Introduction

At the start of 2020, the COVID-19 pandemic swept across the globe, causing widespread disruption to global trade and business operations. Governments around the world implemented strict lockdown measures, including movement restrictions and health regulations like social distancing, sanitizing, and vaccinations. These measures presented significant challenges for companies in develo** countries, particularly in Sub-Saharan Africa, where weaker internet infrastructure and over-stretched health systems exacerbated the situation. In Zimbabwe, the tourism industry, which is the country's third-largest contributor to the economy after mining and agriculture, suffered greatly as a result of the pandemic. The industry was already struggling in the context of Zimbabwe's struggling economy, and COVID-19 worsened the situation. On March 28, 2020, the Zimbabwean government declared a nationwide lockdown, which came into effect within 48 h. All non-essential businesses were closed, and residents were instructed to stay indoors for 21 days. Only those in essential service groups were permitted to leave their homes to assist during the pandemic.

Zimbabwe is blessed with numerous natural tourist attractions, including Hwange National Park, Mana Pools, Gonarezhou, Victoria Falls, Matopos, Nyanga Mountains, Lake Kariba, and the Great Zimbabwe Ruins. During the COVID-19 pandemic, when restrictions were eased, a significant number of tourists came from Africa and the Middle East, while fewer came from Europe, America, Oceania, and Asia, which is the opposite of what usually occurs due to proximity, tiresome quarantine procedures and too many restrictions. The Zimbabwe Tourism Authority's statistics on tourist arrivals show that there was an 18.56% decline in 2017, a 20.89% increase in 2018, a 10.21% decline in 2019, and a sharp decline of 76.84% in 2020 due to the pandemic. In 2021, there was a further decline, but in 2022, there was a steady increase as Zimbabwe opened its borders to tourists, and the post-COVID era began (Fig. 1).

Fig. 1
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Tourists arrival in Zimbabwe (2017–2022)

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In the COVID-19 era, the tourism sector has increasingly embraced social media branding, adopted new technology equipment, and placed a huge emphasis on green tourism. These actions have had many benefits, such as raising campaign awareness, achieving worldwide reach without borders, refining client interactions, increasing e-marketing, and managing public reputation [1]. With movement restrictions in place, the COVID-19 epidemic has further strengthened the use of social media and technology as consumers search for and receive information about goods and services online [2]. Furthermore, [3] suggests that during the pandemic, technology applications and social media have been a welcome relief to the global community as they provide up-to-date health-related information. Social media has shifted the world toward a more unified and symbiotic one, assimilating historical stand-alone national markets into a single large marketplace. [4] defines social media branding as the consistent use of the right methods when engaging with a targeted audience on social media platforms, aiming to enhance awareness and attract new end-users. According to [5, 6], social media includes countless social media platforms such as Facebook, TikTok, LinkedIn, Instagram, Twitter, WeChat, WhatsApp, and many applications that play a strategic role in influencing consumer behavior. Social media branding has become an inescapable medium of communication in people's daily lives and has a significant impact on consumer behavior, including tourists [7].

Service delivery has become increasingly important, and the focus has shifted from product development to service conveyance expansion. Therefore, tourism supply chains are adopting new technologies in service departments, and self-service technologies are increasingly being used in the service delivery process [8]. As part of the service trade, hotels are continuously investing in self-service machinery to maximize service superiority and ease overall expenses [9]. Moreover, the pandemic has shown people that they can generate innovation and expansion. Advancements in artificial intelligence (AI) and new technologies have made it increasingly viable for robotics to perform warden, housekee**, dining, and other service tasks in the tourism sector [10]. However, some scholars have found the acceptance of social automatons to be non-comprehensive, as the tourism sector should retain high-touch facilities [11, 12]. The COVID-19 epidemic has forced the tourism supply chain to change its perspectives on drones, conveyance robots, and facility provision robots as they try to mitigate pandemic woes [13]. The tourism supply chain was forced to adopt new technology and social media branding as they complied with COVID-19 movement restrictions, and nothing has changed post-COVID-19, as people continue to consult social media and make use of ever-changing technology. The exceptional evolution of social media and the usage of technology, motivated by the sharp growth of internet use, have changed the forms of tourists searching for information and arranging excursions [14]. Travelers use social media and technological gadgets for information search when scheduling travel engagements [15]. Social media branding and technology tools frequently provide easy access to important information that can be used by consumers [16].

