1 Entrepreneurial knowledge, technology and the transformation of regions
It seems safe to claim that entrepreneurs with their varying presence and their varying activities play a critical role for the speed with which regions transform as well as for the direction of this transformation. Entrepreneurs are individuals (or groups of individuals) who specialize in making choices that require an intensive use of judgement, i.e. choices that involve unprecedented situations in which different people are likely to make different decisions (Casson, 1982). Entrepreneurship can be defined as the discovery, evaluation and exploitation of entrepreneurial opportunities by potential entrepreneurs with the goal to earn profit (cf. Venkataraman, 1997; Shane and Venkataraman, 2000; Low, 2001). Thus, without entrepreneurial opportunities, there is no entrepreneurship (Short et al., 2011). The entrepreneurial opportunity may be a potential new product (good or service), a new variety of an existing product or a more efficient production or distribution process for an existing product.1
What activities entrepreneurs are capable of performing is, among other things, a function of the entrepreneurial knowledge that they dispose at each moment in time. It is also a function of the general situation in the market place, changes in the market place and changes in available technological and other knowledge. Each potential entrepreneur is located in a particular region2 and these regions vary in terms of their demand and supply characteristics and in terms of their exposure to market changes and technological changes. This implies that entrepreneurship has to be analysed within a spatial context (van Oort and Stam, 2009).
Another important factor to consider is that many goods and services are complex with a contact-intensive production and distribution and/or are traded under complex and contact-intensive conditions. Thus, many new goods and services, in particular, are non-standardized and/or their trading procedures are non-routine. Such contact-intensive goods and services have distance-sensitive transaction costs, which rise sharply when transactions are made between regions. Larger regions have a higher internal market potential, and offer low geographical transaction costs within the region. Thus, larger regions offer better location conditions for the introduction and production of contact-intensive goods and services on account of their ‘economic density’.
This implies that the available entrepreneurial opportunities3 at each point in time vary between regions. This is a fundamental observation that too often has been neglected in entrepreneurship research.4 This is unfortunate since the effect is that it is impossible to understand the potential of entrepreneurship to transform different regions if this fundamental observation is neglected. It is precisely this state of the art that is the basic motivation for putting this book together. Thus, the purpose of this book is to present a number of research contributions that all contribute to a better understanding of the role of entrepreneurial knowledge and technology for the transformation of regions.
The aim of this introductory chapter is to give an overview of research concerning the role of entrepreneurial knowledge and technology for the transformation of regions. It is organized as follows. In the first section the concepts of entrepreneurial knowledge and entrepreneurial human capital are introduced and discussed. The second section focuses on the role of knowledge and technology in generating entrepreneurial opportunities. The transformation of regions and the role of entrepreneurial knowledge and technology are discussed in the third section. The different chapters of this book are then introduced in the fourth section.
Entrepreneurial knowledge and entrepreneurial human capital
What, then, is entrepreneurial knowledge? Entrepreneurial knowledge is knowledge about how to identify, evaluate and act upon entrepreneurial opportunities. At the individual level, entrepreneurial knowledge is part of general human capital and can be named entrepreneurial human capital. It includes know-how, know-why, skills and abilities relevant and needed for discovering, evaluating, acting on and managing entrepreneurial opportunities. Entrepreneurial human capital consists of general entrepreneurial human capital relevant for all types of entrepreneurship and specific entrepreneurial human capital relevant for specific industries, technologies, etc. We assume here that the level of entrepreneurial human capital is a main factor explaining the capacity of potential entrepreneurs to identify, evaluate and use entrepreneurial opportunities.5
How then is entrepreneurial human capital formed? Generally, it is a function of the background and up-bringing of individuals, general and specific education and training, and the general and specific learning an individual has accumulated via her/his different work and other life experiences, through different types of media and through the interaction with other people – entrepreneurs and researchers but also ordinary citizens. Since the influences of these factors vary between individuals, we may conclude that the entrepreneurial human capital will vary substantially over individuals (cf. Hayek, 1945). This implies that in any given context, different individuals will often discover different entrepreneurial opportunities to the extent that they discover any, because they possess idiosyncratic entrepreneurial human capital (Venkataraman, 1997). Furthermore, even if they discover the same entrepreneurial opportunity they might very well evaluate it differently because of the differences in what entrepreneurial human capital they possess. This implies that the existence of information asymmetry is not necessary for entrepreneurial opportunities to exist, as claimed by Shane (2000).
