Knowledge that Transforms

This paper describes the methodology and software tool used to build a database on the careers and productivity of academics, using public information available on the Internet, and provides a first analysis of the data collected for a sample of 360 US scientists funded by the National Institute of Health (NIH) and 291 UK scientists funded by the Biotechnology and Biological Sciences Research Council (BBSRC). The tool’s structured outputs can be used for either econometric research or data representation for policy analysis. The methodology and software tool is validated for a sample of US and UK biomedical scientists, but can be applied to any countries where scientists’ CVs are available in English. We provide an overview of the motivations for constructing the database, and the data crawling and data mining techniques used to transform webpage-based information and CV information into a relational database. We describe the database and the effectiveness of our algorithms and provide suggestions for further improvements. The software developed is released under free software GNU General Public License; the aim is for it to be available to the community of social scientists and economists interested in analyzing scientific production and scientific careers, who it is hoped will develop this tool further.

International new ventures (INVs) have been documented to exist all around the world, but the literature is silent on the frequency of such companies in different countries. We contend that the propensity of new ventures to internationalize by forming international partnerships is higher in small-domestic demand countries because they have a greater motivation given their limited local demand. After discussing the methodological challenges in testing this hypothesis, we do such a test by studying alliances in the health segment of the biotech industry in relatively small-domestic demand countries (Australia, Israel, and Taiwan) and by comparing the results with five large-domestic demand countries (UK, Germany, France, US, and Japan). We find that young firms in the countries with smaller domestic demand are at least 3 times more likely to enter into international partnerships than their counterparts in countries with larger domestic demand. We further demonstrate that this difference can primarily be explained by the difference in the size of domestic healthcare markets rather than other underlying opportunity structure related factors.

Longitudinal micro-data derived from transaction level information about wage and vendor payments made by federal grants on multiple U.S. campuses are being developed in a partnership involving researchers, university administrators, representatives of federal agencies, and others. This paper describes the UMETRICS data initiative that has been implemented under the auspices of the Committee on Institutional Cooperation. The resulting data set reflects an emerging conceptual framework for analyzing the process, products, and impact of research. It grows from and engages the work of a diverse and vibrant community. This paper situates the UMETRICS effort in the context of research evaluation and ongoing data infrastructure efforts in order to highlight its novel and valuable features. Refocusing data construction in this field around individuals, networks, and teams offers dramatic possibilities for data linkage, the evaluation of research investments, and the development of rigorous conceptual and empirical models. Two preliminary analyses of the scientific workforce and network approaches to characterizing scientific teams ground a discussion of future directions and a call for increased community engagement.

This paper introduces a unique database, the Corporate Invention Board (CIB). The CIB combines patent data from the PATSTAT database with financial data from the ORBIS database about the 2289 companies with the largest R&D investments. We illustrate the database by showing a comprehensive overview of national and sectoral patterns of R&D internationalization by multinational corporations in the period 1993–2005. The results show heterogeneity in sectoral and national patterns of internationalization. These patterns have remained relatively stable over the 1993–2005 period. China is among the least internationalized countries and European countries, especially the UK and the Netherlands, are among the most internationalized countries. The largest countries in terms of patent production, such as Germany and the US, have internationalization profiles that can be very well predicted based upon their sectoral composition. Other country profiles, however, diverge significantly from the prediction based on sectoral profile. Asian countries are on average less internationalized than would be expected, whereas the European countries and Canada are more internationalized. We find that while national level indicators explain a large part of the variance observed in the ability of countries to attract R&D from foreign multinationals, there are significant differences between sectors and this has large implications for the design of foreign R&D and innovation policies. The CIB opens up a wide array of opportunities to study the internationalization strategies of firms and countries.

In recent years there has been a growing interest in the role of networks and clusters in the global economy. Despite being a popular research topic in economics, sociology and urban studies, geographical clustering of human activity has often studied been by means of predetermined geographical units such as administrative divisions and metropolitan areas. This approach is intrinsically time invariant and it does not allow one to differentiate between different activities. Our goal in this paper is to present a new methodology for identifying clusters, that can be applied to different empirical settings. We use a graph approach based on k-shell decomposition to analyze world biomedical research clusters based on PubMed scientific publications. We identify research institutions and locate their activities in geographical clusters. Leading areas of scientific production and their top performing research institutions are consistently identified at different geographic scales.

Experimental methods of policy evaluation are well-established in social policy and development economics but are rare in industrial and innovation policy. In this paper, we consider the arguments for applying experimental methods to industrial policy measures, and propose an experimental policy evaluation approach (which we call RCT+). This approach combines the randomised assignment of firms to treatment and control groups with a longitudinal data collection strategy incorporating quantitative and qualitative data (so-called mixed methods). The RCT+ approach is designed to provide a causative rather than purely summative evaluation, i.e. to assess both ‘whether’ and ‘how’ programme outcomes are achieved. In this paper, we assess the RCT+ approach through an evaluation of Creative Credits – a UK business-to-business innovation voucher initiative intended to promote new innovation partnerships between SMEs and creative service providers. The results suggest the potential value of the RCT+ approach to industrial policy evaluation, and the benefits of mixed methods and longitudinal data collection.