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The purpose of this paper is to identify the impact of public support through equity instruments on firm performance, as measured by growth in employment, turnover and innovative activities.

The paper draws on available academic literature and policy evaluation studies and using a mixed-method approach based on evaluation synthesis.

The key findings reflect positive, albeit quantifiably small, outcomes for this type of policy intervention for employment and turnover and no effect on innovation. There is some concentration of positive results, which is also dependent on the number and quality of the available target companies.

The evaluations used in this study vary considerably in their design, nature and the input and output variables used and, thus, limit a robust comparison of their outputs. Most of the evaluations examined in this paper did not control for multiple simultaneous treatment effects and/or subsequent funding rounds.

The evaluations are rarely designed to compare the treatment effects of alternative policy choices. Only seldom is an evaluation designed to assess the impact of the scheme in the context of the broader policy mix (with its framework conditions, etc.) which would provide more fine-grained policy implications.

The recent literature (Duruflé et al., 2017, Da Rin et al., 2011) highlights the dearth of studies exploring the role of government policies supporting venture and, more broadly, equity investments beyond comparisons of the efficiency of independent venture capital and government-backed venture capital. Most studies explore the impact in terms of exits, initial public offering and leverage effects whereas fewer studies look at output effects on companies such as turnover and employment growth. The paper aims to collect the existing evidence including less analysed policy evaluation studies and draw lessons for public policy.

This paper aims to analyse a set of converging trends underpinning a larger phenomenon called science 2.0 and to assess what are the most important implications for scientific method and research institutions.

It is based on a triangulation of exploratory methods which include a wide-ranging literature review, Web-based mapping and in-depth interviews with stakeholders.

The main implications of science 2.0 are enhanced efficiency, transparency and reliability; raise of data-driven science; microcontributions on a macroscale; multidimensional, immediate and multiform evaluation of science; disaggregation of the value chain of service providers for scientists; influx of multiple actors and the democratisation of science.

The paper rejects the notion of science 2.0 as the mere adoption of Web 2.0 technologies in science and puts forward an original integrated definition covering three trends that have not yet been analysed together: open science, citizens science and data-intensive science. It argues that these trends are mutually reinforcing and puts forward their main implications. It concludes with the identification of three enablers of science 2.0 – policy measures, individual practice of scientists and new infrastructure and services and sees the main bottleneck in lack of incentives on the individual level.