An effective knowledge quality framework based on knowledge resources interdependencies
| DOI | https://doi.org/10.1108/VINE-07-2014-0048 |
| Published date | 10 August 2015 |
| Date | 10 August 2015 |
| Pages | 360-375 |
| Author | Farzad Sabetzadeh,Eric Tsui |
| Subject Matter | Information & knowledge management,Knowledge management,Knowledge management systems |
An effective knowledge quality
framework based on knowledge
resources interdependencies
Farzad Sabetzadeh and Eric Tsui
Department of Industrial and Systems Engineering,
The Hong Kong Polytechnic University, Hong Kong, Hong Kong
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 signicant factor in this
study, the verication 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 renement 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.
Keywords Wiki, Knowledge management, Knowledge quality, Knowledge resource
Paper type Research paper
Introduction
Although a plethora of books and journal papers developing theoretical frameworks to
measure and improve the quality of data and information has contributed signicantly
to the development of various topics like data mining and information retrieval in recent
years, there are limitations and drawbacks on how to extend these measurements for the
assessment of quality of the perceived knowledge within a context. According to Dey
(2001), context “is any information that can be used to characterize the situation of an
entity”. Indeed, Bohn (1998) argues that the quality concept in knowledge should extend
beyond merely the quality denitions in data and information to embrace the
decision-making process within a context. These denitions vary from “degree of
usefulness” for quality of data (Juran, 1992) to the broader term of “Satisfying the user’s
This research is being carried out under a PhD studentship award RPVB from The Hong Kong
Polytechnic University. Support of this research is gratefully acknowledged.
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0305-5728.htm
VINE
45,3
360
Received 28 July 2014
Revised 4 November 2014
16 April 2015
Accepted 20 April 2015
VINE
Vol.45 No. 3, 2015
pp.360-375
©Emerald Group Publishing Limited
0305-5728
DOI 10.1108/VINE-07-2014-0048
needs” when referred to quality information (Evans and Lindsay, 2005). On the other
hand, another major drawback in extending the denition of data and information
quality to cover knowledge quality is the indifference to deal with the quality factors
underpinning various knowledge denitions. Although there is no unilateral agreement
on differentiating data, information and knowledge (He and Wei, 2009;Shin et al., 2001),
there are nevertheless dominant approaches to positioning knowledge as a competitive
resource by differentiating knowledge from data and information through
contextualization for decision-making (Mancilla-Amaya et al., 2012;Shin et al., 2001).
Dey’s (2001) denition of the context suggests that, once knowledge is contextualized in
a decision-making process, related quality factors in data and information are
characterized by knowing about that context. In his denition, “knowledge” is dened
as an entity that is characterized by its contextual applicability (Zimmermann et al.,
2007). Although such denition of knowledge contextualization is denitely useful in
differentiating the quality aspect of data and information from knowledge, additional
research is needed to form a sustainable knowledge quality mechanism that can support
longevity of a knowledge management system (KMS) after an initial quality assessment
framework is in place.
This study commences with the proposition of knowledge quality denition within a
context and is followed by a consolidated quality knowledge assessment framework
based on the knowledge value chain (KVC) models. Subsequently, the proposed quality
assessment framework will introduce a sustainability mechanism for knowledge
quality, through user-guided means, for transitioning quality in KVC into a contextual
layer of knowledge quality.
Dening quality in knowledge
Among different components that can be measured in a KMS, knowledge quality is a
key element for representing the value and sustainability of a KMS (Rao and
Osei-Bryson, 2007). Although KMS has been implemented by many organizations
throughout the world, there has been no integrated framework to measure the
usefulness of the deployed KMS in a business context (Chen and Chen, 2005). In fact,
many businesses are relying on their respective KMS as a key source for strategy
formulation and decision-making without being able to systematically evaluate and
improve the quality of the existing knowledge within their business context. Over the
past decade, there have been various attempts to resolve the issue of quality data which
has ultimately led to better quality information (Jarke et al., 1998). However, with no
universal denition for quality, various denitions for quality have been proposed by
researchers over the years, based on the context of their studies (Mancilla-Amaya et al.,
2012). As a result, researchers working on quality of knowledge have applied the same
pathway in dening knowledge quality with the even more generic denitions for
quality (Eppler, 2006;Huang et al., 1999;Lee et al., 2007).
There have been extensive studies observing quality of knowledge from different
perspectives (Holsapple and Joshi, 2001;Owlia, 2010;Rao and Osei-Bryson, 2007). These
studies are either conducted narrowly based on quality attributes (Holsapple and Joshi,
2001) or widely explored through extensive reviews within multiple dimensions based
on knowledge denitions (Rao and Osei-Bryson, 2007). In both the cases, dening the
quality of knowledge is plainly associated with the proposed knowledge attributes
observed in their own studies. Although quality within a KMS can be traced in different
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Knowledge
quality
framework
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