provided empirical data to support their efficacy. As a result, the marketeers who ran these VFR campaigns relied purely on their common sense, trusting that residents and visitors would respond positively to these initiatives because of the plausibility of the argument behind them, which the current study aims to quantitatively evaluate. These three strategies first led to the identification of the study's three key host's constructs (destination image, destination knowledge and motivation to host) that were then measured on a sample of hosts to evaluate the impact on their visitors’ satisfaction. Consequently, the following sections further develop the constructs, as well as the rationale behind the constructs’ relationships and the hypotheses of the study.

Destination image

Destination image is a key element and often the most significant feature influencing travellers’ decision-making, tourism experience and post-trip evaluation, hence, it has been researched extensively during the past 50 years (Lai and Li, 2016; Stylidis et al., 2022; Zhang et al., 2014). Since the concept was born in the early seventies, multiple definitions have been proposed without agreement between scholars, who have argued that the definitions are vague and atheoretical, such as ‘impression of a place’ or ‘perceptions of an area’ (Lai and Li, 2016). Destination image has been defined as a ‘series of beliefs, opinions and impressions’ (Aksoy and Kiyci, 2011, p. 479) and as the ‘subjective interpretation of reality made by the tourist’ (Bigne et al., 2001, p. 607). The concept is therefore, much wider than just a visual perception, involving opinions, ideas, beliefs and impressions.

Destination image has also been tested broadly as a dependent and independent variable in association to various constructs and especially to satisfaction, confirming that it has a direct positive influence on tourists’ experience (Bigne et al., 2005). Most previous studies however, have measured these constructs’ interactions within single individuals, which is different from measuring destination image in one individual and then testing how this affects the experience of another. Although, VFR marketing relies strongly on the belief that hosts’ opinion of the destination will directly affect their visitors’ experience and their motivation to attract visitors. Moreover, Schroeder (1996, p.73) observed that residents’ destination image affected their motivation to recommend their region to potential visitors and argued that ‘improving the residents’ image could help make residents better ambassadors for their state or region’. Thus, based on the literature mentioned it could be expected that:

Hypothesis 1: Hosts’ destination image positively influences their motivation to host.

Hypothesis 2: Hosts’ destination image positively influences their visitors’ experience.

Hosts’ destination knowledge

Previous research suggest that hosts’ destination knowledge has a strong influence on their perception of the place, their motivation to host and their visitors’ experience (Choi and Fu, 2018; Dutt and Ninov, 2017; Humbracht et al., 2022; Stylidis et al., 2022). VFR marketers have also advocated for educating residents about the destination to improve their perception of it, motivate them to encourage visitors and improve their experience (Backer, 2014; Morrison et al., 2000).

From a broader perspective, Murphy et al. (2007, p. 517) argued that in tourism ‘information (knowledge) can be treated as one of the most or even the most important factor influencing and determining consumer behaviour’. However, most authors do not provide a definition of ‘tourist knowledge’ and there is no agreement in how to conceptualise it. Wong and Yeh (2009, p. 10) stated that based on consumer research, tourist knowledge could be defined as ‘the degree of tourist self-assessed destination knowledge’, and it can be ‘objective’, which refers to factual information, or ‘subjective’ meaning people's ‘perceptions of what or how much they know’. Alba and Hutchinson (1987), however, argued that knowledge can also be ‘declarative’, which refers to factual or ‘procedural’ information that are the skills needed to consume a tourism product. Lastly, Sharifpour et al. (2014) claimed that knowledge can be objective, subjective and ‘previous experience’, adding an additional dimension.

Research on tourism information sources suggests that people's destination image is directly affected by the way they gain knowledge/information about destinations (Stylidis et al., 2022). According to Baloglu and McCleary (1999, p. 874) information is ‘a force which influences the formation of perceptions’ and that ‘the type, quality, and quantity of information would determine the type of destination image that is likely to develop’. Murphy et al. (2007, p. 517), also noted that the information people receive about the destination ‘contributes to the development of destination images’. Accordingly, it could be argued that:

Hypothesis 3: Hosts’ destination knowledge positively influences their own destination image.

If visitors get to see the destination ‘through the eyes of their hosts’, residents’ destination knowledge will determine what visitors get to see. Hosts play an important role advising visitors when planning their trips and later leading the activities (Backer, 2012). Hence, according to Morrison et al. (2000, p. 111) DMOs often see hosts as ‘unpaid tourist guides’, whose level of knowledge has a direct positive impact on tourists’ experience. Similarly, Dutt and Ninov (2017) in their analysis of expatriate hosts, observed that residents’ destination knowledge has a clear impact on their visitors’ experience. Therefore, it could be expected that:

Hypothesis 4: Hosts’ destination knowledge positively influences their visitors’ experience.

VFR marketing has strongly relied on the belief that locals will be more motivated to host visitors if they know more about their destination. For example, a VFR marketing manager in Backer (2014, p. 6) argued that ‘after they (residents) became much more aware of attractions of the town, acted as knowledgeable tourism marketing ambassadors by not only encouraging the original visit, but also in encouraging their visitors to make return trips’. Likewise, Dutt and Ninov (2017) found that after every visit hosts learn more about the destination, which also improved their feelings about hosting and motivated them to attract visitors. Therefore, it could be anticipated that:

Hypothesis 5: Hosts’ destination knowledge positively influences their motivation to host.

