Influence of access to finance on the competitive growth of SMEs in Lesotho

Abstract

Background

Access to finance has been identified as one of the biggest problems faced by small and medium-sized enterprises (SMEs) in most developing economies. Similarly, access to finance has been identified as a dominant constraint facing the SME sector in Lesotho. This paper established the factors related to access to finance that influence the competitive growth of the SME sector in Lesotho. The factors that were identified include financial information access, bank and business support services, the structure of banks, and the collateral requirements of the financial sector.

Findings

The results from our analysis indicated that a relationship exists between the independent variables of financial information access, bank and business support services, the structure of banks, and the collateral requirement by commercial banks. As such these independent variables are associated with SMEs’ capacity to attain competitive growth in Lesotho. Explicitly, the results indicated that Basotho entrepreneurs and managers see the predictors (collateral requirement, financial information access, and bank and business support services) as critical factors of access to finance that constrain most enterprises from accessing the necessary credit from banks, which ultimately influence the SMEs’ capacity to attain competitive growth in Lesotho.

Conclusions

The study concludes that access to finance significantly affects the competitive growth of SMEs in Lesotho. Thus, this study suggests that several specific and harmonized financial policy actions are needed in the Lesotho financial market to establish an enabling policy that will ease enterprises’ access to adequate funding programs. These funding programs should target improved financial schemes that are coordinated, competitive, and directed towards Basotho SMEs’ access to finance, and enables a harmonized credit policy that guarantees a win–win for SME loan applicants and the financial market operators.

Introduction

There is an immense body of literature on access to finance in entrepreneurship. However, with the current rapid upsurge in many market-driven economies, most small and medium-sized enterprises (SMEs) face inadequate access to finance, which constrains their capacity to attain competitive growth. According to the entrepreneurship literature, SMEs foster economic development in developed and developing countries, for example, by driving creativity and innovation, and making a significant contribution to countries’ GDPs when they have access to finance (Ghosh, 2016). Unfortunately, most SMEs in developing countries continue to face difficulties related to access to finance from banks, which constrains their growth.

According to Mazanai and Fatoki (2013), access to finance, mainly from banks, is one of the biggest problems SMEs face in most developing countries. Going by the general norm that the availability of finance is a critical source factor of SMEs’ competitive operation, commercial banks, as the main source of finance, tend to be less responsive to them. Singh and Kaur (2014) maintained that this can be attributed to many commercial banks, in their efforts to make profits, considering SMEs as too much of a risk, and consequently, showing little interest in establishing critical credit schemes to allow SMEs access to loans. In the same context, some studies highlighted that most SMEs suffer from limited access to financial resources that constrains their capacity to grow, respond to competitors in the market, and diversify their business operations (Ghosh, 2016; Subairu, 2016).

In the context of Lesotho, SMEs are those enterprises that employ from 6 to 50 employees (GoL, 2016, p. 5). A study by the European Union (EU) (2013) in Lesotho confirmed that access to finance is highly problematic for locally owned private SMEs. Similarly, a survey carried out by the EU (GoL, 2013) for the Ministry of Trade in Lesotho revealed that most SMEs owned and operated by Basotho (citizens of Lesotho) face difficulty in accessing the bank loans that are necessary to effectively operate their businesses. According to the EU’s (2013) study, 71% of small enterprises and 56% of medium enterprises indicated constraints in accessing bank credit. The factors that constituted high constraints to the SMEs’ access to finance were high interest rates and lack of appropriate collateral, as indicated by 89% and 86% of the respondents, respectively. In addition, the phenomenon of ‘discouraged borrowers’ is high, as issues attributed to socio-economic and institutional factors prevent many SMEs from qualifying for credit from banks in Lesotho.

The Government of Lesotho has recognized that many Basotho SMEs face high constraints in accessing the needed finance, which as a result, contributes to the high failure rate of such enterprises (GoL, 2016). A literature search indicated that there has been less focus on the critical factors that constrain most SMEs’ access to finance, and which are seen to influence their capacity to attain competitive growth in Lesotho. Thus, this paper argues that such critical factors are constraints to adequate access to finance, causing most local (Basotho-owned and operated) SMEs to suffer from severe market ineffectiveness, business ineptness, and to suffer various setbacks in the market environment that prevent them from attaining growth. Evidence currently indicates that the number of SMEs in Lesotho has decreased by 39.15%, from the 125,000 in 2010 to 76 067 in 2016 (GoL, 2016, p. 10). Of the 39.15%, Basotho SMEs seem to be most affected. In addition, records show that less than 10% of Basotho SMEs survive, thrive, and attain substantial growth (EU, 2013; Mokoatleng, 2015), and this may be attributed significantly to SMEs’ inadequate access to finance from banks.

Despite SMEs’ remarkable and indisputable contribution to Lesotho’s aggregate economic performance, specifically in terms of employment generation, business creation, and development, they are still victims of credit constraints and rationing from banks (Amadasun, 2013, 2020). Thus, this paper opines that access to finance remains a major obstacle, and may have worsened the prospects for most SME businesses to attain competitive growth in Lesotho.

