Institutional and Resource Based Factors That Impacted Sales Growth of Namibian SMEs in 2014

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Abstract

INSTITUTIONAL AND RESOURCE BASED FACTORS THAT IMPACTED SALES GROWTH OF NAMIBIAN SMALL AND MEDIUM ENTERPRISES (SMES) IN 2014

ABSTRACT

This thesis aims to investigate the impact of institutions and resources on SME sales growth in Namibia. It looks at how these factors in different ways impacted SMEs sales growth through analysing the internal and external operating environment. The paper uses an SME survey done in Namibia by The World Bank Enterprise Surveys from April 2013 to March 2014 in Namibia. Firm-level data was collected using a questionnaire and this paper uses a linear regression model to analyse the magnitude the various constraints had on the sales growth of the SMEs. The analysis offers important insights into the business environment in Namibia. Factors like age of the firm, political connections, government tax policies; access to finance, management experience and ownership of land all impacted the sales growth of the SMEs.

Factors such as difficulty in accessing finance have had a negative impact on sales growth. The reason being smaller and younger firms are viewed as high risk and most likely to default on payments by financial intuitions.  Another finding was that the competitive environment that SMEs operate in is characterised by formal and informal traders. Doing business in these environments is not an easy task hence most managers of the SMEs reported improving their products and marketing strategies. Another key finding was the lack of ownership of land negatively impacted sales growth as land can be used as collateral to acquire loans. This limited the borrowing power of most SMEs who did not have enough capital to grow their business. This research can be of interest to studies of SMEs in the institutional and resource based contexts, and it contributes especially to the accumulation of knowledge on SMEs in developing countries by looking at the Namibia, a country that has not been researched much about before in this field.

Keywords-Small and Medium Enterprises (SMEs), Institutions, Namibia, Land, Resources

Table of Contents

Table of Contents

摘要

ABSTRACT

List of tables

List of figures

Section 1 Introduction

Section 2 Literature Review

2.1. Definition of Small and Medium Enterprises (SMEs)

Section 3 Theoretical framework

3.1 Institutional Framework

3.2 Resource Based View

Section 4 Hypotheses Development

Section 5 Data and Methodology

5.1 Sample and data sources

5.2. Data selection

Section 5 Data and Methodology

5.3. Sample Size and selection

5.4. Variables

Section 5 Data and Methodology

Section 6 Empirical model and results

6.1 Empirical Results

Section 6 Empirical Model and results

Section 7 Discussion of Results

Section  7 Discussion of Results

Section 7 Discussion of Results

Section 8 Conclusions and Limitations

References

Appendix

Acknowledgements

The Originality Statement for Dissertation and the Authorization Instructions

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List of tables

Table 1. SME’s Data…………………………………………………….…….…….4

Table 3. Key factors impacting growth in Small firms…….………..………………14

Table 4. Post-Entry Barriers to Firm Growth…………………………………….….15

Table 5. Descriptive Statistics………………….……………………………………..30

Table 6. Correlation Matrix……………………………………………………………31

Table 7. Regression Table…..…………………………….……………………..…….31

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List of figures

Figure 1. Key factors affecting SMEs growth ……………………………..…….….6

Figure 3. Resources affecting firm growth……………………………….…………..17

Figure 4. Conceptual model……………………………………………….………….20

 

Section 1 Introduction

Section 1 Introduction

In the past policy makers believed large firms were the motor of the economy within a country (Galbraith et al., 1976). Perceptions are changing and small businesses are increasingly being seen as the drivers of entrepreneurship, economic growth, innovation and job creation. Small and Medium Enterprises (SMEs) play a vital role in economic development as they have been the main source of employment generation and output growth, both in developing and developed countries (Love and Roper, 2013). Before SMEs can reach the status of being the motor of the economy they must first overcome domestic barriers that hamper their expansion into the global market. Much of early research on firm growth focuses on size and age; subsequent studies have uncovered the roles management ability has on firm performance and growth (Storey, 1994).

This study looks at the data provided by the World Bank Enterprise Surveys for Namibia and from analysing the data management experience had a major role towards a firm’s competiveness as management is the driver of technological progress (Romer, 1990) and setting strategic growth objectives for the firm. The relevant type of experience can be used as criteria in evaluating business plans for loan applications and also as basis for tailoring development (Dyke, et al, 1992). Venture capitalists also emphasise general management or technical experience when evaluating the attractiveness of new ventures (Stuart, 1990). With the underlying hypothesis that management experience positively impacts sales growth in SMEs, this paper aims to investigate if management experience did grow SMEs sales.

Namibia is one of fastest growing economies in Africa, and this provides an enabling environment for businesses to expand (IMF, 2012). Access to finance and access to land are some of major perceived obstacles to growth that challenged Namibian firms. Institutional factors cannot be influenced by the firm, they are out of the firms control. Institutional forces are from the external environment and some studies argue that they are the main determinants of a firm’s growth. To reach its economic potential Namibia will have to change policies that make access to finance and owning land easier for SMEs. Globalisation has also impacted the sales growth of firms as SMEs find themselves facing increased competition from goods imported from China which are cheaper (Bessant and Tidd, 2007).

