Keywords

Social Media, Marketing, SMES, Performance, Smartpls, Ghana

Introduction

The internet and other forms of instantaneous communication have revolutionized the corporate world (Michael Stelzner, 2017). In recent years, social media has rapidly and dynamically developed into a new channel for advertising and public relations. More organisations' use of social media and other digital channels highlights the need for research into the effectiveness of electronic-based marketing.

Social media marketing is an evolutionary development in the marketing environment (Michael Stelzner, 2017). Businesses and companies in developed markets use social media to improve service delivery and performance (Majeed et al., 2023). However, it is an emerging phenomenon in less developed markets, though the potential is extremely high with the structural nature of developing markets (Michael Stelzner, 2017). Misconceptions about it have slowed its development in other markets (Jeffery Opoku, 2016). Social media marketing, as defined by Priyanka and Srinivasan (2015), is the connection between companies and customers via the provision of a unique medium and mediums of exchange for user-driven social networking and communication. It is fascinating how, in today's technologically advanced world, social networking sites have become a way for businesses to reach a wider audience with their advertisements. The world is becoming more digital, thus developing countries need to start promoting themselves in this way.

With the rise of social media, businesses now have access to new channels and methods for engaging with their customers. Therefore, businesses need to start figuring out how to integrate social media into their overall marketing plan (Mangold and Faulds, 1999; Majeed et al., 2022). The margin or gap between the early adopters of social networks and those still waiting to take advantage of them keeps widening. There is a gap in why the world is forcefully becoming a digital market while some businesses are still operating using traditional ways of marketing. The importance of social media is enormous. It is a platform to share thoughts and opinions. It is not only about selling or advertising goods and services but a platform for disseminating political sentiments and government policies. The victory of Barack Obama of the United States in the 2008 election was his ability to drive and engage voters on social media (Carr, 2008). Several companies use social media marketing to effectively interact with their customers, improve their customers’ services, and maximize profit. A typical example is Vodafone Ghana; they use it to interact with customers, allowing them to ask questions or channel their complaints. With the right marketing tools and personnel, social media marketing will always enhance profits.

According to the Global Digital Report (2019), there was a 9% increase in global social media usage since January 2018, and increased to 3.725 billion in 2019. Countries like the UAE had 99%, Taiwan at 89%, South Korea at 78%, Singapore at 79%, and Hong Kong at 78% are nations with high percentages. Countries with lower usage are Nigeria at 12%, Kenya at 16%, Ghana at 19%, India at 23%, South Africa and Egypt at 40%. From the above statistics regarding countries with lower social media usage, Ghana has the potential to move into social media marketing. The countries with the highest user percentages of social media have the strongest economies in the world. From the Digital Ghana Report (2021), the population of Ghana as of January 2021 was about 31.4 million. Out of the number, 57.7% live in urban centers, and 42.3% live in rural areas. From the same report, internet users in the country were 15.7 million, and its penetration was about 50%. In January 2021, social media usage alone was 8.20 million. On these statistics, individual users are on the ascendency. The major social media websites or platforms in Ghana are Facebook, YouTube, Twitter, WhatsApp, Instagram, and Vimeo.

According to the European Union (2003), a company's size is determined by two factors: the number of people it employs and its annual revenue or balance sheet. Rather than using revenue or net worth, Ghana uses the International Standard Industrial Classification (ISIC) to categorise small and medium-sized enterprises (SMEs). A microenterprise is seen as having 10 or less employees, a small business as having 10 to 99 workers, and a medium business as having 100 to 499 workers. About 80% of all firms in Ghana are considered SMEs. As such, SMEs contribute about 70% to GDP. The success of micro and small businesses relies on their ability to recognize the demands of their target market and build brand recognition via the strategic use of social media marketing. Our research aims to explore how small and medium-sized enterprises (SMEs) in Ghana are leveraging social media marketing to enhance their performance. To achieve this, we will employ the Technology Acceptance Model (TAM) framework, which assesses users' acceptance and adoption of technology-based innovations. By applying TAM to the context of social media marketing, we seek to understand SMEs' attitudes and perceptions towards utilising social media platforms for marketing purposes. Research is needed to determine how social media marketing affects small and medium-sized enterprises' (SMEs) performance for growth and profitability, particularly in emerging economies, given that businesses currently use social media (SM) to boost growth and firm performance. Additionally, the survey provides managers and SMEs with insights on how marketing strategies could improve and promote the purchase of their goods. The study determined how social media improves the performance of SMEs and found out what the Wa municipality's customers thought about SMEs using social media marketing.

Through addressing these research gaps, this paper seeks to advance our understanding of how SMEs could potentially attract customers from developing nations to buy their products. Three study objectives are especially examined in this paper:

(1) To ascertain how SM usage affects SMEs performance.

(2) Examine the relationship between SM usage and perceived usefulness.

(3) Examine the correlation and mediation between perceived usefulness and SMEs performance.

In light of this, this study contributes to a significant area of the literature on social media marketing and provides valuable insights for small and medium-sized enterprises (SMEs) and business managers. Specifically, the study examined how social media enhances the performance of SMEs and what customers think about SMEs using social media marketing beyond their current understanding of product patronage. It is also possible for international marketers to capitalise on opportunities in developing nations stemming on the findings of this study.

