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Journal Article

Organizing Customer Knowledge in Academic Libraries  pp21-32

Farhad Daneshgar, Lyn Bosanquet

© Jan 2010 Volume 8 Issue 1, Editor: Ettore Bolisani, Enrico Scarso, pp1 - 180

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Availability of sophisticated ICT infrastructure combined with emerging business processes such as various service orientation configurations, constitute major characteristics of many of today's libraries in western universities. This has created a vast amount of customer‑related information in libraries. This article provides a methodology for organising customer knowledge in academic libraries. A two‑dimensional Customer Knowledge Taxonomy (CKT) has been presented for organizing the customer knowledge, thus providing a formal and explicit specification to deliver a shared conceptualization of customer knowledge. Based on the proposed CKT, customer knowledge in academic libraries can be classified into (i) knowledge about customers, (ii) knowledge from customers and (iii) knowledge for customers. The knowledge in each of these three categories can be 'explicit' and 'tacit', thus providing six categories of customer knowledge. The second major contribution of this paper is to introduce a method for integrating the above first and second categories of customer knowledge in order to derive the third category. This integration methodology is based on an integrated cyclical knowledge flow model that consists of four phases including: (i) communication, (ii) knowledge sharing & dissemination, (iii) knowledge acquisition and application, and 'iv' knowledge utilization and evaluation. Through a qualitative research, the proposed framework, consisting of the CKT and the corresponding integrated cyclical knowledge flow model, was then applied to a large university library for coding and classifying the vast amounts of existing customer data residing in 2,500 interview scripts within the case study organization. In doing so, a uniform coding scheme had to be developed using a focus group methodology. Data were then stored into a customer knowledge base using the Laximancer software. The proposed framework was evaluated for consistency of conceptualisation to ensure reusability in similar environments. It is expected that similar organisations will benefit from the proposed methodology for classifying the customer knowledge in academic libraries and the associated evaluation methodology for design and development of integrated knowledge based systems which in turn will support emerging processes within the organization.


Keywords: Knowledge taxonomy customer knowledge management knowledge management in library evaluation of customer knowledge innovative services academic libraries


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Journal Article

Knowledge Audit with Intellectual Capital in the Quality Management Process: An Empirical Study in an Electronics Company  pp98-116

Percy Chi Wai Chan, W.B. Lee

© Apr 2011 Volume 9 Issue 2, ICICKM 2010 special issue, Editor: W.B. Lee, pp85 - 180

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Most of the intellectual capital (IC) assessment tools are based on a “top‑down” approach which does not explore deeply into the particular business process and the specific knowledge needs. Those IC assessment tools generally measure the intellectual capital of an organization as the return on intangible assets covering Human Capital (HC) such as staff skills, innovativeness and work experience, Structural Capital (SC) such as IT systems, documents and patents, and Relational Capital (RC) such as relationship with customers and suppliers. Traditional IC assessment tools with “IC reporting” deliverables aim at identifying useful knowledge that can create wealth for the organization in assessing the performance and value creation process. In contrary, a systematic “knowledge audit” is a process‑oriented and stock‑taking approach for evaluating the “knowledge healthiness” of an organization from the “bottom‑up”. There is potential to merge two methodologies into one integrated assessment tool to present a comprehensive IC reporting in an organization. Knowledge assets underpin the capabilities and core competencies of any organization. The importance of a knowledge audit is the first step in determining how knowledge is handled in mission critical business processes in an organization. Quality management processes are the main subsets inside an organization’s critical business processes. A knowledge audit provides an evidence based assessment of the knowledge assets within an organization, however, there is a lack of a systematic approach in the way knowledge audits are conducted. In addition, there is no standard way of measuring Intellectual Capital (IC) through a better understanding of knowledge assets that are captured from a knowledge audit. The two different streams of KM and IC are complementary and provide the cornerstones for the definition of a managerial framework to identify, assess, exploit and manage organizational knowledge. In view of the importance of the knowledge audit and the deficiencies in the standard ways of IC measurement, a structured knowledge audit approach has been applied. This paper presents an integration of knowledge audit and IC reporting approach which has been applied in a Quality Assurance (QA) Department of an electronics company, for knowledge assets stock‑taking in six specified Value Added Quality Management Processes (VAQMP). More than 74 staff, over 4 corporate functions and 5 departments in two manufacturing plants, from different work levels involving 6 quality management processes from each plant, participated in the research. 52 Participants were provided with various knowledge audit forms to complete in order to provide information about the IT tools/platforms, documents, implicit knowledge, as well as the critical industrial technologies in each VAQMP process. Quantitative and qualitative analysis was then undertaken, including stakeholder analysis and the identification of critical knowledge workers, industrial technologies, crucial documents, implicit knowledge, as well as the knowledge fountain and knowledge discovery points of the process. The outcomes and effectiveness of the knowledge audit were evaluated in both KM and IC aspects. In most Intellectual Capital assessment tools, the workflow of the business process and the specific knowledge needs are not taken into account. On the other hand, this structured knowledge audit helps to identify critical organizational knowledge that needs to be captured and transferred for the healthy operation and sustainability of the quality management processes, in order to prevent quality crises. Finally, after the consolidation of the explicit and implicit knowledge inventories, as well as constructing an IC value tree, an intellectual capital statement for the Group Quality Assurance (GQA) Department was produced.


