Access to Credit,Education and Entrepreneurial Competencies: A Study among Women Micro-entrepreneurs in Malaysia

Abstract

This study examines how entrepreneurial competencies, education and total amount of credit received affect the performance of microenterprises owned and managed by Amanah Ikhtiar Malaysia’s (AIM) successful women micro-entrepreneurs in Malaysia. This study, using a cross-sectional design, collected quantitative data from 407 women micro-entrepreneurs through structured interviews. Findings of this study indicate that women micro-entrepreneurs’ level of education, entrepreneurial competencies and total amount of economic credit received have a significant positive effect on microenterprise performance. Among these three aspects, credit received has a relatively higher effect on microenterprise performance followed by level of education and entrepreneurial competencies. Therefore, AIM should focus on designing a flexible and diversified credit programme, followed by specialized training programmes, and facilitate sharing of experiences in order to improve the competencies, which could ultimately improve the performance of microenterprises owned and managed by the low-income women micro-entrepreneurs in Malaysia.

Keywords

Education Microcredit Entrepreneurial Competencies Microenterprise Performance

Introduction

Governments and development organizations all over the world are working together to minimize inequality in the distribution of income, as it has become one of the most widely discussed, controversial issue and a growing concern. Most recently, a study conducted by Motesharrei, Rivas and Kalnay (2014) demonstrated the upcoming devastating consequences of inequality in the distribution of income, and noted that ‘…the elites eventually consume too much, resulting in a famine among commoners that eventually causes the collapse of society’ (p. 99). In addition, Piketty (2014) in his book entitled Capital in the Twenty-first Century explained how the current capitalist system automatically generates arbitrary and unsustainable inequalities. In order to minimize the devastating consequences of inequality in the distribution of income, development banks, local governments and other international aid agencies are focused on providing targeted assistance for the development and growth of small and medium enterprises (SME) all over the world (Beck, Demirguc-Kunt & Levine, 2005). This is due to the positive role of small enterprises in general, and newly started enterprises, in particular, are widely acknowledged in the development literature. Microenterprises play a crucial role in the socio-economic development of low-income households, as well as in the maintenance of a sustainable and healthy economic growth.

In the presence of recent global economic turbulence, SMEs remain one of the main economic contributors in the recovery process by providing an estimated 67 per cent of total jobs. In Asia, SMEs form 96 per cent of all enterprises, and contribute a significant 50–95 per cent to domestic employment and 30–53 per cent to national gross domestic product (GDP) (SME Annual Report, 2012/13, p. 18). Likewise, SMEs are one of the most important contributors to the economic development of Malaysia (Saleh & Ndubisi, 2006). It is expected that the value-added products produced by SMEs will be worth RM120 billion by 2020, which is half of the total production in the manufacturing sector (Saleh & Ndubisi, 2006). Currently, SMEs account for 97 per cent of firms and contribute 40–60 per cent to the GDP and up to 70 per cent to employment (National SME Development Council, 2009).

In Malaysia, SMEs are subdivided into micro, small and medium enterprises. Among them, microenterprise is defined by Malaysian Central Bank (Bank Negara) as a business establishment with sales turnover of less than RM250,000 or less than five full-time employees (Bank Negara, 2005). In Malaysia, microenterprise establishments make up 77 per cent of the total SME establishments. In the service sector, 79.6 per cent of the total establishments are microenterprises. In the agriculture sector, 56.3 per cent of the total establishments are microenterprises. However, the proportion of microenterprises is relatively smaller in the mining and quarrying sectors (19.1 per cent) compared to small enterprises, which account for 42.1 per cent of the total establishments (Department of Statistics, 2011). Despite the positive role of microenterprises for improving the socio-economic well-being of low-income households, microenterprises tend to be associated with high failure rates (Brown & Hanlon, 2004). In order to reduce the failure rate and to improve the contribution of microenterprises, the government of Malaysia has established several development organizations that commonly provide access to finance and enterprise development training to low-income micro-entrepreneurs.