Motivation to host

‘Hosting’ is a vital concept in the VFR phenomenon, as it involves caring and accommodating visitors within one's life, showing them the destination and engaging with them before and after the visit (Munoz et al., 2017). According to Zátori et al. (2017, p. 7) ‘host attitude is one of the most important value factors for the guests…’ and ‘play a crucial role in VFRs tourist experience formation’.

Conceptually ‘motivation’ has been researched extensively as it has been noted as a crucial antecedent of behaviour, yet in tourism ‘motivation’ has mostly been discussed in the context of ‘motivation to travel’ (Lu, 2011). ‘Motivation to host’ however, is a new construct proposed in this study that binds together the two main aspects associated with hosting in VFR, which are: hosts’ motivation to attract visitors (residents seen as a pull factor – widely used in VFR marketing), and hosts’ motivation to show the destination to their visitors, what Zátori et al. (2017, p. 17) described as hosts becoming ‘destination experience mediators’.

These two elements however, have been previously discussed in literature under different contexts. For example, Shani and Uriely (2012) and Dutt and Ninov (2017) observed that hosts feel a ‘duty’ to receive and look after their guests, so they have a ‘good experience’. Accordingly, Lee and Lai (2018), Stylidis et al. (2017a) and Schroeder (1996), conducted quantitative studies where they measured residents’ willingness to recommend destinations compared to other concepts, such as support for tourism development and destination image, which they argued should also have a positive impact on visitors’ experience. Hence, it could be expected that:

Hypothesis 6: Motivation to host positively influences visitors’ experience.

Experience

Experience and satisfaction are key aspects to explain people's attitude and future behaviour towards a product, and therefore, have been researched extensively in tourism (Li et al., 2012; Lu, 2011). However, Huang and Hsu (2010, p. 80) argue that experience is also ‘credited as the most elusive area in tourism research’, which creates confusion among researchers about the concepts. Cole et al. (2002) for example see experience as an antecedent of satisfaction, other authors use both terms synonymously (Baker and Crompton, 2000) and others see satisfaction as an antecedent of pleasurable experiences (Chan et al., 2015). Likewise, there is no agreement between scholars about one clear definition of satisfaction, yet, it has often been described as ‘consumers’ holistic evaluation of an experience’ (Phillips et al., 2013, p. 95), which Huang and Hsu (2010, p. 83) saw as the ‘post-consumption summary evaluation of the vacation experience’.

In terms of conceptualisation, according to Li et al. (2012) there are two major approaches: satisfaction as a ‘process’ that explains satisfaction based on people's expectations and is rooted on discrepancy theory; and satisfaction as an ‘outcome’ that puts the focus on people's experiences for understanding satisfaction instead of their expectations. This study took an ‘outcome’ view of satisfaction that aimed to obtain a perspective of the whole experience and is measured against the three hosts’ constructs (Figure 2).

Figure 2.

Conceptual model.

Methodology

Study context

Guildford, the historic county town of Surrey, is located in the South-East of England and has the highest proportion of VFR trips in the country accounting for 62% of visitors (Visit England, 2019). The town is not a recognised tourism destination, hence, most visitors are not biased by preconceptions of it, which is useful for measuring hosts’ influence. However, for a town of around 100,000 inhabitants, Guildford has several heritage and nature attractions, a museum and a visitors’ information centre that organises regular events. Therefore, depending on their destination knowledge, image and motivation, hosts and visitors could spend several days exploring the area making the town ideal for the study. This situation is common for many small-to-medium-sized towns/cities that have received little attention in academia compared to well-known international destinations, despite most tourism tending to be domestic and to lesser-known areas (Backer, 2012). Moreover, university cities like Guildford are important centres of VFR and have also been greatly under-researched (Bischoff and Koenig-Lewis, 2007).

Questionnaire development

Based on the theoretical framework, two questionnaires (one for hosts and one for visitors) were developed. Four experts in the field assessed both questionnaires’ measurement of the constructs, confirming the face-validity of the instruments. A pilot test with 15 dyads was also conducted to further test the suitability of the questionnaires. Demographic variables such as age, gender, origin, residence, number of visits and their relationship (e.g. friend/relative) were requested at the beginning of both questionnaires.

The first section of the host's questionnaire evaluated their ‘motivation to host’. As seen in the ‘Motivation to host’ section, the construct is defined by the two main aspects associated to hosting in VFR: hosts’ ‘motivation to attract visitors’, extensively used in VFR marketing (Backer, 2014; Morrison et al., 2000); and hosts’ ‘motivation to show the area’, which has been commonly described in literature as hosts acting as ‘unpaid tour-guides’ or a ‘destination experience mediator’ (Morrison et al., 2000; Zátori et al., 2017). Therefore, two items were used to measure those concepts: ‘motivation to encourage visits’ was based on the studies from Schroeder (1996), Stylidis et al. (2017a) and Lee and Lai (2018) who measured residents’ willingness to recommend the destination; and ‘motivation to show the area’ was developed based on Humbracht (2015) and Dutt and Ninov (2017) who emphasised the important role hosts play as local guides.

