Exploring the Link Between Social Media Adoption and Saudi Arabia SME’s Sustainable Performance: The Moderating Role of COVID-19

Abstract

Small and medium-sized enterprises (SMEs) use social media to communicate effectively with stakeholders. However, little is known about the influence wielded by social media adoption on sustainable performance during COVID-19. Based on the technology–organization–environment (TOE) framework, our study developed an integrated model to explore the factors affecting social media adoption and its effect on sustainable performance in SMEs in the Saudi Arabian context. The quantitative method of a survey was used to collect data from SMEs owner-managers and CEOs. Partial least square was used to analyze data collected from 609 respondents. The findings revealed that environmental factors (i.e., the intensity of the competition, competitive pressure, and the bandwagon effect), technological factors (i.e., relative advantages and compatibility), and organizational factors have been the key drivers of social media adoption in SMEs during COVID-19. It also indicated that social media adoption is a key predictor of social, environmental, and economic sustainability. This study provides SMEs with meaningful implications about ways of fostering sustainable performance.

Keywords

social media adoption economic sustainability social sustainability environmental sustainability SMEs

Introduction

During the Covid-19 pandemic, small and medium-sized enterprises (SMEs) were severely harmed by the lockdown measures enforced by governments around the world (Al-Adwan & Kokash, 2019; Hu et al., 2023). Although the pandemic has had a significant impact on the supply and demand situations faced by businesses of all sizes, a report by the OECD (2020) claims that small and medium-sized enterprises (SMEs) have suffered more because of their inability to adapt quickly to sudden changes in the environment (Hu et al., 2023; M. A. Kumar & Ayedee, 2021). Furthermore, in relation to large enterprises, SMEs are especially susceptible to external environmental disturbances due to a lack of liquid and non-liquid resources. There has been a worldwide failure of small and medium-sized enterprises (SMEs), and this has been especially notable in emerging nations. Prior research claims that, due to these countries’ heavy reliance on SMEs, Covid-19 has pushed economies to the verge of collapse (Alghamdi, 2023; V. Kumar et al., 2022; Ragazou et al., 2022). More than half of the labor force is employed in the unofficial sector, while small and medium-sized enterprises (SMEs) account for 95% of the private sector and produce 40% of the countries’ GDP (Abed, 2020). For instance, the Central Bank of Jordan (CBJ) has initiated a quantitative easing strategy with a 500 million Jordanian dinar stimulus package in light of the seriousness of the Covid-19 threat to SMEs (Al-Adwan et al., 2020). Nevertheless, small and medium-sized enterprises (SMEs) have been given the chance to experiment with innovative methods of crisis planning, thanks to Covid-19 (Al-Ajlouni, 2021; Alismaili et al., 2020). Thus, digital technologies, especially social media, offer a one-of-a-kind venue for SMEs to connect with consumers and boost their long-term viability. Covid-19 has been lauded for compelling companies to use both traditional and digital distribution methods (Alrousan et al., 2020).

Many studies have looked into the advantages for companies of using social media for and have determined that they outweigh the disadvantages (Basit et al., 2020). Previous examination revealed that 70% of people in the United Arab Emirates (UAE) said they rely on social media for product recommendations before making a purchase (Bertoni, 2020). Some data show that the social media expands audience size via user-generated content and brand interaction (Bhattacharya & Wamba, 2015). Therefore, people think of social networking sites as an online bazaar where they may buy and sell goods and services (Arora & Predmore, 2013). Small and medium-sized enterprises (SMEs) can use the social media to reach customers in new regions without establishing a physical presence there (Bakri, 2017). SMB owners like it since it eliminates the need to worry about such matters as travel time and distance (Batikas et al., 2012). Because of its relevance to SMEs, social media has emerged as a key theme in academic studies of business and entrepreneurship (Beatty et al., 2001).

Prior study indicates that, with their low resources, SMEs might profit greatly from employing alternative business management tools like social media (Beebe et al., 1998). Much earlier research focused on B2C (business-to-consumer) applications of social media. Numerous studies have looked at the effects of social media on various aspects of business, including customer service (Bergeron et al., 2001) advertising (Bilbao-Osorio et al., 2014) market research (Blanchard, 2011) and word-of-mouth advertising (Buonanno et al., 2005). It is surprising that so few researchers have examined the impact of social media use on sustainable performance in the setting of SMEs (Capterra, 2022). Social media’s potential to enhance business management and, more specifically, its effect on company performance has been the subject of only a small number of studies so far (Cassel et al., 1999). Although social media use, its obstacles and metrics, have been the subject of research in the context of SMEs (Biucky & Harandi, 2017), the impact of social media adoption on the long-term success of SMEs in the Middle East, and particularly in Saudi Arabia, remains unclear. Therefore, our study seeks to develop an integrated model that explains the factors affecting social media adoption and its effect on sustainable performance. It also explores the moderating role of COVID-19 on these relationships.

The current competitive situation is characterized by increased unpredictability and quick changes in market-demand, a lack of resources (financial, organizational, and human), and an increase in competition because of globalization (Qalati et al., 2021). Furthermore, some businesses delay adopting and using social media because of a lack of technical skills and trust considerations (Hu et al., 2023), the diversity of its existing forms, and a misunderstanding of how to implement and manage its utilization (M. A. Kumar & Ayedee, 2021). These factors may contribute to the widening gulf between SME adopters and non-adopters in developing economies. Because of its low cost and ease of use, social media can help small and medium-sized enterprises (SMEs) reach many clients. Despite the rise in popularity of social media platforms, many individuals in Saudi Arabia are still wary of sharing personal information online (Abed, 2020). Despite citizens’ lack of trust, government regulation of e-commerce is ubiquitous in Saudi Arabia (Abed, 2020). However, there aren’t enough research on how SMEs in underdeveloped nations like Saudi Arabia use social media. The conditions and the context in which SMEs are affected by social media are gradually becoming the attention of SMEs and industrial marketing researchers (Qalati et al., 2021).

The purpose of this study is to provide a better understanding of the elements that influence the feasibility and efficacy of social media adoption at the small and medium-sized enterprise (SME) level within the context of the technology-organization-environment (TOE) paradigm. According to Qalati et al. (2020), the TOE framework is made up of three different elements: the technological, the organizational, and the environmental. The term “technological construct” is used to describe the organization’s use of both existing and emerging technologies. Organizational theory pertains to the various facets of organizations, such as their structure, size, scope, management hierarchy, and associated problems. The term “environmental” describes the context in which businesses function, including the presence of regulatory bodies, industries, and rivals. Linear models such as the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) have been employed in previous research (Erjavec & Manfreda, 2022; Khan et al., 2021), however it has been suggested (Qalati et al., 2020) that these models fail to account for contextual elements such organizational culture. Thus, the TOE has integrated human and non-human characteristics into a single model, giving it an edge over more conventional frameworks like UTAUT and TAM (Qalati et al., 2020). In addition, Chang et al. (2022) stated that SM adoption in SMEs employing framework has received insufficient attention. Moreover, Abed (2020) showed that very little work has been done in the context of Saudi Arabia.

The next section describes the study background and hypotheses development. Conceptual Framework and Hypotheses Development section concerns the research methods, while Methods section contains the study analysis and results. Results section outlines the discussion and implications, while Discussion and Implications section indicates the limitations of the research and some directions for further study.

Research Background

Social Media Adoption in SMEs

Using social media has been shown to improve a company’s bottom line in a number of studies before now (Ahmad et al., 2019). The usage of social media has been found to raise revenue, decrease costs, enhance customer service, expand the company’s reach and brand awareness, increase website traffic, and strengthen B2B partnerships (Hoffman & Fodor, 2010). As a result, many companies view it as a top priority and incorporate it into their day-to-day operations as a matter of course (McCann & Barlow, 2015). However, businesses need to think about why they’re using social media and how they’ll know whether it’s working (Hoffman & Fodor, 2010). Small and medium-sized enterprises (SMEs) who do not utilize social media strategically are less likely to reap its full benefits, according to research by McCann and Barlow (2015). The divide between those who have found social media success and those who haven’t is expanding as a result. As a result, long-term viability for non-adopters is reduced (Dwivedi & Pawsey, 2023).

By using social networking sites (SNSs), social media facilitates the very rapid sharing of ideas, opinions, and other expressions amongst a large group of people (Chiu et al., 2017). Twitter, Facebook, Instagram, LinkedIn, and countless blogging platforms are just a few of the many SNSs that have sprung up over the years (Chong & Olesen, 2017; Dutot & Bergeron, 2016). The resource-based view (RBV) of enterprises, which asserts that a company’s competitive advantage arises from its rare, precious, inimitable, and non-subsumable talents, insists on the importance of SNS for SMEs in the current crisis (Zahra, 2018). It has been shown that SMEs) that were able to deploy SNSs amid lockdown limitations fared better than those that were not, making the RBV of competitive advantage particularly useful during crises like Covid-19 (Tajvidi & Karami, 2017).

Social media/digital marketing has been found to have a greater impact on communication, credibility, price, and control mechanisms than traditional marketing communication techniques like advertising, sales promotions, public relations, and personal selling (Auh & Menguc, 2005). This brief analysis demonstrates that social media is a crucial tool that SMEs can use to mitigate the effects of the Covid-19 issue (Norris et al., 2017). Many SMEs are wary of implementing this strategy due to concerns about the potential effects on their business from a variety of factors (Auh & Menguc, 2005). Because there are many different influences on SMEs’ adoption of social media, this study utilizes the TOE framework to develop a conceptual framework to understand the factors affecting social media adoption which in turns impact SMEs sustainable performance.

The Technology–Organization–Environment (TOE) Framework

Tornatzky (1990) created the (TOE) framework. It has been validated as a helpful tool for examining the technological, organizational, and environmental factors at play in an organization’s adoption of new technologies. Many studies have applied the TOE model to examine the rate and nature of technology adoption by micro, small, and medium-sized organizations. Using the TOE model, Alshamaila et al. (2013) analyzed how SMEs in the UK went about adopting cloud computing. Eleven factors that the authors feel significantly affect cloud computing adoption among UK SMEs were found. Perceived value, difficulty, geographical constraints, adaptability, liability, scope, backing from upper management, history of innovation in the industry, business sector, market penetration, supplier initiatives, and outside computing help were some of the factors considered. Likewise, Sugandini et al. looked at how 250 SMEs in the Yogyakarta area of Indonesia used social media to deal with the aftermath of the Covid-19 outbreak. The research found that small and medium-sized enterprises (SMEs) affected by the Covid-19 problem recognize the value of social media and are eager to start using it. However, their intents to do so are heavily influenced by things like their perceptions of relative advantage, complexity, compatibility, employee abilities, management’s backing, a competitive edge, government assistance, and environmental uncertainty. Organizational innovation adoption can be broken down into three categories using the TOE framework (Baker, 2012): technological, organizational, and environmental. Technology adoption research has relied on the TOE framework (Qalati et al., 2021) due to its robust theoretical foundation and empirical backing. A literature assessment on technology adoption in SMEs was carried out to determine the structures within the TOE framework for this investigation. Khan et al. (2021) identified various elements that may affect the adoption of social commerce by SMEs as a result. Therefore, this study adopts the TOE framework to understand factors affecting social media adoption in SMEs enterprise in Saudi Arabia.