Entrepreneurial opportunities may be discovered without active search, i.e. just recognized (Kirzner, 1997), but in many cases we have to imagine that there is an active search initiated by an observed unfulfilled demand in the market, a new technological opportunity without obvious use, etc. We can assume that different potential entrepreneurs differ in terms of their information about particular customer problems, available technologies, their motivation to search, their search costs (Stiglitz, 1994), their search efficiency because of differences in entrepreneurial human capital and so on, which explains relative differences in opportunity discoveries between different potential entrepreneurs. In both cases, we can assume that the ability to recognize entrepreneurial opportunities is a function of the entrepreneurial human capital that people possess.
Entrepreneurial human capital is cumulative and built up through different types of learning processes. In this connection, Andersson and Karlsson (2004) stress the role of learning-by-doing. What is learnt in one period builds upon what was learnt in earlier periods. Thus, the individual's life history matters, which implies risks for lock-in effects (cf. Arthur, 1989) but also a potential for increasing returns, implying that learning over time tends to create the foundation for better decisions6 (Minniti and Bygrave, 1999). Acquired entrepreneurial human capital generates decisional procedures and routines, i.e. patterns derived from successful solutions to some particular problem earlier (Nelson and Winter, 1982).
Entrepreneurial human capital is a dynamic concept. The build-up of entrepreneurial human capital varies over individuals, and the speed of build-up may vary over time. We can imagine, for example, that the speed of learning declines as technologies and industries mature. Thus, the total supply of entrepreneurial human capital varies over time.
At each period in time there are a certain number of individuals equipped with the right volume and type of entrepreneurial human capital that generate the alertness (Kirzner, 1973 and 1979) to detect and/or create entrepreneurial opportunities worthwhile pursuing, and the ability to deal with the uncertainty that entrepreneurial acts involve (Knight, 1921). Uncertainty is inherent in entrepreneurial acts since the knowledge that entrepreneurs possess, in particular of the future, by necessity is imperfect (Keirstad, 1957).
Since human beings are semi-immobile and tend to spend extended periods in each region where they live, it is obvious that the pertinent regional economic, social and cultural milieus will distinctly influence the entrepreneurial human capital of different individuals. For example, some regional milieus are characterized by frequent entrepreneurial events, i.e. entrepreneurial experiments, and this implies that these regional milieus offer better opportunities to build up entrepreneurial human capital and, not least, entrepreneurial skills (Hansen, 2001) than regional economic milieus with relatively few entrepreneurial experiments. Furthermore, the composition of the entrepreneurial experiments differ between regions, which implies that different regions induce differences in terms of from which industries, technologies, markets and so on that people can learn.
Much of the research on entrepreneurial learning has a very strong individualistic focus. The role of the regional context and the networking opportunities it offers with a potential for knowledge spillovers is often not considered enough. It is obvious that individuals also learn from the experiences of other individuals directly or indirectly. The acquisition of external knowledge and experiences often requires the establishment of qualified inter-personal relations and of mechanisms such as trust that are able to mediate knowledge interactions. In every particular case of knowledge exchanges, there will be frictions and the friction costs will vary according to geographic, technological, organizational, cultural and other distances (Johansson and Karlsson, 2009). Frictions appear when knowledge is complex (Beckmann, 2000), tacit (Polanyi, 1966) or ‘sticky’ (von Hippel, 1994). Face-to-face communication is essential under these circumstances because it allows individuals to calibrate their coding and encoding capabilities and their interpretations.
Over time, individuals may build up knowledge networks by investing in intangible ‘channels’ or links for knowledge exchange (Beckmann, 1994). We can assume that many potential entrepreneurs deliberately invest in building up knowledge networks but that these knowledge networks will differ between different potential entrepreneurs on account of resource differences, different locations, different abilities in building knowledge networks, etc. However, what knowledge will be acquired through the different links is uncertain, which naturally implies that such investment, as all other investments, is risky.
Knowledge networks will, to some extent, reduce the importance of distance between regions but resource limitations will reduce the potential of inter-regional knowledge links for potential entrepreneurs. An interesting implication of the stickiness of knowledge is that knowledge can be shared between entrepreneurs and potential entrepreneurs in the local milieu of a functional region with little risk that the knowledge diffuses outside the region. This is one reason why it is often so easy for entrepreneurs to cooperate in clusters and industrial districts and to be open to potential entrepreneurs, and why knowledge spillovers are frequent in such economic milieus.
Summarizing the above discussion, we state that each region at each point in time has a distribution of general entrepreneurial human capital as well as many distributions of specific entrepreneurial human capital over its population. What these distributions look like in different regions is a function of their history including their volume of entrepreneurial experiments in the past, their industrial and technological specialization, their size, their education system, their institutions, their external links and so on. This also implies that regions can be less well equipped when it comes to general entrepreneurial capital and lack certain types of specific entrepreneurial capital but also that part of the available entrepreneurial capital might be obsolete because of technological and/or market changes.