Keywords: group quality assurance, intellectual capital, intellectual capital statement, IC value tree, taxonomy, value added quality management processes


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Journal Article

The Modernisation of Statistical Classifications in Knowledge and Information Management Systems  pp126-144

Andrew Hancock

© Jun 2017 Volume 15 Issue 2, Editor: John Dumay, pp59 - 146

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As technology transforms knowledge and information management systems, statistical data is becoming more accessible, available in bigger and more complex datasets and is able to be analysed and interpreted in so many different ways. Traditional approaches to the development, maintenance and revision of statistical classifications no longer support or enable description of data in ways that are as useful to users as they could be. The ability to search and discover information in ways that were previously not possible means that new methodologies for managing and describing the data, and its associated metadata, are required. The development of structured lists of categories, often hierarchic in nature, based on a single concept, limited by the constraints of the printed page, statistical survey processing system needs, sequential code structures or narrow user defined scopes results in statistical classifications neither dynamically reflecting the real world of official statistics nor maintaining relevance in a fast changing information society. Opportunities exist for modernising the developmental processes for statistical classifications by using, for example, semantic web technology, Simple Knowledge Organisation Systems (SKOS), and Resource Description Frameworks (RDF), and for better describing metadata and information within and across multiple, interconnected information and knowledge management systems. These opportunities highlight the difficulties that come with using traditional approaches to statistical classification development and management, and encourage new thinking for different and more flexible options for developers and users. This paper explores the need to dispense with traditional practices for developing statistical classifications as cornerstones of metadata, knowledge and information management, and comments on the need to change the underlying methodology within statistical classification theory, best practice principles and how they can be used in associated information management systems.


Keywords: Classification Theory, Metadata, Statistics, Taxonomy


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Journal Issue

Volume 8 Issue 1 / Jan 2010  pp1‑180

Editor: Ettore Bolisani, Enrico Scarso

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Knowledge Management at a Turning Point

1. Introduction: Ten years of ECKM

This special issue is a selection of the best papers presented at the 10th edition of the European Conference on Knowledge Management (ECKM), which was held at the University of Padua on 3‑4 September 2009 and which we had the privilege to chair. Symbolically, a decade often represents a turning point for people, who are used to reflecting on their past experiences and setting future goals. The purpose of this Editorial is somewhat similar. We will base our remarks on analysis of the papers presented at ECKM, and on our additional feelings on the matter. We will also introduce the papers selected for this Special Issue.

No longer the exclusive domain of philosophical speculation, today knowledge is really referred to as an essential and concrete element of economic and social development. There is widespread recognition that knowledge is a vital resource, and the way to prosperity is increasingly considered the capability to generate and exchange knowledge. Issues such as knowledge creation, storage, and transfer have moved to the forefront of attention of corporate executives. Also, the building of "knowledge societies" and "knowledge economies" is often indicated as the deliberate goal of policy makers, and there is increasing awareness that, to keep abreast of the volatile and changing global environment, organisations, countries and regions need to develop a better understanding of how knowledge and intellectual capital can help to boost innovation, implement effective business processes, and deliver goods and services. The current economic climate, with the difficulties it brings, represents an additional motivation to invest resources in the production, management and delivery of knowledge, in the hope that this can help our societies to keep on progressing.

Consequently, Knowledge Management (KM) now has a well‑established place in the research community, as is also testified by the great number of interesting papers that are submitted every year to Journals and Conferences like ECKM. So far, the efforts made by the research community have been impressive. If one looks up into a search engine or a bibliographic databank and searches for articles related to "knowledge management", hundreds of thousands of references can be easily found.

The contribution that the research and practice of KM can give to the management of companies and institutions is increasingly important, but so are the responsibilities of researchers and practitioners growing. The results achieved in defining conceptual models and practical approaches for managing knowledge have been significant. But despite all this, many questions remain open and need clarifications, insights, and research efforts. The analysis of the papers presented at the ECKM can give us an idea of these hot issues.

1.1. Multidisciplinarity

A particular issue that KM brings about is that of its multidisciplinarity. This is both a point of strength and weakness at the same time. The point of strength is that the notion of knowledge is multifaceted and pervasive, and requires the combination of different viewpoints: the conceptual and practical analysis of the various issues associated to KM and the identification of appropriate methods for research and practice require the joint efforts of people specialising in very different areas: from economics to business management, from sociology to information technology, from psychology to policy making. But this wealth of perspectives is also a point of weakness. The interaction among so different fields is never easy, requires continuous debate and an effort of mutual adaptation. So far, the researchers and practitioners in KM have made huge efforts to combine and integrate their different perspectives, to share notions and languages, to discuss theories, methods, and findings. This has been facilitated by the organisation of Conferences like ECKM (which are, by nature, multidisciplinary) and the foundation of Journals targeted to KM (including the EJKM) that accept contributions from different areas. But there is now the need to give coherence to this increasingly articulated and complex field of study, in order to make KM an established and recognised discipline in the context of managerial sciences.