The remaining sections of the paper are organised as follows: In the section that follows, pertinent research on the idea of social media, the perceived benefits of social media for SMEs, the challenges SMEs have while using social media, and the technology acceptance model (TAM) is discussed. In Section 3, the approach is described, along with the steps used to conduct the study. In Section 4, the results are displayed. In accordance with the body of existing research, Section 5 offers a thorough examination of the results. Section 6 follows, offering implications for future research, theory, and policy as well as a conclusion to the study.

Literature Review

The Concept of Social Media

The AOL executive Ted Leonis coined the phrase "social media" in 1997 when he said customers required access to social media so they could be amused, communicate, and engage in social interactions. A few examples of social media platforms include; Facebook, a microblogging site like Twitter, a video-sharing website like YouTube, and an online encyclopedia like Wikipedia. (Kaplan & Haenlein, 2010). Boyd and Ellison (2007) provided the first definition of social media, focusing mainly on social platforms. They conducted a study to assess interpersonal communications on social media. It also happened when Facebook usage and awareness among the general public sharply increased (Boyd & Ellison, 2007; Kiron et al., 2012). As early alternative definitions go, Kaplan and Haenlein's (2010) study were widely adopted. They underlined the importance of using social media, particularly Web 2.0, on the internet. The use of social media, especially by small firms, is a tool for doing specific commercial activities while utilizing technical expertise. Social media is well-known as a platform that allows businesses to create user-generated content without having a physical presence (Scott & Orlikowski, 2014).

Firms compete favorably in the global marketplaces with the help of social media (Alhassan et al., 2023). According to Atanassova and Clark (2015), social media enables two-way, real-time communication by sharing tacit knowledge for relationship development (Humaid & Ibrahim, 2019). According to Filo et al. (2015), the advent of social media has ushered in a new age of technological innovation by making it possible for individuals and groups to collaborate on projects and share the results of their efforts. As was said before, it is important for this research to have a distinct viewpoint on the use of social media in marketing. Dwivedi et al. (2015) define social media marketing as an ongoing dialogue between a business and its target audience about the latter's product or service, with the goal of gaining insight into the product or service from the perspectives of the target audience. From the perspective of small and medium-sized enterprises (SMEs), marketing is an approach used to inform clients about a company's offerings and foster lasting relationships with them (Reijonen, 2010). Based on the definitions, the researchers have concluded that social media is a user-generated platform composed of many user-generated components that allow for the sharing of interesting content, the initiation of meaningful dialogue, and the distribution of information to a wider audience. It's an online community developed by and for its users, providing an inviting atmosphere for a wide range of interpersonal and professional connections.

Perceived Usefulness of social media for SMEs

Social media usage continues to increase, which begs the question of how SMEs can efficiently utilize these applications (Clement, 2020). Numerous studies covered a range of advantages, offering proof of the value of social media. From a broader perspective, SMEs can benefit from implementing and using social media, including eWOM branding (Li & Wu, 2018; Ananda et al., 2019; Michaelidou et al., 2011), Brand relationship building (Thompson et al., 2018; Hudson et al., 2015; Dahnil et al., 2014), Real-time product information (Kim & Song, 2018; He et al., 2015; Parveen et al., 2018). There is mounting evidence that SMEs gain advantages from having a social media presence and that these advantages are no longer the exclusive domain of larger companies. Parveen et al (2018) explains how chatbots increase engagement in digital marketing. Stelzner (2017) explains how it has changed and where it is going. All these studies give insight into how social media is becoming the new face of marketing.

There are several network platforms where business owners and customers interact on the need’s assessment of products within the marketing offerings. According to Alalwan et al. (2017), there is a need to research and analyze the effects of various social media platforms on the return on investment of marketing expenditures for promotional activities meant to reach audiences or customers. To comprehend the claim made by Alalwan et al. (2017), for instance, Facebook, YouTube, Instagram, Twitter, LinkedIn, and many other platforms could be researched separately. According to Lindsey-Mullikin and Borin (2017), social media platforms encourage impulsive purchases, boost sales from both new and returning customers, and offer marketing intelligence on consumer attitudes, interests, and perceptions. From the author's viewpoint, consumers using social media platforms become attracted to marketing offerings through the frequent content of a particular product at their disposal. Marketers and business owners effectively use social media to draw clients to their services or goods who may not have otherwise known about them.

Social media platforms connect millions of users, and yet the originators of these platforms may anticipate that the effects could be this far (Samuel & Joe, 2016). The understanding of social media marketing seemed low in developing markets despite its rapid change, and Wa Municipal is no exception. For instance, in May 2019, Facebook was the most popular social platform exceeding 2.3 billion monthly active users (Facebook, 2019), and today it has about 2.936 billion monthly active users (April 2023, Global Digital Report). Social media has seen an upsurge in usage in organizations. The effects of their use may account for this. According to several empirical research (Cesaroni & Consoli, 2015; Kaplan & Haenlein, 2010), social media platforms can be used by both large and small businesses because they do not demand significant financial outlays. These platforms are helpful to small enterprises' growth (Broekemier, Chau & Seshadri, 2015; Dirgiatmo, 2015), especially when dealing with the limits connected to their size. (Cesaroni & Consoli, 2015).

Challenges SMEs faced regarding their social media usage.

