Chapter 2: Conceptual and Empirical Review
2.2 Unpacking the Topic
2.2.1 What Does Entrepreneurship Mean?
2.2.2 How Entrepreneurship Developed?
2.3 Empirical Contributions and Defining the Gap
2.3.1 SMEs Growth
2.3.2 SMEs Growth, clusters, and networks
2.4 Conceptual and Empirical Framework
Entrepreneurship has been examined from multiple disciplinary perspectives at various levels of analysis, using a variety of methods, making it difficult to define the boundaries of the research domain. There is a growing body of research in different disciplines, such as politics, sociology, business history, psychology, economic anthropology, and geography (Carlsson et al., 2013). The domain of entrepreneurship literature embraces numerous dimensions and the analysis can be conducted at different levels (individual level, firm level, and macroeconomic level) taking into consideration various factors, such as environment, cluster, network, and location. One result, pointed out by many authors, is the lack of a common theoretical framework or central research paradigm (Bjerke, 2007).
Accordingly, it is important to have a conceptual framework of what is meant by entrepreneurship and how it can be developed if we are going to understand the role it plays in the economy. Throughout history, there have been tremendous changes in the research field of entrepreneurship. Going back to the roots of entrepreneurship, it was only discussed by economics scholars, such as Richard Cantillon
(1755), Jean Baptiste Say (1855), Joseph Schumpeter (1951), and Israel Kirzner (1973), who were interested in the entrepreneurial function rather than entrepreneurs as individuals (Carlsson et al., 2013). After that, entrepreneurship gradually changed to be a research area within other disciplines, concerned with explaining the role of the entrepreneur and what could lead to the development of entrepreneurship. This shift seems to be related to the structural changes in society worldwide during the 1970s and 1980s, such as oil crises, economic recession, technological progress, increasing globalisation, and political change (Landström, 2005).
All of these changes created the uncertainty and disequilibrium that constitute the breeding grounds for new business opportunities and innovative ventures. As a consequence, policy makers and politicians saw small and medium sized businesses as the main contributors to the economy and society; in turn, this rapid interest had an impact on the academic world. Although the research on entrepreneurship has grown tremendously, the growing body of entrepreneurship literature has questioned whether the research really has created a coherent stream of knowledge that advances the field. Several concerns have been raised by different scholars, such as Landstrom (2005), in respect of 1) the problem of defining entrepreneurship and 2) the lack of theoretical foundations in the field.
Therefore, this chapter will focus on discussing two issues in order to build the theoretical framework for this thesis. First, the definition of entrepreneurship, because it is important to have a conception of what is meant by entrepreneurship if we are going to understand the role it plays in the diversification of the Saudi economy. Second, a discussion of how entrepreneurship can be developed, to explain the role that is played by institutional support in the development of entrepreneurship and the diversification of an economy such as the oil-dominated Saudi economy.
This chapter will examine the first issue, which is defining entrepreneurship, by considering it from three perspectives. First, defining entrepreneurship as a function of the market from economic discipline perspective (Carlsson et al., 2013), second, defining the entrepreneur as an individual, mostly from the behavioural sciences perspective (McClelland, 1967), third, defining entrepreneurship as a process from a management studies perspectives (Landström, 2005). The discussion will then focus on the second issue of how entrepreneurship can be developed based on the conceptual and empirical argument of social capital, network analysis, and cluster analysis. Finally, based on the theoretical argument of these two issues, this chapter will articulate a conceptual and empirical framework that seeks to answer the three main questions of what, how, and why. What refers to the main factors and concepts for explaining the phenomena. How refers to the explanation of casual relationships among these factors or variables to find a pattern of relations. Why refers to the core of a theory that provides logic and justifications for the first and second questions, in addition to generating new insights, challenges, and deep understanding of the phenomena (Crane et al., 2016; Whetten, 1989).
18.104.22.168 Entrepreneurship as a Function of the Market
Cantillon was the first person to give the concept of entrepreneurship an analytical content in 1755. He claimed that entrepreneurs are one of the initial three actors in the economy, being, 1) property owners, who are the main consumers, with all production in the economy being an attempt to meet their desires; 2) entrepreneurs, who live on uncertain income, and 3) employers (Brown & Thornton, 2013). Accordingly, entrepreneurs play a significant role in the economic development (Carlsson et al., 2013), as they attempt to meet the demands of property owners and other consumers in the economy (Brown & Thornton, 2013). Thus, the entrepreneurs are distinctly supply side. They are risk-takers in the face of uncertainty of demand and price, since the entrepreneur buys at a given price but does not know what demand will be or what the selling price will reach (Carlsson et al., 2013).
Although Cantillon narrowly defined entrepreneurship, his definition is broadly applicable. An entrepreneur is anyone who invests with the purpose of selling goods in the future at an uncertain price is an entrepreneur (Brown & Thornton, 2013). This perspective differs greatly from other viewpoints, such as that of Schumpeter and Say.
Say claimed in 1855 that the chief contribution of the entrepreneur is to combine and co-ordinate factors of production. Thus, the entrepreneur stands at the centre of the economic system. Based on his contribution, entrepreneurs are the business builders, since the main role of entrepreneurs is directing and rewarding the various factors of production, and taking the residual as profit (Parker, 2004; Say, 1964). He distinguished three economic activities in entrepreneurship, being: 1) research generating knowledge; 2) entrepreneurship applying this knowledge to useful products by combining the means of production in new ways; and 3) workers doing the manufacturing (Carlsson et al., 2013).
Therefore, entrepreneurship exists in the context of new business establishment, and successful entrepreneurship requires personal characteristics. The judgment, perseverance and experience required for successful entrepreneurship will be in scarce supply, providing higher profits for entrepreneurs that possess these qualities. Furthermore, in order to be a successful entrepreneur, an individual also needs to be resourceful, knowing how to overcome unexpected problems and to exploit (although not develop) existing knowledge (Parker, 2004).
Although some have criticised Say’s view of the entrepreneur as merely a superior kind of worker with managerial duties (e.g., Hebert & Link, 1989), others have offered modern re-statements of Say’s perspective (e.g., Casson, 2003). However, both contributions incorporate the main historical themes of entrepreneurship including, risk, uncertainty, perception and change (Carlsson et al., 2013). Hebert and Link (1989), and Casson (1982) defined the entrepreneur as someone who specialises in making critical decisions related to what could have an impact on the business, such as the location, resources, and the use of goods and institutions. Therefore, the ability to identify and exploit opportunities is essential to entrepreneurship.
On the other hand, innovation is the critical function for entrepreneurship in Schumpeter’s contribution, as he saw the entrepreneur as an inventor, who sees an opportunity, seizes that opportunity and creates new product, changes a production process, or otherwise creates a new marketable contribution to the economy (McDaniel, 2002). He defined entrepreneurship as a “correspondence act” or process for inventing technology, products, methods, industries or markets (Ndhlovu & Spring, 2009). Therefore, people cease to be entrepreneurs once they have introduced an innovation. The entrepreneurs may then become only small business managers, that is, administrators of prior innovations (Carlsson et al., 2013).
Based on this definition, Schumpeter termed five activities “innovation” and claimed innovation as the sole domain of the entrepreneur. He defined innovation as an activity that leads to new production (McDaniel, 2002), which is the mechanism for economic development (Carlsson et al., 2013). These activities could involve 1) the creation of new product; 2) a new method of production; 3) the opening of new market; 4) the capture of new sources of supply, or 5) a new organisation of industry (Parker, 2004). Some of these five activities will initially affect the supply of products, while others may initially influence the consumer or demand for products. While this distinction has created much controversy about demand-induced or supply-induced changes in the market, it is clear that eventually all five cases will affect the production or supply of products (McDaniel, 2002).
Schumpeter viewed the entrepreneur as a rare, unusual creature driven by instinctive motives. He considered profit as a residual, not a return to the entrepreneur as a factor of production, and claimed that the entrepreneur is never a risk bearer (Parker, 2004). However, the view that only capitalists and not entrepreneurs bear risks have been roundly criticised by several subsequent writers (e.g. Kanbur, 1989), for imposing an arbitrary distinction between capitalists and entrepreneurs, and for ignoring entrepreneurs’ actual and opportunity costs in operating ventures that can fail (Parker, 2004).
