Journal of Statistics Applications & Probability
Abstract
Knowledge management (KM) involves strategies and processes for identifying, capturing, and leveraging knowledge to enhance competitiveness. Quality management (QM) has its roots in manufacturing and services to accomplish efficiency and customer satisfaction. This paper seeks to explore the relationship between knowledge management and quality management. The paper also aims to address the reality that for organizational maturity, knowledge management will have to be harnessed and this knowledge management will need to have requisite quality for it to be effective. The main purpose of this paper is to address the nature of knowledge quality, describe its elements and their attributes, and create a valid and reliable instrument to measure the relative importance of the elements and their attributes. A framework is proposed that uses a hierarchical approach to address the dependence relationships of knowledge quality with its elements of intrinsic, contextual and actionable knowledge quality. Each of these elements has their own attributes. Based on the relationships, business managers can judge the need to improve and determine which element to provide the most effective direction towards knowledge quality improvement in knowledge management systems.
Digital Object Identifier (DOI)
http://dx.doi.org/10.18576/jsap/070107
Recommended Citation
Chakrabarti, Deepankar; Arora, Monika; and Sharma, Prayas
(2018)
"Evaluating Knowledge Quality in Knowledge Management Systems,"
Journal of Statistics Applications & Probability: Vol. 7:
Iss.
1, Article 7.
DOI: http://dx.doi.org/10.18576/jsap/070107
Available at:
https://digitalcommons.aaru.edu.jo/jsap/vol7/iss1/7