Knowledge Management In The Innovation Process
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Knowledge Management in the Innovation Process
Author: John de la Mothe
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
It is now widely recognized that many of the central unresolved problems in economic policy, management and research turn on questions of knowledge. Increasingly, complex firms and agencies must ask, and answer, such difficult questions as: What is knowledge? Where is it? Who has it? Does the organization lose or gain competitive advantage or effectiveness by sharing knowledge? Where can we find the knowledge we need? How can we measure knowledge? In a knowledge-based economy, these queries are integral to the pursuits of every policy maker, analyst and strategist. Knowledge Management in The Innovation Process - a joint project between Statistics Canada and Program of Research on Innovation Management and Economy (PRIME) at the University of Ottawa - brings together economic, social, measurement and policy views on these critical issues. This project fits into an ongoing research program at Statistics Canada to develop meaningful indicators for science, technology and innovation in a technology-intensive economy. It also fits into the ongoing program at PRIME to better understand technology policy and innovation strategy. This book tells the story of the dynamic interplay between knowledge and innovation with an eye to developing tools and frameworks for managing knowledge for social and economic benefit.
Enablers of Organisational Learning, Knowledge Management, and Innovation
This book establishes constructivist, interpretivist, and linguistic approaches based on conventions about the nature of qualitative and text data, the author’s influence on text interpretation, and the validity checks used to justify text interpretations. Vast quantities of text and qualitative data in organizations often go unexplored. Text analytics outlined in this book allow readers to understand the process of converting unstructured text data into meaningful data for analysis in order to measure employee opinions, feedback, and reviews through sentiment analysis to support fact-based decision making. The methods involve using NVivo and RapidMiner software to perform lexical analysis, categorization, clustering, pattern recognition, tagging, annotation, memo creation, information extraction, association analysis, and visualization. The methodological approach in the book uses innovation theory as a sensitizing concept to lay the foundation for the analysis of research data, suggesting approaches for empirical exploration of organizational learning, knowledge management, and innovation practices amongst geographically dispersed individuals and team members. Based on data obtained from a private educational organization that has offices dispersed across Asia through focus group discussions and interviews on these topics, the author highlights the need for integrating organizational learning, knowledge management, and innovation to improve organizational performance, exploring perspectives on collective relationships and networks, organizational characteristics and structures, and tacit and overt values which influence such innovation initiatives. In the process, the author puts forward a new theory which is built on three themes: relationship and networks, knowledge sharing mechanisms, and the role of social cognitive schema that facilitate emergent learning, knowledge management, and innovation.
Knowledge Management and Innovation
Author: Pierre Barbaroux
language: en
Publisher: John Wiley & Sons
Release Date: 2016-07-14
This book explores the relationships between knowledge management (KM) processes and innovation management. The geographical extension of markets and intensification of competition have led firms to experiment with novel approaches to innovation. New organizational forms emerged in which firms collaborate with various stakeholders to create, absorb, integrate and protect knowledge. This book explores how knowledge management processes evolve with firms' implementation of interactive, collaborative and open innovation models and it identifies the various knowledge types and processes involved throughout the different phases of the innovation process. The authors provide operational typologies for understanding innovative firms' capabilities and knowledge management practices and also discuss the main properties of four models of interactive innovation, namely open innovation, user-centric innovation, community-based innovation and crowdsourcing.