Social Media Adoption: Small and Medium-sized Enterprises' Perspective in Sri Lanka

Abstract

In this digital age, all organizational environments force businesses to adopt Information and Communication Technologies (ICT) since these technologies have immense impact on such businesses' competitiveness and productivity. Nonetheless, the productivity and the competitiveness enjoyed by such firms vary depending on the size or the organizations, context of the country; developing or developed, and what kinds of technologies are adopted. This investigation focused on small- and medium-sized enterprises (SMEs) of Eastern province of Sri Lanka where such studies are scanty. The adoption of social media (SM) by SMEs is inclined to change how organizations operate, this calls for an investigation of the elements that impact SMEs to adopt SM and such investigation. Technology-Organization-Environment (TOE) framework was based to understand the factors. Research approach was quantitative approach using questionnaire survey. Data were collected using online form to see 285 valid responses. Structural Equation Modelling was deployed to evaluate the proposed model. Results revealed that Relative Advantage, Compatibility, Complexity, Observability, Competitive Intensity, Bandwagon Pressure, and Competitive Pressure were influencing, while Trialability, Top Management Support, CEO's Innovativeness did not show statistically significant influence on SMEs' social media adoption.

1. Introduction

Both governments and the private sector play important roles in constantly looking for new high-efficiency innovation methods in the process of making technical change and product innovation (Lee & Xuan, 2019). The marketplace performance of organizations could be enhanced by using Information Technology (IT), specifically social media (SM), to manage business processes. SM entails the exchange of contents generated by users via real-time responses and the creation of consumer communities that facilitate business processes. As such, products are created collaboratively between companies and consumers and business areas can benefit from the use of social media. Indeed, SM is increasingly developing as an essential part of business. Contemporary studies have indicated the need for SMEs to implement high-tech inventions aptly, i.e., timely and at the right place to ensure their advantage and lucrativeness (McCann & Barlow, 2015). Nevertheless, SMEs have also been shown to have restraints in adopting IT due to the lack of resources in managing major IT undertakings. As a cost-effective business management tool, social media may provide huge benefits for SMEs.

The driving factors for SM use among SMEs in emerging countries such as Sri Lanka has been the subject of a few studies (e.g., Samsudeen & Kaldeen, 2019) and in the case of Eastern province of Sri Lanka, which is one of the worst affected province in the country due to civil war as well as Tsunami and trying to recover to show its resilience, a proper investigation into the matter could help in growing SM adoption by SMEs. Hence, we intend to build and examine a framework for investigating the possible driving factors of SM usage among SMEs in Eastern province of Sri Lanka from various perspectives. Outcome of this investigation will add to the existing literature in the field in two ways, namely, through the development of a proper multiperspective framework investigating the driving factors of use of SM, and the empirical testing of the framework on a sample of Eastern province. Prior studies on this matter had mostly been done in developed countries despite evidence suggesting the non-generalizability of the findings to emerging nations. Hence, this investigation pays attention on a developing country’s emerging region and fills the glaring gap in literature.

2. Literature Review

A small enterprise does not have a singular definition. Its multiple definitions are commonly associated with the degree of economic activity and progress in a certain nation with measurements based on a company’s capital assets, labor skills, turnover levels, legal status, ownership or industry sector (Cheng, Kadir, & Bohari, 2014). Economies have been indicated to fundamentally rely on SMEs as they considerably add to the creation of employment and contribute national economic stability. The SME sector is indeed perceived as a crucial part of modern industrialized societies. There are many distinctions between SMEs and large businesses such as the former being more rigorously controlled, but with less possibility of employing experts. Their significant focus on general skills could also be the reason why SMEs are lacking in the much-needed IT knowledge and expertise.