According to entrepreneurship literature, access to finance plays a major role in SMEs’ capacity to effectively operate and achieve significant growth. Therefore, this paper considers the four core factors, namely, financial information access (FIA), bank and business support services (Bbss), the structure of bank (SoB) and collateral requirement (COLLATA) as predictors that constrain SMEs’ access to finance, and as such, influence their capacity to attain competitive growth in Lesotho. This is because we cannot avoid the fact that the finance access crisis exists and is affecting SMEs’ effective operations, particularly if seen in the light of the independent variables in various economies, particularly in the context of Lesotho.

In Lesotho, current data indicate that formal SMEs make up about 18% of the total number of the micro, small and medium-sized enterprise (MSMEs) sector, while the rest (82%) operate as informal businesses (GoL, 2016, p. 6). It seems that this percentage is not improving, particularly for Basotho SMEs, most likely because most of them find it challenging to raise adequate funds from most banks, as they are often viewed as relatively risky and lack pragmatic and standardized track records.

Thus, this paper considers the four core constructs, namely, financial information access, bank and business support services, structure of bank and collateral requirement, as factors of access to finance, that influence SMEs’ capacity to attain competitive growth in Lesotho. This is because, to the best of the researcher’s knowledge, hardly any study has considered the four core constructs as joint factors that constrain SMEs’ access to finance in the context of Lesotho. Therefore, the four factors mentioned above form the gauge to measure SMEs’ access to finance from banks that constrain their competitive growth in Lesotho.

Literature review

The literature review for this paper will consist of a theoretical review and an empirical review.

Theoretical review

The credit rationing theory

Theoretically, finance literature indicates a well-documented explanation that elucidates finance issues as related to the SMEs, and to assess the aforementioned is to review its fits to the enterprise. To the best of the researcher’s knowledge, the review of strategic literature indicates that no universally accepted theory in the entrepreneurship literature has been adopted as the sole influence on SMEs’ access to finance. Hence, it is essential to review an existing strategic theory, such as ‘the credit rationing theory’ on an enterprise’s access to finance to guide the current study’s analysis.

According to the strategic literature, the ‘financing gap analysis’ is the credit rationing theory by Stiglitz and Weiss (1981), and is one of the major theories that argues the agency problem (a conflict of interest between bank (agent) and the owners of the enterprise, and the information asymmetries, as significant reasons why SMEs are constrained in terms of access to finance. Stiglitz and Weiss (1981) argued that the presence of financial constraints on SME businesses is due to informational problems (that is, principal–agent issues) and transactional costs. Therefore, this paper assumed that due to the lack of collateral/income, most banks classify SMEs as ‘non-bankable’ enterprises and high-risk borrowers that are likely to be less interested in programs that favor them.

Further analysis shows that rationing discourages most SMEs, even in a competitive credit market using interest rates and bank charges as weapons that affect demand and the risk profile of the bank’s customers (Kremp & Sevestre, 2013). Despite this, Stiglitz and Weiss’ analysis focuses on the ‘informational problem and transactional cost’ paradigms. Both paradigms are skewed to the borrower’s capabilities to repay the loan. This suggests that asymmetrical information exists when the credit officers do not have ‘perfect’ information of the funding proposal base.

Although Stiglitz and Weiss (1981) provided compelling explanations of why credit rationing behavior still exists with financial institutions, the theory has not addressed the pecuniary issues of access to finance, such as bank and business support services, the structure of banks and the collateral requirement that may have caused banks to ration potential customers, even in a competitive credit market. Hence, banks insisting on high interest rates and bank charges may have affected demand and the risk profile of the bank’s customers. Subsequently, the fact remains that, in many developing economies like Lesotho, most banks may not have perfect information about the creditworthiness of prospective borrowers. Thus, there is a likelihood of the supply of loans to be backward bending at rates above the bank’s optimal rate (Mazanai & Fatoki, 2013). This implies that financial exclusion may persist even in optimal markets. Whether such an enterprise is excluded based on the price barriers, or financially excluded due to high idiosyncratic risk or poor project quality could be due to a market imperfection such as asymmetric information. This paper considers that these are peculiar to the four factors of access to finance: financial information access, bank and business support services, the structure of banks, and collateral requirement as constraints to SMEs’ access to bank loans.

In Lesotho, the constraints suffered from lack of access to finance tend to be common among SMEs (EU, 2013). While there have been some empirical studies, such as that of Makhetha and Sebolelo (2015), and Mokoatleng (2015), on SME access to finance in Lesotho, these previous studies omitted constructs, such as financial information access, structure of bank, and bank and business support services, as critical factors of access to finance that limits bank funding that negatively influences the competitive growth of SMEs.

To bridge the gap of access to finance, this paper suggests that although various studies have considered access to finance a huge challenge to SMEs in most developing economies, there is a gap in the entrepreneurship literature that has omitted the four factors related to access to finance mentioned above in Lesotho context. Thus, this study aims to determine the constructs (financial information access, bank and business support services, structure of bank and collateral requirement) as factors of access to finance that influence the competitive growth of SMEs in Lesotho.

Empirical review

The four factors of access to finance as related to SMEs are discussed in this section.

