The study adopted the theory of effectuation developed by Prof. Saras Sarasvathy in the early 2000s at an Indian Business School, as a professor researching strategy, entrepreneurship and business ethics (Sarasvathy 2001a). This theory is often considered a process theory because it enlightens the process that entrepreneurs practice to create new endeavours. However, much uncertainty still exists about the relationship between expert entrepreneurs’ psychological mindsets towards EDEs and how they go about providing solutions. In the history of SME development, the theory of effectuation has been thought of as a fundamental factor in making decisions about resource accessibility and availability, algorithms and performing standards that could assist SMEs to adopt EAA for SCM (Sarasvathy 2001b). Critics such as Kitching and Rouse (2020) point out that theory requires reflection on issues of social ontology and conceptualisation of structural and cultural influences on processes of venture creation. Also, Arend, Sarooghi and Burkemper (2016) reject the theory of effectuation based on two narratives. Firstly, it neither refutes the widely accepted criticism that an implementation failed to acknowledge or build on earlier work, nor does it show exactly how an implementation added value to the original. Secondly, it shows implementation as self-interested because it is associated with familiar ideas based on experimentation, risk sharing, resilience, adaptability, action orientation, loss aversion, etc., without explaining why it is important to connect with them. From a different perspective, Dias and Lisuka (2019) reiterate that some authors question impressive innovations because for them, many of the characteristics describing the phenomenon have already been presented in the entrepreneurship literature, so they criticise the failure to acknowledge previous work, including the benefits of causality. On the other hand, despite many criticisms of the theory, it questions the ability of implementing the theory to provide adequate work, but it does not characterise the scientific value that it provides through the educational adoption of ESA (Arend et al. 2016). Implementation of effectuation is central to the research of Blekman (2021), who introduces five principles:

In non-fiction, numerous typologies of complex legal and regulatory constraints are discussed through regulatory system governments that affect SMEs via trading policies, import and export quotas, in some developed economies that have legal and regulatory requirements in place (Jooste et al. 2016; Mzekandaba 2018a). The legal constraint is defined as legitimate control over unlawful activities enabling the satisfaction of the interests of the affected party (Moroz 2018). On the other hand, Taeihagh, Ramesh and Howlett (2021) define regulatory constraints as a process in which government requires certain activities or behavioural patterns from individuals, enterprises and institutions, through legislative processes and Acts. The quick rise of technological advancements introduced a host of legal and ethical issues with copyright and intellectual property compliance because of new ethical and legal considerations that are constantly arising (Walcerz 2018). Legal complexity refers to methods that measure and monitor the legal aspect of an entity governed by legal theorists and statutory regulators such as: (1) Small Enterprise Development Agency, the Department of Trade Industry and Competition, Companies, and Intellectual Property Commission, (2) Limpopo Economic Development Agency and (3) Small Enterprise Development Agency to reflect on the law’s complexity to adhere to trading standards and norms (Ruhl & Katz 2015). This study exemplifies the nature of the forces that compels every enterprise to compete for to execute its strategy based on assets, liquid assets, resources, quality, regulatory compliance, interests of stakeholders, organisational culture and risk tolerance (Spacey 2019). Previous studies suggest that levels of EDEs are independent of the size of the SMEs and business regulations by the government, which include legal frameworks, regulatory instruments for markets, social customs and technology (Leenes et al. 2017). Additionally, legal frameworks are developed to achieve a competitive advantage by challenging predominant SMEs’ modus operandi models on exploiting gaps in legal and regulatory environments (Rossi 2014). Although this is the most comprehensive account of EDEs produced so far, it does suffer from several legislations such as the Cooperatives Act 14 of 2005, which provides for the formation and registration of cooperatives, the establishment of a Co-operatives Advisory Board, and the winding up of cooperatives and matters connected therewith. Financial Advisory and Intermediary Services Act 37 of 2002 intends to regulate the rendering of certain financial advisory and intermediary services to clients; to repeal or amend certain laws; and to provide for matters incidental thereto. The National Credit Act 34 of 2005 promotes a fair and non-discriminatory marketplace for access to consumer credit and for that purpose to provide for the general regulation of consumer credit and improved standards of consumer information. Small Enterprise Finance Agency Companies Act 71 of 2008 provides for the incorporation, registration, organisation and management of companies, the capitalisation of profit companies, and the registration of offices of foreign companies carrying on business within the Republic of South Africa. Industrial Development Corporation Act 22 of 1940 intends to constitute a corporation the object of which shall be to promote the establishment of new industries and industrial undertakings and the development of existing industries and industrial undertakings and to provide for other incidental matters. Small Enterprise Development Agency (SEDA) focuses on designing incubation models, managing national incubation standards, market assessments aimed at feeding opportunities to the ecosystem, influence or direct private sector and government spend accordingly, monitoring and evaluating the entire system, to name a few.