The second section of the questionnaire evaluated hosts’ image of Guildford using three items: overall opinion of Guildford, perception of the local attractions and perception as a place to live. The approach and number of items was based on Bigne et al. (2005) and Zhang et al. (2014) who stated that single items measuring ‘overall perception’ are the most effective method to measure the holistic view of a destination. Moreover, Stylidis et al. (2017b) who tested multi-items against a single overall question about residents’ destination image found a strong correlation between the two measurement styles. Residents’ perception ‘as a place to live’ was included based on Stylidis (2012, p. 84) who measured residents’ destination image and argued that ‘overall image of the place involves aspects that are related to residents’ everyday life’. This dichotomy between places to live or visit has not been explored in VFR but can strongly affect participants’ image and knowledge of the place, therefore, it was introduced in the measurement of both concepts.

The last section of the host's questionnaire evaluated their destination knowledge using three items: overall knowledge of Guildford, knowledge of its attractions and actual visitation to attractions. The first two items aimed to measure subjective knowledge using single questions, suggested by Wong and Yeh (2009) as a better way to measure knowledge and to understand behaviour. All questions until this point used 1-to-5-point Likert scales between opposite adjectives (e.g. 1: very-negative and 5: very-positive). The last item however, provided a list of nine attractions obtained from Visit Guildford and asked hosts to mark which ones they had visited. This measured experiential knowledge as proposed by Sharifpour et al. (2014), but it also assessed their level of objective and procedural knowledge as suggested by Alba and Hutchinson (1987).

The visitor's questionnaire enquired about several contextual aspects of the visits and asked participants about their experience using three items (overall experience of the visit, social experience with their host and touristic experience of Guildford) also using 1-to-5-point Likert scales. As noted earlier in the ‘Experience’ section, the study took an ‘outcome’ approach to measuring visitors’ ‘overall experience’ with single-item questions based on Bigne et al. (2005) and Huang and Hsu (2010). VFR travellers’ activities tend to be divided between spending time with their hosts and experiencing the destination (Shani and Uriely, 2012), hence, two separate items were included to evaluate visitors’ social and touristic experience.

Data collection

University of Surrey's graduating students and their visitors were chosen as the population for this study as students have been found to receive on average more visitors than other residents, which makes them ideal hosts for VFR research (Bischoff and Koenig-Lewis, 2007). Data was collected during the university's undergraduate graduation periods. Groups of graduates and their guests were approached by the first author while waiting for their ceremonies and were asked to answer a self-administered questionnaire that took between 4 and 8 minutes. Self-administered questionnaires were the most suitable option to simultaneously survey hosts and their visitors with different questionnaires, while also decreasing the interference from the data collector. Over 32 graduation ceremonies, 458 dyads of questionnaires were collected with a response rate of 75%.

Findings

Sample profile, missing data and normality

The sample of hosts was composed of 54% females and 46% males, while the population 56% females and 44% males, which suggest the sample is representative. In terms of hosts’ origin, 88% were domestic students, 11% EU and 1% international, which also appears representative when compared to 89% domestic and 11% of EU students in the population if international students are not included. The lack of international students in the sample is probably due to less of them attending graduation, or their visitors (if present) having a language barrier. This bias was not seen as problematic because measuring mostly one cultural group (British/European) decreases the risk of cultural bias. Moreover, domestic students are more under-represented in VFR research than international students, despite being a far larger group that receives substantially more visitors (Bischoff and Koenig-Lewis, 2007). There is no fixed frame to compare the sample of visitors, however, around two-thirds of them (72%) were relatives, which is not unusual according to Backer and Hay (2015).

Dyads of questionnaires with more than 5% of answers missing were excluded (Field, 2024) and there was no imputation of data. This was equivalent to only 6.5% of all cases (30 dyads), fatigue bias might be associated to these cases. Three unengaged participants were removed based on cases that had standard deviation of zero as recommended by Field (2024). From the 458 dyads collected this left a total of 425 usable cases. All the questions had Skewness and Kurtosis within the cut-off points of 2 and −2 (Table 1), which suggests data is normally distributed (Field, 2024). Mardia's critical ratio (7.755) implies data is mildly non-normal from a multivariate perspective, however in sample sizes over 200 this level of non-normality is negligible (Hair et al., 2023).

Table 1.

Normality and descriptive statistics.

Constructs and items	Mean	Standard deviation	Skewness (standard error.118)	Kurtosis (standard error.236)
Motivation to host
Q1-Host_motivation_to_encourage_visits	3.6	1.2	−0.631	−0.268
Q2-Host_motivation_to_show_the_area	3.6	1.0	−0.393	−0.343
Hosts’ destination image
Q3-Hosts’_overall_destination_image	4.2	0.7	−0.752	0.461
Q4-Hosts'_opinion_of_local_attractions	3.1	0.8	−0.055	−0.087
Q5-Hosts'_opinion_about_living_in_Guildford	4.1	0.8	−0.642	0.224
Hosts’ destination knowledge
Q6-Hosts'_overall_ destination_knowledge	3.4	0.9	−0.322	−0.296
Q7-Hosts'_knowledge_of_local_attractions	3.1	0.9	0.069	−0.253
Q8-Hosts'_experiential_knowledge*	2.3	0.7	0.793	0.683
Visitors’ experience
Q9-Visitors'_overall_experience	4.4	0.7	−0.717	0.006
Q10-Visitors'_overall_social_experience	4.3	0.8	−0.927	0.594
Q11-Visitors'_overall_tourist_experience	3.8	0.9	−0.338	−0.361

*Proportionally adjusted to a 1–5 scale.

Descriptive statistics

Destination knowledge received the lowest average scores from the three hosts’ constructs (see Table 1), which might be due to students being temporary residents (although 90% had lived in Guildford for 3 years or more) or lacking interest in learning and exploring the city. Yet, their overall destination image (Q3) and their image of Guildford as a place to live (Q5) have averages of 4.2 and 4.1, respectively, which implies that hosts had a positive or very positive opinion of Guildford, though potentially as a home more than a touristic area. Consequently, all the questions that asked hosts about the local attractions obtained the lowest scores of each construct. This could be expected as Guildford is not a well-known destination, but it could also be related with hosts’ lack of knowledge of the attractions as shown by Q7 and Q8 that measured their subjective and experiential knowledge of the local attractions and obtained the lowest scores in the survey. Visitors’ touristic experience also obtained the lowest scores of the visitors’ questions, however their overall experience was very positive obtaining the highest results in the whole survey.

Standard deviation was similar across the items that measured constructs associated to the destination (knowledge, image and experience) with values between 0.7 and 0.9, but it was higher for the two questions measuring ‘motivation to host’ (Q1:1.2, Q2:1.0). Hosts appear to have more differing feelings towards hosting especially towards ‘encouraging visits’ (Q1:1.2), which seems to be a more personal trait less affected by the destination's characteristics. Motivation to host also received low average scores, so there is a substantial number of students who are either apathetic or do not want to host visitors.

Constructs dimensionality

Two exploratory factor analyses (EFA) were performed using principal component analysis and Varimax rotation to test hosts’ and visitors’ constructs associations. Based on Field (2024) the initial evaluation of the host's questionnaire confirmed the data is adequate for EFA (KMO 0.753 > 0.5 and Bartlett's sphericity significant at 0.000). The EFA shows that there are three clear hosts’ components with eigen-values over 0.7 according to Jolliffe's (1986) criteria (see Table 2). Jolliffe was chosen over Kaiser's criteria due to the low number of items and that one component (motivation to host) has only two items. This was confirmed using a scree-plot as advised by Field (2024).

Table 2.

Rotated components matrix.

Questions	Components
	1	2	3
	D.Image	Knowledge	Mot.Host
Q1-Motivation_to_encourage_visits			0.908
Q2-Motivation_to_show_the_area			0.773
Q3-Overall_destination_image	0.841
Q4-Opinion_of_local_attractions	0.701
Q5-Opinion_about_living_in_Guildford	0.805
Q6-Overall_destination_knowledge		0.776
Q7-Knowledge_of_local_attractions		0.833
Q8-Experiential_knowledge		0.747
Cronbach-alpha	0.728	0.725	0.735
Eigen-value	3.215	1.361	0.971
Percentage of variance explained	25.5	24.5	19.4

These three components explained 69.4% of the total variance, which is acceptable according to Field (2024). After the Varimax rotation, components 1, 2 and 3 accounted for 25.5%, 24.5% and 19.4% of the variance, respectively, that represents an equilibrated result and fit well with the rationale behind the development of the questions. The items’ communalities are between 0.56 and 0.84 and no collinearity was observed as no correlation exceeded 80% (Field, 2024). All the loadings are above 0.40, which satisfies convergent validity and there are also no correlations or cross-loadings above the threshold of 0.7 (Field, 2024). The Cronbach’s alpha measurements had values above the threshold of 0.5 for the three components (Field, 2024).

In the visitor's questionnaire questions 9, 10 and 11 that measured visitors’ experience were used to conduct the EFA. The initial evaluation (KMO 0.669 > 0.5 and Bartlett's sphericity significant at 0.000) showed the data is adequate (Field, 2024). The EFA confirmed that the three items are part of just one latent variable that explains 64.3% of the total variance and has an eigen-value of 1.930. The communalities are between 0.58 and 0.69 that is also seen as adequate (Field, 2024). The EFA provided just one component, hence there is no ‘rotated matrix’. The component matrix, shows loadings ranging from 0.76 to 0.83, which are also deemed as adequate by Field (2024). The Cronbach's alpha indicator of the visitors’ experience is 0.709, which is above the cut-off point of 0.5 and indicates good internal consistency (Field, 2024).

Measurement model

Confirmatory factor analysis (CFA) using maximum likelihood (ML) estimation assessed the constructs’ validity and reliability in the proposed model. Unlike EFA where items are free to associate, CFA tests the variance shared between constructs and items under a fixed structure justified by theory (Hair et al., 2023). Therefore, the structured relationships were tested using several fitness indices, ratios and loadings summarised below in Tables 3 to 5.

Table 3.

Factor loadings, validity and reliability measurements.