Financial information access

Compared to large enterprises, many SMEs face intense competitive disadvantages in accessing the financial information needed to access adequate credit from banks, typically due to the nature of their businesses. Although the nature of SMEs and their capacity do influence the constraints they face regarding access to the needed funds, they require adequate information to identify potential suppliers of credit funds (Osano & Languitone, 2016). According to Aleksandr et al. (2016), SMEs’ access to the necessary credit funds is highly influenced by the degree of access to adequate financial information about potential suppliers and the available credit products of the bank. Many SMEs are denied access to financial credit by banks because they lack the necessary information and awareness related to funding from the financial market. Following the Stiglitz and Weiss (1981) credit rationing theory, seen from the lender’s perspective, banks cannot distinguish among borrowers based on the limited financial information available to them. As a result, it leads to acute information asymmetry between the credit officers and SME applicants.

In addition, due to inadequate information about potential SME applicants, banks are unwilling to take the risk of financing them. In many cases, commercial banks consider most SMEs as high risk, in the sense that they are considered highly indebted and lack the capacity to meet prompt debt repayments (Aleksandr et al., 2016). Consequently, most commercial banks are reluctant to provide the necessary information that could encourage demand from SMEs, and it becomes problematic for these enterprises to obtain a commercial loan. Based on fewer options, many SMEs are forced to access bank credit under stringent circumstances that are not favorable to their enterprises’ flexible repayment capacity, which, as a result, affects their competitive growth in the market.

However, the following are socio-economic reasons why most banks consider limited financial information as a strategic tool to control credit extension to SMEs:

• High administrative costs of lending to small business applicants;

• Information asymmetries in the financial market; and

• The loan officer’s perception of the SMEs being highly risky, including bias related to business ownership.

Therefore, since many bankers lack perfect knowledge of potential borrowers’ solvency, SMEs may continue to face credit exclusion from the financial market.

Therefore, the following hypothesis was formulated for the study:

Hypothesis 1

H0: Financial information access has no statistically significant influence on SME competitive growth.

H1: Financial information access has a statistically significant influence on SME competitive growth.

Bank and business support services

SMEs’ access to financial and business support resources influences the enterprises’ quality in the business environment (Fetisovová et al., 2013). According to Zeebaree and Siron (2017), the main reason for government and agency support for enterprises is to enhance their operational capacity, competitiveness and to assist them to attain market growth. While there are enabling support programs that cover a wide range of services, for example, programs related to creating, developing, training, marketing and consultancy services for SMEs, many of these enterprises are worse hit by a lack of crucial enabling resources, such as a bank loan, that can be a major challenge that hinders their survival and growth (Mazanai & Fatoki, 2013).

By extension, SMEs are constrained by a lack of bank and business support resources that should include the granting of direct and indirect financial credits; managing and advisory services related to the various aspects of the enterprises to enable them to become competitive; and promoting start-up businesses by granting them resources to strengthen their operational bases, such as subsidies and training programs (Amadasun, 2020). According to Zeebaree and Siron (2017), such enabling resources are management training skills and improving the integrated technology capabilities of SME entrepreneurs or managers that can influence the performance of enterprises. A study by Gathii and Ngura (2015) found that few SME entrepreneurs possessed management training skills, and displayed integrated technology capability in their business operations. As a result, this lack of skills impedes their chances of qualifying and obtaining bank loans.

Most SMEs are exceptionally susceptible to the whims and dynamics of the business environment where there is less business support and a lack of guarantees from the government and agencies. This paper found that the inability of enterprises to access loans should be considered a fundamental institutional weakness of bank and business support services, and as such, constrains most the competitive growth of SMEs in Lesotho. The lack of bank and business support services further makes SMEs more vulnerable to bank credit, which could be another reason why credit rationing persists in the competitive credit market of Lesotho.

In addition, inadequate support programs designed for, and strive to make SMEs attractive and competitive, seem to constrain their access to finance and competitive growth. A study indicates that bank lenders simply attach high bank charges and high interest rates to a loan to discourage SME entrepreneurs who lack adequate operational support guarantee schemes (Moro & Fink, 2013). Although banks aim to minimize loans to risky borrowers, it appears that there is a lack of the types of banking schemes and insurance institutions able to bridge the link of credit to SMEs in many smaller and developing economies, and this implies that the lenders’ supply of credit funds will indicate a backward curve, even at rates higher than the bank’s equilibrium rates.

Therefore, the following hypothesis was formulated for the study:

Hypothesis 2

H0: Bank and business support services have no statistically significant influence on SME competitive growth.

H1: Bank and business support services have a statistically significant influence on SME competitive growth.

Structure of bank

Most SMEs’ limited access to financial credit is a consequence of the financial structure of banks, because competition in the financial market is an antidote for the competitive costs of financial products and services in the banking sector (Amadasun, 2020). As such, this grossly affects the competitive growth of enterprises in many developing economies.

Although many factors can be considered in explaining SMEs’ constraints related to access to finance, the level of competition in the banking industry, in particular, determines the price of financial services or products offered to loan applicants or customers. For example, Osano and Languitone (2016) suggested that the lack of competition in the financial sector acts as an obstacle for SMEs in accessing credit. Low competition in the banking sector may affect the overall stability in the financial market. It may affect the effectiveness of the financial service delivery to applicants (SMEs) who need financial credit the most. Thus, direct competition in the banking sector may positively influence new entry, growth, and the existing banks’ effectiveness, and affect SME applicants’ credit for bank loans.

