1 Introduction

In tourism literature, destination branding and social media are appeared as important elements regarding the tourists visit behavior but these constructs are quite distinct. Destinations in particular are considered as brands and treated as competitive positioning tools which lead the destination towards customers’ preferences and motivate them to choose even though they have not experienced it before (Pappu et al. 2007; Morgan et al. 2002) but nevertheless, researchers are agreed on the fact that destination-based branding is complicated to establish due to certain reasons such as administrative difficulties, high number of stakeholders involved, diverse offerings, targeting hybrid segments and involvement of many suppliers (Im et al. 2012; Boo et al. 2009; Pike 2005; Morgan et al. 2004; Dredge and Jenkins 2003; Gnoth 2002). Additionally, once a brand name is established, the assessment of branding is another challenge. In tourism industry, the success of branding is widely measured through brand equity (Pike and Page 2014). Brand equity falls into three types: financial, sales-based and customer-based. Marketing researchers have utilized the customer-based brand equity (CBBE) model for measuring brand names.

In response to the call for measuring brand names in the tourism industry, an extensive body of literature has been produced on measuring destination branding by employing the CBBE model (see, for example, Dedeoğlu et al. 2019; Pike and Bianchi 2016; Shafaei and Mohamed 2015; Bianchi et al. 2014; Kladou and Kehagias 2014; Im et al. 2012; Horng et al. 2012; Ferns and Walls 2012; Evangelista and Dioko 2011; Bianchi and Pike 2011; Gartner and Ruzzier 2011; Pike et al. 2010; Chen and Myagmarsuren 2010; Pike 2010; Boo et al. 2009; Kim and Moon 2009; Pike 2009; Konecnik and Gartner 2007; Pike 2007). These studies examined the CBBE model within specific destinations. Undoubtedly, previous destination branding studies have contributed to the literature significantly. Nevertheless, these studies were only measuring the effectiveness of branding, and it is worthwhile examining to what extent destination branding stimulates tourists’ behavior to visit the destination. Four dimensions are commonly used by researchers for the CBBE model (Aaker 1996; Keller 2003). These are brand awareness, brand image, brand quality and brand loyalty. Therefore, this study has used these four dimensions for the CBBE model as destination brand awareness, destination brand image, destination brand quality, and destination brand loyalty.

The other important construct in tourism literature is social media and according to Cox et al. (2009), almost 80% of tourists depend on social media information to plan a trip, collect information, and carefully consider the travel reviews by other tourists (Murphy and Chen 2014). A significant body of literature has been generated by researchers about the influence of social media on decision-making regarding a trip and they have confirmed the significant role of social media on tourism decisions as it provides a common platform for tourists that leads to social interactions based on shared interests and experiences (Gohil 2015; Zeng 2013; Hudson and Thal 2013; Fotis et al. 2012; Sigala et al. 2012; Ayeh et al. 2012; Verma et al. 2012; McCarthy et al. 2010; Cox et al. 2009; Buhalis and Law 2008). However, although the role of social media is important at every stage of decision-making, it is more critical and influential at the pre-travel stage, as this is the stage when tourists consult social media for planning their trip (Zeng 2013; Cox et al. 2009). Additionally, it is the stage where tourists’ perceptions of a destination are built up. Despite the contribution of the literature, however, these studies are only exploring the role of social media at the decision-making stages and are ignoring the contingent role of social media between the relationship of CBBE and destination visit behavior. The use of social media is seen to be individualistic and personal component as compared to CBBE. As a result, its possible role as a moderating variable in tourism between CBBE and visit behavior appears to have received less attention. A deeper understanding of interactions among CBBE, tourists visit behavior and social media should go a long way in presenting a holistic understanding of tourists’ visits.

The present study contributes to the literature in three ways. Firstly, it explores the impact of destination branding on visit behavior. In other words, it examines the CBBE at first stage and then identify the role of CBBE in initiating the tourists visit behavior. Secondly, it identifies the contingent role social media between CBBE and visit behavior as researchers argued that the use of social media is dictating the tourist’s decision making regarding their visit behavior. Lastly, the context of this study has a valuable contribution as the Pakistan’s tourism sector recently received an impetus due to improved security conditions. According to recent reports, domestic and international tourists have been continuously increasing in Pakistan for the last five years. Previously, Pakistan was listed as being among those countries which suffered badly from terrorism and consequently the tourism industry faced a major setback in the last decade. Meanwhile, foreign tourists preferred to visit Middle Eastern countries and Malaysia due to the better security conditions over there. In contrast, nowadays, keeping in mind the improved security conditions and continuous increase in tourism, it is important to analyze how social media plays a role in forming the actual behavior of tourists. Hence, the purpose of this study is to examine the impact of CBBE on destination visits with the contingent role of social media among international tourists (Fig. 1).