1.2. KM and other fields of study

Another important point is the increasing pervasiveness and the recurring use of topics like knowledge and knowledge management in other more established areas. The best example is probably that of innovation studies. The problem of innovation is often related to a problem of knowledge, which raises issues that are not dissimilar from those analysed in KM. The approaches adopted by researchers are of two opposite types. Some, remaining within the boundaries of their "mainstream" discipline, try to apply concepts and methods typically developed in the KM literature (such as classifications of knowledge, mechanisms and processes of KM, communities of practices and so on) to explain specific phenomena that the theories of their discipline are not able to explain (Jensen et al., 2007; Frenza & Ietto‑Gillies, 2009; Tödtling et al., 2009). Conversely, others start from KM and try to extend the focus of this area to innovation‑related problems (Swan et al., 2002; du Plessis, 2007). What we see is a sort of mutual convergence of methods and research topics, which is clearly significant for the development of our area of study, but is also challenging. The same kind of relationship with KM can be traced in other areas (from strategic management to human resources, from economic modelling to organisational studies).

1.3. Formal models

As we know, the use of formal models is often the reason for contrast between the "hard" sciences, mostly based on mathematical models, and the human and social sciences that deal with more elusive and ambiguous objects. In the case of KM, things are more complicated because this is by nature a multidisciplinary field, where researchers pick from different disciplines and areas.

So, on the one hand the formalisation of definitions, concepts and models is important because it enables us to set the foundational grounds of any discipline, and provides a rigorous common language with which researchers can communicate and interact. But on the other hand, when we talk about models in KM we need to combine different approaches that derive from various areas: linguistics, psychology, sociology, economics, mathematics, informatics, and so on. This debate about formalisation in KM is still at the beginning stage. Researchers are more involved in finding or using definitions for their specific purposes; or it happens that the formal modelling is just relegated to the technological areas.

1.4. The role of technology

The issue of technology is clearly central in KM, and pervasive. However, the views of technology are often very different. Undoubtedly, the development of KM is sometimes preceded and, therefore, driven by the technical advancements. For instance, we wouldn't have started to study the effects of social networking on knowledge sharing, if Web 2.0 applications like Facebook, Google or Twitter hadn't been invented. In some cases, the notions developed by sociology‑based or psychology‑based KM researchers have influenced technical studies (for instance, the reflections on the complex nature of human‑computer interactions). But in some other cases, the technological research poses evident constraints to KM by putting an emphasis on the "explicit" knowledge contents and their treatment. Generally speaking, we can say that there is no consensus on a common interpretative model of the role of technology in KM and vice‑versa, which sometimes raises conflicting views whose trace can often be found in the current debate.

2. The selected papers

The 10th Edition of ECKM reflected many of the aspects mentioned above. The programme included eight streams with more than 110 papers focusing on the various hot areas of KM. As happened in the previous edition, business applications were the most important field, but other emerging areas (such as KM for public policy making, and KM in Education) were well represented. There was a good balance between the technical studies (with an emphasis on the "new" semantic systems) and the sociological, organisational, and psychological research. In some cases, the presentations focused on very specific aspect (from knowledge sharing to KM measurement), which also testifies that the research has started to consider detailed problems.

It is also worth mentioning the hot themes that were treated by three keynote speakers. Irma Becerra‑Fernandez, from the Florida International University, offered a broad view of the recent trends in KM research in her speech entitled "Knowledge Management and Organisational Learning: Where Technology and Socialisation Meet", and provided an interesting view of the complex interrelation among IT, learning, and organisational aspects. The other two keynote speakers focused on technology, but with different views. In his speech entitled "Semantics in Action", Antonio Linari from the Italian company Expert System illustrated the prospects of application of advanced KM technologies and semantic tools. Frieda Brioschi, President of Wikimedia Italia, in her speech entitled "Open Knowledge Management ‑ The Wiki Way", described Wikipedia as a Knowledge Management System, and addressed the complex interconnections between the technological artefact and the social‑relational aspects.

In the rest of this section we will briefly introduce the papers selected for this Special Issue. Fifteen papers were drawn directly from the ECKM proceedings on the basis of the following criteria: the judgement of the Conference Session Chairs; our evaluation about the current degree of completeness of the paper; and the attempt to offer a complete picture of the various point of views and approaches. A last paper, which was not presented at the Conference but was selected by the EJKM Editorial Board, well fits our intentions, as the reader will see: in summary, all the papers are good examples of the current hot issues in KM, as our tentative classification attempts to highlight.

2.1. Definitions and representations of knowledge

Two papers address this basic question that has always been ‑ and still is ‑ a contentious issue. The paper "Evaluating a Living Model of Knowledge" by Paul Parboteeah, Thomas Jackson and Gillian Ragsdell proposes a fresh view and introduces a definition of knowledge based on the notion of autopoietic systems (Maturana & Varela, 1980). This notion was introduced decades ago for representing entities having characteristics that can be assimilated to living organisms, and according to the authors, this is the case of knowledge. An autopoietic perspective can help to overcome the limitations of the typical KM approaches used in KM research that implicitly adopt definitions of knowledge that focus either on "pure objectivity" or, conversely, on "pure subjectivity". In the paper, the authors also illustrate a pilot study for testing their approach: they admit that before this "biologically grounded" model of knowledge can be integrated into KM theories, there is the need to test it empirically. All this makes this research line very stimulating.

