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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.
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.
Competing in a global innovation eConomy: the Current State of r&D in CanaDa Expert Panel on the State of Science and Technology and Industrial Research and Development in Canada Science Advice in the Public Interest COMPETING IN A GLOBAL INNOVATION ECONOMY: THE CURRENT STATE OF R&D IN CANADA Expert Panel on the State of Science and Technology and Industrial Research and Development in Canada ii C [...] Any opinions, findings, or conclusions expressed in this publication are those of the authors, the Expert Panel on the State of Science and Technology and Industrial Research and Development in Canada, and do not necessarily represent the views of their organizations of affiliation or employment, or the sponsoring organization, Innovation, Science and Economic Development Canada. [...] I'd also like to thank the CCA's Board of Directors, its Scientific Advisory Committee, and its three x Competing in a Global Innovation Economy: The Current State of R&D in Canada Member Academies - the Royal Society of Canada, the Canadian Academy of Engineering, and the Canadian Academy of Health Sciences - who continue to provide the wisdom, advice, and expert knowledge that helps keep the CCA [...] This includes all three members of the Tri-Agency (the Natural Sciences and Engineering Research Council, the Social Sciences and Humanities Research Council, and the Canadian Institutes for Health Research), the National Research Council of Canada, the Canada Foundation for Innovation, and the Federation of the Humanities and Social Sciences. [...] The current Expert Panel (the Panel) was tasked with considering the combined charges from the 2012 and 2013 assessments, consisting of the following questions: What is the current state of science and technology and industrial research and development in Canada?
Publicly available statistics from government agencies that are credible, relevant, accurate, and timely are essential for policy makers, individuals, households, businesses, academic institutions, and other organizations to make informed decisions. Even more, the effective operation of a democratic system of government depends on the unhindered flow of statistical information to its citizens. In the United States, federal statistical agencies in cabinet departments and independent agencies are the governmental units whose principal function is to compile, analyze, and disseminate information for such statistical purposes as describing population characteristics and trends, planning and monitoring programs, and conducting research and evaluation. The work of these agencies is coordinated by the U.S. Office of Management and Budget. Statistical agencies may acquire information not only from surveys or censuses of people and organizations, but also from such sources as government administrative records, private-sector datasets, and Internet sources that are judged of suitable quality and relevance for statistical use. They may conduct analyses, but they do not advocate policies or take partisan positions. Statistical purposes for which they provide information relate to descriptions of groups and exclude any interest in or identification of an individual person, institution, or economic unit. Four principles are fundamental for a federal statistical agency: relevance to policy issues, credibility among data users, trust among data providers, and independence from political and other undue external influence. Principles and Practices for a Federal Statistical Agency: Sixth Edition presents and comments on these principles as they've been impacted by changes in laws, regulations, and other aspects of the environment of federal statistical agencies over the past 4 years.
Recently, researchers have focused on challenging problems facing the development of data warehousing, knowledge discovery, and data mining applications.
In the last decade, the use of data sciences in the digital marketing environment has increased. Digital marketing has transformed how companies communicate with their customers around the world. The increase in the use of social networks and how users communicate with companies on the internet has given rise to new business models based on the bidirectionality of communication between companies and internet users. Digital marketing, new business models, data-driven approaches, online advertising campaigns, and other digital strategies have gathered user opinions and comments through this new online channel. In this way, companies are beginning to see the digital ecosystem as not only the present but also the future. However, despite these advances, relevant evidence on the measures to improve the management of data sciences in digital marketing remains scarce. Advanced Digital Marketing Strategies in a Data-Driven Era contains high-quality research that presents a holistic overview of the main applications of data sciences to digital marketing and generates insights related to the creation of innovative data mining and knowledge discovery techniques applied to traditional and digital marketing strategies. The book analyzes how companies are adopting these new data-driven methods and how these strategies influence digital marketing. Discussing topics such as digital strategies, social media marketing, big data, marketing analytics, and data sciences, this book is essential for marketers, digital marketers, advertisers, brand managers, managers, executives, social media analysts, IT specialists, data scientists, students, researchers, and academicians in the field.
This book presents unique insights and advice on defining and managing the innovation transformation journey. Using novel ideas, examples and best practices, it empowers management executives at all levels to drive cultural, technological and organizational changes toward innovation. Covering modern innovation techniques, tools, programs and strategies, it focuses on the role of the latest technologies (e.g., artificial intelligence to discover, handle and manage ideas), methodologies (including Agile Engineering and Rapid Prototyping) and combinations of these (like hackathons or gamification). At the same time, it highlights the importance of culture and provides suggestions on how to build it. In the era of AI and the unprecedented pace of technology evolution, companies need to become truly innovative in order to survive. The transformation toward an innovation-led company is difficult – it requires a strong leadership and culture, advanced technologies and well-designed programs. The book is based on the author’s long-term experience and novel ideas, and reflects two decades of startup, consulting and corporate leadership experience. It is intended for business, technology, and innovation leaders.
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.
Currently, there is no official method for how to measure innovation in business. This is where Innovation Accounting comes in. This book helps businesses to develop their level of capability and performance within innovation and accounting. This guide provides examples of tools, templates, and frameworks that businesses can utilize to improve their business culture, inspire innovation, and find a way to measure innovation. In a world where numbers, statistics, and analytics are increasingly becoming the most important aspect of everyday business, this book can help to find meaning in innovative practices and measure them. This will allow you to demonstrate to stakeholders how capital is used, and the impact it has on the business. So whether you're managing a lean startup aiming to meet a particularly difficult to meet KPI, or a corporation aiming to replicate the level of success you achieved in your most recent financial quarter, this book will contain something for everyone.