Fig. 1
figure 1

Conceptual framework

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2 Literature review

2.1 Destination brand awareness and destination visit behavior

Brand awareness is of primary importance in the CBBE model as it aims to build the unique name of the brand (Jago et al. 2003). Buil et al. (2013) and Balduaf et al. (2003) explain that the reason for its primary status is that it is the component which is solely responsible for creating and maintaining the awareness of a brand, which further develops positive feelings about the brand, and this in turn increases the possibility of destination visit behavior. Brand awareness is considered a main component of a brand’s performance in the tourism industry (Lee and Back 2008; Konecnik and Gartner, 2007; Kim and Kim 2005; Oh 2000). Previously, it was examined in different ways: cognitive image (Boulding 1956), and induced image (Gartner 1994), and recognition, recall and top-of-mind (Aaker 1996). The top-of-mind awareness means that in the consumer’s mind, a particular brand is at first place as compared to other similar brands. This awareness level has been chosen for this study. Previously, it was found that any kind of awareness perception by tourists could affect their actual visit behavior (Kwun and Oh 2004; Oh 2000; Webster 2000; Sivakumar and Raj 1997; Belonax and Javalgi 1989). Therefore, on the basis of the above discussion, the following hypothesis has been developed:

H1

Destination brand awareness positively affects destination visit behavior

2.2 Destination brand quality and destination visit behavior

CBBE models are incomplete and do not present a holistic understanding of brand performance without brand quality (Keller 2003; Aaker 1996; Lassar et al. 1995). The concept of brand quality and perceived brand quality are used by researchers interchangeably (Aaker 1996; Zeithaml 1988). In line with brand image, the brand quality construct also has a complex nature. Keller (2003) identified seven categories of brand quality: namely, performance of the brand, features, conformation quality, reliability, durability, serviceability, and style and design. Among all of these, the brand performance dimension is the most important and reflects the meaning of brand quality within the context of tourism. Destination brand performance is relatable to the functional needs of tourists (Keller 2003); moreover, brand performance is a determinant of brand equity (Lassar et al. 1995). In this study, the meaning of destination brand quality is the actual brand performance. The brand performance of a destination includes the environment and service infrastructure (Williams et al. 2004; Buhalis 2000; Murphy et al. 2000). The positive perception of brand performance increases the probability of actual behavior. Indeed, it is observed in the previous studies that the perceptions of quality affect the actual behavior positively (Kim et al. 2008; Cronin et al. 2000). In this regard, the hypothesis regarding the relationship is developed as follows:

H2

Destination brand quality positively affects destination visit behavior

2.3 Destination brand image and destination visit behavior

Generally, brand image is considered to be the perceptions attached by consumers to specific brands, based on reasoned and emotional perceptions (Keller 2003; Dobni and Zinkhan 1990). Blain et al. (2005) argue that the definition of a destination is not complete without the image of the destination. In other words, destination definitions are usually derived from their image. On the other hand, brand image is an important component of CBBE models as well (Aaker 1996). Therefore, many CBBE models that are applied by researchers in the tourism industry include the destination brand image as a dimension (Konecnik and Gartner 2007; Kim and Kim 2005; Cai 2002). Additionally, due to its importance, variation in definitions and complex nature of this construct, there is some confusion regarding the measurement of this dimension, and therefore, previous researchers used different measurement approaches (Tsai 2005; Low and Lamb 2000; Lassar et al. 1995; Dobni and Zinkhan 1990). The brand image scales in the literature are based on different philosophies, such as the consumer’s perception of social approval (Tsai 2005), self-image (Grace and O’cass 2005), multi-dimensional construct (Martınez and de Chernatony 2004), and social image (Lassar et al. 1995). This study has used brand image as destination brand image within the scope of social-image and self-image of a brand (Grace and O’Cass 2005; Sirgy and Su 2000; Kapferer 1997; Lassar et al. 1995). It is argued by the researchers that brand image is built on brand personality, which is the reflection of both social-image and self-image of the brand (Hosany et al. 2006; Phau and Lau 2000; Patterson 1999; Upshaw 1995). On the other hand, some researchers believed that consumers derive a brand image from their self-concepts (Solomon 1999; De Chernatony and Dall’Olmo Riley 1998; Aaker 1996; Belk 1988). Pitt et al. (2007) argued that branding is the process of creating a brand image that engages the hearts and minds of consumers, and research supports a positive relationship between brand image and consumer actual behavior (Cretu and Brodie 2007; Tsai 2005; Michell et al. 2001). Accordingly, a hypothesis is developed as follows:

H3

Destination brand image positively affects destination visit behavior

2.4 Destination loyalty and destination visit behavior

The last component of the CBBE model is the brand loyalty of the customer (Aaker 1996). Lassar et al. (1995) showed that actual brand loyalty is the confidence of the consumer in brand performance, and as a result, consumers place the brand at a higher-level brand as compared to those of competitors. Confidence is defined as the loyalty of consumers, and additionally, their willingness to pay a premium price for the desired brand. Nevertheless, brands strive to create brand loyalty. The operationalization of this construct in the previous literature showed that it is the main source of CBBE (Keller 2003), which reflects the attachment a customer has to a brand (Aaker 1996). The concept of brand loyalty has been regarded as an attitude or behavioral construct (Odin et al. 2001). However, the measurement of this construct in the relevant literature reveals a lack of clarity. Moreover, the available results in the literature showed inconsistent findings (Odin et al. 2001). Similarly, in tourism research, loyalty has a huge importance but still there is no widely accepted definition or measure available (Nininen and Riley 2004; Baloglu 2001, 2002; Oppermann 2000; Baloglu and Erickson 1998). In tourism, brand loyalty has been treated by some researchers as being a consequence of multi-dimensional cognitive attitudes (Back and Parks 2003), while others argued that brand loyalty affects a firm’s performance (Kim and Kim 2005). This study has limited brand loyalty to its attitudinal and behavioral elements and proposes a significant relationship between destination brand loyalty and destination visit behavior. Therefore, we hypothesize that:

H4

Destination brand loyalty positively affects destination visit behavior

2.5 The role of social media between CBBE and destination visit behavior

The influence of social media sites is strong but only because consumers impact each other’s decisions (Haywood 1989). It is undeniable that social media can have a significant impact on the tourist type of consumers in their decision-making (Fotis et al. 2012). A vast amount of literature is available on the influence of online reviews in final decision-making behavior (Murphy and Chen 2014; Vermeulen and Seegers 2009; Gretzel and Yoo 2008; Gretzel et al. 2007). The role of social media cannot be ignored within the context of the tourism industry as it makes this world a global village. Social media makes it possible for tourists to collect a wide range of information about their desired destination, whereas the pre-social media era had limited information about the available destinations (Hu and Wei 2013) and the only way to collect information for decision-making was through brochures, travel agents of tourist organizations, and independent travel agents (Baruca and Civre 2012). Since those sources have been largely replaced by social media, the latter is now the largest forum for gathering information regarding available places for tourism (Fotis et al. 2012) and tourists make decisions about their final destination based on the information collected from social media (Browning and Sparks 2013). Thus, on the basis of the above discussion the following hypothesis has been developed:

Social media moderates the link between destination brand awareness and the destination visit behavior of tourists

H5a

Social media moderates the link between destination brand awareness and the destination visit behavior of tourists

Social media is actually rebuilding or restructuring information for the purpose of making decisions (Sigala et al. 2012). This reconstruction of information by social media about the travel experiences of other tourists is not only within the context of destination beauty but about all related services and other matters (Sigala et al. 2012). As mentioned earlier, according to Cox et al. (2009) almost 80% of tourists depend on social media information in order to plan a trip and collect information from social media on accommodation by consulting online hotels; moreover, they carefully consider travel reviews by other tourists (Murphy and Chen 2014). It has been found that in this process of travel planning, social media especially provides support in the decision-making process of destination selection (Zeng 2013). Tourists as consumers believe that information on social media from other travelers regarding their experiences is trustworthy, as user-generated content (UGC) is a more trustworthy source of information as compared to any other information source provider such as official tourism websites, which may be biased. Travel agents are also not considered trustworthy, and similarly, mass media advertising also has trust issues (Fotis et al. 2012; Del Chiappa 2011). The assistance of social media in tourism has been widely accepted, although there is some debate about the power of user-generated content and not only its reliability but its genuineness have been questioned (Fotis et al. 2012; Cox et al. 2009). The influence of a source on decision-making is wholly dependent on the trustworthiness of that source (Lopez and Sicilia 2014). There was a time when hotel agents and guides were considered a credible source but they are no longer the main way of obtaining information on decision-making. Instead, social media has taken the place of a credible source by providing online reviews about tourist destinations and the facilities there, such as hotel availability, transportation, and other facilities. Nevertheless, it is the main reason behind the significance of the role of social media in assisting tourists who are consumers, at the stage of evaluating the alternatives. Therefore, based on the above discussion the following hypothesis has been developed:

H5b

Social media moderates the nexus between destination brand quality and the destination behavior of tourists

Advertisements can only be helpful in the pre-travel phase in which tourists actually make their decisions about the journey to be performed or not. In this process, tourists undergo four main stages: firstly, they consider their destination; secondly, they evaluate it on a self-developed criterion; thirdly, they decide whether to purchase or not; and if yes then lastly, they enjoy the decisions made (Court et al. 2009). However, there is another perspective which reveals that sometimes, as an alternative to systematically following their choice till they reach a final decision on whether to purchase, at the evaluation stage tourist-consumers add or subtract alternative brands from a pool of favorites already found and under consideration (Court et al. 2009). At this stage, tourist-consumers decide to search for information about the image of the proposed destination, and after searching they process the searched information from different perspectives, so as to reach the final purchase decision based on the needs identified. After collecting the information, they evaluate the available alternatives on self-developed criteria about the destination (Ayeh et al. 2012). This complete process indicates that it is not a selection of a destination (Baruca and Civre 2012) but more to check the image of the destination. The main difficulty is that destination selection is intangible in nature and the image of a country is also intangible, which is why the buying decision is a highly emotional one and could therefore be emotionally biased. Social media is primarily assisting consumers in filtering their choices based on the different criteria which may vary from one tourist to another (Gretzel and Yoo 2008). In this way, destinations reviews are very helpful for new tourists to consider their next option (Singh and Torres 2015). In this evaluation process, destination decisions are heavily affected by both negative and positive reviews by other tourists. In other words, both type of reviews create an awareness which may lead these consumers towards a change of attitude, whether positive or negative. (Vermeulen and Seegers 2009). For example, Verma et al. (2012) consider that when a destination has negative comments by tourists for any reason, it becomes a less likely choice of destination for prospective tourists to visit, while other researchers such as Almana and Mirza (2013) argue that good ratings and positive assessments about a destination could influence prospective tourists in their final decision and make them more likely to visit that particular destination. Therefore, on the basis of the above discussion the following hypothesis has been developed:

H5c

Social media moderates the association between destination brand image and the destination visit behavior of tourists

The credibility of social media is based on the honest reviews provided by the tourists and the fact that it publishes them rather than concealing them. It therefore includes both positive and negative reviews about a destination and displays them or publishes them online through review sites and blogs (Hudson and Thal 2013). Furthermore, after a visit, tourists use social media for sharing their travel-related experiences, communicating and building connections with other tourists around the world (Zeng and Gerritsen 2014), which leads to further awareness of a destination by other tourists. Thus social media information plays a significant role in the decision-making process of tourists, and has an influence on the dimensions of CBBE models. Thus, based on the above discussion the following hypothesis has been developed:

H5d

Social media moderates the relationship between destination brand loyalty and the destination visit behavior of tourists

3 Methodology

3.1 Sample and data collection

To investigate further hypotheses, predeveloped and validated scales have been adapted to measure destination brand awareness, destination brand quality, destination brand image, destination brand loyalty, destination visit behavior and social media. Data were collected from the Northern Areas of Pakistan due to its substantial role in the tourism industry. The literature mentions that every destination is different in certain ways such as each having its own particular characteristics, culture, environment and weather conditions (Boo et al. 2009) and so every destination must be treated as a separate identity while measuring the CBBE, and the measurement scales must be in accordance with that destination.

This study is focused on the Northern Areas of Pakistan. The tourism industry of Pakistan is currently experiencing a revival and so specific exploration is needed in order to assess it and to build the brand of Pakistan as a tourist destination: historically it was a tourist attraction and now further efforts are required to recover its identity as a beautiful destination in the world. This study has assessed the important indicators in the context of Pakistan about the potential of the tourism industry in the wake of massive security concerns. Therefore, it is suggested that all actors including government and private sector tourism need to explore the tourism industry by fulfilling the needs of tourists. Out of 180 questionnaires delivered to respondents through a convenience sampling technique, 160 were received back, making a response rate of 88.89%. Seven questionnaires were removed from the final sample due to incomplete responses, and so finally there were 153 valid responses.