Research questions

  1. 1.

    What are the effects of social media branding on tourists’ behavior and green tourism post-COVID-19?

  2. 2.

    Does the influence of tourists’ behavior on green tourism post-COVID-19 gets stronger for tourists who make use social media branding and embrace technology, compared to those who do not?

  3. 3.

    Does technology adoption have impact on tourists’ behavior post-COVID 19 and will this relationship get stronger for tourists who are eco-friendly?

  4. 4.

    What are the mediating effects of tourists’ behavior on two independent variables social media branding and technology adoption and a dependent variable green tourism?

The literature review reveals several areas in the research on technology adoption, social media branding, tourists' behavior, and green tourism that require further attention [17,18,19,20]. Previous studies have predominantly focused on these factors in developed countries [21,22,23,24], neglecting the specific challenges faced by develo** nations [25, 26]. These challenges include limited financial resources, inadequate healthcare infrastructure, and insufficient social welfare systems, which were particularly evident during the COVID-19 pandemic when develo** countries heavily relied on external aid [27,28,29]. Additionally, despite the rapid advancements in robotics, artificial intelligence, and service automation as responses to the pandemic, no African develo** country has adopted these advanced technologies [30, 31]. While scholars recognize the importance of technology adoption, tourists' behavior, and social media branding in promoting green tourism, there is limited research on their impact in develo** countries [32]. According to statista [33], as of January 2022, there were approximately 4.65 million internet users in Zimbabwe, accounting for 30.6 percent of the total population. Compared to the previous year, there was a notable increase in 265 thousand internet users, representing a growth rate of 6.0 percent. However, despite this growth, a significant portion of the population remained offline, as around 10.56 million people, comprising 69.4 percent of the total population, did not use the internet at the beginning of 2022, this further explains lack of technology and social media access in Zimbabwe. Therefore, the researchers aim to address these gaps by investigating how social media branding, technology adoption, and tourists' behavior influence green tourism in develo** countries, with a specific emphasis on Zimbabwe in the post-COVID-19 context.

Literature review

Social media branding on tourists’ behavior and green tourism

According to [34, 35], the increasing prevalence of social media and the emergence of wired societies, enabling instant communication, discussions, and the sharing of user-generated information. This has resulted in the remarkable popularity of various social media platforms like Facebook, Twitter, Instagram, TikTok, WhatsApp, WeChat, and Messenger, with billions of active users within the tourism sector [36]. Social media has evolved into a prominent communication channel, extending beyond personal messaging to encompass discussions on pandemic-related information, measures to minimize the transmission among tourists, and it has gain popularity aftermath [37].

The theory of planned behavior, proposed by [38], suggests that social media significantly impacts tourists' personal opinions, behavioral beliefs, subjective norms, and perceived control. In a study conducted by [39], which focused on social media, consumer behavior, and service marketing, it was found that social media has a strong influence on consumer behavior due to its ability to facilitate faster and more direct communication between buyers and sellers. Several studies, such as those by [24, 40, 41], have documented that social media serves as a vital source of information that greatly influences travelers' decisions regarding travel plans and destination preferences. Moreover, research conducted by [42] has indicated a correlation between social media usage and the perception of travel destination image.

Numerous studies on green tourism have demonstrated the positive impact of social media on travel behaviors [43,44,45]. Social media has been found to influence tourists' attitudes, which is a crucial factor in predicting, explaining, and influencing their behavioral intentions, especially during and after the Covid-19 pandemic [46]. Assaker and O'Connor [47] discovered that social media platforms such as Facebook, Twitter, TikTok, Instagram, WhatsApp, WeChat, travel assessment sites, and virtual platforms play a significant role in reducing uncertainties related to visiting degraded environments, pandemic-affected regions, politically unstable areas, and regions prone to terrorist attacks. Hasan and Rahman [48] established a strong positive correlation between attitude and intentions to visit green tourist resorts post-Covid-19.