South African National APEX Co-operative (SANACO) includes assisting cooperatives both financially and non-financially on compliance, which includes assisting cooperatives with financial statements. South African National APEX Co-operative continues to engage all organs and state-owned institutions to support cooperatives in South Africa. Small and micro enterprises be duty-bound to least build an adaptive and agile SC with rapid planning and integrated production. Studies by Schnädelbach (2010) and Laan (2016) indicate an adaptive architecture that includes standard templates, configurations of infrastructure components, new instances of infrastructure and configured components, automated configuration registry storage, configuration registry and definition files with standard templates that are kept in a version control system. Small and micro enterprises’ infrastructure is designed to adapt to technologically accepted models that could inhabit SCM systems, entirely driven by internal data. The legal dynamics regulating SMEs on the adoption of EAA ought to be taken the pressure off so that SMEs will have a better competitive advantage and cost-benefits analysis that could assist them to master economic tools to aid in decision-making for any legal matter arising. Drawing from these, the Acts functions as a catalyst and buffer between the governmental institutions and SMEs for implementing the rules and regulations that are fair and transparent without any deviances.

External financing can be in the form of bonds, loans and debt financing, or to acquire funds from business angels and venture capitalists as a way of raising capital rather than retained earnings (Althuser 2018; Harvey 2012). It is worth noting that external financing results in a financial burden of the interest rate being charged (Rossi 2014). This has negative implications on both the banks and SMEs as they bear a financial burden with exorbitant interest payable on repo rate and prime rate (Gerber 2018). Financial service companies are competing with fluctuating market interest rates that affect SMEs (Mulesoft 2009). From an external view, the acquisition of funds depends on creditworthiness, financial statements, feasible business plans and bank statements (Guimarães 2012; Ritchot 2013). Companies are increasingly unprepared to effectively integrate advanced technological infrastructure that requires additional capital (Benay 2016). Limited expansion of opportunities is a consequence of slow GDP growth and a lack of external financing for SMEs (Brooks 2019). According to Zucker (1987), institutional theory instigates that institutional elements have a direct target as obstacles such as social orders, context on specific rules, and social atomisation widening the gap between the institutional environments, which makes it difficult for SMEs’ internal operations. Interestingly, Sembene (2021) alludes to the highest global institutions: ‘Access to finance in the IMF is concessional resources by temporarily raising its annual access limits at the onset of the Corona virus disease 2019 (COVID-19) pandemic, during the crucial and desperate need for money to combat the global financial crisis’. The analysis of the lack of external financing undertaken extends the knowledge of broadening the financial range of instruments such as asset-based finance, alternative debt, crowdfunding and hybrid instruments.

Low technological capacity indicates an SME’s incapability to absorb technology to transmogrify operations as a technique of maximising production adeptness and gaining a competitive advantage within SMEs (Reichert & Zawislak 2014; Spacey 2015). At the same juncture, there is no clear definition for LTC, while a variety of literature guided this study to propose a definition for LTC as the enterprise’s incapacity to invest in technological infrastructure for the adoption of EAA (Del Carpio & Miralles 2018; Spacey 2015). In support of EDEs, the adoption of EAA induces absorptive capacity theory in several cases that moderates algorithms and routines, which enable enterprises to acquire, assimilate, transform and utilise new external knowledge to create value (George et al. 2001). On the other hand, technological capacity is a sustainable enterprise’s aptitude for adopting new technologies to improve innovation performance (Khalifa 2016). According to Suhadak and Mawardi (2017) and Wayner (2019), SMEs have different business requirements, diverse technological standards and IT systems for sharing data and information and receiving trade advice centre programme. Be that as it may, the absence of technological capacity leads to low network capacity, which in turn leads to slow processing systems for transactions for both internal and external partners in SCM (Buckow & Rey 2010; Del Carpio & Miralles 2018). Although this is the most comprehensive account of LTC encountered so far, it does suffer from a few imperfections during the adoption of EAA. Nevertheless, innovation through technological capacity could accumulate positive results for SMEs. According to Ann (2019), development in the technological transfer is critical to remove barriers and close gaps in achieving increased SCM proficiency. Endro et al. (2017) affirm that new entrants to the business markets bring new capacities leading to an automatic increase in competition.