3.2 Measures

Pre-developed and pre-tested scales are used to measure the constructs of the study. Destination brand awareness measured using 5-item scale developed by Fern and Walls (2012). Two sub-scales are used to measure destination brand quality, destination service quality and destination natural quality. Destination service quality is measured using 5-item scale developed by Washburn and Plank (2002) however destination natural quality is assessed through 8-item scaled adapted from Baloglu and McCleary (1999), Beerli and Martıń (2004), Ferns and Walls (2012), Narayan et al. (2008) and Dedeoğlu et al. (2019). Destination brand image is measure by 4-item scale adapted from Lassar et al. (1995) and Grace and O’Cass (2005). Destination brand loyalty is assessed through 6-item scale adapted from Kim and Moon (2009), Ryu and Han (2011), Zeithaml et al. (1996) and Su et al. (2017). Destination visit behavior is measured employing 3-item scale developed by Dedeoğlu et al. (2019). Social media is assessed by 11-item scale developed by Cox et al. (2009). Respondents’ responses were taken on a 5-point Likert-type scale, ranging from 1 for ‘strongly disagree to 5 for ‘strongly agree.’ The questionnaire had two sections: section one measuring the constructs relating to destination brand awareness, destination brand quality, destination brand image, destination brand loyalty, social media and destination visit behavior; while the second section measured the demographics of tourists.

3.3 Analysis

PLS-SEM was used to analyze the hypothesized framework. A confirmatory factor analysis (CFA) was carried out through a two-step approach (i.e. measurement model and structural model). PLS-SEM has an edge over other techniques because it does not require multivariate normal distribution of data, large sample sizes and interval scales (Chin et al. 2003; Lee et al. 2015). “PLS only requires a sample size of 10 times the most complex relationship within the research model that is the larger value between (1) the construct with the largest number of formative indicators if there are formative constructs in the research model [i.e. largest measurement equation (LME)]; and (2) the dependent latent variable (LV) with the largest number of independent LVs influencing it [i.e. the largest structural equation (LSE)]” (Peng and Lai 2012, p. 469). Since this research has a sample size of 153, variance-based SEM (PLS) is better than covariance-based SEM (AMOS etc.). Furthermore, “the iterative algorithm of a series of ordinary least square analyses in PLS is able to avoid problems of inadmissible solutions and factor indeterminacy” (Scott and Walczak 2009, p. 226).

Data analysis was conducted using a two-step approach (Lee et al. 2015; Chan et al. 2010; Ringle et al. 2005). The first step was to authenticate validity and internal consistency (reliability) of the data, employing CFA, and the second was to estimate the hypotheses, using structural model.

3.4 Common method bias

A full collinearity variance inflation factor (Full Col. VIF) test was carried out to check for common method bias. As reported in Table 1, the results revealed that the values of all the constructs were within the acceptable range (≤ 3.3), showing that common method bias was not present in the data (Kock and Lynn 2012). Additionally, as Kock and Lynn (2012) point out, full col. VIF is conventional and perhaps the important one for analyzing common method bias.

Table 1 Validity and reliability
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3.5 Analysis of measurement model

A measurement model analysis was conducted to calculate construct validity and the internal consistency of the destination brand awareness, destination brand quality, destination brand image, destination brand quality, destination visit behavior, and social media. Discriminant validity and convergent validity were employed to measure construct validity. Convergent validity, as recommended by Fornell and Larcker (1981), was employed to inspect the measurement model through factor loadings, average variance extracted (AVE), and composite reliability (CR). The factor loading scores of all indicators must be more than 0.50 (Kline 1998), the scores of AVE for each construct should be more than 0.50 (Gorla et al. 2010), and the values of CR for all indicators should be more than 0.60 (Bagozzi et al. 1998). However, discriminant validity can be checked by comparing the square root of the AVE with the correlation of the pertinent factors in such a way that the square root of the AVE must be more than the value of the factor. Internal consistency is requiring that the values of Cronbach’s alpha and CR must be more than 0.70 (Nunnally and Bernstein 1994).

The findings presented in Table 1 demonstrate that the values of Cronbach’s alpha and CR for each construct were higher than 0.70 which implies that the measurement model ensured the internal consistency of all the constructs (Bagozzi and Yi 1988; Nunnaly 1978). However, the values factor loading estimates of all items are greater than 0.50 and the AVE values for each construct were more than 0.50, which ensured convergent validity (Kline 1998). To check the discriminant validity, the suggestion by Deng et al. (2014, p. 218) to compare the “square root of AVEs and the correlation between any two constructs” was followed. The findings reported in Table 2 reveal that the scores of the square root of the AVEs were more than the respective correlational values. Consequently, it can be inferred that discriminant validity was attained (Fornell and Larcker 1981; Schaupp et al. 2010).