In order to minimize the inequality in the distribution of income and to improve the socio-economic conditions of low-income households, the government of Malaysia established the Amanah Ikhtiar Malaysia (AIM) in 1987. Amanah Ikhtiar Malaysia is a development organization, funded by the Ministry of Finance, Malaysia. Amanah Ikhtiar Malaysia provides small-scale financial services and training to poor households in order to improve their socio-economic conditions. Amanah Ikhtiar Malaysia uses a group-based Grameen Bank (a Bangladeshi microfinance organization) model. Studies that have examined the effect of AIM’s microcredit programme have reported a significant increase in enterprise and household income after participation (Al-Mamun, Malarvizhi, Hussain & Tan, 2012; Saad, 2011). However, despite the positive effects reported in the empirical studies, researchers are still questioning the effectiveness of the microcredit programme in improving socio-economic conditions (Islam, 2007; Rahman, Rafiq & Momen, 2009). A study conducted by Al-Mamun et al. (2012) indicates the significant positive effect of microcredit on low-income households’ income level and the reduction in the poverty rate in Malaysia. However, the mean income of low-income households, after participating in microcredit programmes, is still far below the poverty line as estimated by Lazim (2011). It indicates that after participation in microcredit programmes, the poor and low-income households’ average monthly incomes have increased, but they still remain poor or close to being poor. Thousands of microcredit organizations have used the group-based microcredit model to provide financial services and training to low-income households in many developing countries over the last two decades, including Bangladesh, India, Nepal, Pakistan, Indonesia and Philippines. Despite the positive effects of microcredit that has been noted in earlier studies, there are studies that highlight the insignificant effects of microcredit as the effectiveness of credit depends on households’ abilities to use the credit in income generating activities. It shows the limitations of the microcredit programme; after participation, the borrowers’ incomes increase, but it commonly increases only to a certain level. Studies focused on overcoming this limitation and further improving the socio-economic conditions of the poor and low-income households have noted that the standardized delivery system including fixed weekly repayment method, required group approval for access to credit, gender preference (only for women) and loan size is a strong limiting factor in effectively serving the microenterprises (Alam & Molla, 2012).

Development organizations are, therefore, searching for a way to improve their credit and training programmes in order to provide more demand-driven services with higher potential impact on microenterprise development and growth. In order to reevaluate and elucidate the ‘what and where’ to focus on, in redesigning the enterprise management training programmes and the credit programmes offered by AIM, this action research project was initiated to improve our knowledge and understanding about the role of education, credit and entrepreneurial competencies on the overall performance of microenterprises owned and managed by AIM’s women micro-entrepreneurs.

Literature Review

Theoretical Foundation

The arguments presented in this study build upon the human capital theory, combined with the theory of planned behaviour and the resource-based view. The human capital theory argues that, as noted by Streletzki and Schulte (2013), ‘an employee’s economic performance is mainly based on his/her general and specific human capital, which evolves from his/her former investments in education and experience’. The effects of education, training and experience of AIM’s underprivileged micro-entrepreneurs on the performance of microenterprises are rationalized using the human capital theory. Moreover, the theory of planned behaviour suggests that intention, a function of behavioural beliefs, is a significant predictor of behaviour (Kautonen, Van Gelderen & Tornikoski, 2013). Intention, determined by attitude towards a specific behaviour, subjective norms and perceived behavioural control (i.e., individual’s perception about his/her skills and abilities to perform a behaviour) is the cognitive representation of a person’s readiness to perform a given task. Most recently, Kautonen et al. (2013) tested the theory of planned behaviour in the prediction of business start-up intentions and subsequent behaviour in Finland. Findings of their study noted that attitude, perceived behavioural control and subjective norms are significant predictors of entrepreneurial intention, and intention and perceived behavioural control are significant predictors of subsequent behaviour. Micro-entrepreneurs’ entrepreneurial competencies and the possible effects can, therefore, be explained through the theory of planned behaviour. Finally, the modern development theory explains the progress of economic growth and inequalities in the distribution of income, where access to finance plays a critical role. As mentioned by Claessens and Tzioumis (2006), the lack of access to finance can generate a persistent income inequality as well as a lower economic growth. The impact of AIM’s microcredit programme on microenterprise performance can be explained through the modern development theory.

