Adoption of Social Media for SME Growth in the Covid-19 Era: A Case of SMEs in the Clothing industry in Lusaka, Zambia

Gladys Kakumbi¹, Jackson Phiri²

¹Graduate School of Business, University of Zambia, Lusaka, Zambia.
²School of Natural Sciences, Department of Computer Sciences, University of Zambia, Lusaka, Zambia.

DOI: 10.4236/ojbm.2022.106159                

Abstract

Social media has become an emerging integral component to any business in the COVID-19 era. This study on social media adoption by SMEs in the COVID-19 era using the VT4 framework is thus essential. This study sought to investigate how the VT4 influences social media adoption and growth of SMEs. A quantitative research design was used to carry out this study. The target population of the study was SMEs staff in the clothing industry in Lusaka. A structured questionnaire was used as the data collection tool on 240 randomly selected sample size. The Statistical Packages for Social Sciences (SPSS) was used for data analysis. The study first sought to establish the social media platform adopted by SMEs in their business and the factors that influence adoption. The findings of the study revealed that Facebook was the most used social media platform among SMEs followed by WhatsApp. The least used was YouTube. The results of the study further revealed that among the factors that influenced social media adoption by SMEs was perceived usefulness and society’s attitude. The study further sought to establish the impact of VT4 on social media adoption and SME growth. Descriptive analysis and the Pearson’s correlation were used to analyze the results. The results of H₁ to H₅ showed a statistically significant Pearson’s correlation with P Value of less than 0.005 (sig. 2-tailed) < 0.05, indicating that there is a statistically significant relationship between the VT4 and social media adoption and SME growth. Consequently, the study established that there was a statistical relationship between the VT4 (the independent variable) and social media adoption and SME growth (the dependent variable). The study thus concluded that SMEs in the clothing industry in Zambia have adopted social media and this has enhanced their growth. To elicit positive impact of the VT4 on social media adoption and SME growth, the study recommends mandatory social media presence by SMEs via any two or three prominent social media platforms such as Facebook, WhatsApp or Twitter and formulation of a deliberate policy that will offer training to staff so that they come to a better understanding of the VT4 model so as to enable them utilize social media optimally. Furthermore, the study recommends putting up of a deliberate policy by government that will make electronic gadgets such as smart phones affordable.

Keywords

Component, VT4, Social Media, Organizational Growth, SME, Lusaka, Zambia

1. Introduction

The coming of the novel Corona Virus Disease, popularly known as COVID-19, has affected the whole world with many countries, including Zambia closing their borders, businesses and placing citizens under quarantine or lockdown. This has had an impact not only on peoples’ lives but also on all businesses especially how business is done. Since most businesses are limited in their operations due to COVID-19, there is need for such businesses to still remain functional and survive. To do that, they need to tap into the opportunity offered by digital technologies and the internet. This study examined the role of social media, in SMEs growth strategies in the clothing industry in Lusaka, Zambia during the COVID-19 era. It proposed the extent to which the social media enhances or lowers the economic growth of SMEs in the clothing industry in Zambia.

The COVID-19 pandemic, since its outbreak in 2019 in Wuhan China (Kandola, 2020), had infected more than 377 million people and caused more than 5.6 million deaths (Worldometer, 2022). Due to its devastating effect, the COVID-19 was declared a global pandemic by the World Health Organization (WHO). As such, there had been frantic efforts by governments, health practitioners, multinationals, businesses, individuals and all stakeholders to prevent the spread of the disease. This led to lockdowns of nations, communities and temporally closure of physical operations of businesses in an effort to prevent the further spread of the corona virus (OECD, 2020). Such restrictions negatively affected human life and businesses and had implications for sustainable operations of businesses including reduction of business activities, Human Resources intervention issues related to staffing and supply chain disruptions. This caused more severe effects on small and medium enterprises (SMEs) than on larger and global firms, since SMEs tend to have a lower capital reserve, fewer assets and lower level of productivity than larger firms, and are most vulnerable (OECD, 2020; Dua, Ellingrud, Mahajan, & Silberg, 2020). The situation has been the same in Zambia. After the outbreak of the COVID-19 pandemic, the use of some technologies that were not considered essential by SMEs such as social media and virtual reality related technologies became crucial to avoid complete shutdown of the global economy (Ting, Carin, Dzau, & Wong, 2020). It is the use of such technology that has now become the survival strategy during the lockdown of communities by different levels of government so as to contain the spread of the coronavirus disease (Vaccaro et al., 2020). This study was done in Lusaka District of Zambia, which has 645 registered businesses at the time of the study and the sample size was 240 calculated by the Moazzam’s formula.

1.1. Statement of the Problem

Digital technologies provide a platform for connectedness around the globe regardless of geographical distance. It is this that provides businesses with the opportunity to carry out their business regardless of the restrictions and disturbances that have come with the COVID-19 pandemic. According to a survey by Fairlie & Fossen (2022), sales losses were the largest in business as most businesses faced the common challenge of reduced sales and revenue with the coming of the Covid-19 pandemic due to lockdowns and movement restrictions posing great growth challenges on SMEs compared to big businesses. A research by UNCTAD (2021) revealed that there has been a dramatic rise in e-commerce amid movement restrictions induced by COVID-19 with global e-commerce jumping to $26.7 trillion in 2019 which is 4% higher compared to 2018. This included business-business (B2B) and business to customer (B2C) sales.

This is a clear indication of the growing importance of online activities by businesses. Perhaps social media could be an effective way to both growing and sustaining a business during the time of the COVID-19 pandemic. Therefore, there was a need to research on the adoption of social media (Facebook, Twitter and WhatsApp, Instagram) in SMEs growth in the case of SMEs in Lusaka District of Zambia. A quantitative study was conducted to establish the role of social media in business growth strategies and its effectiveness in the SMEs sector. Very little research had been carried out on the topic (Papadopoulos, Baltas, & Balta, 2020) and as such, there was need to extend this line of investigation to examine the level of Adoption of social media on SME economic growth. This was the basis for this study.

Therefore, this study sought to establish factors influencing the adoption of social media by SMEs and if there is any relationship between them. The findings of this research will resound with the benefits of small businesses and how that social media plays an influential role in growing and sustaining a business online. Furthermore, this will also help both small and big businesses to derive from this study, recommendations on how to effectively grow and sustain their businesses online regardless of any circumstances.

1.2. Conceptual Framework

This study’s conceptual framework adapted a VT4 theory. This theory is based on the Agenda Setting Theory. Using this model, the study’s variables were marked volume, tone, ties, topics and timing as the independent variables. Social media, represented by Facebook, WeChat, WhatsApp, Twitter and Instagram, YouTube and SME growth represented by market penetration, development, product development and diversification which were the dependent variables. Figure 1 presents the conceptual framework for this study.

2. Literature Review

2.1. Theoretical Review

This study’s focus was on technology (social media) adoption or diffusion among SMEs and the role that this plays in SMEs growth. Several theories and models have been employed to explain technology adoption or diffusion. Among them are the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), Theory of Reasoned Action (TRA), Diffusion of Innovation Theory (Iluba & Phiri, 2020), the Extension of the Technology Acceptance Model (ETAM) (Taherdoost, 2017) and the VT4 model (Carroll & Deepshouse, 2014). This study utilized the VT4 model which best explains how social media can influence social media use among SMEs and help them realign their strategic plans with the expectations of their stakeholders. It is this that will yield success in the use of social media by SMEs.

The VT4 theory is based on the Agenda Setting Theory which holds that the media has strong influence on what people think about or consider as important. This happens when the media selectively highlights certain events or items and gives them prominence. When a certain item is repeatedly highlighted or presented by the media, it has the potential to become the most important topic or

Figure 1. VT4 model (Source: Njuka & Phiri, 2021).

issue to the public (Carroll & Deepshouse, 2014). For example, the current war situation between Russia and Ukraine. The war has become the most important issue to the public because of the publicity that the media has given it. There are many other wars going on around the world but the Russia-Ukraine war has taken center stage due to the influence of the media. The content volume on the Russia-Ukraine was high in the media. This also applies to the business world. For example, when Dr. Mujajati of Zambia broke the news on his social media page about the virility of water melons, the media was awash with the content on the benefits of watermelon on sexual potency. The content volume was high and this was treated as important by the public so much so that there arose an increased demand for water melons which led to a critical shortage of water melons and inflated prices on the Zambian market.