Table 2 Mean, SD, and correlation
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3.6 Analysis of structural model

Prior to testing the hypotheses, the fitness of the structural models with the data is tested. PLS-SEM was employed through WarpPLS 5.0 software. WarpPLS provides a number of fitness indices: namely, average path coefficient (APC), average R-square (ARS), average adjusted R-square (AARS), average block variance inflation factor (AVIF), and average full collinearity variance inflation factor (AFVIF). The values of APC (0.190, p = 0.004), ARS (0.401, p < 0.001), and AARS (0.368, p < 0.001) are significant and the values of AVIF (2.264), and AFVIF (2.002) demonstrate the good fitness of the model with the data. Table 3 shows the results of the hypothesized model. Results reveal that all the dimensions of CBBE have positive significant effect on destination visit behavior. Social media significantly moderates between destination brand loyalty and destination visit behavior as well as destination brand awareness and destination visit behavior. Figure 2 shows that social media establish strong relationship between destination brand loyalty and destination visit behavior. Similarly Fig. 3 presents that social media makes strong nexus between destination brand awareness and destination visit behavior.

Table 3 Hypotheses testing
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Fig. 2
figure 2

Moderation of social media between the link of DBA and DVB

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Fig. 3
figure 3

Moderation of social media between the link of DBL and DVB

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4 Discussion and conclusion

4.1 Theoretical implications

In the present study, the relationships among destination brand awareness, destination brand image, destination brand quality, destination loyalty, social media and destination visit behavior were examined. This study is important in two ways. First, besides examining CBBE within the scope of tourism, unlike previous research the integration of CBBE dimensions into the analysis process with the aim of examining the impact of each dimension on the destination visit behavior of tourists has made a valuable contribution to the literature. Second, this study has examined the contingent role of social media through the relationship between CBBE dimensions and destination visit behavior. In fact, this relationship has not been examined in detail previously, particularly within the scope of destinations, despite previous studies mentioning the role of social media in the decision-making behavior of tourists (Murphy and Chen 2014; Vermeulen and Seegers 2009; Gretzel and Yoo 2008; Gretzel et al. 2007). The present study attempted to eliminate the shortcomings in the literature by investigating the impact of social media on the destination CBBE components. Accordingly, the research results provide findings that contribute to the literature and thus furnish more information to both researchers and destination management and marketing organizations. As with structural relationships, PLS supported the statistically significant relationships between CBBE dimensions and destination visit behavior, moderating the role of social media between awareness and destination visit behavior, loyalty and destination visit behavior. However, no significant impact of social media on destination image and destination visit, and destination quality and destination visit behavior could be found. Therefore, the findings confirmed that tourists’ actual visit behavior increased with destination awareness, positive country-image, destination quality, loyalty and the moderating effect of social media.

The impact of CBBE dimensions were analyzed in more detail. Firstly, the finding that the dimension of destination brand awareness positively influences the destination visit behavior of tourists in the case of Pakistan is in line with the findings of Buil et al. (2013) and Chi et al. (2009). The meaning of a positive relationship between destination awareness and destination visit behavior is that having more information about the destination increase the destination visit behavior. As the tourists have higher brand awareness, there are higher chances of tourist trips. But the destination visit behavior is dependent on the type of awareness created by advertisements. In other words, the effect of destination brand awareness can be due to its image created by an advertisement, which enables consumers to visit the destination. Based on these findings, the present study provides supportive findings that destination brand awareness has a halo and summary effect, as described by Han (1989). Destination awareness is a major influence on tourist decisions. This is the aspect that has most potential to be developed in the case of Pakistan, as it obtains the best response in terms of attracting the international and local tourist. Social media provides considerable support in creating awareness, as compared to travel agents, guides and destinations. Destination awareness starts with the beauty of the destination, safety, availability of hotels and restaurants, food and beverages twenty-four seven, and cleanliness of the environment. This will guide tourists’ preferences and give them motivation in relation to a tourist destination, providing a decent place for reinvigoration (Battour et al. 2010). A reliable supply of food and beverages for tourists provides them with comfortable trips (Karim et al. 2017), while good sanitation where cleanliness is maintained, availability of sufficient water for ablutions, and a clean environment are also important factors in attracting tourists.