In "A Framework for Assessing Commensurability of Semantic Web Ontologies", Liam Magee deals with another recurring problem that is especially critical for the development of advanced KM technologies: the formal representation of knowledge. This issue is central for the researchers in ontologies and Semantic Web: although the advancements have been impressive in theoretical terms, when it comes to practical business applications there are still several unresolved problems. One of these is the issue of co‑ordinating disparate ontologies that refer to distinct knowledge domains, which is obviously essential for effective knowledge sharing. As the author argues, the approaches currently used are algorithmic and don't consider background elements or tacit components, which are indeed essential in many practical KM scenarios. The paper presents a framework for understanding the "tacit assumptions" behind ontologies by describing and comparing cultural information and other related elements. The author also illustrates a prototype software toolkit and the results of a pilot test of it, along with some considerations of how the framework might be further improved.

2.2. KM and learning organisations

The understanding of the effective implementation of KM in organisations is connected to a reflection on the learning processes. Indeed, the relationship between organisational learning and KM is a central issue for the researchers involved in the organisational implications of KM. Our selection proposes two papers that provide interesting perspectives on the mechanisms of organisational learning for innovation and the related implications. In their "Virtual Communities of Practice: Investigating Motivations and Constraints in the Processes of Knowledge Creation and Transfer" Ana Maria Ramalho Correia, Alice Paulos and Anabela Mesquita investigate the efficacy of an organisational approach which is typical in the KM practice but whose effective role and implementation problems still deserve investigations: the Virtual Community of Practice (CoP). CoPs are recognised as an essential method for facilitating co‑operative organizational learning and knowledge creation involving members dispersed in time and space, but their success can't be taken for granted. Starting from the consideration that not all CoPs reach the same level of success, the authors attempt to explore the reasons for this, and particularly the motivations that may push people to participate in a CoP and, conversely, the problems that may hinder an effective KM process. The findings of a case‑study are illustrated, and the authors conclude that the organisational culture and, especially, the individuals' professional and personal development are essential for their fruitful participation in a CoP, while financial rewards do not prove to be a sufficient motivational factor. Other important factors are the alignment of CoP functions with the managerial objectives, and the need for a clear justification of the time spent in working for the CoP. The case‑study, that confirms the hypotheses formulated in other works, is especially precious in that it allows focalising a number of essential issues that need to be explored. The paper "Linking Unlearning with Innovation through Organizational Memory and Technology" by Juan‑Gabriel Cegarra‑Navarro, Gabriel Cepeda‑Carrion, and Daniel Jimenez‑Jimenez also reflects on the problems that can be associated to organisational learning, and in particular the limitations of the use of knowledge memorised in organisations. Two typical distinct mechanisms of learning in an organisation are analysed: one which is based on the organizational memory and can provide tacit knowledge contents, and the other which uses information technologies and mainly focuses on explicit elements. The authors argue that both these mechanisms show the same limit: the previous memories reflect a world that is only partially understood and assimilated. By limiting an "open‑minded" perspective, this might lead individuals to wrong decisions and actions and, especially, to limited innovative potential. Therefore, they propose to consider the importance of "unlearning", seen as a process of re‑orientation of organisational values, norms and behaviours to open the way for new solutions and approaches. The nature of unlearning processes, and the way these can promote organizational innovativeness, is examined with reference to both the "organizational memory" and the "information technology memory". The authors also present the findings of a survey of 291 large Spanish companies that seem to confirm that the establishment of an "unlearning culture" can enable the company's memory to have a positive influence on innovativeness.

2.3. Knowledge networking

An emerging topic for KM research is that of knowledge networking, in other words the issue of sharing and transferring knowledge across and between organisations. Actually, the problem of sharing and transferring knowledge is often addressed in the literature, but when it comes to networked environments the recent studies highlight peculiar aspects such as the importance of structural configuration, the distribution of roles and tasks, etc.

The paper by Eli Hustad, entitled "Exploring Knowledge Work Practices and Evolution in Distributed Networks of Practice"focuses on the evolutionary patterns of the particular networking structures represented by communities of practice, seen as networks. Based on a longitudinal study conducted in a multinational company, the author specifically analyses the life cycle evolution of these structures, identifies different categories of knowledge network, and shows that these networks evolve differently over time according to their peculiar characteristics. Four distinct evolution patterns are singled out: 1) devolution and dissolution, 2) recursive patterns where new networks emerged from the mother network, 3) integration of knowledge practices through cross‑networks, and 4) innovation and expansion in scope and size. These results are particularly interesting not only for the classification proposed, but also because they challenge some typical interpretations of organisational evolution that are suggested in the literature. Especially, the author argues that the social evolution of knowledge networks can have the effect to re‑define and alter the organisational routines of a company.

Remko Helms, Renato Ignacio, Sjaak Brinkkemper and Ard Zonneveld, in their "Limitations of Network Analysis for Studying Efficiency and Effectiveness of Knowledge Sharing" address a methodological question and a practical problem at the same time: their attempt is to test a typical sociological tool – the Knowledge Network Analysis – as an approach to study the tacit dimension of knowledge sharing with the specific purpose of examining the deficiencies of networked structures. For this purpose, a case study of an international software company is proposed, and the authors compare the outcomes of the knowledge network analysis with a qualitative study based on interviews and direct observations that focuses on both the tacit and the explicit dimensions of knowledge. To analyse the qualitative data, a new model is developed, called Knowledge Sharing Environment Model (KSEM), used to examine knowledge sharing bottlenecks. The authors conclude that Knowledge Network Analysis is a powerful tool for the identification of bottlenecks, but the use of additional methods (such as the KSEM) may be needed to study the causes behind the identified bottlenecks.

