Driving forces of social media and its impact on tourists’ destination decisions: a uses and gratification theory

Abstract

This study investigates the impact of social media on tourists’ destination decisions in a less digitalized economy through the lens of the uses and gratification theory. Data was collected from 428 local tourists sampled across various tourist destinations in Ghana (a sub-Sahara Africa) using a structured questionnaire. Analysis was carried out using variance-based PLS-SEM (Partial Least Square Structural Equation Modelling). The results show that tourist contentment, destination image, behavioral goals, and the availability of tourism information are driving forces of social media usage toward tourism destination decisions. The findings imply that tourism service providers should revise and incorporate the trending social media strategies to enhance their interaction with prospective visitors (customers) to increase their market share and become more competitive. This paper not only broadens the social media marketing literature but offers a comprehensive assessment of the integration of social media given the myriad of challenges besetting users and tourism service providers and discusses its impact in shaping tourist destination decisions in emerging and developing economies. Limitations and avenues for future research are discussed.

IMPACT STATEMENT

Undoubtedly, the persistent integration of digital marketing technologies (such as social media, paid media, SEO tools, etc.) has significantly impacted the tourism sector, more importantly, the role and use of social media in visitors’ decision-making and tourism’s operational management have received a growing discussion in the tourism and hospitality research. Study findings carefully demonstrate the strategic importance of social media for tourism competitiveness. Our present study also contributes to theory and practice by providing empirical arguments on the drivers of social media usage from the tourist perspective. This study, based on the findings, provides recommendations for destinations (service providers) on how to design effective social media content sustainably.

Keywords:

• Social media
• tourism
• destination decisions
• tourist
• use and gratification theory
• Ghana

Reviewing Editor:

• Pier Luigi Sacco
• Humanities
• IULM University
• Milano
• Italy

Subjects:

• Technology
• Hospitality
• Tourism
• Heritage Management & Conservation

1. Introduction

The tourism sector is seen as one of the key drivers of the Ghanaian economy. Social media is regarded as an online (network) platform that has the tendency to improve business performance and has become an effective communication tool within which people obtain information, identify options, assess and make tourism destination decisions easier for existing and potential visitors (Song & Yoo, 2016; Pop et al., 2022). Social media plays a role in tourism services through information sharing with both tourists and potential visitors. This is done through the dissemination of their experiences, videos, and photos via social media networking sites to lure other guests or visitors (Paul & Roy, 2017).

Overall, tourism service operators can use social media to advertise their services which increases destination brand awareness, brand trust, and engagement (Abdullaev & Anggraini, 2023; Díaz-Andreu, 2017). Social media content can help to create a destination’s image and expectations (Narangajavana et al., 2017). Due to tourism service risks and uncertainties, potential visitors are recently downloading travel applications for travel information search via the Internet (Icoz et al., 2018). World Tourism Organization (2018) reports that 93% of internet users seek tourism-related information for travel purposes. More importantly, tourists have used social media networking sites for travel information searches (Abbasi et al., 2023; Jamshidi et al., 2023). Consequently, this information search aids tourists to plan before traveling and ultimately influences their destination decision (Jacobsen & Munar, 2012). Besides, other guests or visitors utilized social media throughout their travel processes such as the pre-trip, during-trip, and post-trip stages (Hudson & Thal, 2013; Liu et al., 2020), also for travel evaluation and satisfaction (Dwityas & Briandana, 2017; Pop et al., 2022). Gururaja (2015) further opines those recommendations from other guests or visitors, and friends, and is relatively perceived to be the same as information shared online by guests or visitors.

Jamu and Sari (2022) observed that social media information has an impact on tourists visiting interest, which significantly affect destination decision. Moreover, social media enable tourism operators (local community members, NGOs, government, tourists, and tourism industry players) to collaborate for sustainable tourism through knowledge sharing (Senyao & Ha, 2022). Through social media engagement with the local community, social relationships with the resident, and lifestyle can be changed, which therefore affect the destination’s reputation. Auliya et al. (2020) argued that electronic word of mouth strongly influences tourism destination decisions. Hence, strong electronic word of mouth is perceived to be valuable and has effects on e-reputation and tourist destination visit intention. In addition, social media networking sites have a flow-friendly experience, flow interactivity experience for tourists (Chang, 2022; Baber et al., 2022). Therefore, it has been proposed that tourists can focus on social media usage to choose a destination (Siegel et al., 2023).

Undoubtedly, social media has a significant role in the quest to make tourism destination decisions by visitors (Kiráľová & Pavlíčeka, 2015; Kilipiri et al., 2023; Razak & Mansor, 2022; Gebreel & Shuayb, 2022). This implies that conducting a study on social media usage and tourists’ destination decisions could provide a comprehensive understanding of how tourists utilize social media applications to make travel decisions. Nonetheless, research on the driving force that triggers social media usage among visitors toward tourism decisions in the Ghanaian context is limited (Kotoua & Asiedu-Appiah, 2022; Ofori-Okyere, 2019; Osei et al., 2018), hence the need for further empirical investigations. Moreover, prior studies show that tourism industries mainly located in developing nations, particularly Ghana are far behind in the utilization of digital platforms (i.e. social media applications) and measuring their tourist destination decisions (Preko et al., 2023; Kotoua & Ilkan, 2017). As mentioned by Abbasi et al. (2023), Paul et al. (2019), and Javed et al. (2020), visitors of tourist destinations now rely heavily on social media reviews as a source of information, hence it’s imperative to understand how the tourism industry in Ghana can take advantage of this essential tool and assess its effect on tourist destination decisions and for competitiveness. Considering the aforementioned, this study will fill these knowledge gaps by empirically investigating the driving forces of social media in the tourism sector and the impact of social media on tourists’ destination decisions from the Ghanaian perspective. Specifically, the present study’s main aim seeks to examine the driving forces of social media and its impact on tourists’ destination decisions using multivariate analysis (PLS-SEM).

According to Mandasari (2021), tourists’ destination decision is ‘‘influenced by the quality services provided by tourism service suppliers’’. Besides, tourist contentment, destination image, behavioral goals, and availability of information from visitors have been observed to be the factors that influence tourists in selecting a particular destination (Agyapong & Yuan, 2022). Other factors such as destination accessibilities and settings, psychological boundaries, and demographics have also proven to be the tourist motivation for choosing a destination (Yoo et al., 2018; Pan et al., 2021). Focusing on social media usage by tourists and tourism service providers in Ghana geared toward destination decisions, the present study intends to ascertain the degree to which tourist contentment, destination image, behavioral goals and availability of information from visitors through social media usage influences tourist destination decisions. Drawing on the grounds of User and Gratification theory, the study explores and provides a comprehensive basis for the usage of social media applications in the tourism context.