Scholars such as [49, 50] emphasized that social media branding provides an opportunity for people to interact and share experiences online, motivating others to do the same. Reyes [51] added that social media can shape public opinions and daily lives, depending on users' purposes and goals. According to [52], eco-friendly tourists can easily gather information online and make travel decisions based on that information. Muslim [53] found a positive correlation between social media usage and tourists' intentions, while Wut et al. [54] discovered that social media branding reduces tourists' risk perceptions and increases motivation to visit destinations even in crisis circumstances like natural disasters, extremist attacks, and political conflicts. Social media fosters participation, enabling like-minded consumers, such as those interested in green tourism, to share content, seek opinions, and evaluate products and services through online discussions [55]. Numerous studies have shown that tourists now rely on social media platforms to gather information about products and services from the comfort of their homes. They compare and contrast information or experiences shared by other users, including topics related to environmental issues, prices, modes of transport, destination choices, and essentially anything that tourists seek. Social media provides readily available information for eco-conscious travelers, facilitating informed decision-making processes.

Tourists’ behavior and green tourism

As the tourism and hospitality industry continues to gain prominence, there is a growing recognition of our accountability for contributing to environmental degradation and climate change [56, 57]. Given that natural resources and the physical environment are crucial assets in the tourism industry, neglecting environmental protection would be counterproductive, as it directly influences tourists' decision-making processes [58]. Fernando [59] highlights that although tourism has become one of the fastest-growing industries, global criminal activities such as terrorism, warfare, epidemics, natural disasters, and economic recessions have hindered its progress. These events impact the well-being and safety of tourists’ destinations, thereby affecting tourists' decision-making processes [60, 61].

Tourism is influenced by various external forces, including natural events and human-made disasters, as noted by [62, 63]. These human actions and disasters should be prevented as they can significantly impact the movement of tourists, especially those who prioritize a clean environment [64]. Braun et al. [65] suggest that different types of environmentally related behaviors have distinct causes, and interventions designed to change one behavior may not necessarily influence others. Song et al. [66] conducted research in different cities in China and found that as air pollutant concentrations increased, the number of tourist activities decreased meaning that tourists are eco-friendly sensitive. Additionally, [67] discovered that tourists in Hong Kong spent less time in polluted areas and preferred to spend more time in shop** malls. When planning their travels, tourists must consider various constraints such as the ambiance of tourist resorts, transportation options, length of stay, and financial budget [68]. Moreover, [69] highlighted that tourists' attitudinal beliefs, including their concern for the environment, influence their energy-saving behavior and green purchasing decisions, which can also impact their budgeting for trips.

Lee et al. [70] commented such as destination-related travel restrictions such as the political and security situation, environment, climate and weather [71], or distance traveled are different factors that influence or guide tourists to stall tours or travel to alternative destinations [72]. Bavik et al. [73] added that tourists predetermined thoughts and imagination about resort area or the environment which they intend to visit also affects their decision making. The environment plays a significant part in tourist travelling frequency which are: It influences the decision-making process when choosing travel destinations [74] and coordinates post-decision behavior including participation (field experience) [75], satisfaction (during and off the resort environment) [76], and future behavioral intentions (revisiting intentions) [77].

Lewis et al. [78] similarly established that environment is a strong factor to consider when selecting a travelling destination post-COVID19. Previous studies by [79,80,81] also instituted a positive correlation between green tourism and tourists’ decision making. Therefore, based on the evidence found in previous studies, we can conclude that tourists’ behavior has a positive impact on green tourism that is tourists who are environmental sensitive are affected with the state tourist resort they visit, and it plays a significant role in that decision-making process. Given that natural resources and the physical environment are critical assets in the tourism industry, ignoring environmental protection is counterproductive, as it influences tourist decision-making [81]. From the literature, it is vibrant that as the tourism and hospitality industry continue to expand, it is increasingly clear that people cannot evade responsibility for contributing to environmental degradation and climate change. The relationship confirms a significant relationship between tourists’ behavior and green tourism.