The Agenda Setting theory was developed by McCombs and Shaw (1972) who, after studying the 1968 US Presidential election, found a strong correlation between news and media coverage and opinions held by voters. Overall, this theory is all about the influence of media. To relate this to the corporate world, this study employed the VT4 theory which explained factors that influence social media adoption by organizations and how that helps with growth of SMEs in the clothing industry. In view of this, Njuka & Phiri (2021), assert that “reputation management creates a feedback platform for organization leadership to realize what their stakeholder’s perception about them is about. Using social media analysis can help the organization to realign its strategic approach with the expectations of the stakeholders”.

The VT4 framework can be applied to a variety of organizational forms and media but in this study, it was applied to social media and SMEs in the clothing industry. The VT4 framework/theory is made up of five content dimensions namely volume, tone, topics, ties and timing (VT4). According to Carroll and Deephouse (2014) volume refers to the sheer amount of stories or space dedicated to an organization. It is also known as media salience (Kiousis, 2004), media exposure (Wartick, 1992) or media visibility (Carroll, 2004). All these are concerned with amount of information or news about a particular organization, public awareness of the organization, which is more related to this study, and media content.

Kiousis (2004) explains that media salience has two dimensions namely, media attention which is measured mainly by the sheer volume of stories or space dedicated to topics and media prominence which emphasizes the relative importance of an object. Carroll & Huang-Horowitz (2013) divide media salience or attention into two, namely, an organizations relevant mention which refers to mere mention of an organization in the media and its relevant discussion which refers to mention of an organization in the media where something substantive is said about the organization be it a description of an organizational attribute, action or event.

Carroll and Deephouse (2014) explain tone as the level of support for an organization expressed in a news article, that is, the sentiment, favorability, valence or tenor. Tone can be ordered, slanted or mixed. Ordered tone refers to ordered continuum of negative (−1) to neutral (0) to positive (+1). When ordered tone is used, neutral content can contain both positive and negative content which demonstrates a degree of balance (Pollock & Rindova, 2003). Using slanted tone, neutral tone is conceived as the absence of positive and negative tone while mixed tone refers to the presence of both. Tone captures five different dimensions namely praise, satisfaction, inspiration, blame and hardships. This is pertinent to our study as organizations using social media will be able to interpret tone which is critical to an organizations’ strategy.

Topic refers to the substantive issues, actions or people involved with the organization that appear in the media (Carroll & Deephouse, 2014). For example, when an organization does something for the community or comes up with an innovation that helps solve a particular problem of a community, when a particular celebrity associates or recommends a particular organization or product of a particular organization. The main topic for organizations includes cognitive or substantive attributes connected to corporate reputations, corporate abilities, financial performance, management and leadership, products and services, marketing and corporate communications, treatment of employees and partners, corporate governance, environmental responsibility, innovation, to mention but a few (Einwiller, 2013).

These serve as the basis for media reputations and have been summarized into 5 main categories namely: products/services, descriptive information, strategy, external interactions and people (Wry, Deephous, & McNamera, 2006). There will always be antecedents and consequences for each topic about the organization.

Ties refer to linkages’ news media create between the focal business and another topic, that is between one organization and another such as a person, place, action, event or organization, market or product category. In other words, ties are all about topics organizations want to be associated with as there are some topics organizations want to be associated with and others they want to distance themselves or protect themselves against (Barnet & King, 2008). As such, organizations use the concept of ties to associate themselves to news values as a way of increasing their news coverage. For example, when there is a sports tournament such as the football world cup, grand prix or tennis, these events are news topics and organizations would love to associate themselves with such so that whenever there is something about the tournament in the media, the associated organizations can also be mentioned or shown, e.g., placing of drinks (beer, soft or energy drinks) or water on a table where an interview is taking place. This perfectly demonstrates ties.

Lastly, is timing, which is concerned with a temporal ordering of a series of objects with related content sequentially. Content can be ordered alphabetically, numerically, by order of importance or occurrence, ease of understanding or acceptance by the audience or desired effect among others. This study utilized ease of understanding and acceptance by the audience as well as desired effect when referring to timing as this is among the factors that influence social media use by SMEs.

The VT4 theory or framework was suitable in this study in that it helped explain the factors that influence social media use among SMEs, the role social media plays and how this influences an organizations growth since social media, unlike other media gives an instantaneous interaction and feedback between the organization and its stakeholders. As earlier stated, the use of the VT4 framework enabled SMEs to use social media analysis in realigning their strategic plans with the expectations of their stakeholders so as to make sure their organizations grew. Figure 1 above presents the VT4 theory/framework.

2.2. Empirical Literature Review

In this chapter, a literature review is presented which highlights empirical literature related to this study. It begins by highlighting empirical literature on social media adoption by SMEs before highlighting empirical literature on factors that affect social media adoption. It then looks at empirical literature on the influence of the VT4 on social media adoption and organizational growth. A study by Njuka and Phiri (2021) on factors influencing Social Media in Managing Corporate Reputation for a Christian Organization in Developing Countries Based on the VT4 Model found that there is a significant role played by social media in managing corporate reputation for Christian Organizations, however, the gap was in how impressions or perceptions can be strategically managed in order achieve a positive response to a given content published. In a study called Cutting-edge Technologies for Small Business and Innovation in the Covid-19 Global Health Pandemic, Apkan et al. (2020) established that the use of some technologies that were not considered essential by small businesses, such as virtual reality related technologies became very crucial to avoid a complete shutdown of the global economy. Therefore, many businesses of all sizes have since implemented technologies such as virtual teams, Zoom virtual meetings, synchronous remote learning, and other technologies and these technologies have become the survival strategy during the lockdown of communities. The gap in this study was that the study mainly on the cutting edge technology and excluded ordinary technology such as social media which most SMEs easily use.

In the same year 2020 when the Covid-19 pandemic broke out, Son & Niem (2020) also conducted research titled using Social Media to navigate changing Rural Markets, the Case of small community retail and service businesses. This study argued that social media is an innovative marketing tool to promote interactive, collaborative and personalized interaction with customers and stakeholders. The study also established that the use of social media enabled small businesses to attract new customers and foster commitment to the business.

In a study called “Social Media Implementation by SMEs: Overcoming the Challenges of Measurement” by Choi et al. (2014) it was discovered that lack of time, lack of human resources, lack of market information and lack of planning were the major challenges faced by SMEs. The measurement tools of social media effectiveness included Facebook reach, twitter reach, Youtube subscribers under which the following are included: Clicks, Likes, Shares, Comments, Retweets, Mentions, New Followers and New Fans. The gap in this study was that only one case was selected, the selection of more than one case could have improved the overall representativeness of the study.

Furthermore, in a study on of the impact of Covid-19 on Small Businesses’ Performance and Innovation by Harel (2021), it was found that the revenues of most small businesses in industrial sector were adversely affected by the pandemic. It was also noted that small businesses, most of whose revenues derive from subcontracting work to other businesses, business to business (B2B) and from long-term agreements were likely to cope better during periods of economic uncertainty. Businesses that are active in the international markets have succeeded in adapting that activity to the changing demands and various trade restrictions. The gap that this particular study had was that only one manager from each business participated in the study and the inclusion of many participants from each business would bring out more information that could greatly contribute to the knowledge on the topic.

Another study on the economic effects of the Covid-19 pandemic on Entrepreneurship and Small Businesses, by Beliski, Guenther, & Kritikos (2021) discovered that the Covid-19 Pandemic economically threatened small businesses globally. It was also found that the role of digital technology had significantly increased under Covid-19. Going on further, Engidaw (2022) in the study titled “Small businesses and their challenges during Covid-19 pandemic in developing countries: in the case of Ethiopia” found that doing business in the Covid-19 pandemic time is very challenging and it has a dangerous impact on small businesses, worker life as well as the country’ overall economy. The major gap of this research was that it solely focused on the challenges faced by SMEs due to the Covid-19 pandemic and how these challenges impact their operations. More research should be done on how SMEs can navigate these challenges posed by the pandemic and still be able to grow their businesses and be sustained.