Low competition in the banking sector is an implication of a high regulatory regime, where the financial market’s competitiveness does not rely on the actual market structure but relies on the country’s regulatory regime. Although there may not be a clear relationship between the interference of government on the intermediation process of the banking system’s effectiveness and the enterprises’ access to credit, regulatory restrictions probably affect the overall effectiveness and efficiency in the financial market (Osano & Languitone, 2016). Substantively, El-Said et al. (2015) argued that the low competition in the banking sector implies a high regulatory regime that excludes many SME borrowers from access to bank finance. This effectively forces SMEs to utilize micro-credit loans from informal lenders that are barely adequate, assuming that there would be an enabling environment for their enterprises.

Although SMEs are considered important actors in economic growth in Lesotho, the non-standardized designs of its credit guarantee scheme could result from the bank’s structure. Lesotho has three major banks (First National Bank, Nedbank and Standard Lesotho Bank), of which the primary ownership is foreign-owned, and as a result, the banks are less likely to pursue more information and better enforcement mechanisms. This probably excludes many Basotho SMEs from the financial mainstream through the enforcement of stringent credit conditions.

Therefore, the bank structure that does not promote direct competition in the financial market may severely impact the banking sector’s effective, efficient stability, and as such, constrain SMEs’ access to finance and affect their competitive growth in Lesotho.

Therefore, the following hypothesis was formulated for the study:

Hypothesis 3

H0: Structure of banks has no statistically significant influence on SME competitive growth.

H1: Structure of bank has a statistically significant influence on SME competitive growth.

Collateral requirement

For many SMEs, the situation is exacerbated by the banks’ collateral requirement on the loan before any credit is granted (Mazanai & Fatoki, 2013). A study by Osano and Languitone (2016) in the Maputo CBD in Mozambique, found that the collateral requirement is one major significant factor that hinders SMEs from accessing bank credit. Mazanai and Fatoki (2013) confirmed that 45% of SMEs are denied access to finance due to a lack of collateral security; hence, the survival rate of SMEs is less than 20% in South Africa. Kihimbo et al.’s (2013) study in the Kakamega Municipality in Kenya indicated that before banks consider loan requests from SMEs, they demand equivalent collateral deposits. This implies that banks in Kakamega Municipality require collateral of 100% or above, to consider credit loan proposals (Kihimbo et al., 2013). A study by Bhalla and Kaur (2013) showed that banks’ collateral requirements discourage most SMEs from accessing credit loans, and even more, they are disenfranchised due to banks’ perception that they are very risky borrowers with a low capacity to repay borrowed loans. A study by Ingabire et al. (2016) in Rwanda also considered lack of collateral to be one of the major challenges facing SMEs.

Though it may be justifiable for banks to see this as a strategic approach to avoiding losses in lending to borrowers with a lower repayment capacity SMEs need to access adequate credit to ensure the enterprises’ effective and efficient performance to attain competitive growth in the dynamic business environment, like in Lesotho.

Therefore, the following hypothesis was formulated for the study:

Hypothesis 4

H0: Collateral requirement has no statistically significant influence on SME competitive growth.

H1: Collateral requirement has a statistically significant influence on SME competitive growth.

Competitive growth of SMEs

According to Matharu et al. (2016), competitive growth is a fundamental criteria measure that includes autonomy, independence, and effectively managing the enterprise’s future. However, an enterprise’s competitive growth is generally defined based on its pecuniary, trade, and commerce performance, such as turnover, outputs, profitability, employee turnover rates, and asset return. In this paper, SME competitive growth is defined as the ability of the enterprise to access the needed credit for its operational proficiency, innovativeness, and expert business, which as such, allows it to consistently increase its market share, maintain productivity, increase staff retention, and consistently increase sales growth and profit. This implies that this paper sees an enterprise’s competitive growth from the perspective of the four factors related to access to finance for SMEs to attain competitive advantage in the context of Lesotho.

Conceptual framework

Figure 1 shows the conceptual framework of the study, as indicated by the four selected factors of access to finance that influence the competitive growth of SMEs.

Fig. 1

Selected factors of access to finance

Methodology

This study adopted the descriptive-correlation research design to analyze the influence of access to finance factors, namely, financial information access, bank and business support services, the structure of bank, and collateral requirements, on the competitive growth of SMEs.

Participants

The survey sample size was 400 SMEs from Lesotho’s four main districts (Butha-Buthe, Leribe, Mafeteng and Maseru). These four districts were chosen from the ten available districts because Basotho SMEs are more represented in the selected districts than other districts (Berea, Mohales-Hoek, Mokhonlong, Qachas-Nek, Quthing, Thaba-Tseka) that make up Lesotho.

However, the study considered Basotho SMEs that employed from 6 to 50 people and that are registered with the Ministry of Small Business Development Cooperative and Marketing (GoL, 2016). The stratified random sampling technique was used to select respondents in the four designated districts. The reliability level of 95% and sampling error of ± 5% indicated that the sample size of 400 was adequate.

The response rate was 96%, and this gave a total valid response of 384 respondents that were used in the study analysis. The high response rate was because the researcher and research assistants were familiar with the four districts, and 8 weeks were spent collecting feedback without placing any duress on the respondents.

