Abstract

The aim of this paper is to identify some changes needed in Spain’s innovation policy to fill the gap between its innovation results and those of other European countries in lieu of sustainable leadership. To do this we apply the Delphi methodology to experts from academia, business, and government. To overcome the shortcomings of traditional descriptive methods, we develop an inferential analysis by following a non-parametric bootstrap method which enables us to identify important changes that should be implemented. Particularly interesting is the support found for improving the interconnections among the relevant agents of the innovation system (instead of focusing exclusively in the provision of knowledge and technological inputs through R and D activities), or the support found for “soft” policy instruments aimed at providing a homogeneous framework to assess the innovation capabilities of firms (e.g., for funding purposes). Attention to potential innovators among small and medium enterprises (SMEs) and traditional industries is particularly encouraged by experts.

Highlights

  • Innovation is a complex process where agents produce knowledge based on other pieces of disperse and fragmented knowledge

  • These changes urged policy-makers to embed innovation policies in a broader socio-economic context, to be more consistent with the management of a network. These new approaches allowed for the possibility of legitimizing innovation policy as a solution to market failures, and to tackle system imperfections [16]. Even within this complex environment, innovation is considered a necessary path for growth and increasing competitiveness [17] and, careful design of innovation policy has been a matter of concern for governments and managers that aim for sustainable development through technology changes

  • In this paper we focus on the analysis of problems and policy instruments of the Spanish innovation system

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Summary

Introduction

Innovation is a complex process where agents produce knowledge based on other pieces of disperse and fragmented knowledge. The theoretical approaches to assess innovation have reacted to such changes, shifting from a “linear” and autonomous perspective on the production of knowledge [4] to a comprehensive approach where the innovation process is the result of the co-evolution of society and technology, where agents do not innovate in isolation but within a “system”, and where interactions and feedback processes are key to explaining innovation paths [5,6,7,8] This holistic vision of the innovation process gave rise to new research agendas, such as “open innovation”, in which the discussion is centered at acknowledging the value of using external knowledge [9,10,11]. The efficiency of the innovation policy is tightly linked to its four main activities [20]:

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