In contrast to Schumpeter’s view, Kirzner defined the entrepreneur not as an inventor, but as an opportunist, that is, a person who is looking for imbalances in the economic system which can be exploited to coordinate production resources more effectively than before (Kirzner, 1973). Therefore, according to him, entrepreneurship is about recognising the opportunities and acting upon the profitable ones, essentially, the role of an arbitrageur (Ahmad & Seymour, 2008; Kirzner, 1973).
22.214.171.124 Entrepreneurship as an Individual
Since Schumpeter, society’s attention has moved away from trying to explain entrepreneurship toward developing it. This has been due to the global changes, such as oil crises, economic recession, technological progress, increasing globalisation, and political change that had created uncertainty (Landström, 2005). This has raised an important question: since entrepreneurship plays a significant role in economic development, why do some individuals tend to start their own business, which depends on having certain qualities that others lack?
Economists could not play a useful role in identifying and explaining this entrepreneurial ability. Instead, behavioural science researchers saw the gap in the literature and increasingly assumed responsibility for continuing the theoretical development and searching why some individuals tend to start their own business whereas others do not. When it comes to what motivates entrepreneurs to start a business and strive for success, behaviourists tend to emphasize the psychological factors involved. One of the most influential contributions is by David McClelland in his book “The Achieving Society” (1961), where he suggests that economic development of a nation is linked to its need for achievement (McClelland, 1967). This means that if the need for achievement in a country is high, there will probably be individuals who behave as entrepreneurs. In this respect, entrepreneurs are people who have a high need for achievement, great self-confidence, independent problem-solving skills, and who prefer situations that are characterised by moderate risk, follow-ups of results and feedback, and the acceptance of individual responsibility (McClelland, 1967).
Since McClelland’s contribution, a large number of studies have tried to identify the particular qualities and some of the individual characteristics assumed to be related to entrepreneurs (Landström, 2005). These include 1) the need for achievement, which is based on McClelland’s study; 2) risk-taking propensity; 3) control concerns stemming from whether a potential goal can be attained through one’s action or follows from uncontrolled external factors; 4) over-optimism, and 5) desire for autonomy.
However, since the number of traits identified in the research has gradually increased, with a few exceptions such as need for achievement, it has proven difficult to link any specific traits to entrepreneurial behaviour. For this reason, research into individual traits has been extensively criticised, on both conceptual and methodological grounds. In addition, there is an increasing number of companies that are founded by teams and not by a single individual (Landström, 2005).
Moreover, defining entrepreneurship in terms of who the entrepreneur is and what they do has generated incomplete definitions. For example, defining an entrepreneur as a person who establishes a new firm does not consider the variation in the quality of opportunities that different people identify, which leads researchers to neglect to measure opportunities (Shane & Venkataraman, 2000).
126.96.36.199 Entrepreneurship as a Process
During the 1990s, entrepreneurship research gained an increase interest from management researchers because of a shift in the research questions to mainly how entrepreneurship can be developed, which requires a more process-oriented definition. A significant contribution by William Bygrave and Charles Hofer (1991) defined entrepreneurship as a process that involves all the functions, activities, and actions associated with perceiving opportunities and creating organisations to pursue them. However, this raised an issue among researchers regarding what should form the focus of opportunities perceived and organisations’ creation, which has led to two different streams of interest: the emergence of new organisations and the emergence of opportunities (Landström, 2005).
On the emergence of new organisations, the entrepreneurial process starts when the entrepreneur makes the decision to start a firm, and ends when the entrepreneur has to obtain external resources and create a market niche (Gartner et al., 1992). On the emergence of opportunities, entrepreneurship may be defined through the research questions that are central and unique to the field (Landström, 2005). Venkataraman (1997) argued that entrepreneurship as a research field seeks to understand how opportunities are discovered and exploited, by whom, and with what consequences.
Therefore, the core of entrepreneurship should be concerned with why, when, and how 1) opportunities come into existence; 2) some people are able to discover these opportunities while others are not, and 3) different modes of action are used to discover opportunities. Finally, understanding the economic, psychological, and social consequences of the pursuit of future markets, not only for the entrepreneur, but also for other stakeholders and for society as a whole, is almost important to entrepreneurship research (Shane & Venkataraman, 2000).
In this sense, entrepreneurship is not a fixed characteristic that differentiates some people from others, but rather a tendency of certain people to respond to situational cues of opportunities. Neither does entrepreneurship require, although it can include, the creation of new organisations, and entrepreneurship can occur in different contexts, such as existing organisations (Landström, 2005). Thus, Shane and Venkataraman’s framework is much broader than the emergence of new organisations.
Based on the above discussion, we intend to follow Shane and Venkataraman’s contribution (2000) in defining entrepreneurship, as well as Schumpeter’s contribution. Therefore, entrepreneurship is a “correspondence act” or process for inventing technology, products, methods, industries or markets (Ndhlovu & Spring, 2009). This means that the entrepreneur is an inventor, who sees an opportunity, seizes that opportunity, and creates a new product, changes a production process, or otherwise creates a new marketable contribution to the economy (McDaniel, 2002). Consequently, this involves studying the resources of opportunities, the processes of discovery and evaluation of opportunities, as well as entrepreneurs’ characteristics, who discover, evaluate and exploit these opportunities (Shane & Venkataraman, 2000).
188.8.131.52 Social Capital Theory
There are strong theoretical reasons to expect social capital to affect economic performance and explain the role of institutions in supporting growth of small and medium-sized enterprises (SMEs). The efficient functioning of markets requires a good flow of information to connect buyers and sellers, and the ability to enforce contracts or other negotiated arrangements easily and cheaply. Economies with such features should be conducive to entrepreneurship (SMEs), effective competition, and the efficient allocation of resources (Halpern, 2005; Portes, 1998; Lin, 1999; Burt, 1997).
In general, social capital theory examines certain relations among actors in society, who are seen as having resources over which they have some control and in which they have an interest. The result of the various kinds of exchange that actors engage in to achieve their interests is the formation of social relationships having some persistence over time. Therefore, social capital is created when the relations among actors change in ways that facilitate action (Coleman, 1994). This means that the concept of social capital assumes that people engage through a series of networks with others who share common values, where they may be seen as forming a kind of capital, as they are the heart of the social capital concept (Field, 2008).
To gain a better understanding of social capital, it is necessary to become acquainted with the concept of capital and to place it in the context of different theoretical types of capital (Lin, 1999; Lin & Erickson, 2010). Many contributions in entrepreneurship research studied various types of relationships or network structures that are labelled as “social capital” (Gedajlovic et al., 2013).
Capital as a concept represents investment and possession through which such valued resources are produced, reproduced, and accumulated (Lin & Erickson, 2010). For example, the human capital theory postulates that investment in certain human resources (skills and knowledge) may generate economic returns (Johnson, 1960). Likewise, social capital theory conceives of capital as valued resources that generate returns to individual and collective actors in a society (Lin & Erickson, 2010). Therefore, on one hand, entrepreneurs might intend to invest in social capital to generate economic returns and grow their businesses, on the other hand, institutions as resource generators might use the social capital to allow the entrepreneurs to access their resources.
The first theorists to come up with the idea of social capital included Pierre Bourdieu, James Coleman, and Robert Putnam. According to them, social capital comprises of personal connections and interpersonal interaction as well as with a common set of values related to these contacts. Nonetheless, the theorists have different points of view (Field, 2008). For instance, Bourdieu is more concerned with the questions of unequal access to resources as well as the concentration of power. He asserts that social capital is the total of the real or potential resources that are connected to ownership of a strong system of composed of many organized connections of shared associate or acknowledgment (Richardson, 1986).
On the other hand, Coleman (1988) starts his argument by identifying that in most case people tend to act in a rational manner when they strive to satisfy their own interests. As he identified it, social capital could be characterized by its function with various units and two common components. These components comprise of the social structure characteristics, which encourage certain activities of performers, regardless of whether individual or corporate performers inside the structure. For Putnam, he only acquired and developed the assertions concerning the associations and civil activity as the premise of social integration and prosperity (Field, 2008).