The current study provides the following contributions. The findings of the study could be beneficial to authorities and tourism service providers in their quest to utilize social media applications to achieve competitiveness and sustainable growth. Again, the results and the model of the present study provide comprehensive evidence for academicians and tourists, especially on social media usage and tourist destination decisions from the developing economies context. Moreover, the paper would benefit tourism industry stakeholders and practitioners in integrating and formulating social media strategies to lure tourists to destinations.

The paper is structured as follows: section two presents the literature review, the proposed conceptual framework, and the hypotheses formulation. The research methodology is covered in section three. Next, research findings and analysis are provided in Section Four. Discussions, implications, limitations, and conclusions are highlighted in the final section.

2. Literature review, theoretical foundation and hypotheses development

2.1. Overview of tourism in Ghana

Tourism plays an essential role in the growth of Ghana’s economy and is considered one of the promising and fastest-growing sectors. With a growth rate of about 12% per annum, the tourism sector employs more than 5% of the total population as well as income generation, according to a report from the World Travel and Tourism Council (WTTC),) (2015). Ghana’s Ministry of Tourism, Culture, and Creative Arts is mandated to steer the affairs and development of tourism-related activities in the country. The Ministry is authorized to “facilitate the interface between government, implementing bodies in tourism, culture and the creative industries, as well as international and civil society partners” (MOTCCA, 2015). The sector is seen to become the first foreign exchange earner of Ghana, apart from the main traditional foreign exchange earners (i.e. gold, timber, and cocoa). Girish et al. (2018) acknowledged that highlighted that the tourism sector contributes to the Gross Domestic Product in the areas of employment creation, revenue generation, export diversification, poverty reduction, and private sector investment.

Ghana’s location in the Western part of Africa with beautiful landscapes, wildlife parks, stretched golden beaches, and rich cultural heritage attracts tourists to the country (Anabila et al., 2023). Afrifah and Mensah (2023) further state that Ghana’s thriving economy, stable democracy, and amazing tourist destinations influence tourist decisions. Given the sector’s huge potential, the Government of Ghana through the Ministry of Tourism, Culture, and Creative Arts committed to strengthening the economy via tourism development, and came out with The National Tourism Development Plan (2013–2027) and Strategic Tourism Development Plan (1996–2000). These plans seek to promote and develop the tourism sector to become the leading sector for economic development (Adu-Ampong, 2020). Besides, it has thus become essential for the government to put in place other necessary policies, actions, and resources to reap the full benefits of the sector (Asiedu, 1997) and help preserve historical, cultural, and natural heritage, hence making the tourism sector a significant contributor of domestic income (Anabila et al., 2023), which has an overall impact on improving living conditions (Government of Ghana, 2006). The study conducted by Mensah-Ansah et al. (2011) on the tourism trends in Ghana finally suggested an integrated approach for the tourism sector, unifying public-private investors for the sector to be sustainable.

2.2. Uses and gratification theory

The uses and gratifications theory (UGT) is a communication theory that suggests that individuals actively seek out and use media to satisfy specific needs or goals. UGT proposes that people are not just passive recipients of media messages but are active users who selectively choose media content that fulfills their needs and goals (Joo & Sang, 2013). According to UGT, people use media to gratify four types of needs: cognitive, affective, personal integrative, and social integrative needs (Ruggiero, 2000). Cognitive needs refer to the need for information and knowledge. Affective needs refer to the need for emotional arousal or stimulation. Personal integrative needs refer to the need to reinforce or enhance personal identity and self-esteem. Finally, social integrative needs refer to the need for social interaction and companionship (Kaplan & Haenlein, 2010). UGT has been used to explain media use in various contexts, such as television viewing, newspaper reading, and social media use. In the context of social media, UGT has been used to investigate how people use social media to satisfy their communication and social needs (Lin & Lu, 2011). For example, researchers have used UGT to examine how people use social media to fulfill their need for social interaction, such as by connecting with friends and family, seeking social support, and building new relationships (Papacharissi & Rubin, 2000).

In the context of tourism, UGT has been used to investigate how tourists use media to plan their trips and satisfy their travel-related needs. For example, researchers have used UGT to explore how tourists use travel guidebooks, websites, and social media platforms to gather information about destinations, plan their itineraries, and share their travel experiences with others (Silaban et al., 2022; Ho & See-To, 2018; Gamage et al., 2022). From the foregoing, the researchers argue that the use of social media enhances customer interactivity and engagement by making sufficient information available to help decision-makers make informed decisions. Social media usage also motivates users by redirecting their psychological state, which has an impact on their behavioral goals (Kapoor et al., 2022). This study leverages the UGT to provide an understanding of how social media influences tourist destination decisions. Following Ruggiero’s (2000) assertion, social media use can be related to UGT’s "social integrative needs", which refer to people’s desire for social interaction and companionship. Tourists may use social media to connect with friends and family, seek recommendations and reviews from other guests or visitors, or share their travel experiences with others. Again, the researchers conceptualize tourists’ contentment as a personal integrative need, which refers to people’s need to reinforce or enhance personal identity and self-esteem. Positive travel experiences can contribute to tourists’ sense of self-worth and satisfaction (Vojtko et al. (2022). While destination image relates to the cognitive needs of the tourist, it signifies people’s need for information and knowledge (Költringer & Dickinger, 2015). Tourists may use destination images to gain knowledge about a destination and form expectations about their travel experiences. Furthermore, the study conceptualizes behavioral goals as personal integrative or affective needs that reflect tourists’ desire to fulfill personal goals and desires. For example, tourists may seek adventure or novelty to satisfy their need for excitement and stimulation. The study synthesizes the availability of information with the cognitive needs of users. This represents the information and knowledge that tourists may seek to make informed travel decisions. Tourists may use different sources of information, such as travel guides, websites, and social media, to fulfill their cognitive needs and gather relevant information about their destination (Marzouk, 2022). In effect, the theory provides a useful framework for understanding how media use satisfies individuals’ needs and goals in various contexts, including social media use and tourism. By understanding the needs that social media satisfies for tourists, researchers and practitioners can develop strategies to promote sustainable and responsible tourism practices. The study, thus argues that, while social media drives tourist user engagement, it also heightens their actions to decide on which destination site meets their desire. Hence, the use of the UGT to investigate the impact of social media on tourist destination decisions. From the foregoing discussion, the researchers conceptualize the factors that stimulate tourist decisions and how they beset settling on a tourism destination selection in Figure 1. In the next sections, the researchers present the hypotheses for the study.

Figure 1. Conceptual framework.

