Votre recherche

Discusses the measurement of innovation and the use of the resulting indicators to shape policy, exploring whether innovation can be measured everywhere, not just in the business sector, in a rapidly changing world. Reviews systems, innovation, and innovation policy. Details current innovation policies. Describes scoreboards and their use for monitoring existing innovation policy. Focuses on the implementation of innovation policy. Presents the general definition of innovation applicable in all economic sectors and considers the importance of language in the innovation discourse. Provides the conceptual framework for the specification of the statistical measurement of innovation. Addresses non-sector-specific innovation in the informal economy, green economy, social innovation, and innovation resulting from the use of general-purpose technologies. Examines global challenges for innovation such as sustainability restrictions. Considers the future of innovation in the digital economy, informal economy, and social innovation. Gault is Professorial Fellow at UNU-MERIT, Professor Extraordinary at Tshwane University of Technology, and Visiting Professor at the University of Johannesburg. Index.

Society is at a crossroads. Interconnected systems, radical transparency, and rapidly increasing sophistication in skills, communications, and technologies provide a unique context for fostering social innovation at a planetary scale. We argue that unprecedented rates of systemic social change are possible for co-creating a future where humans and all life can thrive. Yet, this requires innovation in the conceptions, practice, teaching, and researching of social innovation itself to reimagine what it is and can be. As a multidisciplinary group of academics, practitioners, and educators, we integrate our perspectives on social innovation and humanistic management to suggest the notion of systemic social innovation. We introduce the concept of “transformative collaboration” as central to facilitating systemic social innovation and propose a multilevel model for accelerating systems change. We then develop an integrated framework for conceptualizing systemic social innovation. Four levels of social impact are identified, and these levels are bracketed with a call for transforming individual consciousness at the micro level and new collective mindsets at the macro level. Blooom is presented as a case study to illustrate transformative collaboration, demonstrate the role of mindset shift in practice, and introduce four key ingredients to systemic social innovation. Finally, a call to action is issued for social innovation practice, teaching, and research. Most importantly, we seek to inspire and accelerate systemic social innovation that enables the flourishing of every human being and all life on earth.

This chapter is about evidence and whether we can, or should, know our impact, the effect we have in the world. It addresses the difficulties as well as the possibilities of evidence for innovators and politicians, civil servants and head teachers, charities and doctors. I also touch on the question at the level of daily life, the moral question of whether we help those around us to be healthier, happier and more prosperous. Knowing our own impacts is, I argue, as much a moral prerogative as the traditional philosophical injunction of knowing ourselves.The enlightenment storyMany of us imbibed from an early age what can be called the enlightenment story. In this story new knowledge is steadily accumulated, mainly in universities and from academic journals. Theories are invented, tested, refuted and then improved. Scepticism helps to refine them and, as Wittgenstein wrote, the child first learns belief and only then learns doubt. You could say that at school we learn knowledge, and then at university we learn to question that knowledge.Belief is strengthened precisely because it has already been knocked down. And so, accumulating knowledge shows that this medicine, that economic policy or this teaching method works and many others don’t. The successful method then spreads, because when you design a better mousetrap the world beats a path to your door. It spreads because people are rational and want to do better and are persuaded by evidence. And so, the world progresses. Light replaces darkness. Effective solutions displace failed ones.It's easy to mock the enlightenment story. The sociologists of science have shown a much messier pattern of change – full of barriers, wilful resistance and peer pressure. But the old enlightenment story contains a good deal of truth and is preferable to the alternatives. Because of intense pressures to act on evidence, and habits of doubt among maintenance staff and engineers, aircraft do not drop out of the sky. Smoking made the slow progress from evidence of harm, through taxes and warnings to full-scale bans, and millions of lives were saved.Experimental methods have been used for many decades.

In the kingdom of ends everything has either a price or a dignity. What has a price can be replaced by something else as its equivalent; what on the other hand is raised above all price and therefore admits of no equivalent has a dignity.One of the fascinating features of the history of science is how often new ways of seeing preceded new insights. The achromatic-lens microscope in the early 19th century paved the way for germ theory, and X-ray crystallography in the early 20th century played a vital role in the later discovery of the structure of DNA. In the same way flows of data – for example, about how people move around a city, or how blood cells change – can prompt new insights.But how important is measurement to social change? Many people are attracted to metrics and indices of all kinds. But, as my colleague Mark Moore used to warn, ‘do you really think the leaders of the Civil Rights Movement were counting the placards or measuring the decibels of their cries for human rights?’ In social change, as in our own daily lives, measurement often feels inappropriate for the things that matter most.This chapter examines some of the history of social observation as a tool for public policy, social innovation and social change, and I suggest where it might lead in the future. Without some means of measurement, it can be hard to know if a social innovation is good. It may feel good to the beneficiaries – but still be less effective than an alternative. Or it may work well for one group but not another. And, even if it may not be appropriate to measure the passions of movements, once these ideas become part of the mainstream, and are transformed into the cool logic of laws, regulations and programmes, measurements do start to matter a lot, as the Civil Rights Movement discovered.A short history of measurementFor centuries, governments have sought to map and measure social phenomena in order to better exercise control over them. In the modern era these attempts can be traced back to figures like Sir William Petty in England and the cameralists in Prussia.

The aim of this research is to explore the dynamics and impact of open social innovation, within the context of fab labs and makerspaces. Using an exploratory methodology based on 12 semi-structured interviews of fab lab founders belonging to The Centres for Maker Innovation and Technology (CMIT) programme – a network of 170 fab labs located in Eastern Europe – this research explores the impact of an adopting an open approach in relation to the different stages of social innovation (prompts, proposals, prototypes, sustaining, scaling and diffusion, systemic change) as well as social impact. The main results of this study are that while the CMIT programme provided each fab lab with similar initial conditions (identical funding, objectives and rules), the open social innovation approached adopted enabled to give birth to a wide diversity of fab labs, each being very well adapted to the local environment, social needs and constraints and able to deliver social impact in just a matter of years; a result that would be hard to achieve with a centralised top-down approach. The study identified three types of CMITs – Education, Industry and Residential – which could be similar or different depending on the stage of social open innovation. Furthermore, this paper discusses the main difficulties social entrepreneurs encounter as a part of the open social innovation process, as well as means to overcome them. In this respect, this study adds to the literature on fab labs by providing more comprehensive view of the challenges faced by fab labs (and makerspaces) founders, as well as suggestions of strategies enabling to ensure their long-term sustainability.