2.4. KM implementation: open issues and causes of failure

Even though they adopt a different perspective, the two following papers analyse a similar topic: the possible problems that the implementation and use of KM can raise in specific situations.

In the paper "The Adoption of Knowledge Management Systems in Small Firms" Pietro Evangelista, Emilio Esposito, Vincenzo Lauro and Mario Raffa consider the critical issue of KM implementation in small businesses, where its potential benefits have not been fully exploited yet. The authors observe that the literature lacks contributions to the critical success factors for KM adoption in SMEs. They illustrate the results of an empirical investigation on a cluster of 25 high‑technology small businesses in Southern Italy, and argue that while small companies can show significant KM needs especially in terms of inter‑company collaboration, they usually adopt very simple KM systems. Also, they argue that it is important to consider that for these companies, knowledge exchanges are mainly tacit and based on personal relationships and interactions. In summary, the paper makes the point that there are some relevant factors that may motivate the adoption of KM systems by small businesses, but also significant barriers, such as the cultural barriers and the concerns for intellectual capital protection.

Alexeis Garcia‑Perez and Robert Ayres, in their "Wikifailure: the Limitations of Technology for Knowledge Sharing", investigate the possible difficulties of KM implementation in a Web2.0‑based environment. Indeed, although the modern systems of social networking are often considered to be an essential support for knowledge sharing, the technology itself may not be enough for successful KM processes. In their paper the authors illustrate an original case study of a Wiki system implemented to support a group of dispersed researchers belonging to the same organisation. The paper shows that, after a good initial success, the use of the Wiki rapidly declined. The study shows two factors that appear to be particularly significant. First, the lack of critical mass: only a small proportion of users are likely to contribute and there may be a threshold size for a community to be able to support a vibrant Wiki. Second, time is another critical issue, since the people may think they are too busy to contribute to or use the system. Although it is always difficult to generalise from a single case‑study, the paper makes interesting points that deserve further validation.

2.5. KM success factors and assessment

The following two groups of papers more directly focus on typical managerial issues. In particular, this first group considers the issue of KM assessment and of success factors evaluation. This is a recurring problem in the managerial practice, but in the case of KM there are very peculiar challenges especially due to the intangible nature of knowledge.

Franz Lehner and Nicolas Haas in their "Knowledge Management Success Factors – Proposal of an Empirical Research" start from the assumption that to measure the effectiveness of KM programmes it is first necessary to identify their possible success factors. This topic is not new in the literature, but despite the various research efforts it remains an open question. After an overview of previous works and the identification of a number of potential success factors, the authors propose an application of the Structure Equation Modelling (SEM) approach to assess KM success; the model is also based on the theory of planned behaviour and is adapted to the context of KM. The attempt is to empirically evaluate the distinct success factors already identified in previous studies. The connection with the company strategic view may represent a further development of this research.

In "Assessing the Impact of KM on Organisational Practice: Applying the MeCTIP Model to UK Organisations", Sandra Moffett and Anne Hinds analyse the critical success factors for KM especially in knowledge intensive industries, where organisations heavily rely on the competencies of staff for their competitive advantage. The paper presents the results of an empirical investigation undertaken in early 2009 with 588 UK companies, with the aim of assessing the impact of the MeCTIP (Macro environment, Culture, Technology, Information and People) model on UK companies. The key factors for successful implementation, practice and development of KM are analysed. The research, that employed the "Benchmarking KM" online survey tool, showed that five key elements (two related to the infrastructure of the organisations and three to the process orientated activities for information, technology application and human expertise) have to be considered by organisations seeking to implement successful KM programmes. These findings seem to confirm previous studies on the topic.

Geoff Turner and Clemente Minonne in their "Measuring the Effects of Knowledge Management Practices" address the issue of KM assessment by considering a foundational perspective. Based on a survey of the previous literature, the authors identify three interdependent and complementary pillars that support the concept of KM, i.e.: Organisational Learning Management (OLM), Organisational Knowledge Management (OKM) and Intellectual Capital Management (ICM). The first concerns the problem of capturing, organising and retrieving explicit knowledge and, according to the authors, has led to the simplistic misconception that KM only involves the capture of the "content of employees' minds". The last is dominated by those particularly interested in defining key performance indicators. The authors argue that it is the second pillar which is the most important (i.e. the OKM pillar), because the essential task of measurement can only be undertaken once an organisation has clearly established its strategy‑structure‑process parameters that enable it to access, create and embed the knowledge that it needs. Accordingly, the paper by Turner and Minonne looks more deeply at the OKM pillar and, more generally, it highlights the lack of a general integrative approach to enhancing organisational performance in this key strategic area.

2.6. KM in strategic planning and decision‑making

The following three papers propose another relevant issue particularly important for managers. They directly analyse the contribution of KM as a strategic resource for companies and its implications in terms of decision‑making approaches.

In "Functional concept for a Web‑Based Knowledge Impact and IC Reporting Portal" Gaby Neumann and Eduardo Tomé discuss the effective use of knowledge as a strategic resource. They illustrate a study that combines different methods and tools, and proposes a web‑based infrastructure for understanding knowledge impacts and IC markets in order to support decision‑making. This infrastructure consists of two sections: the first allows to benchmark a company's knowledge management maturity and suggests changes in the company's strategy concerning knowledge‑related activities; the second section consists of a "World Atlas on Intellectual Capital" comprising world‑wide data on constituents of the IC market (demand, supply, equilibrium, investment, need, stock, flow, and returns). Also, the paper contributes to R&D measurement and tries to develop a better understanding of the impact of KM and IC on the delivery of effective business processes and high value services.