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The informal sector makes up a large chunk of the businesses operating in Namibia and it employed 15.2% of the population in 2006. This increased competition impacts the growth of SMEs as they scramble to develop marketing strategies and new products that enable them to stay competitive. Stagnant or unproductive firms will not last long in the marketplace as their competitors begin to outpace them (Geroski, 1999). It is important in competitive markets to have a marketing strategy that is aimed towards acquiring new customers as well as retaining old ones. Hence a marketing mix that is suited to the market has to be constantly renewed at a pace that either matches or outweighs the competitors.   Failure to stay relevant leads to the high failure rate of SMEs as shown by a study of 1000 firms done by the Small Business Administration in the United States of America which found that 24% of all new businesses failed within two years, and that 63% failed within six years (Wheelen and Hunger, 1999). In most developed countries the growth of SMEs has been well documented and in other less developed countries acquiring data about SMEs is not an easy task.

Substantial research that has been conducted has shown a positive relationship between the relative size of the SME sector in a country and economic growth (Beck et al., 2005), with SMEs typically comprising over 90% of all firms in both low and high-income countries (OECD, 2005). Most academic research focuses heavily on the effect of capital and labour constraints on firm growth. Firms in developing countries rarely have ownership of the land necessary to complement most of their capital inputs. Hence this paper aims to show an assessment of land ownership and political connections as well as other institutional and resources and see how these impacted sales growth in Namibia. This will complement current academic and policy discussions on SME growth in developing countries. The contribution of my thesis is that I am looking at the factors that affected SME sales growth in Namibia which is a country where little research has been done about SMEs and also how access to land impacted sales growth.

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Section 2 Literature Review

SMEs are defined as non-subsidiary, independent firms which employ fewer than a given number of employees (OECD, 2000). SMEs are defined by their size and different countries and regions have different definitions. This makes it complicated to have one universal definition of an SME as it is determined by a lot of factors such as business environment, industry and a country’s population to name a few.

In Africa the definition of SMEs is varies since different countries have different cut off points based on employee size. Europe has a more standardized definition bases on employee size as shown in Table 1 below. However the World Bank recommends that SMEs in Africa adopt a more uniform definition of an SME.  This will make policy planning easier and lead to more sustainable growth.

Table 1 SMEs data

Africa Small Medium
Egypt 5 to < 14 15 to < 49
South Africa 21 to <  50 51 to < 200
Nigeria 11 to < 100 100 to < 300
Namibia 5 to <  19 20 to < 99
Europe < 50 < 250

 Source: World Bank

 

SMEs in Namibia engage in a wide range of activities such as:

Crafts- (woodwork, pottery, handicraft, basketry, jewellery-making, leatherworking),

Small-scale construction – (building, brick-making, plumbing, welding, carpentry and electricity);

Section 2 Literature Review

Small-scale mining;

Informal services- (transport, repairs of cars, shoes, electric household appliances, subsistence farming; weaving, sewing, and furniture-making);

Small scale manufacturing – (including: bread making, tailoring, food catering, candle making, and confectionery);

Informal trade, urban information markets, informal cross-border trade, informal meat markets and informal/illegal diamond smuggling (van der Linden, 1993).

The Namibian Chamber of Commerce and Industry reported that the SME sector contributed 14% to the national GDP in 2014 (refer to table 1) for additional SME contributions to African employment.  In Europe SMEs represent 99% of all businesses and have created around 85% of employment (OECD). Growth of SMEs can be measured using various indicators such as market share, profits, a firm’s output and asset value. These indicators are not as commonly used as compared with sales and employment. This thesis looks at sales growth as the main indicator of SME growth. This is also supported by studies by (Steiner and Solem, 1988), and the US Small Business Administration (1980) which used sales growth as a key indicator of small business success and overall performance. However (Rodriguez et al., 2003) argues that there is no single theory which offers a generalized framework on SME growth.

As observed by (Hart, 2000) most studies relating to periods since 1985 show that small firms grow more quickly than larger firms.  Despite these fast growth rates SMEs also have high failure rates as they are more susceptible to external and internal business environment changes. JP and Morgan in South Africa reported that approximately 50% of SME’s, fail within the first two years. This is because small firms have to cope with additional constraints of size and limited resources in comparison with large firms (Acs and Audretsch, 1988). According to research done by the USAID on SMEs in the developing countries in 2005 the following factors in Fig.1 below were found to be the key factors affecting SMEs growth.

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Figure1. Key factors affecting SME growth

Source: USAID

Firm growth has important effects for the domestic economy since many times an increase in firm growth causes increased demand in other sectors of the economy, which results in extensive economic growth. Technological advances to keep and stay ahead of the competition can have spill over effects through knowledge sharing.  This creates backward and forward relationships which aids in building a more balanced growth, as firms outside regional economic hubs are included in the value chain. SMEs in Namibia reported receiving trade credit from suppliers to be very useful towards growing the business. This is especially useful because the SMEs can acquire the goods and pay at a later date, rather than halt business operations and lose customers.

An empirical study was done by Hart where he compared growth among UK and US firms, and found that while firm growth is largely random, certain systematic factors like capital investment and research and development impact growth, though there is a low probability for the influence of these factors to remain present in the long-term (Hart, 1999). This shows the importance of taking into account individual firm characteristics such as their management experience, as Hart found that research and development is highly likely to be positively correlated with management ability.