2.3. Social media and tourist destination decisions

Social media can be defined as web-based applications that help in sharing user-generated content. Social media can be in the form of forums, social media networking sites, microblogs, and photo archives (Kaplan & Haenlein, 2010). Social media networking sites’ capabilities have provided opportunities for different stakeholders to interact and share information among themselves (Leung et al., 2013). Scholars have acknowledged the significant role of social media in guests’ or visitors’ decision-making (Zarezadeh et al., 2018; Tham et al., 2020; Tsiakali, 2018). According to Singh (2021), social media has gained acceptance and is utilized for different purposes including pre-trip and post-trip stages of tourists. Khan and Hashim (2020) for instance, asserted that the emergence of tourism social media (TSM) platforms has facilitated the interaction between existing and prospective; in this context, social media improves communication between tourism operators and visitors. Rathore et al. (2017) further postulate that social can help tourists to get a clear image of a particular destination before traveling. In a similar vein, tourism information posted online facilitates tourist information search, which in turn reduces tourism uncertainties and risks associated with travel plans (Fodness & Murray, 1997). More recently, Sun et al. (2022) opine that social media influences tourist behavior, which ultimately affects tourism destination decisions. According to Tešin et al. (2022), social media networks serve as a source of external information to tourists, which assists them in making informed decisions regarding destinations. From the consumers’ perspective, it is evident that tourists post and share experiences during their traveling planning process (Liu et al., 2013; Fakharyan et al., 2012; Davies & Cairncross, 2013). Furthermore, Yuan et al. (2022) submit that tourism service providers to promote and perform other different tourism-related functions can also utilize social media networking sites. However, other researchers concluded that social media have no significant effect on tourist destination choice due to the lack of source credibility and negative comment posts on destinations (Turktarhan & Cicek, 2022).

Destinations have unique facilities and services that motivate tourists to visit (Gregory, 2015). From this perspective, scholars have suggested that guests or visitors need adequate information to plan and choose their destinations (Riyadi & Nurmahdi, 2022; Paniagua et al., 2022). Tarigan and Tinambunan (2022) argued that potential visitors need information search to choose from many competing destinations. Several studies have highlighted the relevance of social media in tourism destination decisions. Beerli and Martín (2004) identified social media as an avenue for tourists to seek tourism-related information. Senyao and Ha (2022) posit the availability of tourism-related information online helps in reducing uncertainties about the destination and influences his/her final destination decision. Tourism destinations, on the other hand, can equally utilize social media networking sites to market, promote, and share their tourism-related services and content (Gebreel & Shuayb, 2022), effectively communicate with prospective and existing tourists (Chang et al. 2022; Chen et al., 2014) and influences their destination decision (Pachucki et al., 2022; Camilleri & Kozak, 2022). Similar work by Liu et al. (2022) witnessed a positive correlation between social media usage and tourist behavior concerning destination decisions. In addition, other researchers have identified factors influencing tourist destination decisions, such as price, dishes, local communities, and destination images (Giang, 2022; Haryani et al., 2022).

2.4. Tourists contentment

Khan and Hashim (2020) highlighted the essence of staying competitive to ensure sustainable tourism growth. According to Vojtko et al. (2022), tourist contentment is a significant signal of sustainable tourism. Tourists’ contentment is crucial in achieving tourism sustainable growth (Surugiu & Surugiu, 2015; Lam-González et al., 2020; Yusendra & Paramitasari, 2018). Pop et al. (2022) submit that social media has been used to increase and stimulate travel and build trust, which serves as an extremely important factor in influencing tourists’ decision-making and tourists’ contentment. Prior studies have established the importance of utilizing social media in tourists’ contentment (Ramesh & Jaunky, 2021; Chon, 1990; Prentice & Kadan, 2019; Yusendra & Paramitasari, 2018). According to Awaritefe (2004), social media enables tourism service providers to engage tourists and improve satisfaction, leading to tourists’ loyalty. Recently, it has been confirmed that tourism operators use social media as a source of building a relationship, hence achieving competitive advantages (Bruce et al., 2022; Kotoua & Asiedu-Appiah, 2022; Kumar et al., 2022). Furthermore, Lai et al. (2018) and Yusendra and Paramitasari (2018) evidenced that social media in tourism does not only have a significant effect on tourists’ superior value but also destination decisions. Swarbrooke and Horner (2007) investigated consumer behavior in tourism and highlighted that satisfied tourists are likely to recommend and create positive words about the destination to friends and relatives. When a tourist is satisfied, they usually share their happiness or satisfaction on social media platforms, which eventually influences tourism destination decisions (Pop et al., 2022; Turktarhan & Cicek, 2022). Besides, Chi and Qu (2008) surveyed tourists in Arkansas, Eureka Springs, and found that social media has a significant effect on tourist contentment and tourism destination decisions. Furthermore, Amissah and Amenumey (2015) study on tourist satisfaction demonstrated that tourist contentment significantly affects behavioral intention toward a tourism destination decision in the hospitality context. Other empirical studies have proved that tourist contentment positively contributes to perceived value, tourist loyalty, and tourism destination choice (Kam et al., 2016; Glaveli et al., 2022; Goo et al., 2022; Mas’ Ud et al., 2022). Therefore, based on the, the study proposes the following;

• H1: Tourist contentment would positively trigger the use of social media for tourism purposes and destination decisions.

2.5. Destination image

Tourism destination image serves as a tool to assess the place one intends to visit (Diposumarto et al., 2015). Költringer and Dickinger (2015) described destination image as “an interactive system of thoughts, ideas, feelings, imagery, and goals toward a destination”. Destination image is considered as a guest’s or visitors’ perception of the company and its products (Malhotra, 2012). Song et al. (2022) posit that destination image is pivotal in travel planning. In this context, Grover and Kar (2020) argued that effective promotion of tourist destinations has a significant effect on tourists and suggest the usage of social media applications to help promote tourism destinations and position a destination in the minds of tourists. Tourism operators can update tourism destinations on social media platforms by posting pictures and videos, which ultimately helps tourists to make an informed decision regarding destination choice (Pan et al., 2021; Arifiansyah & Saragih, 2022; Srivastava et al., 2022). Extant literature has highlighted a positive association between social media and destination image (Li & Yu, 2022; Chang & Chiang, 2022; Tapachai & Waryszak, 2000; Jenkins, 1999; Molina et al., 2010; Lam-González et al., 2020). Stepaniuk (2015) witnessed that social media usage has helped to portray a good image of places in the tourist setting. Moreover, Srivastava et al. (2022) and Ghazali and Cai (2013) posits that social media platform enables tourists to form a cognitive image of a particular before planning a trip. Furthermore, Kim et al. (2017) study collected data from Sina Weibo users in China and evidenced that destination photos and videos on Sino Weibo have a significant long-term effect on travel destination decisions. Destination image attributes such as amenities, quality services, and customer support systems create a positive image for tourists (Tapachai & Waryszak, 2000; Pereira et al., 2022). In this regard, the findings of Jose et al. (2022) sampled 246 foreign tourists and witnessed that culture, amenities, leisure, attractions, and other support systems influence destination decisions in the context of India. Thus, tourism service providers can effectively utilize social media to influence tourist destination decision through the formation of a perceived image of a tourist destination, which in turn motivate them to visit. From the above argument, propose that:

• H2: Destination image would positively trigger the use of social media for tourism purposes towards destination decisions.