Regarding these contributions, three components should be recognisable in almost any form of social capital; a network; a cluster of norms, values and expectancies that are shared by group members, and sanctions that help maintain the norms and network (Halpern, 2005). The first component of social capital is a network that can be characterised by its density (the proportion of people know each other) and closure (the preponderance of intra- versus inter-community links).
The second component is norms, which refers to the rules, values, and expectancies that characterize the community (or network) members. The third component, sanctions, include formal sanctions, such as punishments, and informal sanctions that are effective in maintaining social norms. These three components can be used to analyse any kind of community or network (Halpern, 2005).
Therefore, taking together with the work of other scholars (Burt, 1997; e.g. Coleman, 1988Coleman, 1988; Lin & Erickson, 2010), we can acknowledge the general premise that social capital is network based. Thus, social capital is a capital captured in social relations, and its production is a process by which value is generated through investment in social relations so that resources embedded in these relations become the mechanism through which individual and collective actors gain advantage (Lin & Erickson, 2010). Consequently, repetitive interaction among individuals is a sign of a robust network and an important form of social capital, since it is assumed that trust is an outcome of social capital formation and a key link between social capital and collective action (Ostrom & Ahn, 2003).
Accordingly, when individuals network with one another in multiple ways, and are within institutions that facilitate the growth of trust, they can influence behaviour directly by establishing formal and informal rules. These rules, directly or indirectly, help individuals govern themselves by providing information, technical advice, alternative conflict resolution mechanism, and so on. Therefore, when formal and informal institutions exist that specify applying rules, they affect a trustee’s future behaviour and the quality of a rule in use, or institutions as a form of the social capital, depends not only on content but more critically on how it is implemented (Ostrom & Ahn, 2003).
Notably, various forms of social capital could be helpful in accomplishing distinctive objectives. Sandefur and Laumann (1998) said that a given type of social capital may give at least one advantage, which involves information, influence, and control as well as social solidarity. Besides, one specific type of social capital can be of much help in attaining other higher objectives. This means that types of social capital are different in relation to their end benefits and they result in liabilities on the grounds that a type of social capital gained to help in an activity hinders other activities. In general, it can be deduced that varied forms of social capital might have a certain power dependent upon the objectives the performers wish to achieve.
The whole idea of social capital seems clear and that an investment in social relations brings straightforward returns. Therefore, we can contend that systems as a type of social capital represented by the organizations’ guidelines boost the results of the interaction at the individual as well as the aggregate level (Lin, 1999). This is on account that an organization’s guidelines encourage the development of trust among system performers, which is essential for having a powerful system that permits full association on the individual or the aggregate level. Hence, it is important to build a community or a system that is directed on the basis of specific standards and guidelines to ensure entrepreneurs (at the individual and collective level) have access to resources and support the growth of SMEs.
It is evident from the discussion that analysis of the advantages and returns of social capital as well as system analysis can be done either at an individual or at an aggregate level. In the case of individuals, the emphasis is how social capital is used by an individual, for instance, how the resources are accessed and utilized within social systems to attract returns in instrumental activities (Burt & Celotto, 1992). On the other hand, the aggregate level focuses on social capital in a group setting. This is where the group’s way of developing and maintaining social capital as a collective resource as well as the way the resource benefits the group members’ business is considered (Lin, 1999; Coleman, 1994).
This is the background against which we can incorporate some of the elements of social capital theory into the development of cluster theory, since networks are seen as a part of the cluster (Bjerke, 2007). Cluster theory has undergone many developments since Marshall suggested that clusters should be based on localisation of industry in one area to take advantage of interlinked activities and increase the efficiency of SMEs that assist in generating specialised economies(Marshall, 2009; Rocha, 2004).
While development has also been observed through connections between institutions, businesses and organisations (Rocha, 2004), it has been suggested that networks and relations between firms are not adequate to explain clustering. In other words, in an uncertain business environment, social networks should also be considered. Uncertainty in social networks takes the form of habits, informal rules, and conventions (Rocha, 2004). Nevertheless, these approaches are still considered to be insufficient in explaining the types of activities that constitute clusters.
Accordingly, to understand how the network affects access to resources and growth of SMEs, we can incorporate some of the elements of network analysis into the development of cluster theory for two reasons. First, the main assumption in social capital theory is that individuals engage in interactions and networking in order to enhance outcomes (Gedajlovic et al., 2013). Second, networks and collaborative activities have primarily been seen as part of the cluster (Bjerke, 2007).
184.108.40.206 Cluster Analysis
In general, the characteristics of clusters are often described as if they were building on vertical and horizontal networks and their relations. Although cluster theory has gone through many developments and the overall concept of clustering has been very well explained, the underlying cluster definitions and the principals behind them are characterised as broad and fuzzy (Ingstrup et al., 2009).
This fuzziness is caused by the fact that cluster definitions are used in different contexts and for different purposes, such as regional development, firm growth and analysis of innovative systems. This means scholars from different research areas, such as geography, business studies, and sociology, are contributing, which add to the fuzziness. Therefore, the lack of common definition regarding clusters has resulted in a complex picture, which is further complicated due to policy makers’ increased interest in the area, since the concept can be applied in a wide range of situations and without a coherent understanding (Ingstrup et al., 2009).
There are four dominant theoretical schools of clustering. First, contributions which focus on the localisation of industry, such as Marshall’s argument (Marshall, 2009; Rocha, 2004). Second, contributions which focus on social aspects and networks, such as the Italian districts (Becattini, 1991). Third, contributions which focus on competitiveness, such as Porter’s model (Porter, 1990; 1998). Finally, contributions which focus on innovativeness, such as the Saxenian contribution (Morgan, 1996).
Marshall’s theory suggests that clusters should be based on localisation of industry in one area, in order to take advantage of interlinked activities and increase the efficiency of SMEs that assist in generating specialised economies and the key factors that foster economic development (Rocha, 2004). He identifies three overall sources that foster spatial cluster formation through increasing returns to scale in the long run: knowledge spill-overs, labour pooling, and cost advantages caused by economies of specialisation (Ingstrup et al., 2009).
For example, Marshall argues that knowledge flows more easily between local actors than over longer distances, which influences local inter-firm cooperation. Moreover, labour pooling benefits present firms as well as attracting new ones to a certain geographical area, which in turn benefits information transfer and improvement of industry skills. As a result, this increases inter-firm cooperation with extensive links and resource ties. Cooperation through sharing resources can thus be enhanced and the cost of innovation can be shared (Marshall, 2009; Ingstrup et al., 2009). Although Marshall’s argument was carefully investigated, as later studies considered cluster formation and gradually adopted descriptive, ideographic work, Marshall’s logic justifications were assumed not carefully investigated and specified (Maskell & Kebir, 2006).
Regarding localised industries, the example of the Italian industrial districts is concerned with social aspects, as the main contribution was to move the centre of attention of the individual firms in the cluster of interconnected firms in small geographic areas (Becattini, 1991). Based on this argument, clusters are characterised by social relations and inter-firm cooperation and competition. This means that the main driver of entrepreneurship is the interaction and relations among different actors within the clusters (Ottati, 1994). The interaction in the clusters in not limited only to firms, but it also involves interaction between institutional and market actors (Ingstrup et al., 2009), such as the resource generators and entrepreneurs in the cluster. However, the value or the analysis of these interactions and networks are not explained in this model.
It is for this reason that Porter (1998) highlighted the importance of business environment factors in enhancing competitiveness in the industrial clusters. These factors include 1) production factors, such as skilled labour or infrastructure; 2) demand conditions, which refers to the nature of market demand for the industry’s product or service; 3) related and supporting industries, meaning the presence or absence in the nation of supplier industries and other related industries, and 4) firm strategy, structure, and rivalry (Raines, 2002).
However, Porter’s contribution has attracted a significant criticism from academics due to its theoretical basis, form, identification and significance. According to (Martin and Sunley, 2003), although the generalizable concept of Porter’s model has attracted policy makers, it still raises several concerns. These are related to the geographical scale of the cluster, lack of coherence in the theoretical basis, and methodological issues ((Rocha, 2004; Markusen, 1999). Consequently, academics applied the model in various settings, redefined what constituted a cluster through their use, and produced an array of definitions (Martin & Sunley, 2003Swords, 2013).