Sustainable Performance

The industrial sector’s use of natural and green resources has vastly improved as the sector itself has developed and expanded (Yavuz et al., 2023). In particular, this circumstance has drawn on the availability of natural resources, leading to environmental depletion. As a result of rising expectations, the situation has become increasingly dire (Abdelmoety et al., 2022; Datta et al., 2019). Environmentalists and ecologists have praised companies for incorporating green practices and cutting-edge research into their operations (M. A. Kumar & Ayedee, 2021). These issues have also been addressed as aspects of sustainable development in the modern literature on environment management. Experts and academics who are giving the topic its prominence at the moment still disagree on the concept and meaning (Aboul-Dahab et al., 2021; Mousa & Othman, 2020). Sustainable development, as defined by the “World Commission on Environment and Development” (WCED, 1987), is universally agreed to mean “development that satisfies the requirements of the present without compromising the ability of future generations to satisfy their needs.” For the sake of this concept, sustainable performance takes into account not only financial but also environmental and social factors. The “triple bottom line” (TBL) encompasses three pillars of sustainable performance that will be important for present and future generations (Agag, 2019; Kaplan & Haenlein, 2010). Giving equal weight to the environment, economy, and society, it may be called an integrative theory of sustainability (Agag et al., 2020; Trainor et al., 2014).

To measure sustainability, we focus in this study on the environment and on economic and social sustainability. Managing industrial waste properly, cutting down on toxic waste and carbon dioxide emissions, lowering the probability of dangerous incidents in manufacturing facilities, and making eco-friendly products are all crucial to SMEs (Ahmad et al., 2015; Denkta et al., 2020). We need to rein in industrial decline for the sake of environmental sustainability if we want to forestall global warming and unpredictable weather. As a second point, economic sustainability (ECOS) is closely linked to the urge, for instance, to save money, make money, conserve energy, and turn trash into cash (Agag and El-Masry, 2016; Ainin et al., 2015; Alarcon et al., 2015). In fact, businesses that prioritize environmental sustainability by cutting down on the harmful byproducts of production will see their bottom lines improve as a result (Agag et al., 2023a; Coombs, 2007). Last but not least, social sustainability (SOCS) is concerned primarily with promoting open lines of communication between the public and private sectors, guaranteeing everyone an equal shot at success, and protecting and improving the public’s health, safety, and welfare (Agag et al., 2023b; Dahnil et al., 2014; Davis, 1989; Leonardi & Vaast, 2017). Many strategic combinations, including the use of social media, have been shown in recent research to be vital for attaining sustainable development (Agag et al., 2024a; Maduku et al., 2016). Thus, sustainable performance can be understood as “an improvement that incorporates environmental, economic, and social elements.”

Conceptual Framework and Hypotheses Development

This study developed an integrated model based on TOE framework to explain the variables affecting social media adoption in Saudi Arabian SMEs. It also explores the influence of social media adoption on sustainable performance through the moderating effect of COVID-19 (Figure 1).

Figure 1.

Research model.

Environmental Factors

According to E. Rogers (2003), the company’s culture can be a driving force for or a stumbling block in the introduction of new technologies. Here, the term “environmental context” refers to the surrounding conditions that must be favorable to a company in order for it to thrive. Forces from suppliers, a firm’s associates, and competitors all play a role in pushing SMEs to use e-commerce platforms (Agag et al., 2024b). However, businesses can’t embrace technology unless they have the resources to do so and the backing of the government. According to research conducted by Ragazou et al. (2022), small and medium-sized enterprises (SMEs) in Jordan can reap benefits from adopting digital marketing strategies. The benefits, however, will not be realized until there is sufficient network infrastructure and government assistance. The firm’s external environment consists of the market structure and factors that make up the environmental construct. Competitive pressure, regulatory support, external pressure, competitive intensity, the bandwagon effect, and institutional pressure are all elements that make up an organization’s surrounding environment (V. Kumar et al., 2022; Qalati et al., 2021). In keeping with previous research, the environmental component of the TOE framework in the context of SMEs has been taken to be competitive pressure, intensity, and the bandwagon influence.

Prior research revealed that the corporate setting is a major influence on whether or not employees are willing to embrace new technologies (Abu Bakar et al., 2019; Agag and Eid, 2020). Here, we understand the environmental context to refer to the non-internal forces that must align in order for a company to thrive. Prior examination claims that suppliers, a firm’s colleagues and its competitors all exert immense pressure on SMEs to use e-commerce platforms (Agag et al., 2024c; Haseeb et al., 2019). Without the proper resources and political backing, however, businesses cannot adopt new technologies. Researchers found that SMEs could reap benefits from adopting digital marketing strategies (Agag et al., 2019; Godina et al., 2020). Nonetheless, the intensity of the competition, the pressure to survive the competition, and the “bandwagon effect” are driving the widespread use of social media by small and medium-sized enterprises.

The present study maintains that SMEs in developing nations can use the cutting-edge technology of the social media to implement new strategies and react to competition. Moreover, prior research has argued that this is especially important for SMEs today, which operate in a more volatile business environment as a result of globalization and increasing digitalization (Aldossary et al., 2024; Dias Canedo et al., 2020). In this regard, competition intensity is one of the primary causes of an unfriendly ecosystem. When there are many competitors in a market but few ways for any of them to advance, the result is often a high level of competitive intensity (Alghamdi and Agag, 2023a; Qalati et al., 2021). Research based on the adoption of information systems shows that organizations can exert influence on their respective industries and markets if they adopt cutting-edge technologies. However, it could affect how rivals do business, providing the early adopter an edge. This research stated that the theory can be used to SM since it represents a novel technological platform for small and medium-sized enterprises (SMEs) in emerging economies. In addition, Qalati et al. (2021) revealed that this is necessary because SMEs today operate in a more volatile business-environment due to the effects of globalization and the increasing adoption of digital technology. Therefore, we suggest the following hypothesis:

H1:“Competitive intensity has a significant impact on social media adoption in SMEs.”

Competitive pressure is the degree to which an organization perceives pressure from competitors operating within the same industry or market. The bigger the number of competing organizations, it is argued, the greater the predicted number of technologies to be adopted (Alrawad et al., 2023; Pateli et al., 2020). Technology, globalization, and the rapid dissemination of new technologies may also have a role in this phenomenon. An industry has greater opportunities for innovation and progress when many different companies are operating in the same industry (Alsuwaidi et al., 2022; Studen & Tiberius, 2020). Previous studies indicate that there is a causal link between competitive pressure and output (Zhang et al., 2019). It has been stated that in the context of SMEs, the bigger the number of competing organizations, the greater the projected number of technologies to be adopted (Hu et al., 2023). Technology, globalization, and the rapid spread of new technologies could also play a role. According to Qalati et al. (2021), competition encourages creativity and technological progress within an industry. In addition, in a study of 167 Malaysian CEOs and executives from SMEs a significant influence has been discovered between the strict implementation of competition laws and the rise of e-commerce (Alyahya et al., 2023a; Seo et al., 2020). That the social media (SM) is subject to the same logic is not surprising. Thus, this research contends that rivalry also affects SM adoption and SMEs’ efficiency. Thus, we propose the following hypothesis:

H2: “Competitive pressure has a significant impact on social media adoption in SMEs.”

This is the contagion effect, or the “bandwagon effect.” It’s a psychological phrase that suggests companies or people may act in a certain way (such using cutting-edge technology) simply because their rivals or peers are doing the same thing (Abed, 2020). The phenomenon is known as the bandwagon effect or the contagion effect. This psychological term suggests that companies or people may act in a certain way (such as using cutting-edge technology) simply because their rivals or peers are doing the same thing (Tella & Ukwoma, 2020). As more businesses in each sector or industry adopt a given technology, the pressure on those businesses that have yet to do so increases (Alzaidi and Agag, 2022; Geurin & Burch, 2017), typically due to the fear of underperformance (Alyahya et al., 2023b; Ngai et al., 2015). More volatile environments, like the digital one, magnify the impact of the bandwagon effect (Alyahya et al., 2023c; Reyaee & Ahmed, 2015). Thus:

H3:“The bandwagon effect has a significant impact on social media adoption in SMEs.”

Technological Factors

Several technological variables, such as relative advantage, complexity, perceived usefulness, and cost effectiveness (Abed, 2020; Qalati et al., 2021), have been discussed in prior studies as impacting SM adoption. Traditional research grounded on the theory of diffusion innovation (DOI) have focused on relative advantage and cost effectiveness as reliable forerunners of technology adoption (Eid et al., 2019; Khan et al., 2021). Three variables of technology were examined in this analysis: cost effectiveness; relative advantage, and compatibility.

Using the TOE framework, which describes the internal and external developments that apply to a corporation (Rodriguez et al., 2015), the diffusion of innovation model was used to investigate the technological aspects influencing the adoption of social media by SMEs in Saudi Arabia (Eid et al., 2020; Rodriguez et al., 2015). However, the interactive platform that SM provides, with features like comments and answers enabling firms to communicate with customers, is essential to its uptake and utilization. According to a survey of 210 small and medium-sized enterprises (SMEs) conducted by Khan et al. (2021), SM has a number of advantages for both product and service-based SMEs. How much more productive and beneficial a new technology is in relation to its cost is what we mean when we talk about its cost-effectiveness. This factor in the spread of new technologies is widely recognized as an important one (Abed, 2020). From an SM vantage point, organizations can have timely, direct interaction with end-consumers at low costs and with more efficiency than with traditional forms of communication-tools (Elbaz et al., 2018; Qalati et al., 2021). Therefore, we suggest the following hypothesis:

H4:“Cost effectiveness has a significant impact on social media adoption in SMEs.”