Although businesses have a positive attitude regarding social platforms and how faster they can get returns on their modest investments (Tajudeen et al., 2018), there are still barriers preventing SMEs from using new social platforms. Although these platforms have several benefits for small and medium-sized enterprises (SMEs), their adoption rate is low (Ahmad et al., 2019).

There are several obstacles that limit the ability of SMEs to adopt cutting-edge technology. Small and medium-sized enterprises (SMEs) are less likely to invest in cutting-edge technology than their bigger counterparts (Cesaroni & Consoli, 2015; Haller & Siedschlag, 2011) because of funding limitations. Since of this, small and medium-sized enterprises (SMEs) are notoriously frugal since it is so difficult for them to get the resources they need (Ghobakhloo et al., 2011). Small and medium-sized enterprises (SMEs) are often seen to be risk-averse and to have a low propensity for taking chances (Bharati & Chaudhury, 2015). Online technology adoption by small and medium-sized enterprises (SMEs) is hampered by a lack of funding, according to studies (Carcary et al., 2014; Kannabiran & Dharmalingam, 2012). This causes them to forego high-priced initiatives like the development of new technology (Harindranath et al., 2008). Ongori and Migiro (2010) reviewed the literature on IT adoption in SMEs and found that it was unrelated to industry and legislative framework.

Technology Acceptance Model (TAM)

The Technology Acceptance Model (TAM) evolved from the earlier Theory of Reasoned Action (TRA) developed by Fishbein et al. (1977) to evaluate individuals' adoption of technology. TRA posits that individuals consciously act independently and assess available information to apply it in their lives. Building upon this theoretical foundation, Davis enhanced TRA into TAM in 1986. TAM employs a behavioural theory approach to assess technology implementation processes, offering a structured framework for understanding individuals' acceptance of technology. As per the research conducted by Carlos Martins Rodrigues Pinho and Soares (2011) and Kamal et al. (2020), the Technology Acceptance Model (TAM) framework serves as a foundational concept for examining and understanding the behavior of individuals towards technology adoption and acceptance. Rooted in psychological principles, TAM elucidates how users' beliefs, attitudes, intentions, and behaviours interrelate when interacting with technology.

The primary objective of the Technology Acceptance Model (TAM), as outlined by Alam et al. (2023), is to delineate the factors influencing the widespread adoption of information-based technology and to elucidate users' behaviors toward such technology, considering the impact of external factors on psychological underpinnings. TAM was devised to fulfill this objective by identifying pivotal variables gleaned from prior research on technology adoption theory and by leveraging the Theory of Reasoned Action (TRA) as a foundational theory to elucidate the interrelationships among these variables. According to Venkatesh and Davis (2000), the Technology Acceptance Model (TAM) is noted for its simplicity compared to other frameworks. This aligns with the advantages of TAM, which prioritize an economical and yet still valid approach. TAM focuses solely on interpreting the relationship between behavior and belief, specifically regarding the perceived benefits and ease of use of an information system. The ultimate objective is to predict the actual usage of information systems by users (Macedo, 2017). TAM is believed to be capable of forecasting technology adoption based on two factors: perceived usefulness (PU) and perceived ease of use (PEOU) (Lanlan, et al., 2019).

Perceived Ease of Use (PEOU)

According to research by Lanlan et al. (2019), Zongo and Nassè (2019), and Al-Adwan (2020), perceived ease of use (PEOU) refers to individuals' confidence in the ease with which technology can be utilised and comprehended to simplify tasks. It underscores users' perceptions that the applied information technology is user-friendly and does not pose a burden. Government online services that are easily navigable and accessible by users exemplify this ease of use. Al-Adwan (2020) describe PEOU as the extent to which individuals believe that using a specific system can alleviate the workload. The frequency of usage and the user-system relationship indicate the level of ease of use, with more frequently used systems being more familiar and easier to navigate. Lanlan et al. (2019) proposed a PEOU index comprising attributes such as ease of learning, controllability, comprehensibility, flexibility, ease of mastery, and user-friendliness.

Perceived Usefulness (PU)

According to Sagnier et al. (2020), perceived usefulness is the criterion by which the utility of technology is assessed by its users. On the other hand, Qi (2019) define usage confidence as an individual's capacity to enhance organisational performance in the future by utilising a specific application system. An individual is inclined to use information technology if they possess a clear understanding of its advantages or applications (Kabra et al., 2017). Perceived usefulness (PU) is a component of the Technology Acceptance Model (TAM) that has been empirically tested in previous studies (Qi, 2019; Sagnier et al., 2020). Research findings affirm that PU has experimental validity in explaining users' adoption of technology. Chandra et al. (2020) delineates several dimensions of perceived usefulness, including usefulness, enhancement of capabilities, speedier work processes, increased productivity, simplified tasks, and effectiveness.

Attitude Toward Using

According to Setiawan et al. (2021) and Kelly et al. (2023), the Attitude Towards Using (ATU) construct in the Technology Acceptance Model (TAM) represents an individual's disposition towards using a system, whether they accept or reject the use of technology for their tasks. ATU serves as a determinant influencing behaviour in the adoption of technology. It can be inferred that ATU reflects an individual's inclination towards either supporting or rejecting the application of technology, serving as an indicator of their intention to use it or their level of interest in its utilisation.