Subsequently, there was a general shift from considering material links and input-output linkages towards a broader concern with social and institutional factors as sources of competitive advantage in the national and global economy. The concept of innovative milieu receives significant attention among academics, and the work of the GREMI school of economists has played a significant role in advancing the innovative milieu concept (Keeble & Wilkinson, 1999; MacKinnon et al., 2002). The innovative milieu emphasises the role of an innovative atmosphere in supporting entrepreneurship, where technology, organisation, and territory are the key elements forming a localised cluster without strict boundaries.
The innovative milieu assumes that within a given geographical area, relationships develop naturally and generate a localised dynamic process of collective learning that reduces uncertainty in the innovative networking system. According to Spigel (2015a), combinations of social, political, economic, and cultural elements within a region support the development and growth of innovative businesses, and encourage entrepreneurs and other actors to take the risks of starting, finding, and assisting high-risk ventures .
However, these models do not include socio-cultural factors, so the emphasis is on networks of knowledge, socio-cultural, political, institutional and governmental agencies to encourage innovative activities (Audretsch, 1998Spigel, 2015a), and enhance business performance and economic development (Ingram & Roberts, 2000).
Clearly, a richer and more balanced cluster analysis incorporates not only elements of the social capital approach covering social relations and collaborative activities, but also historical and socio-cultural factors. Empirical work on network relationships and entrepreneurs’ access to resources, as well as its implications for the success and growth of SMEs during their early-stage, has been patchy. There is therefore a need for analysing and testing network relationships on multiple levels in order to understand two matters: (1) how network relations and structure enable entrepreneurs accessing resources during the early-stage of SME’s, and (2) how network relations and structure impact SMEs success and growth. Accordingly, network analysis may be adopted to investigate these matters.
220.127.116.11.1 Network Analysis
Social network analysis focuses on ties that combine to form networks among people, groups of people, organisations, and countries. Social network analysts assume that interpersonal ties matter, as do ties among organisations or countries, because they transmit behaviour, attitudes, information, or goods. Social network analysis offers a methodology to analyse social relations, and it tells how to conceptualise and analyse social networks. The main goal of social network analysis is detecting and interpreting patterns of social ties among actors (Nooy et al., 2005). There are two perspectives relating to the level at which return or profit is conceived. These are whether profit is accrued for the group or for the individual.
At the individual level, the main focus is on individual’s use of social capital. This means examining how individuals access and use resources embedded in social networks to gain returns in instrumental action. The focal points for analysis in this perspective are 1) how individuals invest in social relations, and 2) how they capture the embedded resources in the relations to generate a return (Lin, 1999). These perspectives have been explored in different terms, such as the strength of weak ties (Granovetter, 1973), or the structural autonomy created by network complexity (Burt, 1997).
Granovetter (1973) argued the network structure based on the idea of “the strength of weak ties”. He claimed that weak ties in relations, such as business-based relations, could be more beneficial than strong ties, such as friendship-based relations, since the former provide an access to diverse resources that might not be available within the latter. Therefore, it is better for the individual to invest in weak-ties relations to capture the embedded resources in the relation to generate a return.
As a way of making social capital effective, the strength of ties has also been suggested to be essential. This idea comes in as a blend of the measure of time, the emotional power, the closeness, and the proportional services that portray the tie (Granovetter, 1973). Nevertheless, this model is exceptionally restricted, in light of the fact that it only considers the strength of ties and disregards all other essential issues including their content and the sequence of development for the system structures as they unfold.
On the other hand, Burt’s argument is framed in terms of the structural hole concept, which describes the social capital defined by the brokerage opportunities in a network (Burt, 1997). He argues that social capital is a function of an individual’s opportunities in a network, which means that certain network forms deemed social capital can enhance the entrepreneur’s ability to identify and develop opportunities (Burt, 2005). Therefore, the entrepreneur with more social capital gets higher returns, because the network affects resource flow and access (Pollack et al., 2015; Tan et al., 2015; Yiu & Lau, 2008).
At the collective level, the main focus is on social capital at the group level, with discussions on how certain groups develop and maintain more or less social capital as a collective asset, and how such collective assets enhance the entrepreneurs’ group chances (Lin, 1999). Network density is often used to measure collective social capital (Burt, 2005De Clercq et al., 2015), as it is assumed that defines it as the resources made available to all individuals via social linkages within the collective (Tan et al., 2015).
Since access to resources is a significant element in the growth and success of SMEs, networking at a collective level is generally expected to provide considerable advantages to these firms in the early stages of their development. According to Semrau and Werner (2014), the resulting resources derived by that entrepreneurs at this early-stage are: (1) financial capital, (2) information and knowledge, and (3) access to additional business-relevant contacts, such as consultants and customers. Moreover, Martin et al. (2016) emphasise that entrepreneurs can thus benefit from their networks on an individual and collective level.
Using networks can, therefore, potentially increase a firm’s chances of success and growth and lower its risk of failure (Watson, 2010). For example, when entrepreneurs are able to access to resources not under their control in a cost-effective way through networking that can influence the success and growth of SMEs. Lin (1999) also argued that networks facilitate the flow of information that can provide the entrepreneur with useful knowledge about opportunities and choices. In addition, networks may exert influence on the actors who play a critical role in decisions involving the entrepreneur due to their strategic locations, positions, possession of valued resources and greater power.
The above analysis highlighted several key concepts, including actors, relational ties, groups, relations, and networks, that are fundamental to the social network discussion. The first concept, actors, are discrete individual, corporate, or collective social units that applicably focus on collections of actors that are all of the same type (Wasserman & Faust, 1994) such as entrepreneurs and institutions of resource generators. However, some methods allow looking at actors of conceptually different types or levels, or from different sets (Leenders, 2002), such as at the individual and collective level.
Second, relational ties refer to the link between actors. The defining feature of a tie can be quite extensive due to the variety, types and range of ties. However, there are common examples of ties that are usually employed in network analysis, such as transfer of material resources and formal relations as authority (Wasserman & Faust, 1994).
Third, the group concept has been given a wide range of definitions by socialists, but in general, we can define it as the collection of all actors on which ties are to be measured. One can argue by theoretical, empirical, or conceptual criteria that actors in the group belong together in a more or less bounded set. Indeed, once one decides to gather data on a group, a more concrete meaning of the term is necessary. A group, then, consists of a finite set of actors who for conceptual, theoretical, or empirical reasons are treated as a finite set of individuals on which network measurements are made (Wasserman & Faust, 1994).
The relation concept suggests that the collection of ties of a particular kind are measured on sets of performers from a particular performer set and that the ties themselves just exist between particular sets of performers. In general, the social system comprises of sets of performers who are related. The relational information for these performers is a basic and characterizing feature of the social system (Wasserman & Faust, 1994).
Therefore, a social network can be analysed based on its features at the individual and collective level. Network density presents the social network feature at the individual level, and can be defined as the average frequency of communication among the entrepreneurs or SMEs in the inter-network. It is assumed that the higher the density of a network, the more it resembles a clique in which all members communicate and interact with each other (Tan et al., 2015).
On the other hand, the social network can be analysed at the collective level by what is called network structure. Social structure can be identified by the network size, which refers to the total number of people with whom the entrepreneur interacts for business-relevant purposes such as accessing resources. It can also be identified by network ties, which refers to the network relations characterised by frequent interactions, a long duration of relations and a closed socio-emotional bond. Accordingly, it is assumed that the size of an entrepreneur’s network in the early stages of business is positively associated with access to resources. In addition, an entrepreneur’s number of weak ties in early-stage business may be positively associated with access to resources (Sullivan & Ford, 2014).
Empirical studies on SMEs’ growth have been criticised for being limited and scattered today, meaning, the researcher who set out to contribute meaningfully to this line of empirical has a number of challenges to address, due to the large number of empirical studies without a high yield of generalizable knowledge. According to Davidsson and Wiklund (2006), the major challenge in the empirical studies of the SMEs growth is the lack of longitudinal design, where growth is a process that needs to be studies over time. Studies in this area are usually based on secondary data, survey data or case studies.