Constructs and items	Stand. loadings	Composite reliability	AVE	MSV
Motivation to host		0.759	0.622	0.358
Q1-Host_motivation_to_encourage_visits	0.62
Q2-Host_motivation_to_show_the_area	0.93
Hosts’ destination image		0.739	0.5	0.358
Q3-Hosts'_overall_destination image	0.79
Q4-Hosts'_opinion_of_local_attractions	0.63
Q5-Hosts'_opinion_about_living_in_Guildford	0.69
Hosts’ destination knowledge		0.748	0.493	0.179
Q6-Hosts'_overall_destination_knowledge	0.72
Q7-Hosts'_knowledge_of_local_attractions	0.82
Q8-Hosts'_experiential_knowledge	0.53
Visitors’ experience		0.726	0.472	0.075
Q9-Visitors'_overall_experience	0.79
Q10-Visitors'_overall_social_experience	0.67
Q11-Visitors'_overall_tourist_experience	0.59

AVE: average variance extracted; MSV: maximum shared variance.

Table 4.

Square root of AVE and standardised correlations.

Factors	H._Dest.Image	H._Knowledge	Mot._to_Host	V._Experience
Hosts’_Dest._Image	0.707
Hosts’_Dest._Knowledge	0.424**	0.702
Motivation_to_Host	0.598**	0.419**	0.788
Visitors’_Experience	0.225**	0.275**	0.225**	0.687

**=p < .01.

AVE: average variance extracted.

Table 5.

Fitness indices and advised thresholds by Jackson et al. (2009).

Most common fitness indices	CFA model	Threshold
Chi-square/df (Cmin/df)	2.099	<3
Chi-square p-value	0	>.05
Comparative-fit-Index	0.966	>.9
Tucker–Lewis Index	0.951	>.9
Adjusted-GFI	0.942	>.9
Goodness-of-Fit-Index (GFI)	0.967	>.9
Standardised root-mean-square residual	0.037	<.08
Root-mean-square residual	0.029	<.05
Root-mean-square error of approx.	0.051	<.06

CFA: confirmatory factor analysis.

Table 3 shows that composite reliability (CR) values are over the suggested threshold of 0.7 in all factors (Hair et al., 2023), confirming the Cronbach's alpha seen in the previous section and adding evidence of internal consistency. All the factor loadings are above 0.4 that implies acceptable convergent validity (Hair et al., 2023). However, the average variance extracted (AVE), which also tests convergent validity, is just under the standard threshold of 0.5 in two factors (0.493 and 0.472). According to Fornell and Larcker (1981) though, AVE is often too stringent and a threshold of 0.4 is more appropriate if CR is over 0.6, as seen in this model. Moreover, Table 3 shows that the maximum shared variance (MSV) is lower than the AVE that according to Hair et al. (2023) suggests adequate discriminant validity between the factors.

Table 4 presents the square root of AVE and the standardised correlations between the factors where no value is over the threshold of 0.8, which implies good discriminant validity (Hair et al., 2023). Additionally, according to Hair et al. (2023) the square roots of AVE should be larger than the correlations between the constructs, as seen in this case also suggesting acceptable discriminant validity. Linearity was confirmed by inspecting bivariate scatterplots for each of the relationships as suggested by Hair et al. (2023).To assess the model's fitness Table 5 presents a selection of the most frequently used indicators based on Jackson et al. (2009). The model performs well under all the indices demonstrating a good level of fitness, the only exception is the Chi-square p-value that according to Hair et al. (2023) should not be considered in large samples. As a result, no variable was deleted nor adjusted.

Structural model

All the factor loadings and fitness indices presented in the CFA remained unchanged (Tables 3 and 5), which suggests good construct validity as it means that there is no interpretational confounding (Hair et al., 2023). The results can be seen in Table 6, all the relationships between the host's constructs were significant (H1, H3 and H5) and only destination knowledge has a significant path to the visitors’ experience (H4). Hosts’ destination image (H2) and motivation to host (H6) link to visitors’ experience were not supported by the data. The lowest path scores were seen in the relationships between the host's constructs and their visitors’ experience, which makes noticeable the differences between testing constructs’ relationships in single or different individuals. There was no clear mediation effects observed between hosts’ and visitors’ constructs.

Table 6.

Hypotheses and coefficients.

Hypothesised relationships		Stand. estimate	Stand. error	Critical ratio
H1	Host_dest_image→Motivation_to_host	0.512**	0.10	6.093
H2	Host_dest_image→Visitors_experience	0.087(.33)	0.08	0.983
H3	Dest_knowledge→Host_dest_image	0.424**	0.06	6.452
H4	Dest_knowledge→Visitors_experience	0.201**	0.06	2.703
H5	Dest_knowledge→Motivation_to_host	0.202**	0.07	3.188
H6	Motivation_to_host→Visitors_experience	0.088(.28)	0.06	1.071

**p < .01, (p)=p > .05.

Discussion

Figure 3 presents a diagram of the model with the path's standardised coefficients and the status of each hypothesis. There are two clear groups in the model: the paths between hosts’ constructs, therefore measured in single individuals; and the paths linking hosts’ constructs and their visitors’ experience, thus measured between different individuals. All the hypotheses tested within single individuals/hosts (H1, H3 and H5) were significant with moderate to strong coefficients, but the associations between separate individuals, hosts’ and their visitors (H2, H4 and H6), exhibited much lower coefficients and two non-significant hypotheses. This indicates that constructs’ interpersonal connection when measured in dyads is much lower than the constructs’ relationship within the same person, which is a fundamental difference that can strongly affect results and is one of the study's contributions. Hence, this section is divided into these two groups, starting with the paths measured within the host's constructs.