Technology adoption on tourists’ behavior and green tourism

According to [82], technology applications and social media platforms have played a crucial role in providing the global community with vital health-related information during and after the COVID-19 pandemic. Similarly, [83, 84] emphasize the significance of technology and social media in promoting green tourism and influencing tourists' decision-making processes. The utilization of technology is highly important in the research of green tourism, as highlighted by [85], and the success of technological implementations in tourism relies on user acceptance [86]. The COVID-19 pandemic has led to a shift from traditional marketing approaches toward technology, which has proven instrumental in facilitating decision-making among tourism stakeholders [87].

Early theories on technology acceptance, such as the Diffusion of Innovation Theory (DIT) by Rogers [88], were centered around the decision-making process related to adopting innovations. They considered factors like relative advantage, compatibility, complexity, testability, and observability. Another theory called Flow Theory, introduced by Csikszentmihalyi [89], introduced the concept of optimal experience by incorporating elements like concentration, playfulness, and perceived control. Ajzen and Fishbein [90] proposed the Theory of Rational Action (TRA), which focused on behavioral intentions to use innovations, influenced by behavioral beliefs and subjective norms of end-users. As consumer technologies emphasizing hedonic properties became more prominent, researchers started examining factors like satisfaction to explain adoption behavior [91].

Research studies have indicated that visually appealing content and the integration of multi-sensory cues, such as combining images and sounds, play a crucial role in creating high levels of arousal and presence in virtual environments [91, 92]. Moreover, [93] argues that tech-savvy tourists are increasingly utilizing smart tourism applications for travel planning, while Kabadayi [94] highlights that smart tourists now employ sophisticated algorithms and data from various sources to enhance their travel experiences in a cost-effective manner. Furthermore, Reis et al. [95] underscore the significance of technology and internet usage in facilitating connectivity among people, enabling information sharing, and fostering relationship building.

Robotic technologies are gaining popularity in various high-traffic public areas, including tourist resorts, airports, and shop** malls, due to their ability to navigate and detect potential risks that may go unnoticed by the human [96, 97]. According to Hansi et al. [98], tourists are more inclined to adopt technology that is reliable, safe, and user-friendly. The emergence of the COVID-19 pandemic has further accelerated the integration of robotics in the tourism industry, driving innovation and benefiting all stakeholders, including tourists [99]. The widespread use of mobile devices has also led to the proliferation of mobile applications (apps), revolutionizing the operations of the travel industry and transforming the way people travel [2).

The outer loadings of a factor analysis for the tourist behavior construct, based on five variables (TB1, TB2, TB3, TB4 andTB5). According to your table, tourist behavior is highly correlated with TB2 and TB3, with loadings of 0.858 and 0.858, respectively. This suggests that these variables are strong indicators of the tourist behavior construct. All other variables are strongly related; TB1 value is 0.756, TB4 value is 0.818, and TB5 value is 0.857.

Green Tourism is highly correlated with all variables, but especially GT4 which loadings of 0.844. This implies that these variables are powerful predictors of the green tourism construct. Furthermore, GT1, GT2, GT3 and GT5 have high loadings of 0.803, 0.799, 0.822 and 0.801, respectively, indicating that they are strong indicators of Green Tourism. This result is important since it assists in understanding the relationships between these variables and green tourism and to potentially develop strategies for promoting and measuring Green Tourism practices in the tourism industry.

Technology adoption had five variables (TA1, TA2, TA3, TA4 and TA5), respectively, as shown in table. The construct had highly rated variables with TA1 and TA4 both having 0.941values meaning the variables were powerful predictors of the technology adoption construct, while TA2, TA3 and TA5 have 0.924, 0.873 and 0.928, respectively. This result is significant since it assists in accepting the relationships between these variables and technology adoption and to possibly develop policies for promoting and measuring technology adoption in the green tourism industry. The study went on to calculate the direct relationships.