Cavallari (2020) maintains that a failure to embrace SMEs’ culture that lacks the propensity to face internal and external challenges such as resistance to change, support from the leadership team, transparency in the complexity, poor governance and communication, a lack of collaboration between teams with poor algorithms and procedures could lead to disastrous adoption of EAA. Schulz and Dankert (2017) assert that emerging technologies provide the assurance for reliable and predictable SCM activities. They also point out that outsourcing strategies should be in line with regulatory objectives and within the framework of corporate social responsibility in order to protect the image of SMEs and normative factors that influence and determine the behaviour of end users. In support, Bell, Mondliwa and Nyamwena (2019) report that dynamic capabilities are viewed as being a firm’s capacity to shape its market in ways that lead to the creation and capture of value. The quantitative method is considered in this context for determining the impact of EDEs on the AA of EAA. A key strategy and precedence in absorptive capacity theory should balance acquisition and assimilation, transformation and exploration of overwhelming LTC.

According to Reichert and Zawislak (2014), Maduku et al. (2015) and Tagged (2019), RA is regarded as the process whereby customers realise the benefits of a product or service based on its enhanced features and benefits rather than those of other substitutional computer software or hardware systems. A more comprehensive RA on computer systems includes the use of advanced laptops rather than old-school devices such as typewriters. Furthermore, Zhang and Jensen (2006), and Skoko, Buerki and Ceric (2006a) denote the RA on two consonants: the variable capturing the relative productive efficiency based on monetary value and relative balance and management of factors. Consequently, RA includes customer relationship management systems (CRMSs), knowledge management systems, sales and marketing systems, manufacturing and production systems, finance, accounting, and links with human resources management (Ann 2019; Kehring 2018). It is also vital to highlight that DTI postulates five characteristics of innovation that affect diffusion, namely: (1) RA reflects the degree to which new IT provides more advantages to the existing tools. (2) Compatibility refers to its reliability with collective practices and norms among its users. (3) Complexity refers to its ease of use with processes. (4) Trialability denotes the opportunity to explore new technological systems (the AA of EAA). (5) Observability depicts the positive side before the actual use (Dillon & Morris 1996). Adopting EAA in SCM can lead to RA by integrating different business strategies (Gerstein 2012). The RA is advantageous if SMEs change the existing business models for the adoption of EAA (Rossi 2014).

A comprehensive SCM system initiates, monitors and supports decision-making and reports on activities required to complete SC operations and planning (Bowersox et al. 2013; Gulati, Kahn & Baldwin 2018). This concept has recently been challenged by Ahmad and Mehmood (2015) who allude that if sustainability factors are incorporated from the very inception, benefits are realised in the sustainability dimensions, and the adoption could yield positive results. The RA could lead to a competitive advantage in SMEs with an element of superiority in SCM. The existing accounts on SMEs’ infrastructure fail to resolve the contradiction between EDEs and the adoption of EAA. However, there is an inconsistency with this disagreement. Nevertheless, the EAA algorithm employs stochasticity for optimisation (Oldewage, Engelbrecht & Wesley 2019), and the introduction of stochastic demand reinforces the benefits for SMEs to invest in early product design knowledge in building a successful EAA (Zha & Sriram 2006). Surveys such as that conducted by Parise, Lygeros and Ruess (2015) show that a proposed approach for dealing with stochasticity requires data from many different replicates of the system. Drawing on the theory of planned behaviour, SMEs will adopt EAA for a specific platform only if they perceive RA surpassing traditional channels (Choudhury & Karahanna 2008; Escobar-Rodríguez & Bartual-Sopena 2015). Sharing information across the SC compels SMEs to improve accuracy and reduce the cost of orders at strategic, tactical and operational levels (Mzekandaba 2018b; Reyes et al. 2015; Sewdass 2012). Also, the RA of using IT is that it allows the reach of all types of systems and employees can give their inputs and suggestions (Endro et al. 2017; Sweeney 2011). The RA might be classified based on AA of EAA into compatibility, resource availability, self-efficiency, subjective norm and interest, and institutional branding.