In addition, another study on ICT adoption in small and medium Enterprises, an empirical evidence of service sectors in Bangladesh by Miraz & Habib (2016) found that, the usage of ICT applications for business purposes brings many advantages for its users in this business area. Secondly, they found that implementing ICT in the organization will be able to offer businesses a wide range of possibilities for improving their competitiveness. This study has some knowledge gaps in that it focused on the service sector only and therefore, a detailed study on adoption of ICT by other sectors other than the service sector will help bridge this knowledge gap.

Another study is Social Media adoption in SMEs impacted by Covid-19: the TOE Model in which Effendi et al. (2020) discovered that the SMEs affected by the Covid-19 pandemic crisis have a high awareness of social media and have a high intention to adopt social media as a way to market their products and also connect with customers. This study also found that the intention to adopt social media is significantly influenced by the technological context, and social media awareness. This was a study conducted at the peak of the Covid-19 pandemic, conducting longitudinal studies by analyzing the adoption of information technology in the post-Covid-19 era would bridge the knowledge gap. A study on SMEs’ readiness to adopt e-business more broadly, beyond social media is lacking.

Mooya & Phiri (2021) in the year 2021, also discussed factors hindering the adoption of E-Marketing among cable manufacturers in Zambia, Based on Technology Acceptance Model (TAM). In this study, it was discovered that age influenced perceived usefulness of E-marketing, frequency of internet use has influence on perceived ease of use of E-marketing and that the internet knowledge has an influence on perceived security of E-marketing. The knowledge gap in this study was that the research only identifies the factors that hinder adopting of E-marketing, a study of how the identified factors actually hinder the adopting would help more. Iluba & Phiri (2020) in a study conducted in the year 2020 which is titled the FinTech Evolution and its effect on Traditional Banking in Africa—A case of Zambia” It was established by this research that there is a significant relationship between relative advantage and adoption and also that there is a strong positive correlation of 0.450 between relative advantage and adoption. However, the use of one model limited the research results and so a revised model that shows factors affecting adoption of an innovation that might help banks is required to be used.

The other studied reviewed was on the impact of social media marketing for Indonesian SMEs sustainability: Lesson from Covid-19 pandemic conducted by Patma et al. (2021). The findings of this study were that adoption of internet/e-business technology can be explained by perceived usefulness, perceived ease of use and cost. Besides, it was also found that adoption of internet/e-business technology has a link between internet/e-business technology, social media marketing and SMEs sustainability. On the gap side, this study focused on the impact of social media marketing for SMEs, further research could be done to examine the impact of internet on SMEs general performance.

Among the many studies undertaken in 2020 having been the peak of the Covid-19 pandemic, another one was “The use of digital technologies by small and medium enterprises during the Covid-19: Implications for theory and practice” conducted by Papadopoulos, Baltas, & Balta (2020), the study observed that digital technologies (DT) has helped SMEs deal with the repercussions of interruptions due to extreme events such as Covid-19 pandemic. The study also revealed that the appropriate strategic adoption of DT can lead to enhanced competitiveness, productivity and performance. The knowledge gap in this study was that it focused on digital technologies at large and did not look at social media specifically.

Lastly, another research reviewed was the social media adoption and its impact on firm performance: the case of UAE. This is a research carried out way before the coming of the Covid-19 pandemic in the year 2018 by Ahmad et al. (2019) argued that social media adoption had no effect on SMEs’ performance. This study has major knowledge gaps because it did not examine links between social media adoption and firm strategy. It would be very insightful to know whether firms whose strategy influenced the adoption of social media applications saw stronger effects on business performance.

2.2.1. SMEs and the Internet (Social Media)

As earlier pointed out in the first chapter, the havoc caused by COVID-19 on businesses and SMEs in particular has forced businesses, especially SMEs, to resort to the use of ICT in their business. Before the pandemic struck, the use of ICT or social media by most SMEs was peripheral. This is due to the fact that most SMEs perceived the use of ICT or social media with skepticism due to what Gilbert, Lee-Kelley and Barton (2003) referred to as “technophobia”. Rosen & Maguire (1990) explain that technophobia simply refers to anxiety about current or future interactions with computers or computer-related technology.

SMEs have generally not been very enthusiastic in their involvement with electronic commerce, and in particular with Electronic Data Interchange (Tuunainen & Saarinen, 1997). This is because SMEs have traditionally implemented and used information technologies in their business as a reactive measure in response to requests by larger organizations who are customers and therefore provide the business imperative for them to become IT compatible (Poon & Swatman, 1995). The use of ICT by a few SMEs has not really been because of the opportunities ICT presents them or as part of their business strategy but rather to conform to the demands of larger companies they do business with (Tuunainen & Saarinen, 1997).

The internet presents SMEs with various opportunities such as efficient communication with customers regardless of geographical limitations and effective advertising and marketing campaigns. Other opportunities include access to valuable information, wide/global reach, marketing through content, building customer relationships and offering customer service, to mention but a few (Lawrence, 2002). With such opportunities, some SMEs have started utilizing ICT especially social media in their business particularly in their marketing strategy. According to Kaplan & Haenlein (2010), social media, which is part of the internet communication technology, refers to “a group of Internet-based applications that build on the ideological and technological foundations of Web 2.0, and that allow the creation and exchange of User Generated Content.”

These include, Facebook, Twitter, Whatsapp, Instagram, YouTube, LinkedIn, to mention but a few (Oji, Iwu, & Tengah, 2017). In business circles, social media provide organizations with an opportunity to improve several of their business activities such as relationships with trading partners, sharing information and managing communications and logistics across supply chains (Humphrey, Mansell, Pare, & Schmitz, 2003). This is because so because, using the VT4 model, social media analysis can influence social media use among SMEs and help them realign their strategic plans with the expectations of their stakeholders.

However, while the significance of social media in business is being acknowledged, the decision to use this new promotional technology by SMEs is not automatic (Pentina, Koh, & Le, 2012). This is because, as Abou-Shouk, Megicks and Lim (2013) argued, SMEs, particularly from developing countries, are slow adopters and users of social media. A study by Kyakulumbye & Pather (2022) established that there is low adoption of social media amongst SMEs in Africa, particularly in Uganda due to demographic antecedents and beliefs and attitudes of users.

This is in line with a study by Mavimbela & Dube (2016) which established that SMEs in South Africa (SA) have been slow to adopt internet technologies. The slow adoption is due to, among others, lack of infrastructure and skills, lack of cyber laws, which will provide trust, slow internet speed and high costs of connection. Kabanda & Brown (2017) too in their study of e-commerce in the context of Tanzanian SMEs found that there is potential for SMEs employing ICT in their business but there is low level of e-commerce adoption due to lack of awareness, resources, readiness, support, infrastructure, and social factors. The situation is similar in Indonesia where many SMEs are not yet familiar with using digital marketing due to lack of human resources with adequate technical skills and the perceived high cost of using social media (Sugandini, Feriyanto, Muafi, Hadioetomo, & Darpito, 2018).

The situation seems to be taking a different turn since the advent of the COVID-19 pandemic. Digital technologies were becoming increasingly influential to businesses before the pandemic hit and during lockdowns their influence accelerated as whole parts of the economy shifted onto digital platforms (Van Daalen, 2020). Teleworking, remote learning, teleconferencing, online health services, e-commerce and digital payments all kept the world going during the global lockdown in the first half of 2020. Businesses that were already operating online before the pandemic reinforced their ability to manage the surge in demand for goods, and brick and mortar shops shifted resources to e-commerce as consumers shifted to online shopping (WTO, 2020).

Since the pandemic forced communities into a shutdown, SMEs have resorted to use of technologies that were not considered essential before the pandemic to avoid a complete shutdown. It is these technologies that have become the survival strategy for SMEs during the pandemic (Ting et al., 2020). Effendi et al. (2020) in their research on social media adoption in SMEs impacted by COVID-19 established that social media is increasingly being adopted by SMEs for purposes of marketing. The use of outstanding social media helps SMEs under challenging times as it enables them to remain in direct contact with their customers. Digital media has become the most effective and efficient choice for communicating with communities and also customers. Digitalization is the answer to the quarantine policy brought about by COVID-19 so that SMEs can still market their products because e-marketing makes it easy for SMEs to provide accurate, attractive, and useful information to their customers (Effendi et al., 2020).