The use of KM approaches to manage risks in decision‑making is analysed in Eduardo Rodriguez and John S. Edwards' paper "People, Technology, Processes and Risk Knowledge Sharing". They specifically deal with KM and its relationship to the perceived value of enterprise risk management, with a special emphasis on financial services. A survey of risk management employees of several organisations, concentrating on the factors affecting the perceived quality of risk knowledge sharing, is proposed. The analysis considers five explanatory variables: two relating to people (organizational capacity for work coordination and perceived quality of communication among groups), one relating to processes (perceived quality of risk control) and two related to technology (web channel functionality and risk management information systems). Preliminary findings indicate that four of these five variables have a significant positive association with the perceived quality of risk knowledge sharing. In particular the "people" variables appear to have the greatest influence on the perceived quality of risk knowledge sharing, even in a sector that relies heavily on technology and on quantitative approaches to decision making.

The issue of formulation of knowledge‑intensive business strategies is analysed in "Knowledge‑Based Strategies for Knowledge Intensive Business Services: a Multiple Case‑study of Computer Service Companies" by Enrico Scarso and Ettore Bolisani. The models for formulating business strategies that explicitly consider knowledge as the core resource are analysed in the particular case of computer service firms. Since the activity of those companies is based on the capability to manage knowledge flows among various actors, the formulation of their business strategies requires new approaches that directly focus on cognitive processes. The study consists of an extensive survey involving the computer service companies located in Northeast of Italy. Findings allow to draw useful schemes for the identification of knowledge‑based strategies. In particular, the paper: a) analyses approaches that can be used to establish a knowledge‑based business strategy; b) uses such approaches to identify how computer service firms pursue their business strategy by means of a proper management of their knowledge assets; c) discusses the utility of the illustrated approaches, and provides some suggestions for a future research agenda.

2.7. KM in universities and education

The last two papers deal with an issue that has sometimes been considered "implicit" in KM but actually deserves a specific analysis: the problems of knowledge sharing involving education and universities. In "The Role of Multinational Corporations (MNC's) in Developing R&D in Thailand: the Knowledge Flow between MNC's and University" Lugkana Worasinchai and Aurilla Aurelie Arntzen Bechina analyse the issue of knowledge sharing between firms and Universities, which has been always considered a challenging task especially in the case of developing countries where multinational corporations play a significant role in knowledge creation, technology diffusion and R&D. Worasinchai and Arntzen Bechina present the results of an empirical study aimed at understanding knowledge flows between foreign companies and local Universities in the case of the automotive industries in Thailand. In particular the research investigates the interrelated factors (industrial characteristics, firm characteristics and business models) that can play a substantial role in the knowledge sharing mechanism.

The final paper, which was proposed by the Journal's Editorial Board, is "Organizing Customer Knowledge in Academic Libraries" by Farhad Daneshgar and Lyn Bosanquet. The paper aims to discover and demonstrate ways of organizing customer knowledge in academic libraries using a large library in Australia as a case study. A Customer Knowledge Taxonomy (CKT) has been presented for organizing the customer knowledge, providing a formal and explicit specification to deliver a shared conceptualization of customer knowledge. This taxonomy was then applied to the case study for coding and classifying the vast amounts of existing customer data. It is expected that similar organizations to that investigated will benefit from the proposed methodology for classifying the customer knowledge in academic libraries and the associated evaluation methodology for design and development of integrated KM systems, which in turn may support emerging processes within the organization.

3. Signals from the 10th ECKM: new foundations or new frontiers?

After 10 years of ECKM (and, more generally a longer time of KM) some questions arise about the future of this research field. The analysis of ECKM proceedings and particularly of the selected papers, suggested to us some general remarks.

First, there may be a sort of "identity" problem. Today, many researchers and practitioners declare they work in the field of KM. But can we say that KM is a well‑defined disciplinary area in the management sciences, with established objects, boundaries, and methods? Or is it just a different way to see topics that are also considered in other areas and fields? This suspicion comes from the fact that knowledge is a pervasive term that tends to be used substantially in all the branches of management, economics, organisation science, but also psychology, sociology, computer sciences etc. The need to "recognise the peculiarity" of researchers and managers that explicitly work in KM is not just an academic question, but is also important in practical terms, for instance for research funding or recruitment. This clearly raises a question of definition: to institutionalise KM as a discipline, the characteristics of KM, its typical research objects, methods and foundational references, should be clarified and "declared". Some recent studies (e.g. Holsapple, 2003; Edwards et al., 2003) move towards this direction, but they still appear to have an exploratory nature, and a further focalisation may be useful. On the other hand, it should be remembered that a formalisation of KM may reduce the characteristics of "openness" that this field has so far shown.