Additionally, without sufficient financial support, SMEs will not pump in their money on IT segment as they are mindful of the fact that they do not have the needed resources to control any arising issues (Baby & Joseph, 2016). Globalization has caused persistent technological changes, which affect the competitive ability of businesses. Hence, their business activities need sufficient support in terms of IT, i.e., a critical tool for enhancing economies. Nevertheless, small businesses do not have the same ICT investment capability as larger organizations which affect their prospects for sustainability. The process of ICT diffusion is still slow despite empirical proof that technology can enhance the prospects of business success. Hence, businesses need to adopt technological advances to stay relevant in the market.

Potluri and Vajjhala (2018) examined the opportunities and challenges facing the adoption and use of Web 3.0 technology in developing countries. An array of ICT tools can be adopted by businesses, one of the most prominent being social media of which agility can transform business operations. Its increasing use across businesses is projected to continue. Hence, it can be assumed that businesses of all sizes and activities know the necessity of adoption of SM, which brings about significant business advantages through advertisement, promotion including word-ofmouth, response from client, market research, and product development. Such advantages are now not exclusive to major businesses as social media is also applicable for SMEs. Social media use could facilitate SMEs in managing and resolving issues related to this sector. The optimism demonstrated by the SME owners/managers with regards to social media usage also indicates their awareness that popular following on social media platforms can be translated into concrete business opportunities.

Notwithstanding all the arguments above, literature still show that only a handful of SMEs trust the apparent advantages offered by social media. SM’s use has been associated with increased sales, reduced costs, wider outreach, increased awareness about brand, increased number of visits to the business web, and improved B2B relationships (McCann & Barlow, 2015). Based on this, social media adoption has been deemed as a strategic business priority and a regular component of business operations. Nevertheless, prior to its adoption, businesses must first determine the aims and objectives of its use and the means to measure its outcomes as according to McCann and Barlow (2015), the failure to devise a strategic social media adoption plan could result in the failure to attain the full advantage of its usage. SMEs are well-known to be averse to the use of information technology, which could be due to their hesitation with regards to the aspect of profitability when undertaking business changes. Despite evidence of a positive correlation between usage of SM and enhanced organizational performance, a majority of businesses are still averse to the idea. McCann and Barlow (2015) pointed to poor strategic planning as the root cause. Another study found that despite the usage of SM by 97% of marketers, 85% of them were unsuccessful to grasp the exact benefit of SM, which may cause a miscalculation of promotional undertakings (Dutot & Bergeron, 2016). Further, that study found that SMEs have shown reservations with regards to social media engagement in terms of duration and retention, selecting a platform suitable for their organization, and determining proper format and substance for their communication. Such deficiency in online marketing knowledge prevents entrepreneurs from taking advantage of its benefits in advancing their business. Research works are scanty to delineate the barriers that halt social media adoption among SMEs (Ahmad, Bakar, & Ahmad, 2019), but several theories have been suggested to explain the phenomenon. Identifying the main reasons for social media adoption could facilitate businesses that are still hesitant in adopting it.

3. Theoretical Framework

This investigation pays attention on all possible applications of SM. The research framework takes into consideration numerous factors entailing the aspects of technology, organization, and environment, which could be used on other types of businesses apart from SMEs. Many studies (e.g., Wamba & Carter, 2016) on adoption of SM are concentrate on developed nations. Responding to the demand for theoretical validation concerning IT adoption across various contexts, this current study conducts an empirical testing on the proposed framework using sample from a developing country’s affected but emerging economy, specifically Eastern province of Sri Lanka. Such variation in study is crucial because the adoption of IT systems rely on the particular social, cultural, economic, legal, and political circumstance of a country. As such, the outcomes taken from a developed nation may not be applicable to a developing country.

