Asymmetric information theory, developed by Smith (1987), occurs when a situation of uncertainty arises concerning the debtor’s financial health or creditworthiness, due to the presence of informational asymmetries. Trade credit acts as a contractual mechanism for assisting with informational asymmetry in establishing credit terms between both parties involved in the credit agreement that acts as a mechanism of display to provide valuable information specific to the debtors default risk. Specially in the case of trade credit, such information proves resourceful to creditors, as it acts as a strategic mechanism in assisting creditors to protect their investment or forecast for the possibility of default posed by the debtor.

Furthermore, the management of trade credit is of particular importance to SMEs, while various business environmental variables affect business sustainability for the majority of African SMEs making various business environment variables related to SMEs’ management of trade credit relevant and in need of investigation (Bosma et al. 2020; OECD 2020). With the aim of the study in mind, the literature (first objective) reviewed eight business environmental variables: managerial competencies, collateral, financial and business information and networking (internal) and legal system, ethical management practices, macro-economic conditions and corruption (external).

Managerial competencies allow SMEs to grow into sustainable businesses. Therefore, a high managerial competency level exhibited by SMEs will yield greater financial and business viability. Malinao and Ebi (2022) support this observation by revealing a positive correlation between new venture profits and greater levels of education and experience possessed by the business. Bosma et al. (2004) support this, by indicating that human capital influences the entire set of performance measures, namely employment, profitability, and survival. In addition, should SME owners possess former industry experience similar to their current operating industry, this set of performance measures appears to improve including SMEs’ survival and creation rate (Bosma et al. 2004). Studies by Veliu and Manxhari (2017) support this observation, as the importance of managerial competencies to SME success is amplified, becoming increasingly relevant in the case of South Africa that is regularly burdened by education system inequalities, thereby emphasising the relevance of managerial competencies to SMEs trade credit management (Bosma et al. 2020).

Creditors show a higher level of commitment and assurance and feel better protected with credit extension when collateral is available, given that collateral could reduce the risk of lending, thereby signalling debtor’s capacity for credit repayment (Gassiah & Kikula 2022; Voordeckers & Steijvers 2006). However, asymmetric information is a regular occurrence for SMEs subjected to high trade credit interest rates that act as a display mechanism from which information pertaining to the debtors default risk portrays asymmetrically resulting in uncertainty related to debtors’ creditworthiness (Smith 1987). Asymmetric information acts as an incentive for the extension of trade credit and the formulation of a credit policy as one of the main fundamental theories of trade credit that underpins this study (Smith 1987). Collateral solves several financial problems derived from information asymmetry, namely monitoring and screening costs and moral hazard that result in uncertainty specific to debtors’ financial viability, given that collateral requirements mitigate the risk of debtors not committing to credit repayment improving SMEs trade credit management (Barbosa & Moraes 2004; Blumberg & Letterie 2008).

Concrete financial and business information is regularly unavailable for SMEs, resulting in a financial and business information supply gap that contributes to information asymmetry (Nguyen, Tran & Truong 2022). Vander Bauwhede, De Meyere and Van Cauwenberge (2015), as well as Palazuelos, Crespo and Del Corte (2018) support this observation as creditors feel more secure and willing to extend lending volumes to debtors. In addition, financial and business information availability is important to the entire SME sector as SMEs source credit as debtors, while facilitating credit supply as creditors termed a ‘two-way transaction’ (Otto 2015). Therefore, it is observed that SMEs directly contribute to the viability of their net trade credit positions, as the availability of financial and business information becomes essential to avoid a spill-over of information deficiency, given their interdependency (Otto 2015).

Several authors argue in favour of networking, in order to improve SMEs’ trade credit management. Networking opportunities position creditors to benefit from vital resources such as trust-based networks that facilitate the provision of valuable information pertaining to debtors’ reputation, disclosing debtors’ character and capacity, alerting to any possibility of default (Amoako & Matlay 2015; El Ghoul & Zheng 2016). However, creditor and debtor relationships usually fall victim to conditions of information asymmetry, although, if networking takes place, asymmetric information can be mitigated among same-sector SMEs, strengthening inter-SME trade credit management (Gulati & Gargiulo 2002).