Education and Microenterprise Performance

In the advanced competitive business environment, specialized knowledge and innovation are the key contributors towards growth and competitive advantages. Therefore, the creation of new knowledge, followed by the implementation of innovative methods, generates competitive advantages (Magoutas, Papadogonas & Sfakianakis, 2012). The role of education is crucial, as earlier studies have reported that the level of education is the determining factor for research and innovation, since specialized knowledge improves decision-making, problem-solving and team-working skills (Fuente & Domenech, 2006; Magoutas et al., 2012; Switzer & Huang, 2007). In a more specific context, the study conducted by Chirwa (2008) demonstrates that education is a critical factor in contributing towards women micro-entrepreneurs’ performance (measured by profit margin and growth in employment) in Malawi. Micro-entrepreneurs’ level of education was investigated as a predictor for enterprise performance since well-educated owner-managers of enterprises are expected to be more effective decision makers compared to others (Read, Song & Smit, 2009). Berry (1996) noted that both special and general management education contributes to the formulation of innovative strategies and to the success of an enterprise. The women owner-managers of microenterprises examined in this study were poor before participating in AIM’s microcredit programme. These underprivileged poor rural women were expected to have limited education. Given this special situation of women micro-entrepreneurs, this study intends to examine how general education affects microenterprise performance. Thus, this study hypothesizes as follows:

H1: Women micro-entrepreneurs’ level of education has a significant positive effect on microenterprise performance.

Entrepreneurial Competencies and Microenterprise Performance

Entrepreneurial competencies are considered as the key determinant of enterprise performance (Erikson, 2002; Man, Lau & Snape, 2008). The psychological and behavioural characteristics of the owner-managers of microenterprises together with their enterprise management and field-specific skills are known as entrepreneurial competencies, which ultimately influence enterprise competitiveness (Bird, 2002; Man, Lau & Chan, 2002). Lerner and Almor (2002) examined the entrepreneurial competencies of women entrepreneurs and found a link between entrepreneur’s skills and enterprise performance. The study conducted by Man et al. (2008) reported the direct and indirect effects of competencies on SMEs’ long-term performance through a competitive scope and organizational capabilities. Sanchez (2012) also found the influential role of entrepreneurial competencies on enterprise capacity, performance and competitiveness.

Entrepreneurship is a complex phenomenon that involves a great variety of contexts and factors (Pinillos & Reyes, 2011). Understanding these competencies can promote the development of competencies, which can consequently lead to microenterprise growth (Low & MacMillan, 1988). Studies have attempted to identify the most influential entrepreneurial competencies that affect enterprise performance. However, each is to some extent context dependent. For example, Mitchelmore and Rowley (2013) identified four clusters of competencies among women entrepreneurs, which include (i) personal and relationship, (ii) business and management, (iii) entrepreneurial and (iv) human relations competencies. Similarly, based on earlier studies, Oosterbeek, van Praag and Ijsselstein (2008) demonstrated 10 entrepreneurial competencies dimensions, including the need for achievement, market awareness, need for autonomy, creativity, need for power, social orientation, flexibility, self-efficacy, endurance and risk-taking propensity. According to Hossain, Naser, Zaman and Nuseibeh (2009), the desire for financial independence and having some control over resources, ability to take decision, having some market and informational network, access to start-up capital, specific skills and knowledge are the key contributing factors that affect one’s decision to become an entrepreneur.

There are growing numbers of self-employed women in Malaysia and the performance of their microenterprises is highly dependent on their characteristics and skills. Women micro-entrepreneurs may have certain disadvantages in terms of access to resources, working experience and other socio-economic and cultural context (Carter & Shaw, 2006). As discussed, earlier studies used a wide range of indications to measure the entrepreneurial competencies. However, this study focused on AIM women microentrepreneurs. As AIM only provides access to financial services to poor households (average monthly household income that is below the national poverty line income) and mostly to those located in rural areas, there is a high level of similarities among the borrowers. Moreover, since this study intends to examine the key entrepreneurial competencies possessed by successful micro-entrepreneurs from AIM (in order to improve the overall entrepreneurial competencies among all participants), the focus was on the competencies grounded in the components that are deeply rooted in the micro-entrepreneur’s background. After a detailed review of existing literature along with the local context, this study decided to focus on three main entrepreneurial competencies and examine how they affect the performance of microenterprises owned and managed by AIM’s women micro-entrepreneurs. These include (i) the need for achievement, (ii) cognitive indicators and (iii) entrepreneurial alertness. Need for achievement creates the drive to excel and striving to succeed. Behavioural achievement jointly depends on motivation and ability. Motivation is one of the driving forces for an individual to achieve success. As such, an entrepreneur can be motivated by personal drive or desire to achieve success in his/her business. Cognitive indicators involve knowledge acquisition by an entrepreneur, resulting from entrepreneurial education, and/or training, which is also known as experiential learning. This produces the skills needed to identify and exploit entrepreneurial opportunities. Moreover, it provides learning opportunity for individuals to develop their skills, attitudes and abilities. Finally, entrepreneurial alertness commonly refers to an entrepreneur’s ability to identify and tap into entrepreneurial opportunity in the environment. From the above discussion, this study, therefore, formulates the following hypothesis:

H2: Women micro-entrepreneurs’ entrepreneurial competencies have a significant positive effect on microenterprise performance.

Access to Credit and Microenterprise Performance

Generally, for rural micro-entrepreneurs, access to credit is the main constraint for business start-up and informal sources are the main source of funds for business expansion. Earlier studies have noted that access to finance for SMEs has positively contributed to economic growth, and reduced poverty and inequality (Levine, 2005; World Bank, 2008). Therefore, entrepreneurial development policies frequently address the issue of credit constraints. In Malaysia, the government and non-government organizations provide access to working capital to improve the socio-economic conditions of the poor and low-income households. Among the development organizations, AIM (government-linked company) provides doorstep financial services and enterprise development training to more than 80 per cent of the total poor households in Malaysia.

Study conducted by Sutoro (1990) showed that respondents’ enterprise income increased by 93 per cent, 26 per cent increase in the ownership of productive machineries, about 16 per cent increase in the ownership of business vehicle and 76 per cent increase in household income. Sebstad and Walsh (1991) also noted a positive impact of microcredit on microenterprise sales. Latifee (2003) in his study on Grameen Bank’s microcredit clients in Bangladesh noted that the effect of Grameen loan on reducing unemployment rate among clients and on their households was impressive. He also mentioned that about 90 per cent of borrowers reported an improvement in standard of living. He also noted that poverty rate among borrowers declined significantly and as of 2002, over 46 per cent borrowers have crossed the poverty line. In 2005, Elizabeth Dunn conducted an impact study on ‘Local Initiative (microfinance) Project II’ clients in Bosnia and Herzegovina. The findings of her study indicated that microcredit had a significant positive impact on household income, employment, business investment, business registration and post-war transition. Dunn (2005) also noted that participation in microcredit programme significantly reduced poverty rate among the clients from 51 per cent in 2002 to 46 per cent in 2004. Panda (2009) in his study conducted in India noted a significant increase in borrowers household income (11.41 per cent), asset position was 9.75 per cent higher than non-participants and savings increased by 42.53 per cent. This study also found an increase in annual employment days among the clients. Empirical studies on AIM’s underprivileged clients have noted that access to credit and training has significantly reduced the poverty rate (Al-Mamun et al., 2012), and has reduced the level of economic vulnerability among participating households (Al-Mamun, Mazumder & Malarvizhi, 2014). From the above discussion, this study, therefore, formulates the following hypothesis:

H3: Access to Credit by women micro-entrepreneurs has a significant positive effect on microenterprise performance.

Research Methodology

The primary objective of this study is to examine the effects of education, entrepreneurial competencies and access to credit on microenterprise performance. This study was initiated to reevaluate and elucidate the ‘what and where’ to focus on, in redesigning AIM’s credit and training programmes to further improve the socio-economic conditions of low-income and underprivileged households in Malaysia. This study employed a cross-sectional design and a quantitative approach. Respondents were selected from a list of 601 most successful borrowers and micro-entrepreneurs, based on the length of participation (more than 5 years) and average monthly income from the microenterprise (≥RM5,000). Out of 601 borrowers, only 12 were from the state of Sarawak. Given the isolated location of the borrowers in Sarawak, and the number of borrowers, this study decided not to collect data from Sarawak. The remaining 589 respondents are from Kelantan (146 or 24.3 per cent), Kedah (193 or 32.1 per cent), Pahang (42 or 7 per cent), Sabah (47 or 7.9 per cent) and Terengganu (161 or 26.8 per cent). After receiving the list, the data collection team attempted to contact each of the 589 borrowers for an appointment. A total of 429 or around 72 per cent of the borrowers were reached through the phone. Out of the 429 selected respondents, complete data were collected from 407 successful micro-entrepreneurs from Kelantan (95 out of 146 from Kelantan), Kedah (126 out of 193 from Kedah), Pahang (36 out of 42 from Pahang), Sabah (24 out of 47 from Sabah), and Terengganu (126 out of 161 from Terengganu). A structured interview method was adopted to collect data through a face-to-face interview.

