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| Author | : OECD |
| Publisher | : OECD Publishing |
| Total Pages | : 456 |
| Release | : 2015-10-06 |
| Genre | : |
| ISBN | : 9264229353 |
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.
| Author | : Michael Moesgaard Andersen |
| Publisher | : Routledge |
| Total Pages | : 117 |
| Release | : 2021-03-02 |
| Genre | : Business & Economics |
| ISBN | : 100032916X |
Today, innovation does not just occur in large and incumbent R&D organizations. Instead, it often emerges from the start-up community. In the new innovation economy, the key is to quickly find pieces of innovation, some of which may already be developed. Therefore, there is the need for more advanced means of searching and identifying innovation wherever it may occurs. We point to the importance of data-driven innovation based on digital platforms, as their footprints are growing rapidly and in sync with the shift from analogue to digital innovation workflows. This book offers companies insights on paths to business success and tools that will help them find the right route through the various options when it comes to the digital platforms where innovations may be discovered and from which value may be appropriated. The world hungers for growth and one of the most important vehicles for growth is innovation. In light of the new digital platforms from which data-driven innovation can be extracted, major parts of analogue workflows will be substituted with digital workflows. Data-driven innovation and digital innovation workflows are here to stay. Are you?
| Author | : José María Cavanillas |
| Publisher | : Springer |
| Total Pages | : 312 |
| Release | : 2016-04-04 |
| Genre | : Computers |
| ISBN | : 3319215698 |
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.
| Author | : Edward Curry |
| Publisher | : Springer Nature |
| Total Pages | : 399 |
| Release | : 2021-08-01 |
| Genre | : Computers |
| ISBN | : 3030681769 |
This open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society. It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data. The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems. The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation.
| Author | : Strydom, Moses |
| Publisher | : IGI Global |
| Total Pages | : 427 |
| Release | : 2019-09-27 |
| Genre | : Computers |
| ISBN | : 1522596895 |
Big data and artificial intelligence (AI) are at the forefront of technological advances that represent a potential transformational mega-trend—a new multipolar and innovative disruption. These technologies, and their associated management paradigm, are already rapidly impacting many industries and occupations, but in some sectors, the change is just beginning. Innovating ahead of emerging technologies is the new imperative for any organization that aspires to succeed in the next decade. Faced with the power of this AI movement, it is imperative to understand the dynamics and new codes required by the disruption and to adapt accordingly. AI and Big Data’s Potential for Disruptive Innovation provides emerging research exploring the theoretical and practical aspects of successfully implementing new and innovative technologies in a variety of sectors including business, transportation, and healthcare. Featuring coverage on a broad range of topics such as semantic mapping, ethics in AI, and big data governance, this book is ideally designed for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research on the production of new and innovative mechanization and its disruptions.
| Author | : Doug Hall |
| Publisher | : Clerisy Press |
| Total Pages | : 425 |
| Release | : 2018-11-13 |
| Genre | : Business & Economics |
| ISBN | : 1578605822 |
Transform the art of innovation into a reliable system! System Driven Innovation enables you and everyone on your team to use innovation to work smarter, faster, and more creatively. It transforms innovation from a random act to a reliable science. This new mindset ignites confidence in the future. It enables the creation of bigger and bolder ideas—and turns them into reality faster, smarter, and more successfully. With this new mindset, innovation by everyone, everywhere, every day becomes the norm. The rapidly changing world becomes a tremendous opportunity to achieve greatness. Innovation Engineering defines innovation in two words: Meaningfully Unique. When a product, service, or job candidate is Meaningfully Unique customers are willing to pay more money for it. This links to the two simple truths in today’s marketplace: If you’re Meaningfully Unique life is great! If you’re NOT Meaningfully Unique you’d better be cheap. Innovation Engineering is a new field of academic study and leadership science. It teaches how to apply the science of system thinking to strategy, innovation, and cooperation. Research finds that it helps to increase innovation speed (up to 6x) and decrease risk (by 30 to 80%). Innovation Engineering accelerates the creation and development of more profitable products and services. However, the bigger benefit may well lie in its ability to transform organizational cultures by enabling everyone to work smarter every day. What makes Innovation Engineering unique is that it’s grounded in data, backed by academic theory, and validated in real-world practice. Collectively, it’s the number one documented innovation system on earth. Over 35,000 people have been educated in Innovation Engineering classes, and more than $15 billion in innovations are in active development. In his book Driving Eureka!, best-selling business author Doug Hall presents the System Driven Innovation scientific method for enabling innovation by everyone, everywhere, every day. It’s the essential resource you need to enable yourself—and your team—to innovate, succeed, and do amazing things that matter, on a daily basis.