Researchers have invoked the relative advantage factor because it is widely acknowledged to play a significant role in the diffusion of novel technologies (C. R. Rogers, 1996; E. Rogers, 2003). In this context, “relative advantage” refers to the extent to which a given individual believes that a certain innovation is superior to existing technologies (E. M. Rogers, 2010). Therefore, the likelihood of adoption increases the more of an innovation’s proportional advantage the SMEs perceive. It has been shown that the relative advantage factor plays a crucial role in easing the transition to new technologies (Elbeltagi and Agag, 2016; Elhoushy et al., 2020; Scupola & Nicolajsen, 2013). The belief in one’s own organization’s relative advantage has also been praised for its positive effects on productivity and efficiency within an organization (Alghamdi, 2023; Elhoushy et al., 2020; Sheth, 2011). Thus, we suggest the following hypothesis:

H5:“Relative advantages have a significant impact on social media adoption in SMEs.”

Compatibility refers “to what extent innovation is appropriate with regard to the technology infrastructure, value, work practices, and culture that already exist in the firm” (Rahayu & Day, 2015, p. 144). According to these authors, technology is more likely to be adopted within an organization if it is consistent with its values, meets employees’ needs, and fits in with its established norms and practises. In addition, businesses can quickly and easily spread the word about what they have to offer to a wide range of people by incorporating social media activities into firm operations in a way that is consistent with the firm’s objectives, policies, and values (Ahmad et al., 2019). Compatibility with the adopters’ ideas, experiences, and wants is the hallmark of this technological element (Siamagka et al., 2015). Technology adoption is less likely to fail when it is aligned with the organization’s systems (Hamdy et al., 2024; Sin Tan et al., 2009). Equally, SMEs would be more likely to use social media if they believed that doing so would align with the organization’s values.

H6:“Compatibility has a significant influence on social media adoption in SMEs.”

Organizational Factors

The organizational structure is related to the characteristics of the company itself, including its size, number of employees, degree of the formalization or decentralization of operations, and management concerns (Stockdale et al., 2022). It is well known that a firm’s core-members make key-strategic decisions that affect the firm’s overall performance and its future operations, and that this makes clear the importance of management support (Sun, 2003). Despite the advantages of IT, businesses should evaluate whether or not they have the internal infrastructure and personnel to successfully use SM (Laradi et al., 2024; Teo & Pok, 2003). As has been found in other research (Al-Adwan & Kokash, 2019; Bakri, 2017), the concept of management support is widely employed to represent the TOE framework in organizations. Managerial approval entails the approval of a company’s owner or manager for implementing a company-wide project, policy, or change (Jin & Hurd, 2018). Similarly, prior research notes that, in the context of (SMEs), the acceptability of IT-based solutions is mostly impacted by the top management, whose members make most of the decisions about daily operations and investment opportunities (Bocconcelli et al., 2017).

Top management support is defined as “resources that are available to managers as part of strategic view of the organization” (Zwikael & Levin, 2008, p. 22). It can be developed by the implementation of rules and standards, the use of available information resources, and open lines of contact with other supervisory personnel. Gradually, in the context of innovation adoption, the term “top management support” has been adopted in the existing literature (Chen et al., 2022; Selim et al., 2022). Adoption of innovations requires a conducive atmosphere and adequate resources, both of which can be facilitated by management’s backing (Abed, 2020; Sharkasi and Agag, 2024). Furthermore, the top management has effects on coordination and the availability of resources by verifying that adequate human talents, time, and financial resources are accessible for SM adoption (E. Rogers, 2003). In view of this, the present study can state that the owners or CEOs typically govern SMEs due to the highly centralized nature of the system in these organizations. Previous studies revealed that top management support is a key driver of social media adoption (Abed, 2002; Shaalan et al., 2022; Qalati et al., 2021). Thus, we propose the following hypothesis:

H7:“Top management support has a significant impact on social media adoption in SMEs.”

Without the proper expertise, a company’s attempt to adopt cutting-edge technology is doomed to fail (Erjavec & Manfreda, 2022). According to research by Ahmad et al. (2019), a lack of IT skills is a significant obstacle to SMEs adopting technology. There have been a number of research (Ahmad et al., 2019) that have found that experienced workers are more likely to make good use of technology.

Previous examinations reveal that SMEs are more likely to adopt SM if their senior management are well-versed in the technology, optimistic about its potential, and committed to seeing it implemented (Ringle et al., 2015). There is a close correlation between the effectiveness of an organization’s senior management and the data presented (e.g., Alshamaila et al., 2013). Firms’ willingness to adopt new technologies has been hypothesized to hinge on the encouragement of upper management.

H8: “Employee expertise has a significant impact on social media adoption in SMEs.”

Social Media Adoption and Sustainable Performance

Technology has been shown in many studies (e.g., Cao et al., 2018; Shehawy et al., 2018) to enhance corporate operations and productivity. Several studies reveal a correlation between a company’s use of social media and an increase in profits (Zahra, 2018). Research shows that engaging with customers via social media boosts sales results (Shehawy et al., 2024; Zieba et al., 2016). Organizational social capital was found to increase as a result of social media use, which in turn improved performance (Li et al., 2020). Using Facebook to connect with customers was demonstrated to increase sales performance for SMEs (Manfreda et al., 2008; Wood et al., 2021). One study indicates that social media can dramatically affect businesses by swaying consumers’ decisions to make purchases (Chang et al., 2022). Results from these studies corroborate those from earlier literature on the effects of technology adoption on business outcomes, both monetary and otherwise (Basit et al., 2020).

Previous research has explored the relationship between SMEs’ performance and mediating factors such communication effectiveness (Khan et al., 2021), trust and selling abilities (Alghamdi, 2023), and marketing prowess (Erjavec & Manfreda, 2022). However, this study asserts that SMs adoption also play a mediating function between TOE components and SMEs’ sustainable performance, which is consistent with, for example, (Abed, 2020; Youssef et al., 2022). Positively influencing the relationship between behavioral intention and user motivation, social media experience was discovered to exist (Erjavec & Manfreda, 2022). Accordingly, Chen et al. (2022) proposed that the adoption of social media would serve as a mediator between the TOE factors and SMEs sustainable performance. Thus, we propose the following:

H9:“Social media adoption has a significant impact on economic sustainability.”

H10:“Social media adoption has a significant impact on environmental sustainability.”

H11:“Social media adoption has a significant impact on social sustainability.”

The Moderating Role of COVID-19

As a result of a Covid-19 response, such as the adoption of social distance, online purchasing channels have become the only ways in which enterprises and customers can communicate (Lashitew, 2023). Several internet retailers, including Amazon, Target, and Wal-Mart, made profits throughout the pandemic (Ngo et al., 2023). At the same time, despite government aid, SMEs have faced closure since customers have been unable to visit stores owing to pandemic-related restrictions (Gao et al., 2023). While digital technologies have been identified as the only means for SMEs to adapt to quarantine restrictions (Lukito-Budi et al., 2023), however, their use, particularly in the context of Saudi SMEs, remains limited. Despite the rise of social media marketing, most SMEs in Saudi Arabia continue to rely on traditional marketing strategies, resulting in low productivity (Putritamara et al., 2023). The business rationale for implementing social media marketing is acknowledged as increased income, cost reduction, and improved organizational effectiveness. Social media has been praised for allowing businesses to communicate with customers in a variety of ways. Businesses can leverage client feedback to improve customer satisfaction with SMEs (Ahmad et al., 2019), and social media, as opposed to expensive traditional marketing tactics, gives cost-effective ways of engaging customers (Alrousan et al., 2020). Saudi Arabia has seen great growth in social media users, with a 7.4% increase to 5.7 million users between 2019 and 2020, accounting for 56% of the Saudi population (Abed, 2020). As a result, the social media has a huge influence in Saudi Arabia and has become an important promotional tool for the country’s SMEs. Prior research claims that research can make theoretical contributions by proposing new concepts, evaluating well-established and verified theories in new contexts, and discovering new links between diverse concepts (Li et al., 2020). The purpose of this study is to investigate why Saudi SMEs were digitally unable to respond fast to the Covid-19 issue, despite the widespread use of social media platforms.

H12: Covid-19 moderates the relationship between social media adoption and sustainable performance.

Methods

Sampling and Data Collection

The data for this study were drawn at random from a directory of SMEs in Saudi Arabia. Since 90% of private companies in Saudi Arabia are SMEs, we should expect to compile a representative sample easily and receive a respectable number of replies. Owner-managers and chief executive officers (CEOs) were sought out as primary respondents since they are in the best position to understand their company’s environment and performance (Zaid et al., 2018). In this case, SMEs were chosen because of the negative impact that Covid-19 has had on their performance.

Survey Monkey’s online poll platform was used to administer the survey to a pool of more than 1,000 possible participants (www.surveymonkey.com). All eligible individuals were invited to take part in the study by electronic mail, which included an in-depth description of the study and a link to the survey. The survey was available online from October 15, 2022, November 15, 2022. Due to their speed, ease of use, and low cost (Fornell & Larcker, 1981), online surveys are now widely regarded as indispensable for contemporary research (Bakri, 2017; Rodriguez et al., 2015). Furthermore, the collection period is shortened, and additional instructions can be added to provide help when it is needed (Biucky & Harandi, 2017). The present study utilized quota sampling technique for the data collection purposes. National representativeness quotas were identified based on respondents age and gender according to the Saudi Arabia population data from Office for National Statistics (2019). The final response rate was 609 out of a possible 1,000, despite attempts including phone calls and emails to persuade more people to fill out the surveys. Bartlett et al. (2010) propose using a minimum of 10 cases per predictor to determine the sample size for PLS estimation, and this sample size (609) is consistent with that recommendation. The number of possible routes to the trust construct was the most difficult regression in our model. According to this guideline, we would need a minimum of 80 cases to conduct our study. With a total of 609 cases, the current sample size is large enough to employ PLS with confidence. Westland (2010) proposed an alternative test formula: n ≥ 50r 2 – 450r + 1,100, where n is the number of observations and r is the indicator-to-latent variable ratio. The current study’s sample size of 609 cases is adequate for structural equation modeling, as recommended by Westland (2010).

Most of the respondents were owners, executives and managers, and 69% were male. This is unsurprising, given the typical demographics of business owners and managers in the Middle East, including Saudi Arabia (E. M. Rogers, 2010). Most of the respondents (43.2%) were under 40 years old, with a university or postgraduate degree (71%). This suggests that decision makers in SMEs using social media tend to be younger and better educated. They may also be more aware of business developments in their industry and beyond.