By having specific empirical support for the factors impacting adoption of SM in developing countries, this study can evade issues related to the non-transferability of findings specific to developed nations. In this investigation, SM is deemed as a novel, never-before-used innovation for organizations. Since there is very little information available about technology adoption undertakings that could lead to the entrenching of SM in an organization’s strategic approach, emerging literature about new technology adoption and organizational behavior was used in creating an organizational technology adoption framework (Wamba & Carter, 2016). This study is also centered on determining whether the technology adoption – intended or actual – is occurring at the organizational level, in total or in certain departments or agencies. Several theories explain new technology adoption at both levels. All of the theories indicate multiple driving factors for innovation adoption. In the context of this study, to investigate the effect of technological, organizational, and environmental factors on the adoption of new innovation, the TOE Framework by Tornatzky and Fleischer (1990) is used, which has reliable empirical evidence in the domains of technological and information system. As a universal technology dispersion theory, numerous studies on organizational technology adoption has benefited from its use.

3.2. Technology Context

Technological factors refer to technology that is already in use in an organization, or one that is existing and recognized as valuable, but has yet been employed (Zhu & Kraemer, 2005). The technological background focuses on internal and external technology that is useful to companies that have the technical skills needed for the use of SM (Effendi, Sugandini, & Istanto, 2020). Technological characteristics determine how the innovation is utilized and adopted, which could either be advantageous or detrimental for the organization. This also applies to social media of which technological factors could entail relative advantage, compatibility, complexity, trialability, and observability (Rogers, 2003). The adoption of a certain technology is commonly decided by equating its possible advantages and disadvantages to that of other options. Once it is determined that the technology’s advantages are far greater than its disadvantages, then the possibility of adopting it is higher. The perceived compatibility of an innovation refers to its suitability with the existing business processes, suppliers, and customers. Substantial evidence had highlighted that the compatibility between a technology and an organization’s values, culture and way of working can significantly determine the adoption of the technology in the organization, even SMEs. Without compatibility, technology adoption would be difficult (Zhu & Kraemer, 2005). The complexity of use of a certain technology including the requirement for extensive training may hinder its adoption as suggested by Zhu and Kraemer (2005).

At the individual level, the correlation between intention to use and ease of use has been substantially proven. However, at the organizational level, this relationship has not been sufficiently investigated. Also, Nguyen, Nguyen, and Dang (2020) found that the lack of consistency between current systems and new technologies, such as the latest generation of digital technology, has made it difficult to incorporate information technology. Trialability refers to the possibility for the technology to be tested first before being adopted completely (Rogers, 2003) such as a pilot run in one department. In the environment of electronic commerce adoption, trialability has been found to be an important factor as it lessens doubts. The use of social media is rather low-cost; hence, a trial run for a certain period is highly viable. Observability refers to the visibility of the effect of technology adoption. When the positive effect and success of technology adoption can be clearly observed in others, individuals and organizations will become more confident in following suit (Rogers, 2003). The study by Lin and Chen (2012) confirmed that businesses refuse to adopt cloud technology without having successful case studies or models. From the aforementioned, the following hypotheses are formulated:

H1: Relative Advantage impacts Social Media Adoption by SMEs

H2: Compatibility impacts Social Media Adoption by SMEs

H3: Complexity impacts Social Media Adoption by SMEs

H4: Trialability impacts Social Media Adoption by SMEs

H5: Observability impacts Social Media Adoption by SMEs

3.2. Organization Context

Organizational factors entail features such as number of staff, revenue, extent of centralization and formalization, managerial structure as well as resources (e.g., employees, employee relations and networking) (Tornatzky & Fleischer, 1990). As the number of staff and revenue in the context of SMEs are limited, this current study uses top management support as an organizational factor. Top management is pivotal in determining technology adoption as it is responsible in explicating the compatibility of the technology with the organization’s general strategy, and in driving and rewarding creativity and innovation. The top management creates the perfect setting and provides the necessary resources so as to drive technology adoption (Lin, 2014). There is substantial evidence that top management support significantly drives organizational technology adoption (Ahmad, Bakar, & Ahmad, 2019). CEOs’ Innovativeness and the receptiveness of novel ideas and innovative products can also affect technology adoption. As the owner-manager of an SME is primarily responsible in decision-making (Wilson, Khazaei & Hirsch, 2015), this factor is linked to the attitude and openness of the CEOs of SMEs towards novel innovations. Numerous published studies have investigated this factor (Christodoulides, Siamagka, & Michaelidou, 2015). Thong and Yap (1995) highlighted that SMEs are more prone to IT adoption when their CEOs are open to innovativeness. Hence, the innovativeness of CEOs is expected to influence social media adoption in SMEs. The following hypotheses are proposed based on the above discussion:

H6: Top Management Support impacts Social Media Adoption by SMEs

H7: CEOs’ Innovativeness impacts Social Media Adoption by SMEs

3.3. Environment Context

Environmental factors refer to the external conditions within which the organization is operating. These factors include industry structure, technology availability, and governing rules (Tornatzky & Fleischer, 1990). Technology adoption may cause changes to industry structure hence leading to possible changes in competition rules, the creation of competitive advantage, and the leveraging of new means for outperforming other industry players. As social media is a form of information systems, it is usable as organizational and information strategies against industry rivals. Competitive pressure refers to the extent of rivalry in an industry as a result of globalization, new technological advancement, and usage of knowledge. Technology adoption is a means of innovation for organizations in a competitive environment. A study on the adoption of e-business among European companies indicated that the adopters are pressured by their business partners to adhere to certain technological criteria due to the fact that e-trade necessitates all business partners to implement compatible systems (Zhu, Kraemer, & Xu, 2003). Similarly, integrated social media applications and platforms must be adopted by all the related trading partners.

The bandwagon effect refers to the psychological drive to adopt a certain technology because other companies have done so, even to the extent of ignoring existing corporate strategies (Ahmad & Monfaradi, 2017). This is prevalent in new information systems adoption. The popular adoption of a certain technology will greatly influence others to do the same (Ahmad & Monfaradi, 2017) and companies in unstable business environments are more prone to such bandwagon effect. Based on the above discussion, the following hypotheses are proposed:

H8: Competitive Intensity impacts Social Media Adoption by SMEs

H9: Bandwagon Pressure impacts Social Media Adoption by SMEs

H10: Competitive Pressure impacts Social Media Adoption by SMEs

4. Methodology

Variables from technology, organizational and environmental context instituted the exogenous variables of this investigation while the adoption of SM by SMEs was the endogenous variable. These indicators were adapted from prior validated investigations on innovation adoption and wordings were amended to suit the context under investigation. Responses were captured using a seven-point Likert type scales from 1 for Strongly Disagree to 7 for Strongly Agree. The questionnaire was circulated among 35 academics to see if there are any ambiguity and to how much time it takes to complete. According to the suggestions from them some questions were changed in wording to improve easy understanding. Population of the study was all SMEs in the Eastern province of Sri Lanka. Since it was very hard to obtain the entire list of SMEs, we resorted to adopt non-probabilistic sampling to reach the respondents conveniently. The instrument was made online using Google Forms and the links were shared to SMEs owners and those who were in charge of handling SM in those SMEs via email, Facebook messenger, and WhatsApp contacts. We persuaded them personally to complete the forms without any financial motivations. Allowing four months for this data collection, we ended up with 294 responses. After downloading the responses into MS Excel software, they were checked for completeness. Nine responses were not taken for analysis as they were incomplete thereby allowing 285 responses for further analysis. Data were screened and missing values and outliers were treated properly. Finally, the dataset was loaded into SPSS 25 software for initial exploration. To test the proposed hypotheses and to evaluate the hypotheses Structural Equation Modeling (SEM) was deployed using AMOS 24 software.

5. Data Analysis

Descriptive statistics were used to obtain respondents’ profile. A Confirmatory Factor Analysis (CFA) was used to evaluate the measurement model and Structural Equation Modelling (SEM) was employed to test the proposed hypotheses. Respondents profile was derived as shown in Table 1. Accordingly, 210 respondents were male (74%) and females were 68 (24%). More than 75% of the respondents were between the age of 40 to 59 years and less than 25% were below 40 years age.

