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There is a sense of dynamism and excitement relating to prospects for increased cooperation in trade, investment, and cultural exchange between emerging market nations and the developed countries of the world economy. There is also a sense of uncertainty and instability inherent in the transitioning into more responsive economic systems and the shifting power bases which have come to characterize economic globalization. This has created a dual need, shared by developed countries and emerging markets alike, to understand dynamic international business environments and to learn from each other.

Emerging markets are propelled by the need to catch up with the developed countries in the areas so well delineated by the World Economic Forum’s Global Competitiveness Reports -- technological innovation, predictable public institutions, labor standards, capital utilization, and efficiency. Business education provides one of the key and necessary ingredient in this third wave of globalization, as it has come to be termed. Professors from overseas are often invited as foreign experts to teach, develop curricula, and train the trainers. Simultaneously, developed countries want to tap the potential of emerging markets as evidenced in differing wages, cost advantages, and resource acquisition. Multinational companies and minimultinationals, whether through efficiency or resource or market-seeking, are keen on sourcing products and services overseas and selling their products and services to the same destinations. This virtuous cycle fuels the economic growth so evident in emerging market dynamism and provides the impetus for new models of educational cooperation.

This chapter has presented empirical estimates of the impact of the local technological infrastructure on innovative activity. Using the SBIR Phase II award as the measure of innovation, this impact was examined at two levels: (1) on the likelihood of innovative activity occurring in a metropolitan area and (2) on the level of innovative activity.

The evidence indicates that geographic proximity to the sources of knowledge spillovers and agglomeration plays a significant role in the innovative process and that this role varies across industries. This supports previous research with similar findings at both the state and metropolitan area levels for patents and innovation counts. Industrial R&D and research universities provide significant spillovers to high-tech firms, particularly in terms of their likelihood to engage in innovative activity. Agglomerative economies due to the clustering of industrial employment, business services, and general economic activity also influence innovative activity. The following chapter examines the impact of the government agency that funds SBIR activity on the effect of the local technological infrastructure.

This chapter has reviewed the theoretical relationship between innovative activity and spillovers from knowledge and agglomeration. The local technological infrastructure encompasses the sources of agglomeration and knowledge spillovers. Positive externalities emanating from the local technological infrastructure can foster increased innovative activity within a geographic area. It has been established that geographic proximity influences the strength of these spillovers. Agglomeration of resources, particularly labor supply and business services, provides incentives for firms to cluster geographically and to innovate. Knowledge spills over from both private and public arenas. The most significant source of private knowledge is industrial R&D activity, while universities serve as the bastions of public knowledge. Proximity to the source of knowledge spillovers matters for innovative activity.

This chapter has outlined the methodology used in this study to estimate the effects of knowledge spillovers and agglomerative economies on innovative activity. Following past research, a knowledge production function is employed to examine the effects of knowledge spillovers and agglomerative economies on the innovative activity of high-tech small firms at the metropolitan area level. A unique data set is constructed using Phase II awards from the SBIR Program as the primary measure of innovative activity, and a hurdle model for count data is used to econometrically estimate the spillover and agglomeration effects related to the innovation process. The hurdle model uses a two-step procedure, so that the effect of the local technological infrastructure is first estimated on whether or not innovative activity occurs (probit equation) and then on the rate of innovation (negative binomial equation).

The empirical findings are reported in Chapters 5 and 6. Chapter 5 presents the findings for Phase II activity by industry. Chapter 6 explores whether or not the spillover process is related to the federal agency providing the SBIR funding for Phase II. Chapter 7 presents empirical results for patent activity, where patents serve as the measure of innovation. Chapter 7 broadens the scope of this analysis by examining the local technological infrastructure’s effect on the patent measure of innovation and thus provides the means for comparison between Phase II activity and patenting.

This chapter has presented empirical estimates of the impact of the local technological infrastructure on innovative activity. Using the SBIR Phase II award as the measure of innovation, this impact was examined at two levels: (1) on the likelihood of innovative activity occurring in a metropolitan area and (2) on the level of innovative activity.

The evidence indicates that geographic proximity to the sources of knowledge spillovers and agglomeration plays a significant role in the innovative process and that this role varies across industries. This supports previous research with similar findings at both the state and metropolitan area levels for patents and innovation counts. Industrial R&D and research universities provide significant spillovers to high-tech firms, particularly in terms of their likelihood to engage in innovative activity. Agglomerative economies due to the clustering of industrial employment, business services, and general economic activity also influence innovative activity. The following chapter examines the impact of the government agency that funds SBIR activity on the effect of the local technological infrastructure.

There is a sense of dynamism and excitement relating to prospects for increased cooperation in trade, investment, and cultural exchange between emerging market nations and the developed countries of the world economy. There is also a sense of uncertainty and instability inherent in the transitioning into more responsive economic systems and the shifting power bases which have come to characterize economic globalization. This has created a dual need, shared by developed countries and emerging markets alike, to understand dynamic international business environments and to learn from each other.

Emerging markets are propelled by the need to catch up with the developed countries in the areas so well delineated by the World Economic Forum’s Global Competitiveness Reports -- technological innovation, predictable public institutions, labor standards, capital utilization, and efficiency. Business education provides one of the key and necessary ingredient in this third wave of globalization, as it has come to be termed. Professors from overseas are often invited as foreign experts to teach, develop curricula, and train the trainers. Simultaneously, developed countries want to tap the potential of emerging markets as evidenced in differing wages, cost advantages, and resource acquisition. Multinational companies and minimultinationals, whether through efficiency or resource or market-seeking, are keen on sourcing products and services overseas and selling their products and services to the same destinations. This virtuous cycle fuels the economic growth so evident in emerging market dynamism and provides the impetus for new models of educational cooperation.

This chapter has presented empirical estimates of the impact of the local technological infrastructure on innovative activity. Using the SBIR Phase II award as the measure of innovation, this impact was examined at two levels: (1) on the likelihood of innovative activity occurring in a metropolitan area and (2) on the level of innovative activity.

The evidence indicates that geographic proximity to the sources of knowledge spillovers and agglomeration plays a significant role in the innovative process and that this role varies across industries. This supports previous research with similar findings at both the state and metropolitan area levels for patents and innovation counts. Industrial R&D and research universities provide significant spillovers to high-tech firms, particularly in terms of their likelihood to engage in innovative activity. Agglomerative economies due to the clustering of industrial employment, business services, and general economic activity also influence innovative activity. The following chapter examines the impact of the government agency that funds SBIR activity on the effect of the local technological infrastructure.

This chapter has reviewed the theoretical relationship between innovative activity and spillovers from knowledge and agglomeration. The local technological infrastructure encompasses the sources of agglomeration and knowledge spillovers. Positive externalities emanating from the local technological infrastructure can foster increased innovative activity within a geographic area. It has been established that geographic proximity influences the strength of these spillovers. Agglomeration of resources, particularly labor supply and business services, provides incentives for firms to cluster geographically and to innovate. Knowledge spills over from both private and public arenas. The most significant source of private knowledge is industrial R&D activity, while universities serve as the bastions of public knowledge. Proximity to the source of knowledge spillovers matters for innovative activity.