An effective knowledge quality framework based on knowledge resources interdependencies

Abstract

Purpose – The purpose of this paper is to introduce a new knowledge quality assessment framework based on interdependencies between content and schema as knowledge resources to enhance the quality of the knowledge that is being generated, disseminated and stored in a collaborative environment. Design/methodology/approach – A knowledge elaboration approach is based on intervening factors of schematic clustering applied to a trial wiki bulletin board. Through this schematic intervention in the form of group creation within a wiki environment, a user-centric mechanism is created to substantiate, compose and narrate the generated contents in a self-organizing way. Findings – Through this approach, quality in content can be enhanced by means of a favourably manipulated collaboration schema adopted by the knowledge management system (KMS) users instead of applying knowledge mining tools. Research limitations/implications – With consideration to trust as a significant factor in this study, the verification and referral process may vary for KMS structures that are of larger scale or in low-trust collaborative environments. Originality/value – This study demonstrates transition to higher quality knowledge with less time spent on the original content refinement and composition by paying due consideration to the interdependencies between knowledge resource content and its schema. Validation is done via a clustered group structure in a specially designed wiki which had been used as a discussion bulletin board on directed topics over an extended period.

Knowledge quality and non‐financial performance—A Malaysian experience

“…Because of high competition in an international market, using knowledge management (KM) and implementing a knowledge management system (KMS) more is not enough to tackle such disordered and turbulent markets (Eugenie et al, 2016). Many businesses are relying on their respective KMS as a key source for strategy formulation and decisionmaking without being able to sustainably evaluate and improve the quality of the existing knowledge within their business context (Sabetzadeh & Tsui, 2015). Hence, all companies and organizations in industrial and service sectors should improve quality inside their organizational thinking and also business operations and activities.…”

Implementation of Decision Tree Algorithm to Classify Knowledge Quality in a Knowledge Intensive System

“…Knowledge quality is defined as created knowledge which is relevant to knowledge workers and is valuable in content [8,38]. Knowledge quality is a significant factor when it comes to the success of knowledge intensive systems [6][7][8][9][10][11][12]. Knowledge quality has its own attributes and are as follows; intrinsic knowledge quality, contextual knowledge quality, actionable knowledge quality and accessibility knowledge quality [8,38,46].…”

“…Without an effective knowledge-intensive system, knowledge could not be shared effectively [2][3][4][5]. Furthermore, knowledge quality itself is integral in the success of a knowledge-intensive system [6][7][8][9][10][11][12]. The usage of knowledge-intensive systems is affected by the quality of knowledge present in the system [13][14][15].…”

The Development Model of the Influence of Knowledge Quality Towards Organizational Performance Based on Entrepreneurial Learning

“…Thus, defining, explaining, and assessing knowledge quality is interesting for researchers. However literature studies show that the dominant research is the absence of consensus regarding the definition of quality for knowledge (Sabetzadeh & Tsui, 2015). Valaei & Rezaei, 2017 explained that the quality of knowledge is a new concept and there is little research in SMEs.…”