Knowledge, technology and entrepreneurial opportunities
In this section, we discuss the role of knowledge and technology for the emergence of entrepreneurial opportunities. It seems to be an unfortunate tradition in most of the entrepreneurship literature to treat entrepreneurial opportunities as exogenous and instead explain the level of entrepreneurship as a function of the characteristics of individuals (Audretsch and Keilbach, 2011). However, there are strong reasons to believe that there are systematic differences in entrepreneurial opportunities over industries, technologies and regions. In the last decade, this has led researchers to try to find explanations to the variations in the emergence of entrepreneurial opportunities. One major attempt is the ‘Knowledge Spillover Theory of Entrepreneurship’ (Audretsch and Aldridge, 2008) that will be briefly discussed here. However, the conclusion in this section is that this ‘theory’ only can give a partial explanation and that it is necessary to consider how other changes in society than the emergence of new knowledge and new technologies can generate entrepreneurial opportunities. Without a good understanding of how entrepreneurial opportunities emerge, it is very difficult to formulate prescriptions for policies aimed at stimulating entrepreneurship (McMullen, Plummer and Acs, 2007).
Important work on the role of knowledge and technology in modern endogenous growth theory claims that ‘knowledge’, and its accumulation and application in the form of new technologies, are fundamental for the generation of sustained growth in industrialized economies (Romer, 1986: Lucas, 1988; Koo, 2005; Henderson, 2007). The spillover of knowledge is here a central mechanism through which incumbent firms and potential entrepreneurs can benefit from research results or from relevant knowledge within incumbent firms. Potential entrepreneurs exploit the entrepreneurial opportunities that are not observed or not exploited by incumbent firms (Audretsch, Keilbach and Lehman, 2006). The emergence and growth of new firms is seen as the missing link between investments in knowledge and technology and economic growth (Audretsch and Lehmann, 2005).7
However, what is unclear in this approach is how the knowledge spillovers generate entrepreneurial opportunities. It is clear that knowledge spillovers are neither automatic nor costless. Thus, as stressed by Karlsson and Nyström (2011), a fundamental question in entrepreneurship research concerns how potential entrepreneurs discover new knowledge-based entrepreneurial opportunities. There are certainly important restraints on the magnitude and mechanisms of knowledge transfers (Grossman and Helpman, 1991; Acs and Plummer, 2005). Indeed, knowledge does not diffuse instantaneously within and between regions (Döring and Schnellenbach, 2006). This implies that different economic actors, even if they are located in the same region and active in the same trade, do not share exactly the same knowledge (Karlsson, Johansson and Stough, 2012). In the endogenous growth theory, knowledge investments are decided endogenously, which implies that entrepreneurial opportunities generated by knowledge spillovers are endogenous. Since knowledge investments vary over industries, technologies and regions, and knowledge spillovers are partly bounded in space, entrepreneurial opportunities will vary over industries, technologies and regions. We may also assume that the extent to which entrepreneurial opportunities will be appropriated by incumbent firms will also vary over industries, technologies and regions.
Knowledge varies depending to what degree it is protected by intellectual property rights, and knowledge is also characterized by a greater degree of uncertainty and asymmetry than other types of goods, which generates higher transaction costs for new knowledge (Arrow, 1962). This implies that the mean expected value of any new idea will vary across economic agents, as well as the variance. If an incumbent firm, on account of inherent uncertainty, reaches the conclusion that it is not profitable or worthwhile for other reasons to exploit an idea, a potential entrepreneur may reach a different conclusion.8 Such differences in the valuation of new knowledge may lead to the start up of a new firm by a potential entrepreneur to appropriate the value of the new knowledge. Such a start-up functions as a mechanism by which new knowledge spills over from the source that has produced the knowledge to the new firm through which it is commercialized. A critical question here is, of course, how potential entrepreneurs become aware of and collect the necessary information about various entrepreneurial opportunities since the underlying knowledge is created in incumbent firms, universities and various research institutes. The literature is not very clear concerning the information channels and knowledge links that are involved.
Such entrepreneurial opportunities should, ceteris paribus, be more frequent in contexts where new knowledge plays a greater role, since the degree of uncertainty and asymmetry will be greater as well as induce a higher propensity among potential entrepreneurs to start new firms in order to appropriate the value of the knowledge-based entrepreneurial opportunities they have discovered. Already, Griliches (1992) has stressed that investments in knowledge by firms have a high likelihood to spill over to other firms, which do not pay the full costs of accessing and implementing these ideas for commercialization. Since knowledge spillovers tend to be greater in the presence of higher investments in knowledge, it follows that entrepreneurial opportunities based on exploiting such knowledge spillovers also will be greater. Thus, entrepreneurial activities will tend to be greater in contexts where investments in new knowledge are relatively high, since new firms will be started from knowledge that has spilled over from the source actually producing the new knowledge. In a context with low investments in knowledge production, the relative lack of new ideas will generate fewer entrepreneurial opportunities.