Section 2 Literature Review

Human capital makes a critical contribution to post-entry small firm performance (Storey, 1994). Storey put small firm growth factors in three categories: entrepreneur-specific factors, firm-specific factors, and strategy-specific factors (as shown in Table 3). This theory states that firms will try to maximize their growth if they are able to optimize factors from all three categories.  Some of the factors which affect firm growth can be controlled and some are not controllable, leading economists to include another important characteristic of firm growth: randomness. Hence from this standpoint growth of the firm is not generated only by a collection of governable factors, but also a series of unforeseen events that affect the firm’s growth.

Table 3, Key factors impacting growth in Small firms

Entrepreneurial Organizational Strategic
Education

Management experience

Prior self- employment

Training

Prior sector experience

Prior firm size

Gender

Sector

Legal form

Location

Size

Ownership

Workforce training

Market positioning

New products

Management recruitment

State support

Competition

Source: Storey, 1994

SME’s face other barriers that can affect their growth (see Table 4). Firms must then rely on collaborations with other contributors to firm growth as well as supportive policies that exist within the environment for rapid growth. For example, management capabilities can be controlled by the firm, but policies that govern access to land or finance are heavily impacted by policies from the government and banks. This creates the need for the government to research and create policies that reduce the constraints SME’s face towards growth. In Namibia access to land is a major obstacle and to tackle this, the government has introduced policies aimed at redistributing land among the less privileged and it has also introduced the willing buyer willing seller.

Section 3 Theoretical Framework

Section 3 Theoretical framework

3.1 Institutional Framework

An institutional framework was defined by (OECD, 2003), as a set of governmental and other institutions responsible for the design and implementation of policies. However there is no common definition that is accepted either within or across various social sciences (Vatn, 2005). There is hardly any debate on a key proposition in the institution-based view of entrepreneurship: institutions matter (North, 1990). Institutions guide managers and firms to rationally pursue their interests and make strategic choices within the formal and informal constraints in a given institutional framework” (Peng  etal 2009: 67).

According to (Bartlett et al., 2001) the institutional framework within which firms interact with customers, government and each other can have a profound influence on firms’ economic performance. Looking from the institutional theory standpoint, North (1990) said that, the institutional framework of a society comprises the fundamental political, social, and legal ground rules that establish the basis for production and distribution, and organizations must conform to it if they are to receive support and legitimacy. Present institutions in any society can help or harm SMEs development such that they can serve as restraints and/or provide incentives for SMES to flourish (Roxas, et al,. 2006).

The business environment and policies set in place also determine the boundaries of firm financing which has a major impact on innovation, size, location and other factors for SMEs. A study done on China SMEs found the top five institutional barriers as perceived by the business owners to be competition fairness, access to financing, laws

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and regulations, tax burden, and public support systems (Yanmei, et al., 2011). Furthermore (Store, 1994; Smallbone and Welter, 2009) state institutional determinants can be manifested in corruption, legal systems level of crime and functionality of judiciary systems. All these factors from the results of the Enterprise survey affect Namibian SMEs in their own varying degrees.

This paper looks at the institutional problems that impact sales growth as perceived by the managers or owners of the surveyed SMEs. Researchers have used the institutional perspective based on the institutional theory to analyse the impact of both formal institutions and informal activities on the development of entrepreneurship in the transitional environment, (Feige, 1997; Van de Mortel, 2002; Aidis, 2006; North, 1990).

Global Financial Integrity has estimated that illicit financial flows, from bribery and corruption and also from theft and tax evasion, cost developing countries US$1.26 trillion each year; an estimated €120bn is lost to corruption each year within the 27 member states of the EU alone (Malmström 2011). A culture of bribery will always facilitate and perpetuate unfairness and inequalities, both of which tend to have wider

social and economic consequences in the longer term. The problem with such a culture is that for a business to operate in such a corrupt environment they also have to pay the bribes resulting in an ongoing culture where inefficient business practices will continue.

Corporate finance theory suggests that market imperfections, such as those caused by underdeveloped financial and legal systems, may constrain firms’ ability to fund investment projects (Beck et.al, 2002).  The World Bank alone has approved more than $10 billion in SME support programs, and still the basis for supporting SMEs’ access to capital remains unclear. In a study carried out in Ghana it was found the main financial challenge facing SMES in Ghana was the access to affordable credit (Tagoe et al.2005). Further studies by (Wolf, 2004) observed that, interest rates, access to credit, depreciation and inflation as the important finance obstacles faced by SMEs in Ghana. The absence of viable or bankable projects are cited by bankers as the reason attributing to the high financial rejection rates

Section 3 Theoretical Framework

among SMEs and business owners state it also is because they were not seen to have good collateral (Aryeetey, et al., 1994).  In a study done in SMEs in Romania access to loans was found to be an important determinant in sales growth (Brown, et al, 2005). Additional results of this study also found that external financing is a huge constraint to the overall firms’ growth.

Cross-country evidence shows that small and medium enterprises are more constrained in their operations and growth than large enterprises and access to financial services features importantly among the constraints (Ayyagari, Demirgüç-Kunt and Maksimovic, 2006). Financial and institutional development helps create a level playing field between small and large firms, while the lack of an effective financial system explains the phenomenon of the missing middle observed in many developing countries (Beck, 2007).

