AKM 2017 : Call for Book Chapters: Analytics and Knowledge Management (Taylor & Francis Group)
Call For Papers
Call for Book Chapters
Book Title: Analytics and Knowledge Management
Editors: Suliman Hawamdeh and Hsia-Ching Chang, University of North Texas
*To be published in the “Data Analytics Applications” book series (https://www.crcpress.com/Data-Analytics-Applications/book-series/CRCDATANAAPP) edited by Jay Liebowitz and published by Taylor & Francis Group, LLC.
Data is considered an organizational asset when properly managed, processed, and used to support the organizational decision-making process. The inability to manage organizational data can lead to a serious knowledge management problem. The intersection of different areas such as data curation, data analytics, knowledge discovery and knowledge management practices are essential to the organization the long survival. Knowledge Management (KM) is an interdisciplinary field deals with all aspects of knowledge processes and practices from knowledge creation to knowledge retention. It is about the ability see the big picture and takes a holistic approach to solving problems. This includes the ability to gather, process, and manipulate data in a way that enhances daily operations and aids the long-term strategic planning process.
Analytics is the examination, interpretation and discovery of meaningful pattern, trends and knowledge from data and textual information. Knowledge management on the other hand is concerned with the knowledge processes and practices from knowledge creation to the knowledge utilization. While analytics provides the foundation for knowledge discovery, knowledge management completes the cycle through informed decision-making and enhanced knowledge utilization and retention processes. This book examines the role of analytics in knowledge management including the integration of analytics theories, methods and technologies into knowledge management processes. Additionally, it has been recognized that the analytics skills gap exists and most organizations do not have adequate analytics competencies. In essence, analytics alone cannot achieve a sustainable future. This book brings together analytics and knowledge management from perspectives in information science, management information systems, and learning technology. This book aims to identify the role of analytics in knowledge management and how analytics can be seamlessly integrated in the knowledge management processes.
Topics of Interests: Chapter articles should be original and previously unpublished work. All aspects of research efforts, including empirical studies, quantitative studies, conceptual framework, experimental results, case studies, industrial developments, are welcome.
Potential topics include, but are not limited to the themes below:
* Data analytics in the context of big data and data science
* Knowledge management
* The nexus of data analytics and knowledge management
* Analytics in information architecture
* Analytics and decision making in the context of knowledge management
* Data analytics in knowledge management processes and practices
* Big data information and knowledge architecture
* Business analytics and knowledge utilization
* Predictive analytics for knowledge retention
* Data analytics and knowledge audit
We would like to invite chapter proposal submissions from researchers/scholars whose original ideas and high-quality work are relevant to the scope of the book. This book will mainly focus on the new perspectives on the role of analytics in knowledge management and/or how knowledge management can facilitate the success of data analytics efforts.
The book aims to not only provide state of the art research findings and emerging trends in the intersection between analytics and knowledge management, but also bring together analytics and knowledge management from perspectives in information science, management information systems, and learning technology. The targeted audience of the book consists of graduate students, knowledge management specialists, knowledge managers, business intelligence analysts, data scientists, (data) analytics managers, researchers, and practitioners.
Schedule & Important Dates:
* December 1st, 2016
One-page Chapter Abstract/Proposal and Intention to submit a chapter via email to Dr. Hsia-Ching Chang at Hsia-Ching.Chang@unt.edu. Authors may submit in Word or PDF format. The author(s) may also submit a short biography.
* March 15th, 2017
Full chapter submissions
* May 15th, 2017
Review comments sent to the authors
* August 15th, 2017
Final revision submissions
Submission Instructions: Authors of accepted chapter proposals could submit their full chapters based on the instructions as follows.
* Each manuscript should be written in English.
* Expected manuscript length is 30~60 pages (approximately 12,500 to 25,000 words).
* The formatting style must be followed using Word format as given by the publisher.
* Submit your chapter proposal and full chapter to Dr. Suliman Hawamdeh at Suliman.Hawamdeh@unt.edu and/or Dr. Hsia-Ching Chang at Hsia-Ching.Chang@unt.edu.