2.6. Behavioral goals

Warshaw and Davis (1985) defined behavioral goals as the degree to which individuals conceived and planned toward a specific activity or behavior. Individuals’ intentions to make decisions are based on behavioral goals. In the context of tourism, Nguyen and Tong (2022) stated that behavioral goals drive tourists to make destination choices. Arowosafe et al. (2022) argued that tourists’ revisit intention is motivated by their behavioral goals. The accessibility and understandability of content generated online by tourist service providers affect tourists’ behavioral goals (Chen et al., 2014). A study by Sultan et al. (2019) observed that online tourism reviews have a profound effect on tourist behavior regarding destination choice. Khan et al. (2022) explained that guests’ or visitors’ behavioral goals can be influenced by social media. Barreda et al. (2015) also revealed that social media significantly influences tourist behavioral intention. Posting positive experiences online, particularly on social media platforms influences the perceived trust of tourists, which affects their destination decision (Ye et al., 2011). Further to this, Majeed and Ramkissoon (2022) explored social media’s impact on tourists’ behavior and witnessed that social media usage mediates the relationships between behavioral goals and tourism destination decisions. Previous studies conducted in the tourism setting have highlighted the significant role of tourist behavioral goals in tourist destination decisions (Novianti et al., 2022; Li & Su, 2022; Mainolfi et al., 2022). For example, Karl et al. (2022) investigated the cognitive and behavioral constraints in tourism destination decisions and reported that behavioral intention has a positive effect on travel planning and tourist destination choice. Kim et al. (2022) also found that behavioral goals have a positive impact on individual travel planning, which significantly influences destination choice. Their study findings suggest that perceived behavioral control and attitude have a positive effect on the tourist’s behavioral intentions to choose a destination. Other studies (Lam & Hsu, 2006; Pandža Bajs, 2015; Nazir et al., 2022) have found a positive correlation between behavioral goals and tourist destination decisions. From the above evidence, the study hypothesizes that:

• H3a: Behavioral goals would positively enhance the use of social media for tourism purposes.

• H3b: Behavioral goals would positively affect tourist destination decisions.

2.7. Availability of information obtained from other guests or visitors

In a study conducted by Dey and Sarma (2010), information available to tourists is critical in choosing a destination. Bormann et al. (2016) identified information available to guests or visitors, tourists’ own experience, and information from friends and relatives as valuable and significant in destination choice. Recently, Razak and Mansor (2022) submitted that social media plays a crucial role in social media-induced tourism. Guests or visitors have become influencers and content creators, where they share their experiences and provide adequate information to other potential visitors (Marzouk, 2022; Kumar et al., 2022; Kempiak et al., 2017). Information gathered online by guests or visitors informs tourists and influences their destination decisions. In this context, Zhu et al. (2015) report that online information shared by other guests or visitors has become highly influential in tourist destination choice. Besides, adequate and reliable information can be obtained from social media platforms through videos and photos shared by other guests or visitors (Garcia et al., 2015; Ramírez-Gutiérrez et al., 2018). A study conducted by Tešin et al. (2022) explored Instagram’s influence on tourist destination decisions and concluded that information shared by other guests or visitors on Instagram has a strong and positive influence on destination decisions. Furthermore, Gamage et al. (2022) applied the user and gratifications theory in assessing social media and mobile payment apps’ effect on tourism destination decisions and witnessed that guests’ or visitors’ information posted on WeChat influences the hotel selection process in China. In support of this, Boto-García and Baños-Pino (2022), corroborate that other guests’ or visitors’ information positively affects tourist destination decisions about others influences decisions on destinations, hence confirming the bandwagon effects in tourist destination choice. Similarly, Schroeder and Pennington-Gray (2015) indicated that past travel experience shared by other guests or visitors affects destination decision among tourists. Based on the above discussions, the study proposes the following:

• H4a: Available information to tourists would positively influence social media usage for visitors’ destination decisions.

• H4b: Available information to tourists would positively affect their destination decisions.

• H5: Social media usage will have a direct positive relationship with tourism destination decisions.

The framework below is a summarized hypothetical relationship of the study goal(s).

Driving forces

3. Research methodology

3.1. Sampling and data collection

To accomplish the study’s purpose, the study used a quantitative approach. Importantly, the study relied on local tourists (as respondents) who visit various tourist destination sites in Ghana. A structured questionnaire was developed to suit the objective of the study. The structured questionnaire contains participants’ profile details and that of the research constructs for the hypotheses testing. Onsite-self-administered questionnaires were used to intercept tourists (respondents). This was achieved through the usage of non-probability, specifically the purposive-convenient sampling technique. To elaborate more, the researchers first visited the tourists’ destination sites in the regions selected to familiarize themselves and subsequently move in for the data collection mission. It is also important to highlight the selection of the sampling techniques (convenience and purposive) used in this study. The usage of the sampling techniques was a result of its efficiency, cost implications, and above all simplicity of implementation. Additionally, the sampling techniques were very helpful in time-sensitive because they require little planning to use for data collection. Before embarking on the data collection processes, the various selected tourist sites were officially consulted in writing seeking their permission to use their local visitors for such a study. After the approval was granted, the data collection process began. Participants were informed about the reason behind the study. It is of interest to reveal that some employees/staff of the selected tourist sites assisted in the data processes. It is quite important to highlight that some of the tourists were not ready to answer the questionnaire and therefore, requested for the soft copy to be sent to their digital platforms while others used part of their leisure time to answer the questionnaire. Respondents were strictly given only one chance to answer the questionnaire. The various tourist sites visited for data collection included Accra Zoo, Rawlings Park, Shai Hills in the Greater Accra region, Kakum National Park, Cape Coast Castle, Hans Cottage, Elmina Castle in the Central region, whilst Busia Beach Resort, Fort Metal Cross, Nzulenzu, and Cape Three Point are in the Western region. In the Ashanti region, the researchers visited Lake Bosomtwe, Manhyia Palace, Okomfo Anokye Stool Site, Bonwire Kente Weaving Village, Bobiri B, butterfly, and Hippo sanctuary in the Upper West region. The usage of these tourist sites for data collection was based on the regular visitation of local tourists to these tourist sites since these tourist sites have unique attractions, cultural experiences, local activities, and compelling scenery (Agyapong & Yuan, 2022).

For ethical purposes (anonymity and confidentiality), the tourists who were used as the respondents were strongly assured of confidentiality at the utmost. Out of a total of 500 structured questionnaires distributed across the selected tourist sites in Ghana, 452 were returned of which 428 (86 percent response rate) were correctly filled for data processing and analysis. However, concerning the research goal(s), the the study considered only respondents (325) who use social media for tourism purposes whilst the remaining respondents (103) were expunged from the data analysis. It is imperative to note that in the literature, there is no consensus regarding sample size for structural equation modeling (SEM). Some authors are of the view that even a small sample size could be tested meaningfully (see Marsh & Hau, 1999; Hoyle, 1999). Again, some consider that the minimum sample size required for structural equation modeling is between 100 and 150 (Tinsley & Tinsley, 1987; Anderson & Gerbing, 1988; Markus, 2012). However, some methodological researchers (Hair et al., 2019; Podsakoff et al., 2003; Moshagen & Musch, 2014) have recommended a relatively large number, for instance, a sample size of 200 respondents is quite appropriate for carrying out analysis through SEM, and the present study processed over 300 respondents as a sample size to accomplish the study goal(s).

