Electronic Resource

Enablers of Organisational Learning, Knowledge Management, and Innovation

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Penilaian

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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.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2108000041	EB0004707	658. Kes e	Central Library (OPAC)	Available

Detail Information

Series Title

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Call Number

658. Kes e

Publisher

Singapore : Springer Nature Singapore., 2021

Collation

xvii, 308p.:ill

Language

English

ISBN/ISSN

978-981-15-9793-0

Classification

658.

Content Type

Ebook

Media Type

-

Carrier Type

online resource

Edition

1

Subject(s)

Business and Management

Specific Detail Info

-

Statement of Responsibility

BRF

Other version/related

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