The World Bank competition policy states that productivity is driven by competition and this shifts market share toward more efficient producers, and it induces firms to become more efficient so as to survive. However that only applies

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when competition is done right. SMEs face major competition from larger firms, the unregulated informal sector and sometimes preferential treatment of other competitors that is not legal. Given the financial constraints they will be under they cannot invest highly into marketing promotions. In a study done in China 67% of SMEs interviewed unfair competition as their main constraint to innovation which then impacts their sales growth. Large firms both domestic and foreign tend to corner or monopolize the  market due to preferential treatment by the government and broader access to resources (Yanmei, et al., 2011).  This led to China to create the Unfair Competition Law in light of the fast pace of private sector development, which created the need for rules to govern competition, as these unfair practices  made it difficult for small firms particularly in their early stage of formation to grow.

Regulation occurs when a government exerts control over the activity of individuals and firms. Through regulation the government can manage the economy to achieve sustainable social and economic outcomes. Laws can also be used to protect small businesses and create an environment and policies that foster their growth. Governments also pass laws that control how they collect revenue and manage property. These can be in the form of trademarks protection, copyright protection and bankruptcy acts. In a study done in Bulgaria they found that the legal framework is one of the biggest obstacles to firm growth (Manolova, et al, 2002). The same can also be said for Polish SMEs where they found that non-transparency in laws and regulations had the yielded strong negative results to firm growth (Balcerowicz, et al,. 1998).

In China because of a lack of concrete regulations and/or clear policies at the operational level SMEs are still disadvantaged as policies on how to assess intangible collateral are still missing (Zhu et al, 2009). In South Africa regulations are intended to achieve at least two objectives (Liebenberg et al, 2007) with the first objective being to promote healthy market competition and to control consumers and small businesses during their operations. To achieve these objectives the state has to have

Section 3 Theoretical Framework

proper evaluation, implementation and monitoring strategies. The second objective is to alleviate any negative effects of company activities on the environment and other organisations within the society (Banjtes et al, 2006). However in the developing countries there is still need to create and properly implement policies that nurture the SME business environment.

Infrastructure matters in all areas of the economy for economic growth as it is one of the major drivers of economic development.               A lack of good infrastructure can be a big impediment to SME growth. Transportation and telecommunications systems are very important as they both aid the delivery of goods timeously to keep customers satisfied. A study in the USA found that SMEs located in areas of high infrastructural development were also accompanied by high growth rates (Munel, 1990). These infrastructures noted were roads, highways, and water and energy supply capacities.

Land lies at the heart of the economic, social and political life of most African countries (UNECA, 2010). In Africa agriculture and natural resources form the backbone of economic development.  In the rural and urban populations mining, farming, tourism (dance, sculpture) creates employment and offer income for people. Most of the population relies on land for their livelihood and sustainability. However, land in Africa is not only an economic asset; it has major historical, political, cultural and spiritual significance. Good governance of land and natural resources contributes to conflict prevention, consolidation of peace and public security (UNECA, 2010).

From the 1990s there land policy formulation has been intensively done across most of the African Continent. National land policy frameworks are now in place in Botswana, Malawi, Mozambique, Namibia, South Africa, Tanzania and Zimbabwe (UNECA, 2010). In Namibia in the Enterprise surveys the second biggest obstacle to SME growth was access to land. This then brings about the issue of how the land institutions and policies set in place by the Namibian government are meeting and sustaining business growth.

Section 3 Theoretical Framework

3.2 Resource Based View

The idea of viewing a firm as a bundle of resources was pioneered by Penrose in 1959 who stated that it was a firm’s heterogeneity of the productive services available from its resources that give each firm its unique character. The resource-based view of the firm rests on two basic premises that the resources are the foundations that provide the direction for firm’s strategy, and that resources are the primary source of a firm’s performance (Grant, 1991).  These resources can be tangible or intangible such as employee’s knowledge, experiences and skills, firm’s reputation and organizational procedures and can include in-house technology and the employment of skilled personnel (Dollinger, 1995). A firm’s resources and competencies are the basics for establishing and sustaining competitive advantage. The four key attributes a firm must have in order to raise the sustainable competitive advantage are valuable, rare, imperfectly mobile, and non-substitutable (Barney, 1991).

Entrepreneurs may be seen as a unique resource embedded in their human capital from a resource based perspective (Alvarez and Busenitz, 2001; Bowman and Swart, 2007). Human capital is shaped through education and previous entrepreneurial experience (Brüderl et al 1992). Hence a higher education offers greater technical knowledge and thus adds favourably to growing individual learning capabilities to process new information and also, recognize business opportunities (Shane, 2000).  Having previous entrepreneurial experience regardless the final result of this experience may be the best preparation for the entrepreneurial role according to (Brüderl et al. 1992).

A firm’s location is important. In China for example industrial clusters are located in the special economic and export processing zones of coastal areas (Janson et al., 2007). The growth issue also could be enhanced by the competitiveness of the firm and the external features of the cluster, e.g. cost advantages due to the co-location, access to competent personnel, information and joint marketing, as well as connections to institutions and public goods (Porter, 2000).

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Brand image has long been considered as a resource (Barney, 1991). Brand image is important as it makes a firm differentiate itself from other competitors.  It is generally accepted by small business managers that a good corporate reputation is important to receive support from different stakeholders (Goldberg et al., 2003). High-performing SMEs implement key brand management to a greater extent than low-performing SMEs (Berthon et al., 2008). If SMEs are focused on improving their brand they can achieve a clear performance advantage over competitors by understanding their customers’ needs and brand perceptions. This will enable them to create brands that are valued by their customer base and make them stay relevant in the in the business environment.