Direct relationships

In this study, the PLS-SEM technique is utilized to predict relationships and construct statistical models that explain causal correlations, as suggested by Hair et al. (2019). This approach involves generating numerous subsamples (e.g., 5000) from the original sample with replacement to derive bootstrap standard errors, which in turn yield T-values for testing the significance of structural paths. The use of bootstrap** helps approximate data normality by estimating the distribution's spread, shape, and bias within the sampled population, following the insights of Chin (1998). The results of this analysis are summarized in Table 4 and depicted in Fig. 2 below and the present direct relationships:

Table 4 Direct relationships and hypothesis testing
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Fig. 2
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PLS-SEM-bootstrap** results

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Direct relationship refers to the direct effect between two variables in a model, the magnitude and significance of the direct relationship can be interpreted using path coefficients or path weights obtained from the analysis and the research has five direct relationships: H1 social media branding (SMB) to green tourism (GT), H2 social media branding (SMB) to tourists’ behavior (TB), H3 technology adoption (TA) to green tourism (GT), H4 technology adoption (TA) to tourists’ behavior (TB), H5 tourists’ behavior (TB) to green tourism.

The results from H1 hypothesis show T-statistics value of 6.756 exceeding the threshold of 1.96, indicating a significant positive relationship. This finding supports the H1 hypothesis, suggesting a significant positive relationship between SMB and GT. On the other hand, for the H2 hypothesis, the T-statistics value of 8.466 suggests a strongest significant positive relationship SMB and TB. Hence, the H2 hypothesis is supported, indicating there is a direct relationship between the variables. Moreover, for the H3 hypothesis, the T-statistics value of 5.253 indicates a significant positive relationship, supporting the H3 hypothesis. This implies that TA has a direct effect on GT. H4 and H5 have T-statistics values of 4.085 and 4.889, respectively, indicating both positive direct relationship between TA and TB as well as TB and GT. All the T-value statistics for 5 hypotheses were above the 1.96 threshold indicating a direct significant relationship between the constructs. The research went testing the mediation relationship of tourists’ behavior.

Specific indirect effects

Specific indirect effects show the effects of a mediator on independent variables and dependent variables which is also called a mediation relationship. A mediation relationship refers to a relationship between three variables: the independent variable (IV), the mediator variable (MV), and the dependent variable (DV). It represents a process in which the IV influences the DV indirectly through the MV. The MV acts as an intermediate variable that mediates the relationship between the IV and the DV. In this study, we had two mediation relationships: H6 SMB (IV), TB (MV) and GT (DV), H7 TA(IV), TB (MV) and GT (DV) as shown in Table 5.

Table 5 Mediation relationships and hypothesis testing
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The results of the variance accounted for (VAR) analysis indicate that tourists’ behavior partially and fully mediates the relationships between the variables. H6 tourists’ behavior has a significant indirect effect on the relationship between SMB and GT, accounting for 53.5% of the variance, meaning TB partially mediates the relationship. Similarly, H7 tourists’ behavior has a strong indirect effect on the relationship between TA and GT, accounting for 75% of the variance, meaning TB fully mediates the relationship.

Discussion of findings

The discussion of the findings will be based on the conceptual model (Fig. 3). Firstly, hypothesis H1 the results supported that social media branding has a direct correlation with green tourism, and social media branding plays a vital role in promoting sustainable tourism practices. The use of social media platforms such as We Chat, Facebook, Instagram, Twitter, and YouTube can efficiently increase awareness of green tourism and encouraging tourists to engage in sustainable tourism activities. This is in line with some literature for example: [20, 40, 50] found that social media platforms, such as Facebook, Twitter, Tik Tok, Instagram, WhatsApp, We Chat, travel assessment sites, and virtual scenes are predominantly supportive in eradicating uncertainties of visiting degraded environments, pandemic infested regions, political unrest and terrorist attacks areas. Social media branding can be of importance in creating a positive image of green tourism in the minds of potential tourists. The research findings can aid green tourism supply chain in Zimbabwe and other develo** countries to implement operational social media branding approaches that promote green tourism.