Conceptualization of Measures

Valid measurements of all the study variables were adopted from previous studies. Technological factors (i.e., relative advantages, cost effectiveness, and compatibility) were measured using scales from previous valid measurements (Ahmad et al., 2019; Odoom et al., 2017; Qalati et al., 2020). Environmental factors were adopted from prior research (Ahmad et al., 2019; Qalati et al., 2020). Organizational factors were evaluated from previous studies (Ahmad et al., 2019; Qalati et al., 2020). Social media adoption was assessed using a scale adopted from prior research (Parveen et al., 2016). Sustainable firm performance was evaluated based on economic, social, and environmentally sustainable data from prior studies (Yusliza et al., 2020; Zhu et al., 2013). Finally, COVID-19 was assessed using a scale adopted from previous examinations (Chen et al., 2022). All measurements were assessed using a 5-point Likert scale.

Common Method Bias

Due to the nature of the collection process, self-reported data is prone to common method biases (CMB), including the consistency theme and social desirability bias (Wang et al., 2021). When calculating how much CMB was present in our samples, we turned to statistical analysis. CMB was evaluated using SPSS. As a reinforcement, a prior study suggested conducting a CFA, loading all items on a single variable, and analyzing the fit indices (Li et al., 2020). The use of a single variable was interpreted as a “methods factor 2,” suggesting that bias may have played a role in data gathering. Weak fits were discovered for one-factor models, but the fit for the hypothesized model was statistically significant. As a means of detecting CMB, we employed the correlation marker method (Bagozzi & Yi, 1988). These unrelated variables were used to eliminate some of the correlations that were caused by the CMB. We used the reasoning of prior examination to assess the importance of the associations (Zieba et al., 2016). Our results showed that the importance of the connections remained the same. The analysis revealed that standardized regression weights of the models with and without the common latent factor were found to be comparable (“differences less than 0.20”). Both models had comparable model fit indices (“model with common latent factor: χ²/df = 2.3904; model without CLF: χ²/df = 2.6210”). Thus, the official survey data does not suffer from a severe common method variance problem. According to these findings, any variation in commonly used methods has little effect (CMV). To look for non-response bias, we used a technique developed by prior research (Abu Bakar et al., 2019). We tried to determine whether or not there was a significant difference between the early and late groups of respondents. No significant differences between early and late responders were found using the chi-square test at the 5% significance level. Therefore, we concluded that non-response bias was not a serious problem.

Measurement Model

Internal consistency reliability, convergent validity, and discriminant validity were used to evaluate the measurement quality of these reflecting instruments. Cronbach’s alpha, composite reliability (CR), and the average extracted variance were used to determine the dependability of the study’s internal consistency (AVE). Cronbach’s alphas, composite reliability, and average AVE were all above 0.8, as indicated in Table 1. The obtained values for Cronbach’s alpha, CR, and AVE seem respectively to indicate sufficient internal consistency reliability and convergent validity, with acceptable threshold values of 0.7, 0.7, and 0.5 (Hair et al., 2011). We examined the square root of the AVE of each construct and their correlation coefficients with other constructs to test their discriminant validity. It can be shown from Table 2 that the AVEs had satisfactory discriminant validity because their square roots were greater than their associated correlation coefficients.

Table 1.

Measurement Statistics of Construct Scales.

Construct/Indicators	SFL	Mean	Standard deviation	Cronbach’s α	CR	AVE	t-Values	Skewness	Kurtosis
Economic sustainability (ECS)				.930	0.952	0.538
ECS1	0.981	4.09	1.718				14.230	−1.03	1.83
ECS2	0.938	3.102	1.029				8.209	−1.12	1.06
ECS3	0.929	3.235	1.217				6.120	−1.29	1.12
Social sustainability (SOS)				.929	0.948	0.607
SOS1	0.910	3.192	1.126				15.204	−1.374	1.23
SOS2	0.932	2.883	1.430				19.290	−1.189	1.19
SOS3	0.908	2.129	1.312				7.348	−1.023	1.08
Environmental sustainability (ENS)				.908	0.921	0.628
ENS1	0.943	3.120	1.128				5.029	−1.73	2.39
ENS2	0.972	3.028	1.278				9.125	−1.06	2.17
ENS3	0.908	3.162	1.323				13.028	−1.21	2.20
Social media adoption (SMA)				.953	0.973	0.609
SMA1	0.936	2.993	1.098				21.209	−1.46	1.20
SMA2	0.919	3.125	1.462				15.327	−1.29	2.16
SMA3	0.945	3.437	1.170				8.093	−1.27	1.43
SMA4	0.970	2.823	1.127				11.236	−1.68	1.72
Competitive intensity (CMI)				.931	0.948	0.505
CMI1	0.939	2.897	1.127				10.048	−1.45	1.35
CMI2	0.947	3.210	1.029				12.109	−1.06	1.01
CMI3	0.928	3.218	1.548				9.037	−1.61	1.90
Competitive pressure (CMP)				.920	0.941	0.589
CMP1	0.930	3.238	1.342				21.237	−1.45	1.35
CMP2	0.917	3.167	1.128				19.120	−1.08	1.27
CMP3	0.949	2.309	1.439				9.039	−1.16	1.77
Bandwagon effect (BDE)				.939	0.958	0.588
BDE1	0.903	3.093	1.329				13.209	−1.54	1.32
BDE2	0.948	2.120	1.125				11.245	−1.21	1.90
BDE3	0.927	2.154	1.388				24.396	−1.89	1.43
Cost effectiveness (CSE)				.919	0.930	0.618
CSE1	0.919	2.039	1.205				22.109	−1.20	1.29
CSE2	0.887	2.124	1.470				11.045	−1.43	1.41
CSE3	0.904	3.286	1.056				26.409	−1.05	2.05
Relative advantages (RTA)				.948	0.961	0.519
RTA1	0.936	3.203	1.209				19.204	−1.26	1.42
RTA2	0.902	3.129	1.346				23.893	−1.09	1.37
RTA3	0.918	2.846	1.203				20.459	−1.25	1.70
Compatibility (CMT)				.927	0.940	0.583
CMT1	0.918	3.029	1.420				8.039	−1.39	1.24
CMT2	0.937	2.738	1.289				16.203	−1.26	1.05
CMT3	0.906	2.520	1.038				14.290	−1.05	1.58
Top management support (TMS)				.932	0.951	0.617
TMS1	0.930	2.938	1.283				14.209	−1.20	1.02
TMS2	0.963	2.673	1.627				18.327	−1.47	1.28
TMS3	0.917	3.029	1.025				22.069	−1.52	1.06
TMS4	0.896	3.127	1.238				10.034	−1.64	1.26
Employee expertise (EMP)				.926	0.943	0.572
EMP1	0.938	3.291	1.208				12.120	−1.29	1.47
EMP2	0.910	3.273	1.327				9.307	−1.03	1.29
EMP3	0.883	2.120	1.092				6.992	−1.62	1.06
EMP4	0.906	3.760	1.526				10.637	−1.25	1.18
COVID-19 effect (COD)				.948	0.970	0.510
COD1	0.889	3.208	1.203				23.209	−1.20	1.25
COD2	0.903	3.027	1.472				28.120	−1.34	1.07
COD3	0.937	3.107	1.295				17.024	−1.27	1.38
COD4	0.916	2.374	1.207				11.206	−1.02	1.42

Table 2.

Discriminant Validity of the Correlations Between Constructs.

Construct	Correlations and square roots of AVE
Construct	ECS	SOS	SNS	SMA	CMI	CMP	BDE	CSE	RTA	CMT	TMS	EMP	COD
ECS	.733 ^a
SOS	.394^b	.779
SNS	.408	.329	.792
SMA	.236	.230	.320	.780
CMI	.510	.547	.438	.430	0.711
CMP	.420	.412	.237	.228	.569	.767
BDE	.438	.325	.418	.340	.340	.349	.766
CSE	.332	.227	.226	.327	.510	.410	.349	.786
RTA	.412	.489	.318	.296	.327	.332	.247	.458	.720
CMT	.475	.237	.422	.430	.329	.436	.507	.376	.407	.764
TMS	.226	.540	.356	.218	.356	.293	.254	.610	.329	.327	.785
EMP	.549	.325	.277	.429	.258	.410	.336	.430	.336	.560	.448	.756
COD	.327	.440	.439	.217	.419	.337	.360	.316	.413	.329	.301	.409	.714

^aComposite reliabilities are along the diagonal

Correlations.

Results

This study used Partial Least Scale Structural Equation Modeling (PLS-SEM) to test the relationships between the study variables.

Hypotheses Testing

Table 3 and Figure 2 indicate the hypothesis testing results using SEM/PLS. All the proposed hypotheses were supported, except H4. Specifically, environmental factors (i.e., competitive intensity, competitive pressure, and bandwagon effect) were found to have a significant effect on social media adoption (β = .406, p < .001; β = .290, p < .001; β = .637, p < .001; respectively). Therefore, H1, H2, and H3 are supported (Table 4).

Table 3.

Results of Hypotheses Testing.

Hypothesis	Path	β	Result
H1	CMI → SMA	.406***	Supported
H2	CMP → SMA	.290***	Supported
H3	BDE → SMA	.637***	Supported
H4	CSE → SMA	.077ns	Unsupported
H5	RTA → SMA	.377***	Supported
H6	CMT → SMA	.283***	Supported
H7	TMS → SMA	.692***	Supported
H8	EMP → SMA	.407***	Supported
H9	SMA → ECS	.499***	Supported
H10	SMA → SOS	.540***	Supported
H11	SMA → ENS	.365***	Supported
H12	SMA → COD → SPF	.251***	Supported

Note. The asterisks represent the level of significance of the coefficient. ***.001.

Table 4.

Variables Measurement.