Behavioural Intention

As per Fatmawati (2015), behavioural intention refers to the inclination of technology users to consistently engage with information systems over time. In line with TAM theory, users' preferences for system usage are shaped by their perceptions of perceived usefulness (PU) and perceived ease of use (PEOU). Hence, it can be inferred that individuals are more likely to be interested in utilising a technology if they believe it can enhance their performance and if they perceive it to be easy to use or require minimal effort. Behavioural intention encompasses several indicators, including willingness to market, recommend, and continue using the technology (Chen, & Tsai, 2019; Lee et al., 2020).

Businesses can gain significant insights by analysing the influence of social media marketing on the performance of small and medium-sized firms (SMEs) in Ghana using the Technology Acceptance Model (TAM). TAM offers an organised framework for comprehending SMEs' opinions about the utility and usability of social media platforms, assisting in the formulation of strategic decisions about the adoption of social media. SMEs may improve performance outcomes, hone their strategies, and maintain their competitiveness in the digital market by identifying adoption barriers and evaluating the efficacy of social media marketing initiatives. The use of TAM in this situation makes it easier to make well-informed decisions and optimise resource use, which eventually helps SMEs in Ghana flourish.

Results and effects of using social media on SMEs

In the view of Aral et al., (2013), businesses may evaluate the impact of social media on their bottom lines by looking at accounting or financial market developments. The advantages of a company's participation in social media were investigated by (Rishika et al. 2013). The findings of Kwok and Yu (2013) provide support to the research of Rishika et al. (2013) by showing that the use of Facebook by SMEs may boost sales. These findings are consistent with the idea that user-generated content affects financial performance, as proposed by Paniagua and Sapena (2014). Surprisingly, Ahmad et al.'s (2019) research reported the results of a quantitative survey of SMEs in the United Arab Emirates to examine the factors that influenced their usage of social media and the consequences on performance. In contrast to Kwok and Yu's (2013) findings, they found that SMEs' performance was unaffected by social media marketing.

Social media integration inside corporate systems was shown to have improved user interactions and solidified relational links among virtual players in a 2013 study by Subramaniam and Nandhakumar. According to research by Van Osch and Steinfield (2016), users of enterprise systems who participate in online discussion boards exhibit different boundary-crossing behaviours based on their position in the organization. Staff production is impacted by social media platforms, and user engagement is improved (Benthaus et al., 2016).

In addition, as Leonardi (2014) elucidated, the ability to observe communications across companies fosters meta-knowledge without resulting in information duplication. According to an analysis by Miller and Tucker (2013), most companies' social media posts highlight the company's achievements rather than the customers' interests. Social media management and utilisation is known to increase employee engagement, which in turn boosts innovation, loyalty, and morale. The use of social media has a substantial and beneficial effect on the financial and non-financial performance of small enterprises (Ainin et al., 2015). Parveen et al. (2015) used the viewpoints of Malaysian social media managers to investigate the impact of social media on business performance. The research uncovered eleven key social media use patterns, including: enhanced customer interactions and services; reduced expenses; more information sharing; heightened brand recognition; expanded opportunities for making money and gaining a competitive edge; and so on. In addition to cost savings, greater consumer interactions, and better access to information, Tajudeen et al.'s (2017) study showed that an organization's performance increases when its employees utilize social media.

Hypothesis

To develop this research hypothesis, the researchers read through some theories, models, and an overall picture of social media marketing. Understanding the link between some independent factors and their dependent variables became important. The study used latent variables demonstrate the factors given the null hypotheses;

Hypotheses development

H1- Social Media Usage has a direct positive effect on SMEs' Performance.

H2- There is a direct and significant relationship between Social Media Usage and Perceived Usefulness

H3- Perceived Usefulness directly and positively relates to SMEs' Performance.

H4-Perceived Usefulness mediates the relationship between Social Media Usage and SMEs Performance.

The independent variable is social media usage, and the dependent variables are SMEs' performance and the perceived usefulness of social media usage see figure 1.

Social media usage by SMEs with its factor loadings;

• SMU1- easier than traditional marketing.

• SMU2- less promotion cost

• SMU3- user friendly

SMEs Performance with its factor loadings;

• P1- good financial health

• P2- productivity of the firm is enhanced

• P3- cost savings

• P4- improved information accessibility of the firm

Perceived usefulness with its factor loadings;

• PU1- advertising food brands on social platforms are helpful to consumers

• PU2- it increases brand awareness to consumers

• PU3- it increases brand loyalty

• SI4- it increases brand usage

• PU5- advertising and promotion

• PU6- accessibility to so many targets’ markets

• PU7- build credibility and community

Methodology

Research design and approach

Information search was done ted for the study using both primary and secondary sources. The primary data was obtained by addressing a questionnaire to the respondents. The secondary data was obtained from various literature sources including: journals, textbooks, websites about social media marketing. To ensure that readers had a clear understanding of social media usage and how it affects SMEs in relation to the study's goals, the researchers employed positivist orientation. According to Johnson and Onwuegbuzie (2004), it is a logical and practical approach that provides a natural complement in quantitative research.

