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Article

Nydia MacGregor and Tammy L. Madsen

A substantial volume of research in economic geography, organization theory, and strategy examines the geographic concentration of interconnected firms, industries, and institutions. Theoretical and empirical work has named a host of agglomeration advantages (and disadvantages) with much agreement on the significance of clusters for firms, innovation, and regional growth. The core assertion of this vein of research is that geographically concentrated factors of production create self-reinforcing benefits, yielding increasing returns over time. The types of externalities (or agglomeration economies) generally fall into four categories: specialized labor or inputs, knowledge spillovers, diversity of actors and activity, and localized competition. Arising from multiple sources, each of these externalities attracts new and established firms and skilled workers. Along with recent advancements in evolution economics, newer research embraces the idea that the agglomeration mechanisms that benefit clusters may evolve over time. While some have considered industry and cluster life-cycle approaches, the complex adaptive systems (CAS) theory provides a well-founded framework for developing a theory of cluster evolution for several reasons. In particular, the content and stages of complex adaptive systems directly connect with those of a cluster, comprising its multiple, evolving dimensions and their interplay over time. Importantly, this view emphasizes that the externalities associated with agglomeration may not have stable effects, and thus, what fosters advantage in a cluster will change as the cluster evolves. Furthermore, by including a cluster’s degree of resilience and ability for renewal, the CAS lens addresses two significant attributes absent from cyclical approaches. Related research in various disciplines may further contribute to our understanding of cluster evolution. Studies of regional resilience (usually focused on a specific spatial unit rather than its industrial sectors) may correspond to the reorganization phase associated with clusters viewed as complex adaptive systems. In a similar vein, examining the shifting temporal dynamics and development trajectories resulting from discontinuous shocks may explain a cluster’s emergence and ultimate long-term renewal. Finally, the strain of research examining the relationship between policy initiatives and cluster development remains sparse. To offer the greatest theoretical and empirical traction, future research should examine policy outcomes aligned with specific stages of cluster evolution and include the relevant levels and scope of analysis. In sum, there is ample opportunity to further explore the complexities and interactions among firms, industries, networks, and institutions evident across the whole of a cluster’s evolution.

Article

Erik E. Lehmann and Julian Schenkenhofer

The pursuit of economic growth stands out as one of the main imperatives within modern economies. Nevertheless, economies differ considerably in their competitiveness. Theories on the endogeneity of growth agree on the value of knowledge creation and innovativeness to determine a country’s capability to achieve a sustained performance and to adapt to the dynamics of changing environments and faster information flows. To this effect, national institutional regimes shape nation-specific contexts and embed individuals and firms. The resulting incentive structures shape the attitudes and behavior of individuals and firms alike, whose interactions contribute to the accumulation and flow of knowledge among the nodes of their networks. National systems of innovation (NSIs) therefore embody a concept that aims to analyze the national innovation performance of economies. It rests its rationale in the variation of national institutions that shape the diffusion of technologies through the process of shared knowledge creation and the development of learning routines. Both public and private institutions are thought to interact in a given nation-specific institutional context that essentially affects incentive schemes and resource allocation of the involved economic agents in creating, sharing, distributing, absorbing, and commercializing knowledge. To this effect, public policy plays a key role in the NSI through building bridges between these actors, reducing information asymmetries, and providing them with resources from others within the system. The different actors contributing to the creation and diffusion of knowledge within the system are needed to exchange information and provide the engine for sustained economic growth. Universities, research institutes, companies and the individual entrepreneur are in charge of shaping their economic system in a way that resource and skill complementarities are exploited to the mutual benefit.

Article

Cristina Chaminade and Bengt-Åke Lundvall

This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Business and Management. Please check back later for the full article. Scientific advance and innovation are major sources of economic growth and are crucial for making social and environmental development sustainable. A critical question is if private enterprises invest sufficiently in research and development and, if not, to what degree and how governments should engage in the support of science and innovation. While neoclassical economists point to market failure as the main rationale for innovation policy, evolutionary economists point to the role of government in building stronger innovation systems and creating wider opportunities for innovation. Research shows that the transmission mechanisms between scientific advance and innovation are complex and indirect. There are other equally important sources of innovation, including experience-based learning. Innovation is increasingly seen as a systemic process where the feedback from users needs to be taken into account when designing public policy. Science and innovation policy may aim at accelerating knowledge production along well-established trajectories or at giving new direction to the production and use of knowledge. It may be focused exclusively on economic growth, or it may give attention to the impact on social inclusion and the natural environment. An emerging topic is the extent to which national perspectives continue to be relevant in a globalizing learning economy facing multiple global complex challenges, including the issue of global warming. Scholars point to a movement toward transformative innovation policy and global knowledge sharing as a response to current challenges.