The advantages for small firms come from their flexible managerial structures, which can respond quickly to changes in the business environment. SMEs are always highly dependent on external knowledge sources, and technological innovation is important for a small firm (Steward and Gorrino, 1997). Information and technology can give firms a head start into new channels of business. Hence if a business has the capabilities it can enter new markets and in turn have the first mover’s advantage.

Tangible resources

-IT systems

-Equipment

SMEs sales growth

Intangible Resources

-Human Capital

-Brand

-Internal and external financing

Source: Authors Illustration

Figure 3 Resources factors which affect firm growth

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3.3. The interrelationships between resource and institutional factors

There are numerous reasons why some proponents of these two theories a relationship. They both look at different domains where the resource based looks at the internal aspects and the institutions looks at the external environment of the firm. However there are some instances when some internal factors can influence different responses from the external environment.

Studies done previously show that female owned SMEs project a lower growth rate compared to their male owned firms and this was partly due to poor access to debt financing. Studies done in Ghana by (Abor and Biekpe, 2006) showed that that male-owned SMEs are significantly more likely to have easier access to and to employ more debt financing Previous studies have highlighted sexual stereotyping and discrimination in the lending process, which places women at a disadvantage. Hence this supports the results from earlier studies that female-owned firms have greater difficulty accessing debt finance (Coleman, 2000).

In Namibia they have developed preferential requirements for SMEs owned by people from previously disadvantaged backgrounds and they will be considered during Tender Board Meetings. A Public Procurement Bill was passed in 2013 which aims to “promote preferential treatment in the allocation of procurement contracts and the advancement of persons or categories of persons who have been socially, economically or educationally disadvantaged by past racially discriminatory laws or practices.” Hence these highlight that government backed initiatives and laws can influence the competitiveness of SMEs as they may receive preferential treatment over other counterparts. This will in turn impact their growth and sustainability.

Complex tax laws and procedures intensify the likelihood of corruption in the tax system. Sometimes SME owners do not have access to the proper information and this makes them unaware of their rights and as they become more exposed to discretionary treatment and exploitation. A common phenomenon in many middle-income countries such as India is the extreme unwillingness of taxpayers to comply with the law. This in turn may increase their likelihood and readiness to bribe tax collectors in order to reduce their tax liability.

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Section 4 Hypotheses Development

Based on the literature review the following conceptual model with the variables which will be used in the empirical analysis was developed. The variables where reduced by rejecting those that did not comply with the literature. This framework is  to test the effect of the independent variables on the dependent variables. Variables were chosen and selected on their theoretical and empirical importance. (see figure 4).

Independent Variables

Institutional factors

  • Access to finance
  • Government Tax policies

Dependent variable

Sales growth

Resource factors

  • Marketing Strategies
  • Management Experience

Control Variables

  • Firm Age
  • Size
  • Location

Contribution

  • Land
  • Political Connection

 

 

Figure 4 Conceptual model: relationship between independent constructs on SME sales growth

Source: Author’s Illustration

 

Section 4 Hypothesis Development

Political Connection

From research it has been found that firms with political connections could be able to secure preferential access to loans and financing (Johnson and Mitton, 2003). However some studies have shown that political connections may improve or reduce firm value and performance (Liu et al., 2010). In Namibia SMEs would use their political connections to get reduced tax payment, and some would use them to get an electricity and water connection to start business operations ahead of competitors without connections. These competitors will be waiting for the general municipality to cnnect for everyone. This then gives the firms with electricity connections aa headstart on theor rivals and in turn increase their sales.

H1: Political connection positively impact impacts sales growth

Government Tax Policies

Tax policies can put pressure on SMEs as finances that can be used for aiding future growth will be used for payment of taxes.  Reduction in tax rates increases the profit margin of SMES as well as intensifying government tax revenues since such provisions reduce the size of the shadow economy (UNESCAP, 2009). Tax policies that are not implemented properly can result in low efficiency and productivity by SMEs. Currently the government has been working on making the business climate more favourable for SMEs by making the tax policies more favourable toward them. However s many factors come into play as some SMEs do not employ a Tax professional to help with tax submissions and thus get the deductions due to them, as they want to reduce operating costs. Also the government has a set tax rate for all SMEs based on number of employees. This is a disadvantage as the SMEs are all employed in different sectors and this varies their tax margins greatly. Thus:

H2: Government Tax policies negatively impacts sales growth

Finance

The general assumption is that the growth of a firm is enabled by access to finance and a lack thereof then mean that the growth of a firm is constrained. Lack of access to financing has been identified in many countries as one of the most significant obstacles to the survival and growth of SMEs (Acs, et al, 1999; OECD,

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2008). In Africa SMEs have little access to finance, which hinders their growth and inhibits their main sources of capital to retained earnings and informal savings which can be very unpredictable and have little scope for risk sharing because of their regional or sectoral focus (Kauffman, 2005). SMEs have poor access to finance because they are viewed as risky and have high rate of default on payments. Access to finance for some SMEs is determined by gender as done in Uganda and other countries.  This then creates and unfair playground in the industry. Furthermore SMEs are viewed as high risk by banks to loans them money and they require more documentation and collateral. The issue then arise as most SMEs interviewed are more for subsistence and some are based in the villages and cannot meet these bank collateral demands. This in turn inhibits SMEs access to finance.   Thus

