Classifying Technology Policy from an Evolutionary Perspective

Asked for the most important driving forces of economic development, most economists do not hesitate to state, that it is technical progress which is the main source of quanti-ta-ti-ve and qualitative economic development generated in National Systems of Innovation (NSI). To classify and analyze NSI's the con-cepts of mission- and diffusion-oriented policy designs were introduced. Although, we suppose this taxonomy to be well suited to analyze techno-logy policy, it seems to us in its basic formulation somewhat crude, especially with respect to the supposed characteristics to assign a specific innovation system to the one or the other policy design. To surmount these shortcomings we develop a new classificatory scheme building on a questionnaire approach and suggesting four categories to spread out between the tech-nology and the economic side. This scheme allows for deeper insights and more evident com-pa-risons of different NSI's.

Heterogeneity and Evolutionary Change - Empirical Conception, Findings and Unresolved Issues

In this position paper we deal with the conception of heterogeneity as both the force and the result of evolutionary change. We ask, how this heterogeneity can be measured empirically and how we can get a measure which allows to get a broad comparable empirical account especially on several levels of aggregation. Based on this discussion we suggest that for several questions the measures of total factor productivity (TFP) and local changes of TFP seem to be acceptable candidates for measuring heterogeneity and its dynamics. Examples out of a number of empirical investigations applying this measures show how interesting empirical facts about evolutionary change on several levels of aggregation can be detected. The paper concludes by raising a number of unresolved issues mainly related to the question about the relationship between evolutionary dynamics on several levels of aggregation.

The Use and Effect of Social Capital in New Venture Creation - Solo Entrepreneurs vs. New Venture Teams

This paper examines the use of social capital in the venture creation process. We compare solo entrepreneurs (n=182) and new venture teams (n=274) from a random sample of start-ups in innovative industries and test social capital use and its effects on firm performance. Our results reveal that solo entrepreneurs and new venture teams do not differ in their degree of use of social capital. However, there are differences in the determinants of social capital use in both groups. We find that weak ties assist solo entrepreneurs and have positive significant effects on new venture performance. For team start- ups, we find no direct effect of social capital. However, further tests indicate for teams that human capital variety positively moderates the effect of social capital on performance.Entrepreneurship, Nascent entrepreneurship, Social capital, Start-up teams, Entrepreneurial learning

The Regional Dimension of Sectoral Innovativeness An Empirical Investigation of Two Specialised Supplier and Two Science-Based Industries

The aim of this paper is to test how geographical and technological proximity relate to a particular industry's innovative output. Two mechanisms are therefore tested, i.e. agglomeration economies and the regional exploitation of technological proximity. A new dataset is applied, which includes German patent applications from within the period 1995 to 2006. Four industries are considered, two of which are science-based, whereas the remaining two are specialised supplier industries. While diversity is associated with high innovative output in the specialised supplier industries, the results for specialisation are mixed. However, all industries seem to benefit, at least to a certain degree, from the regional re-combination of their own technologies with those of specific key industries.Innovation, Proximity, Diversity

Disentangling the Effects of New Venture Team Functional Heterogeneity on New Venture Performance

Previous research on entrepreneurial teams has failed to settle the controversy over whether team heterogeneity helps or hinders new venture performance. Reconciling this inconsistency, this paper suggests a new conceptual approach to disentangle differential effects of team heterogeneity by modeling two separate heterogeneity dimensions, namely knowledge scope and knowledge disparity. Analyzing unique data on functional experiences of the members of 337 start-up teams, we find support for our contention of team heterogeneity as a two-dimensional concept. Results suggest that knowledge disparity negatively relates to both start-ups' entrepreneurial and innovative performance. In contrast, we find knowledge scope to positively affect entrepreneurial performance, while it shows an inverse U-shaped relationship to innovative start-up performance.Entrepreneurial teams, New venture performance, Team heterogeneity, Team diversity

Picking the Winner? - Empirical Evidence on the Targeting of R&D Subsidies to Start-ups

This paper investigates the allocation of R&D subsidies given to start-ups. Considering the coexistence of various R&D project schemes, we take an aggregate view and analyze the determinants of the receipt of (any) R&D subsidies within the first three business years of the start-ups. We argue that policymakers and funding authorities follow a strategy of "picking the winner". Analyzing a unique data set of start-ups in the East German state of Thuringia, we conduct logistic regressions and find ambiguous support. R&D subsidies are given to start-ups with innovative business ideas, especially academic spin-offs. On the other hand, the ambitions and the patent stock of the founder(s) do not decide the receipt of R&D subsidies. These insights into the overall allocation of R&D subsidies are important since they have implications for policy effectiveness and efficiency. The implied difficulties of policy targeting fundamentally question the massive subsidization of private R&D.Start-ups, R&D subsidies, Subsidy allocation

Entrepreneurial ecosystems: a dynamic lifecycle model

The concept of entrepreneurial ecosystems has been used as a framework to explain entrepreneurial activities within regions and industrial sectors. Despite the usefulness of this approach, the concept is under-theorized, especially with regard to the evolution of entrepreneurial ecosystems. The current literature is lacking a theoretical foundation that addresses the development and change of entrepreneurial ecosystems over time and does not consider the inherent dynamics of entrepreneurial ecosystems that lead to their birth, growth, maturity, decline, and re-emergence. Taking an industry lifecycle perspective, this paper addresses this research gap by elaborating a dynamic entrepreneurial ecosystem lifecycle model. We propose that an ecosystem transitions from an entrepreneurial ecosystem, with a focus on new firm creation, towards a business ecosystem, with a core focus on the internal commercialization of knowledge, i.e., intrapreneurial activities, and vice versa. Our dynamic model thus captures the oscillation that occurs among entrepreneurs and intrapreneurs through the different phases of an ecosystem’s lifecycle. Our dynamic lifecycle model may thus serve as a starting point for future empirical studies focusing on ecosystems and provide the basis for a further understanding of the interrelatedness between and co-existence of new and incumbent firms

Cooperation and Specialization in German Technology Regions

We investigate cooperative behavior within technology regions in patenting activities. Case studies of local innovation systems point out certain characteristics fruitful to innovation and regional growth but often pronounce historical singularities as major influence. We provide evidence on the same theoretical basis in an econometric study. Based on a theoretical discussion of research cooperation hypotheses are derived which relate a regions technological characteristics to that regions account of research cooperation. Patent data are used to define the technological specialization of German regions and identify cooperations within and between them. Most cooperations tend to take place in modestly specialized regions, indicating a need for similar technological capabilities between partner firms.

Determinants influencing the choice of a cooperation partner

This paper provides empirical tests of hypotheses of cooperative behavior provided by evolutionary approaches in the resource-based view of the firm. The influences of "technological proximity", individual incentives to cooperate and managerial tools to the choice of research partner are analyzed. Using German patent data we can show the positive influence of those three determinants. The results of this paper confirm theories dealing with the path-dependency of research activities.innovation, resource-based view of the firm, cooperation, technological proximity, organizational know-how