Fig. 3
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Conceptual model

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Secondly, hypothesis H2 was supported and showed that social media branding has a direct relationship with tourist behavior, and meaning social media branding can affect the tourists’ behavior toward green tourism. Social media branding can create awareness of sustainable tourism practices and provide information on how tourists can engage in green tourism. Tourists share their involvements and experiences on green tourism, and this can influence the behavior of other tourists. The results support H2 hypothesis is significant because social media branding plays an essential role in promoting green tourism by influencing tourist behavior, and it is agreement with [6, 53]who established a high impact positive correlation between social media, attitude and intentions to visit green tourist resorts post-COVID 19. Generally, the results support hypothesis H2 and stresses how important social media branding influences the tourist behavior toward green tourism, and it highlights the need for green tourism supply chain to develop an effective social media branding tactics targeting tourists who are interested in sustainable tourism practices.

Third hypothesis H3, signified that technology adoption has a direct relationship with tourist behavior and the results supported the notion. Making technology can impact the tourists’ behavior toward green tourism. Technology adoption aids access to information and resources that help in engaging green tourism practices for instance mobile applications help tourists to find environmentally friendly accommodation, access to information on green tourism and provide feedbacks on their experiences. The results agree with previous scholars [3, 39, 75] emphasize that technology and internet usage facilitate people to connect with each other, share information, and build relationships. Inclusively, the results support hypothesis H3 and the significance of technology adoption as a tool for influencing tourist behavior toward green tourism, and it emphasizes the need for green tourism supply chain to develop an effective technology adoption plans that target tourists who are pro eco-friendly tourism.

Fourth hypothesis H4 pointed out that technology adoption has a direct relationship with green tourism and the results supported the notion meaning technology adoption positively influences green tourism. If green tourism supply chain embrace technology, it facilitates the growth and promotion of green tourism as they share information and resources related to green tourism. The literature from [3, 12, 98] highlights the important role that technology and social media have played in promoting green tourism and influencing tourists' decision-making which is in line with researchers’ results. Lastly, the results that support hypothesis H4 highlighted how important technology adoption is as a weapon for promoting green tourism and reducing negative impacts on the tourist environment.

Firth hypothesis H5 proved that tourism behavior has a direct relationship with green tourism as supported by the results meaning tourist behavior’s influence in promoting green tourism is significant. Tourist behavior can be affected with many factors such as availability of green accommodation choices, transport options, infrastructure, access to information and resources available to them through technology adoption and social media branding. Previous studies by [56, 67, 77] also instituted a positive correlation between green tourism, tourists’ behavior and decision making. The findings supporting hypothesis H5 are significant because they suggest that tourist behavior can play a critical role in promoting green tourism practices. Green tourism supply chain can use the information and resources available through technology adoption and social media branding to influence tourist behavior and promote green tourism.

Sixth hypothesis H6, social media branding has a direct correlation with green tourism, and this relationship is partially mediated by tourist behavior, and the results supported the equation. The direct association in between social media branding and green tourism tells that social media can be used to promote green tourism. The partial mediating effect of tourist behavior expresses that tourist behavior has a positive significant relationship between social media branding and green tourism. The results agree with researches from [31, 37, 52] who found that social media branding reduces tourist risk perceptions and increases tourist motivation to visit in crisis circumstances such as natural tragedies, extremists’ attacks and political conflicts. Conclusively, results support that social media branding and tourist behavior are important variables in green tourism and reducing the negative eco-friendly impacts.

Seventh hypothesis H7 technology adoption has a direct association with green tourism, and this relationship is partially mediated by tourist behavior, and the results supported the model. The direct relationship between technology adoption and green tourism suggests that the use of technology can promote green tourism. Scholars like [Recommendations and areas of future research

Green tourism supply chain in Zimbabwe and other develo** countries should develop and implement effective social media branding and technology adoption strategies that target changing tourist behavior toward green tourism. The government and non-governmental organizations should provide education and training programs to increase awareness of green tourism among tourists and green tourism supply chain. The green tourism supply chain should collaborate to improve infrastructure to support green tourism. Green tourism supply chain should promote outdoor activities to encourage more ecologically tourism practice.

A study can be conducted to investigate the effectiveness of different social media branding and technology adoption strategies in promoting green tourism in Southern Africa. On another note, a study can be conducted to examine the role of government policies and regulations in promoting green tourism in Zimbabwe.