H3: Poor access to finance negatively impacts sales growth

Management Experience

SME growth is related to research and development, innovation, and the ability to gain advantage over competitors in the product market (Romano, 1990). Additionally previous research has found that management past experience in the industry contributes to the competence of the team in seizing new growth opportunities (Kor, 2003). I posit that for some firms depending on the industry such as software development, if the management has a plethora of experience, it could assist in new product development. New product development then creates new markets for firms and exposure which leads to high sales. This innovation also increases market share in the current customer base and attracts new customers by opening new markets (Zahra and Nielsen 2002).  We then see that this creates demand and increases the customer base of the firm ultimately growing its sales and profits. Thus:

H4: Management Experience positively impact sales growth

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Marketing Strategies

It is of prime advantage for the firm to possess the ability of consistent and planned marketing activities to meet and exceed customer preferences and value that can be regarded as customer performance (Cavusgil and Zou, 1994). Customer performance is achieved by the firm regardless of the approach of marketing strategy pursued either undertaking standardization or adaptation (Saif, 2001). A firm’s product offering and marketing strategy establish its survival in the marketplace.  ICT can also be used for marketing purposes and expanding SMEs (Locke, 2004). Use of web sites and e-mails to communicate with customers and clients contributes to improved customer service and can expand the market share of the firm enabling the firms marketing techniques to reach a broad array of customers.  Thus:

H5: Marketing Strategies positively impact sales growth

 Land

For my contribution there has not been much literature written about the impact of land ownership and cost to SME s growth in Sub-Saharan Africa and Namibia. This was listed as the second biggest obstacle to growth in the Enterprise Survey with 21.8% citing land as an obstacle. In 2014, 54% of the population was living in rural areas (World Bank). This then means that land is crucial to their business activities such as tourism (sculpting etc). Thus:

H6: Lack of ownership of land negatively impacts sales growth

 

 

 

 

 

 

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Section 5 Data and Methodology

5.1 Sample and data sources

This section addresses the methodology used in this study. Data was obtained from the Enterprise Surveys database. A properly designed survey and a uniform sampling methodology are used to enhance the credibility of World Bank analysis. The Enterprise Survey team aims to achieve the following objectives:

  • To provide statistically significant business environment indicators that are comparable across all of the world‘s economies;
  •  To assess the constraints to private sector growth and enterprise performance;
  •  To build a panel of establishment-level data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms and policy changes; and
  •  To stimulate policy dialogue on the business environment and to help shape the agenda for reform. (World Bank, Enterprise survey).

For this sample the definition of the SME by the World Bank was used to collect data from the firms that suit the description. A total of 580 firms were interviewed on a one on one basis. The SMEs where grouped into three categories namely manufacturing, retail services and other services.

5.2. Data selection

To make sure that the paper is objective the sample was selected as follows:

  1. Firms that were listed as large firms were not included.
  2. Samples with missing sales figures
  3. Firms with missing information on their size were excluded.
  4. Firms with missing information about the obstacles they faced where excluded.
  5. Firms that were not formed at the in the 4 years required to calculate the sales growth were also excluded.
  6. Firms with missing information on their date of operations were excluded.

Section 5 Data and Methodology

5.3. Sample Size and selection

In total the number of SMEs data collected came up to 580 and those selected for this study came up to 305. They were selected based on sales figures, thus the ones with missing numbers or the ones that were not formed yet within the 4 year time frame employed were not used.

5.4. Variables

The models analyse sales growth of Namibian SMEs from 2009 to 2013. Data was collected in 2014. To conduct the analyses a record of the Small and Medium firms was created over these years. Sales growth is the dependent variable and government tax policies, land obstacles, management experience, access to finance obstacles, and political connection obstacles. I also developed other control variables that are known to affect SME sales growth. These were firm age, size and region.

Dependent variables

The growth of the firm was measured using sales growth. This was calculated using the growth rate. Sales growth is a common measure of firm performance and typically has a positive correlation with firm growth (Heshmati, 2006).

Sales growth rate =  2013 sales

          2009 sales

*100%

Independent Variables

All the independent variables were measured using the same scale. The SME interviewees would be asked to rank from 1 to 5 how much a factor was an obstacle to their business operations and how much it impacted growth.

Peking University Master Degree Thesis

For example

How much were government tax policies an obstacle to business growth?

Factor Responses
Government tax policies No obstacle Minor Obstacle Moderate Obstacle Major Obstacle Very Severe Obstacle

In this regard the respondent would have listed tax obstacles as a Moderate obstacle to business growth.

This was done for all the other independent variablesland obstacles, management experience, access to finance obstacles, political connection obstacles, marketing strategies obstacles.

Control Variables

I included three measures that could have an impact on the sales of SMEs. These were the region where the firm is located, the size that is whether the firm was small or medium and then the firm age.

Firm size

Prior studies have found that smaller firms have a faster growth rate compared to larger firms. Studies on firms in the United States of America by (Hall, 1986) found that smaller firms in the sample grew faster. Also (Evans, 1987) found that firm growth decreases at a diminishing rate with firm size. Hence for my studies I chose to use firm size as a control.

Firm age

Firm age has been found to have an impact on sales growth. The older the firm is the lower the sales growth. (Evans, 1987) found that the variability of a firm’s growth decreases as firms’ age. Therefore since this could impact the growth of the firm I chose to use it as a control variable.

Section 5 Data and Methodology

 

Location

Studies done in Germany of small technology firms found that firm growth is impacted by locational characteristics. For example if a firm is located in an area with a bigger knowledge base their growth was found to be positive along with other factors such as firm size (Audretsch and Dohse, 2007).