Measures

The scale proposed by Aleksandr et al. (2016) was considered as a measure for financial information access. The financial information access predictor considered inadequate financial information related to the following: available credit funding, financial programs, and agency provision items. Bank and business support services and bank structure considered selected items from the study of Zeebaree and Siron (2017). The items considered for bank and business support services relate to inadequate policy initiatives, support programs, financial schemes and funding programs. Structure of bank considered items such as low competition, system regulation, legal status and ownership patterns that were selected from Osano and Languitone (2016). The collateral requirement scale adopted selected items from Mazanai and Fatoki (2013), Kihimbo et al. (2013), and Ingabire et al. (2016).

The predictor items from various authors were selected because they represent access to finance in the context of the study. This suggests that the measure of the four factors of access to finance (financial information access, bank and business support services, structure of bank and collateral requirement) considered some scale of items that measure the bank perception of SMEs, and the experience and behavior of banks to SME operators as related to the aforementioned four items.

The research tool comprised a 19-item questionnaire (Amadasun, 2020). The predictor scale measured four facets: financial information access (3 items, e.g., “inadequate information available on credit opportunities and programs to SMEs”); bank and business support services (3 items, “inadequate support programs such as financial schemes and credit programs are in my district designed to support my enterprise”); structure of bank (5 items, e.g., “low competition in the banking sector has greater constrains on SMEs access to credit”); collateral requirement (4 items, e.g., “collateral requirement is a major constraint to my enterprise’s access to credit funding from the bank”); and competitive growth (4 items, e.g., “it is very difficult for my enterprise to retain customer patronage, maintain sale growth and profit, and manage staff turnover”).

The study adopted the seven-Likert scale response rate format, ranging from 1 = “strongly disagree” to 7 = “strongly agree”. The research tool indicated that the higher the scores, the higher the level of agreement by respondents. The Cronbach’s alpha ranged from 0.755 to 0.861 for all the variables in this study.

Data analysis

Before the analysis, to ensure that the test indicated minimal measurement error, the necessary validity tests, such as content validity and reliability tests, were first performed to ensure that quality was maintained. The confirmatory factor analysis was first adopted to measure how the items came together to form the factors of access to finance of financial information access (FIA), bank and business support services (Bbss), structure of bank (SoB), and collateral requirement (COLLATA). This was followed by tests to calculate the coefficients of variation for and between the explanatory variables, and between the explanatory variables and dependent variables with a view to eliminating quasi-constant variables and checking for the concern of multicollinearity.

The correlation and regression analysis and results are presented in subsequent tables in the analysis section.

Results

This paper opines that understanding the concept of “access to finance” is explained by the effect of critical factors such as financial information access, bank and business support services, bank structure, and collateral requirement on SME competitive growth in Lesotho. This study’s results indicated that all tests and analyses are in line with the study’s objectives, and are consistent with the descriptive and explorative statistics used in the study.

Validity and reliability scale

Confirmatory measures

The CFA test results first indicated that all items in each of financial information access, bank and business support services, structure of bank, and collateral requirement scale items sufficiently measured variables that represent each construct. The CFA results, combined with the construct validity test, showed analytically the quality of their measures and confirmed that the theoretical specification of factors of access to finance matches the actual data, hence, confirming the study’s theoretical model.

The eigenvalues of all the factors of access to finance showed that each loads within each construct of a particular predictor factor. The results from a summary of communalities indicated that the 15 items extracted represented all the factors of access to finance, and the amount of variance accounted for by the common factors was above 0.3. All the observed items’ extraction values ranged from 0.354 to 0.894 which suggests that there is an adequate association among the 15 items, and it is acceptable (Hair et al., 2014).

Furthermore, the exploratory factor analysis (EFA) was used to identify the underlying constructs that explain the correlations among a set of factors. Since there were no preceding theories and factor loadings, the EFA was used to identify the factor pattern of the data. Bartlett’s test of sphericity and the Kaiser–Meyer–Olkin (KMO) results showed that all observed factors of access to finance in the analysis loaded as anticipated. The total value of KMO was found to be 0.840, and it is meritorious, according to the guidelines of Hutcheson and Sofroniou (1999). Bartlett’s test of sphericity was significant at 105 degrees of freedom. The determinant of the association matrix was 0.000, which showed no multicollinearity in the factors (significant at p < 0.001).

The total variances indicated that all four factors (i.e., financial information access, bank and business support services, structure of bank, and collateral requirement) are appropriate to retain because they had a minimum of three significant loadings. The principal component analysis (PCA) of the factor loading of the four observed variables converged after five iterations of rotation; hence, they were retained for further analysis. The EFA was used for the rotation, followed by the PCA using the Varimax with Kaiser normalization.

Reliability scales

Cronbach’s alpha was used to assess the reliability of factors and the internal consistency of the scale of the data. This paper followed Babbie et al.’s (2011) postulation on reliability measures for exploratory research, which asserts that a minimum of 0.7 Cronbach’s alpha is acceptable. Five factors were obtained after running the Cronbach’s alpha and EFA tests, and the values obtained were all above 0.7. Hence, they were considered acceptable for exploratory analysis (Hair et al., 2014) (see Table 1).

Table 1 Reliability outputs (final list of factors after running Cronbach’s alpha and EFA)

In line with the descriptive-correlation method, further reliability tests were run to ascertain the coefficients of variation for the explanatory factors with a view to eliminating quasi-constant variables, and to test for coefficients of variation between all four explanatory factors. The results indicated that the association between each of the explanatory factors was below 0.60, which suggests no multicollinearity concern between the four predictors in the data (Hair et al., 2014).

