Eric Tsui

Trust as an antecedent to knowledge sharing in virtual communities of practice

This study focusses on the role of trust in knowledge sharing within the context of virtual communities of practice. Trust is widely accepted as an important enabler of knowledge management (KM) processes. We conceptualise trust across three dimensions, namely: competence, integrity and benevolence; we test hypotheses as to the effect of these facets of trust on knowledge sharing by surveying an intra-organisational global virtual community of practitioners. The results indicate that all three dimensions of trust are positively related to knowledge-sharing behaviour. Trust based on the perceived integrity of the community was found to be the strongest predictor of knowledge-sharing behaviour. Our findings suggest that the dimensions of trust buttress each other; although they are theoretically distinct, they appear to be empirically inseparable. We propose that in order for knowledge sharing to be enabled, trust must concurrently exist in all three dimensions. Implication to organisations in their recruitment policy is to include competence, integrity and benevolence in their sought-for attributes of new employees. KM practitioners also have to encourage these attributes in existing employees, who are potential members of on-line communities of practice. Knowledge sharing itself was conceptualised with three components – quantity (frequency), quality (usefulness or value) and focus (the degree to which an individual feels that they engage in knowledge sharing). Of the three components, focus exhibits the most significant relationship with trust factors. This finding makes knowledge sharing less tangible than perhaps would be expected. It suggests that establishing whether knowledge has been shared is more than counting the frequency or trying to evaluate the usefulness of the shared knowledge. These aspects are important especially to management, but to the individual who shares knowledge, her feelings of having shared knowledge appear to be more important. With the current understanding that knowledge sharing is more of a human activity than technology, it is important that any information system should be assistive in boosting users’ confidence that they are indeed sharing knowledge. If the systems do not re-enforce the users’ knowledge-sharing orientation, knowledge sharing may be discouraged. Notwithstanding the point made about knowledge-sharing focus, it is necessary to take into consideration all the components of knowledge sharing to fully capture the concept. This was well indicated when the combined variable of all (rather than individual) knowledge-sharing items had the strongest correlation with trust factors.

The role of IT in KM: where are we now and where are we heading?

Purpose – To provide a summary of the major trends in the evolution of knowledge management (KM) technologies in the last five years.Design/methodology/approach – Drawing from a range of literature published in the academic and industry arenas including the articles accepted in the special issue, the author also applied his own personal experience and practice knowledge in the field to summarize the three major trends in the use of KM technologies for the workplace and individual knowledge workers.Findings – First, KM is becoming more and more process‐centric and relevant technologies are gradually being aligned to support process‐based KM activities. Second, there is the emergence of personal networks and applications. Third, knowledge sharing and capturing are becoming more instantaneous (i.e. on‐demand and just‐in‐time).Practical implications – KM is becoming more and more just‐in‐time. Large‐scale KM programmes still prevail but, in future, the technical infrastructure and information content of these...

Tracking the Role and Evolution of Commercial Knowledge Management Software

With a plethora of commercial Knowledge Management (KM) tools and portals on the market, it has been difficult to understand the similarities and differences between these products and their role(s) in supporting various knowledge processes. This paper presents several frameworks to categorise, better appreciate the power of these tools, and relate them to common types of KM applications. These frameworks are based on the origin, characteristics, problem solving capabilities, alignment with business processes, and control (i.e., centralised versus localised) of KM Systems (KMS). The majority of commercial KM software are enterprise-wide software packages; tools that support knowledge processes at the individual level (i.e., Personal KM (PKM) tools) are seriously inadequate. Tools that foster virtual collaborations across organisational boundaries are becoming popular. For the latter, it is felt that Peer-to-Peer (P2P) computing will have a significant impact on KM at the group level in three aspects — file sharing, collaboration, and search. Criteria for the evaluation of tools and portals are outlined. KM tools are increasingly being absorbed into Portal products that host, among others, E-Business and intranet services. Emerging business models for the deployment of (technical) KM systems are also discussed. By identifying the dominant fields of KM, Artificial Intelligence (AI) and Information Retrieval (IR), it is possible to develop a broader perspective of the applicable technologies available for KM and align appropriate tools/gadgets to support various applications.

A framework for the improvement of knowledge‐intensive business processes

Purpose – This paper aims to present research into the improvement of knowledge‐intensive business processes.Design/methodology/approach – A literature review is conducted that indicates that a gap exists in the area of knowledge‐based business process improvement (KBPI). Sir Karl Poppers theory of objective knowledge is used as a conceptual basis for the design of a business process improvement (BPI) framework. Case studies are conducted to evaluate and further evolve the improvement framework in two different organisations.Findings – Highlights the gap in the literature. Draws attention to the merits of KBPI. Reports on the design of an improvement framework for knowledge‐intensive business processes, and on the lessons learned from the conducted case studies.Research limitations/implications – Practical and time constraints limit the scope of the case studies. General applicability can be inferred, but not tested, due to the small number of case studies.Practical implications – A new practical way to ...

Short communication: Knowledge management perspective on e-learning effectiveness

The synergies, functional effectiveness and integration of KM within an e-learning environment have attracted little interest for serious research, despite the overarching importance of knowledge acquisition by students for fostering their innovation and creativity. Learners often fail to reach their desired learning objects due to the failure of indexing methods to provide them with a ubiquitous learning grid. The aim of this paper is to discuss how knowledge management can be used effectively in e-learning, and how it can provide a learning grid to enable the learner to identify the right learning objects in an environment which is based on the learners context and personal preferences.