At first glance, compatibility is described as the interoperability of hardware and software systems to work together without requiring further alterations (Wigmore 2013). This distinction is further exemplified using the general semantic theory of computer systems, which includes operational semantics in three dimensions. Firstly, operational semantics indicate that a construct is specified by the computation it induces when it is executed on a machine. Secondly, denotational semantics assume that different meanings are modelled through mathematical objects that represent the effect of executing the constructs. Thirdly, axiomatic semantics reflect specific properties of the effect of executing the constructs expressed as assertions. A more recent point of view on the general semantic theory of computer systems has been summarised by Golenkov et al. (2018), which includes the following: (1) semantic theory of knowledge depends on metaphor knowledge base, ultra-ontology dynamic knowledge base used in generalised valence mode, and the integration of information based on multilingual translation; (2) semantic theory of problem-solving models indicates that some problems are solved when the ontology is applied, and ambiguity can also appear on the syntactic level; (3) semantic theory of interaction of information processes for human–computer interaction is dysfunctional without semantic computing; (4) semantic theory of user, including natural language interfaces, requires semantics for the purpose of natural language processing and understanding; (5) semantic theory of non-verbal sensory-effector interfaces; and (6) theory of universal interpreters of semantic models of computer systems and the theory of semantic computers. Wang, Wang and Yu (2017) narrate the explicit nature of semantic theories in all magnitudes explaining their values and functions. However, much ambiguity still exists about the relation between hardware and software systems and semantic theory. Drawing upon two hardware for EAA adoption and research into EFTs, this study distinguishes between these two peripherals as a single-and-joined component.

Software systems compatibility is widely used in two types of testing as denoted by Bagthaliya (2021): firstly, backward compatibility testing is considered as a technique to intersect the behaviour and compatibility of developed hardware or software with their previous versions. The testing is entirely predictable as almost all alterations from previous versions, and it is predictable, as several changes, are known. Secondly, forward compatibility testing is a technique to check the developed hardware or SSC with the latest versions, and it is challenging to predict the changes. Further testing compatibility is explored in six dimensions. These dimensions are:

Last of all, one of the most noticeable requirements in SSC is that it requires precise and detailed installations with regard to operating system, central processing unit (CPU), random access memory (RAM) and storage capacity. This relates to the setting out and development of the thinking in relation to computer programming, which includes to create, debug, maintain or otherwise support other programmes and applications of the ideas as well as the language used in the writing.

The questionnaire was structured in the form of a Likert scale, with probable options ranging from strongly disagree (1), disagree (2), moderate (3), agree (4) and strongly agree (5). A door-to-door inspection was conducted for collecting data. About 340 questionnaires were distributed, of which 30 were not recovered, and 10 were not fully responded on. As such, about 310 were considered for data analysis. Questions were guided by literature review, and using the relationship research questions seeking to explore and define trends and interactions between EDEs and the AA of EAA, see Appendix 2: Questionnaire, extracted from Lamola (2021). Questions were categorised between EDEs and the AA of EAA. The target industry included retail stores that use the e-commerce transaction data, customer feedback and in-store (physical or web) browsing behavioural pattern. Both SMEs’ owners and managers were considered as the sample frame relevant to the study based on exposure to 4IR characterised by the fusion of the digitisation, as well as the growing utilisation of new technologies such as artificial intelligence, cloud computing, robotics, 3D printing, the Internet of Things (IoT) and advanced wireless technologies, among others. The industry stratum included the following: wholesalers, electricity, gas and water; catering and accommodation, transport, storage and communications; and finance and business services. Data were collected in Capricorn District Municipality that include Blouberg (Bochum) Municipality, Molemole (Dendron) Municipality, Polokwane Municipality and Lepelle-Nkumpi (Lebowakgomo) Municipality. A critical analysis into the emergence of 4IR and its implications in SCM through automation, as well as the critical analysis of technological additivity and competencies for e-commerce organisations.

The total proportions of the population in the sample calculation were calculated by adopting the n-formula from Leedy and Ormrod (2014). The n-calculation includes 310 for two reasons: 15 questionnaires were not returned and 5 were not fully answered.

The study considered a stratified sapling, as the SMEs comprised of 1900 (N), with 135 SME owners and 175 managers. This was made up of 55 women and 45 men, which produced a representative of 100 people.

Ethical clearance to conduct this study was obtained from the University of Limpopo, Turfloop Research Ethics Committee (TREC) (No. REC-0310111-031).

Table 3 provides the results on correlations between EDEs and the AA of EAA. The p-value is near zero at ‘˂ 0.001’ with the required value set at 0.05.

Pearson correlations is on positive associations between variables at 0.239, Sig. (two-tailed) at 0.000 and values are given as means (n = 310), p < 0.005, p < 0.000. The findings on association suggest that, in general, there is a positive relationship between EDEs and the AA of EAA bearing the change of the sign in mind.