To decide which rotation to use for the EFA, a component correlation matrix was run to see if the four factors of access to finance are correlated, and the results indicated that none of the correlations was less than − 0.5 or greater than + 0.5. This suggests that the components are not correlated, therefore, the principal component analysis was run using a Varimax rotation. The test for normality adopted the Shapiro–Wilk test because it is known to have more power in detecting differences from normality (Field, 2018). The normality test indicated that none of the p-values in the data is greater than 0.05, which suggests that the data differ from normality, hence, the nonparametric test was used. Therefore, the nonparametric Spearman’s correlation analysis was adopted.

Spearman’s correlation analysis

Spearman’s correlation shows the association analysis of all access to finance factors (financial information access, bank and business support services, structure of bank and collateral requirement) and the degree to which each is associated with SME competitive growth. Table 2 indicates that there is a medium and higher effect of correlation between the four independent constructs to the dependent factor¹ (competitive growth), which suggests a direct relation to SME competitive growth.

Table 2 Spearman’s correlation of factors related to access to finance

Table 2 indicates that the following list addresses the aim of the paper for further analysis:

• The results showed a positive association between financial information access (FIA) and competitive growth (large effect), r = 0.54, p < 0.05.

• The analysis indicated a positive correlation between bank and business support services (Bbss) and competitive growth (medium effect), r = 0.36, p < 0.05.

• There is a positive association between the structure of bank (SoB) and competitive growth (medium effect) r = 0.31, p < 0.05.

• The analysis indicated a positive correlation between collateral requirement and competitive growth (large effect), r = 0.74, p < 0.05.

In addition, the results showed a positive association between financial information access and bank and business support services (r = 0.44, medium effect p < 0.05). There is a positive association between financial information access and collateral requirement (r = 0.37, medium effect p < 0.05), and a positive association between bank and business support services and structure of bank (r = 0.33, medium effect p < 0.05). The structure of bank is positively related to collateral requirement (r = 0.389, medium effect p < 0.05), there is a positive association between financial information access and collateral requirement (r = 0.37, medium effect p < 0.05), and the association is positive and significantly related to SME competitive growth (COMPGRO) (a large effect, r = 0.54).

The medium and high association between the predictors of access to finance and the dependent variable of competitive growth indicated a relatively positive and significant level of agreement among the respondents that the predictors are related to the SMEs’ capacity, and are associated with competitive growth. This probably suggests that the factors mentioned above are critical facets of access to finance that SMEs need in order to operate dynamically and attain competitive growth.

Regression analysis

Regression techniques, such as coefficient of determination, analysis of variance, and standardized coefficient, were adopted to establish the level of the relationship between factors (i.e., predictors and dependent variable) and their validity fit. The specification of the regression model of access to finance was significant at the 95% level and with a p-value less than 0.05. The analysis showed a positive and significant relationship between some of the independent factors and explained variables.

However, the regression model adopted in this paper subscribes to the following econometric model:

$${\text{COMPGROW}} = \beta 0 + \beta 1{\text{FIA}} + \beta 2{\text{Bbss}} + \beta 3{\text{SoB}} + \beta 4{\text{COLLATA}} + \varepsilon ,$$

(1)

where COMPGROW = dependent factor (competitive growth); β0 = constant, β1–β4 = model coefficients; FIA = financial information access, Bbss = bank and business support services, SoB = structure of bank, and COLLATA = collateral requirement are predictors; and ε = error term.

The regression results presented in Table 3 show the degree of variance in the four predictors of access to finance explained in the analysis. The results presented in Table 3 (the model summary) below show R = 0.888 and R² of 0.788. The R = 0.888 shows the degree of relatedness of the four predictors to the explained variable (competitive growth). The R² of 0.788 shows the total variance of competitive growth explained by the regression model. This means that the model fitness is 0.788, which indicates that 79% of the variability of the dependent factor (competitive growth) is explained by the independent factors of collateral requirement, financial information access, and bank and business support service, and it fits well.

Table 3 Model summary (coefficient of determination)

Adjusted R² gives the correct estimation of the variance predicted by the covariates included in the model. The results indicate that the predictor factors, namely, collateral requirement, financial information access and bank and business support service predict SME competitive growth (adjusted R² = 0.786), and expressed as a percentage, the model explains 79% of the variance in competitive growth.

The F-ratio analysis explains the overall model fit. The F-ratio output explains that factors of access to finance reduce the error by 78.8% (163.968 ÷ 207.979). This is statistically significant with the F-ratio of 353.008, and it explains that the group’s analysis is not similar. This suggests significant differences between variations within the groups, and the p < 0.001 shows strong evidence between group means, which justifies that the model is suitable at a p < 0.05 significance level (the data fit the model).

In addition, the outputs presented in Table 4 suggest that the regression model directly explains the positive influence of the three predictors on the competitive growth of SMEs. Thus, the null hypothesis (H0) was rejected for the three factors (collateral requirement, financial information access, and bank and business support services) as related to access to finance, and the alternative hypothesis was accepted, and is consistent with the outputs of Table 5.

Table 4 Analysis of variance (ANOVA)

Table 5 Standardized coefficient

H1: Collateral requirement) has a statistically significant influence on SME competitive growth.