| Author | : Dale Neef |
| Publisher | : Pearson Education |
| Total Pages | : 320 |
| Release | : 2015 |
| Genre | : Business & Economics |
| ISBN | : 0133837963 |
Will "Big Data" supercharge the economy, tyrannize us, or both? Data Exhaust is the definitive primer for everyone who wants to understand all the implications of Big Data, digitally driven innovation, and the accelerating Internet Economy. Renowned digital expert Dale Neef clearly explains: What Big Data really is, and what's new and different about it How Big Data works, and what you need to know about Big Data technologies Where the data is coming from: how Big Data integrates sources ranging from social media to machine sensors, smartphones to financial transactions How companies use Big Data analytics to gain a more nuanced, accurate picture of their customers, their own performance, and the newest trends How governments and individual citizens can also benefit from Big Data How to overcome obstacles to success with Big Data - including poor data that can magnify human error A realistic assessment of Big Data threats to employment and personal privacy, now and in the future Neef places the Big Data phenomenon where it belongs: in the context of the broader global shift to the Internet economy, with all that implies. By doing so, he helps businesses plan Big Data strategy more effectively - and helps citizens and policymakers identify sensible policies for preventing its misuse. By conservative estimate, the global Big Data market will soar past $50 billion by 2018. But those direct expenses represent just the "tip of the iceberg" when it comes to Big Data's impact. Big Data is now of acute strategic interest for every organization that aims to succeed - and it is equally important to everyone else. Whoever you are, Data Exhaust tells you exactly what you need to know about Big Data - and what to do about it, too.
| Author | : Weidong Li |
| Publisher | : Springer Nature |
| Total Pages | : 218 |
| Release | : 2021-02-20 |
| Genre | : Technology & Engineering |
| ISBN | : 3030668495 |
This book reports innovative deep learning and big data analytics technologies for smart manufacturing applications. In this book, theoretical foundations, as well as the state-of-the-art and practical implementations for the relevant technologies, are covered. This book details the relevant applied research conducted by the authors in some important manufacturing applications, including intelligent prognosis on manufacturing processes, sustainable manufacturing and human-robot cooperation. Industrial case studies included in this book illustrate the design details of the algorithms and methodologies for the applications, in a bid to provide useful references to readers. Smart manufacturing aims to take advantage of advanced information and artificial intelligent technologies to enable flexibility in physical manufacturing processes to address increasingly dynamic markets. In recent years, the development of innovative deep learning and big data analytics algorithms is dramatic. Meanwhile, the algorithms and technologies have been widely applied to facilitate various manufacturing applications. It is essential to make a timely update on this subject considering its importance and rapid progress. This book offers a valuable resource for researchers in the smart manufacturing communities, as well as practicing engineers and decision makers in industry and all those interested in smart manufacturing and Industry 4.0.
| Author | : Steen Høyrup |
| Publisher | : Springer |
| Total Pages | : 450 |
| Release | : 2012-05-31 |
| Genre | : Business & Economics |
| ISBN | : 1137014768 |
Presents research in Employee-Driven Innovation, an emergent field of study that meets the demand for exploiting new innovative potentials in organizations. There is a growing interest in creating new knowledge in innovation, emphasizing human resources and social processes. The authors intend to take the global lead in research on these areas.
| Author | : Martin Schymanietz |
| Publisher | : Springer Nature |
| Total Pages | : 225 |
| Release | : 2020-09-30 |
| Genre | : Business & Economics |
| ISBN | : 3658316918 |
Martin Schymanietz explores dynamic capabilities that help organizations to cope with the challenges and chances of the utilization of data for service provision. Data-driven service innovation provides a fruitful pathway for organizations to extend their current offerings, deepen customer relationships and increase revenues. He examines the nature of data-driven service innovation, accompanied challenges and identifies relevant actors and their roles on an individual level. This approach helps organizations to develop dynamic capabilities based on individual actors that in sum shape the whole organization.