Table 4 displays the ANOVA results attained for scores on EDEs and the AA of EAA. The dependent variable is regarded as the AA of EAA, while the independent variable is regarded as EDEs. The statistical technique ‘ANOVA’ tests the hypotheses between the dependent variable, namely, the AA of EAA, and the independent variable, such as EDEs.

The general F-statistic is significant (F = 18.615, p ˂ 0.001), thus signifying that, overall, the model accounts for a significant proportion of the variation in the adoption of EAA for SCM in SMEs. The relative scale of the sum of squares of EDEs in ANOVA generated in SPSS increases as the variation in AA of EAA within the categories of EDEs decreases. The alternative H_a1 that ‘EDEs affect the adoption of EAA for SCM in SMEs’ is accepted, while the null H₁ that ‘EDEs do not affect the adoption of EAA for SCM in ‘SMEs’ is rejected. This means that there is a statistically significant difference between the means of the different levels of the EDEs variable.

Table 5 presents the results for the coefficient between EDEs and the AA of EAA. The p-value is 0.000 ≈ 0.001, while the Pearson coefficient is 0.239, thus indicating that there is a positive relationship between EDEs and the AA of EAA, which is below the cut-off point at 1.

The independent t-test is used to determine the confidence interval at 95% of the coefficient; therefore, the t-test is (20.603, 4.294). The results on the coefficient state that there is a positive correlation between EDEs and the AA of EAA.

Figure 2 projects summaries on different characters where Ӯ = AA of EAA, a = y-axis intercept, b = + slope and x-axis intercept as EDEs. The R² value is 0.057 of the variances that are accounted for in this scatter plot from the independent variable as EDEs.

The positive linear regression ascertains the assumptions on a model for best fit. As indicated, there are many points above or below the line of regression, and the ones that lie outside the line of regression are the outliers. The linear regression where Y = 19.82+0.15*x. The slope of 0.15 will bring the same increase in Y. The R² value of 0.057 indicates that the level of variation in the prognostic variable could be described by variation in the independent variables. Likewise, the R² is converted to r, thus √0.057 = 0.238, which is ≈ 0.239, confirmed in Table 1 and Table 4 for Pearson correlation and coefficients. This approves that the model is adequate with a positive slope and the model is adequate. The results indicate that EDEs are the important factors for the AA of EAA in SCM.

In this study, the CV is considered as an important concept that allows to predict variables within and outside data sets that are between EDEs and the AA of EAA. While it has its roots in mathematics and statistics, CV applied in different contexts including population demographics.

Arithmetically, CV = σ / μ * 100:

Based on this result, SMEs could direct greater focus on EDEs that could produce interesting findings that account more for the AA of EAA.

Although the findings might be valuable, worthwhile and cherished, they are confronted with some limitations. The findings in this report are subject to at least three limitations: firstly, stakeholder misalignment on how each team is measured according to EAA design by taking into account management by objectives (MBOs) and key performance indicators (KPIs) that can impact how different functional departments react towards a new technology; secondly, risk assessment by neglecting perceived attitudes on two dimensions: perceived value and usefulness of the technology are outweighed by the required investment. Although the study focused on six EDEs, the major limitation of this study was to determine SMEs’ level of visualisation, transformational impact, long-term competitive advantage, cybersecurity, trialability and observability.

In future studies, it might be possible to use the different EDEs in which SMEs could be able to circumnavigate and dominate challenges that might affect their enterprise operations, particularly in SCM. This may include suppliers and partners being disinclined to compromise, employees struggling to adjust to new processes and tools, lack of practice and training before implementation, difficulties with communication internally and externally, and customers’ concerns, issues and poor experience. It is recommended that further research be undertaken in the following areas: (1) complex legal and regulatory requirements should address issues such as the following: licensing processes and opaque tax assessment rules are among the most important regulatory issues facing companies. (2) A lack of external funding should be taken into account, derives policy recommendations and encourages discussions between policymakers, financial institutions and SME representatives on new approaches to financing entrepreneurship. (3) Low technological capacity should be identified within new sectors close to the current national production space and then design targeted strategies to encourage innovation, either by improving the product or the production process. (4) The relative benefit should be acknowledged and recognised by all key stakeholders for effective implementation. (5) The compatibility of software systems should include the following aspects: best software testing tools, software testing courses, freelance software testing writer job for technical content, software testing course feedback and reviews and application testing. (6) Hardware system compatibility should include problems restoring hardware configurations by performing the following steps: identify the problem, update drivers and firmware, replace hardware, adjust settings and use compatibility mode.