This recalls a second issue: the "method". What are the scientific approaches that are the most appropriate to study KM? And is this question relevant, or useless? As our small selection of papers clearly demonstrates, diverging methods are often used by different researchers, which clearly reflect the broad coverage of KM topics. Case‑studies and surveys are still important for those that study organisational or sociological aspects, while mathematical and logical approaches (including semantics and ontologies) are especially used by people that study computer applications applied to KM. But also special techniques (like, for instance systems modelling, computer simulation, social network analysis) are starting to appear (many examples can be found in the 10th ECKM proceedings as well). This is clearly a rich toolbox, but in our opinion, the question is not just to identify the "most appropriate" method out of these, but rather to reflect on the comparative usefulness and applicability of each of them to the various research situations and objects. This is directly connected with the particular interpretation of the notion of "knowledge" that each study adopts. Specific research on this "methodological question" may also help the new generations of KM researchers.

A third question is particularly relevant for practitioners. Is KM really becoming an established component of the managerial practice? As it has often occurred in the past, the risk is that the focalisation on knowledge just becomes the "last fad" that may be overcome once new managerial paradigms have set other priorities. Personally, we don't think this can happen: the issue of knowledge as a central resource for organisations has serious foundations. Nevertheless, the issue of "institutionalisation" is still important.

Reading once again the proceedings of ECKM and particularly the paper presented in this special issue, our impression is that time is mature for researchers and practitioners to start providing answers to the mentioned questions. So far, the literature on KM has shown two main concerns: first, to explore the potentials of this field of study, especially in conceptual terms; secondly, to find solutions to practical problems of organisations. Now that we are at a turning point, a phase of consolidation is starting. Two contrasting challenges open: on the one hand to look back to the past for setting the foundational "institutionalisation" of the discipline by defining research objects, methods, disciplinary boundaries, etc; and on the other hand to look ahead to the future, for exploring the frontiers of this field and shedding light on the real potential of KM for the future societies. Combining these two goals is no easy task. But that's the beauty of the challenge.

Ettore Bolisani and Enrico Scarso
University of Padua, Italy

du Plessis, M. (2007) "The role of knowledge management in innovation", Journal of Knowledge Management, Vol 11, No 4, pp 20‑29.
Edwards, J.S., Handzic, M., Carlsson, S. & Nissen, M. (2003) "Knowledge management research & practice: visions and directions", Knowledge Management Research & Practice, Vol No 1, pp 49‑60.
Frenza, M. and Ietto‑Gillies, G. (2009) "The impact on innovation performance of different sources of knowledge: Evidence from the UK Community Innovation Survey", Research Policy, Vol 38, No 7, pp 1125‑1135.
Holsapple, C.W. (ed.) (2003) Handbook on Knowledge Management, Springer, Berlin.
Jensen, M.B., Johnson, B., Lorenz, E & Lundvall, B‑Å (2007) "Forms of knowledge and modes of innovation", Research Policy, Vol 36, No 5, pp 680‑693.
Maturana H.R. & Varela F.J. (1980), Autopoiesis and Cognition. The Realization of the Living. Dordrecht: Kluwer.
Swan, J., Scarbrough, H. & Robertson, M. (2002) "The Construction of ‘Communities of Practice' in the Management of Innovation", Management Learning, Vol 33, No 4, pp 477‑496.
Tödtling, F., Lehner, P. & Kaufmann, A. (2009) "Do different types of innovation rely on specific kinds of knowledge interactions?", Technovation, Vol 29, No 1, pp 59‑71.

Addendum from the Editorial Board
Last year, included in EJKM Volume 7 Issue 1 Special Issue for ECKM 2008, the paper "Dynamic Knowledge and Healthcare Knowledge Ecosystems" by Virginia Maracine and Emil Scarlat of the Academy of Economic Studies, Bucharest, Romania, was a result of research activity carried out under the aegis of the project "The Development of Theoretical Fundaments of Knowledge Ecosystems and Their Applications on Economy and Healthcare", funded by the Romanian Education and Research Ministry.


Keywords: academic libraries, autopoiesis, benchmarking, business strategy, clustering, collaborative technologies, communities of practice, companies, competitive advantage, computer services, CoP, critical success factors, customer knowledge management, distributed network of practice, empirical knowledge sharing investigation, empirical survey, Enterprise 2.0, enterprise risk management, epistemology, evaluation of customer knowledge, evolution patterns, factor analysis, high-technology sectors, impact analysis, Information communication technology, innovation, innovative services, intellectual capital management, KIBS, KM success, knowledge activities, knowledge creation, knowledge management in library, knowledge management maturity, knowledge management practices, knowledge network analysis, knowledge networking infrastructure, knowledge sharing, knowledge taxonomy, knowledge transfer, knowledge-based strategy, knowledge-producing cultures, learning network, LISREL, logistics, MeCTIP model


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Journal Issue

Volume 9 Issue 2, ICICKM 2010 special issue / Apr 2011  pp85‑180

Editor: W.B. Lee

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Prof. W.B. Lee is Director of the Knowledge Management Research Centre of The Hong Kong Polytechnic University.    Prof. Lee is the editor of the Journal of Information and Knowledge Management Systems, and International Journal of Knowledge and Systems Science. He established the Knowledge Solution Laboratory, the first of its kind in Hong Kong and has pioneered research and practice of knowledge management and knowledge audit in various organizations.  Prof. Lee and his team have launched Asia’s first on‑line MSc. Program in Knowledge Management.  His research interest  includes manufacturing systems, knowledge management, organizational learning and intellectual capital‑based management.