Among the used social media technologies among some SMEs are Facebook, Twitter, YouTube, Instagram, Whatsapp, Linkedin to mention but a few (Ahmad et al., 2019). Studies on the use of Facebook among SMEs found that few SMEs use Facebook for various organizational objectives such as marketing, communication, sales, advertising, innovation, problem resolution, customer service, human resources, information technology, driving cultural change (Bhanot, 2012; Beloff & Pandya, 2010; Handayani & Lisdianingrum, 2012; Meske & Stieglitz, 2013). The results of a study by Moghavvemi (2015) showed that 61.4 percent of SMEs do not use any other social media tool other than Facebook, while 38.6 percent of SMEs reported that they do use other social media tools such as Twitter, Instagram and Blogs, etc. Ahmad et al. (2019) established that the most used social media platforms among SMEs were Facebook followed by Instagram then Whatsapp. Other used social media platforms though to a low extent were Linkedin, Twitter and YouTube.

2.2.2. Factors that Affect Adoption of Social Media by SMEs

The use of social media by SMEs has been influenced and affected by various factors. Among them are firm innovativeness, age and geographic location which, in the study by Wamba and Carter (2013) had a significant impact on Twitter adoption by SMEs. Others indicated that SMEs adopt the use of social media if these applications provide a significant amount of relevant and high-quality up-to-date content (Zeiller & Schauer, 2011). Compatibility, cost effectiveness, trust and interactivity are among other factors that influence social media adoption among SMEs (El-Gohary, 2012; Wang, Wang, & Yang, 2010; Chong & Chan, 2012; Chai et al., 2011; Lee & Kozar, 2012).

Complexity too affects SMEs’ adoption of Information technology under which social media falls. Chong and Olesen (2017) assert that complexity is the extent to which new technological innovations are difficult to use. They established that when technological innovation seems difficult to use, it makes it difficult for SMEs to adopt such technology. Zhai (2010), Wu and Chuang (2009) too revealed that the complexity of technology influences e-commerce adoption by SMEs. El-Gohary (2012) also concluded that complexity influences social media marketing adoption decisions. Porter (2012) shows that individuals with confidence in excellent performance abilities will easily use new technology based on the experience they have. The perception of the complexity of the use of information technology is usually associated with the rejection of users on social websites that are antecedents of e-commerce adoption (Ali et al., 2015).

Related to Complexity is perceived ease of use. Tahar, Riyadh, Sofyani, & Purnomo (2020) revealed that perceived ease of use positively affects attitudes and behavior of e-Filing adoption in Indonesia. This is supported by Gekombe, Tumsifu, & Jani (2019) who in their study “social media use among SMEs in the fashion industry” established that there is a positive relationship between perceived ease of use and social media usage among SMEs. This is due to the fact that when a user/users believes a particular systems or technology can be used free of effort and that they can easily navigate the system, then they are likely to use it and are likely to easily accept it.

Therefore, empirical findings confirm that perceived ease of use is a key factor in determining a users’ intention to accept and adopt ICT (Venkatesh & Davis, 2000). Thus, if social media is perceived easy to use, it is more likely to be accepted by users (Davis, 1989).

Social media awareness is another factor that influences SMEs adoption of social media in their business. It is a prerequisite for further use of social media (Effendi et al., 2020). Alencar (2018) established that there was meaningful relationship between social media awareness and social media adoption for informal scientific communication. Bugshan (2019) too asserted that social media awareness has become a means of diffusion and improvement of information. Praveena and Thomas (2014), Shen (2015) agreed that awareness is an essential factor influencing the intention to continue to adopt web technology. Furthermore, perceived relative advantage or benefit too affect social media adoption or diffusion by SMEs. Nedbal & Stieninger (2014) and Oliveira et al. (2014) argue that organizations will adopt technological innovation if it can bring benefits to the organization both in organizational performance and economically.

Kyakulumbye & Pather’s (2022) study identified four pre-use factors which significantly influence decisions to adopt and use ICT among SMEs. These include benefit expectation, ICT learnability, User-confidence, and User-friendliness.

2.2.3. Influence of Social Media on the Growth of SMEs

Though adoption of social media among SMEs is low, the use of social media by SMEs plays a major role in the growth of SMEs. Previous studies have investigated usage of social media by organizations and the impact that this has had to contribute to the growth of the organizations. Rodriguez, Ajjan, & Peterson (2014) revealed that social media technologies like Facebook positively impact the customer-orientated processes of organizations which in turn impact their sales performance. These processes include understanding customers, adapting to customers changing needs, measuring customer satisfaction, and aligning customer needs with sales and marketing activities. Social media use brings several benefits to an organization such as improved sales and marketing alignment, access to decision-makers, shorter sales cycles, and better collaboration with customers. Moghavvemi (2015) too established that SMEs used social media, particularly Facebook, to enhance their customers’ relationship.

This is supported by a study by Gekombe, Tumsifu, & Jani (2019) which established that the use of social media has improved business competitiveness and provided SMEs with an opportunity to compete favorably and experience growth via increased sales, building better, effective and interactive relationships with clients and prospects. Social media also exposes SMEs and increases their visibility which in turn allows their products to be seen by prospects. Past research suggests that accessible content on the social media platforms increases the potential of making a sale which in turn translates to business growth (Wang, 2017). The use of social media by organizations has presented a wide range of possibilities for organizations to improve their competitiveness as it provided mechanisms for getting access to new market opportunities and specialized information services. Furthermore, through the use of social media, organizations are able to receive immediate feedback which allows them to react quickly to changing client demands and recognize new market niches (Miraz & Habib, 2016).

The study by Moghavvemi (2015) revealed that Facebook usage has a strong positive impact on financial performance as well as non-financial performance of SMEs in that it enables SMEs to increase sales transactions, sales volume, sales enquiries, and number of customers. It also reduces cost of advertising, enhances customer relations and information accessibility as it allows customers direct access to information for which they would previously not have had access to. Furthermore, via use of social media (Facebook), organizations are also able to get information about their customer tastes or wants and their competitors’ activities, tactics and brand sentiments.

The study findings of Gekombe et al. (2019) too, showed that there is a significant relationship between social media use and growth of SMEs because through social media, SMEs can build better, effective and interactive relationships with customers and prospects. This increases the chances for making repeated sales and online visibility which exposes SMEs to prospects. Previous research suggests that accessible content on the social media platforms increases the potential of making a sale which in turn translates to business growth (Wang, 2017).

Patma, Wardana, Wibowo, Narmanditya, & Akbarina (2021) revealed that social media use is a valuable tool for marketing purposes as it increases business productivity, helps with better query management, and promotes customer satisfaction. As such, social media technologies positively impact the social capital of an organization and therefore its performance (Ferrer et al., 2013). This is consistent with Wong (2012) who found that Facebook usage has a positive impact on SME business and is supported by findings by Kwok and Yu (2013) who found that sales can be increased with Facebook usage. In Kenya a study by Waithaka, Muturi and Nyabuto (2014) found that Facebook and Twitter impacted small businesses by improving communication between owners/managers and customers.

Similarly, Kimani (2014) revealed that Facebook and Twitter were the most used social media platforms and they provided a perfect way to share information among different social classes, created product awareness, and more active communication. Khan and Karodia (2013), in a related study in South Africa, established that 51% of SMEs agreed that Facebook was an effective channel for marketing, 70% agreed that the platform was useful for public relations, 62% said it was useful for marketing while 43% agreed that it was useful for customer relations. All these highlight the role played by social media in the growth strategies of SMEs.

3. Research Methodology

3.1. Research Design

This study employed a quantitative research approach defined by Basias & Pollalis (2018) as an approach used to test objective theories by examining two or more variables so as to find out if any relationship exists. This study aimed at establishing whether a relationship exists between the VT4 and social media adoption and SME growth. The most suitable research design for this study was the causal research design as the study sought to establish if a cause-and-effect relationship existed between the independent and dependent variables which are the VT4 and social media adoption and SMEs growth.