Additionally, the study used the SmartPLS 4.0 software version and the PLS-SEM (Partial least squares and structural equation modeling) technique to run and analyze the data for this investigation (research model and proposed hypotheses). The researchers adopted the Partial Least Square Structural Equation Modeling (Henseler, 2017) because compared to unstructured data, it is simpler to analyze. After all, less processing is needed. In Table 1, the details of the characteristics of the respondents or participants used in this study are presented.

Table 1. Respondents’ profile.

Variables	Category	Frequency	Percentage (%)
Gender	Male	278	65.12
	Female	150	34.88
Age	20–25	120	27.91
	26–30	110	25.58
	31–35	78	18.14
	36–40	56	13.02
	Above 41	64	15.35
Educational Level	Diploma/Certificates	100	23.26
	Higher National Degree	170	39.53
	Bachelor’s Degree	86	20.00
	Masters/PGD	72	16.82
Social Media Platforms	Facebook	67	15.58
	Twitter	93	21.63
	WhatsApp	149	34.65
	Others	119	27.80
Tourism destination regions	Greater Accra	138	32.09
	Central Region	114	26.52
	Upper West	48	11.16
	Western Region	83	19.77
	Ashanti region	45	10.46
How often do you use SM	Daily	180	41.86
	Weekly	100	23.26
	Monthly	148	34.58
Social Media Devices	Mobile Device Only	125	29.07
	PC/Computer	105	24.42
	Both	198	46.26
Do you use social media for tourism traveling purposes?	Yes	325	56.98
	No	103*	43.02
Sample Size (n)		428	100

Note.*This figure was deleted before hypothesis testing to get the actual respondents who use social media for tourism purposes.

Source: Author’s field survey September–January 2023.

The demographic data shows that participants from Accra Zoo represent were 10%, Rawlings Park 5%, Shai Hills 8%, Kakum National Park 10.5%, Cape Coast Castle 11%, Hans Cottage 5%, Elmina Castle 6%, Busia Beach Resort 2.5%, Fort Metal Cross 1.5%, Nzulenzu 7%, and Cape Three Point 2%. Again, Lake Bosomtwe 5%, Manhyia Palace 8.5%, Okomfo Anokye Stool Site 4.5%, Bonwire Kente Weaving Village 5%, Bobiri B 3%, butterfly 1.5%, Hippo Sanctuary 4%.

3.2. Data analysis technique

The study used partial least square and structural modeling (PLS-SEM) to test the research model. PLS-SEM was utilized instead of co-variance-based structural equation modeling (CB-SEM). CB-SEM requires that the data be normally distributed, whereas PLS-SEM makes no assumptions about data distributions. Since non-normal data do not fundamentally alter the conclusions of a statistical test, the use of PLS-SEM is justified (Hair et al., 2019).

3.3. Measurement of the constructs

The research constructs were measured by taking inspiration from the available literature. The measurement scale was gauged on a five-point Likert scale; the study used the following - (1 = highly disagree, 2 = disagree, 3 = neutral, 4 = agree, and 5 = highly agree). Notably, tourists’ contentment (Gupta et al., 2021, Destination Image (Akroush et al., 2016; Pike, 2002; Chon, 1990; Mak, 2017), Behavioral Goals (Tussyadiah, 2017; Meng & Choi, 2016; López-Sanz et al., 2021), Tourism Destination Decision (Krakover & Corsale, 2021; Um & Crompton, 1992; Patterson, 2007), Availability of Information (O’Mahony et al., 2009; Lunt & Carrera, 2011), Social Media (Gebreel & Shuayb, 2022; Giglio et al., 2019; Kiráľová & Pavlíčeka, 2015). This was done to find out how much the respondent agreed or disagreed based on his/her perception of the use of social media for tourism purposes. Given that it is easier for respondents to complete and takes less time than open-ended questions, a five-point Likert scale was applied (Sullivan & Artino, 2013).

3.4. Common method bias

The researchers initially investigated the likelihood of CMB (common method bias) during the analysis. Two approaches were followed, notably, the procedural and the statistical approaches. In the procedural aspect, the study referenced from Kock and Hadaya (2018) and Attor et al. (2022), in which respondents were given stringent confidentiality guarantees and the construct items were carefully designed. Importantly, the survey was created to guarantee that participants would preserve their privacy and have the complete option to withdraw from taking part in the survey. With the statistical aspect, the study performed a rigorous multicollinearity test, focusing on the variance inflation factor (VIF) to ensure how much the behavior (variance) of an independent variable is influenced, or inflated, by its interaction/correlation with the other independent variables. Hence, relying on a threshold of 10 by earlier authorities (see Alin, 2010; Salmerón et al., 2020) CMV is not an issue because the computed VIFs are fewer than the cut-off value in this computations (see Table 2).

Table 2. Construct, indicator, loading, VIF, CR, AVE, and CA.

Construct	Indicator	Loading	VIF	CR	AVE	CA
Availability of information	AIT1: Online information shared on destinations by other guests or visitors motivates me to visit	0.838	2.290	0.941	0.798	0.916
	AIT2: Information from other guests or visitors is critical and highly influential in destination choice	0.904	3.241
	AIT3: Obtaining valuable information from other guests or visitors assists in trip planning and destination decisions	0.927	3.980
	AIT4: Recommendations from other guests or visitors serve as a source to make destination choices.	0.903	3.231
Destination Image	DI1: Social media promotion helps to conceive a positive image of a destination	0.863	2.413	0.921	0.744	0.885
	DI2: Adequate information about current culture, leisure, amenities, quality service, and community engagement positively affects one’s image of a destination.	0.905	3.012
	DI3: Tourism destination with a good reputation influences my destination choice	0.883	2.812
	DI4: Web designs, videos, and other images posted online form a positive image of a particular destination.	0.797	1.756
Behavioral Goals	BG1: Information shared on social media is having a strong impact on my intentions to decide.	0.888	3.259	0.927	0.718	0.902
	BG2: Destination image and perceived value directly affect tourist Behavioural intentions	0.838	3.045
	BG3: Experienced posts and videos from tourists on social media platforms influence tourist behavioral goals	0.777	2.220
	BG4: The attitude of tourism service providers in executing services influences tourists’ intention to visit the destination.	0.862	2.970
	BG5: Quality service, destination image, and satisfaction have a strong impact on Behavioural goals	0.867	2.931
Social Media	SM1: social media provides tourism-related information to potential tourists.	0.886	2.816	0.947	0.816	0.925
	SM2: Social media aids tourists in the information search process and facilitates travel	0.899	3.088
	SM3: social media helps in conveying new tourism destination information	0.921	3.680
	SM4: social media facilitates customer service	0.907	3.186
Tourism Contentment	TC1: Tourist satisfaction is essential in making destination decisions	0.883	2.600	0.947	0.812	0.823
	TC2: Satisfied tourists are likely to recommend to others through social media platforms	0.902	3.361
	TC3: Information provided by tourist service providers online is satisfied by potential tourists.	0.923	3.996
	TC4: Tourism quality services enhance tourist satisfaction	0.896	3.033
Tourism Destination Decisions	TDD1: Information online helps to evaluate different tourism destination	0.797	4.269	0.920	0.744	0.937
	TDD2: In my view, the information provided online is my reliable source of information to make a destination choice.	0.731	4.311
	TDD3: Quality service, community engagement, and tourism destination promotion influence tourist destination decisions.	0.923	4.314
	TDD4: In my view, destination image influences my decision to choose a particular destination	0.977	3.909