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Section 6 Empirical model and results

The Linear regression model will be used to empirically test hypotheses.  Some researchers have studied the obstacles that impacted sales growth and in this paper the linear regression model used by (Lu and Beamish, 2001) was used.  The model is as follows

Sales Growth =β1Marketing Strategies + β2 Management Experience+ β3Government tax policies + β4 access to finance + β5 land  + β6Political connection + Controls + ε

Control Variables are:

  • Location,
  • Size,
  • Firm age and
  • Industry Sector

In order to remove of multicollinearity the Variance inflation factor (VIF) was used. The acceptable measurements for VIF are (0<VIF<10) which means there is no multi collinearity problem. The ones that show multicollinearity are (10<VIF<100). In the Correlation Matrix the values are less than 0.9 which shows that the values are related without being highly correlated which could end up affecting the model.

6.1 Empirical Results

Descriptive Statistics

Table 3 shows the means, standard deviations, median, maximum and minimum of the key variables in the analysis. The mean value for the sales growth highlights that the proportion of the data that grew by more than 5% is 14%. The mean and the median of the dependent variable which is sales growth is 0.144 and 0.052 to showing the firms that gained profit. The maximum and the minimum are 3.6416 and -0.679 this highlights that there were significant differences between firms that performed well and those that did not.

Section 6 Empirical Model and results

 

For the independent variables ownership of land the minimum is 1 and the maximum was 5. This shows that there were varying responses to the level of significance ownership of land hindered sales growth. The median for ownership of land is 3 meaning that overall the firms thought ownership of land was moderate obstacle to firm growth. The mean and the median of access to finance is 3 showing that on average difficulty to obtain loans was perceived to be a moderate obstacle to sales growth. For government tax policies the maximum was 3 meaning that the highest SME owners perceived this to be an obstacle is 3. The mean for management experience is 1.8 which is almost close to the highest ranking of 2, which means that a higher number of SMEs did have more management with experience in the industry.

For the control variables the maximum age for the oldest firm was 63 years. The average firm age will be 10 years. The median for location is 1, meaning that most of the firms in the Sample are located in the 3rd biggest city in Namibia. For Size the median is 1 meaning that most of the firms in the sample where small.

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Table 3 : Descriptive Statistics
 Variable Mean Median sd min max
Location 1.845 1.000 .982 1.000 3.0
Size 1.348 1.000 .478 1.000 2.0
Firm Age 10.580 8.000 8.543 3.000 63.0
Sales Growth 0.144 0.052 .577 -0.679 3.642
Government Tax Policies 1.343 1.000 .487 1.000 3.0
Management Experience 2.044 2.000 1.016 1.000 5.0
Marketing Strategies 1.807 2.000 .396 1.000 2.0
Ownership of land 2.519 3.000 1.3064 1.000 5.0
Access to finance 3.055 3.000 1.205 1.000 5.0
Political connections 2.337 2.000 1.347 1.000 5.0

 

 

 

 

Section 6 Empirical Model and results

 

Table 4 Correlation Matrix

Sales growth Location Firm Size Firm age Manu Dum Retail Dum Tax Mng Exp Mrkt Strat Land Finance Poltical Conn
Sales growth 1.000
Location .135 1.000
Firm Size -.094 -.233 1.000
Firm Age -.052 .066 -.244 1.000
Manuf Dum -.038 .387 -.223 .140 1.000
Retail Dum .107 -.188 .003 .122 -.355 1.000
Tax -.091 .026 .151 -.029 .061 -.048 1.000
Mng Exp .269 .114 -.021 -.127 .108 -.050 .064 1.000
Mrkt Strat .153 -.226 .057 .050 -.111 .102 .009 -.057 1.000
Land -.221 -.157 .177 -.108 -.094 .100 -.013 -.076 -.042 1.000
Finance -.232 -.286 .249 -.181 -.063 -.005 .023 -.012 .030 .266 1.000
Polticl Conn .277 .115 -.080 -.125 .081 -.037 -.085 .050 -.079 -.102 -.124 1.000

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Table 5 : Regression Analysis of the Impact on Sale growth

Variables
  Model 1 Model2 Model 3 Model 4 Model 5 Model6 Full VIF
Control
Firm age -0.074 -0.117 -0.128 -0.055 -0.053 -0.111 -0.063 1.19
Location 2.926* 2.693* 2.065* 2.739* 2.730* 3.903*** 2.137 1.37
Firm Size -1.598 -1.192 -1.063 -1.685 -1.337 -1.843 -0.251 1.22
Manufacturing Dummy -0.979 -1.452 -1.085 -2.221 -1.957 -1.514 -1.848 1.41
Retail Dummy 2.449 2.818 2.387 2.307 2.309 2.231 2.261 1.21
Independent variables
Government Tax -1.852** -1.945** 1.05
Lack of land ownership -1.566*** -0.976** 1.13
Access to Finance -1.616** -1.129** 1.23
Mng Exp 2.336*** 2.293*** 1.05
Political Connections 1.662*** 1.470*** 1.07
Mark Strategies 3.570*** 3.606** 1.07
R2 0.058 0.097 0.090 0.117 0.116 0.087 0.268
Adjusted R2 0.024 0.066 0.058 0.085 0.085 0.054 0.220
Note: *p<0.10    **p<0.05    ***p<0.01

 

 

 

Section 7 Discussion of Results

 