Table 1: Demographic of the Respondents

Measurement model was evaluated first and then estimation of the structural model was carried out. Using construct reliability and validity test, the fitness of the model was estimated in the measurement model. According to Hair, Hult, Ringle, & Sarstedt (2016), Confirmatory Factor Analysis (CFA) and evaluation of structural model are two main phases in Structural Equation Modelling. Relationship among variables and their measurement are established in CFA and hypothesized relationship among variables are tested in test of structural model.

CFA tests validity in two stages; one is by assessing Goodness-of-fit (GoF) indices and the other is assessment of construct validity (Hair, Hult, Ringle, & Sarstedt, 2016). GoF considers some indices for assessment. Initially χ² was used to determine the fitness of a model. This χ² is sensitive to sample size, hence it is not considered to be the best indicator (Hu & Bentler, 1999). Therefore, its ratio to Degree of Freedom (df) (χ² /df) is used instead. The χ² / df in this study is 2.354. This is considered excellent as it is ≤ 3 (Hair, Hult, Ringle, & Sarstedt, 2016). Further, GFI = 0.912 ≥ 0.900; AGFI = 0.836 ≥ 0.800; NFI = 0.923 ≥ 0.900; CFI = 0.935 ≥ 0.950; RMSEA = 0.061 ≤ 0.06 (Hu & Bentler, 1999; Hair, Hult, Ringle, & Sarstedt, 2016). Hence, as it can be seen that all these fitness indices are within the cut-off thresholds, the model establishes to be fit. Construct validity confirms the results of the CFA (Hair, Hult, Ringle, & Sarstedt, 2016). This validity checks whether the scales well-represent the underlying concept of variables (Bryman & Bell, 2011). In order to validate the adequacy of psychometric properties of measurement model, this study used convergent validity and discriminant validity tests. The statistical difference of measures of different concepts is evaluated by discriminant validity. This study used Composite Reliability (CR) and Average Variance Extracted (AVE) to evaluate the reliability and convergent validity as recommended by Hair, Hult, Ringle and Sarstedt (2016). The threshold for CR is above 0.7 to ensure adequate reliability and AVE above 0.5 as well as CR values should be greater than AVE to make sure convergent validity. According to Fornell and Larcker (1981) square root of AVE of each factor is expected to be larger than its correlation with other factors.

According to Table 2, the CR values for all constructs are above 0.7 with the lowest value of 0.738 and highest value being 0.89 ensuring the adequacy of internal consistency. With all constructs having the AVE value above the threshold of 0.5 the convergent validity is also established. Further, the square root of AVE for each construct is also well above its correlation with other constructs ensuring the discriminant validity. All these satisfactory results ensure the fitness of the measurement model.

Table 2: Model Validity Measures

Note: RA - Relative Advantage, CMP – Compatibility, CML – Complexity, TRL – Trialability, OBS – Observability, CEO - CEO’s

Innovativeness, INTN - Competitive Intensity, BNP - Bandwagon Pressure, CPR - Competitive Pressure, TOP - Top Management Support.

Researchers use Path Estimate, t-Values and p-Values to test hypotheses. If the relationships of the variables have t-Value greater than 1.96 and p-Values below 0.05, then they are considered to statistically significant. Path estimate results of the proposed ten hypotheses are shown in Table 3. Accordingly, Relative Advantage, Compatibility, Complexity, Observability, Competitive Intensity, Bandwagon Pressure and Competitive Pressure had statistically significant impact on SMEs’ Social Media Adoption while Trialability, Top Management Support and CEOs’ Innovativeness did not have such significant impact. Hence, hypotheses H1, H2, H3, H5, H8, H9, H10 were supported while H4, H6, and H7 were not supported.