The first option serves the purpose of testing theoretical propositions or estimating empirical relationships, and thus cannot be used to develop conceptually richer theories. The second alternative can be used if we need data on attitudes, perceptions, strategies and resources from a large number of cases. Case studies, on the other hand, are sometimes longitudinal in the sense of firms’ growth followed in real time, where these studies are valuable in developing hypotheses, yet might never suffice for making generalisations about relationships. Accordingly, longitudinal data can really yield satisfactory analyses for theory testing and development can be undertaken; yet his could require more time and more funds to collect the data.
Another challenge the researcher might face while conducting SMEs’ growth study is the complex nature of the firm’s growth, because it involves economic, social, and cultural factors, meaning, different conceptions of firms’ growth (Audretsch et al., 2014). Therefore, complicity in analysing the firm’s growth comes from depending not only on specific firm characteristics, but also on external characteristics, such as location, clusters, and networks. Further challenges concern which measures are suited best to capture growth, and a gap between what business growth means for practitioners and how it is defined and measured by academics scholars (Achtenhagen et al., 2010).
Therefore, Davidsson and Wiklund (2006) have suggested overcoming the challenges of conducting SMEs’ growth studies. First, develop a satisfactory basic research design. Second, apply a well-founded conceptualisation of growth, which in turn requires a well thought-out conceptualisation of the firm. Third, adequately match this conceptualisation with the purpose of the study, the theories used and the operationalisation of growth. To follow these suggestions, we first need to discuss the growth conceptualisation, and then develop the research design to match it with the study purpose.
Firm’s growth is conceptualised and measured in a number of ways. The term of growth is used with two different implications: one to represent the change in the assets, sales or employment (Cressy, 2009; Davidsson & Wiklund, 2006); and the other represent an increasing in size or improvement in quality as a result of an internal process of development (Achtenhagen et al., 2010). The first one is considered the dominant concept in the entrepreneurship studies. Sales growth is considered the best growth measure, because it seems unlikely that growth in other dimensions, such as employment and assets, could take place without increasing sales (Davidsson & Wiklund, 2006).
Although sales growth has a high generality, it could be criticised of being lack of robustness, because some SMEs might seek to minimise their reported sales to avoid VAT. Therefore, researchers have adopted alternative measurements, such as employment and assets growth (Cressy, 2009), but the researcher should be aware of the problem of assets growth as a measure in the service sector. Measuring growth in term of assets is often problematic in the service sector, due to the difficulty in data collection rather than lack of relevance (Davidsson & Wiklund, 2006). Therefore, the suitability of utilising any of these three aspects of growth is contingent on the unit of analysis, which, as mentioned before, include individual, activity, or the governance structure.
According to Davidsson and Wiklund (2006), sales and assets indictors are more suitable, where employment is the least suitable indicator when the analysis on the individual level, yet all these indicators are suitable if the government structure is studied. If the activity is used as the unit of analysis, employment and asset indicators have limited suitability. Therefore, applying multiple indicators of growth gives richer information and might be better than a single indicator.
There is increasing interest in SMEs’ growth among academics and policy makers, due to the role played by SMEs (Blackburn & Schaper, 2012) in economic and social development, such as job creation, fostering economic growth, improving competitiveness and regional development. However, only limited evidence supports the notion that SMEs create many jobs. In the U.S, Canada and the UK, only a minority of SMEs employs workers with 20% to 30% (Carroll et al., 2000), where other countries such as Denmark and Germany have employed workers with 46% and 51%, respectively (Cowling, 2003). The literature has identified serval growth barriers that can enhance or hinder the survival of entrepreneurial businesses (Caves, 1998).
First, motivation drivers, such as desire, need for additional income and socialising, are often cited as important factors in starting entrepreneurial activities. Second, it is noteworthy that entrepreneurial skill development is likely to be achieved by providing organisational support, such as training and coaching (Vik & McElwee, 2011). Third, cultural and organisational aspects, such as motivating competition and innovation, strengthen business and industries (Williams & Vorley, 2014; Mayer, 2013). Therefore, supporting industries through entrepreneurship could require massive changes in entrepreneurial environment (Vik & McElwee, 2011; Williams & Vorley, 2014), and this should be considered when designing and adopting the entrepreneurship development policy (Down, 2012).
Accordingly, one can argue that the role played by SMEs in the economy can be determined or facilitated by the entrepreneurial environment, such as rules and regulations, education and culture, which might be under the heading of institutions that shape economic interactions (Fogel, 2006). To explain, rules and regulations matter because they affect transactional trust and so facilitate entrepreneurship by establishing rules to protect rights and to minimise the time and the cost of business establishment. Moreover, cultural and organisational aspects also matter, such as motivating competition and innovation, which would strengthen the SMEs’ growth and success (Williams & Vorley, 2014; Mayer, 2013). Therefore, this could require providing institutional support to create the entrepreneurial environment (Vik & McElwee, 2011; Williams & Vorley, 2014) in order to promote the motivations and remove the obstacles to SMEs growth (D. B. Audretsch et al., 2007).
In the case of Saudi Arabia, although the government has adopted policies to strengthen the private sector by enhancing the business environment, namely easing business establishments through programmes (e.g. Kafalah programme) that provide different types of supports (e.g. financial, training, educational and legal support). However, previous studies indicate that SMEs did not contribute to the economic development in Saudi Arabia significantly (Thompson et al., 2012; Mohammad & Ahmad, 2012), with only 33% and 25% to the GDP and employment, respectively, and less than 3% revenues to the total private sector, which from the other side generates low skilled job opportunities (Albakr, 2015).
One can argue that the reason for the insignificant role of the SMEs in the Saudi economy could refer to the lack of entrepreneurial culture in Saudi Arabia. To explain, the main features of Saudi culture could have a negative impact on the SMEs’ performance and therefore weaken their role in the economy, namely, favouring the large-scale enterprise, favouring public sector jobs, fearing change, risk aversion, and orienting towards security (Mohammad & Ahmed, 2013). The Global Entrepreneurship Mentor (GEM) data of the entrepreneurial behaviour and attitudes in Saudi Arabia (2016) indicate that the early stages entrepreneurial activity rate and business establishments are low— less than 10%. This could be because 40% of the population (18–64 years old) fear failure, which prevents them from setting up a business, and low entrepreneurial intentions rate are, a mere 1%. In addition, the data shows that some of the government support considered sufficient, where other supports are inefficient. For example, the government entrepreneurship programmes and business services are insufficient, where the entrepreneurial finance and governmental regulations and policies are sufficient.
Although the GEM indicators show that 70% of entrepreneurs believe they have the required skills and knowledge to start a business, yet another study indicates the majority of entrepreneurs lack the required skills to manage their business, which negatively impacts the growth of their businesses (Elmahgop et al., 2015). Accordingly, this guides us to another reason for the insignificant role of the SMEs, which is focusing on the financial support to increase the business establishment rate more than the quality of SMEs (Khorsheed et al., 2014). Therefore, selective categories for adopting and encouraging SMEs in the early stages could be useful to achieve the potential results of SMEs in the economy. In addition to enhance the businesses and entrepreneurship services (Salem, 2014), such as establishing networks among entrepreneurs to enable them to access different resources (e.g. financial, practical, knowledge and information) (Khorsheed et al., 2014)
Regarding the selective categories of the SMEs, these selections could be based on specific characteristics as mentioned in the GEM report by Singer et al. (2015). These include the main business drivers, high-growth expectation, new product-oriented market and international-oriented market. First, the main drivers to start new business include 1) opportunity-based, which involves taking advantage of a business opportunity or having a job but seeking a better opportunity; 2) necessity-based, which involves having no better choice for work as opposed to opportunity; and 3) improvement-driven opportunity, which indicates the main driver is independence or increased income, rather than just maintaining income.
Another initial charachteristis of the early stage entrepreneurial activity is the high-growth expectation, which refers to the expectation to employ at least 20 people five years from now, and the new product-market-oriented, which refers to producing a new product or service to at least some customers and that not many businesses offer the same product or service. Finally, internatational-oriented indicate the percentage of their customers from foreign countries, and according to this report it should be at least 25% (Singer et al., 2015).