The survey questionnaire was divided into two sections. The first part of the questionnaire includes demographic questions based on personal and enterprise information. The second part of the questionnaire used the five-point Likert scale of 1–5 points (strongly disagree, disagree, neutral, agree and strongly agree) to measure the entrepreneurial competencies. The questions used to measure need for achievement, cognitive indicators and entrepreneurial alertness were adopted from Isaga (2012). Questions used to measure need for achievements are (i) even though people tell you it cannot be done, but you will persist, (ii) you look upon your work simply, as a way to achieve your goals, (iii) you will not be satisfied unless you have reached the desired level of results and (iv) you try to do your job as well as possible even when the tasks assigned to you are difficult. To measure entrepreneurial alertness, this study intended to identify the sources of business ideas generating from their abilities to solve business-related problems and their knowledge about the industry. Cognitive style is defined as a person’s typical or habitual mode of thinking, problem-solving, perceiving and remembering. Questions used to measure cognitive style indicators are (i) you want to have a full understanding of all problems, (ii) you make detailed analyses, (iii) you study each problem until you have understood the underlying logic, (iv) you always want to know what should be done when, (v) you like detailed action plans, (vi) you prefer wellprepared meetings with a clear agenda and strict time management and (vii) you make definite engagements, which you follow up meticulously. After the data were collected, it was analyzed and summarized in an easy-to-understand format for interpretation and tabulations. Analysis started with a descriptive analysis, followed by reliability and validity testing, and the path analysis.

Findings and Discussion

Entrepreneurs’ Demographic Characteristics

As presented in Table 1, all the selected micro-entrepreneurs are women. This is because AIM adopted a group-based microcredit model (the same as Grameen Bank, Bangladesh), and targets women to represent the poor and low-income households, as women are more reliable in repaying debts on time (Gibbons & Kasim, 1990). This study also, therefore, represents the women micro-entrepreneurs in Malaysia.

The five age categories utilized in this study include 20–30, 31–40, 41–50, 51–60 and 61 and above age groups. As noted in Table 1, 204 out of 407 or 50.1 per cent of the respondents are from the age range of 41–50 years. The age of 72 per cent of the selected successful micro-entrepreneurs from AIM is above 41. Only 2 per cent of the respondents are below 30. All these respondents were poor before participation in AIM’s microcredit programme (household income below RM720) and now they are considered successful micro-entrepreneurs (enterprise income of more than RM5000). Based on the age differentials presented in Table 1, it is apparent that experience plays a crucial role in the performance of microenterprises. In addition, women over 40 years of age are expected to have more time for the enterprise and more support from family members, especially from their children. This support from family members and having more time for microenterprises can be crucial in the performance of microenterprises owned and managed by rural women micro-entrepreneurs in Malaysia.

Table 1.

Demographic Characteristics of the Respondents

Category	N	%	Category	N	%
Gender			Age
Male	0	0	20–30	8	2.0
Female	407	100.0	31–40	105	25.8
Total	407	100.0	41–50	204	50.1
			51–60	82	20.1
			Over 60	8	2.0
			Total	407	100.0
Marital status			Education level
Married	380	93.4	Never attended school	9	2.2
Single	1	0.2	Primary school	73	17.9
Separated	2	0.5	SPM	279	68.6
Divorced	10	2.5	STPM/diploma	43	10.6
Widowed	14	3.4	Undergraduate degree	3	0.7
Total	407	100.0	Total	407	100.0

Source: Author’s own.

As per the marital status, 380 out of the 407 respondents are married, 14 or 3.4 per cent are widowed, 10 or 2.5 per cent are divorced and only one respondent is single. Marital status data show a strong family bond among the respondents. With regard to the level of education among the successful micro-entrepreneurs, findings in Table 1 show that around 80 per cent of the respondents have completed Sijil Pelajaran Malaysia (SPM) and above (SPM or Malaysian Certificate of Education is a national examination taken by all fifth-year secondary school students).