In addition, the impact of destination brand quality on destination visit behavior was examined. The results showed that the destination quality influenced the destination visit behavior of tourists positively. This result is similar to the results of Kim et al. (2008) and Chen and Hu (2010). Destination brand quality is purely based on the perception of tourists in terms of destination services available, as well as natural quality components. The process of building the perception starts with estimating the cost factors, then later the experiences regarding services and natural facilities provided by the destination are ranked. After this tourists decide whether the benefit obtained from the experiences is high or low (Dedeoğlu et al. 2019). The respondents in this study mentioned that they selected this destination because of its natural beauty, which means that destination brand quality is mainly dependent on natural quality. In other words, destination natural quality is a dominating factor in destination service quality. The natural quality features of any destination triggering the behavioral component more as natural quality perceptions are mostly emotion-based situations such as atmosphere and the culture in the destination. The finding that destination natural quality is more decisive in terms of behavioral output also partly supports the S–O–R model of M–R (Mehrabian and Russell 1974). According to this model, environmental regulation is a stimulus that drives consumers’ emotions. However, as compared to the above discussion, the dimension of destination brand quality influences the destination visit behavior positively and this dimension represents both natural and service quality.

The next important factor is the destination image. The transportation service is one of the major aspects in the selection of the Northern Areas of Pakistan as a tourist destination. It provides reasonable packages and has a list of accommodation as well as providing a list of food and beverages. Some of these services are provided by travel agencies as well. Transportation packages along with accommodation are considered the most essential by international tourists. Managers of tourist destinations need to establish and maintain good relationships with travel agencies in relation to sales promotion (Widagdyo 2015). Guides who serve tourists in a communicative, friendly, honest and responsible manner are the factor that has the best response. Serving tourists in a friendly and communicative manner will provide satisfaction for tourists (Hong et al. 2017). In general, the attributes of tourist destinations and tourist satisfaction have a significant impact on loyalty (Rahman 2014; Bazazo et al. 2017). Ensuring the availability of the best attributes in destinations and services can lead to tourist satisfaction as well as inspire multiple return visits (Suid et al. 2017). Consumer loyalty is thus seen as crucial to the success of an organization’s business, as attracting new customers is much more expensive than maintaining existing ones (Donio, 2016; Kotler and Keller 2014).

The last dimension of the CBBE model is loyalty, and the results indicate that the relationship between destination brand loyalty and destination visit behavior is positively significant. In line with other dimensions of the CBBE model, such as destination brand awareness, destination brand quality and destination image, the component of destination loyalty is also a determining factor of tourists’ destination visit behavior. In this study, destination loyalty involves revisit behavior and positive word of mouth. Loyal tourists are not prone to switching behavior and they tend to be consistent in their repurchase behavior (Bowen and Shoemaker 1998). This finding also indicates that tourists’ commitment towards a brand can help improve the operational and natural performance of a destination. Additionally, this finding collectively showed that once already visited, this destination has a higher chance of being visited again and recommended to others, b Because it is solely derived from the experience of various services, from word-of-mouth reports from other tourists and from recollections of advertising and promotion. It should be pointed out that most of the time, promotion is only used to reinforce existing behavior. This finding implies that to build a strong relationship with a tourist destination, the supplier has to obtain into the black box of dealing with tourists’ attitudes; ensuring, for example, that they are, first of all, satisfied, have intentions of visiting the destination again, and intend to recommend it as a first-choice destination to other tourists.

This study has made some important findings regarding the contingent role of social media. First of all, social media influences the relationship between awareness and destination visit behavior in a positive way. This finding shows that the destination awareness is a major influence on tourist decisions and that this relation is moderated by social media.

In contrast to the role of social media between awareness and destination visit behavior, social media does not demonstrate any significant positive relationship between destination quality and destination visit behavior. In line with the results of social media, destination brand quality and destination visit behavior, no significant positive relationship was found in social media between destination image and destination visit behavior. The influences of social media on destination brand loyalty and destination visit behavior was found to be significant and positive. This denotes that as tourists are turning more frequently to social media to conduct their information searches and to make their purchasing decisions, as suggested by Kim and Ko 2011, social media further positively influences the relationship between destination brand loyalty and destination visit behavior. Previous studies have suggested that high levels of loyalty drive permanent purchases of the same brand (Cobb-Walgren et al. 1995; Yoo and Donthu 2001). Loyal customers tend to purchase more than moderately loyal or new customers (Yoo et al. 2000).

