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This report improves the evidence base on the role of Data Driven Innovation for promoting growth and well-being, and provide policy guidance on how to maximise the benefits of DDI and mitigate the associated economic and societal risks.
4. 1. 1 ImportanceofComputerSimulation The importance of experimenting for quality improvement and innovation of pr- ucts and processes is now very well known: “experimenting” means to implement signi?cant and intentional changes with the aim of obtaining useful information. In particular, the majority of industrial experiments have two goals: • To quantify the dependence of one or more observable response variables on a group of input factors in the design or the manufacturing of a product, in order to forecast the behavior of the system in a reliable way. • To identify the level settings for the inputs (design parameters) that are capable of optimizing the response. The set of rules that govern experiments for technological improvement in a ph- ical set-up are now comprehensively labeled “DoE. ” In recent years, the use of - perimentation in engineering design has received renewed momentum through the utilization of computer experiments (see Sacks et al. 1989, Santner et al. 2003), which has been steadily growing in the last two decades. These experimentsare run on a computer code implementing a simulation model of a physical system of int- est. This enables us to explore the complex relationships between input and output variables. Themain advantageofthis is that thesystem becomesmore“observable,” since computer runs are generally easier and cheaper than measurements taken in a physical set-up, and the exploration can be carried out more thoroughly. This is particularly attractive in industrial design applications where the goal is system - timization. 4. 1.
'A great book to understand and foster innovation at all levels: a truly innovative piece of work.' Enrico Giovannini, Minister of Labour and Social Policies, Italy 'This book brings together original contributions from world leading experts on innovation indicators and is unique in several respects. First, the focus is upon innovation in terms of commercialized products and processes and not on secondary indicators of research or patenting. Second, it combines academic perspectives with user perspectives from industry and international organizations. Third, it strikes a good balance between old and new indicators, opening up new dimensions of innovation for measuring. It is a book worth reading for scholars studying innovation, for policy makers and, not least, for innovation managers in the private sector.' Bengt-Åke Lundvall, Aalborg University, Denmark and Sciences-Po, Paris, France This Handbook comprehensively examines indicators and statistical measurement related to innovation (as defined in the OECD/Eurostat Oslo Manual). It deals with the development and the use of innovation indicators to support decision-making and is written by authors who are practitioners, who know what works and what does not, in order to improve the development of indicators to satisfy future policy needs. This unique volume presents: the historical and geographical context for innovation indicators and measurement practical examples of how measurement is actually undertaken new areas of innovation indicators and measurement, including consumer innovation, public sector innovation and social innovation. This informative Handbook will appeal to policy makers in government departments, statistical offices and research institutes and international organizations such as the EU, OECD and the UN, as well as university departments of economics, sociology, law, science and technology, and public policy.
The National Center for Science and Engineering Statistics (NCSES), at the U.S. National Foundation, is 1 of 14 major statistical agencies in the federal government, of which at least 5 collect relevant information on science, technology, and innovation activities in the United States and abroad. The America COMPETES Reauthorization Act of 2010 expanded and codified NCSES's role as a U.S. federal statistical agency. Important aspects of the agency's mandate include collection, acquisition, analysis, and reporting and dissemination of data on research and development trends, on U.S. competitiveness in science, technology, and research and development, and on the condition and progress of U.S. science, technology, engineering, and mathematics (STEM) education. Improving Measures of Science, Technology and Innovation: Interim Report examines the status of the NCSES's science, technology, and innovation (STI) indicators. This report assesses and provides recommendations regarding the need for revised, refocused, and newly developed indicators designed to better reflect fundamental and rapid changes that are reshaping global science, technology and innovation systems. The book also determines the international scope of STI indicators and the need for developing new indicators that measure developments in innovative activities in the United States and abroad, and Offers foresight on the types of data, metrics and indicators that will be particularly influential in evidentiary policy decision-making for years to come. In carrying out its charge, the authoring panel undertook a broad and comprehensive review of STI indicators from different countries, including Japan, China, India and several countries in Europe, Latin America and Africa. Improving Measures of Science, Technology, and Innovation makes recommendations for near-term action by NCSES along two dimensions: (1) development of new policy-relevant indicators that are based on NCSES survey data or on data collections at other statistical agencies; and (2) exploration of new data extraction and management tools for generating statistics, using automated methods of harvesting unstructured or scientometric data and data derived from administrative records.
Competitive Innovation and Improvement: Statistical Design and Control explains how to combine two widely known statistical methods‘statistical design and statistical control in a manner that can solve any business, government, or research problem quickly with sustained results. Because the problem-solving strategy employed is pure scientific metho
What is innovation and how should it be measured? Understanding the scale of innovation activities, the characteristics of innovative firms and the internal and systemic factors that can influence innovation is a prerequisite for the pursuit and analysis of policies aimed at fostering innovation.
Because of the role of innovation as a driver of economic productivity and growth and as a mechanism for improving people's well-being in other ways, understanding the nature,determinants, and impacts of innovation has become increasingly important to policy makers. To be effective, investment in innovation requires this understanding, which, in turn, requires measurement of the underlying inputs and subsequent outcomes of innovation processes. In May 2016, at the request of the National Center for Science and Engineering Statistics of the National Science Foundation, the Committee on National Statistics of the National Academies of Sciences, Engineering, and Medicine convened a workshop - bringing together academic researchers, private and public sector experts, and representatives from public policy agencies - to develop strategies for broadening and modernizing innovation information systems.This publication summarizes the presentation and discussion of the event.
Ce rapport, étude statistique des divers aspects de l'innovation technologique dans l'industrie canadienne, renferme: (1) une analyse du modèle des coûts d'innovation; (2) des informations sur les sources d'idées pour les innovations; et (3) des tableaux statistiques décrivant les traits dominants des projets reçus. Cette étude expérimentale fut menée en 1971 et 1973.
This book is the foremost international source of guidelines for the collection and use of data on innovation activities in industry.
In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment.