Negation and entropy: Effectual knowledge management equipment for learning organizations. (1st November 2020)

• Record Type: Journal Article
• Authors: Anjaria, Kushal
• Is Part Of: Expert systems with applications. Volume 157(2020)
• Publication Date: 2020-11-01
• Subjects: Entropy -- Negation -- Learning organization -- Knowledge management -- Decision making; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2020.113497
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: Equipment is developed by utilizing negation and entropy concepts. The equipment allows the learning organization to refine existing knowledge. The equipment helps the learning organization in the decision-making process. The equipment is validated and tested on two well-known organizational cases. Abstract: The present paper aims to put forward negation and entropy as novel perspectives for knowledge management in learning organizations. The present work considers the surrounding factors of information to enumerate the effectiveness of information in the knowledge management field. Moreover, by utilizing the effectiveness of surrounding factors, a framework inspired by Dempster-Shafer theory has been presented to generate negation. Finally, the present paper defines and calculates entropy for information. We have applied negation and entropy concepts to two well-known cases of organizational systems and management domains to study their impact on the knowledge management domain. The cases have supported our decisions taken after the calculation of proposed negation and entropy concepts. The proposed method has a quality interpretation of the information operators and has the merit of simplifying knowledge management and decision making problems in the context of a learning organization. The present study combines multiple aspects of knowledge management, organizational systems, decision making, and organizational learning.