Enablers of Organisational Learning, Knowledge Management, and Innovation - Preethi Kesavan

Enablers of Organisational Learning, Knowledge Management, and Innovation (eBook)

Principles, Process, and Practice of Qualitative Data

(Autor)

eBook Download: PDF
2020 | 1st ed. 2021
XVII, 308 Seiten
Springer Singapore (Verlag)
978-981-15-9793-0 (ISBN)
Systemvoraussetzungen
139,09 inkl. MwSt
  • Download sofort lieferbar
  • Zahlungsarten anzeigen
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. 


Preethi Kesavan has extensive teaching and learning experience, educational leadership, and executive oversight of strengthening a high-quality student experience, enriching student global mobility, and enhancing academic quality and professional staff effectiveness. She has extensive experience in the Singapore Private Education systems and local public universities, online/mobile/blended learning and professional learning initiatives, quality assurance of curriculum, assessment, and people development and organizational policy development. She is a contemporary architect of flexi-learning, blended learning, e-learning, and education management. She has also designed and implemented IT solutions for the hospitality industry and private schools. She enjoys teaching various programming languages, database and enterprise solutions, and a strong interest in teaching and research activities in spreadsheet modelling and analytics.
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. 
Erscheint lt. Verlag 20.11.2020
Zusatzinfo XVII, 308 p. 8 illus., 1 illus. in color.
Sprache englisch
Themenwelt Mathematik / Informatik Informatik Datenbanken
Informatik Office Programme Outlook
Mathematik / Informatik Mathematik Finanz- / Wirtschaftsmathematik
Wirtschaft Betriebswirtschaft / Management Unternehmensführung / Management
Wirtschaft Betriebswirtschaft / Management Wirtschaftsinformatik
Schlagworte Knowledge Management and Innovation in Dispersed Teams • Knowledge Management and Organizational Learning • Text Analytics for Fact-Based Decision Making • Text Analytics for Knowledge Management • Text Mining and Sentiment Analysis • Text Mining and Text Analytics
ISBN-10 981-15-9793-6 / 9811597936
ISBN-13 978-981-15-9793-0 / 9789811597930
Haben Sie eine Frage zum Produkt?
PDFPDF (Wasserzeichen)

DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasser­zeichen und ist damit für Sie persona­lisiert. Bei einer missbräuch­lichen Weiter­gabe des eBooks an Dritte ist eine Rück­ver­folgung an die Quelle möglich.

Dateiformat: PDF (Portable Document Format)
Mit einem festen Seiten­layout eignet sich die PDF besonders für Fach­bücher mit Spalten, Tabellen und Abbild­ungen. Eine PDF kann auf fast allen Geräten ange­zeigt werden, ist aber für kleine Displays (Smart­phone, eReader) nur einge­schränkt geeignet.

Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.

Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.

Mehr entdecken
aus dem Bereich