Variables	Items	Sources
Competitive intensity	It is easy for our customers to switch to another company for similar services/products without much difficulty.	Ahmad et al. (2019), Qalati et al. (2020)
	Our customers are able to easily access to several existing products/services in the market which are different from ours but perform the same functions.
	There is rivalry among the firms in the industry, our firm is operating in intense.
Competitive pressures	Social media would allow the firm stronger competitive advantage.	Ahmad et al. (2019), Qalati et al. (2020)
	Social media would increase firm ability to outperform competition.
	Social media would allow the firm to generate higher profits.
Bandwagon effect	Social media is a popular application; therefore, our firm would like to use it as well.	Ahmad et al. (2019), Qalati et al. (2020)
	We follow others in adopting social media.
	We choose to adopt social media because many other firms are already using it.
Cost effectiveness	We adopt social media to cut down cost on marketing communications.	Odoom et al. (2017), Qalati et al. (2020)
	Social media platform saves costs relating to time and effort in marketing, branding and customer service.
	Social media is more cost effective to us than traditional media.
Relative advantages	Social media provides new opportunities.	Ahmad et al. (2019), Qalati et al. (2020)
	Social media allows us to accomplish specific tasks more quickly.
	Social media allows us to enhance our productivity.
Compatibility	Social Media adoption is compatible with the company’s IT infrastructure.	Ainin et al. (2015)
	Social media adoption is consistent with the company’s beliefs and values.
	Social media adoption is compatible with our business processes and operations.
Top management support	Top management in my organization is interested in adopting social media.	Ahmad et al. (2019), Qalati et al. (2020)
Top management support	Top management in my organization considers social media adoption important. Top management in my organization has shown support for social media adoption. Top management emphasis on R&D, technological leadership, and innovations.	Ahmad et al. (2019), Qalati et al. (2020)
Social media adoption	Social media adoption enables us to conduct marketing research.	Parveen et al. (2016)
	Social media adoption enables us to get referrals (word of mouth via likes, shares and followers in Facebook).
	Social media adoption enables us to advertise and promote product/services.
	Social media adoption enables us to deliver customer services.
Economic sustainability	Decrease in costs for materials purchasing.	Yusliza et al. (2020), Zhu et al. (2013)
	Decrease in costs for energy consumption.
	Decrease in fees for waste treatment.
Environmental sustainability	Improved compliance with environmental standards.	Yusliza et al. (2020), Zhu et al. (2013)
	Reduction in air emissions.
	Reduction in energy consumption.
Social sustainability	Improved overall stakeholder welfare.	Yusliza et al. (2020), Zhu et al. (2013)
	Improvement in community health and safety.
	Reduction in environmental impacts and risks to the general public.
Covid-19 disruption	The COVID-19 disrupts our ability to get our business done.	Chen et al. (2022)
	The COVID-19 causes us to stop and think about how to respond.
	The COVID-19 alters our normal way of doing business.
	The COVID-19 requires us to change the way we do our work.

Figure 2.

Structural model with standardized path estimate.

Technological factors (i.e., relative advantages, and compatibility) were found to have a significant effect on social media adoption (β = .377, p < .001; β = .283, p < .001; respectively). Therefore, H5 and H6 are supported but H4 was rejected. Regarding the organizational factors, our study revealed that top management support and employee expertise have a significant effect on social media adoption (β = .692, p < .001; β = .407, p < .001; respectively). Therefore, H7 and H8 were supported. Our study indicated that social media adoption has a significant influence on economic, environmental, and social sustainability (β = .499, p < .001; β = .540, p < .001; β = .365, p < .001; respectively). Thus, H9, H10, and H11 are supported. A multiple group analysis using PLS/SEM was conducted to explore the moderating role of COVID-19 on the links between social media adoption and sustainable performance. The results of the analysis indicated that COVID-19 has a significant effect on these relationships. Thus, H12 was supported.

Discussion and Implications

Key Findings

The main purpose of this study was to develop an integrated model that can explains the factors affecting social media adoption and its effects on sustainable performance in SMEs in Saudi Arabia. It also examined the impact of COVID-19 on these relationships.

Environmental factors were found to be a significant predictor of social media use. These results are consistent with previous studies that have found that external factors, including competitive intensity, competitive pressure, and the bandwagon effect, significantly affect social media adoption (Abed, 2020; Khan et al., 2021). This result demonstrates that SMEs need to use social media as a countermeasure to those taken by their competitors in order to obtain competitive advantage and information, respond to customers, and develop the best possible connections with customers and other stakeholders. The findings also show that some SMEs adopt new technologies solely because their competitors have started using them. Some businesses also made the switch out of concern for the loss of clients and loss of ground to their competitors. Since globalization and increased rivalry within an industry and a particular market have destabilized the environment in which SMEs in developing nations operate, these businesses must keep constant attention on the shifting conditions in order to reap the benefits they provide. The findings of this study showed that SMEs in Saudi Arabia regularly account for and adapt to changes in their external environment.

The present study’s findings, which are confirmed by previous examinations (Cao et al., 2018; Li et al., 2020; Sin Tan et al., 2009), show that technology has a favorable and significant effect on the performance of SMEs. These findings corroborate those of previous studies (Li et al., 2020; Qalati et al., 2021). As a result, it can be said that technological advancement and stringent management are prerequisites for long-term growth and financial success. Innovations, through new products and technology, have an immense impact on the development of organizations. In particular, inventive activity, which becomes the major explanation for the competitive advantage and performance of firms (Alshamaila et al., 2013; Denkta et al., 2020; Zieba et al., 2016), allows SMEs to contribute significantly to economic growth and job creation. Technological construct has been found crucial in SMEs’ decisions to embrace and use SM. The present study’s results are consistent with those of other research done in developing nations like Malaysia, Africa, the United Arab Emirates, and China (V. Kumar et al., 2022; Pateli et al., 2020; Trainor et al., 2014). This research implies that the major reasons for SM adoption in SMEs operating in Saudi Arabia are the predicted benefits (interactivity, cost-effectiveness, compatibility, relative advantage, and visibility). The country’s acceptance of social media is still in its infancy (Ringle et al., 2015; Stockdale et al., 2022; Zieba et al., 2016), therefore more focus should be placed on fostering the sector’s expansion and raising its profile. Moreover, the results of this study reveal that the use of technology in SMEs is outsourced by upper management, who ask personnel to use it in tactical or marketing operations. We hypothesize that the relatively young age and high education level of respondents may indicate that they are personal users of the technology, which in turn may explain their interest in using it for commercial purposes.

Earlier research has demonstrated that the backing of upper management is crucial for SM implementation. To a great extent, this result accords with the findings of others (Abu Bakar et al., 2019; Hu et al., 2023; Zieba et al., 2016). Results suggest that management buy-in is critical in influencing SM adoption and motivating staff to use it extensively in marketing. Additionally, the current research suggests that young, well-educated owners and managers in Saudi Arabia prefer to adopt SM as a marketing strategy because they already use it in their everyday lives and connect with friends and family by this means. Additionally, it has been documented that SMEs in other developing nations lacked management assistance when it came to the implementation of cutting-edge technologies (Alghamdi, 2023; Cao et al., 2018).

There was strong evidence that SMEs’ long-term success was correlated with their use of social media. This suggests that SMEs’ sustainable performance (i.e., enhanced environmental, social, and economic sustainability) and access to a wide number of clients are strongly influenced by the adoption and use of social media. This result agrees with what has been found before (Li et al., 2020). Findings demonstrated that SMEs reaped benefits from their efforts in this area. According to a prior study, gauging the success of one’s social media efforts should not be attempted too soon, given that such efforts are inherently experimental (Alghamdi, 2023). The author advocated in Hu et al. (2023) for an increase in reports detailing the returns on investment in social media by businesses of all sizes.

Theoretical Contributions

This research adds to the body of knowledge on the topic of SMEs’ use of social media in developing countries like Saudi Arabia. This study’s results are applicable to other emerging countries of the same kind, where there is a dearth of relevant research. This research builds on previous work by expanding the TOE framework to analyze the rising trend of SMEs’ use of social media. The current study adds new empirical support to the previous literature by focusing on the role of social media as a mediator. Even though prior research has looked into the direct effects of TOE constructs on social media adoption and the long-term performance of SMEs (Bakri, 2017; Basit et al., 2020; Jin & Hurd, 2018; Ngai et al., 2015), more study is needed.

Considering that some emerging technologies may start to seem the same, and that many businesses may want to use unique platforms for the same tasks as their competitors’, this disparity is significant. Academic attention on the topic of SMEs’ adoption of social media in developing nations has been scant. Earlier researchers have either looked at the constructs in isolation or in a number of contexts (Li et al., 2020) or asked for further empirical investigations on theory formation and validation in third world nations. By using the Theory of Everything (TOE) paradigm, this study offers a practical and efficient approach to analyzing this occurrence in the academic literature. The origins and effects of numerous IT-based technologies have recently been studied (Stockdale et al., 2022; Zahra, 2018; Zieba et al., 2016). However, little has been written on the adoption of social media in the context of SMEs. Therefore, the current study adopted an integrated framework to investigate the causes of SMEs’ sustainable performance in developing countries via the TOE framework and social media.

Practical Contributions

Based on the ongoing discussion on the pros and downsides of social media use and the way in which it affects long-term performance by SMEs, the present study illuminates the full scope of the issues in play, enabling business owners and managers to grasp accurately the impact of social media use. This article should help readers to understand quickly how better managing SMEs’ use of social media may boost their economic, environmental, and social sustainability. For instance, the data shows that SMEs can benefit greatly from using social media in terms of lowering the expenses associated with general operations and marketing. Using social media to interact with customers actively helps to strengthen ties with them and boosts loyalty. The use of social media also raises the awareness of a business, facilitates communication with a large audience, and makes it easier for consumers to find answers to their questions. Since the advent of the social media, two-way contact between businesses and their customers has been much easier, giving consumers greater say in product development and feedback mechanisms.

In addition, SMEs can spread their goodwill and positive brand images to the general public. Adopting and using social media has also aided SMEs to connect with prospective partners and customers. This research demonstrates that SMEs in developing nations, particularly Saudi Arabia, can benefit from using social media. It was also mentioned that owners and managers might encourage SMEs to use social media because doing so may boost a business’s overall performance. SMEs benefit from TOE structures because of the favorable environment that they provide for the use of social media. Few studies have supported the idea that SMEs use social media because of the influence of their competitors. This wasteful behavior by SMEs causes them to have to scrape by on a daily basis, which means that their adoption of social media may not produce the expected benefits. But, as this research shows, SMEs need to know not only why they should use social media, but also how, when, and why it might work for them. Finally, this research shows why and how social media can be effectively used in SMEs during COVID-19.

Conclusions

The main aim of this paper was to explore the main factors affecting social media adoption in Saudi Arabian SMEs and its effect on their sustainable performance within the TOE framework. It also explored the impact of COVID-19 on this relationship. Our study used the quantitative method to collect data and analyze it using PLS/SEM. The analysis revealed that environmental factors (i.e., competitive intensity, competitive pressure, and the bandwagon effect); technological factors (i.e., relative advantages, and compatibility); and organizational factors have been key drivers of social media adoption in SMEs during COVID-19. It also indicated that social media adoption in SMEs is a key driver of economic, environmental, and social performance.