From a legal system perspective, an inefficient legal system contributes to unprofitability because of business insolvency impeding operational viability, leaving creditors unprotected and subjected to lengthy judgement periods that regularly end up in liquidations. In practice, creditors remain unprotected in an attempt to resolve accounts in arrears because of business insolvency. The country’s efficiency in enforcing creditor contracts is utterly low, thereby confirming the incapability of the South African legal system in support of SMEs (Palacin-Sánchez, Canto-Cuevas & Di-Pietro 2019). To this end, it is no surprise that SMEs in South Africa fail extensively, with unprofitability and financial problems observed as the two major reasons for SME failure within the 2017 and 2018 GEM South Africa Report (Singer et al. 2018). The study by Palacin-Sánchez et al. (2019) suggests a significant negative relationship between efficiency of the legal system and trade credit, given that trade credit depends on a country’s institutional factors. The authors state that individuals responsible for formulating and implementing institutional policies should be mindful of how these regulations influence trade credit. Therefore, the efficiency of the legal system in South Africa could prove to be relevant to SMEs’ trade credit management.

In addition, the general risk perception in credit lending is increased when sound ethical perceptions are lacking as different sources of information will impact on SMEs’ trade credit decision-making (Fatoki 2010). Ethics is instrumental in mitigating a variety of trade credit constraints in the business environment, namely adverse selection and moral hazard, due to information asymmetries (Howorth & Moro 2006). Therefore, ethics may well be the most important assessment criteria available to a creditor in extending credit to a debtor (Amoako, Akwei & Damoah 2020). Because the essence of successful lending revolves around mitigating asymmetric information, the disclosure of ethical information could limit debtors’ incentives to default, thereby improving SMEs’ trade credit management.

Small and medium-sized enterprises should also consider macro-economic fluctuations such as inflation, interest rates, and foreign exchange rates, as these might challenge SMEs’ operational abilities, leaving SMEs exposed to negative debt leverage (Lui 2020). However, SMEs’ ability to fully comprehend macro-economic conditions is subjected to their managerial competency levels, as the understanding of macro-economic conditions can help SMEs better plan for disruptive future events as economic downturns impose a destructive influence on SMEs forcing SMEs to operate under a negative debt leverage (Kwenda & Holden 2014). In addition, South Africa’s low economic growth prospects impede SMEs’ ability to act as drivers of economic prosperity as the situation worsened from the devastating impacts of the coronavirus disease 2019 (COVID-19) pandemic on trade credit from a creditor’s perspective (Lui 2020), raising the usefulness of determining macro-economic conditions as a construct relevant to SMEs’ management of trade credit.

Numerous other external business environmental elements challenge SMEs’ ability to adapt to institutional environmental variations, including being more exposed to variations in economic policy because of corruption (Rashid & Saeed 2017). Small and medium-sized enterprises incorporate 99% of all established businesses globally; yet the effect of corruption is prevalent within SMEs, while there is hardly any research on how corruption affects the smaller business (Le & Doan 2020). Literature does, however, distinguish between two perspectives, namely ‘grease in the wheels’, incorporating a positive implication because of business corruption, and ‘sand in the wheels’, incorporating a negative implication. According to Khwaja and Mian (2005), corruption places businesses in a better position to receive external funding by overcoming complex regulations that limit businesses, due to existing bureaucratic processes. This ‘grease-in-the-wheels’ viewpoint is supported by a number of authors stating that SMEs do decide to engage in corruption as a means of survival, due to problems combining regulatory compliance and bureaucracy, especially in developing countries burdened by defective government bureaucracy and the presence of private monopolies (Wellalage, Locke & Samujh 2019). Alternatively, corruption could influence the SMEs’ repayment capacity once credit is granted. This could impair SMEs’ management of trade credit, as several studies align with the ‘sand-in-the-wheels’ viewpoint incorporating negative corruption implications threatening SMEs’ financial viability (Le & Doan 2020; Ullah 2020).

Bosma et al. (2020) observed that SMEs are exposed to several business environmental influences all relevant to their operational viability. The above literature shares a common similarity in that South African SMEs are exposed to numerous internal and external business environmental variables affecting their business success, particularly their trade credit management. It can be argued that SMEs do not rate these variables equally and that a list of many criteria items can be clumsy with hardly any support in practice. Because SMEs‘ are critical to address South Africa’s SDGs, the importance of constructing SMEs’ internal and external business environmental factors to determine SMEs’ ratings of these factors relevant to their trade credit management becomes essential, in order to mitigate SME failure as a result of business exits, due to financial problems.