The 7th International Conference on Intellectual Capital, Knowledge Management & Organizational Learning (ICICKM 2010) was hosted by the Knowledge Management Research Centre ,The Hong Kong Polytechnic University, Hong Kong, China, the first time in Asia.

The conference is well attended by more than 100 delegates from over 30 countries and regions.  This conference series is unique in the sense that it unifies all the important themes in this multidisciplinary area which can be pursued from either the knowledge management, intellectual capital management or organizational learning perspectives or any combinations of them.  The relationship between these themes is important. It is  only  through  the effective management of our knowledge assets  and the continuous  learning   of   individuals, teams and  organization  that we  are able to build the intellectual capital which is the underlying power driving corporation’s future growth.

Apart from the rich tacit knowledge exchange among delegates during the conference, the conference proceedings give a good record of papers delivered at the conference. Our thanks and appreciation go out to all those who presented papers and participated in the conference. Feedback to date from delegates and participants has been extremely positive. The support from departments within the University and our session Chairs and Keynote speakers is gratefully acknowledged. We also recognize the efforts of both the Executive and Conference Committees for their contribution to the double blind peer review process. Based on the input of the session chairs, we are able to select 10 papers of these to be published in this electronic Journal.  These cover a lot of topics including KM models, strategy, innovation, organizational leaning, and intellectual capital measurement, and provide various new insights to the readers.

Grant started by asking the question if knowledge Management (KM) is just another fab.   Through the lens of management fashion theory and a good review from bibliometric evidence he assures us that KM is unlike other management themes and is an enduring management activity. However, there is a potential conflict between the interests of practitioners and researchers. With different perspectives and prescriptions, Imani furthers the discussion by examining the KM strategy in 18 global companies and finds out how they are linked to the business strategy, which are either formulaic (to support routine activities) or embryonic (to address corporate strategic agenda).  On the other hand, Tan and Nasurdin focus on the influence of KM effectiveness on innovation in 171 large manufacturing firms in Malaysia and find out that the effectiveness of knowledge acquisition has a positive influence on both the technological and administrative (organizational) innovation. 

Another issue of concern to researchers in this conference is on how knowledge management  is linked to business performance and its evaluation. These findings and observations are reinforced in a study conducted by Rabhi in Saudi Arabia on the effect of KM on the Key Performance Indicators (KPIs), including customer satisfaction, business savings and projects completed. Tiago et al. studied the relationship between the knowledge management and eBusiness activities by applying a structural equation model in a large database of KM activities of European and American firms. In a study of performance of a Quality Assurance Department conducted by Chan in an electronic factory, the performance of the quality management processes is related to the intellectual capital involved which is captured from a knowledge audit of the plant.

De Alvarenga Neto and Vieira from their Brazil experience described the four main components of KM Model in a Brazilian research  cooperation, that is, strategy, the environment (from social, information, cognitive and business), tool boxes, and  tangible and intangible outputs, and concluded that  for the model to be useful it should be collaboratively built  among  organization units instead of one from top‑down. Inter‑organizational and organizational learning has been recognized to be important for knowledge creation. Laursen, based on an empirical study of four organizational development projects at four Danish high schools revealdifferent perspectives on the projects set up by the staff and the management and how the perspectives have consequences  on what is actually learned by individuals as well as the whole organization.  As team learning and performance is closely related to the shared mental models of the team members, Zou and Lee explored the shared mental model of eight sigma project teams through collective sensemaking workshops conducted in an electronics factory in China. It was found that a high performance team perceived stronger interrelatedness between key teamwork concepts than average teams did.  An area that has been less studied is the effect of age diversity on knowledge transfer in workplace, which roots from the retirement of baby boom generation in many mature organizations. Wang and Dong undertook a study on some basic questions in intergenerational knowledge transfer such as analysis framework and transfer mechanism from a sociological perspective.  

Despite the diversity of topics they all tend to address on how KM performance is related to business goals, how the effectiveness is evaluated and how organizational learning takes place,  one feature of all these papers is that they all have data to support their cases and cut across various countries and cultures.  I hope this special issue serves as a timely and updated reference for the KM, IC and OL professions.


Keywords: Action Research, administrative innovation, BA, bibliometric analysis, data, development projects, educational partnerships, Embrapa, embryonic KM strategy, enabling contexts, , formulaic KM strategy, group quality assurance, human resource management practices, IC value tree, implementation of knowledge , innovation diffusion, innovative teaching, intellectual capital, intellectual capital statement, KM strategy, KM strategy as social practice, know-how, knowledge management effectiveness, knowledge management, , knowledge-based view of organizations, KPI, link between KM and business strategy, Malaysian manufacturing firms , management fashion, metrics, organizational coaching, organizational concepts, organizational learning, practicum, process innovation, product innovation, reflective practitioner, statistics, sustainable, taxonomy, the SET KM model, transfer of training, value added quality management processes, workplace development,


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Journal Issue

Volume 15 Issue 2 / Jul 2017  pp59‑146

Editor: John Dumay

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Keywords: SECI model, digital transformation, folk song, knowledge conversion, Knowledge Sharing, Cross-Functional, NPD Teams, New Product Development, Knowledge Management, Information and Communication Technology, Construction Industry, Competitiveness, Learning, dynamic system, local context, MNE subsidiary, knowledge sharing barriers, educational management, educational institutions’ administrative processes, Classification Theory, Metadata, Statistics, Taxonomy


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