Consideration is needed when creating an effective sampling method to ensure compatibility (Collins et al., 2007). Pure restaurants in the Wa Municipality were the study's target population. The respondents were chosen by the researchers using a random sampling technique. According to Acharya, Prakash, Saxena, and Nigam, (2013), each person has an equal chance of selection from the population. To obtain representativeness, the degree to which the sample accurately represents the population, the study used simple random sampling techniques; a probability sampling approach to draw sample units. The simple random sampling provided fair opportunity for sample units in the frame to be selected for the study. The principle in using the technique was that, the list of registered elements (small and medium enterprises that are providing restaurant services only) were put into a draw and randomly selected. The study also adopted the convenience sampling technique to obtained responses from the customers. This questionnaire was designed into a google link and shared to customers that were at the restaurants or floated on social media for some customers to offer their responses. This was done until a target quota of 100 respondents as customers were reached.

Sample Frame and Sample Size determination

The study used a reconnaissance survey to obtained a list of registered small and medium business that are providing restaurant services only within the Wa Municipality. A list of 2,637 SMEs in restaurants service only were obtained from the Business Resource Center, Wa. This constituted the sample frame. To determine the sample size, the study used the following formula of Ganassali (2009), and Nassè et al. (2019) : n ꞊ (p x (1-p)) / (e / 1.96)²;

p represents the observed percentage and e representing the maximum error. Thus, n ꞊ (0.5 × (1 - 0.5)) / (e / 1.96)² ꞊ 0.25 / (e / 1.96)² ꞊ 196. The number of respondents for a maximum error of 7% is 196. The researchers have 200 respondents to fill the questionnaire and this is a little bit representative.

Data analysis

Data analysis was performed using SmartPLS modelling. Researchers such as (Djakasaputra, Wijaya, Utama, Yohana, Romadhoni, & Fahlevi, 2021; Kartika, 2021; Borah, Iqbal, & Akhtar, 2023), linked social media usage and SME's sustainable performance and have all used SmartPLS to analysis the relationships between variables. SmartPLS allows researchers to simultaneously model connections between endogenous and exogenous latent variables while simultaneously building connections between latent and manifest variables.

Ethical consideration

According to Ritchie et al. (2013), the "heart of high-quality research" is concerned with moral concerns. Ethical issues should be emphasised and described on all survey forms, including online surveys (Bakla, ekiç, & Köksal, 2013; Buchanan & Hvizdak, 2009; Buchanan, 2004; Buchanan, et al., 2004). Ethical principles and the guidelines established by the institution must be followed. Because participants' or respondents' responses become tainted when anxieties become actual, ethics play a role in all study inquiries. Good ethical practice while conducting an online survey may be ensured in part by informing respondents of the research's ethical principles and code of conduct (Bakla, Ekiç, & Köksal, 2013). Respondents are more likely to believe you after this (Buchanan & Hvizdak, 2009). The study ensured ethical issues were considered. The name of firms, and the identity of the respondents were kept confidential (Nassè, 2022). Security of data during collection, transmission, and storage are additional online survey research ethical problems that must be taken seriously. As a result of the measures used during data collection, storage, and administration, respondents could feel confident that their responses would remain private.

Findings and Discussion

The first step in analyzing PLS-SEM results is to analyze the measurement model. Empirical measurements of the connections between the indicators are provided by a model estimate. It is important to think about how the two models (measurement and structural) relate to one another (Sarstedt et al., 2017). Due to the introspective nature of the research, it is essential that the validity and reliability of the measuring model be assessed prior to the structural model's evaluation. The indicator's convergent validity, discriminant validity, reliability, and internal consistency reliability were all examined in this research (Hair et al., 2019; Urbach and Ahlemann, 2010).

Indicator reliability

The degree to which "a variable or group of variables is consistent regarding what it intended to assess" is how indicator dependability is defined (Urbach and Ahlemann, 2010, p. 18). Reflective indicator loadings assess the indicator's dependency. Usually, the threshold to meet the required dependability is 0.708 and above figure 2.

From the diagram above, the latent variables were Social Media Usage, Perceived Usefulness, and SME performance. SMU1, SMU2, and SMU3 were the indicators for Social Media Usage, P1, P2, P3, and P4 for SME's performance, PU1, PU2, PU3, PU4, PU5, PU6, and PU7 were the indicators for Perceived Usefulness. The hypothesis development captured all the indicators' definitions. All the indicators had a substantial loading on their related latent variables. All the indicators were above the threshold of 0.708 when analyzed. It revealed that the indicators met the minimal threshold criteria, and thus, all the factor loadings were reliable for their latent variables. According to Shen (2012), people or customers become comfortable transacting with an online source when they are sure that a trusted human is present.

Internal consistency reliability

After checking the precision of the indicator, the researchers used Cronbach's alpha to determine the level of internal consistency. The scores are equivalent in range and significance when latent variable indicators have large alpha values (Cronbach, 1951). The lowest acceptable value for Cronbach's alpha is 0.70 (Nunnally, 1978). All latent variables or constructs had an Alpha value more than or equal to 0.70, as shown in Table 1 below.