Article

Fred Gault and Luc Soete

Innovation indicators support research on innovation and the development of innovation policy. Once a policy has been implemented, innovation indicators can be used to monitor and evaluate the result, leading to policy learning. Producing innovation indicators requires an understanding of what innovation is. There are many definitions in the literature, but innovation indicators are based on statistical measurement guided by international standard definitions of innovation and of innovation activities. Policymakers are not just interested in the occurrence of innovation but in the outcome. Does it result in more jobs and economic growth? Is it expected to reduce carbon emissions, to advance renewable energy production and energy storage? How does innovation support the Sustainable Development Goals? From the innovation indicator perspective, innovation can be identified in surveys, but that only shows that there is, or there is not, innovation. To meet specific policy needs, a restriction can be imposed on the measurement of innovation. The population of innovators can be divided into those meeting the restriction, such as environmental improvements, and those that do not. In the case of innovation indicators that show a change over time, such as “inclusive innovation,” there may have to be a baseline measurement followed by a later measurement to see if inclusiveness is present, or growing, or not. This may involve social as well as institutional surveys. Once the innovation indicators are produced, they can be made available to potential users through databases, indexes, and scoreboards. Not all of these are based on the statistical measurement of innovation. Some use proxies, such as the allocation of financial and human resources to research and development, or the use of patents and academic publications. The importance of the databases, indexes, and scoreboards is that the findings may be used for the ranking of “innovation” in participating countries, influencing their behavior. While innovation indicators have always been influential, they have the potential to become more so. For decades, innovation indicators have focused on innovation in the business sector, while there have been experiments on measuring innovation in the public (general government sector and public institutions) and the household sectors. Historically, there has been no standard definition of innovation applicable in all sectors of the economy (business, public, household, and non-profit organizations serving households sectors). This changed with the Oslo Manual in 2018, which published a general definition of innovation applicable in all economic sectors. Applying a general definition of innovation has implications for innovation indicators and for the decisions that they influence. If the general definition is applied to the business sector, it includes product innovations that are made available to potential users rather than being introduced on the market. The product innovation can be made available at zero price, which has influence on innovation indicators that are used to describe the digital transformation of the economy. The general definition of innovation, the digital transformation of the economy, and the growing importance of zero price products influence innovation indicators.

Article

Poverty is more than a lack of money or an inability to afford basic necessities. It is an experience that is multidimensional and includes challenges related to literacy, health, food security, housing, transportation, safety, fatigue, underemployment, limited social networks, and limited access to many opportunities available to those in other income categories. Poverty is a pernicious global problem with unacceptably high levels persisting in spite of trillions of dollars of annual spending by governments and other organizations. While this kind of investment represents a critical lifeline to many individuals and families, it is not moving enough of them out of poverty. As a result, there is a need to explore alternative solutions and approaches. Entrepreneurship, or the creation of businesses, by those experiencing poverty is one potential pathway to a better life. Yet it is a pathway about which we understand relatively little. While the poverty–entrepreneurship interface has received growing attention from scholars over the past few years, very little theoretical or conceptual work has been done. More critically, there is scant empirical evidence on such basic questions as the rate of business creation by those in poverty, success and sustainability rates, key success factors, the role of institutions and entrepreneurial ecosystems in venture outcomes, and much more. The unique difficulties faced by these entrepreneurs can be captured through the liability of poorness, a concept which includes gaps in five types of literacy, a scarcity or short-term orientation, severe nonbusiness distractions, and the lack of any safety net. As a result, the ventures that are created tend to be survival businesses that are labor intensive, with low margins, little differentiation, no bargaining power with suppliers or customers, lack of equipment and technology, and limited capacity. These are fragile enterprises, suggesting the priority may not simply be fostering higher levels of start-up activity among the poor, but interventions that enable them to become sustainable. A beginning point in realizing the potential of entrepreneurship as a poverty alleviation tool is the development of new insights on expanding opportunity horizons of these individuals, helping them escape the commodity trap, rethinking resourcing and microcredit, and assisting with adoption of the entrepreneurial mindset.