The effectiveness of Science and Technology Parks (STPs) as instruments of innovation policy has generated thriving debate among academics, practitioners and policy makers. However, research mostly does not consider STPs' heterogeneity. The present paper analyses the influence of different STP characteristics on their tenants' performance. Using data on 849 firms and 25 STPs from the 2009 Community Innovation Survey for Spain and a survey of STP managers respectively, we find that: (i) firms located in very new or longer established STPs show better innovative performance; (ii) the size of the STP and its management company positively affects the innovative performance of tenants while services provision has no effect on firms' achieving better results; and (iii) firms in less technologically developed regions benefit more from location in an STP.2

Although the notion of Science and Technology Parks (STPs) has become fairly widespread, however, the level of university involvement in these parks differs hugely. At the extremes, there are parks that are owned and managed by universities, and parks with no formal links of any kind with a university. We use data from the Community Innovation Survey (CIS) for Spain and a survey of STP park managers to analyse how the level of involvement of a university in the STP affects the innovation outputs of its tenants and their links with universities. We find that higher involvement of a university in the STP negatively affects tenant's innovation sales and positively affects the number of patent applications. We find no robust evidence of the involvement of a university in the propensity for park firms to cooperate with a university or to purchase external R&D services from the university.

a b s t r a c tIn this article we develop an analytical model of the selection process for R&D cooperative projects, to study the factors that motivate public project selection and corresponding funding, using two different financial instruments: subsidies and credits. For this purpose, we propose a three stage empirical strategy to analyse the differential individual effects of several factors on the decisions taken by the public agency. This analysis is based on project level data from cooperative R&D project calls under the Spanish PROFIT initiative, for the period 2000-2003. The main results show that the public agency uses the two financial instruments to address different objectives. First, some projects close to the market are well supported through credits, while basic research projects receive only selective support in the form of subsidies. Second, there is significant diversity in the selection and funding of technological areas. Third, regarding the explicit goal of fostering cooperation, the public agency selectively favours partnerships with universities and technology institutes through the award of subsidies. However, there seems to be less incentive for large consortia. Fourth, there are significant regional differences among financed projects and, also, our data show sharp yearly fluctuations.

The issue of intellectual capital and its measurement is investigated in this paper. We provide an overview of how a data envelopment analysis (DEA) approach was used to investigate some characteristics of performance for joint intersectoral research and development collaboration projects, with a specific emphasis of use of intellectual property (ie, patents) as one of the outcomes of these collaborations. Some knowledge-based factors are investigated in this paper to determine if there is a relationship between these factors and research partnership performance. Of particular focus in this paper, and focusing on the special issue topic, is whether knowledge management and knowledge goals play a role in whether these collaborations perform better or worse. The study is based on empirical data from a programme of technological policy existing in Spain, known as the Concerted Projects.

The objective of this work is to evaluate the impact of research and technology organizations (RTO) on firm competitiveness. To this end, we develop a framework that includes strategies to deal with the methodological problems highlighted in the literature. The main features of this framework are the definition and classification of different types of impacts, the estimation of (rough) quantitative measures of them and the development of a multivariate model to explain the different impacts including the traditional indicators of firm characteristics and their relationships. The empirical work is based on a database constructed from information from the responses to a questionnaire designed specifically to estimate the impact of RTOs on Spanish firms, and information from the Spanish Inno vation Survey. Our findings show that firms are able to recognize the influence of these relationships on different technical, economic, investment and intangible impacts and to roughly estimate their economic impact, and that several characteristics of these rela tionships affect the impact of RTOs.