Therefore, the government can adopt a selective policy focusing on the SMEs that have the capacity to improve the economy (Storey & Greene, 2010; Landström, 2005). This means focusing on the SMEs that have a potential role in increasing employment (Allen, 1989; Storey & Greene, 2010), innovation (Acs & Audretsch, 1989), and enhancing the private sector in Saudi by providing the necessary support for success and growth. In other words, adopting SMEs that have a high potential to grow; therefore, the quality of SMEs is more important than the quantity. According to Levie and Autio (2013) entrepreneurs with growth intentions in the population are a more significant predictor of economic growth than general start-up rates or self-employment rates, because they might reflect three groups of characteristics: individual, business and environmental. Different empirical studies have examined different factors and how they influence the SMEs growth, namely, clusters and social network analysis.
Current research on entrepreneurship is a dynamic and multifaceted theoretical perspective influenced by a number of contextual factors. Gedajlovic et al. (2013) suggest paying more attention to the context of the investigation to achieve greater rigour and relevance, in addition to social capital to theory partially fill the need for good theory in entrepreneurship. To explain, they discuss research challenges that might bring many opportunities for future research, such as differentiating between social capital resources and their sources, possibly examining the relationships between social capital sources and the outcomes, and considering different levels of analyses and contexts.
Similarly, Zahra (2007) discusses and suggests three strategies for conceptualising in entrepreneurship research. First, presenting the boundaries of contexts to apply a model that is suitable for context. For example, institutional context plays an important role in shaping role structures, opportunity cost, and the amounts and types of resources available (Gedajlovic et al., 2013). Second, the researcher should question the widely held assumptions associated with a given theory. Third, the researcher should recognise contingencies that influence relationships.
Many studies on entrepreneurship have searched and examined various types of relationships or network structure (Gedajlovic et al., 2013) and how these relationships and network might affect the SMEs’ growth; namely, the cluster and network analysis. Firstly, empirical evidence shows that, given institutional support, clusters have a positive impact in fostering innovation (Baptista & Swann, 1998) and competitiveness (Porter, 1990), especially in high-technology clusters (Keeble & Wilkinson, 2000). Secondly, clusters increase the firms’ productivity and profitability, becuase businesses perform better within clusters than non-clustered businesses (Visser, 1999). Clusters also support businesses on an international scale, as they enhance competiveness that results in an increase in their contribution to world trade (Porter, 1990).
Thirdly, another study indicates that clusters help to increase employment (Sonobe et al., 2012), although it has impacted negatively in other cases (Rocha, 2004). Moreover, some clusters assist in increasing their regions’ contribution to national GDP, because the best economic performance occurs within clusters due to networking (Rodríguez-Pose & Comptour, 2012). Therefore, empirical studies indicate the importance role of cluster’ networks in fostering SMEs growth and strengthening their contribution to national and international economy; yet none of the previous studies have analysed and searched clusters’ networks and how they influence entrepreneurship (SMEs).
An interest in networks has permeated SMEs research that could be categorised as either focusing on the causes of network structure or their consequences, where the networks took three main perspectives in the network research; entrepreneurial network, social network and business network (Slotte-Kock & Coviello, 2010).
Scholars have begun to recognise the idea that entrepreneurs and entrepreneurship are socially situated (Gedajlovic et al., 2013).
Mention is made of investment in social relations with expected returns (Lin, 1999); thus, individuals engage in interactions and networking to enhance outcomes concerning access to resources at multiple levels of analysis and across a diverse set of situations and contexts (Gedajlovic et al., 2013). Resources such as knowledge, information and trust derive from relationships among individuals or collectives, as well as the frequency of the interaction, relationship or strength of ties to those resources (Gedajlovic et al., 2013).
Pollack et al (Pollack et al., 2015) found that the revenue generated is significantly influenced by the quality of the network, that is, the entrepreneur’s affective commitment to a networking group. Moreover, there is evidence to suggest that the frequency of interaction has a significant impact on venture growth and survival (Hansen, 1995; Watson, 2007), as well as the growth of small businesses (Lee & Tsang, 2001). However, there was no evidence to suggest a significant impact on the performance of emerging entrepreneurs (Johannisson, 1996), let alone the survival of ventures (Aldrich & Reese, 1994).
From a theoretical perspective, it has been claimed that weak ties in relations, such as business-based relations, could be more beneficial than strong ties, such as friendship-based relations, because the former provide access to diverse resources that might be not available within the latter (Mark S Granovetter, 1973). Network analysis also focuses on relations between individuals or organisation and entrepreneurs’ access to resources. Theoretically, Burt (2005) contends that the structure of the network represents social capital, particularly as it affects the flow of resources and what network actors can do with it (Pollack et al., 2015; Tan et al., 2015; Yiu & Lau, 2008).
Network structure characteristics, such as network size and the strength of the ties, are often used to capture social capital at the firm level (Burt, 2005; Semrau & Werner, 2014; Tan et al., 2015). It was found that entrepreneurs rely significantly on their network of social relationships as a crucial and primary source of all kinds of resources (Ozdemir et al., 2014), where the size of the entrepreneurs’ network has a positive impact on venture survival (Hansen, 1995; Raz & Gloor, 2007). However, evidence shows that size of the entrepreneurs’ network has no significant impact on revenue (Batjargal, 2007), performance of nascent entrepreneurs (Johannisson, 1996), and business survival (Aldrich & Reese, 1994).
At the collective level, network density is often used to measure collective social capital (Burt, 2005; De Clercq et al., 2015). Tan et al. (2015) define it as the resources made available to all individuals via social linkages within the collective. Empirical contributions show that network solidity has a positive impact on sales growth, performance (Stam & Elfring, 2008) and venture growth (Tan et al., 2015). Other evidence examined the impact of structural hole as the gap between disconnected members in social network, and found that it has a negative impact on entrepreneurs’ performance (Batjargal, 2007) and venture’s profit growth (Batjargal, 2003).
Reachability is another characteristic of the network that some researchers consider in the network analysis. This concept searches for whether an actor is reachable by another if there is a set of connections that can be traced from the source to the target actor, regardless of how many others fall between them (Hanneman, 2014). Reachability can measure and present whether different resource generators are reachable and entrepreneurs can have access to different resources through close or distant contacts (Greve, 1995). Different measurements can be found in the literature to measure resource access, such as resource generator, position generator and name generator, which in general examine a variety of ties that the entrepreneur can use to access different resources. Strong ties refer to emotional intensity, and frequency, such as friend and family, whereas weak ties refer to infrequent, irregular contacts such as work and business relations (Memon, 2016; Seibert et al., 2001; Brüderl & Preisendörfer, 1998).
According to Van Der Gaag and Snijders (2005), three main issues should be considered in choosing the measurement to investigate resource access in a certain network. These include, distribution and productivity, meaning how it helps individuals attain their goals in addition to personal resource collection, and to what extent the network is responsible for which effects and under what conditions. By comparing three measurements, the resource generator is the suitable measure to consider these issues. To explain, the name generator maps the individual social network that depends on the conclusion of name interpretation questions; thus, this can result in very detailed and informative social capital descriptions. The position generator measures access through network members to occupations, seen as representing social resource collection based on job prestige in a hierarchically modelled society, yet it has limited use. The resource generator measures the availability of resources by measuring the tie strength through which resources are accessed and indicated by the role of these ties. This instrument can be administrated quickly, and it can result in valid and easily interpretable representations network analysis.
In the broadest term, the social networks are defined by a set of actors (individuals or organisations) and a set of linkages between actors. In the entrepreneurship literature, developed and entrepreneurial network have a significant impact on resource access and flow, and hence, on the positive outcome of SMEs. According to Hoang and Antoncic (2003), three components emerge to explain the process of network development and they have impact on business outcomes: 1) the nature of the content that is exchanged between actors; 2) governance mechanisms in relationship; and 3) the network structure created by the crosscutting relationships between actors. Empirical studies show this can be found in the cluster network with shared common actors (Walker et al., 1997) where positive outcomes are in opportunity identification, resource mobilisation, the creation of business (Shane & Venkatartaman, 2000), and innovative performance (Spigel, 2015b; Tan et al., 2015).