H1: Financial information access has a statistically significant influence on SME competitive growth.

H1: Bank and business support services have a positive and significant influence on SME competitive growth.

Table 5 presents the Standardized coefficient analysis that established the regression coefficient (β) for the four predictors. To assess how well each of the four predictors (collateral requirement, financial information access, bank and business support services, and structure of bank) contribute to the final equation, the tolerance value test indicated that the four predictors exceeded the 0.10 cut-off point, proof that multicollinearity was not violated (Field, 2018).

The results presented in Table 5 indicate that collateral requirement, financial information access, and bank and business support services have a unique statistically significant contributory influence (at p < 0.05 and at t-statistic > 2) on SME competitive growth. Accordingly, SME entrepreneurs are more likely to be constrained regarding finance due to the current collateral requirement factor (magnitude 77%). This is followed by the inadequate financial information access needed by most SMEs from banks (the magnitude of 27%). Next was the inadequate financial schemes, funding programs and other enabling resources which support SME attractiveness for bank credit (level 6%).

These results suggest that for every 1% competitive growth an SME anticipates attaining, it will require 77% harmonized bank collateral requirement to the applicant’s access to a bank loan. Similarly, every 1% competitive growth an SME intends attaining would require a 26% improvement in adequate information available to the enterprises to identify potential suppliers of credit funds. Furthermore, the result suggests that for every 1% competitive growth an SME anticipates attaining, it will require a 6% improvement in the bank and business support services to boost their operational capacity and competitiveness to access needed loans from the financial market. (i.e., if all other independent factors remain constant in each case) and will likely influence the enterprise’s capacity to attain competitive growth in Lesotho. However, as seen in Table 5, ‘structure of banks’ did not positively influence SME competitive growth, a finding that went against the researcher’s expectations in the analysis.

The analysis suggests that structure of bank does influence SME access to bank loans but it does not affect the enterprise’s capacity to attain competitive growth in Lesotho. This result is inconsistent with Osano and Languitone’s (2016) findings in Maputo, Mozambique. Thus, the results suggest that the construct ‘structure of bank’ is probably a new concept not familiar to SME respondents in Lesotho.

Therefore, the equation below indicates the extent that the four predictors contribute to the regression analysis and the substitution to the final equation of the study:

$${\text{COMPGROW}} = 0.820 + 0.771\left( {{\text{COLLATA}}} \right) + 0.271\left( {{\text{FIA}}} \right) + 0.060\left( {{\text{Bbss}}} \right) + - 0.138\left( {{\text{SoB}}} \right).$$

(2)

Discussion

This paper followed a descriptive and explorative approach, factor analysis, and employed the Spearman correlation matrix and the regression analyses to address its objective. The initial analysis showed that the four constructs related to access to finance, namely, financial information access, bank and business support services, structure of bank and collateral requirement, form the measure of access to finance of SMEs in Lesotho. The correlation analysis showed that the explanatory factors, such as financial information access, bank and business support services, structure of bank and collateral requirement showed a positive and statistical association with the enterprises’ access to the needed finance and their capacity to attain some competitive growth in Lesotho. The analysis also suggests that SMEs’ access to finance is significantly linked to the positive and significant association between the explanatory factors to potentially gear enterprises’ ability to attain some competitive growth in Lesotho. Thus the correlation results indicate that the four predictors of access to finance are factors that hinder most Basotho SME from accessing credit and are correlated to their growth in the enterprise.

For further robust analysis, various regression analysis techniques, such as coefficient of determination, analysis of variance, and the standardized regression coefficient, were used to establish the strength of the relationship between the factors that explained competitive growth, as in the objectives of the study. The results of the regression analysis summarily indicated that the collateral requirement, financial information access, and bank and business support services factors have a unique statistically significant contributory influence (at p < 0.05) on SMEs’ capacity to attain competitive growth in Lesotho. In explicit terms, the positive and statistical significance of the collateral requirement’s influence on competitive growth in the analysis suggests that most SMEs face a huge constraint in the financial market to access the needed credit. The results suggest that the collateral requirement is a major significant factor that hinders and discourages most Basotho SMEs from seeking credit from banks, since the banks insist on collateral almost equivalent to the credit needed, and as such, disenfranchises most SME applicants.

Although it is the bank’s prerogative to use a strategic approach to avoid losses in lending to borrowers, SMEs need to access the necessary credit. It is therefore evident that alternative sources of finance outside the conventional banking services, such as credit guarantee schemes, venture funds, and business angels, specific to the SME sector are needed to ameliorate the situation in the financial market. Thus, this result is consistent with the findings of Mazanai and Fatoki’s (2013) and Ingabire et al. (2016).

Furthermore, the significant positive relationship between financial information access and competitive growth shown in the analysis suggests that many Basotho SMEs face an intense competitive disadvantage in accessing the financial information needed to access adequate credit from banks, which affects their capacity to attain some competitive growth in Lesotho.

Although the nature and capacity of many SMEs actually constrain their access to credit from the financial market, the following possibilities indicate that the availability of adequate financial information on the financial market will decrease the lenders’ perception of SMEs applicants as being too highly risky, and harmonize the lending costs to loan applicants. Thus, the positive significance between access to financial information and competitive growth is consistent with the findings of Aleksandr et al. (2016).