Participation in AIM’s Microcredit Programme

The successful micro-entrepreneurs were selected based on their enterprise income and length of participation. As noted in Table 2, the mean length of participation among respondents is 166.22 months or nearly 14 years, with a standard deviation of 50.84 months or 4.2 years. Length of participation is one of the independent variables used in impact studies where the researcher tries to examine the effectiveness of any development initiatives. This is because the higher the length of participation, the higher the amount of credit clients are able to receive, which in turn is expected to lead to a higher income.

As per the economic loan (loan received for income generating activities), the mean economic loan received by respondents is around RM80,000 with a standard deviation of RM61,137. The higher standard deviation indicates that some micro-entrepreneurs’ borrowings are much higher than that of others. Although the average amount per year (RM80,000/14 years) is RM5,714, it is not much to improve the microenterprise’s performance (all borrowers’ micro-enterprise income per month is ≥RM5,000). Furthermore, the high standard deviation associated with economic loan indicates that a significant number of micro-entrepreneurs are not actually borrowing much.

Table 2.

Participation in Microcredit Programme

n = 407	Mean	Std. Dev.
Length of participation (months)	166.22	50.835
Amount of ‘Economic Loan’ received from AIM (RM)	80,281.49	61,158.234

Source: Author’s own.

Microenterprise Characteristics

Among the 407 microenterprises owned by respondents, 43 or 10.6 per cent have been established for 1–5 years, 112 or 27.5 per cent have been established for 5–10 years, 123 or 32.2 per cent have been established for 10–15 years, 64 or 15.7 per cent have been established for 15–20 years, 41 or 10.1 per cent have been established for 20–25 years and 24 or 5.9 per cent have been established for more than 25 years. Findings show that around 70 per cent of the total microenterprises owned and managed by microentrepreneurs were started more than 10 years ago. The overall experience of owning and managing the microenterprises for such a long period can be one of the key factors contributing to the performance of micro-enterprises, which ultimately leads to the recognition of the respondents as the most prosperous borrowers and micro-entrepreneurs of AIM.

With regard to the main activities of the microenterprises, 140 or 34.4 per cent of the 407 microenterprises are involved in manufacturing activities, 170 or 41.8 per cent are involved in retailing and the remaining 97 or 23.8 per cent are wholesalers. As per the principal decision maker of the microenterprises, 113 or 27.8 per cent of the respondents reported that they take all major decisions regarding their microenterprise on their own. However, 245 or 60.2 per cent reported that they make decisions regarding the microenterprise jointly with their spouses. For 12 per cent of the microenterprises, the respondents’ spouses or other relatives are the principal decision makers in the management of microenterprises owned by the respondents.

Reliability Measures

The Cronbach’s alpha values, as presented in Table 3, for all the indicators are more than 0.75, which is more than 0.7, and therefore considered reliable. Moreover, the composite reliability, which takes into account the indicators that have different loadings for all items, is more than 0.85, which is higher than 0.7 (Hair, Ringle & Sarstedt, 2013), and therefore considered reliable. Convergent validity signifies that a set of indicators represents one and the same underlying construct, which can be demonstrated through their unidimensionality. The average variance extracted (AVE) values for all items, except for entrepreneurial competencies, are more than 0.5, which indicates sufficient convergent validity.

Indicators are assumed to be reliable if the absolute standardized outer (component) loadings are higher than 0.7. As noted in Table 4, all items of need for achievement (NFA, four items), cognitive indicators (CI, seven items), entrepreneurial alertness (EA, two items) and microenterprise performance (MP, two items) are seven, and therefore assumed to be reliable. However, only two out of 13 items used to measure entrepreneurial competencies are more than 0.5, while seven out of 13 items are more than 0.6 and the remaining five items are more than 0.7.

Table 3.

Microenterprise Characteristics

Category	n	%	Category	n	%
Main activity of the microenterprise			Duration of microenterprise establishment
Manufacturer	140	34.4	1–5 years	43	10.6
Retailer	170	41.8	5–10 years	112	27.5
Wholesaler	97	23.8	10–15 years	123	30.2
Total	407	100.0	15–20 years	64	15.7
			20–25 years	41	10.1
Principal decision maker			Over 25 years	24	5.9
Respondent	113	27.8	Total	407	100.0
Spouse	41	10.1
Client and spouse	245	60.2
Other relatives	8	2.0
Total	407	100.0

Source: Author’s own.