One of the main limitations of the current study is that it focused on SMEs. Future studies can test our model in large companies. Second, our study focuses on exploring the factors affecting social media adoption in the Saudi Arabian context. It would be interesting to test this study model elsewhere, such as developed countries to understand the role of the national culture in these relationships. Third, our study used the quantitative method to test the relationship between the study variables. Future studies can use mixed methods to provide more in-depth insights into these relationships. Finally, our study used a survey to collect the required data. Future research can use experimental methods to explore the relationships that have been developed in our conceptual framework.

Footnotes

Declaration of Conflicting Interests

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

Funding

The author disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors are thankful to the Deanship of Graduate Studies and Scientific Research at Najran University for funding this work under the Easy Funding Program grant code (NU/EFP/SEHRC/13/22).

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the deanship of scientific research ethical committee, Najran University (project number: NU/EFP/SEHRC/13/22, date of approval: 10 February 2022).

Informed Consent Statement

All subjects gave their informed consent for inclusion before they participated in the study. The study was conducted in accordance with the Declaration of the author university, and the protocol was approved by the Ethics Committee.

ORCID iD

Omar A. Alghamdi

Data Availability Statement

Data is available upon request from researchers who meet the eligibility criteria. Kindly contact the first author privately through the e-mail.

References

Abdelmoety

Z. H.

Aboul-Dahab

Agag

2022. A cross-cultural investigation of retailer’s commitment to CSR and customer citizenship behaviour: The role of ethical standard and value relevance. Journal of Retailing and Consumer Services, 64, 102796.

Abed

S. S.

(2020). Social commerce adoption using TOE framework: An empirical investigation of Saudi Arabian SMEs. International Journal of Information Management, 53, Article 102118.

Aboul-Dahab

Agag

Abdelmoety

Z. H.

2021. Examining the influence of cultural and ethical ideology on consumers’ perceptions about the ethics of online retailers and its effects on their loyalty. Journal of Retailing and Consumer Services, 61, 102559.

Abu Bakar

A. R.

Ahmad

S. Z.

Ahmad

. (2019). SME social media use: A study of predictive factors in the United Arab Emirates. Global Business Organizational Excellence, 66(38), 53–68.

Agag

2019. E-commerce ethics and its impact on buyer repurchase intentions and loyalty: An empirical study of small and medium Egyptian businesses. Journal of Business Ethics, 154(2), 389–410.

Agag

Brown

Hassanein

Shaalan

2020. Decoding travellers’ willingness to pay more for green travel products: Closing the intention-behaviour gap. Journal of Sustainable Tourism, 28(10), 1551–1575.

Agag

El-Masry

A. A.

2016. Understanding consumer intention to participate in online travel community, efects on consumer intention to purchase travel online, WOM: An integration of innovation difusion theory. TAM with Trust. Computers in Human Behaviour, 60(3), 97–111.

Agag

Abdelmoety

Eid

2023a. Understanding factors affecting travel avoidance behaviour during the COVID-19 pandemic: Findings from a mixed method approach. Journal of Travel Research, 34(8), 67–93.

Agag

Durrani

B. A.

Shehawy

Y. M.

Alharthi

Alamoudi

El-Halaby

Hassanein

Abdelmoety

Z. H.

2023b. Understanding the link between customer feedback metrics and firm performance. Journal of Retailing and Consumer Services, 73, 103301.

10.

Agag

Durrani

B. A.

Abdelmoety

Z. H.

Daher

M. M.

Eid

2024a. Understanding the link between net promoter score and e-WOM behaviour on social media: The role of national culture. Journal of Business Research, 170, 114303.

11.

Agag

Eid

Lababdi

H. C.

Abdelwahab

Aboul-Dahab

Abdo

S. S.

2024b. Understanding the impact of national culture differences on customers’ online social shopping behaviours. Journal of Retailing and Consumer Services, 79, 103827.

12.

Agag

Eid

2020. Which consumer feedback metrics are the most valuable in driving consumer expenditure in the tourism industries: A view from macroeconomic perspective. Tourism Management, 80(3), 104–109.

13.

Agag

Shehawy

Y. M.

Almoraish

Eid

Lababdi

H. C.

Labben

T. G.

Abdo

S. S.

2024c. Understanding the relationship between marketing analytics, customer agility, and customer satisfaction: A longitudinal perspective. Journal of Retailing and Consumer Services, 77, P.103663.

14.

Agag

G.M.

Khashan

M. A.

Colmekcioglu

Almamy

Alharbi

N. S.

Eid

Shabbir

Abdelmoety

Z. H. S.

2019. Converting hotels website visitors into buyers: How online hotel web assurance seals services decrease consumers’ concerns and increase online booking intentions. Information Technology & People, 31(70), 63–90.

15.

Ahmad

S. Z.

Abu Bakar

A. R.

Ahmad

(2019). Social media adoption and its impact on firm performance: the case of the UAE. International Journal of Entrepreneurial Behavior & Research, 25(1), 84–111.

16.

Ahmad

S. Z.

Abu Bakar

A. R.

Mohamad Faziharudean

T. M.

Zaki

K. A.

(2015). An empirical study of factors affecting e-commerce adoption among small- and medium-sized enterprises in a developing country: Evidence from Malaysia. Information Technology for Development, 21(4), 555–572. https://doi.org/10.1080/02681102.2014.899961

17.

Ainin

Parveen

Moghavvemi

Jaafar

N. I.

(2015). Factors influencing the use of social media by SMEs and its performance outcomes. Industrial Management & Data Systems, 115(3), 570–588. https://doi.org/10.1108/IMDS-07-2014-0205

18.

Al-Adwan

A. S.

Albelbisi

N. A.

Aladwan

S. H.

Horani

Al-Madadha

Al Khasawneh

M. H.

(2020). Investigating the impact of social media use on students’ perception of academic performance in higher education: Evidence from Jordan. Journal of Information Technology Education: Research, 19(7), 953–975.

19.

Al-Adwan

A. S.

Kokash

(2019). The driving forces of Facebook social commerce. Journal of Theoretical and Applied Electronic Commerce Research, 14(2), 15–32.

20.

Al-Ajlouni

(2021). Could Covid-19 push Jordan to the edge? Middle East Institute.

21.

Al-Khalidi

(2021, March 14). Protests erupt in Jordan after COVID-19 hospital deaths scandal. https://www.reuters.com/world/middle-east-africa/protests-erupt-jordan-after-covid-19-hospitaldeaths-scandal-2021-03-14/

22.

Alarcon

del

Rialp

(2015). The effect of social media adoption on exporting firms’ performance. In Zou

Shi

L. H.

(Eds.), Entrepreneurship in International Marketing, 1990–2012 (pp. 161–186). Emerald Group Publishing. https://doi.org/10.1108/S1474-7979201525

23.

Aldossary

Alyahya

Agag

2024. How and when does engaging customers in environmental sustainability pay of? The Role of Business Strategy. Sustainability, 16(12), 4924.

24.

Alghamdi

O. A.

(2023). The relationship between social CRM adoption and competitive advantage: A study during the COVID-19 outbreak. International Journal of Customer Relationship Marketing and Management (IJCRMM), 14(1), 1–21.

25.

Alghamdi

O.A.

Agag

2023a. Boosting innovation performance through big data analytics powered by artificial intelligence use: An empirical exploration of the role of strategic agility and market turbulence. Sustainability, 15(19), 14296.

26.

Alghamdi

O.A.

Agag

2023b. Unlocking the power of reporting: Exploring the link between voluntary sustainability reporting, customer behavior, and firm value. Sustainability, 15(21), 15584.

27.

Alismaili

S. Z.

Shen

Huang

Zhan

(2020). Organisational-level assessment of cloud computing adoption: Evidence from the Australian SMEs. Journal of Global Information Management, 28(2), 73–89.

28.

Alrawad

Lutf

Alyatama

Al Khattab

Alsoboa

S. S.

Almaiah

M. A.

Ramadan

M. H.

Arafa

H. M.

Ahmed

N. A.

Alsyouf

Al-Khasawneh

A.L.

2023 Assessing customers perception of online shopping risks: A structural equation modelling–based multigroup analysis. Journal of Retailing and Consumer Services, 71, 103188. https://doi.org/10.1016/j.jretconser.2022.103188.

29.

Alrousan

M. K.

Al-Adwan

A. S.

Al-Madadha

Al Khasawneh

M. H.

(2020). Factors affecting the adoption of e-marketing by decision makers in SMEs: Evidence from Jordan. International Journal of E-Business Research, 16(1), 1–27.

30.

Alshamaila

Papagiannidis

(2013). Cloud computing adoption by SMEs in the north east of England. Journal of Enterprise Information Management, 26, 250–275.

31.

Alsuwaidi

Eid

Agag

2022. Tackling the complexity of guests’ food waste reduction behaviour in the hospitality industry. Tourism Management Perspectives, 42, 100963.

32.

Alyahya

Agag

Aliedan

Abdelmoety

Z. H.

2023a. A cross-cultural investigation of the relationship between Eco innovation and customers boycott behaviour. Journal of Retailing and Consumer Services, 72, 103271.

33.

Alyahya

Agag

Aliedan

Abdelmoety

Z. H.

2023b. Understanding the factors affecting consumers’ behaviour when purchasing refurbished products: A chaordic perspective. Journal of Retailing and Consumer Services, 75, 103492.

34.

Alyahya

Agag

Aliedan

Abdelmoety

Z. H.

Daher

M. M.

2023c. A sustainable step forward: Understanding factors affecting customers’ behaviour to purchase remanufactured products. Journal of Retailing and Consumer Services, 70, 103172.

35.

Alzaidi

M.S.

Agag

2022. The role of trust and privacy concerns in using social media for e-retail services: The moderating role of COVID-19. Journal of Retailing and Consumer Services, 68, 103042.

36.

Arora

Predmore

(2013). Social media as a strategic tool: Going beyond the obvious. In Olivas-Luján

M. R.

Bondarouk

(Eds.), Social media in strategic management (advanced series in management) (Vol. 11, No. 5, pp. 115–127). Emerald Group Publishing Limited.

37.

Auh

Menguc

(2005). Balancing exploration and exploitation: The moderating role of competitive intensity. Journal of Business Research, 58(7), 1652–1661.

38.

Bagozzi

R. P.

(1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94.

39.

Baker

(2012). The technology–organization–environment framework. Information Systems Theory: Explaining and Predicting Our Digital Society, 1, 231–245.

40.