Table 1 Determinacy of Construct Reliability Using Cronbach
	Cronbach’s Alpha	Rho_A	Composite reliability	Average Variance Extracted (AVE)
Perceived Usefulness	0.949	0.949	0.958	0.768
SMEs Performance	0.89	0.895	0.924	0.753
Social Media Usage	0.858	0.858	0.913	0.779
Source: Field Survey, 2023

Convergent Validity

The investigation determined the convergent validity of each component after assessing its internal consistency and reliability. The "degree to which separate items representing a construct converge to compare items measuring other constructs" is known as convergent validity (Urbach and Ahlemann, 2010, p. 19). According to Fornell and Larcker (1981), Average Variance Extracted (AVE) criteria measure convergent validity. Each indicator loaded on a build must be squared to calculate the average variance extracted. The AVE cut-off value is 0.50 (Hair et al., 2019). It shows that the latent factor or concept displays significant convergent validity when it accounts for at least 50% of the variability of its components (Hair et al., 2019; Urbach and Ahlemann, 2010). Table 1 above shows AVE values above the minimum threshold of 0.50, indicating adequate convergent validity was achieved.

Discriminant Validity

The extent to which a concept is empirically distinct from other constructs in the structural model is what is meant by "discriminant validity," as defined by Hair et al. (2019, p. 9). In PLS-SEM, the cross-loading of each latent variable score with all other items is determined to establish or evaluate discriminant validity (Chin, 1998). When each indicator loads higher for its construct than any other construct, we say that the indicators are discriminant against one another and that the latent variable or construct is present. All objects have a greater loading with their designated construct or latent variable. Table 2 shows that the latent variables may be used to distinguish between one another.

Table 2 Cross-Loading Indicator
Cross –Loading Indicators	SMEs Performance	Social Media Usage	Perceived Usefulness
SMU1	0.693	0.887	0.497
SMU2	0.614	0.747	0.438
SMU3	0.704	0.798	0.444
P1	0.924	0.747	0.467
P2	0.897	0.755	0.47
P3	0.956	0.774	0.477
P4	0.816	0.583	0.62
PU1	0.541	0.536	0.944
PU2	0.419	0.412	0.866
PU3	0.525	0.479	0.904
PU4	0.558	0.503	0.941
PU4	0.731	0.471	0.924
PU5	0.725	0.468	0.934
PU6	0.637	0.42	0.864
Source: Field Survey, 2023

Hypothesis Testing Structural Model Assessment

It is possible to verify the structural model once the measurement model has been verified (Urbach and Ahlemann, 2010; Hair et al., 2019). In furtherance of model assessment, Hair et al. (2019), PLS-SEM uses an inner model test to assess hypotheses, which involves a significance test for direct and indirect effects and a measurement of the extent to which exogenous factors impact endogenous variables.

The route coefficient between latent variables is a crucial statistic, as emphasized by Urbach and Ahlemann (2010). According to the definition provided by Streukens and Leroi Werelds (2016), bootstrapping is a resampling method that does not rely on parametric assumptions to assess the precision of its results. Since PLS-SEM does not ensure normal data distribution (Hair et al., 2016), a non-parametric test should be conducted (Hair et al., 2016). Bootstrapping may provide T-statistics for examining both direct and indirect impacts. Table 3 below displays the findings. For a 10% (two-tailed) significance level, Hair et al. (2011) proposes a minimal critical T-value of 1.65 due to the inclusion of a 95% confidence interval. Table 3 shows that all three hypotheses are accepted since their minimal essential T-values are more than or equal to 1.65. A statistically significant result is one with a P value less than 0.05, which means the null hypothesis was confirmed. As can be seen in Table 3 and figure 3 above, P values of 0.000 (less than the 0.05 threshold) imply a perfect significance level between the constructs, lending credence to the null hypothesis. The null hypothesis is accepted if the "P" value is less than 0.05.

Table 3 Hypotheses Result of the Structural Model showing H1, H2, H3, and H4
Constructs with their paths effect	Coefficient	T statistics	P values
	(|O/STDEV|)
Perceived Usefulness -> SMEs Performance	0.423	4.44	0
Social Media Usage -> Perceived Usefulness	0.898	35.795	0
Social Media Usage -> SMEs Performance	0.577	6.086	0
Social Media Usage -> Perceived Usefulness -> SMEs Performance		4.44	0
	0.382
Note: **, p-value < 0.05, is significant, and T value >1.96, is also significant
(Source: Field Survey, 2023)

Table 4 R–Square Model of Fit Criteria
Dependent constructs	Rsquare	R-square adjusted
Perceived Usefulness	0.806	0.804
SMEs Performance	0.949	0.948
Source: Field Survey, 2023

H1: Social media usage has a direct positive effect on SMEs performance

Table 3 show that a T value of 6.086 >1.96 shows that SMEs are significantly impacted by the use of social media and its advantages. Table 3 shows a perfect and positive association with a P value of 0.000< 0.05 and a coefficient value of 0.423. This implies that if SME social media metrics improve, so will business outcomes for small and medium enterprises. The efficiency with which a small or medium-sized enterprise (SME) use social media to accomplish management objectives in actual business practice is a measure of performance (Porter, 1991). According to the model proposed by Rishika et al. (2013), customers' engagement with a company's social media might affect the frequency and profitability of their visits. This finding supports the results of Kwok and Yu (2013), who found that Facebook use was associated with a rise in sales.

