Despite the key role of actor networks in progressing new sustainable technologies, there is a shortage of conceptual knowledge on how policy can help strengthen collaborative practices in such networks. The objective of this paper is to analyze the roles of such policies – so-called network management – throughout the entire technological development processes.
Science, technology and innovation (STI) policy is shaped by persistent framings that arise from historical context. Two established frames are identified as co-existing and dominant in contemporary innovation policy discussions. The first frame is identified as beginning with a Post-World War II institutionalisation of government support for science and R&D with the presumption that this would contribute to growth and address market failure in private provision of new knowledge.
This article conceptualizes the diffusion of user innovations from a service ecosystem perspective. With the focus on sustainable innovations, the service ecosystem is evaluated, along with other systemic innovation concepts, as a possible theoretical basis for explaining the first adoption and diffusion of user innovations.
Rather than merely supporting R&D and strengthening innovation systems, the focus of innovation policy is currently shifting towards addressing societal challenges by transforming socio-economic systems. A particular trend within the emerging era of transformative innovation policy is the pursuit of challenge-based innovation missions, such as achieving a 50 % circular economy by 2030. By formulating clear and ambitious societal goals, policy makers are aiming to steer the directionality and adoption of innovation.
So far, numerous studies have exhibited Silicon Valley and other thriving innovation ecosystems by distinguishing special characteristics in which their survival rely on sustaining activities that convert them to specific regions. These regions provide ready-made grounds for networking to be innovative. Meantime, it is struggling for innovations to be transformed into measurable economic results if players encounter a weak network of collaborative relationships in the ecosystem.
Research on next generation agricultural systems models shows that the most important current limitation is data, both for on-farm decision support and for research investment and policy decision making. One of the greatest data challenges is to obtain reliable data on farm management decision making, both for current conditions and under scenarios of changed bio-physical and socio-economic conditions.
To successfully realize the African transformation agenda, governments will have to capitalize on the potential of Africa’s youth. Growing up in an increasingly free and fair continent, the young people of Africa are dynamic, forward-looking and best positioned to find innovative solutions to local chal-lenges through the use of science and technology. To do this, conditions have to be suitable and young people need an environment in which barriers to self-actualization are broken.
Esta revisión de la literatura muestra la diversidad de puntos de vista en la caracterización del AIS (visión estructural, visión funcional, visión ba-sada en procesos, visión basada en capacidades). Estas diferentes visiones del AIS se basan en diferentes hipótesis y abarcan diferentes métodos de análisis del AIS. Los académicos consideran que estos puntos de vista son complementarios y útiles para una evaluación operativa del AIS. Debido a esta multiplicidad de puntos de vista analíticos, se ha desarrollado un gran número de métodos.
Este libro está dirigido a todos aquellos interesados en la innovación como fenómeno sistémico. El marco teórico general es el de los siste-mas de innovación, dada su capacidad de explicación de un fenómeno complejo, su centralidad en el diseño de políticas y –como se verá a lo largo del libro– su potencial para discutir los problemas del desarrollo. Este libro no pretende ser un manual, en el sentido que se presentarán elementos centrales y constitutivos del enfoque y relaciones de causas y consecuencias.
América Latina es una región muy heterogénea en términos de los niveles de desarrollo de los países y la madurez de sus SNI. Sin embargo, la región tiene una característica común que cruza desde la Patagonia hasta el Río Grande y desde el Pacífico hasta el Atlántico: es muy desigual socialmente hablando. Después de décadas de esfuerzos por avanzar más rá-pidamente en la senda del desarrollo, América Latina sigue siendo la región más desigual del mundo.