It is obvious that knowledge spillovers only provide a partial explanation of the emergence of entrepreneurial opportunities – an explanation focusing the supply side only. Unfortunately, there is very little general research on the emergence of entrepreneurial opportunities (Plummer, Haynie and Godesiabois, 2007; Companys and McMullen, 2007). To develop a theory that is more complete in explaining the emergence of entrepreneurial opportunities we need also to include the demand side and the general functioning of markets. Large markets generally tend to offer more entrepreneurial opportunities than smaller markets because of a more varied stock of customers with varying preferences. Changes on the demand side generating entrepreneurial opportunities are driven by changes in relative prices, real incomes, preferences and taste. Rising real incomes will generally spur the demand for services as well as a general demand for variety. Public procurement has, for centuries, been another demand-side source of entrepreneurial opportunities.
Changes in institutions and in laws are other obvious sources of entrepreneurial opportunities. Investments in transport and communication infrastructures also open up many entrepreneurial opportunities. They provide the basis for new transport and distribution solutions but, in particular, they reduce the geographical transaction costs, which lower the costs of serving distant markets making it possible for potential entrepreneurs to reach production levels that give them economies of scale in their production.
Either entrepreneurial opportunities emerge on the supply side, on the demand side or through mismatches between supply and demand to the extent that incumbent firms do not seize emerging opportunities (cf. Grek, Karlsson and Klaesson, 2011). They are not exogenously given. Instead, they are created by changes and shocks (Casson, 1999) within the economic, infrastructural, and institutional systems including the generation of new knowledge and technologies, changes that are at least partly driven by various successful entrepreneurial actions, i.e. they are a natural consequence of economic volatility (Casson and Wadeson, 2007). Thus, earlier and ongoing entrepreneurial actions give opportunities for other potential entrepreneurs to exploit entrepreneurial opportunities left out or generated by earlier entrepreneurs (Holcombe, 2003).
In a sense, existing entrepreneurial opportunities are available to all individuals in a region. ‘They are in the air’, to paraphrase Alfred Marshall. However, they are not in a state that they can be used directly. Instead, they consist of unstructured bits and pieces of knowledge and information distributed unevenly over the population in the region (cf. von Hayek, 1945) offering hints about unexploited options9 to earn a profit by meeting a demand in a superior manner, i.e. higher quality and/or lower price. Entrepreneurial human capital is critical for the discovery, evaluation and exploitation of entrepreneurial events (Rønning, Ljunggren and Wiklund, 2010). However, only a share of the individuals possess the necessary entrepreneurial human capital to discover these opportunities (cf., Kirzner, 1973) and even fewer have the necessary human capital to transform these opportunities into actual entrepreneurial events.10 Doh (2012) stresses the importance of social networks for the discovery of entrepreneurial opportunities.
Some entrepreneurial opportunities might be discovered by chance but normally scarce resources, including time, must be devoted to the search for such opportunities and not least to evaluate and develop them into concrete offers of better and/or cheaper goods and services in the market place. The resources devoted represent sunk costs and cannot be recovered if no new goods or services are launched in the market place. Entrepreneurial opportunities are, to a varying degree, characterized by uncertainty, i.e. the potential entrepreneur cannot know in advance how good the entrepreneurial opportunity is. Furthermore, external conditions may change when the potential entrepreneur has started to explore and take advantage of the opportunity.
New entrepreneurial opportunities are created continuously in the economic system even if we can imagine waves in the forthcoming of new entrepreneurial opportunities in relation, for example, to the emergence of new technologies or investments in new infrastructures. These opportunities are not all equally profitable, and not all are discovered immediately on account of lack of information and the fact that it takes time and resources to discover them. There are also diminishing returns in searching for entrepreneurial opportunities, since those opportunities that are discovered first are those that need fewer resources to be discovered. It is also important to observe that the discovery of an entrepreneurial opportunity, and in particular its successful realization, stimulates other potential entrepreneurs to search for similar entrepreneurial opportunities thereby stimulating competition, which may result in the first mover, after some time, going out of business. The followers might have been able to find better entrepreneurial opportunities, or they may just be better entrepreneurs.
