Towards defining dimensions of knowledge systems quality

Rao, Lila; Osei-Bryson, Kweku-Muata

doi:10.1016/j.eswa.2006.05.003

Cited by 86 publications

(80 citation statements)

References 37 publications

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“…Like Rao and Osei-Bryson (2006), we suggest that end users could benefit from having access to visual ontologies when interacting with knowledge repositories, such as KMSs or the Web. Such visual ontologies could help individuals learn about the domain, and thereby enable them to identify what knowledge to search for in the KMS.…”

Section: Contributions To Practicementioning

confidence: 99%

Guidelines for Designing Visual Ontologies to Support Knowledge Identification

2011

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Organizations often provide workers with knowledge management systems to help them obtain knowledge they need. A significant constraint on the effectiveness of such systems is that they assume workers know what knowledge they need (they know what they don't know) when, in fact, they often do not know what knowledge they need (they don't know what they don't know). A way to overcome this problem is to use visual ontologies to help users learn relevant concepts and relationships in the knowledge domain, enabling them to search the knowledge base in a more educated manner. However, no guidelines exist for designing such ontologies. To fill this gap, we draw on theories of philosophical ontology and cognition to propose guidelines for designing visual ontologies for knowledge identification.We conducted three experiments to compare the effectiveness of guided ontologies, visual ontologies that followed our guidelines, to unguided ontologies, visual ontologies that violated our guidelines. We found that subjects performed considerably better with the guided ontologies, and that subjects could perceive the benefits of using guided ontologies, at least in some circumstances. On the basis of these results, we conclude that the way visual ontologies are presented makes a difference in knowledge identification and that theories of philosophical ontology and cognition can guide the construction of more effective visual representations. Furthermore, we propose that the principles we used to create the guided visual ontologies can be generalized for other cases where visual models are used to inform users about application domains.Keywords: Knowledge work, knowledge identification, visual ontologies, knowledge management system, ontology, cognition Introduction 1Organizations often provide knowledge workers with knowledge management systems (KMSs). Salespeople, for example, rely on KMSs to help them discover how to close sales with customers (Ko and Dennis 2011). Although knowledge resources are designed to make up for users' lack of knowledge, this very lack of knowledge may prevent users from knowing what to look for. The information retrieval literature has recognized a similar problem in information seeking. Belkin et al. (1982, p. 62) state that "in general the user is unable to specify precisely what is needed," a problem which Ford (2004) refers to as an "age-old paradox" (p. 772). Organizations could attempt to overcome this paradox in 1 Alan Dennis was the accepting senior editor for this paper. Hock Chuan Chan served as the associate editor.The appendices for this paper are located in the "Online Supplements" section of the MIS Quarterly's website (http://www.misq.org). MIS Quarterly Vol. 35 No. 4 pp. 883-908/December 2011 883 Bera et al./Designing Visual Ontologiesvarious ways. One approach is to provide an ontology-a description of concepts and their interrelationships in a domain-to help people understand the content available in their knowledge resources. An example by Heflin (2001) demonstrates this idea. Whe...

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Section: Contributions To Practicementioning

confidence: 99%

Guidelines for Designing Visual Ontologies to Support Knowledge Identification

2011

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“…The effective use of knowledge will depend, to a large extent, on its quality (Rao and Osei-Bryson, 2007;Yu et al, 2007). In this study, knowledge quality is defined as the fitness of operational knowledge being created and shared amongst organizational members to fulfill user requirements and expectation, relevant and valuable to the context of quality management systems.…”

Section: Knowledge Quality (Kq)mentioning

confidence: 99%

Knowledge Quality Effect on Process Based Management Effectiveness

Mustapha¹,

Nor²,

Wahab³

et al. 2018

IJET

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The objective of this study is to examine the effect of knowledge quality (KQ) on process-based management effectiveness (PBME). The knowledge quality for effective process-based management is an increasingly important issue to the business community. The current review conducted on research work in Knowledge Management and Quality Management Systems field has shown that there are deficiencies in the current research domain which, investigation on knowledge quality and its effect on process-based management was not an interest of previous researchers. The deficiencies shed light for future research that explores in details the effect of KQ on PBME. This issue has initiated interest amongst academicians to empirically examine the effect of knowledge quality on the process-based management effectiveness especially on the ISO9001:2008 certified organization. This study has found that KQ has significant direct effect with PBME in the certified ISO9001:2008 organization. This is indicated by the path coefficients and t-statistics of the relationship between KQ and PBME using PLS-SEM. The results is in line with the opinion derived from semi-structured interview conducted and also accords with earlier research which showed that the quality of knowledge can improve the performance of the processes. The evidence from this result suggests that organization should emphasize on the quality of knowledge to increase the process-based management effectiveness.

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“…KMS extend organisation and employees' memory, knowledge, and skills, enabling people to easily access at any time to best practices, problem solutions, and other types of knowledge through knowledge repositories and expert networks (Wu and Wang, 2006). Organisations have created KMS to enable the sharing of the intellectual capital created by knowledge workers in the organisation in order to increase decision making effectiveness and ultimately competitive positioning (Rao and Osei-Bryson, 2007). Knowledge repositories and expert maps enable the retrieval and the reuse of complex knowledge within but also between manufacturers and suppliers.…”

Section: Knowledge Transfer Technologiesmentioning

confidence: 99%

A knowledge-based view of the extending enterprise for enhancing a collaborative innovation advantage

Alguezaui

Filieri

2014

IJASM

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Abstract:The extended enterprise (EE) framework emerged in high-tech industries with large chains of suppliers to address the current challenges related to innovation and competition in complex scenarios. Since its conceptualisation, many transformations have interested the business landscape, such as the emergence of the knowledge economy, the rise of a more open approach to innovation, and the outsourcing and offshoring of value creating activities. This paper acknowledges these transformations and attempts to provide an updated model of the EE, termed extending enterprise, based on the knowledge-based view of the firm. The paper is conceptual in nature and research heralding from supply-chain management, operations, strategy, innovation, knowledge management has been brought together in this paper. After more than ten years from its conceptualisation, this is the first attempt that discusses the EE framework in light of the knowledge economy.Keywords: extended enterprise; knowledge-based view; knowledge transfer; innovation.Reference to this paper should be made as follows: Alguezaui, S. and Filieri, R. (2014) 'A knowledge-based view of the extending enterprise for enhancing a collaborative innovation advantage', Int.

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Towards defining dimensions of knowledge systems quality

Cited by 86 publications

References 37 publications

Guidelines for Designing Visual Ontologies to Support Knowledge Identification

Guidelines for Designing Visual Ontologies to Support Knowledge Identification

Knowledge Quality Effect on Process Based Management Effectiveness

A knowledge-based view of the extending enterprise for enhancing a collaborative innovation advantage

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