Source: Author’s processing from SmartPLS 4.0 software.

4. Empirical results

4.1. Model assessment

The assessment was centered on academic studies that employed PLS-SEM in the illustrative literature, including the use of Dijkstra-rho Henseler’s with Cronbach alpha coefficients to measure the reliability and validity of the research constructs (see Hair et al., 2019; Edeh et al., 2023). Inspired by the methodological researchers (Hair et al., 2019), with the threshold of 0.5, all the coefficients of these indices exceeded the cut-off value. Again, the cognitive properties of the study variables’ underlying components were evaluated. The test achieved the requirements for the composite reliability of constructs as specified by meeting the minimum values for Jöreskog’s rho (pc) and Cronbach Alpha of 0.77 and 0.70 respectively (Table 2). The higher the composite reliability, the higher the level of reliability. According to Hair et al. (2014), it is acceptable if composite reliability values are between 0.60 and 0.70.

More importantly, factor loading for all the constructs was computed and loaded to their perspective latent variables, meeting the criterion of 0.6 and demonstrating the efficacy of the indicators. The coefficients of the associated constructs showed 0.73 representing the minimum loading and 0.98 representing the maximum loading (see Table 2 below for details). Moreover, the researchers employed the common method variance (CMV) to find it utilized in proving the variance inflation factor (VIF) because they were highly concerned about the issue of multicollinearity.

The literature work of Henseler (2017) inspired the researchers to evaluate the discriminant validity of the latent variables through the Fornell-Larcker criteria. From (Table 3) below, it can be deduced that all the values or figures on the diagonal form exceeded the minimum threshold of 0.5 which invariably demonstrates the Average Variance Extracted (AVE) as affirmed by Hair et al. (2019). According to Fornell-Larcker criteria (1981), the fundamental and rigorous assumptions of the study constructs were developed after the AVE was necessary to have greater values (both column and row position) compared to the other constructs as seen in the discriminant validity table below.

Table 3. Discriminant validity-Fornell-Larcker criterion.

Constructs	Available Information	Behavioral Goals	Destination Image	Social Media	Tourism Destination Decision	Tourist Contentment
Available Information	0.893
Behavioral Goals	0.777	0.847
Destination Image	0.873	0.799	0.863
Social Media	0.801	0.751	0.797	0.903
Tourism Destination Decision	0.082	0.034	0.051	0.046	0.863
Tourist Contentment	0.830	0.791	0.811	0.774	0.051	0.901

Note. The diagonal bold values indicate the square root of Average Extracted Variance (AVE).

Source: processing from SmartPLS 4.0 software.

4.2. Hypothesis testing - PLS-SEM

Following the evaluation of the model fit, the structural model (path analysis) is required. This stage is crucial to the analysis because it identifies and establishes the causal effect (or links) of the study construct that is highlighted. The empirical findings of the present study revealed that four of the hypotheses have a positive and significant effect on the dependent construct (tourism destination decisions). Again, in Table 4, various constructs’ regression coefficients, Beta (β), and significant values, T-values >1.96 (or P-values 0.05), are displayed. The coefficient of determination (R2) of the regression model was evaluated regarding the prediction ability (coefficient of determination) of the research model. The coefficient shows how much of the variation in the dependent variable can be attributed to the independent (predictor) variable. Hence, R² of 70 percent (social media) as shown in Table 4 and Figure A1 below.

Figure A1. Empirically tested research model.

Table 4. Hypothetical path coefficient.

Constructs	Original Sample	Sample Mean	Standard Deviation	T- Statistics	P Values	Test Outcome
H1: TC -> SM	0.774	0.776	0.038	20.372	0.000	Agreed
H2: DI -> SM	0.797	0.799	0.037	21.758	0.000	Agreed
H3a: BG-> SM	0.751	0.752	0.039	19.309	0.000	Agreed
H3b: BG -> DD	−0.046	−0.018	0.117	0.391	0.696	Not Agreed
H4a: AI -> SM	0.801	0.804	0.042	18.972	0.000	Agreed
H4b: AI -> DD	0.212	0.073	0.194	1.094	0.275	Not Agreed
H5: SM -> DD	−0.013	−0.033	0.120	0.108	0.914	Not Agreed
		R Square		R Square Adjusted
Tourism Destination Decision		0.009		−0.002
Social Media		0.711		0.706

Source: processing from SmartPLS 4.0 software.

Note. Availability of Information (AI), Destination Image (DI), tourist contentment (TC), social media (SM), Destination Decision (DD), and Behavioural Goals (BG).

5. Discussions of results

The decision to settle on a tourist destination, in most cases, is a challenging task. Tourists, in most circumstances, are unaware of the hidden factors that stimulate their final decision (Darko & Liang, 2022). But, the advent of social media, nonetheless, has become a key enabler by influencing tourists’ decision-making processes. The avalanche of social media thus, untangles the fuzziness in the tourist’s decision, making it easier for them to settle on their destinations. Thus, this study investigated the driving force of social media usage and its impact on tourism destination decisions in Ghana among local tourists. Based on an extensive literature review guided by the UGT, the study proposed five hypotheses aimed at achieving the study’s goal.

The first hypothesis (H1) investigated how tourist contentment influences social media usage towards tourists’ destination decisions. This hypothesis was supported. In line with (Jeong & Kim, 2019; Prentice & Kadan, 2019; Lam-González et al., 2020), the findings imply social media influences how content a tourist is. The discovery lends credence to the reasons why tourists frequently flock to social media and other social network sites to express their feelings about their travel-related experiences. In line with this, Darko and Liang (2022) aver that tourists will rate and recommend tourist sites as an expression of their contentment in textual form. Tourists can express their feelings about their experiences on social media, primarily through online social networking tools. In sum, tourists regardless of their level of contentment will want to express their sentiments using available technology.