H 2: There is a direct and significant relationship between Social Media Usage and Perceived Usefulness

A T value of 35.795 > 1.96, as shown in Table 3, indicates that social media use influences the perception of utility. Table 3's positive coefficient value of 0.898 and matching P value of 0.000< 0.05 demonstrate an ideal positive connection. Researchers have shown a favorable correlation between Perceived Usefulness and time spent on social media platforms (Gefen & Straub, 2000; Pavlou, 2003). According to Davis's Technology Acceptance Model, the perceived utility and simplicity of use of a social network by a corporation or an individual will determine whether or not they will utilize the network for commercial purposes.

H3: Perceived usefulness directly and positively relates to SMEs performance

From Figure 3 and Table 3 above, a T value of 4.440 > 1.96 indicates that perceived usefulness directly relates to SMEs' performance. Its corresponding P-value of 0.000 < 0.05 and a positive coefficient of 0.577 shows a significant and positive relationship between Perceived Usefulness and SME Performance. This strengthens Ainin et al.'s (2015) research which revealed that the usefulness of Facebook has a strong positive impact on financial performance, as measured by an increase in sales transactions and volume.

H4: Perceived usefulness mediates the relationship between social media usage and SMEs' performance.

Table 4 also measures the specific indirect effect of the hypothesis. The analysis revealed that Perceived Usefulness as the mediating variable between Social Media Usage and SME performance has a positive and significant relationship. The T value of 4.440>1.96 with a corresponding P value of 0.000 showed a mediation. The is occurred because all three hypotheses revealed some significant and positive effects between their paths, especially between the independent variable (Social Media Usage) and the dependent variables (SMEs Performance and Perceived Usefulness).

Assessing the goodness of fit

The significance of the goodness of fit and the path coefficient in the structural model are used to reach a conclusion. If the model is well-fit or not, this analysis will show it (Henseler et al., 2015). Measurement and structural model misspecifications may be detected with the use of the GOF test (Dijkstra and Henseler, 2015). The R-squared determination coefficient is the standard for this purpose (Hair et al., 2019). R2 is the measured model's power. Cumulative effects of exogenous latent variables are represented by the endogenous latent variable (Hair, Sarstedt, Hopkins, & Kuppelwieser, 2014).

R2 values between 0 and 1 indicate a high level of explanatory power. Weak, moderate, and substantial R2 values are respectively 0.25, 0.50, and 0.75 (Hair et al., 2011; Henseler et al., 2009). According to Chin (1998), an R2 of 0.333 is about average, 0.190 is about weak, and values around 0.670. Table 4 below displays the R2 values of the model, which range from 0.806 to 0.949. According to the research (Hair et al., 2019; Urbach and Ahlemann, 2010), the total external latent variable may account for 80–94% of the variance in the endogenous components. These results suggest that the model is a good fit for the data.

Social media and its benefits to SMEs over traditional marketing

The researchers have made efforts to summarize and put into components the responses of the various SMEs regarding how beneficial social media marketing is to their firms over the traditional form of marketing. The researchers categorized these responses under three major components; awareness, advertising cost, and relay of information.

Advertising costs

Nassè (2019) has demonstrated that SMEs in the West African context are using technology and management tools to enhance their performance, to reduce cost, and to boost their customer satisfaction. This research in the context of Ghana shows that some SMEs confirmed that social media usage leads to low advertising costs. They explained that their firms do not allocate funds towards advertising as their form of social media marketing is free. The belief is that most of the consumers who patronize their food brands are people who belong to the Internet age. They also admitted that sending an advert to a radio station is costly compared to advertising on Facebook, TikTok, or any social media platform.

Relay of information

Unlike traditional marketing, social media allows SMEs to directly communicate with their customers on their need’s assessment of food brands. "…We received complaints and compliments from our consumers, unlike traditional marketing where it is a one-way communication for us..." In Dave Evan's feedback cycle, he differentiates social media marketing from traditional marketing in terms of interaction. With social media marketing, firms or brands can receive feedback and interact with consumers to understand their perceptions of their content. Scholars have noted that the ability of a social platform to increase visibility and information separates them from other communication platforms (Boyd, 2010; Grudin, 2006).

Awareness

With 60% of SMEs that confirmed the usage of social media out of the 200 SMEs contacted, reaching out to a large number of customers was the ideal response given. Social media affords users to make behaviors, knowledge, preferences, and communication network connections that were once invisible (or at least hard to see) visible to others (Treem & Leonardi, 2013). Some SMEs admitted they became popular with consumers through their social media handles. An SME says, "Our Facebook handle has about 12,000 likes and almost 4,200 followers and my client base has doubled." Through this effect, many of these firms said their customer base has increased from their previous use of only radio stations.

To determine whether social media is an efficient marketing medium for restaurants in the Wa Municipality, we identified consumers’ perceptions of this marketing medium. The figure 4 above depicts the perception of customers in percentages whether using social media in buying food is stress-free or not. 66% of the respondents said it was stress-free, and 34% said it was not. In analyzing this, it appears to the researchers that many of the customers who responded to the questionnaires know how useful social media is in their buying decisions.