3.2. Population

According to Kombo and Tromp (2006) target population refers to a group of people, objects or items under study from where a sample is taken for measurement. The target sector of this study was SMEs in the clothing industry in Zambia, specifically those in Lusaka District. These were the target population of the study. From the Patents and Companies Registration Agency (PACRA), there are 645 registered SMEs in the clothing sector in Lusaka District at the time of the research and that was the population of this study. The employees in these clothing businesses were used at the providers of the needed information. They had relevant information for this study as they were more knowledgeable about the influence of the VT4 in social media adoption and which social media platforms SMEs use and the factors that influenced the adoption of social media as well as whether the adoption of social media played any part in the growth of SMEs.

3.3. Sample Size

This study did not use a census and thus needed to pick a small group from the target population to be studied. It is this small group that Morgan (2008) refers to as the sample size. This study picked a sample of 240 staff from a population of 645. The sample size was arrived at using Moazzam’ (2014) formula and the Krejcie and Morgan (1970) for determining sample size given a population size. The first part presents the determination of the sample size using the Moazzam (2014) formula as follows:

$n=N\ast X/\left(X+N–1\right)$, (1)

where,

$\begin{array}{l}X=Z_{\alpha /2}^2\ast p\ast \left(1-p\right)/{\text{MOE}}^2\text{or}\\ X=z^{2}pq/d^2\\ N=645\end{array}$ (2)

n: the desired sample size

z: the standard normal deviate usually set at 1.96 (which corresponds to the 95% confidence level)

p: the proportion in the target population to have a specific characteristic. If no estimate available set at 50% (or 0.50)

q: 1 − p

d: absolute precision or accuracy, normally set at 0.05.

The sample size in this study was.

$X={\left(1.96\right)}^2\left(0.5\right)\left(0.5\right)/{\left(0.05\right)}^2=384$

$n=645\left(384\right)/\left(384+645-1\right)=247680/1028=240$

Therefore, a sample of 240 was the target from SMEs. This sample will be representative of the target population.

The conclusion of the Moazzam (2014) formula was verified using the Krejcie and Morgan (1970) sample determination table to establish accurateness of the sample size arrived at, as presented in Figure 2.

As can be seen from the from Figure 2, the estimated sample size for a population size of 650 is about 242, which validates the choice of a 240 sample size in this study.

3.4. Sampling Technique

The sampling technique used to select study units was probability sampling technique and particularly simple random sampling. There are two broad sampling techniques namely probability and non-probability sampling techniques (Elfil & Negida, 2017). Probability sampling refers to a mechanism by which from the population of the study, a smaller group called a sample is chosen (ibid). This is done in such a way that each and every unit in the population has, not necessarily an equal opportunity, but also a positive probability of being selected. This allows each and every member of the population to have an equal chance to be part of the study.

Figure 2. Krejcie and Morgan (1970) sample determination table. Source: Krejcie and Morgan (1970).

3.5. Data Collection Methods

This study made use of data obtained from both primary and secondary sources. The primary source of data was direct from the respondents obtained by the researcher via use of questionnaires specifically for this study. The questionnaire used was semi-structured, that is, it consisted of closed as well as open-ended questions. The use of both open and closed-ended questions enabled respondents not to drift from the research topic but to remain focused on the topic. It also enabled respondents not to be confined in the information they give but to be able to give information that might have been left out by the questionnaire. The questionnaire was distributed to the respondents directly with the approval of managers. A period of four days was given to the respondents to complete answering the questionnaire and after that, the questionnaires were collected back by the researcher.

The secondary data was obtained from various sources including journals, research articles, theses, books and the Zambian Patents and Company Registration Agency (PACRA) database of registered small and medium entrepreneurs. Journals were mainly on topics and literature related to the aim and areas of interest of this study.

3.6. Data Analysis

The data collected by questionnaires was raw and thus needed to be analyzed in order to make meaning out of it because primary data in its raw form does not make much sense. To carry out the data analysis, collected data was first coded, entered into SPSS and then analyzed using Statistical Package for Social Sciences (SPSS) to determine the correlation between the VT4 social media adoption and SME growth. Data was presented using tables, pie or bar charts using descriptive statistics such as frequencies and percentages. Inferential statistics was also used including chi-square, cross-tabulation and correlation. This enabled the study to investigate the effects of predictor variables on an outcome variable and to measure the confidence levels and test the hypotheses.

4. Results and Discussion

The objectives of the study were to find out factors that affect adoption of social media platforms by SMEs and to develop a framework for improving the level of adoption of social media in order to improve on SMEs business growth.

To understand the current social medial adoption, respondents were asked whether their organizations use any social media platforms in their business. The results show that 60.96% majority use social media whereas 39.04% stated otherwise. Figure 3 presents these results.

In addition, respondents were asked to state whether COVID-19 prompted their adoption of Social media. According to the results, as presented in Table 1 below, majority of respondents agreed that COVID-19 prompted them to adopt the use of social media in their business as shown by 58.2% and 30.8% majority who strongly agreed and agreed respectively that they used social media more after the coming of COVID-19.

Figure 3. Use of social media among small & medium enterprises.

Table 1. Whether COVID-19 in any way prompted their organizations to use social media.

Source: Researcher’s Computations using SPSS from Sample Data.

Model Results

This section outlines sample data results tested on the assumptions of the VT4 model presented in Figure 1.

From the sample data, it is seen that the first objective of the study was met by running Chi-Square goodness of fit tests and Pearson’s correction. The idea was to establish factors that influence the adoption of social media using the VT4 model. Table 2 presents these results.

One of the factors established to influence social media adoption by SMEs was perceived usefulness/benefit. This is due to the fact that SMEs’ main aim of adopting social media is to gain some benefit in terms of marketing or promotion, visibility and importantly making sales. This is supported by studies Nedbal & Stieninger (2014), Oliveira et al. (2014) and Kyakulumbye & Pather’s (2022) who argued that organizations will adopt technological innovation if they can bring benefits to the organization in terms of organizational performance and economically. Another factor that influenced SME adoption of social media was perceived ease of use. This is due to the fact that SMEs want to use user friendly social media that will not waste much of their time trying to learn and understand how a particular social media platform works. Therefore, they go for social media platforms that are perceived to be easy to use.

This finding is supported by Tahar et al. (2020) whose study revealed that perceived ease of use positively affects attitudes and behavior of e-Filing adoption in Indonesia. It is also consistent with Gekombe, Tumsifu, & Jani (2019) who in their study “social media use among SMEs in the fashion industry” established that there is a positive relationship between perceived ease of use and social media usage among SMEs. This is due to the fact that when a user(s) believes a particular systems or technology can be used free of effort and that they can easily navigate the system, then they are likely to use it and are likely to easily accept it.

Table 2. Impact of VT4 on SME growth.

The second objective of the study was to develop a framework that can help improve level of adoption of social media in order to improve SMEs business growth. This objective was met by running tests to find out if there is any relationship between the VT4 and social media adoption and SME growth. Results show that the VT4 variables namely volume, tone, ties, topic and timing have a statistical correlation with social media adoption and SME growth. This is due to the fact that the VT4 play a key role in SMEs adoption of social media and the adoption of social media thereby enhance SME growth. This agrees with a study by Njuka & Phiri (2021) which revealed that the VT4 and social media adoption and organizational reputation management have significant statistical association.

These findings are also in line with a study by Gekombe, Tumsifu, & Jani (2019) which established that the use of social media has improved business competitiveness and provided SMEs with an opportunity to compete favourably and experience growth via increased sales, building better, effective and interactive relationships with clients and prospects. Wang (2017) too supports this by establishing that social media exposes SMEs and increases their visibility which in turn allows their products to be seen by prospective customers as accessible content on social media platforms increases the potential of making a sale which in turn translates to business growth.

It can be seen therefore, that there is significant relationship between VT4 and social media adoption and business growth as discovered by Gekombe et al. (2019) whose study showed that there is a significant relationship between social media which facilitates content volume, tone, topics, ties and timing and growth of SMEs because through social media, SMEs can build better, effective and interactive relationships with customers and prospects.

This study has therefore shown that SMEs in the clothing industry in Zambia have adopted social media and that this adoption is more for particular social media platforms than others. The study has also revealed that the VT4 have an influence on social media adoption by SMEs and on SME growth. Therefore, SMEs should use the VT4 model in making decisions on social media adoption in their business so as to maximize on the benefits of social media adoption.

