Big Data Approach To Firm Level Innovation In Manufacturing
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Author | : Seyed Mehrshad Parvin Hosseini |
Publisher | : Springer Nature |
Total Pages | : 78 |
Release | : 2020-08-03 |
Genre | : Business & Economics |
ISBN | : 9811563004 |
This book discusses utilizing Big Data and Machine Learning approaches in investigating five aspects of firm level innovation in manufacturing; (1) factors that determine the decision to innovate (2) the extent of innovation (3) characteristics of an innovating firm (4) types of innovation undertaken and (5) the factors that drive and enable different types of innovation. A conceptual model and a cost-benefit framework were developed to explain a firm’s decision to innovate. To empirically demonstrate these aspects, Big data and machine learning approaches were introduced in the form of a case study. The result of Big data analysis as an inferior method to analyse innovation data was also compared with the results of conventional statistical methods. The implications of the findings of the study for increasing the pace of innovation are also discussed.
Author | : Matthew N. O. Sadiku |
Publisher | : Springer Nature |
Total Pages | : 297 |
Release | : 2023-03-15 |
Genre | : Technology & Engineering |
ISBN | : 3031231562 |
The manufacturing industry is a cornerstone of national economy and people’s livelihood. It is the way of transforming resources into products or goods which are required to cater to the needs of the society. Traditional manufacturing companies currently face several challenges such as rapid technological changes, inventory problem, shortened innovation, short product life cycles, volatile demand, low prices, highly customized products, and ability to compete in the global markets. Modern manufacturing is highly competitive due to globalization and fast changes in the global market. This book reviews emerging technologies in manufacturing. These technologies include artificial intelligence, smart manufacturing, lean manufacturing, robotics, automation, 3D printing, nanotechnology, industrial Internet of things, and augmented reality. The use of these technologies will have a profound impact on the manufacturing industry. The book consists of 19 chapters. Each chapter addresses a single emerging technology in depth and describes how manufacturing organizations are adopting the technology. The book fills an important niche for manufacturing. It is a comprehensive, jargon-free introductory text on the issues, ideas, theories, and problems on emerging technologies in manufacturing. It is a must-read book for beginners or anyone who wants to be updated about emerging technologies.
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 | : |
Publisher | : |
Total Pages | : 156 |
Release | : 2011 |
Genre | : Competition, International |
ISBN | : |
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 | : Chris Rowley |
Publisher | : Routledge |
Total Pages | : 177 |
Release | : 2021-11-29 |
Genre | : Business & Economics |
ISBN | : 1000505855 |
In many countries, business practitioners, policy makers, pundits and laypeople want to know how strong China really is in business. In the preceding century, the overall tone of business comments on China was filled with fanfare and ovation. However, despite economic performance and seemingly inexorable growth, some global data in areas such as labour productivity and digital competitiveness, show a different and more nuanced picture. This collection provides a multi-level reality check on the Chinese economy, firm performance and managerial ties. Given that China must transform its economy and business that can pull global talent together to produce high-end technologies for radically innovative products and services, this book proposes two questions. First, can China restructure its economy from a low-cost growth model to a high value-added innovative model without incurring major structural inertia? Second, can Chinese firms outperform competitors in global high value markets without relying on state initiatives, central funding mechanisms and public R&D institutions? This book was originally published as a special issue of the journal, Asia Pacific Business Review.
Author | : Marco Cucculelli |
Publisher | : Edward Elgar Publishing |
Total Pages | : 163 |
Release | : 2024-05-02 |
Genre | : Business & Economics |
ISBN | : 1035327465 |
Unpacking Innovation is a detailed and empirically grounded account of business model diversity and innovation in the context of increasing competition and digitalization. Focusing on incumbent firms, the book presents a novel perspective on how business model reconfiguration can help companies to compete effectively.
Author | : Patricia Ordóñez de Pablos |
Publisher | : MDPI |
Total Pages | : 416 |
Release | : 2019-12-31 |
Genre | : Social Science |
ISBN | : 3039280082 |
The evolution of knowledge management theory and the special emphasis on human and social capital sets new challenges for knowledge-driven and technology-enabled innovation. Emerging technologies including big data and analytics have significant implications for sustainability, policy making, and competitiveness. This edited volume promotes scientific research into the potential contributions knowledge management can make to the new era of innovation and social inclusive economic growth. We are grateful to all the contributors of this edition for their intellectual work. The organization of the relevant debate is aligned around three pillars: SECTION A. DATA, KNOWLEDGE, HUMAN AND SOCIAL CAPITAL FOR INNOVATION We elaborate on the new era of knowledge types and the emerging forms of social capital and their impact on technology-driven innovation. Topics include: · Social Networks · Smart Education · Social Capital · Corporate Innovation · Disruptive Innovation · Knowledge integration · Enhanced Decision-Making. SECTION B. KNOWLEDGE MANAGEMENT & BIG DATA ENABLED INNOVATION In this section, knowledge management and big data applications and systems are presented. Selective topic include: · Crowdsourcing Analysis · Natural Language Processing · Data Governance · Knowledge Extraction · Ontology Design Semantic Modeling SECTION C. SUSTAINABLE DEVELOPMENT In the section, the debate on the impact of knowledge management and big data research to sustainability is promoted with integrative discussion of complementary social and technological factors including: · Big Social Networks on Sustainable Economic Development · Business Intelligence
Author | : Zeki Simsek |
Publisher | : Edward Elgar Publishing |
Total Pages | : 599 |
Release | : 2024-07-05 |
Genre | : Business & Economics |
ISBN | : 180220881X |
This pioneering Handbook surveys the research landscape of strategic leadership in what is referred to as the ‘Fourth Industrial Revolution’: a fusion of technologies and systems which blurs the boundaries between the digital, physical and biological spheres.
Author | : Luciana Lazzeretti |
Publisher | : Taylor & Francis |
Total Pages | : 207 |
Release | : 2024-10-04 |
Genre | : Business & Economics |
ISBN | : 1040144306 |
This volume offers a wide-ranging discussion on the interrelations among AI, algorithms, big data, and Industry 4.0 to understand the importance of these new paradigms for the development of firms, districts, clusters, cities, regions, and innovation. Drawing on theoretical, empirical, and qualitative studies and using local perspectives, the chapters in this book explore theoretical aspects of AI and its evolution in social sciences, focusing on industry 4.0, smart cities, big data, and other related topics. They examine the role of industrial robots in employment, productivity, and knowledge absorption in industrial districts. They also discuss innovation in the context of local production systems, AI ecosystems, and the growth and potential of the Metaverse. Taken together, the book offers insights to help understand the new dynamics generated by the advent of these technologies and how they may affect regions, cities, clusters, industries, and organizations, and identifies avenues for future research in the development of new trajectories for clusters and firms. This book will be a key resource for scholars and advanced students in the fields of economics, geography, architecture, planning, and management as well as for interdisciplinary researchers who want to learn more about the development of new technologies, the relevance of AI, Big Data and I4.0 for firms and in relation to their adoption in clusters. This book was originally published as a special issue of European Planning Studies.