Arifiansyah and Saragih (2022) affirmed that the quality of service being provided by a tourism destination site significantly enhances its reputation, which translates into an increase in its market share. Following this, the study hypothesized that H2: Destination image would positively trigger the use of social media for tourism purposes towards destination decisions. This hypothesis was supported by the present findings contrary to the works of Song et al. (2022) and that of Srivastava et al. (2022). Typically, it is a fact that tourists would want to be associated with tourist sites with a good reputation. It is therefore not surprising that the finding was in line with this established assertion. As mentioned by Chang and Chiang (2022), using social media to showcase one’s adventure from a tourist destination site is common. The authors add that this adventure often tends to influence others’ destination decisions.

Regarding the effect of behavioral goals towards the use of social media by tourists, the result of the hypothesis (H3a); that behavioral goals would positively enhance the use of social media for tourism purposes was supported. This hypothesis suggests that having specific behavioral goals would lead to a positive impact on the use of social media for tourism-related activities. As affirmed by Kim et al. (2022), when individuals have clear behavioral goals related to tourism, such as finding travel recommendations or planning trips, they are more likely to utilize social media platforms to achieve these goals. This implies social media can provide a wealth of information, reviews, and recommendations from other visitors, making it a valuable resource for those looking to enhance their visit experiences. Having behavioral goals aligns with actively seeking information and assistance on social media platforms, engender tourist in their activities.

On the contrary, the direct relationship between behavioral goals and tourist destination hypothesis (H3b); behavioral goals would positively affect tourist destination decisions decisions was not supported. Even though this proposition was not supported, studies affirmed, that social media plays an intermediary role that influences visitors’ intention toward destination decisions (Pandža Bajs, 2015; Nazir et al., 2022). Given that behavioral goals are naturally intrinsic, an individual’s degree of willingness to settle on a destination is influenced by a self-driven motive. Indeed, Nguyen and Tong (2022) discovered that behavioral motivations influence tourist destination selection and, by extension the accessibility and appreciation of the quality of service being rendered through their online tools by tourism service providers. Besides, tourist revisit intentions are also behavioral tendencies motivated by extrinsic motivation based on online cues from peers and other holidaymakers (Karl et al., 2022). Given the apparent impact of social media on the tourist decision-making process, a positive relationship exists between a tourist’s intent and destination preferences.

The study also set out to investigate the availability of tourism information on social media and its consequences on guests’ or visitors’ destination decisions. The findings show that there is a positive relationship between information availability and social media usage as well as tourism destination decisions. However, regarding a significant relationship, Hypothesis (H4a); that available information to tourists would positively influence social media usage for visitors’ destination decisions was supported. The proposition is supported by existing research, indicating that when tourists have access to information about potential destinations, they are more likely to use social media as a tool to aid their decision-making process (Garcia et al., 2015; Ramírez-Gutiérrez et al., 2018). Tourists rely on social media platforms to gather information about destinations, including reviews, recommendations, travel itineraries, and tips from fellow visitors. When a destination provides ample information through various channels, such as official tourism websites, travel blogs, or online forums, it encourages tourists to use social media platforms to further explore and validate their choices. Moreover, the positive impact of available information on social media usage aligns with the changing dynamics of travel planning. With the prevalence of smartphones and easy access to the internet, tourists increasingly turn to social media to gather real-time information and insights from other visitors, enhancing their overall visit experience.

On the other hand, hypothesis (H4b); available information to tourists would positively affect their destination decisions was not. This suggests contrary to the fact that the availability of information about existing tourism destinations will influence users of social media to ascertain information for decision-making (Bormann et al., 2016; Garcia et al., 2015). Note that, the availability of adequate information has the propensity to influence decision-makers since it presents an opportunity to make an informed decision.

Finally, hypothesis (H5); social media usage will have a direct positive relationship with tourism destination decisions which tested how social media usage and its relationship with tourism destination decisions was not supported. Succinctly, this finding was not expected given the affordances of social media to influence tourist destination decision-making processes (Riyadi & Nurmahdi, 2022; Paniagua et al., 2022). Considering the thought process that goes on before a decision-maker settles on a destination site, it is assumed that the availability of social media will mediate the decision-making process. This is especially true given that most tourists will seek information on a destination site before embarking on their journey. Social media usage significantly reduces information asymmetry, thereby enhancing decision-makers’ choices (Munar & Ooi, 2012). The preference of a tourism destination will thus, be informed by the amount of information possessed by the tourist. The preferred place for promotions and frequent interaction by tourism service providers is social media (Haryani et al., 2022; Ross et al., 2019). Given that the service providers will want to cash in, reliable information is often made accessible to potential tourists on their social media platforms. This explains why tourists would seek first-hand information about a destination site on social media.

6. Implications

The decision to settle on a tourism destination is often a complicated task given the thought process that the individual must go through. As a result, tourists will seek relevant information on available platforms, particularly social media, to help shape and simplify their destination decision-making. Thus, this study makes several contributions to the literature. Nonetheless, studies that focus on segments of tourists, especially in Ghana’s context are limited. Studies on tourism and its accompanied destination decision-making, for example, are understudied (Davies & Cairncross, 2013). Meanwhile, there is a rising interest of tourists in tourism adventures, especially when there are vacations in Ghana (Wireko-Gyebi, 2021). Besides, not much has been explored in this regard. Moreover, the increasing use of social media and its consequences on tourist destination decisions among tourists have not been extensively explored. Thus, positioning this study as key to contributing to knowledge on tourism destination decision-making among tourists would help service providers and relevant stakeholders for sustainable tourism and development in the local economy.

Through the use of UGT, this study explores how social media and its affordances contribute to influencing tourists’ tourist destination decisions. Empirically, understanding tourists’ destination decisions while leveraging social media through the use of the UGT is underexplored. Thus, this study is one of the fore to bring to light the need to understand how social media play a key role in engendering tourists’ decision-making process. Premised on the UGT that technology especially social media plays an important role in generating users’ traction to events, this study shows that, in tourism, social media is symbiotic with the underlying process of tourism destination decisions. Using the UGT provides an understanding of the behavior of tourists when using social media for their destination decisions. Particularly, the utility derived from the use of social media to fulfill the needs of tourists. Thus, contributing to the empirical understanding of gratification sought by tourists through social media. This will also inform tourism marketers to strategically tailor their information on their social media handles to suit the desires of tourists. Factors elucidated through the UGT to explore social media’s effect on tourism destination decisions add to the overarching factors that existing literature has explored. Thus, this study adds to the existing online and social media factors that significantly impact tourist decision-making. UGT emphasizes that individuals select media based on their preferences and needs. The study’s findings shed light on which social media platforms and content formats are preferred by tourists for destination-related information. This knowledge can guide researchers in tourism marketing in choosing the right frameworks for unearthing the drivers of social media in tourism research.