Figure 3.

Model with path coefficients.

Hosts’ constructs relationships

The first hypothesis in this group (H1) is the path between hosts’ destination image and their motivation to host, which is the strongest association in the model (0.512**). This is one of the main assumptions behind VFR marketing when aiming to attract visitors (Backer and Hay, 2015; Morrison et al., 2000), and it was also noted by Schroeder (1996), Stylidis et al. (2017a) and Stylidis et al. (2022) who observed that residents’ positive destination image increased their willingness to recommend the destination. This study can strengthen those findings, which adds validity to the survey and further support for current VFR marketing theory and practice.

The loadings in the dependent variable however, provide a new perspective on the phenomenon. The concept of ‘motivation to host’ was composed of two questions with different loadings (see Table 3). Question 1 asked hosts if they encourage visits and has a considerably lower loading (Q1:0.62) than question 2 that measured hosts motivation to show the area (Q2:0.93). This means that hosts’ destination image has a stronger influence on motivating locals to become better ‘tour-guides’, than on their willingness to attract visitors. As discussed in the ‘Descriptive statistics’ section (descriptive statistics), this is compatible with the idea that encouraging visits is a more personal trait (wanting or not to see friends and family) that is less associated to residents’ perception of the destination. This effect might have been exacerbated by students’ relatively short-term residency at the destination (compared to long-term resident-hosts) and their lack of experience hosting, which might have negatively affected their level of knowledge and motivation to receive visitors. Nevertheless, the idea that hosts’ main motivation to attract visitors is their emotional connection and not the destination's characteristics, or in this case students’ perception and knowledge of it, has also been suggested by Munoz et al. (2017) and observed by Bakri et al. (2024) and Gafter and Tchetchik (2017) with different samples of hosts.

The second hypothesis in this group is the path between hosts’ destination knowledge and their own destination image (H3), which is the second strongest relationship in the analysis (0.424**). These findings support some of the ideas behind the development of VFR marketing campaigns, in particular the assumptions that if residents are educated about the destination their image will also improve (Backer and Hay, 2015; Dutt and Ninov, 2017). Consequently, authors like Baloglu and McCleary (1999) and Stylidis et al. (2022) found that destination knowledge often as ‘information sources’, has a positive influence on the same person's destination image. Therefore, the findings from this research also support this idea adding validity to the study.

The last hypothesis in this group (H5) tested the influence of hosts’ destination knowledge on their motivation to host, obtaining a direct effect of 0.20** and an indirect effect through hosts’ destination image of 0.216**, which adds to a total effect of 0.420 (p-value 0.016). These results also support the assumptions of VFR marketers that residents tend to be more motivated to host when they get to know more about their destination. However, similarly to H1 the loadings in the ‘motivation to host’ construct suggest that learning about the local attractions has a stronger effect on hosts’ motivation to show the area (Q2:0.93 associated with becoming better ‘tour-guides’), instead of trying to attract more visitors (Q1:0.62), which seems to be a more personal/emotional need to see friends and family, and is different to the beliefs of most VFR marketers (Backer, 2014; Morrison et al., 2000).

Hosts’ and visitors’ constructs relationships

In the second group of hypotheses, destination knowledge (H4) was the only significant host's construct affecting visitors’ experience (0.20**). This result suggests that hosts’ destination knowledge is the most important attribute that DMOs should consider when trying to influence visitors’ experience through the residents. Thus, Destination Melbourne's manager in Backer (2014, p. 6) stated that ‘hosts’ local knowledge can influence the VFR experience much more than any destination marketing campaign’.

The mechanism through which hosts’ destination knowledge influence their visitors’ experience has not been explored in VFR research. However, based on the qualitative findings from Humbracht (2015), Humbracht et al. (2022) and Shani and Uriely (2012), it could be argued that this is associated to hosts becoming better ‘group leaders’ or ‘destination experience mediators’. Accordingly, Humbracht (2015, p. 649) called hosts ‘semi-autonomous tourist agencies’ because when receiving visitors, they ‘package their local context, daily lives and knowledge of place into tourist experiences’. In which case, better or more destination knowledge is translated into a better ‘interpretation of the place’ and a better or wider selection of local attractions that could then lead to improving visitors’ experience.

Between the three questions that measured destination knowledge, hosts’ knowledge of the local attractions received the highest loading (Q7: 0.82) compared to the overall knowledge of the destination (Q6: 0.72) and experiential knowledge (Q8: 0.53). Hosts’ knowledge about the local attractions is a key element and confirms further assumptions of VFR marketing. For example, Mildura's, Australia VFR campaign manager argued that ‘after the residents became much more aware of the town's attractions they acted as knowledgeable tourism marketing ambassadors’ (Backer, 2014, p. 6). Similarly, Morrison et al. (2000) also suggested educating the residents about the local attractions.

In practical terms this would be an important element to improve for Visit Guildford, the local DMO, because hosts’ destination knowledge received the lowest scores in the model. This might be due to students’ busy schedule, lack of interest or that most of them tend to live in the town for only 3 years, which may not be sufficient for them to gain a better knowledge of the local attractions (e.g. Stylidis, 2012; residents lived on average 32 years in Kavala, Greece). Considering the impact that hosts’ destination knowledge can have on their visitors’ experience, it should be imperative for DMOs with large numbers of short-term residents (e.g. students) to increase their level of knowledge soon after their arrival.