Trying to come up with information concerning SMEs growth can be done depending on some assumptions. However, concerning the general assumptions, concepts, and the relationships in these concepts, it was distinguished that there are four theoretical viewpoints that fall into either the element or the process classifications. These incorporate the resource-based viewpoint, motivation, strategic adaption, and the configuration viewpoint (Sexton & Landström, 2000; Davidsson & Wiklund, 2006).
In the resource-based viewpoint, the main emphasis is on the firm as a pool of resources as well as the activities that can be done using the same resources. This assertion brings out the idea of using a business activity or any related set of business activities to analyze the growth of SMES in the resource-based viewpoint. On the other hand, motivation viewpoint emphasis on the people and their activities to explore the connection between individual’s motivation and the growth of the firm (Sexton & Landström, 2000; Davidsson & Wiklund, 2006).
Third, the strategic adaption perspective relates to the governance structure and activity as units of analysis of the strategic options, which clearly is not designed for individual unit of analysis. Finally, the configuration perspective deals with the growth process, which means focusing on the managerial problems appear and can be dealt with during a firm’s growth through presumed typical stages of development (Sexton & Landström, 2000; Davidsson & Wiklund, 2006).
Access to resources is a significant element in the growth and success of SMEs; therefore, networking at a collective level is generally expected to provide considerable advantages to SMEs at the early stages of their development. According to Semrau and Werner (2014), the resulting resources derived by that entrepreneurs at this early-stage are : (1) financial capital; (2) information and knowledge, which involves knowledge that is useful to the process of starting and managing a business (Jenssen & Koenig, 2002); and (3) access to additional business-relevant contacts, such as consultants and customers. Moreover, Martin et al. (2016) emphasise that entrepreneurs can thus benefit from their networks on individual and collective levels. In addition, access to human resource that involves the workforce that has the required education, experience, knowledge, personal experience and training for a job in a business (Rotefoss & Kolvereid, 2005). Another advantage, access to the practical resources, can cover all legal and registration procedures to start, ease business establishment and protect business owner rights (Klapper et al., 2010).
Clearly, a richer and more balanced cluster analysis incorporates not only elements of the social capital approach and network analysis corning social relations and collaborative activities, but also historical and socio-cultural factors. Empirical work on network relationships and entrepreneurs’ access to resources, as well as its implications for the success and growth of SMEs during their early stage, has been patchy. Thus, here is a need for analysing and testing network relationships on multiple levels in order to understand two matters: (1) how network relations and structure enable entrepreneurs accessing resources during the early-stage of SME’s; and (2) how network relations and structure impact on SMEs’ success and grow. Accordingly, this research will search these matters based on the theoretical and empirical framework in the next section.
As mentioned before, the government should adopt a selective policy focusing on the SMEs that have the capacity to improve the economy (Storey & Greene, 2010; Landström, 2005). These SMEs could play a positive role in innovation (Acs & Audretsch, 1989), job creation potential (Allen, 1989; Storey & Greene, 2010), and regional development (Storey & Greene, 2010). However, we believe these policies should not only focus on the quantity, but also focus on the quality of the SMEs to achieve these potential results in the economy. This means it is better to have selective categories for adopting and encouraging SMEs, which raises an important question: what should these categories include?
Following the GEM report (Singer et al., 2015), first, we consider two of its characteristics of the entrepreneurial activity, due to the initial problems in the Saudi economy high unemployment and weak private sector. Second, focusing on the early-stage phase to define our category of the SMEs, because accessing resources is considered a significant challenge and a key element for SMEs’ success and growth in their early stages. According to this report, the characteristics of the early stage entrepreneurial activity include the high-growth expectation and the new product-market of the early stage entrepreneurial activities. High-growth expectation, as to who expects to employ at least 20 people five years from now, and the new product-market, as to who reports their business is new to at least some customers and that not many businesses offer the same product or service. Finally, the early stage phase include setting up businesses 0–3 months and up to 3.5 years old.
As mentioned, because accessing resources is considered a significant challenge and key element for SMEs’ growth in the early stages, institutional, along with other governmental, entities are working to support SMEs through providing three main resources that contribute to business’ growth and success. First, shared social awareness and a supporting business environment can engender business cooperation and facilitate access to resources (Rauch, 2013) within a community. Second, social networking to create pathways for spreading and sharing resources, such as knowledge, financial, practical and human resources (Ozdemir et al., 2014). Finally, these communities are governed by certain norms to support business and remove obstacles to entrepreneurs’ access to resources (Spigel, 2015b).
Accordingly, we tend to assume this cannot be achieved without employing the key forms of social capital, which consist of a network, a cluster of norms, values and expectancies shared by a community; and sanctions that help maintain the norms and network (Halpern, 2005). The promise behind the notion of social capital is simple and straightforward, investment in social relations with expected returns, we can argue that networks, as a form of the social capital, governed by the institutions’ rules to enhance the outcomes of the interaction on the individual (entrepreneurs) and collective level (e.g. entrepreneurs and resource generators) (Lin, 1999).
The main focus of this thesis is searching for the role of institutional support and SMEs’ growth in Saudi Arabia through searching how these institutions enable entrepreneurs access resources, and therefore how this influence the growth of the SMEs, we tend to focus our argument on the resource-based perspective. The growth in this respect can refer to the expansion of related business activities; thus, the individual and the collective level are alternatives for the unit of analysis (Davidsson & Wiklund, 2006). Therefore, the unit of analysis is on the individual (entrepreneurs) and the collective level (institutions and entrepreneurs).
By considering 1) social capital as an asset in networks (Lin, 1999); 2) assuming that individuals interact and network in order to enhance outcomes (Gedajlovic et al., 2013); and 3) networks and collaborative activities have primarily seen as part of the cluster (Bjerke, 2007), we tend to co-operate some of the network analysis into the development of the cluster analysis. It was mentioned that the interaction in the clusters is not limited to only firms, but also involves interaction between institutional and market actors (Ingstrup et al., 2009), such as the resources generators and entrepreneurs in the cluster. However, the analysis of these interactions and networks are not explained in the previous contributions of the cluster theory. Therefore, to do this we will apply the network analysis.
Analysing the benefits and returns of the social capital, network analysis can be done on individual or collective levels. On the individual level, the focus is on the use of social capital by individuals, and how entrepreneurs access and use resources embedded in social networks to gain returns (Ronald S. Burt & Celotto, 1992). On the other hand, for collective level, the attention on social capital is at the group level. In the group, a scrutiny of how the group develops and maintains social capital as a collective resource and how the resource will enhance the members’ business is done (Lin, 1999; Coleman, 1994).
Accordingly, we tend to present the theoretical and empirical framework of this thesis to answer the main three questions of what, how and why in order to understand two matters: (1) how network relations and structures enable entrepreneurs to access resources during the early stage of SME’s; and (2) how network relations and structure impact SMEs success and grow. First, (what) refers to the main factors and concepts for explaining the phenomena. Second, (how) refers to the explanation of casual relationships among these factors or variables to find a pattern of relations. Third, (why) refers to the core of a theory that provides logic and justifications for the first and second questions, in addition to generating new insights, challenges and deeper understanding of the phenomena (Crane et al., 2016; Whetten, 1989).
There are several key concepts at the heart of network analysis, including actor, relational tie, group, relation and network. The first concept, actors, are discrete individual, corporate, or collective social units who applicably focus on collections of actors that are all of the same type (Wasserman & Faust, 1994) yet, other methods allow looking at actors of conceptually different types or levels, or from different sets (Leenders, 2002), such as the individual and collective levels. Therefore, the actors in this thesis refer to the group of entrepreneurs interact on the individual and collective level to access resources within this community as governed by certain institutions to support SMEs growth.