It is obvious against this background that the presence, as well as the profitability, of entrepreneurial opportunities varies over geographical space. Furthermore, the supply of entrepreneurial human capital varies over space as well as the resources that potential entrepreneurs dispose to search for entrepreneurial opportunities. The general pattern is that larger dynamic regions with a large demand, plenty of knowledge generating activities and other investments, and good infrastructures will offer more entrepreneurial opportunities than smaller regions (Karlsson and Johansson, 2006). These larger regions normally also have a larger supply of entrepreneurial human capital, and potential entrepreneurs in these regions tend, on average, to have more economic resources than potential entrepreneurs do in smaller regions.
The discussion in this section might be summarized as follows. In each region at each point in time, there exists a distribution of entrepreneurial opportunities related to different industries, technologies and markets that differ from those in other regions. Because of the existence of spatial interaction costs, most of these entrepreneurial opportunities concern the regional market of which some, later on, might be scaled up to also serve distant markets. In each period, local potential entrepreneurs will explore a certain share of these entrepreneurial opportunities at the same time as new entrepreneurial opportunities emerge because of changes in both the demand side and the supply side. There is no guarantee that the potential entrepreneurs will succeed since all entrepreneurial opportunities are associated with risks and uncertainties and not all potential entrepreneurs have the necessary ability and skills to manage entrepreneurial projects. The extent to which local potential entrepreneurs will identify and explore entrepreneurial opportunities can be expected to be a function of the expected profitability of these opportunities. The expected profitability for each level of competition can be assumed to be greater the higher the growth rate of the region. Thus, we expect regional growth to induce a higher level of entrepreneurship. However, the opposite may also be true. In regions with low or negative growth, unemployment will normally increase and when people become unemployed they, in many cases, turn to entrepreneur-ship to find another source of income. Thus, they will try to identify and explore entrepreneurial opportunities. However, unemployed people are often not those individuals with the highest entrepreneurial human capital, so we can expect that the entrepreneurial opportunities they identify are often not the best and that there are limitations in their ability and skills to manage entrepreneurial projects.
Entrepreneurial knowledge, technology and the transformation of regions
We are now in a position to discuss how entrepreneurial knowledge, i.e. entrepreneurial human capital, contributes to transform regions, as well as the importance of regions and their economic milieu for entrepreneurship. The role of location is a sadly neglected issue in the entrepreneurship literature (cf. Parker, 2009). This neglect is not easy to understand since it is obvious that entrepreneurial acts are located in geographical space, and since there is clear evidence that entrepreneurial activities measured as start-up or entry rates vary across geographical space (Santarelli and Vivarelli, 2007). The regional environment is important and cannot be ignored when exploring the causes of firm creation and of new firm growth. The features of the region (Sternberg, 2009) influence both entrepreneurial activities and entrepreneurial success.
Recently, some scholars have started to use multi-level regression models in order to take into account location attributes as well as individual characteristics. Since entrepreneurial activity is a phenomenon that depends on both individual characteristics and features of the regional environment, it seems reasonable to use a regression technique that utilizes multi-level data and makes it possible to separate between regional and individual effects. Stuetzer et al. (2011) argue that we gain a better understanding of how regional characteristics influence entrepreneurial behaviour by combining aggregated data at the regional level with individual level data. The authors state the importance of research investigating the effect of the pathways through which the region actually affects individual entrepreneurship. The results from their study are in line with the notion that a favourable regional environment is linked with individual entrepreneurial engagement. Sanditov and Verspagen (2011) use multi-level analysis to explain how individual factors (such as education and employment status) and country characteristics (such as R&D expenditures and education level) influence individuals' decisions to enter innovative entrepreneurship, i.e. to start up an innovative business. They find that the scope of country-level variables to explain the probability of an individual becoming an entrepreneur is low, i.e. entrepreneurship seems to be driven mainly by individual-level characteristics. However, this does not imply that regional-level variables, i.e. the regional context, do not play a significant role for the probability that an individual becomes an entrepreneur. Multi-level models are also used to investigate how firm characteristics and regional milieu may interact and spur entrepreneurial activity (Raspe and van Ort, 2011).
The reasons why entrepreneurial activities vary over regions are, of course, that the supply and demand conditions as well as growth rates vary over regions thereby generating very different entrepreneurial opportunities, that they differ in terms of entrepreneurial human capital and that potential entrepreneurs dispose of different amounts of economic resources (cf. Karlsson, Stough and Johansson, 2009). On the supply side, regions vary structurally in terms of their knowledge base, information supply, industrial structure, company structure, infrastructure supply, regional institutions, business climate and so on. However, they also vary in terms of dynamic activities, such as knowledge generation, start-up rates, infrastructure investments, imports, exports, etc. This implies that regions vary substantially concerning those conditions that can generate potentially synergetic situations as well support for entrepreneurial learning. It is obvious against the short background that regions differ concerning the extent to which their supply sides contribute to generate entrepreneurial opportunities, entrepreneurial human capital and resources for potential entrepreneurs to engage in the discovery of entrepreneurial opportunities. Our general conclusion is that the larger a region, ceteris paribus, the stronger these supply side effects.
Turning to the demand side, it is obvious that concentrations of (potential) customers (consumers, firms and public sector organizations) with a high purchasing power and a taste for new product varieties stimulate the generation of entrepreneurial opportunities. Certainly, incumbents may seize many of these opportunities, since they know the market better and have established links with customers. However, it need not be a disadvantage with many competitors in the market since, when competition in the product market is imperfect, there are always opportunities to supply new differentiated products (Fujita and Thisse, 2002).
A general advantage of large regions is that the search cost for entrepreneurial opportunities is lower than in smaller regions. This is critical since entrepreneurial opportunities consist of different bits and pieces of knowledge and information that are not neatly structured and the probability to find the necessary bits and pieces is higher in larger than in smaller regions. The lower search costs in larger regions are also critical during the evaluation of discovered entrepreneurial opportunities, since such regions offer a larger supply of potential customers, suppliers, service firms and all kinds of specialists needed to develop entrepreneurial opportunities into entrepreneurial acts.
Another advantage offered by large regions is the larger potential information spillovers in such regions, through which potential entrepreneurs can receive signals about the strength of the regional demand by observing incumbents' successful trade. There are generally large potentials for production knowledge to spill over in large regions, not least because large regions are generally dense regions with well-developed interaction infrastructures. Such observations also inform about varieties of existing goods and services, which of course can highlight potential entrepreneurial opportunities.
The fundamental role of large regions in generating new entrepreneurial opportunities depends in particular upon their role as communication centres because of their more developed transport and communication infrastructure. They are centres of international communication in media, culture, business, politics and science. Actually, large urban regions are each a nucleus of numerous networks ranging from the local to the global (Nijkamp, 2003) and offer network thickness, which tends to encourage the emergence of entrepreneurial opportunities but also reduces the risks involved in transforming such opportunities into new start-ups, since it makes it possible to externalize some of the risks involved (Shapero, 1984). Thus, they offer superior opportunities to develop, in particular, closely-knit intra-regional communication networks, within as well as between sectors in the economy, by offering different interaction networks with various interaction arenas. As a result, the economies of information flows (Acs, Audretsch and Feldman, 1992) on both the demand and the supply side are greater in larger regions than in smaller regions.
One important reason why larger regions tend to generate more entrepreneurial opportunities than smaller regions is that they offer physical proximity with good opportunities and lower costs for face-to-face interaction. This facilitates the integration of multi-disciplinary knowledge that is tacit and therefore embodied in people as well as allowing for the rapid decision-making needed to cope with uncertainty (Patel and Pavitt, 1991). Because of the existence of urbanization economies, these regions also offer diversity, i.e. economies of scope, in information, knowledge, skills, competence, producer services, etc., which are critical for entrepreneurial processes. This diversity advantage is fundamental since entrepreneurial processes are critically dependent upon handling diverse bits and pieces of information and knowledge, which are non-structured, uncertain, complex and often not well understood. It includes access to a large pool of well-educated and specialized labour (Marshall, 1920), particularly specialized workers in accounting, finance, marketing, logistics and various technical fields. This reduces the costs for evaluating and developing entrepreneurial opportunities as well as for starting up and expanding a new business (Krugman, 1993). Furthermore, large and densely populated agglomerations are conducive to a greater provision of non-traded inputs, since their service structure is more developed. Such inputs are provided both in greater variety and at lower costs in large urban regions (Krugman, 1991a and b).
Generally speaking, the larger (and denser) a region, the more entrepreneurial opportunities are generated, the larger the stock of entrepreneurial human capital and the larger the economic resources of the potential entrepreneurs located there. The implications of this statement are far reaching. Since larger regions not only generate more entrepreneurial opportunities but also possess a larger stock of entrepreneurial human capital and have richer potential entrepreneurs, these regions will experience not only more entrepreneurial events – successful as well as unsuccessful – but they will also experience a superior build-up of entrepreneurial human capital, since there are more entrepreneurial acts to learn from in such regions. Thus, we are dealing with cumulative processes, where entrepreneurial success breeds entrepreneurial success. The successful entrepreneurial events will stimulate economic growth and structural change in these regions, which will be the source of still more entrepreneurial opportunities. The structural change will take the form of the emergence and growth of new clusters at the expense of some older clusters, since resources will be attracted to the new and growing clusters, where the new and growing firms generally can pay higher remunerations on account of the market power they possess in their markets characterized by monopolistic competition. The incumbents in the declining clusters will have to, on the one hand, become more productive and, on the other hand, to relocate their production to other, smaller regions that offer lower production costs if they want their business to continue.