Section  7 Discussion of Results

I tested the 6 hypotheses using one set of 7 linear regressions. One for the full sample of 305 SMEs and the other was individually testing each of the 6 hypotheses. The results of the regressions are displayed in the table above. All of the models were significant hence each can be explained. Additionally the results of the full table and the subsamples were consistent but the effects of firm age could be seen to have a strong negative relationship with firm sales growth.  SMEs should be levied lower taxes to enable them to have enough funds to use to grow their business and pursue new markets. Model 1 tested hypothesis 2 which predicts that government tax policies negatively impact sales growth. From the regression model it can be denoted that government taxation policies have a significant negative impact on sales therefore we accept the null hypothesis.  This result is consistent with the results by (Abrie and Doussy, 2006) who carried out research on SMEs in the Gauteng Province in South Africa. They found that the majority of SMEs found tax liabilities to be an increasing burden. Also a lack of skills to comply with the Revenue services meant that they incurred extra costs because of lack of timely payments.  It can be seen that the burden of tax policies is two way, one is to pay the revenue services and the other is to hire experienced professionals to do it for them. Further making the taxes burden heavy as the SMEs will incur double costs.

Model 2 tests to see if the ownership of land or lack thereof will impact sales growth of the SMEs. The results show that land and sales growth have a significant negative relationship. So we accept the null hypothesis. Hence it can be concluded based on the results above that ownership of land significantly impacted sales growth. The negative change shows that ownership of land does impact the growth of sales in the SMEs. This is because land can be used as collateral to borrow from banks thus increasing their chances of securing a loan. Also access to finance is cited as one of the main obstacles to SME growth and ownership of land could make this easier for collateral and also cut on rental costs. The rent money would then be sued to develop their business further and could also go into savings.

In Model 3 the type of finance referred to is trade credit and bank loans. There is a negative significant relationship between form growth and access to finance. Therefore we accept the null hypothesis. This result is consistent with (Beck, et al., 2008) who did a research for the World Bank analysing the lending practices of banks around the world.

Peking University Master Degree Thesis

They discovered that exposure of banks to SMEs in developing countries was low and this resulted in them charging higher interest rates and fees because of the risk associated with SMEs. Additionally banks in developing countries provide a lower share of investment loans to SMEs. These results are also fit with (Chen and Guariglia, 2013) who found that financing constraints lower the level productivity in the majority of Chinese firms.

In Model 4 shows the impact of management experience on SME sales growth. The results above show that management experience has a positive and significant impact on sales growth. Therefore we accept the null hypothesis which was management experience had a positive impact on sales growth. This is consistent with studies by (UNCTAD, 2008) on Thailand SMEs which showed that firms that hired managers with more experience showed enhanced firm productivity and growth. Also a study on Finnish SMEs in the manufacturing and service sector found that firms which employed managers with more experience had a significant positive impact on productivity and sales (Maliranta and Rouvinen, 2003).

Political connections can reduce the number of local and foreign investors willing to invest in SMEs and increase the capital costs for the entrepreneur as this can be seen as corruption. However in Model 5 Political connections were statistically significant and had a positive effect on sales growth so we reject the null hypothesis. After researching SMEs in Indonesia (Karuna, 2003) reported similar results where they found a positive and significant relationship between firm growth and political connections. This was also supported by (Acemoglu and Verdier (1998, 2000), who found that to some degree that political connection will facilitate investment especially in low development countries due to lack of proper formal institutions.

In model 6 it can be seen that marketing strategies have a positive and significant effect to sales growth. Hence we accept the null hypothesis.  (Wolff and Pett, 2005) also found similar results where they saw a positive growth between growth and a firms marketing strategy.

 

 

 

 

 

Peking University Master Degree Thesis

Section 8 Conclusions and Limitations

I used secondary data from the Enterprise Surveys. However secondary data has its own drawbacks such as the data collected had more respondents from Windhoek and Oshakati than Walvis Bay. Therefore not all major provinces were properly represented. There was a lack of consistency in how some of the questions were answered. This makes data cleaning more severe and losses of some parts of the data are lost. Only 305 firms from 580 firms had complete information necessary to carry the research. Most of the parts were blank. Hence this results in a smaller sample which may not represent the SME sector properly.

This study concludes that the key drivers in SME sales growth are management experience and marketing strategies. The implication is that SMEs are most likely to improve their sales growth by being more innovative than larger firms. Also implementation of new technologies is assimilated within the organisation faster than larger firms because of their smaller size. This enables smaller firms to put new strategies in action to face competition. The study also found that ownership of land impacts sales growth as land could be used as collateral to reduce the risk of lending SMEs by banks. Hence government should set about some policies to assist SME owners to acquire land at low rates as this will cut on other costs such as rent. The institutional factors such as government taxation policies and access to finance both had negative effects towards sales growth. This shows that SMEs are very susceptible to changes in the external environment due to their size and hence they need support from government policies and incentives to lessen the impact of these factors.

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Appendix

Appendix 1

SME share of employment in Africa

Country SME share of employment
Zimbabwe 15%
Malawi 39%
Kenya 38%
Zambia 37%
Burundi 20%
Ivory Coast 33%
Cameroon 19%
Tanzania 32%
South Africa 21%

Source: World Bank

 

 

 

Appendix 3

Ranking of the Top Business Environment Obstacle for firms in Namibia

Political connections

Source: Enterprise Survey, World Bank

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