Conversely, in H2 hosts’ destination image was not found to have a significant influence on their visitors’ experience (0.087, p-value 0.29). This relationship was backed by an extensive amount of research that has shown that travellers’ destination image has a positive impact on their experience (Bigne et al., 2005). However, this relationship has always been measured in the same individuals (tourists), which is different from measuring constructs’ associations in host–guest dyads. Therefore, the way in which destination image affects experience changes, making these findings a good example of how dissimilar the interaction between constructs can be, if these are measured within one person or between different individuals. In practice VFR marketers generally also expect this relationship to be significant between hosts and guests (see the second section), but as discussed in H4 the mechanism through which this should happen has not been studied. Based on the view of hosts as ‘tour-guides’, these results imply that a more positive interpretation of the place does not directly influence visitors’ experience, but a more ‘knowledgeable’ interpretation and a better selection of attractions have a stronger impact on their experience as seen in H4.

The last hypothesis in the model is the link between motivation to host and visitors’ experience (H6), which was not supported by the data (0.088, p-value 0.284). This could also be related to the mechanism that associates hosts’ destination knowledge (H4) and destination image (H2) with their visitors’ experience. In this case, it could be argued that if residents are more motivated to host, their ‘interpretation of the place’ would be better, as well as, the quantity and quality of the attractions shown to their guests, which would lead to a better visitors’ experience. Nonetheless, hosts’ interpretation and choice of attractions are more associated to their destination knowledge and to some extent also to their destination image. Therefore, those two constructs explained all the variance in the visitors’ experience that ‘motivation to host’ could have explained.

As noted earlier all these effects might have been intensified by students’ short-term residency at the destination, and thus their potential lack of knowledge about it compared to longer-term residents. This could have increased the impact of any destination knowledge on their visitors’ experience, and particularly their knowledge about the local attractions, which is crucial for performing tourism activities. It could be expected then that in populations of long-term resident-hosts with higher levels of destination knowledge the construct would have less influence on visitors’ experiences. This however, would not be due to the construct having a lower impact on visitors’ experience, but to the fact that with higher levels of destination knowledge there's less variability in the construct's measurement and consequently less space for improvement as long-term residents might have almost full knowledge of the destination. Although, for DMOs this is an important issue to take in consideration, the findings of the study remain relevant for groups of residents with lower levels of destination knowledge. As a result, students are a particularly valuable target for destination marketing, because educational initiatives could generate greater improvements in their visitors’ experience, whereas the marginal benefits of increasing destination knowledge among long-term residents may be more limited.

Theoretical and practical implications

The model's measurement shows that hosts’ destination knowledge, and particularly hosts’ knowledge of the local attractions, has a direct impact on their visitors’ experience, perhaps through the hosts becoming better ‘tour-guides’ or ‘group leaders’, which includes a better ‘interpretation of the place’ and selection of attractions. Although for some DMOs, educating residents about the local attractions was already one of their main approaches to VFR, the practice was not based in previous research and it is not widely spread (Backer, 2009; Backer and Morrison, 2015; Morrison et al., 2000). Therefore, the findings provide more certainty that DMOs efforts will reach the visitors, helping them to justify spending on VFR in front of tourism boards, which according to Backer (2009) and Backer and Morrison (2015) is one of DMOs problems when requesting funds to target the VFR market.

In the specific case of Guildford for example, the study showed that although residents’ destination knowledge is key for their visitors’ experience, it was also the construct that obtained the lowest scores. This suggests that destination knowledge might be even more important for less recognised destinations or towns/cities with large groups of new or short-term residents (e.g. students and immigrant communities). To counter this, DMOs should investigate residents’ level of destination knowledge, and target new and ‘destination illiterate’ residents with educative interventions and campaigns. For university cities local DMOs and the university should work together to target new students, through marketing material, student media, free tours, events and residents’ discounts in specific attractions for them to gain experiential learning of the destination.

The model proposed a new construct ‘motivation to host’ that combines two key aspects of hosts’ attitude towards the act of hosting (attracting visitors and acting as pseudo-tour-guides), which is crucial in the VFR phenomenon. Thus, the study showed that hosts’ knowledge and image of the destination have a positive effect on their ‘motivation to host’ as expected by previous research. The model however, offered a new perspective by noting that knowledge and image have a stronger impact on hosts’ motivation to show the area (becoming better pseudo-tour-guides), than on hosts’ motivation to attract visitors, which seems to be a more personal/emotional trait. Therefore, if DMOs aim is to increase visitation, their marketing should focus more on residents’ emotional connection with their family and friends than on their destination knowledge, which is more likely to improve visitors’ experience but not to motivate hosts to push them to visit. This for example was done successfully by Victoria's V/Line ‘Guilt Trips’ where the residents of small towns in Victoria, Australia were ‘taught’ how to make their relatives (often adult children) feel ‘guilty’ for not visiting (Backer, 2014). In terms of Backer's (2008) definitional typology, this is particularly relevant for attracting VFR travellers whose main purpose is to see their hosts instead of the destination (labelled as commercial and pure VFRs), which is often the type of visitor to less well-known destinations, such as many university cities. In terms of hosts’ and visitors’ characteristics based on Yousuf and Backer (2017) and Zentveld and Yousuf (2022), DMOs should also focus on residents’ relatives and potentially immigrant communities where the strength of host–guest emotional connection is stronger than the natural pull of the destination.