Table 2: Hypotheses Testing​​​​​​​

6. Finding and Discussion

This study aimed to explore the leading factors that support or hinder SM adoption among SMEs in Eastern province of Sri Lanka. The findings revealed strong theoretical and empirical support for TOE in examining social media adoption. A comprehensive hypotheses were proposed and tested for this purpose. Results show that technological, organizational and environmental factors except trialability, and top management support and CEO innovativeness were found to have significant effects on social media adoption by SMEs. In terms of technological factors, relative advantage, complexity, compatibility, and observability significantly influence the adoption of social media. Relative advantage entails the SMEs’ perception that the adoption of socia media would improve their online business performance, hence positively influencing their intent to adopt its usage. Complexity entails the SMEs’ perception of the ease of use of social media, which is in fact an application that they are highly familiar with and constantly use in their daily life; hence, this factor has a positive and significant effect on their intent to adopt it in line with the results of Ahmad, Bakar and Ahmad (2019). Compatibility indicated a significant effect on the intent to adopt social media. Incompatibility in procedures could hinder users from adopting social media. Trialability, however, does not have a significant effect on social media adoption SMEs. This finding is in alignment with that of Alshamaila (2013) , which indicated that experimental usage does not affect technology adoption among SMEs. This hence suggests that opportunities to test or make experimentally use social media would not demonstrate SMEs’ likelihood to adopt the application. Observability is also found to significantly predict social media adoption. Widespread social media adoption by individuals and organizations can motivate SMEs to do the same.

Business decisions including those entailing IT adoption are directly determined by the top management. However, the finding of this study with regards to this matter is not in line with the results of previous studies that support the critical role of top management in IT adoption (Wilson, Khazaei, & Hirsch, 2015). This could be due to the fact that SMEs do not perceive their support as crucial in the early stages of IT adoption. Similarly, due to the perception that social media adoption is still a novel idea to be implemented in organizations, the top management, hence may not see the crucial need for their involvement and commitment. CEO innovativeness is also found to be an insignificant factor in this study consistent with the findings of Tehrani and Shirazi (2014). Developing countries tend to avoid uncertainties, a trait that has been identified to hinder innovativeness. In the context of this study, i.e., Sri Lanka, the prevalence of avoiding uncertainties as suggested by Hofstede (1984) hampers the emphasis on innovativeness and risk-taking, which is associated with social media adoption.

In terms of environmental factors, competitive intensity, bandwagon and competitive pressure are found to be significant in influencing SMEs to adopt SM. Due to competitiveness, certain firms could feel left behind when their rivals adopt a certain technology hence leading them to do the same. But this had only been proven in the context of e-commerce and ERP software adoption. In the context of this current study, SMEs may want to adopt the usage of SM when there are expectations for them to do so. Hence, it can be said that the trend of social media usage is driven primarily by the bandwagon effect, and not so much by competitiveness and social pressure. Modern-day customers utilize advanced technologies and platforms in building social groups, which hence stimulates relational developments with others as well as content and feedback exchanges with regards to products and services. This in turn influences business behavior and drives firms to adopt certain technologies to fulfil the requirements and trends of the current market. Business environment factors are shown to have an effect on social media adoption among entrepreneurs. The relationships among companies can influence the structure of the industry and sectors. Competitiveness drives SMEs to adopt a certain technology when they see their counterparts doing the same. Hence, SM usage could be influenced by a mixture of competitive intensity, bandwagon effect and competitive pressure in keeping up with recent market trends.

7. Conclusion

The efficiency of companies in the marketplace could be improved by the use of Information Technology specifically social media to govern business processes. Social networking includes the sharing of user-generated content through real-time responses and the development of customer communities that promote business processes. As such, items are generated collaboratively between businesses and customers, and the business sector may benefit from the use of social media. This study attempted to investigate the factors influencing SMEs adoption of social media in Eastern province of Sri Lanka. Valid data collected from 285 respondents were analyzed deploying structural equation modelling. Findings revealed that Technology, Organization and Environment factors except Trialability, Top Management Support and CEO’s Innovativeness significantly influenced SMEs adoption of Social Media in this context. This study has made a contribution to the existing body of literature.