Table 4.

Descriptive and Reliability Measures

	Number of Items	Descriptive		Reliability
	Number of Items	Mean	Std. Dev.	CA	CI	AVE
NFA	4	4.4042	0.5229	0.785	0.861	0.608
Cog I	7	4.2327	0.5555	0.866	0.897	0.556
EA	2	3.9521	1.0229	0.858	0.934	0.876
LR	1	80,281.5	61,158.2	n.a.	n.a.	n.a.
EDU	1	2.9000	0.6240	n.a.	n.a.	n.a.
EC	13	4.1963	0.5672	0.894	0.911	0.443
MEP	2	2.5676	1.7821	0.966	0.983	0.967

Source: Author’s own.

Note: NFA: need for achievement; Cog I: cognitive indicators; EA: entrepreneurial alertness; LR: loan received; EDU: level of education; EC: entrepreneurial competencies; MEP: microenterprise performance; CA: Cronbach’s alpha; CI: composite reliability; and AVE: average variance extracted.

The cross-loadings are checked for discriminant validity. If an indicator has a higher correlation with another latent variable than with its respective latent variable, the appropriateness of the model should be reconsidered. As noted in Table 5, cross-loading values are far below the outer loadings, which suggest good discriminant validity. The Fornell–Larcker criterion assesses the discriminant validity at the construct level. As noted by Hair et al. (2013), the AVE of each latent construct should be higher than the construct’s highest squared correlation with any other latent construct. The Fornell–Larcker criterion in Table 5 is largely unable to detect a lack of discriminant validity. Furthermore, the Heterotrait–Monotrait Ratio (HTMT) is an estimate of the correlation between constructs, which parallels the disattenuated construct score creation. Using a value of 0.9 as the threshold, this study concluded that there is no evidence of a lack of discriminant validity.

Path Coefficients

Verifying the reliability and validity of the outer model allowed an evaluation of the inner path model estimates. The coefficient of determination (r²) of three endogenous latent variables, that is, loan received, respondent’s level of education and entrepreneurial competencies, is relatively low. However, this r² value is acceptable because this study is not designed to identify how much the key factors together affect performance; rather, it attempts to identify direction and significance only of each of these three factors.

The path coefficients, as presented in Table 6, show that the total loan received by respondents, respondents’ entrepreneurial competencies and education, have a significant (at the chosen 5 per cent level of significance) positive effect on their microenterprise performance. Among them, total loan received by micro-entrepreneurs has a relatively higher effect on microenterprise performance, followed by micro-entrepreneurs’ level of education and entrepreneurial competencies. The effect size (f²) is calculated as the increase in r² relative to the proportion of variance of the endogenous latent variable that remains unexplained. As shown in Table 5, all three significant exogenous latent variables, that is, loan received, entrepreneurial competencies and education, have a relatively small effect size.

Table 5.

Outer Model Loading and Cross-loading

	NFA	Cog I	EA	EC	MEP
NFA-1	0.761	0.453	0.260	0.602	0.018
NFA-2	0.798	0.540	0.488	0.713	0.080
NFA-3	0.775	0.504	0.214	0.632	0.073
NFA-4	0.783	0.506	0.249	0.641	–0.010
Cog I-1	0.560	0.796	0.366	0.769	–0.006
Cog I-2	0.483	0.713	0.310	0.680	0.073
Cog I-3	0.380	0.713	0.354	0.651	–0.022
Cog I-4	0.463	0.793	0.295	0.719	0.010
Cog I-5	0.537	0.774	0.344	0.743	0.029
Cog I-6	0.467	0.723	0.348	0.688	0.104
Cog I-7	0.455	0.698	0.253	0.650	0.048
EA1	0.367	0.427	0.938	0.573	0.126
EA2	0.373	0.388	0.933	0.550	0.145
MEP1	0.048	0.038	0.143	0.068	0.982
MEP2	0.056	0.049	0.142	0.077	0.984
Fornell–Larcker Criterion
NFA	0.780
Cog I	0.644	0.745
EA	0.369	0.436	0.936
EC	0.832	0.941	0.600	0.665
MEP	0.053	0.044	0.145	0.074	0.983
HTMT
NFA
Cog I	0.776
EA	0.473	0.505
EC	0.995	1.059	0.709
MEP	0.059	0.049	0.160	0.083

Source: Author’s own.

