Call for Chapters: Cases on Enhancing Business Sustainability Through Knowledge Management Systems

Editors

Meir Russ, University of Wisconsin-Green Bay, United States

Call for Chapters

Proposals Submission Deadline: September 30, 2022
Full Chapters Due: December 13, 2022

Introduction

This book is envisioned as a manuscript that presents case studies exploring the formulation and implementation of knowledge management systems in organizations at times when Artificial Intelligence (AI) is becoming a reality for pioneering organizations while they are facing complex multifaceted aspects of business sustainability with ambiguous and changing ethical norms and vague or not existing legislation. The first quarter of the 21st century was identified as the beginning of the continuous, ongoing, and accelerating wave of simultaneous ‘general purpose technologies’ revolutions causing accelerated shrinkage of half-life of knowledge. At such a pace of change, one would experience multiple paradigm shifts during their lifetime leaving no time in between to allow the individual, organizations and/or society to adjust; forcing society at large and the organizations to develop and adopt a different set of new tools, systems and procedures (Russ, 2021a).

One such tool is a new model of knowledge management for sustainable development (see Russ, 2021a, Figure 3) which incorporates the most recent developments of big data, machine learning in the context of cybersecurity, humanistic paradigms, steering toward a circular and ‘smart’ sustainable economy. This model proposed a three-layer model of knowledge management (KM) that incorporates a human layer, a machine layer and a unified new knowledge development and knowledge sharing layer. Finally, the model suggests combining decision making and learning into a unified, synergistic managerial activity as critical aspects for human and machine actors (Russ, 2021a; 2021b).

Specifically, this call is soliciting chapter proposals of teaching case studies of organizations formulating and implementing KMS where the AI algorithms and/or big data systems are infused with human centered knowledge while supporting economic, social and/or environmental sustainability issues. The call hopes to attract contributions from different countries, covering different industries, discussing different aspects of KMS during their complete life cycle, and covering a diverse set of technologies and processes. The focus of the cases should be on the decision making and learning opportunities at the individual, team, organizational and interorganizational levels while uncovering business, sustainability and ethical dilemmas facing the learning and decision-making actors.

For the purpose of this call for chapters, the broad and holistic definition of KMS as defined by ISO 30401:2018 is used. KMS is defined as the set of interrelated or interacting elements of organizations that establish, embed, and enable the knowledge management policies and objectives, as well as the processes to achieve those objectives (ISO, 2018). Those objectives must (or at least have the potential to) create value (Russ et al., 2010) to a set (or subset) of stakeholders.

References
ISO (International Organization for Standardization) (2018). ISO 30401:2018. Knowledge management systems-Requirements. https://www.iso.org/obp/ui/#iso:std:iso:30401:ed-1:v1:en
Russ, M. (2021a). Knowledge management for sustainable development in the era of continuously accelerating technological revolutions: A framework and models. Sustainability, 13(6), 3353. https://www.mdpi.com/2071-1050/13/6/3353
Russ, M. (2021b). The individual and the organizational model of quantum decision-making and learning: An introduction and the application of the quadruple loop learning. Merits, 1(1), 34-46. https://www.mdpi.com/2673-8104/1/1/5
Russ, M., Fineman, R., and Jones, J.K. (2010). “Conceptual Theory: What Do You Know?” in Russ, M. (Ed.) Knowledge Management Strategies for Business Development: 1-22. Hershey, PA: Business Science Reference.


Objective

This book will present teaching case studies exploring the formulating and implementing of knowledge management systems (KMS) in organizations, framed by the changes and the model mentioned above; and by deficiencies of teaching cases that I (and others) observed while teaching KM classes at the advanced undergraduate and graduate levels.

Target Audience

KM is taught as a standalone class and/or as a module in classes in business, decision making, information systems and computer sciences (among others) sometimes under a different title. Such teaching includes models, tools, and some theoretical aspects (depending on the discipline), but usually lacks updated, relevant and detailed teaching cases, which could enable a fruitful class discussion, covering technological, organizational and human aspects, including managerial, design, moral and ethical dilemmas.

Recommended Topics

Table of Contents-anticipated
Introduction
Strategic aspects of Knowledge Management for business sustainability
Strategy Formulation
Strategy Implementation

Human aspects of Knowledge Management for business sustainability
Human Capital
Talent Management

Technology/machine aspects of Knowledge Management for business sustainability
Artificial Intelligence/Machine Learning
Big Data

Learning aspects in Knowledge Management for business sustainability
Organizational Learning and Learning Organization (interorganizational and organizational)
Team Learnings
Individual Learnings

Decision Making (DM) aspects in Knowledge Management for business sustainability
Interorganizational and Organizational DM
Team DM
Individual DM

Knowledge aspects of Knowledge Management for business sustainability
New Knowledge Development
Knowledge Sharing

Ethical and Moral dilemmas cases

Country specific cases

Industry specific cases

Project Management cases


Submission Procedure

Researchers and practitioners are invited to submit on or before September 30, 2022, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by October 2 2022 about the status of their proposals and sent chapter guidelines.Full chapters are expected to be submitted by December 13, 2022, and all interested authors must consult the guidelines for manuscript submissions at https://www.igi-global.com/publish/contributor-resources/before-you-write/ prior to submission. All submitted chapters will be reviewed on a double-blind review basis. Contributors may also be requested to serve as reviewers for this project.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, Cases on Enhancing Business Sustainability Through Knowledge Management Systems. All manuscripts are accepted based on a double-blind peer review editorial process.

All proposals must be submitted through the eEditorial Discovery® online submission manager.



Publisher

This book is scheduled to be published by IGI Global (formerly Idea Group Inc.), an international academic publisher of the "Information Science Reference" (formerly Idea Group Reference), "Medical Information Science Reference," "Business Science Reference," and "Engineering Science Reference" imprints. IGI Global specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit https://www.igi-global.com. This publication is anticipated to be released in 2023.



Important Dates

September 30, 2022: Proposal Submission Deadline
October 2, 2022: Notification of Acceptance
December 13, 2022: Full Chapter Submission
February 14, 2023: Review Results Returned

Inquiries

Meir Russ
University of Wisconsin-Green Bay
russm@uwgb.edu


Classifications


Business and Management; Computer Science and Information Technology; Environmental, Agricultural, and Physical Sciences; Medical, Healthcare, and Life Sciences; Social Sciences and Humanities; Science and Engineering
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