By far, this study comes with some overarching implications for practice. It is imperative that, in recent times, the tourism sector has become one of the most competitive economic sectors globally and locally (Auliya et al., 2020). Ghana, as a key tourism destination, has observed some rising development in the sector. This impressive development has occasioned stern competition among tourism service providers, who are racing against each other. This study brings to the fore a multiplicity of factors that add to their competitive strategies. The study results make it apparent that the evolution of social media has changed the face of tourism locally for which the tourism sectors can reap the dividend if well integrated. The study found that factors such as the image of a tourism destination, the tourists’ behavioral goals, level of contentment, and the availability of destination information on social media significantly influence tourist destination decisions. The study also informs the type of social media and the mechanisms used to mediate the decision-making process. This reinforces that the proliferation of social media and networking platforms such as Facebook, TikTok, WhatsApp, and Instagram play a key role in shaping the tourism sector. While the study found social media to influence tourist contentment, destination image, behavioral goals, and the availability of information, no significant relationship was found between these factors and the final decision to choose a tourism destination. Even though no significant relationship was found between those factors and the destination decision, that does not imply those factors do not affect the tourism decision-making of tourists. Perhaps, their preferences may be under the control of some intrinsic factors that need to be explored by managers of tourism destination sites. Managers need to consider the behavioral tendencies of tourists before tailoring their promotional messages on social media which this study has brought to light in its findings. Contingent on the study’s findings, managers of tourism sites will be guided by the kind of social media strategies they adopt in a bid to keep up with their competitors. Amid the COVID-19 pandemic, several tourism sites were drastically affected. As a solution, some turned to social media to bridge the gap, which fueled social media’s capabilities in transforming the sector. Thus, in times of pandemic, social media can be used to drastically change the mode of service delivery. The study’s insights into tourists’ motivations can inform collaborations with social media influencers. Tourism brands can partner with influencers whose content aligns with the gratifications sought by their target audience, leveraging influencer marketing effectively.

7. Conclusion

This study set out to investigate the driving forces of social media usage and its impacts on the tourism destination decisions of local visitors in Ghana. Drawing on the uses and gratification theory, factors that influence tourist decisions in the literature were derived and quantitatively measured. Based on data collected from 428 tourists around tourism destinations in Ghana, it emerged that most of the tourists (325) used social media in their decision to select a tourism destination. Following the nine hypotheses generated, it emerged that social media usage positively and significantly mediate the relationships between tourist contentment, destination image, behavioral goals, the availability of information, and tourism destination decision. Finally, social media was also found not to have any direct relationship with tourism destination decisions. The study adds to the literature on the increasing competition among tourism destination sites and the factors that influence tourist motivation to choose a specific destination and thereby shape the increasing use of social media by service providers as a key marketing communication tool.

7.1. Limitations

While the researchers believe that this study is sufficiently comprehensive, it was constrained by the focus and thus the tourists centered. The study focused on tourists at selected tour destination sites across Ghana. Again, given the number of tourists who participated in the study at the various tourist destinations, caution must be taken when generalizing the study across developing countries. Thus, future studies can take into consideration the characteristics of the chosen study context and a possible increase in the sample size this study used. Perhaps future studies could also look at not only the generality of tourists but could focus on segments and actors in the tourism value chain, who form the core of the tourism sector. Lastly, the authors will welcome a mixed approach in the future to dive into relevant areas which the present study failed to.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Solomon A. Keelson

Solomon Abekah Keelson is an Associate Professor of Marketing and Strategy at the Business Faculty of Takoradi Technical University, Ghana. He holds a PhD in Marketing and Strategy from Open University, Malaysia, an MBA in Marketing, and a Bachelor of Arts in Economics from the University of Cape Coast, Ghana. Prof Keelson also holds a professional certificate in Marketing from the Chartered Institute of Marketing UK. He is a Chartered member of Marketing - UK and Ghana and a fellow of the Chartered Institute of Management Consultants. Keelson is a renowned academic with several publications and taught for over 25 years. He has also worked as theses Assessor (internationally and externally) for various tertiary institutions in Ghana and other countries. Keelson has also gotten industry experience from working with the Electricity Company of Ghana for about 10 years and consulting for companies such as Ghana Rubber Estate and Laine Service. He is currently the Dean of the Faculty of Business, at Takoradi Technical University.

Emmanuel Bruce

Emmanuel Bruce is a Doctoral researcher at the University of Electronic Science and Technology of China, Chengdu-China, School of Management and Economics. Emmanuel has been in the research domain for the past three years and the results of his research have been published in high-ranked respected journals. He also serves as a reviewer for some respected journals around the globe. His main research areas are SME development, social media Analysis, and Service Marketing.

Sulemana Bankuoru Egala

Sulemana B. Egala holds a Ph.D. in Management Science and Engineering with specialization in Data mining and Information Management from the University of Electronic Science and Technology of China (UESTC). He also holds a bachelor’s and master of philosophy degrees in computing and information systems. He is currently a lecturer at the Department of Informatics, Faculty of ICT at the SDD University of Business and Integrated Development Studies (SDD-UBIDS), Wa. He has a vast interest in the areas of health Informatics, Open Data, and social business analytics.

John Amoah

John Amoah holds a PhD from the Tomas Bata University, Zlin, Czech Republic. He is currently a lecturer at KAAF University College, Kasoa, Ghana specifically with the Marketing and Human Resource Management Department. His main research areas are SME Development, Social Media Analysis, Marketing and Innovation, Consumer Behavior, and Service Marketing. Currently, he is the coordinator for the Business Masters Program of the university. The results of his research have been published in peer-reviewed scientific journals and presented at numerous international conferences around the globe.

Abdul Bashiru Jibril

Dr. Abdul Bashiru Jibril is a Senior Lecturer (Marketing) at Westminster International University in Tashkent, Uzbekistan. Dr Jibril holds a PhD in Marketing Management from Tomas Bata University in Zlin, Czech Republic. His research focuses on Technology adoption, social media analytics, Service marketing, Brand management, and Sustainable e-tourism. He is interested in deploying data mining techniques in extracting intelligence to improve business decision making especially for marketers and corporate success in emerging and developing economies. He has led and been involved in a research team to execute several external projects in Europe and Africa. He is currently a principal investigator of a Fair Work project (UK) between the University of Oxford and the International University of Rabat, Morocco. The results of his research have been published in impacted and ABS/ABDC ranking journals, such as the International Journal of Information Management, International Journal of Consumer Studies, etc., and contributed to book chapters (in Springer) and Conference proceedings. He has also actively participated and presented in numerous international scientific conferences (indexed in WoS/Scopus/Springer), with host countries such as the USA, UK, France, Germany, Saudi Arabia, etc. He serves as Associate Editor for Cogent Business and Management (Taylor & Francis), Editorial review board member for the International Journal of Neuroscience and Neuroinformatics (IJNN) (IGI Global), and Sectional Editor for Current Social Sciences (Bentham Science Publishers).