Note: NFA: need for achievement; Cog I: cognitive indicators; EA: entrepreneurial alertness; EC: entrepreneurial competencies; and MEP: microenterprise performance.

The predominant measure of predictive relevance is Stone–Geisser’s Q², which postulates that the model must be able to provide a prediction of the endogenous latent variable’s indicators. The Q² values of the three endogenous latent constructs, that is, loan received, entrepreneurial competencies and education, are more than 0, which is indicative of the predictive relevance. Moreover, the q² value measures the predictive relevance for the exogenous latent variables. The q² values revealed that the total loan received by micro-entrepreneurs has a relatively higher predictive relevance on microenterprise performance, followed by micro-entrepreneurs’ level of education and entrepreneurial competencies.

Table 6.

Path Coefficients

	Path Coefficient	t	p	r²	f²	Q²	q²
NFA –> EC	0.351	22.123	0.000		36,219.17
Cog I –> EC	0.634	32.551	0.000	1.000	113,789.12
EA –> EC	0.185	14.771	0.000		13,932.63
EC –> MEP	0.089	1.781	0.038		0.008		0.0010
LR –> MEP	0.139	2.646	0.004	0.034	0.019	0.023	0.0154
EDU –> MEP	0.106	1.989	0.024		0.011		0.0072

Source: Author’s own.

Note: NFA: need for achievement; Cog I: cognitive indicators; EA: entrepreneurial alertness; EC: entrepreneurial competencies; EDU: level of education; and MEP: microenterprise performance.

Conclusion

This study aimed to identify how the total amount of loan, education and entrepreneurial competencies affect the microenterprise performance of AIM’s most successful micro-entrepreneurs. Findings of this study revealed that the ‘total amount of loan received’, ‘entrepreneurial competencies’ and ‘level of education’ have a significant positive effect on microenterprise performance. Among these three, total loan received by micro-entrepreneurs has a relatively higher effect on microenterprise performance, followed by micro-entrepreneurs level of education and entrepreneurial competencies. This study was undertaken to identify ‘where to focus’ in order to design and provide better financial services to improve the socio-economic conditions of low-income micro-entrepreneurs in Malaysia. Since the findings have shown that the total amount of credit received has a relatively higher effect on microenterprise performance, AIM should focus more on providing a more supportive environment for loan processing, along with identifying the types of loans that borrowers need, the maximum loan limit, repayment schedule and repayment flexibility. Although all the borrowers are poor before participating, many of them are no longer poor as their businesses have expanded over the years. A flexible credit programme and a higher amount of credit may enable micro-entrepreneurs to borrow a higher amount of credit when they need, and retain the successful clients who otherwise may move to other sources. A flexible credit programme can enable micro-entrepreneurs to borrow more to take advantage of short-term business opportunities.

Findings of this study also reported that around 80 per cent of the respondents have completed SPM and above, and respondents’ level of education has a significant positive effect on microenterprise performance. This provides a unique opportunity for AIM to design a more sophisticated and specialized training programme for different types of enterprises and sizes of enterprises to improve entrepreneurial competencies among the relatively educated borrowers, instead of offering one-size-fits-all type of programmes. Moreover, besides a formal trainer, AIM can use their successful micro-entrepreneurs in sharing their experience to motivate and provide crucial information to the others. An advisory board from successful entrepreneurs from all sectors can be formed to provide solutions to specific problems commonly encountered by micro-entrepreneurs. Concrete understanding of what borrowers need and why they need it can further motivate the borrowers to start new enterprises. Sharing real-life experiences with successful borrowers, who were just like them a few years ago, can be a great motivator.

On the whole, a flexible credit programme, a higher amount of loan, specialized training programmes, an advisory board and sharing of experiences can lead to an increase in the microenterprise performance among the low-income households in Malaysia. However, it is imperative to note that the suggestions presented above in response to the findings are intended to be neither exhaustive nor absolute. Rather, this study has attempted to offer some thoughts for discussion based on what other development organizations are doing and the issues highlighted in the earlier studies.

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