5. Conclusion

This study sought to establish social media adoption among SMEs in the clothing industry. A quantitative research methodology was used to collect data for the study and as such questionnaires were used for this purpose. Based on the objectives of the study, it has been established that, SMEs in the clothing industry in Zambia adopt social media in their business such as Facebook, WhatsApp, Twitter, to mention but a few. That social media adoption by SMEs is influenced by various factors among them perceived usefulness or benefit and ease of use.

Furthermore, the study has also established that the VT4, as expected from Figure 1 plays a key role in influencing social media’s contribution to organizational growth. As a result of the influence of the VT4, SMEs adopt social media in their business. This adoption of social media by SMEs made it possible for SMEs to be more visible and to communicate more with clients. It also made it possible for SMEs to communicate their products and be able to market their products using prominent people. Not only, SMEs were also able to create ties and be able to get feedback from clients. This helped in the growth of SMEs as they were able to penetrate new markets and develop new products.

Figure 4. Proposed model for social media adoption for SME businesses.

6. Recommendations

With social media becoming an important component to any business especially in this COVID-19 era, SMEs will do well to make it mandatory to have social media presence via any two or three prominent social media platforms such as Facebook, WhatsApp or Twitter and to formulate a deliberate policy that will offer training to staff so that they come to a better understanding of the VT4 model so as to enable them utilize social media optimally. Another recommendation is for the government to put up deliberate policies to make electronic gadgets used for social media such as smart phones affordable so that SMEs can afford them and be able to use them for social media activities for their business. This forms the basis for the proposed model presented in Figure 4.

Future Works

The future of every organization is online or electronic, thus there is need for future research to focus on organizations going electronic in general and how this can enhance organizational performance.