Finally, in methodological terms collecting data in pairs of related individuals (dyads), which is rare in tourism research due to its practical difficulties, shared new light into the ways in which common tourism concepts interact. For example, in this case hosts’ destination image was found not to significantly affect visitors’ experience, although, there is a vast amount of research that support this relationship when measured in single individuals. Tourism is an extremely social phenomenon where participants often affect each other experiences, hence for researchers this means that is important to conduct more dyadic research to evaluate construct relationships between individuals that generally have been assumed to exist based on research in single individuals. For DMOs this is a call for caution and to consider collecting data in dyads where is necessary to know how individuals influence each other, such as families and couples affecting each other's decisions, residents affecting visitors and tourism providers affecting customers.

Conclusion

VFR is one of the largest tourism segments offering several benefits to the local economies, yet is also one of the more neglected areas in tourism marketing, which is partly due to the lack of understanding of its unique characteristics such as the important role that hosts plays in the phenomenon (Zentveld et al., 2022).

This study aimed to fill this gap by exploring how hosts’ key characteristics affect their visitors’ experience, which is a question at the core of the VFR phenomenon. For researchers this is useful to better understand the phenomenon and explore more specific areas of host–guest's interactions, while for DMOs the findings can help to better choose, direct and justify their marketing efforts towards the VFR market.

More specifically, the model's measurement noted the importance that hosts’ destination knowledge has on their visitors’ experience, while residents’ destination image only affected their own motivation to host. This goes against a wide body of literature that based on measurements on single individuals assumed that hosts’ destination image would positively affect their visitors’ experience, which calls for further dyadic research to measure construct relationships in separate individuals. Furthermore, destination knowledge and image showed to have a stronger impact on hosts’ motivation to act as pseudo-tour-guides, instead of their motivation to attract visitors, which is more related to their emotional connection with family and friends. Finally, the study presented an innovative methodological approach tailor-made to VFR's unique needs and characteristics. Dyadic research has shown to be a promising approach for measuring construct relationships between individuals, which is a common yet underexplored phenomenon in tourism scholarship.

Limitations and future research

The study proposed a novel approach in VFR that involved a series of challenges not tackled by previous studies, hence, there are several limitations to consider and new avenues for future research.

Guildford was an ideal location for the project, and graduation periods were excellent for surveying large numbers of hosts alongside their visitors. However, collecting cross-sectional data in just one destination and group of participants restricts the generalisability of the results. More research ideally using longitudinal data in different destinations and types of participants is necessary to further test the theoretical model. Thus, developing new means to survey hosts and their guests in large numbers across time would be a valuable improvement. Accordingly, it would be useful to test for example how accurate can hosts describe their visitors’ feelings and opinions, to facilitate measurements.

In terms of locations, it would be valuable to test the model in destinations with various characteristics, such as, well-known locations to evaluate the effect of pre-conceptualisations and expectations of the destination. In terms of population, the sample tended to survey close relatives of domestic students due to the nature of the graduation ceremonies, missing to include factors that have been shown to strongly affect VFR experiences, such as participants’ relationship (visiting friends vs. relatives) and their origin (local vs. immigrant), as suggested by Yousuf and Backer (2017) and Zentveld and Yousuf (2022). Furthermore, Backer (2008) definitional typology showed that visitors main purpose of travel also strongly affects VFR experiences. In this case most visitors in the sample were likely ‘pure’ or ‘commercial VFRs’ because the sample was mainly composed of relatives (72%) and Guildford is not a well-known destination, so most visitors’ main purpose was to see the students. Hence, it would be valuable to investigate how VFR travellers with other purposes, for example EFRs, would be affected by their hosts. Moreover, the study would have benefited from further exploring the domestic student VFR market in terms of literature and data, as it is greatly under-research, although it represents a substantial number of visitors for university cities.

Overall, more research is needed to understand how individuals influence each other's experiences and opinions particularly from a quantitative perspective, which is greatly under-researched in tourism due to the practical difficulties it implies. This study for example noted the need to re-evaluate destination image relationships with other constructs when measured in related individuals. Moreover, there is great need to research the reciprocal (non-recursive) nature of the relations between constructs within and between individuals, which is also seriously neglected, although, most construct relations in tourism are rarely purely one-directional.

Footnotes

Acknowledgements

We thank Professor Margaret Deery for her support and advice developing this project.

ORCID iDs

Julio R Munoz

Albert N Kimbu

Jason Chen

Ethical considerations

University of Surrey Ethics Committee research protocol number 160708-160702-11905725.

Consent to participate

Respondents gave written consent for review and signature before starting interviews.

Author contributions

Julio Munoz: Conceptualisation, data curation, formal analysis, methodology, investigation, writing, review and editing.

Albert N Kimbu: Supervision.

Jason Chen: Supervision.

Funding

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

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability statement

The datasets generated and analysed during the current study are available from the corresponding author on reasonable request.

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