Progressive Post-Keynesian Economics by Liebowitz, Jay;

Hosszú leírás:

Elgar Research Agendas outline the future of research in a given area. Leading scholars are given the space to explore their subject in provocative ways, and map out the potential directions of travel. They are relevant but also visionary.

Leveraging the knowledge gained from knowledge management and from the growing fields of Analytics and Artificial Intelligence (AI), this Research Agenda highlights the research gaps, issues, applications, challenges and opportunities related to Knowledge Management (KM).

Exploring synergies between KM and emerging technologies, leading international scholars and practitioners examine KM from a multidisciplinary perspective, demonstrating the ways in which knowledge sharing worldwide can be enhanced in order to better society and improve organisational performance. Chapters investigate KM as it applies to business, library and information science, enterprise-wide strategies, innovation, privacy and data, measurement, Analytics, and AI, before summarising the lessons learned and best practices for future research.

A Research Agenda for Knowledge Management and Analytics will be a key resource for students, academics and practitioners working in the fields of KM and Analytics, helping the academics of the future to build on existing successes and identify ways to further develop the field.

Leveraging the knowledge gained from Knowledge Management and from the growing fields of Analytics and Artificial Intelligence (AI), this Research Agenda highlights the research gaps, issues, applications, challenges and opportunities related to Knowledge Management (KM). Exploring synergies between KM and emerging technologies, leading international scholars and practitioners examine KM from a multidisciplinary perspective, demonstrating the ways in which knowledge sharing worldwide can be enhanced in order to better society and improve organisational performance.

'Knowledge management and analytics originate from different viewpoints. One focuses on people and organizations knowing (or not knowing); the other on people and organizations doing (or hoping to do). As there is little point in knowing without doing, let alone doing without knowing, the potential for synergy is tremendous. This book identifies the variety of directions in which analytics might be integrated into knowledge management to give an even more powerful approach for coping with the challenges of uncertain times.'

Tartalomjegyzék:

Contents:

Foreword by Jim Lee xv
Preface xvii
Introduction to A Research Agenda for Knowledge
Management and Analytics xix
1 Knowledge management: library and information
science writ large 1
Qiping Zhang and Michael E. D. Koenig
2 Knowledge management placement in organizations 19
Ramin Assa
3 Knowledge management: enterprise-wide strategies 31
Joanna Paliszkiewicz
4 Knowledge management from a technology perspective 43
Vincent Ribiere, Cheng Gong and Kaiyu Yang
5 Knowledge management and artificial intelligence
analytics: a bibliometric study of research trends 67
Francisco J. Cantu-Ortiz
6 Knowledge management and measurement 89
Anthony J. Rhem
7 Knowledge management and innovation: issues,
gaps, applications and opportunities 107
Vida Skudienė
8 Serendipitous encounters to support innovations
via knowledge visualizations 121
Simon Li and Eric Tsui
9 Decisions, advice and explanation: an overview
and research agenda 149
Jan Vanthienen
10 KM, analytics, and AI: a winning combination to
survive the post-truth world 171
Kimiz Dalkir
11 Privacy and data: some research venues 191
Kenneth Carling and Johan Håkansson
12 Lessons learned and best practices in KM:
a personal perspective 205
Douglas Weidner
Index 225