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Research in the domain of 'Innovation Studies' has been claimed to allow for the study of how technology will develop in the future. Some suggest that the National and Sectoral Innovation Systems literature has become bogged down, however, into case studies of how specific institutions affect innovation in a specific country. A useful notion for policy makers in particular, Balzat & Hanusch (2004) argued that there is a need for NIS studies to develop complementary and also quantitative methods in order to generate new insights that are comparable across national borders. We use data for patents granted by the World Intellectual Property Organization (WIPO) to map innovation systems. Groupings of patents into primary and secondary classes (co-classification) can be used as relational indicators. Knowledge from one class may be more easily used in another class when a co-classification relation exists. Using social network analysis, we map the co-classification of patents among classes and thus indicate what characterizes an innovation system. A main contribution of this paper is methodological, adding to the repertoire of methods NIS studies use and using information from patents in a different way. Policy makers may also find benefits in the social network analysis of the complete set of patents granted by the WIPO to firms and individuals in a country. Social network analysis indicates what innovation activity occurs in a countries and which fields of technology are likely to give rise to innovative products in the near future. We offer such analysis for the Dutch and Indian Innovation Systems. This social network analysis could also be done for a Sector Innovation System, and we do so for Nanotech to determine empirically the knowledge field relevant for this emerging scientific domain.

Evolutionary economics has developed into an academic field of its own, institutionalized around, amongst others, the Journal of Evolutionary Economics (JEE). This paper analyzes the way and extent to which evolutionary economics has become an interdisciplinary journal, as its aim was: a journal that is indispensable in the exchange of expert knowledge on topics and using approaches that relate naturally with it. Analyzing citation data for the relevant academic field for the Journal of Evolutionary Economics, we use insights from scientometrics and social network analysis to find that, indeed, the JEE is a central player in this interdisciplinary field aiming mostly at understanding technological and regional dynamics. It does not, however, link firmly with the natural sciences (including biology) nor to management sciences, entrepreneurship, and organization studies. Another journal that could be perceived to have evolutionary acumen, the Journal of Economic Issues, does relate to heterodox economics journals and is relatively more involved in discussing issues of firm and industry organization. The JEE seems most keen to develop theoretical insights.

Can the knowledge base of an economy be measured? In this study, we combine the perspective of regional economics on the interrelationships among technology, organization, and territory with the triple-helix model, and offer the mutual information in three dimensions as an indicator of the configuration. When this probabilistic entropy is negative, the configuration reduces the uncertainty that prevails at the systems level. Data about more than a million Dutch companies are used for testing the indicator. The data contain postal codes (geography), sector codes (proxy for technology), and firm sizes in terms of number of employees (proxy for organization). The configurations are mapped at three levels: national (NUTS-1), provincial (NUTS-2), and regional (NUTS-3). The levels are cross-tabled with the knowledge-intensive sectors and services. The results suggest that medium-tech sectors contribute to the knowledge base of an economy more than high-tech ones. Knowledge-intensive services have an uncoupling effect, but less so at the high-tech end of these services.

Purpose: to provide a view and analysis of the immediate field of journals which surround a number of key heterodox economics journals. Design/methodology/approach: Using citation data from the Science and Social Science Citation Index, the individual and collective networks of a number of journals in this field are analyzed. Findings: The size and shape of the citation networks of journals can differ substantially, even if in a broadly similar category. Heterodox economics cannot (yet) be considered as an integrated specialty: authors in several journals in heterodox economics cite more from mainstream economics than from other heterodox journals. There are also strong links with other disciplinary fields such as geography, development studies, women studies, etc.

In this paper we offer a way to measure the knowledge base of an economy in terms of probabilistic entropy. This measure, we hypothesize, is an indication of the extent to which a system, including the economic system, self-organizes. In a self-organizing system, interactions between dimensions or subsystems will unintentionally give rise to anticipations that are properly aligned. The potential reduction of uncertainty can be measured as negative entropy in the mutual information among three (or more) dimensions. For a knowledge-based economy, three dimensions can be considered as key: the distribution of firm sizes, the geographical locations, and the technological classifications of firms. Based on statistics of these three dimensions and drawing on a unique dataset of all Dutch firms registered with the Chambers of Commerce, we are able to refine well-known empirical findings for the geographical dimension. Counter-intuitive, however, are our empirical findings for the dimension of technology. Knowledge diffusion through medium-tech industry is much more important for a localized economy than knowledge creation in high-tech industry. Knowledge-intensive services tend to uncouple economic activities from the regional dimension.

Arthur [1,2] provided a model to explain the circumstances that lead to technological lock-in into a specific trajectory. We contribute substantially to this area of research by investigating the circumstances under which technological development may break-out of a trajectory. We argue that for this to happen, a third selection mechanism--beyond those of the market and of technology--needs to upset the lock-in. We model the interaction, or mutual shaping among three selection mechanisms, and thus this paper also allows for a better understanding of when a technology will lock-in into a trajectory, when a technology may break-out of a lock-in, and when competing technologies may co-exist in a balance. As a system is conceptualized to gain a (third) degree of freedom, the possibility of bifurcation is introduced into the model. The equations, in which interactions between competition and selection mechanisms can be modeled, allow one to specify conditions for lock-in, competitive balance, and break-out.