4.2 Managerial implications

This study has multidimensional managerial implications in the tourism industry. Firstly, it examines different variables related to the destination selection of Pakistan, which provides an insight into how tourism managers and tourism agencies operate. Firstly, managers should create an awareness of the Northern Areas as a travel destination. However, the awareness should portray a secure image of the location. International tourists are more concerned with security conditions than with other aspects of destination selection. This, in turn, allows the identification of destination brands that compete against other destinations from a tourist perspective. This strategy enables managers to evaluate the competitive position of their brand and to consider its uniqueness and superiority. Moreover, travel agencies also play their role in the expansion of market share by targeting the different tourists from different places and backgrounds, based on their nationality and perception. In this regard, destination suppliers have to build the image traits that should fully reflect the unique characteristics of destinations. However, managerial expertise is required in adapting ethnic attributes, especially in relation to their perception by western tourists. In addition, the next important factor for consideration after creating successful awareness and a good image is the facilities that are available at the destination. Hotel managers in the Northern Areas need to improve the looks, services and facilities. This will initiate a new dimension in the tourism industry that can begin to meet the unique needs and expectations of travelers from different regions of the world. This study has identified that social media has the power to influence tourists’ perception regarding their awareness, which in turn influences their behavior. Tourism product awareness, product development, innovation, transformation and marketing through social media have an important role in rebuilding the image of Pakistan as a tourist friendly country. Destination suppliers are using social media in their strategic marketing process, especially in developing and monitoring their perception. Effective positioning is only achieved by creating and managing an appropriate destination image (Sirgy and Su 2000).

5 Limitations and future research

There is no study without limitations, and presenting the limitations of a study makes it more worthwhile. So this research has limitations that need to be mentioned when considering the contributions of this study. The first limitation is about the research area and the sample used in this study. As explained, the research was conducted in the Northern Areas of Pakistan, and the findings were based on 150 participants consisting of both international and local tourists. This means that the small sample size and restriction of respondents to only two categories (international and local tourists) can be regarded as a limitation. In response, future research should consider a larger sample size and moreover, it should segregate the sample size of international tourists according to their nationalities. Bianchi et al. (2014) criticize the fact that tourism studies are mostly conducted on tourists who are geographically close to the studied destination. Since in the present study the sample size is composed of both national and international tourists, it counteracts the criticism by Bianchi et al. (2014). Future studies could involve distant respondents as a sample in any destination of Pakistan. In addition, another limitation to the sample is their demographic characteristics. The characteristics of the tourists will affect the characteristics of their journey as well (Phosikham et al. 2015). So future research should categorize the responses of tourists according to their demographic characteristics, such as age, occupation, and home country. The age factor is an important determinant in the selection of a tourist destination. The groups aged 18–26 years and 26–40 years tend to prioritize attractions, whereas the age group of tourists aged over 40 years prioritize guides and their attentive and courteous behavior. Tourists who come from Europe, for example, tend to be more concerned with security concerns in Pakistan than other variables, whereas tourists from the region of Asia tend not to prioritize any of the other aspects studied, but only focus on the attraction of the destination.

The second limitation of this study is related to the questionnaire. The questionnaire is only in two languages, hence it is limited in scope and unable to reach as wide an audience as it could if more languages were included. Additionally, every destination has its own unique characteristics and environments, which requires the model and measurement of constructs to be developed in such a way as to measure within the scope of its physical, environmental and socio-cultural features. In this study, the measurement of items is limited only to destinations in Pakistan. Thus, future studies in Pakistan should consider this limitation and translate the questionnaire into each of the respondents’ languages, as far as possible, so as to enhance the rate of return and improve the presentation of the results.

The third limitation relates to the data collection method. In this study, data collection was quantitative. However, Boo et al. (2009) suggest conducting detailed interviews in order to measure the destination branding, due to certain advantages of qualitative research such as the fact that it minimizes the misperception of the tourists regarding a destination and provides an in depth analysis as compared to quantitative research. This is because the purpose behind destination brand measurement is to obtain an in-depth analysis as compared generalizability. Therefore, future research should consider the qualitative and mixed method approach in order to obtain detailed results. Sequential exploratory mixed method research, which is characterized by an initial phase of qualitative data collection and analysis, followed by a phase of quantitative data collection and analysis is more appropriate, when compared to other mixed method research designs. By following this design, the researchers first identified the CBBE constructs and developed their measurement scales by conducting interviews and then tested the instrument through quantitative research.