Section A of the questionnaire collected demographic data revealing the average age of the respondent to be 52 years, predominantly classified as a White male. Close to half of the total respondent group is in possession of a postgraduate qualification, while their average trade credit management experience amounted to 18 years. Most of the SMEs were based in Gauteng, with close to half of the respondents total operating within the manufacturing industry and three quarters of the total group of respondents operating independently as an entity. In addition, over half of the total group of respondents employ up to 50 staff members, while both SMEs and individuals equally represent the largest percentage allocation as a description to respondents’ clientele.

Table 1 shows the results of the 49 components in Section B of the questionnaire, which tested SMEs’ ratings pertaining to internal and external business environmental variables relevant to SMEs’ management of trade credit (second objective). The descriptive statistics mean value and SD are shown for each component. Table 1 tabulates descriptive statistics of Section B of the survey questionnaire before EFA.

The KMO measure of sampling adequacy demonstrates the suitability of the SMEs’ business environment data for factor analysis and the Bartlett’s test indicates redundancy is not a problem amongst components (Table 2).

A principal component analysis extraction method was used with Oblimin rotation to reduce the data from the 49 components to a more manageable number of factors for further analysis. Eigenvalues greater than 1.00 was the criterion used to identify factors. Items with factor loadings less than 0.300 were removed, and another round of EFA was carried out (Leech, Barrett & Morgan 2005). Eleven items were removed as a result of this process. Five internal and six external business environment factors were confirmed after EFA. To reach the third objective the results of the initial EFA were considered against the research reviewed in the literature section. Table 3 show the rotated factor loadings related to SMEs’ internal and external business environment factors after EFA.

Table 4 shows eigenvalues for the 11 factors. The total variance explained for the internal and external business environmental factors totalled 70.374%.

Cronbach’s alpha was used to test the construct reliability (Table 5). Reliability for all 11 SME business environmental constructs is confirmed to be adequate. Table 5 presents a selected summary statistics for the 11 factors.

This section starts with a discussion on the prioritisation of the 49 components (Table 1) in attaining the second and third objectives. The literature review (first objective) provided a basis to develop the questionnaire. These 49 individual components could easily be linked to existing studies. For a detailed review of the questionnaire, refer to (Otto 2022).

Table 1 provides the average mean score values of the set of business environmental components needed to understand SMEs’ ratings of internal and external business environmental variables before EFA (second objective). Three of the four internal variables, consisting of several sub-variables, obtained a mean score of more than 3, revealing that respondents rated their business’ credit management in case of managerial competency quality (4.02) as good and their business itself in case of networking (3.40) and financial and business information (3.01) quality between average and good. However, for collateral (2.87), respondents rated the business itself related to quality of collateral between poor and average. Only one of the four external variables, ethics (3.61), has a mean score of more than 3, indicating that SMEs rated either the business’ debtors or the business itself to quality of ethics between average and good. For legal system (2.75) and macro-economy (2.07), the mean scores of less than 3 indicate that SMEs rated the quality of both variables between poor and average. Lastly, for corruption² (2.72), SMEs indicated that the extent to which corruption occurs from the perspectives of debtor to SME and SME to creditor is between small to moderate.