Conclusion and Future Research Direction

The main research objective of the study was to determine the effects of social media marketing on small and medium-sized enterprises. According to the explored literature and the data analysis, social media marketing is a crucial marketing strategy for SMEs' survival in the digital era. The research concludes that social media marketing positively and significantly affects SMEs. The hypothesis that SMEs lack the resources for growth and the capacity to accept new marketing paradigms sums up the research problem. However, the study revealed that social platforms used by SMEs ultimately lead to positive performance through cost savings and sound financial health. Without spending money on an outside research study, it is simpler to understand the demands of target consumers by observing and analyzing key performance indicators and feedback. The anticipation is that as new platforms gain popularity and acceptance among businesses, research on their use will become more and more crucial. This effort may be the beginning in that direction since it had an exploratory goal to produce a comprehensive picture of social media marketing among SMEs.

Ghana Enterprise Agency and the Ministry of Business Development, which are to interrelate and administer the development of small and medium-sized enterprises, can rely on this study to fashion out a more revamped model of SME marketing in the context of social media. Though 60% of the 200 SMEs that filled out the online questionnaires agreed they were into social media marketing, which indicates enough representative sample size, a percentage more than this number of SMEs should have known about and utilized these social platforms to meet the emerging market trends. These are well-developed platforms that innovative SMEs can use to do marketing in all parts of the globe.

Some steps to address the issue of mistrust in social media marketing is needed. Customers are always worried about dealing with unknown people online. Thus, SMEs should have trusted influencers or promoters for their brands. From the literature reviewed and the data analyzed, influencers represent brands as the first consumers because they know much about the product, and other potential consumers rely on their experience to make their purchasing decisions. These are also platforms that unscrupulous people also explore to their advantage. As a result, many customers still see these platforms as unsafe for transacting business. Indicates that negative feedback from a consumer about a product deters customers from purchasing that product. Thus, the issue of mistrust must be investigated by researchers.

Lastly, the relevant administrative agencies such as; Special Development Initiatives, National Board for Small Scale Industries (NBSSI), National Entrepreneurship and Innovation Plan (NEIP), Association of Ghana Industries (AGI), Ghana National Chamber of Commerce and Industry (GNCCI), and Ghana Investment Promotion Centre (GIPC) can rely on this study to campaign on the enormous usefulness of these online social platforms to marketers and buyers.

Due to its geographic concentration on SMEs in a Municipality in the Upper West Region, this research may have suffered from a sampling bias. This complicates extrapolating the findings to other small and medium-sized enterprises (SMEs) in other districts and towns. In order to understand a complete picture of small business social media marketing, further research is needed to cover the entire region or the whole country on a wide range of Upper West Region SMEs is essential.

In addition, the scope of this study was broadened to include small and medium-sized enterprises (SMEs) generally, rather than just one. Studying social media marketing at several companies may lead to overgeneralization, but this method let the researcher see the big picture of SMB marketing and avoid the prejudice that comes from focusing on only one sector. This paper provides a foundation for future research into the topic of social media marketing as it pertains to a certain kind of small and medium-sized enterprise (SME) in Wa Municipality. The idea is that every field has its own set of specific features and needs. Therefore, certain kinds of social media are more suited to specific industries than others.

Theoretical and Practical Implications

The theoretical understanding and practical ramifications of our research are greatly enhanced by our work. Theory-wise, our research adds to the body of knowledge on social media marketing by concentrating on how it affects SMEs that are based in Ghana, which is a distinctive setting. We enrich theoretical understandings of digital marketing techniques in many contexts by exploring this particular demography and offering insightful information on how social media habits differ across cultural and economic landscapes. Additionally, we expand the usual scope of the theoretical framework by utilising the Technology Acceptance Model (TAM) to evaluate SMEs' adoption and utilisation of social media marketing tools. By providing insightful theoretical information about SMEs' adoption of technology-driven marketing, this extension highlights the adaptability of TAM in assessing attitudes and actions linked to digital advances.

Adaptation to new management trends in the African context is one of the keys to stimulate companies’ success, thus, this research provides managers and owners of SMEs with practical advice on how to improve their social media marketing campaigns. Our research offers specific suggestions for creating social media marketing strategies that work for the Ghanaian market by identifying important aspects that affect SMEs' adoption and utilisation of social media platforms. This useful advice gives SMEs the know-how and resources they need to use social media to interact with clients, build brand awareness, and eventually accelerate business expansion. Our research is also important for government agencies and policymakers that help small and medium-sized enterprises grow and go digital. Our research contributes to the development of focused policies and initiatives that aim to promote digital literacy, facilitate access to digital resources, and foster an environment that allows SMEs to flourish in Ghana's dynamic market landscape by highlighting the role of social media in enhancing SME competitiveness and performance.

Acknowledgement

The researchers would like to acknowledge the numerous respondents who participated to the research. They are grateful to Dr. Clement Nangpiire, Dr. Théophile Bindeouè Nassè, Dr. Mohammed Majeed and Dr. Felicia Naatu for their valuables inputs to better the quality of this paper. They are also grateful to the editorial board of the International Journal of Entrepreneurship for their steady support and inputs.

Conflict of Interest Statement

No conflict of interest has been declared by the authors.

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Received: 27-Jan-2024, Manuscript No. IJE-24-14550; Editor assigned: 01-Feb-2024, Pre QC No. IJE-24-14550 (PQ); Reviewed: 15-Feb-2024, QC No. IJE-24-14550; Revised: 22-Feb-2024, Manuscript No. IJE-24-14550 (R); Published: 29-Feb-2024