Bakri

A. A. A.

(2017). The impact of social media adoption on competitive advantage in the small and medium enterprises. International Journal of Business Innovation and Research, 13(2) 255–269.

41.

Bartlett

Kotrlik

Higgins

(2010). Organizational research: Determining appropriate sample size in survey research. Information Technology, Learning, and Performance Journal, 19(1), 43–50.

42.

Basit

Tiong

Hassan

(2020). Determinants of social media adoption and its effects on social media returns among small medium enterprises in Malaysia. Solid State Technology, 63(5), 263–277.

43.

Batikas

van Bavel

Martin

Maghiros

(2012). Use of social media by European SMEs (European Commission Report Number 32448). European Union.

44.

Beatty

R. C.

Shim

J. P.

Jones

M. C.

(2001). Factors influencing corporate web site adoption: A timebased assessment. Information & Management, 38(6), 337–354.

45.

Beebe

K. R.

Pell

R. J.

Seasholtz

M. B.

(1998). Chemometrics: A practical guide (4th ed.). John Wiley & Sons.

46.

Bergeron

Dubois

M.-J.

Dumont

Dial

Skrobik

(2001). Intensive care delirium screening checklist: Evaluation of a new screening tool. Intensive Care Medicine, 27(5), 859–864.

47.

Bertoni

(2020). Why target, walmart and best buy are booming amid the pandemic – 2020, and being hailed as heroes. https://www.forbes.com/sites/stevenbertoni/2022/10/15/why-these-retailgiants-are-booming-amid-the-pandemic-and-being-hailed-as-heroes/

48.

Bhattacharya

Wamba

S. F.

(2015). A conceptual framework of RFID adoption in retail using TOE framework. International Journal of Technology Diffusion, 6(1), 1–32.

49.

Bilbao-Osorio

Dutta

Lanvin

2014, January. The global information technology report 2014: Rewards and risks of big data. In World Economic Forum and INSEAD (pp. 1–369). Palgrave Macmillan.

50.

Biucky

S. T.

Harandi

S. R.

(2017). The effects of perceived risk on social commerce adoption based on TAM model. International Journal of Electronic Commerce Studies, 8(2), 173–196.

51.

Blanchard

(2011). Social media ROI: Managing and measuring social media efforts in your organization. Pearson Education.

52.

Bocconcelli

Cioppi

Pagano

(2017). Social media as a resource in SMEs’ sales process. Journal of Business and Industrial Marketing, 79(23), 693–709.

53.

Buonanno

Faverio

Pigni

Ravarini

Sciuto

Tagliavini

(2005). Factors affecting ERP system adoption: A comparative analysis between SMEs and large companies. Journal of Enterprise Information Management, 18(4), 384–426.

54.

Cao

Ajjan

Hong

(2018). Using social media for competitive business outcomes. Journal of Advances in Management Research, 15(86), 211–235.

55.

Capterra

(2022). Top 10 social media management software. Retrieved May 6, 2022, from https://www.capterra.com/.

56.

Cassel

Hackl

Westlund

A. H.

(1999). Robustness of partial least-squares method for estimating latent variable quality structures. Journal of Applied Statistics, 26(4), 435–446.

57.

Chang

Walimuni

A. C.

Kim

M. C.

Lim

H. S.

(2022). Acceptance of tourism blockchain based on UTAUT and connectivism theory. Technology in Society, 71, Article 102027.

58.

Chen

Liu

Zhou

Chen

(2022). IT-business alignment, big data analytics capability, and strategic decision-making: Moderating roles of event criticality and disruption of COVID-19. Decision Support Systems, 161, Article 113745.

59.

Chiu

C. Y.

Chen

C. L.

(2017). An integrated perspective of TOE framework and innovation diffusion in broadband mobile applications adoption by enterprises. International Journal of Management, Economics and Social Sciences, 6(1), 14–39.

60.

Chong

J. L.

Olesen

(2017). A technology-organization-environment perspective on eco-effectiveness: A meta-analysis. Australasian Journal of Information Systems, 21, 1–26.

61.

Coombs

W. T.

(2007). Protecting organization reputations during a crisis: The development and application of situational crisis communication theory. Corporate Reputation Review, 10(3), 163–176.

62.

Dahnil

M. I.

Marzuki

K. M.

Langgat

Fabeil

N. F.

(2014). Factors influencing SMEs adoption of social media marketing. Procedia-Social and Behavioral Sciences, 148, 119–126.

63.

Datta

Sahaym

Brooks

(2019). Unpacking the antecedents of crowdfunding campaign’s success: The effects of social media and innovation orientation. Journal of Small Business Management, 57(2), 462–488.

64.

Davis

F. D.

(1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 34(7), 319–340.

65.

Denkta

Sakar

Sürücü

. (2020). Stakeholder engagement via social media: An analysis of third-party logistics companies. The Service Industries Journal, 40(8), 866–889.

66.

Dias Canedo

Morais do Vale

A. P.

Patrão

R. L.

Camargo de Souza

Machado Gravina

Eloy dos Reis

Lúcio Lopes Mendonça

de Sousa

R. T

. (2020). Information and Communication Technology (ICT) Governance Processes: A case study. Information, 11(69), 462.

67.

Dutot

Bergeron

(2016). From strategic orientation to social media orientation. Journal of Small Business and Enterprise Development, 23(7), 1165–1190.

68.

Dwivedi

Pawsey

(2023). Examining the drivers of marketing innovation in SMEs. Journal of Business Research, 155, Article 113409.

69.

Eid

El-Kassrawy

Y. A.

Agag

2019. Integrating destination attributes, political (in) stability, destination image, tourist satisfaction, and intention to recommend: A study of UAE. Journal of Hospitality & Tourism Research, 43(6), 839–866.

70.

Eid

Abdelmoety

Agag

2020. Antecedents and consequences of social media marketing use: An empirical study of the UK exporting B2B SMEs. Journal of Business & Industrial Marketing, 35(2), 284–305.

71.

Elbaz

A.M.

Agag

G. M.

Alkathiri

N. A.

2018. How ability, motivation and opportunity influence travel agents’ performance: The moderating role of absorptive capacity. Journal of Knowledge Management, 22(1), 119–141.

72.

Elbeltagi

Agag

2016. E-retailing ethics and its impact on customer satisfaction and repurchase intention: A cultural and commitment-trust theory perspective. Internet Research, 26(1), 288–310.

73.

Elhoushy

Salem

I. E.

Agag

2020. The impact of perceived benefits and risks on current and desired levels of outsourcing: Hotel managers’ perspective. International Journal of Hospitality Management, 91, 102419.

74.

Erjavec

Manfreda

(2022). Online shopping adoption during COVID-19 and social isolation: Extending the UTAUT model with herd behavior. Journal of Retailing and Consumer Services, 65, Article 102867.

75.

Fornell

Larcker

D. F.

(1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(94), 39–50.

76.

Gao

Siddik

A. B.

Khawar Abbas

Hamayun

Masukujjaman

Alam

S. S.

(2023). Impact of e-commerce and digital marketing adoption on the financial and sustainability performance of MSMEs during the COVID-19 pandemic: An empirical study. Sustainability, 15(2), Article 1594.

77.

Geurin

A. N.

Burch

L. M.

(2017). User-generated branding via social media: An examination of six running brands. Sport Management Review, 20(76), 273–284.

78.

Godina

Ribeiro

Matos

Ferreira

Carvalho

Peças

(2020). Impact assessment of additive manufacturing on sustainable business models. Sustainability, 12(68), 71–76.

79.

Hair

J. F.

Ringle

C. M.

Sarstedt

(2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(91), 139–152.

80.

Hamdy

Zhang

Eid

Agag

2024. Is warmth more critical than competence? Understanding how destination gender affects destination identification and destination advocacy. Journal of Product & Brand Management, 23(6), 23–51.

81.

Haseeb

Hussain

H. I.

Slusarczyk

Jermsittiparsert

(2019). Industry 4.0: A solution towards technology challenges of sustainable business performance. Social Sciences, 8(67), 154–167.

82.

Hoffman

D. L.

Fodor

(2010). Can you measure the ROI of your social media marketing? MIT Sloan Management Review, 34(8), 45–61.

83.

Olivieri

Rialti

(2023). Dynamically adapting to the new normal: Unpacking SMEs’ adoption of social media during COVID-19 outbreaks. Journal of Business & Industrial Marketing, 38(8), 1675–1688.

84.

Jin

Hurd

(2018). Exploring the impact of digital platforms on SME internationalization: New Zealand SMEs use of the Alibaba platform for Chinese market entry. Journal of Asian-Pacific Business, 19(78), 72–95.

85.

Kaplan

A. M.

Haenlein

(2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizon, 53(4), 59–68.

86.

Khan

M. I.

Saleh

M. A.

Quazi

(2021). Social media adoption by health professionals: A TAM-based study. Informatics, 8(1), 6–9.

87.

Kumar

M. A.

Ayedee

D. N.

(2021). Technology adoption: A solution for SMEs to overcome problems during COVID-19. Academy of Marketing Studies Journal, 25(1), 1–16.

88.

Kumar

Verma

Mittal

Tuesta Panduro

J. A.

Singh

Paliwal

Sharma

N. K.

(2022). Adoption of ICTs as an emergent business strategy during and following COVID-19 crisis: Evidence from Indian MSMEs. Benchmarking: An International Journal, 30(6), 1850–1883.

89.

Laradi

Alrawad

Lutf

Agag

2024. Understanding factors affecting social commerce purchase behavior: A longitudinal perspective. Journal of Retailing and Consumer Services, 78, 103751.

90.

Lashitew

A. A.

(2023). When businesses go digital: The role of CEO attributes in technology adoption and utilization during the COVID-19 pandemic. Technological Forecasting and Social Change, 189, Article 122324.

91.

Leonardi

P. M.

Vaast

(2017). Social media and their affordances for organizing: A review and agenda for research. Academy of Management Annals, 11(65), 150–188.

92.

Qalati

S. A.

Khan

M. A. S.

Kwabena

G. Y.

Erusalkina

Anwar

(2020). Value co-creation and growth of social enterprises in developing countries: Moderating role of environmental dynamics. Entrepreneurship Research Journal, 12(4), 501–528.

93.

Lukito-Budi

A. S.

Manik

H. F. G. G.

Indarti

(2023). Reorienting the organisational strategy of SMEs during the COVID-19 crisis: Can entrepreneurial orientation help? Journal of Strategy and Management, 16(1), 28–40.

94.

Maduku

D. K.

Mpinganjira

Duh

(2016). Understanding mobile marketing adoption intention by South African SMEs: A multiperspective framework. International Journal of Information Management, 36, 711–723.

95.

Manfreda

K. L.

Bosnjak

Berzelak

Haas

Vehovar

(2008). Web surveys versus other survey modes: A meta-analysis comparing response rates. International Journal of Market Research, 50(90), 79–104.

96.

McCann

Barlow

(2015). Use and measurement of social media for SMEs. Journal of Small Business and Enterprise Development, 22(2), 273–287.

97.

Mousa

S. K.

Othman

(2020). The impact of green human resource management practices on sustainable performance in healthcare organisations: A conceptual framework. Journal of Cleaner Production, 243, Article 118595.

98.

Ngai

E. W.

Tao

S. S.

Moon

K. K.

(2015). Social media research: Theories, constructs, and conceptual frameworks. International Journal of Information Management, 4(35), 33–44.

99.

Ngo

V. M.

Pham

H. C.

Nguyen

H. H.

(2023). Drivers of digital supply chain transformation in SMEs and large enterprises–a case of COVID-19 disruption risk. International Journal of Emerging Markets, 18(6), 1355–1377.

100.

Norris

G.H.

Porter

C.M.

Jiang

Millar

C.L.

Blesso

C.N.

2017. Dietary sphingomyelin attenuates hepatic steatosis and adipose tissue inflammation in high-fat-diet-induced obese mice. The Journal of nutritional biochemistry, 40, 36–43.

101.

Odoom

Anning-Dorson

Acheampong

(2017). Antecedents of social media usage and performance benefits in small-and medium-sized enterprises (SMEs). Journal of Enterprise Information Management, 30(3), 383–399.

102.

OECD. (2020). OECD Economic Outlook. OECD Publishing. Retrieved May 23, 2023, from https://doi.org/10.1787/0d1d1e2een

103.

Office for National Statistics. (2019). People, population and community. Retrieved November 15, 2022, from https://www.stats.gov.sa/en

104.

Parveen

Jaafar

N. I.

Ainin

(2016). Social media’s impact on organizational performance and entrepreneurial orientation in organizations. Management Decision, 45(7), 56–78.

105.

Pateli

Mylonas

Spyrou

(2020). Organizational adoption of social media in the hospitality industry: An integrated approach based on DIT and TOE frameworks. Sustainability, 12(71), Article 7132.

106.

Putritamara

J. A.

Hartono

Toiba

Utami

H. N.

Rahman

M. S.

Masyithoh

(2023). Do dynamic capabilities and digital transformation improve business resilience during the COVID-19 pandemic? Insights from beekeeping MSMEs in Indonesia. Sustainability, 15(3), Article 1760.

107.

Qalati

S.A.

Vela

E.G.

Bux

Barbosa

Herzallah

A.M.

2020. Effects of technological, organizational, and environmental factors on social media adoption. The Journal of Asian Finance, Economics and Business, 7(10), 989–998.

108.

Qalati

S. A.

Yuan

L. W.

Khan

M. A. S.

Anwar

(2021). A mediated model on the adoption of social media and SMEs’ performance in developing countries. Technology in Society, 64, Article 101513.

109.

Ragazou

Passas

Sklavos

(2022). Investigating the strategic role of digital transformation path of smes in the era of COVID-19: A bibliometric analysis using R. Sustainability, 14(18), Article 11295.

110.

Rahayu

Day

(2015). Determinant factors of e-commerce adoption by SMEs in developing country: Evidence from Indonesia. Procedia-Social and Behavioral Sciences, 195, 142–150.

111.

Reyaee

Ahmed

(2015). Growth pattern of social media usage in Arab Gulf states: An analytical study. Social Networking, 4(2), 23–32.

112.

Ringle

C. M.

Wende

Becker

J.-M.

(2015). SmartPLS 3 (p. 81). SmartPLS GmbH.

113.

Rodriguez

Peterson

R. M.

Krishnan

(2015). Social media’s influence on business-to-business sales performance. Journal of Personal Selling and Sales Management, 32(3), 365–378

114.

Rogers

C. R.

(1996). The interpersonal relationship. Harvard Educational Review, 32(4), 416–429.

115.

Rogers

(2003). Diffusion of innovations (5th ed., p. 80). Free Press.

116.

Rogers

E. M.

(2010). Diffusion of innovations (4th ed.). Simon and Schuster.

117.

Scupola

Nicolajsen

H. W.

(2013). Using social media for service innovations: challenges and pitfalls. International Journal of E-Business Research, 9(3), 27–37.

118.

Selim

Eid

Agag

Shehawy

Y. M.

2022. Cross-national differences in travellers’ continuance of knowledge sharing in online travel communities. Journal of Retailing and Consumer Services, 65, 102886.

119.

Seo

S.-W.

Kim

H.-C.

Zhu

Z.-Y.

Lee

J.-T.

(2020). What makes hotel chefs in Korea interact with SNS community at work? Modeling the interplay between social capital and job satisfaction by the level of customer orientation. International Journal of Environmental Research and Public Health, 17(74), 71–84.

120.

Shaalan

Agag

Tourky

2022. Harnessing customer mindset metrics to boost consumer spending: A cross-country study on routes to economic and business growth. British Journal of Management, 34 (7), 67–81.

121.

Sharkasi

Agag

2024. How does risk interplay with trust in pre-and post-purchase intention to engage: PLS-SEM and ML classification approach. Journal of Marketing Analytics, 1–35.

122.

Shehawy

Y.M.

Elbaz

Agag

G. M.

2018. Factors affecting employees’ job embeddedness in the Egyptian airline industry. Tourism Review, 73(4), 548–571.

123.

Shehawy

Y.M.

Agag

Alamoudi

H. O

Alharthi

M. D.

Brown

Labben

T. G.

Abdelmoety

Z. H.

2024. Cross-national diferences in consumers’ willingness to pay (WTP) more for green hotels. Journal of Retailing and Consumer Services, 77, 103665.

124.

Sheth

J. N.

(2011). Impact of emerging markets on marketing: Rethinking existing perspectives and practices. Journal of Marketing, 75(4), 166–182.

125.

Siamagka

N.-T.

Christodoulides

Michaelidou

Valvi

(2015). Determinants of social media adoption by B2B organizations. Industrial Marketing Management, 51(1), 89–99.

126.

Sin Tan

Choy Chong

Lin

Cyril Eze

. (2009). Internet-based ICT adoption: Evidence from Malaysian SMEs. Industrial Management & Data Systems, 109(2), 224–244.

127.

Stockdale

Ahmed

Scheepers

(2022). Identifying business value from the use of social media: an SME perspective. Conference Proceedings of the 16th Pacific Asia Conference on Information Systems (PACIS), Ho Chi Minh City, July 11–15, 2012. Retrieved April 22, 2022, from https://pdfs.semanticscholar.org/902b/4a16bb0f6364c77f1f7c06ed6e490cc1ed11.pdf

128.

Studen

Tiberius

(2020). Social media, Quo Vadis? Prospective development and implications. Future Internet, 12, Article 146.

129.

Sun

, (2003). A longitudinal study of herd behavior in the adoption and continued use of technology. MIS Quarterly, 37(4), 1013–1041.

130.

Tajvidi

Karami

(2017). The effect of social media on firm performance. Computers in Human Behaviour, 3, 105–174.

131.

Tella

Ukwoma

S. C.

(2020). Adeniyi, I. K. A two models modification for determining cloud computing adoption for web-based services in academic libraries in Nigeria. The Journal of Academic Librarianship, 46(75), Article 102255.

132.

Teo

T. S. H.

Pok

S. H.

(2003). Adoption of the internet and WAP-enabled phones in Singapore. Behaviour & Information Technology, 22(2), 281–289.

133.

Tornatzky

L. G.

Fleischer

Chakrabarti

A. K.

(1990). Processes of technological innovation. Lexington Books.

134.

Trainor

K. J.

Andzulis

J. M.

Rapp

Agnihotri

(2014). Social media technology usage and customer relationship performance: A capabilities-based examination of social CRM. Journal of Business Research, 67(2), 1201–1208.

135.

Wang

Liu

Qian

Parker

S. K.

(2021). Achieving effective remote working during the COVID-19 pandemic: A work design perspective. Applied Psychology, 70(1), 16–59.

136.

Westland

C. J.

(2010). Lower bounds on sample size in structural equation modeling. Electronic Commerce Research and Applications, 9(6), 476–487.

137.

Wood

B.P.

Eid

Agag

2021. A multilevel investigation of the link between ethical leadership behaviour and employee’s green behaviour in the hospitality industry. International Journal of Hospitality Management, 97, 102993.

138.

World Commission on Environment and Development (WCED). (1987). Our common future. Oxford University Press.

139.

Yavuz

Uner

M. M.

Okumus

Karatepe

O. M.

(2023). Industry 4.0 technologies, sustainable operations practices and their impacts on sustainable performance. Journal of Cleaner Production, 387, Article 135951.

140.

Youssef

M.A.E.A

Eid

Agag

., 2022. Cross-national differences in big data analytics adoption in the retail industry. Journal of Retailing and Consumer Services, 64, 102827.

141.

Yusliza

M. Y.

Yong

J. Y.

Tanveer

M. I.

Ramayah

Faezah

J. N.

Muhammad

(2020). A structural model of the impact of green intellectual capital on sustainable performance. Journal of Cleaner Production, 249, Article 119334.

142.

Zahra

S. A.

(2018). Entrepreneurial risk taking in family firms: The wellspring of the regenerative capability. Family Business Review, 31(5), 216–226.

143.

Zaid

A. A.

Jaaron

A. A.

Bon

A. T.

(2018). The impact of green human resource management and green supply chain management practices on sustainable performance: An empirical study. Journal of cleaner production, 204, 965–979.

144.

Zhang

Zhu

Wang

(2019). Social capital on consumer knowledge-sharing in virtual brand communities: The mediating effect of pan-family consciousness. Sustainability, 11(73), 339–356.

145.

Zhu

Sarkis

Lai

K. H.

(2013). Institutional-based antecedents and performance outcomes of internal and external green supply chain management practices. Journal of Purchasing and Supply Management 19(2), 106–117.

146.

Zieba

Bolisani

Scarso

(2016). Emergent approach to knowledge management by small companies: Multiple case-study research. Journal of Knowledge Management, 20(88), 292–307.

147.

Zwikael

Levin

(2008). Top management support—The project friendly organization. Cost Engineering, 50(9), 22–37.