Collaborative knowledge networks emergence for innovation: Factors of success analysis and comparison

TL;DR

This paper analyzes the success factors of collaborative knowledge networks in fostering innovation, emphasizing the role of information systems, social dynamics, and best practices to overcome barriers and enhance virtual collaboration.

Contribution

It identifies key success and failure factors for collaborative networks and proposes a framework for designing effective knowledge ecosystems based on best practices.

Findings

Balanced formalism and social fuzziness enable effective knowledge sharing.

Virtual collaboration maintains coherence beyond natural group sizes.

Success factors facilitate transition to expertise-driven innovation models.

Abstract

New product development needs new engineering approaches. Knowledge is a key resource that impacts traditional, organisational, economic and innovative models. Through NICT (New Information and Communication Technologies), globalisation encourages the emergence of networks that overcome traditional organisation boundaries. International enterprises, European-Community Networks of Excellence or Clusters (competitiveness poles) indicate the need to define a new way of thinking. This new way moves towards an agile, continuous innovative use of knowledge. Based on an epistemic study of knowledge management best practices, four examples show the barriers that can be encountered today. This paper aims defining the key elements that enhance collaborative networks. The analysis of best practices from collaborative environments enables the design of high standard information systems and initiate knowledge ecosystems. A balance between formalism required to share knowledge and fuzziness of social networks triggers new initiatives. This ensures the validity of information exchange through virtual collaboration. It helps to maintain group coherence despite exceeding the natural maximum number of collaborators. Finally the main success or failure factors are highlights and commented to ease the transition from economic-driven to expertise-driven models is then facilitated.