Thus, the renewal of the economy in smaller regions is stimulated by the relocation of the production of maturing products from larger regions. We can also assume that potential entrepreneurs in smaller regions observe successful ongoing businesses and, to a certain extent, imitate the actual production and start production in their own region. However, the limited market potential in smaller regions reduces the number of potentially profitable entrepreneurial opportunities in smaller regions. In principle, there exist two major strategies for smaller regions to encourage entrepreneurship and to stimulate economic development. The first strategy is to stimulate entrepreneurship within existing (and potential) clusters to increase the level of external economies, so called co-location or localization economies. The second strategy is to stimulate entrepreneurship concerning products that are characterized by low geographical transactions costs, and thus can more easily be exported to other regions.
The contents of this book
Below we briefly summarize the contributions in the sequence they appear in this book in an attempt to provide the reader with a plan for the reading experience.
The first chapter, by Acs, examines the impact of productive, unproductive, underproductive and destructive entrepreneurship on social value creation. A Global Entrepreneurship and Development Index (GEDI) is constructed which captures the contextual features of entrepreneurship across countries and stages of development. The chapter points out that a country's level of economic development is strongly related to their institutional environment. Better institutions create the incentives to shift agents from less productive activity to more productive activity. Implications for public policy suggest that institutions need to be strengthened before entrepreneurial resource can be fully deployed.
Most current empirical entrepreneurial literature shows a positive correlation between entrepreneurship and economic growth. However, the mechanisms by which entrepreneurship exerts its positive influence on economic growth are not obvious. Westlund, Rader Olsson and Larsson study the connections between entrepreneurship (measured as the number of start-ups) and local development (measured as population and employment growth) at the municipal level in Sweden. In contrast to previous research, their findings indicate that for several branch groups start-up effects on growth may be more pronounced in low density areas than in urban agglomerations.
The objective of the chapter by Crema, Verbano and Venturini is to identify and characterize different profiles of openness of the innovation process towards the external environment in Italian manufacturing firms. The results indicate that two clusters with different levels of openness can be found, in which group membership is significantly influenced by open innovation, employee's innovation capability, collaborative management practices, aggressive technology strategy, information and communications technology (ICT) adoption, employee development and by context variables such as size and performance.
The growth of informal networks has been identified as one of the distinctive features of the evolution of high-tech economies. Less attention has been paid to the extent of the role of formal networks in regional economic development in establishing informal interactions. The chapter by Lawton Smith and Romeo contributes to understanding where and how business networking happens and the value of business networking to participant companies and business professionals. To do so, the chapter uses evidence from a case study of business networks in Oxfordshire in the UK. The chapter argues that extent, membership and utilization reflect stages in development of economic activity in particular locations.
The patterns of shift in production of the European automotive industry is analysed in the chapter by Warda. The focus is on outsourcing strategies performed as offshoring in production of physical goods. Three results are highlighted in the chapter: First, the world producing automotive industry is highly exposed to foreign direct investment (FDI) flows. Second, both employment and local production are decreasing in most Western European countries, but increasing in Central and Eastern Europe. Third, the automotive industry in a few Western European countries is increasing but with a decreased local production.
The chapter by Carbonara and Tavassoli contributes to the ongoing debate concerning the role of knowledge and knowledge heterogeneity for the innovative capability of industrial districts. An analysis on 32 Italian district provinces is applied and the results show that knowledge, knowledge heterogeneity and absorptive capacity of the industrial districts have positive effects on innovation capability.
The role of absorptive capacity is also analysed in the chapter by Márquez-Ramos, Martínez-Zarzoso and Johannsen. The chapter provides empirical evidence on the relationship between technological innovation and international trade using firm-level data in Egypt. The authors take the technological innovation process as absorptive capacity and consider two facets of technological innovation: creation and absorption. Their results show that both creative and absorptive capacity has an important effect on the decision to trade in developing countries.
Cattaneo et al. investigate the valuation and merger and acquisition dynamics of the population of 254 biotech firms that went public in Europe over the last two decades. The authors find that the affiliation with a university is recognized as beneficial for investors and enhances the probability of being targeted in subsequent merger and acquisition deals. They also conclude that initial public offerings and acquisitions by incumbent firms are mechanisms to complete the technology transfer process and to effectively exploit academic innovations.