Acknowledgements

The author acknowledges the support of study participants drawn from the clothing sector in Lusaka Zambia. The author would also like to acknowledge the support of faculty at the Graduation School of Business her supervisor Dr Jackson Phiri.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Abou-Shouk, M., Megicks, P., & Lim, W. M. (2013). Perceived Benefits and E-Commerce Adoption by SME Travel Agents in Developing Countries Evidence from Egypt. Journal of Hospitality and Tourism Research, 37, 490-515. https://doi.org/10.1177/1096348012442544
[2]	Ahmad, S. Z., Bakar, A. R. A., & Ahmad, N. (2019). Social Media Adoption and Its Impact on Firm Performance: The Case of the UAE. International Journal of Entrepreneurial Behavior & Research, 25, 84-111. https://doi.org/10.1108/IJEBR-08-2017-0299
[3]	Alencar, A. (2018). Refugee Integration and Social Media: A Local and Experiential Perspective. Information Communication and Society, 21, 1588-1603. https://doi.org/10.1080/1369118X.2017.1340500
[4]	Ali, N. M, Mat, N. K., & Ali, N. M. (2015). The Conceptual Framework for E-Commerce Adoption Model. South African Journal of Information Management, 5, 148-154.
[5]	Apkan, I. J., Soopramanien, D., & Kwak, D. A. (2020). Cutting-Edge Technologies for Small Business and Innovation in the Era of COVID-19 Global Health Pandemic. Journal of Business & Entrepreneurship, 33, 607-617. https://doi.org/10.1080/08276331.2020.1799294
[6]	Barnet, M. L., & King, A. A. (2008). Good Fences Make Good Neighbors: A Longitudinal Analysis of an Industry Self-Regulatory Institution. Academy of Management Journal, 51, 1150-1170. https://doi.org/10.5465/amj.2008.35732609
[7]	Basias, N., & Pollalis, Y. (2018). Quantitative and Qualitative Research in Business & Technology: Justifying a Suitable Research Methodology. Review of Integrative Business and Economics Research, 7, 91-105.
[8]	Beliski, M., Guenther, C., & Kritikos, A. S. (2021). Economic Effects of the COVID-19 Pandemic on Entrepreneurship and Small Businesses. IZA Discussion Paper No. 14630. https://doi.org/10.2139/ssrn.3905065
[9]	Beloff, N., & Pandya, P. (2010). Advertising Models on Social Networks for SMEs—An Advertising Methodology. In 2010 International Conference on Internet Technology and Applications (pp. 1-6). IEEE. http://ieeexplore.ieee.org/ https://doi.org/10.1109/ITAPP.2010.5566329
[10]	Bhanot, S. (2012). Use of Social Media by Companies to Reach Their Customer. SIES Journal of Management, 8, 47-55.
[11]	Bugshan, L. (2019). The Role of Social Media in Raising Special Needs Awareness among Saudi People. Master’s Thesis, Arkansas State University. https://www.proquest.com/openview/67783d8e70a1d2762fcd3f8fab61ebc4/1?pq-origsite=gscholar&cbl=18750&diss=y
[12]	Carroll, C. E. (2004). How Mass Media Influence Perceptions of Corporate Reputation: Exploring Agenda-Setting Effects within Business News Coverage. Doctoral Dissertation, University of Texas at Austin.
[13]	Carroll, C. E., & Deephous, D. L. (2014). The Foundations of a Theory Explaining Organizational News: The VT4 Framework of Organizational News Content and Five Levels of Content Production. In Organizing in New Media Landscape. https://www.academia.edu/9677259/The_Foundations_of_a_Theory_Explaining_Organizational_News_The_VT4_Framework_of_Organizational_News_Content_and_Five_Levels_of_Content_Production
[14]	Carroll, C. E., & Huang-Horowitz, N. C. L. (2013). The Organizational Society Meets the Civil Society: The Media Salience of Corporations and Their Connection to Political Issues in the Public Sphere. Working Paper.
[15]	Chai, S., Das, S., & Rao, H. R. (2011). Factors Affecting Bloggers’ Knowledge Sharing: An Investigation across Gender. Journal of Management Information Systems, 28, 309-342. https://doi.org/10.2753/MIS0742-1222280309
[16]	Choi, G., Bolan, P., Hutchinson, K., & Mitchell, R. (2014). Social Media Implementation by SMEs: Overcoming the Challenges of Measurement. In BAM2014 Conference Proceedings. British Academy of Management
[17]	Chong, A. Y. L., & Chan, F. T. (2012). Structural Equation Modeling for Multi-Stage Analysis on Radio Frequency Identification (RFID) Diffusion in the Health Care Industry. Expert Systems with Applications, 39, 8645-8654. https://doi.org/10.1016/j.eswa.2012.01.201
[18]	Chong, J. L. L., & Olesen, K. (2017). A Technology-Organization Environment Perspective on Eco-Effectiveness: A Meta-Analysis. Australasian Journal of Information Systems, 21, 1-26. https://doi.org/10.3127/ajis.v21i0.1441
[19]	Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use and User Acceptance of Information Technology. MIS Quarterly, 13, 319-340. https://doi.org/10.2307/249008
[20]	Dua, A., Ellingrud, K., Mahajan, D., & Silberg, J. (2020). Which Small Businesses Are Most Vulnerable to COVID-19 and When. McKinsey & Company.
[21]	Effendi, M. I., Sugandini, D., & Istanto, Y. (2020). Social Media Adoption in SMEs Impacted by COVID-19: The TOE Model. Journal of Asian Finance, Economics and Business, 7, 915-925. https://doi.org/10.13106/jafeb.2020.vol7.no11.915
[22]	Einwiller, S. (2013). Corporate Attributes and Associations. In C. E. Carroll (Ed.), The Handbook of Communication and Corporate Reputation (pp. 291-305). Blackwell Publishing Ltd. https://doi.org/10.1002/9781118335529.ch25
[23]	Elfil, M., & Negida, M (2017). Sampling Methods in Clinical Research. An Educational Review. Emergency, 5, e52. https://www.researchgate.net/publication/311535854_Sampling_Methods_in_Clinical_Research_an_Educational_Review
[24]	El-Gohary, H. (2012). Factors Affecting E-Marketing Adoption and Implementation in Tourism Firms: An Empirical Investigation of Egyptian Small Tourism Organizations. Tourism Management, 33, 1256-1269. https://doi.org/10.1016/j.tourman.2011.10.013
[25]	Engidaw, A. E. (2022). Small Businesses and Their Challenges during COVID-19 Pandemic in Developing Countries: In the Case of Ethiopia. Journal of Innovation and Entrepreneurship, 11, Article No. 1. https://doi.org/10.1186/s13731-021-00191-3
[26]	Fairlie, R., & Fossen, F. M. (2022). The Early Impacts of the COVID-19 Pandemic on Business Sales. Small Business Economics, 58, 1853-1864. https://doi.org/10.1007/s11187-021-00479-4
[27]	Ferrer, E., Bousono, C., Jorge, J., Lora, L., Miranda, E., & Natalizio, N. (2013). Enriching Social Capital and Improving Organizational Performance in the Age of Social Networking. International Journal of Information, Business and Management, 5, 94-109.
[28]	Gekombe, C., Tumsifu, E., & Jani, D. (2019). Social Media Use among Small and Medium Entreprises: A Case of Fashion Industry Growth. University of Dar es Salaam Library Journal, 14, 3-18.
[29]	Gilbert, D., Lee-Kelley, L., & Barton, M. (2003). Technophobia, Gender Influence and Consumer Decision-Making for Technology-Related Products. European Journal of Innovation Management, 6, 253-263. https://doi.org/10.1108/14601060310500968
[30]	Handayani, P. W., & Lisdianingrum, W. (2012). Impact Analysis on Free Online Marketing Using Social Network Facebook: Case Study SMEs in Indonesia. Institute of Electrical and Electronics Engineers.
[31]	Harel, R. (2021). The Impact of COVID-19 on Small Businesses’ Performance and Innovation. Global Business Review. https://journals.sagepub.com/doi/full/10.1177/09721509211039145 https://doi.org/10.1177/09721509211039145
[32]	Humphrey, J., Mansell, R., Paré, D., & Schmitz, H. (2003). Reality of E-Commerce with Developing Countries. Technical Report, Department for International Development. http://eprints.lse.ac.uk/3710/
[33]	Iluba, E., & Phiri, J. (2020). The FinTech Evolution and Its Effect on Traditional Banking in Africa—A Case of Zambia. Open Journal of Business and Management, 9, 838-850. https://doi.org/10.4236/ojbm.2021.92043
[34]	Kabanda, S., & Brown, I. (2017). Interrogating the Effect of Environmental Factors on E-Commerce Institutionalization in Tanzania: A Test and Validation of Small and Medium Enterprise Claims. Information Technology for Development, 23, 59-85. https://doi.org/10.1080/02681102.2016.1263593
[35]	Kandola, A. (2020). Corona Virus Cause: Origin and How It Spreads. Medical News Today. https://www.medicalnewstoday.com/articles/coronavirus-causes
[36]	Kaplan, A. M., & Haenlein, M. (2010). Users of the World, Unite! The Challenges and Opportunities of Social Media. Business Horizons, 53, 59-68. https://doi.org/10.1016/j.bushor.2009.09.003
[37]	Khan, S., & Karodia, A. M. (2013). The Effectiveness of Using Social Media Networking Technology for Marketing in South Africa. Singapore Journal of Business Economics and Management Studies, 2, 10-17. https://doi.org/10.12816/0003857
[38]	Kimani, W. R. (2014). Effect of Social Media on the Growth of Small Businesses in Kenya: A Case Study of Go Places Kenya. Unpublished Masters’ Thesis, University of Nairobi.
[39]	Kiousis, S. (2004). Explicating Media Salience: A Factor Analysis of New York Times Issue Coverage during the 2000 US Presidential Election. Journal of Communication, 54, 71-87. https://doi.org/10.1111/j.1460-2466.2004.tb02614.x
[40]	Kombo, D. K., & Tromp, D. L. A. (2006). Proposal and Thesis Writing. Paulines Publications Africa.
[41]	Krejcie, R. V., & Morgan, W. D. (1970). Determining Sample Size for Research Activities. Educational and Psychological Measurement, 30, 607-610. https://home.kku.ac.th/sompong/guest_speaker/KrejcieandMorgan_article.pdf
[42]	Kwok, L, & Yu, B. (2013). Spreading Social Media Messages on Facebook an Analysis of Restaurant Business-to-Consumer Communications, Cornell Hospitality Quarterly, 54, 84-94. https://doi.org/10.1177/1938965512458360
[43]	Kyakulumbye, S., & Pather, S. (2022). Understanding ICT Adoption amongst SMEs in Uganda: Towards a Participatory Design Model to Enhance Technology Diffusion. African Journal of Science, Technology, Innovation and Development, 14, 49-60. https://doi.org/10.1080/20421338.2020.1802843
[44]	Lawrence, E. J. (2002). The Use of the Internet in Small to Medium-Sized Enterprises. Doctoral Thesis. University of Salford.
[45]	Lee, Y, & Kozar, K. (2012). Understanding of Website Usability: Specifying and Measuring Constructs and Their Relationships. Decision Support Systems, 52, 450-463. https://doi.org/10.1016/j.dss.2011.10.004