In relation to EFA results, six Section B factors have scale means above three out of five and five factors have scale means below two out of five (5-point Likert scale was used). In relation to determining if factors derived from the EFA are rated equally by SMEs (third objective), the following factors ranked from highest to lowest mean, indicating that SMEs do not rate these business environmental factors equally. MC (4.03) reveal the highest means score value of all internal factors, as SMEs rated this factor as good. This finding corresponds with the observations by Veliu and Manxhari (2017), Bosma et al. (2020), as well as Malinao and Ebi (2022), expressing the importance of managerial competencies to SME success. NET (3.73) obtained the second highest means score that aligns with the findings by Amoako and Matlay (2015), as well as El Ghoul and Zheng (2016) who observed the importance of networking in obtaining valuable information to create trust-based networks. FI (3.25) followed closely and showed an average rating that aligns with the findings of Vander Bauwhede et al. (2015) and of Palazuelos et al. (2018). Small and medium-sized enterprises rated COL (3.02) as average. This corresponds with the study by Voordeckers and Steijvers (2006) revealing a mediocre importance, less so compared to the previous three factors, of collateral in protecting creditors from information asymmetries. As a last internal factor, DED obtained a mean of 2.96, while DEP, external factors listed further, scored a mean of 3.49, which aligns with the studies by Howorth and Moro (2006) and Amoako et al. (2020), in that ethics is instrumental in mitigating financial problems associated with credit lending and therefore important. Small and medium-sized enterprises rated ELS between poor and average (2.75), which corresponds with Singer et al.’s (2018) viewpoint that the inefficiency of the country’s legal system contributes to SMEs’ reasons for business exits. MEC obtained a mean of 2.06 that corresponds with the observation by Lui (2020), in that SMEs are constrained by a poor macro-economic climate furthermore impaired by the COVID-19 pandemic. Lastly, for corruption factors SME rated: CCPP (3.04), CDPP (2.83), and DCUL (2.50), showing that SMEs rate the extent of corruption from creditor to SME as more prevailing than debtor to SME. Altogether, given that SMEs rated the extent of corruption between small to moderate, the results align with the viewpoints of Le and Doan (2020) and Ullah (2020), who observed the negative corruption implications (‘sand-in-the-wheels’ perspective) associated with corruption to SMEs’ financial viability.

Table 2 depicts the results obtained after performing the KMO and Bartlett’s test for item validity tests (second objective). The results for Section B are as follows: BTS at 1176 and the level of significance at P = 0.000, indicating that the data is appropriate with sufficient correlation between components for the purpose of factor analysis. The result of the KMO measure of sampling adequacy was 0.860 for Section B of the survey questionnaire, which indicates that there are sufficient components for each factor. Both tests support the appropriateness of the factor analysis technique, given that the results from the KMO were very high and statistically significant, indicating high validity for Section B of the questionnaire.

The results display the factorisation of individual questionnaire components into factor constructs (third objective) and each factor’s eigenvalue (refer to Table 3 and Table 4). The rotated factor loadings for SME business environmental factors delivered five internal business environmental factors and six external business environmental factors relevant to SMEs’ management of trade credit. Factor one – Financial information included three components: B3.2, B3.4, and B3.6. The following components were removed, due to cross loading: B3.3, B3.8, and B3.1. Factor two – Managerial competencies matching theoretically and empirically, included five components: B1.3, B1.5, B1.2, B1.1, and B1.4. Factor three – DCUL – SME and debtor corruption through approving unviable loans. Debtor’s ethical disclosure of accurate and transparent financial and business information included four components: B8.7, B8.6, B8.8, and B8.5. Factor four – Efficiency of legal systems, matching theoretically and empirically, included six components: B5.4, B5.2, B5.3, B5.5, B5.6, and B5.1. The fifth factor – Debtor’s ethical disclosure of accurate and transparent financial and business information included two components: B6.5 and B3.7, with component B3.5 removed, due to cross loading. Factor six – Networking included four components: B4.2, B4.4, B4.3, and B4.1. The resultant factor seven – Macro-Economic conditions is exactly as originally conceptualised and included four components: B7.2, B7.3, B7.1 and B7.4. Factor eighth – Corrupt debtor payment practices through forcefully delaying payments due to the SME, the second corruption factor, included two components, B8.1 and B8.3 and factor nine – Corrupt SME payment practices through forcefully delaying payments due to creditors of the SME included four components: B2.2, B2.3, B2.1, and B2.4. Factor ten – SME and debtor ethical performance.

CCPP, the third corruption factor, included two components: B8.4 and B8.2 with components B6.4, B4.5, B6.6, B4.6, and B2.5 removed, due to cross-loading. Lastly, factor eleven DEP included two components: B6.1 and B6.2, with component B6.3 removed due to cross-loading.

Table 4 displays factors with eigenvalues greater than one, as, according to the rules of factor analysis, only factors that have eigenvalues greater than one should be retained. The Initial eigenvalues for Section B’s cumulative percentage is 70.374%, with the total factor count amounting to 11.

Table 5 displays the reliability (second objective) and summary statistics for SMEs’ internal and external business environmental factors. A Cronbach’s alpha coefficient value above 0.7 is regarded as a reliable scale, with the provided results indicating that all SME internal and external business environmental factors have a Cronbach’s alpha coefficient higher than 0.7, ranging between 0.915 and 0.707, indicating high factor reliability for all factor constructs.