Second, relational ties refer to the link between actors. The defining feature of a tie can be employed here in network analysis, such as the transfer of material resources and formal relations as authority (Wasserman & Faust, 1994). Thus, relational ties in this thesis refer to the link of the individual and collective level that allow entrepreneurs to access resources, whereas the collection of these relational ties defines the relation concept. In other words, entrepreneurs can access resources through a verity of ties: 1) strong ties, such as family and friends; and 2) weak ties, such as business and work related. Strong ties include emotionally intense and frequent of contacts, where the ties that reach outside of one’s social network (on the individual level) are likely to be weak; that is, infrequent contacts and business related (on the collective level) (Memon, 2016). Finally, the social network consists of sets of actors and the relations defining them, meaning the defining feature of a social network depends on the presence of relational information (Wasserman & Faust, 1994). Therefore, the social network could be analysed based on its features on the individual (personal network using the strong ties) and collective levels (outside the personal social network) (Memon, 2016; Seibert et al., 2001; Brüderl & Preisendörfer, 1998).
Social network can be analysed based on several characteristics on both individual and collective levels. First, network density presents the social network feature, which could be defined as the average frequency of communication among the entrepreneurs or SMEs in the inter-network (Tan et al., 2015). Second, the social network could be analysed by the network structure, which can be defined as the pattern of direct and indirect ties between actors and can be identified by the network. Network size refers to the total number of people with how the entrepreneurs interacts for business-relevant purposes such as access resources through weak strong ties (Hoang & Antoncic, 2003). The term of tie refers to the network relations characterised by frequent interactions, a long duration of relations and a closed socio-emotional bond, where the weak ties are the opposite (Sullivan & Ford, 2014). Third, resources access is another characteristic of the network that is also can be affected by the network density and structure (Hanneman, 2014; Greve, 1995), which can be measured by the resource generator measure. The resource generator measures the availability of resources by measuring the tie strength through which resources are accessed, as indicated by the role of these ties. This instrument can be administrated quickly, and can result in valid and easily interpretable representations network analysis (Van Der Gaag & Snijders, 2005).
As we mentioned before, investment in the networks is a form of social capital governed by certain rules within a community to generate returns. Accordingly, SMEs’ growth are more likely when the network is more developed on the individual and collective level (Martin et al., 2016), because social networks create pathways for spreading and access resources, such as knowledge spill-overs between businesses and universities, and connecting entrepreneurs with resource generators (Ozdemir et al., 2014).
On the one hand, social networks might facilitate information and resources flow, which could reduce the transaction cost for SMEs to engage better and enhance trust among entrepreneurs in the inter-network; and, thus, this would support the early stages SMEs (Lin, 1999). Therefore, the higher the density network, the more it resembles a clique in which all members communicate and interact with each other (Tan et al., 2015); thus, it might enable entrepreneurs’ access to resources on the individual level.
On the other hand, network size and tie might have a significant impact on access resources in the early-stages SMEs. This means increasing the number of organisations with whom the entrepreneurs interact for resources access, and also increasing the frequency of business relations interactions positively associated with access resources. This is because during the very early stage, an entrepreneur engages in many learning and information-seeking activities to organise the initial form of the business. Moreover, during the business launch, the entrepreneur is likely to benefit from a larger set of network ties to gain access to resources (Sullivan & Ford, 2014).
Accordingly, because it was claimed that access resources are associated positively with network relations (Ozdemir et al., 2014) and structure (Sullivan & Ford, 2014), entrepreneurs can use their networks, on the individual and collective levels, as resources generators to assist their growth and success (Martin et al., 2016) during the early stages of SMEs. This means SMEs’ growth is more likely when the network is more developed on the individual and collective levels, that is, when different resources (financial, knowledge, practical and human resources) are available, accessible and productive. In addition to the size and strength of weak ties, the network is associated positively with network development and, hence, on the outcome of the SMEs. To explain, enhancing the size of the network, the entrepreneurs may get an access to resources from others by strong or weak ties. Thus, the structure of the network may be helpful for entrepreneurs to organise and expand the opportunities that are available to the entrepreneur (Memon, 2016). The density of a network may give insights into the speed at which resources are accessed by entrepreneurs through weak and strong ties (Hanneman, 2014), and thus influence the potential growth of their businesses when SMEs are more likely to grow in a developed network.
To investigate and analyse in-depth how the cluster network enables entrepreneurs to access different resources and thus influence the potential growth of the SMEs, the following questions need to be addressed regarding the collective and individual levels:
Frist: On the collective level (institutional level):
- Who are the network’s actors in the cluster?
- What is the link between these actors in the cluster?
- What is the network structure (size), and density?
- How does cluster network enable entrepreneurs to access different resources (e.g. financial, knowledge and information, practical, and human resources)?
- What is the role of the cluster network in influencing the potential growth of SMEs?
Second: On the individual level (entrepreneur’s level):
- How much does the cluster network enable entrepreneurs to access different resources (e.g. financial, knowledge and information, practical, and human resources)?
- Does resource access via cluster’s network influence the potential growth of SMEs?
To address these questions, several concepts need to be clarified to provide the empirical evidence for each question. Table (2-1) summarises the main concepts to answer each of the above questions. Table (2-2) and Figure (2-1) summarise the conceptual and empirical framework of the network analysis on the individual and collective levels.
|Question||Required Concepts to Answer Research Questions|
|1. Who are the network actors in the cluster?||The cluster’s actors include those who own the resource, make them available for an entrepreneur and can access them through social network to help entrepreneurs attain their goals.|
|2. What is the link between these actors in the cluster?||Strong tie refers to emotionally intense and frequent contact such as friend and family, whereas weak tie refers to infrequent and irregular contact, such as work and business relations.|
|3. What is the network structure (size) and density in the cluster?||1. Network structure: A) network size: the total number of ties that institutions interact in the cluster to enable entrepreneurs to access to different resources.
2. Network density: the average frequency of communication between institutions in the cluster to enable entrepreneurs to access to different resources.
|4. How does cluster network enable entrepreneurs to access different resources?||Availability, accessibility, and productivity of different resources (e.g. financial, knowledge and information, practical, and human resources) via the cluster network.|
|5. What is the role of the cluster network in influencing the potential growth of SMEs?||Potential growth of SMEs in the early stage can be identified by: 1) High-growth expectation as to who expects to employ at least 20 people five years from now; 2) New product-market as to who reports that their product or service is new to at least some customers and that not many businesses offer the same product or service.|
|6. How much does the cluster network enable entrepreneurs to access different resources?||Resource generator measurement: availability, accessibility, and productivity of the collection of resources on the individual level.|
|6. Does resource access via cluster’s network influence the potential growth of SMEs?||Compare the resource generator measurement for each resource (financial, practical, knowledge and information, and human resources) between two groups of SMEs (has potential growth and does not have potential growth).|
|Characteristic of developed network:|
|1. Network structure: the pattern of direct and indirect ties between actors that can be identified by network size and the number of the weak and strong ties to access resources.||The number of ties is positively associated with resources access and thus with the potential growth of SMEs.||Enhancing the size of the network, the entrepreneurs may get an access to resources via the cluster network. This is because increasing the actors in the cluster network might be helpful to expand the opportunities available to the entrepreneur.|
|2. Network density: the average frequency of ties communications between the network actors.||The strength of ties is positively associated with the rescores access and thus with the potential growth of SMEs.||The frequency and strength of ties between different actors indicate the level of trust between them, which might positively influence the process of resource access and thus the potential growth of SMEs.|
|3. Resource generator: it presents the availability, accessibility and productivity of resources in the cluster network on the individual and collective levels.||The more resources available, easy to access and productive, the more the network is developed; thus, the potential growth of SMEs is positively influenced.
A developed network should be able to make sure that different resources (financial, knowledge and information, practical, and human resources) are available, easy to access by entrepreneurs and help entrepreneurs to achieve their goals.
|The influence of the cluster network on the potential growth of SMEs:|
|The potential growth of SMEs can be identified by: 1) High-growth expectation as to who expects to employ at least 20 people five years from now; and 2) New product-market as to who reports that their product or service is new to at least some customers and that not many businesses offer the same product or service.||The more entrepreneurs access to different resources the more positive influence on their potential growth. To explain, the more entrepreneurs access resources the more profits they can make through producing new services and products that differ from other SMEs, thus, the opportunity to grow and employ people.|
Table (2-2) Conceptual and Empirical Analysis of the Network Analysis
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