In addition, the analysis suggested a positive relationship between bank and business support services and competitive growth. The result suggests Basotho SMEs lack adequate access to business support resources which affects their operational capacity, causes them to be unattractive to banks in terms of loans, and consequently, affects their ability to attain some competitive growth. Business support and enabling resources, such as training programs, advisory, financial management training, machinery, and equipment support, are significant enough to ease SMEs’ access to finance and may enable them to operate effectively to attain some competitive growth. This significance between bank and business support services and competitive growth is congruent with the findings of Zeebaree and Siron (2017) and Osano and Languitone (2016).

However, the structure of bank construct did not have a positive significant influence on SME competitive growth, and this was contrary to the researcher’s expectations. According to the strategic management literature, lack of competition in the financial sector constrains most SMEs’ access to needed loans, and this grossly affects the enterprises’ competitive growth in many developing countries. This finding suggests that although there are three main banks in Lesotho, as indicated in the literature, while bank structure does have a significant influence on SME applicants in securing a loan from banks, it does not influence the enterprises’ capacity to attain competitive growth in Lesotho. This finding was also in contrast to that of Osano and Languitone (2016). As indicated earlier, the results suggest that the construct ‘structure of bank’ is probably a new concept not familiar to most SME respondents in Lesotho.

Moreover, the positive and statistical significance of the predictors (collateral requirement, financial information access, and bank and business support services) with competitive growth, as found in the analyses, indicates that SMEs’ ability to access the needed loans and possibly attain competitive growth depends on various factors. For example, it depends on whether the policy on the collateral requirement in the financial market is harmonized, and whether the banks adopt practice and technology that decreases information asymmetry between lenders (banks) and SME applicants, and promote practices that encourage financial and business support resources to enterprises in Lesotho.

These findings further elucidate the critical issues related to access to finance, namely, collateral requirement, financial information access, and bank and business support services that SMEs face, which constrain their application and access to funds, and affect their capacity to attain competitive growth in Lesotho.

Nonetheless, the entrepreneurial literature indicates that similar studies have been carried out in some sub-Saharan African countries, such as the study by Ingabire et al. (2016) in Rwanda; Kihimbo et al. (2013) in Kenya; Osano and Languitone (2016) in Maputo’s Central Business District in Mozambique; and Mazanai and Fatoki (2013) in South Africa. These studies have considered some and similar factors of access to finance that are regarded as a critical influence on SMEs’ access to loans that affect enterprise growth. Thus, the positive and significant influence of collateral requirement, financial information access, and bank and business support services suggest that with less constraint from the aforementioned factors, SMEs may likely have access to needed finance from the financial market and attain some significant competitive growth in Lesotho.

Limitation and outlook

This study limited the factors related to access to finance to four predictors that were considered critical factors that constrain SMEs from accessing the needed loans from the financial market, as indicated in the review and in the analysis. The analysis focused on SMEs registered with the Ministry of Small Business Development, Cooperative and Marketing (MSBDCM), which constitutes 18% of the total MSME sector in Lesotho. This implies that 82% of SMEs in Lesotho are classified as micro and informal businesses that are not registered with MSBDCM, and that were not included in the study. Due to their informal status, banks consider them highly risky and unfit for bank loans.

However, this study found that the construct ‘structure of bank’ did not positively influence the competitive growth of SMEs. In further research, a similar investigation may be conducted in other districts of Lesotho to see if better outcomes might be achieved. In addition, to explore the solution to the identified constraints of access to finance that most SMEs face in Lesotho, future studies could investigate the suitability of alternative sources of finance outside the conventional banking services, such as the improvement of government incentive programs and credit guarantee schemes (i.e., Partial Credit Guarantee Scheme in Lesotho), venture funds and business angel funding, specific to Basotho SMEs, even at the start of the business and at low cost.

Conclusion

In sum, the analysis suggests that the critical factors of access to finance, such as collateral requirements by banks, inadequate access to financial information, and inadequate bank and business support services constrain most SMEs from attaining competitive growth in Lesotho. Thus, the analysis showed that the mentioned factors of access to finance significantly hinder SMEs’ from accessing adequate funds from banks, and affect their capacity to attain competitive growth. Therefore, to reduce the constraints of access to finance that SMEs face, the study opines the need to promote the financial inclusion of credit to enterprises.

This suggests the need for policy interventions geared to harmonizing the collateral requirements by the banks, promoting adequate access to financial information to SMEs in all rural and urban districts of Lesotho, and improving bank and business support services to SMEs to enhance their capacity, and to enable them to stand a chance to access adequate loans from banks. This will gradually ease the problems of asymmetric information between SME loan applicants and the banks, ease access to loans, and influence enterprises’ chances to attain competitive growth in Lesotho. Furthermore, due to the banks’ conservative and risk-averse policies, bank loans remain a limited source of finance for most SMEs in developing market economies. For these reasons, there is a need for a call to develop diversified sources of finance as an alternative and suitable source of finance outside the conventional banking services. Such specific programs for SMEs could include improving government incentive programs and credit guarantee schemes, venture funds, business angels investing in the business right from the start of business and at low cost, to address the specific financial needs of enterprises properly and in a timely fashion, and to support their capacity to attain competitive growth in Lesotho.