[46]	Mavimbela, R., & Dube, E. (2016). Can an Internet Adoption Framework Be Developed for SMEs in South Africa. Journal of Entrepreneurship and Innovation in Emerging Economies, 2, 120-135. https://doi.org/10.1177/2393957516647250
[47]	McCombs, M., & Shaw, D. (1972). The Agenda-Setting Function of Mass Media. The Public Opinion Quarterly, 36, 176-187. https://www.jstor.org/stable/2747787?seq=1 https://doi.org/10.1086/267990
[48]	Meske, C, & Stieglitz, S. (2013). Adoption and Use of Social Media in Small and Medium-Sized Enterprises. In F. Harmsen, & H. Proper (Eds.), Practice-Driven Research on Enterprise Transformation (pp. 61-75). Springer. https://doi.org/10.1007/978-3-642-38774-6_5
[49]	Miraz, H. M., & Habib, M. (2016). ICT Adoption in Small and Medium Enterprises: An Empirical Evidence of Service Sectors in Bangladesh. Journal of Economics, Business and Management, 4, 482-485.
[50]	Moazzam, A. (2014). Sampling and Sample Size Estimations. WHO.
[51]	Moghavvemi, S. (2015). Factors Influencing the Use of Social Media by SMEs and Its Performance Outcomes. Industrial Management & Data Systems, 115, 570-588. https://doi.org/10.1108/IMDS-07-2014-0205
[52]	Mooya, N., & Phiri, J. (2021). Factors Hindering the Adoption of E-Marketing among Cable Manufacturers in Zambia, Based on Technology Acceptance Model (TAM). Technology and Investment, 12, 51-65. https://doi.org/10.4236/ti.2021.122004
[53]	Morgan, D, L. (2008). Sampling. In L. M. Given (Ed.), The SAGE Encyclopedia of Qualitative Research Methods (Vol. 1&2). Sage Publications.
[54]	Nedbal, D., & Stieninger, M. (2014). Exploring the Economic Value of a Cloud Computting Solution and Its Contribution to Green IT. International Journal of Business Process Integration and Management, 7, 62-72. https://doi.org/10.1504/IJBPIM.2014.060605
[55]	Njuka, D. A., & Phiri, J. (2021). Factors Influencing Social Media in Managing Corporate Reputation for a Christian Organization in Developing Countries Based on the VT4 Model. Technology and Investment, 12, 66-81. https://doi.org/10.4236/ti.2021.122005
[56]	OECD (2020). Coronavirus (COVID-19). SME Policy Responses. https://www.oecd.org/coronavirus/policy-responses/coronavirus-covid-19-sme-policy-responses-04440101/
[57]	Oji, O. N. E., Iwu, P. G., & Tengeh, R. K. (2017). Social Media Adoption Challenges of Small Businesses: The Case of Restaurants in the Cape Metropole, South Africa. African Journal of Hospitality, Tourism and Leisure, 6, 1-11.
[58]	Oliveira, T., Thomas, M., & Espadanal, M. (2014). Assessing the Determinants of Cloud Computing Adoption: An Analysis of the Manufacturing and Services Sectors. Information and Management, 51, 497-510. https://doi.org/10.1016/j.im.2014.03.006
[59]	Papadopoulos, T., Baltas, K. N., & Balta, M. (2020). The Use of Digital Technologies by Small Medium Enterprises during COVID-19: Implications for Theory and Practice. International Journal of Information Management, 55, Article ID: 102192. https://doi.org/10.1016/j.ijinfomgt.2020.102192
[60]	Patma, S. T., Wardana, L. W., Wibowo, A., Narmaditya, B. D., & Akbarina, F. (2021). The Impact of Social Media Marketing for Indonesian SMEs Sustainability: Lesson from Covid-19 Pandemic. Cogent Business and Management, 8, Article ID: 1953679. https://doi.org/10.1080/23311975.2021.1953679
[61]	Pentina, I., Koh, A. C., & Le, T. T. (2012). Adoption of Social Networks Marketing by SMEs: Exploring the Role of Social Influences and Experience in Technology Acceptance. International Journal of Internet Marketing and Advertising, 7, 65-82. https://doi.org/10.1504/IJIMA.2012.044959
[62]	Pollock, T. G., & Rindova, V. P. (2003). Media Legitimation Effects in the Market for Initial Public Offerings. Academy of Management Journal, 46, 631-642. https://doi.org/10.2307/30040654
[63]	Poon, S., & Swatman, P. M. C. (1995). The Internet for Small Businesses: An Enabling Infrastructure for Competitiveness. In K. Chon (Ed.), Proceedings of the Fifth Internet Society Conference (pp. 221-231).
[64]	Porter, G. (2012). Mobile Phones, Livelihoods, and the Poor in Sub-Saharan Africa: Review and Prospect. Geography Compass, 6, 241-259. https://doi.org/10.1111/j.1749-8198.2012.00484.x
[65]	Praveena, K., & Thomas, S. (2014). Continuance Intention to Use Facebook: A Study of Perceived Enjoyment and TAM. International Journal of Industrial Engineering and Management, 4, 24-29. https://doi.org/10.9756/BIJIEMS.4794
[66]	Rodriguez, M., Ajjan, H., & Peterson, R. M. (2014). CRM/Social Media Technology: Impact on Customer Orientation Process and Organizational Sales Performance. Journal of Marketing Development and Competitiveness, 8, 85-97. https://doi.org/10.1007/978-3-319-10951-0_233
[67]	Rosen, D. L., & Maguire, P. (1990). Myths and Realities of Computerphobia: A Meta-Analysis. Anxiety Research, 3, 175-191. https://doi.org/10.1080/08917779008248751
[68]	Shen, G. C. (2015). How Quality of Life Affects Intention to Use Social Networking Sites: Moderating Role of Self-Disclosure. Journal of Electronic Commerce Research, 16, 276-289.
[69]	Son, J., & Niehm, L. (2020). Using Social Media to Navigate Changing Rural Markets: The Case of Small Community Retail and Service Businesses. Journal of Small Business and Entrepreneurship, 33, 619-637. https://doi.org/10.1080/08276331.2021.1871711
[70]	Sugandini, D., Feriyanto, N., Muafi, Hadioetomo, & Darpito, S. H. (2018). The Influence of Novelty Seeking Behavior and Autonomy toward New Product Trial in the Context of E-Business Learning: The Role of Mediation of Perceived Behavioral Control. Journal of Entrepreneurship Education, 21, 1-9.
[71]	Tahar, F., Riyadh, H. A., Sofyani, H., & Purnomo, W. E. (2020). Perceived Ease of Use, Perceived Usefulness, Perceived Security and Intention to Use E-Filing: The Role of Technology Readiness. Journal of Asian Finance, Economics and Business, 7, 537-547. https://doi.org/10.13106/jafeb.2020.vol7.no9.537
[72]	Taherdoost, H. (2017). A Review of Technology Acceptance and Adoption Models and Theories. Procedia Manufacturing, 22, 960-967. https://doi.org/10.1016/j.promfg.2018.03.137
[73]	Ting, D. S. W., Carin, L., Dzau, V., & Wong, T. Y. (2020). Digital Technology and COVID-19. Nature Medicine, 26, 459-461. https://doi.org/10.1038/s41591-020-0824-5
[74]	Tuunainen, V. K., & Saarinen, T. (1997). EDI and Internet-EDI: Opportunities of Effective Integration for Small Businesses. In R. Galliers, C. Murphy, H. R. Hansen, R. O’Callaghan, S. Carlsson, & C. Loebbecke (Eds.), Proceedings of 5th European Conference on Information Systems (pp. 164-177).
[75]	UNCTAD (2021). Global E-Commerce Jumps to $26.7 Trillion, COVID-19 Boosts Online Sales. https://unctad.org/news/global-e-commerce-jumps-267-trillion-covid-19-boosts-online-sales#:~:text=The%20dramatic%20rise%20in%20e,report%20published%20on%203%20May.&text=%E2%80%9CThese%20statistics%20show%20the%20growing%20importance%20of%20online%20activities
[76]	Vaccaro, A. R., Getz, C. L., Cohen, B. E., Cole, B. J., & Donnally III, C. J. (2020). Practice Management during the COVID-19 Pandemic. The Journal of the American Academy of Orthopaedic Surgeons, 28, 464-470. https://doi.org/10.5435/JAAOS-D-20-00379
[77]	Van Daalen, M. (2020). Going Digital as a Way Out of the COVID-19 Crisis. International Trade Centre. http://www.intracen.org/covid19/Blog/Going-digital-as-a-way-out-of-the-Covid-19-crisis/
[78]	Venkatesh, V., & Davis, F. D. (2000). A Model of the Antecedents of Perceived Ease of Use: Development and Test. Decision Sciences, 27, 451-481. https://doi.org/10.1111/j.1540-5915.1996.tb01822.x
[79]	Waithaka, G. M., Muturi, W., & Nyabuto, K. (2014). Effects of Marketing Strategies on the Growth of Small Businesses in Kenya: A Survey of Kariakor Market. European Journal of Business Management, 1, 261-275.
[80]	Wamba, S. F., & Carter, L. (2013). Twitter Adoption and Use by SMEs: An Empirical Study in System Sciences (HISS). In 46th Hawaii International Conference on System Sciences (pp. 2052-2049). https://doi.org/10.1109/HICSS.2013.577
[81]	Wang, T. (2017). Social Identity Dimensions and Consumer Behavior in Social Media. Asia Pacific Management Review, 22, 45-51. https://doi.org/10.1016/j.apmrv.2016.10.003
[82]	Wang, Y.-M., Wang, Y.-S., & Yang, Y.-F. (2010). Understanding the Determinants of RFI Dadoption in the Manufacturing Industry. Technological Forecasting and Social Change, 77, 803-815. https://doi.org/10.1016/j.techfore.2010.03.006
[83]	Wartick, S. L. (1992). The Relationship between Intense Media Exposure and Change in Corporate Reputation. Business and Society, 31, 33-49. https://doi.org/10.1177/000765039203100104
[84]	Wong, C. (2012). Facebook Usage by Small and Medium-Sized Enterprise: The Role of Domain Specific Innovativeness. Global Journal of Computer Science and Technology, 12, 52-59.
[85]	Worldometer (2022). COVID-19 Corona Virus Pandemic. https://www.worldometers.info/coronavirus/
[86]	Wry, T., Deephous, D. L., & McNamera, G. (2006). Substantive and Evaluative Media Reputations among and within Cognitive Groups. Corporate Reputation Review, 9, 225-242. https://doi.org/10.1057/palgrave.crr.1550031
[87]	WTO (2020). Role of E-Commerce during COVID-19 Pandemic. https://www.wto.org/english/news_e/news20_e/rese_04may20_e.htm
[88]	Wu, I. L, & Chuang, C. H. (2009). Analyzing Contextual Antecedents for the Stage-Based Diffusion of Electronic Supply Chain Management. Electronic Commerce Research and Applications, 8, 302-314. https://doi.org/10.1016/j.elerap.2009.04.013
[89]	Zeiller, M., & Schauer, B. (2011). Adoption, Motivation and Success Factors of Social Media for Team Collaboration in SMEs. In S. Lindstaedt, & M. Granitzer (Eds.), Proceeding of the 11th International Conference on Knowledge Management and Knowledge Technologies (pp. 1-8). Association for Computing Machinery. https://doi.org/10.1145/2024288.2024294
[90]	Zhai, C. (2010). Research on Post Post-Adoption Behavior of B2B E-Marketplace in China. In The International Conference on Management and Service Science (pp. 1-5). IEEE. https://doi.org/10.1109/ICMSS.2010.5576774