The roles and values of personal knowledge management: an exploratory study

Purpose – This paper aims to describe the roles and values of personal knowledge management (PKM). It seeks to investigate the roles of PKM in the KM process cycle and assess the values for improving the competences of both individuals and organizations.Design/methodology/approach – A research model was developed based on a critical review of KM and the PKM literature, followed by a survey of the KM participants in KM associations/interest groups/societies. The results and conclusions were made based on the quantitative analysis approach.Findings – The results indicate that PKM is playing important roles in the KM process and both individuals and organizations are benefitting by PKM in improving their competences. The roles of PKM are positively correlated to the values of PKM for individuals and organizations. It is also found that the values of PKM for individuals are correlated to the values of PKM for the organization.Research limitations/implications – This study is intended as a starting point for e...

An ontology-based similarity measurement for problem-based case reasoning

Traditional case-based reasoning uses a table/frame or scenario to represent a case. It assumed that similar input/event results in similar output/event state. However, similar cases may not have similar output/event states since problem solver may have different way to break down the problem. Thus, authors previously proposed problem-based case reasoning to overcome the limitation of the traditional approaches and used clustered ontology to represent the problem spaces of a case. However, synonym problem causes the mismatch of similar sub-problems of historical cases for new case. Thus, this paper proposed ontology-based similarity measurement to retrieve the similar sub-problems that overcomes the synonym problems on case retrieval. The recall and precise of ontology-based similarity measurement were higher than that of the traditional similarity measurement.

Dynamically Creating Indices for Two Million Cases: A Real World Problem

Efficiently indexing and retrieving cases from a very large case library are major concerns when building a Case-Based Reasoning (CBR) system. Most CBR research has focused on representation of cases, how to identify features that should be used for retrieval; and similarity measurement between values of attributes. In this paper, we propose a method for dynamically creating indices, and, also different similarity-measurement methods for different types of attributes. We also discuss the use of a relational database for representing cases, taxonomy knowledge, and spatial information. Our real world problem domain consists of 2 million incomplete insurance cases, with 30 different attributes. Even though all of these are valid cases, only 10 percent of these policies have lodged claims. These situations create a very complex case base for reasoning and problem solving. In response to this complexity, the approach adopted in building our CBR system involves a considerable amount of statistical pre-analysis of the contents of the case base to generate domain knowledge that could be used by the “Dynamic Index Creation Mechanism”. The main contribution of this paper is in describing the techniques used in our CBR system to dynamically create indices for the purpose of effective case retrieval.

Knowledge-based extraction of intellectual capital-related information from unstructured data

Nowadays, there is an increasing demand for the identification of an organizations intellectual capital (IC) for decision support and providing important managerial insights in knowledge-intensive industries. In traditional approaches, identification of an organizations IC is usually done manually through interviews, surveys, workshops, etc. These methods are labor and time intensive and the quality of the results is highly dependent on, among other things, the experience of the investigators. This paper presents a Knowledge-based Intellectual Capital Extraction (KBICE) algorithm which incorporates the technologies of computational linguistics and artificial intelligence (AI) for automatic processing of unstructured data and extraction of important IC-related information. The performance of KBICE was assessed through a series of experiments conducted by using publicly available financial reports from the banking industry as the testing batch and encouraging results have been obtained. The results showed that, through the use of hybrid intelligent matching strategies, it is possible to extract commonly referred IC-related information from unstructured data automatically. IC information analyst can rely on this method as an additional mean to identify and extract the commonly sought IC information from financial reports in a fast, systematic and reliable manner.

TaxoFolk: A hybrid taxonomy–folksonomy structure for knowledge classification and navigation

Abstract With the emergence of Web 2.0, user-generated metadata or so-called folksonomies facilitates management of digital content in the World Wide Web. The folksonomies have increasingly become a viable alternative for knowledge seekers to classify their knowledge (resources) and navigate the resources. Traditionally, in expert systems, taxonomy has been fulfilling these roles. However, in a taxonomy, the taxonomic structures are defined by the taxonomists or professional experts of the domain which often do not reflect user vocabulary. In addition, the terms of the taxonomy become outdated very fast which in turn compromises the efficiency and effectiveness of knowledge classification and navigation. On the other hand, maintenance of the taxonomy is time consuming and exhausted. This paper presents taxonomy and folksonomy integration algorithm, namely TaxoFolk to integrate the folksonomy into a taxonomy to enhance knowledge classification and navigation. The output is a hybrid taxonomy–folksonomy structure. The TaxoFolk algorithm comprises of data mining techniques, namely formal concept analysis (FCA), ID3 classification and simple matching coefficients (SMC). Three different taxonomy domains and its folksonomy are used to setup the experiments to identify and to evaluate the threshold values for filtering infrequent tags and invalid tags to automate the TaxoFolk algorithm to integrate a filtered folksonomy with a pre-defined taxonomy for enhancing knowledge navigation. The conducted experiments have ascertained the most appropriate thresholds values for effective building of TaxoFolk structure.