The effects of spatial agglomeration on KIBS (Knowledge Intensive Business Services) vertical disintegration are analysed in the chapter by Antonietti and Cainelli. The authors use firm-level data for the metropolitan area of Milan and define a set of distance-based density indicators counting the number of neighbouring firms located within a series of concentric rays from each KIBS firm location. They find that KIBS tend to be more disintegrated as the number of neighbouring firms increases. This result is particularly strong for creative KIBS, whereas the correlation for traditional technology-related ones is weaker.
The chapter by Angelakis draws on the innovation system literature with the aim of providing an interpretation on growth aspects, while integrating policy-oriented research into the field of innovation studies. Specifically, it examines institutional and policy methods for the enhancement of production and adoption of knowledge resources in the light of fostering capabilities and economic growth. In focus is the regional innovation system in the Swedish region, Skåne, and particular attention is given to regional institutional and knowledge endowments as well as the role of innovation-supporting institutions and organizations. The chapter illustrates the path through which the Skåne region has developed with several institutional, policy and organizational arrangements in order to form an integrated regional innovation system.
The concepts of innovation and entrepreneurship in relation to job creation from start-ups and young and small second-stage businesses are examined in the chapter by Hackler. The chapter proposes a role for local government policy in cultivating and fostering an innovation and entrepreneurship ecosystem with strategies that, research has shown, help to remove barriers and support entrepreneurs' and small businesses' development. Local actions and programmatic approaches can facilitate networks of public and private stakeholders that build trust and collaboration and leverage local and regional assets. The author also suggests possible problems that these approaches can encounter on account of varied conceptions of entrepreneurship and innovation.
The chapter by Cornett, DaCosta and Ingstrup provides a comparative assessment of cluster initiatives in two medium-sized city regions in very different economic settings, one in the southern part of Denmark and the other in Wisconsin, USA, as well as identifying the impact of cluster-promoting policies in these settings. Despite differences, the regions also have similarities, facing severe challenges from economic restructuring with loss of traditional blue collar employment and the transformation of the local economy toward service and IT-based activities. The findings show that on account of different traditions and economic institutions significant differences in the policies are identified. One of the major aspects appears to be the level of commitment to a cluster development policy.
Doh, Kim and Kim have conducted a study that explores the impact of government policy on the performance of small and medium-sized enterprises (SMEs) in the regional industries in South Korea. The empirical results indicate that patent acquisitions and new design registrations of regional SMEs are positively affected by technological development assistance by government and networks with universities. The authors of the chapter also suggest that there is an important need to build a strong social relationship in today's networked economy.
Attitudes to and perceptions of enterprise support in deprived communities are in focus in the chapter by Huggins and Williams. A survey of 142 entrepreneurs and potential entrepreneurs in the UK city of Leeds is conducted where the entrepreneurial activity and the use of enterprise support are examined. The authors find that certain forms of enterprise support may actually discourage entrepreneurship. Also, where entrepreneurial ventures are supported, they tend to operate in activities relating to generic trades with low entry barriers, with many enterprises having little actual or perceived requirement for external support; it being likely that they would have been established with or without support.
Notes
1. In the literature there are some unfortunate attempts to define entrepreneurial opportunities as only those opportunities that require the discovery of ‘new means-ends relationships that are generated by a given change’ (Shane and Venkataraman, 2000: 222). We don’t agree with this narrow definition of entrepreneurial opportunities.
2. When we use the concept ‘region’ we are thinking of functional regions, which can be approximated with labour market regions, i.e. in most cases an urban centre surrounded by a hinterland that it dominates in terms of inward commuting (Karlsson, Stough and Johansson, 2009).
3. Entrepreneurial opportunities are opportunities to introduce new goods, services, raw materials and organization methods that allow the output to be sold at a price that covers introduction and production costs (cf. Casson, 1982), i.e. an opportunity to engage in entrepreneurial action (Companys and McMullen, 2007).
4. Kirzner (1997) is one obvious example. He claims that entrepreneurial opportunities exist because different people possess different information.
5. Gimeno et al. (1997) analyse the role of entrepreneurial human capital for the survival of new firms.
6. The evidences in the literature point in the direction that entrepreneurs who have been involved in starting up a new venture seem to be more successful and effective in starting up and managing their second and third venture (Politis, 2005).
7. For a review of the relationship between entrepreneurship and growth, see Friis, Karlsson and Paulsson (2006).
8. Alvarez (2003) actually claims that the competitive advantage of potential entrepreneurs increases when uncertainty increases.
9. Casson and Wadeson (2007) use the term unexploited projects.
10. There are probably also some examples where potential entrepreneurs create entrepreneurial opportunities themselves.
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