Inter-organisational knowledge transfer process model

Knowledge management (KM) is an emerging discipline (Ives, Torrey & Gordon, 1997) and characterised by four processes: generation, codification, transfer, and application (Alavi & Leidner, 2001). Completing the loop, knowledge transfer is regarded as a precursor to knowledge creation (Nonaka & Takeuchi, 1995) and thus forms an essential part of the knowledge management process. The understanding of how knowledge is transferred is very important for explaining the evolution and change in institutions, organisations, technology, and economy. However, knowledge transfer is often found to be laborious, time consuming, complicated, and difficult to understand (Huber, 2001; Szulanski, 2000). It has received negligible systematic attention (Huber, 2001; Szulanski, 2000), thus we know little about it (Huber, 2001). However, some literature, such as Davenport and Prusak (1998) and Shariq (1999), has attempted to address knowledge transfer within an organisation, but studies on inter-organisational knowledge transfer are still much neglected. An emergent view is that it may be beneficial for organisations if more research can be done to help them understand and, thus, to improve their inter-organisational knowledge transfer process. Therefore, this article aims to provide an overview of the inter-organisational knowledge transfer and its related literature and present a proposed inter-organisational knowledge transfer process model based on theoretical and empirical studies.

Knowledge management and the limits of knowledge codification

Purpose - The idea that knowledge needs to be codified is central to many claims that knowledge can be managed. However, there appear to be no empirical studies in the knowledge management context that examine the process of knowledge codification. This paper therefore seeks to explore codification as a knowledge management process. Design/methodology/approach - The paper draws on findings from research conducted around a knowledge management project in a section of the UK Post Office, using a methodology of participant-observation. Data were collected through observations of project meetings, correspondence between project participants, and individual interviews. Findings - The principal findings about the nature of knowledge codification are first, that the process of knowledge codification also involves the process of defining the codes needed to codify knowledge, and second, that people who participate in the construction of these codes are able to interpret and use the codes more similarly. From this it can be seen that the ability of people to decodify codes similarly places restrictions on the transferability of knowledge between them. Research limitations/implications - The paper therefore argues that a new conceptual approach is needed for the role of knowledge codification in knowledge management that emphasizes the importance of knowledge decodification. Such an approach would start with one's ability to decodify rather than codify knowledge as a prerequisite for knowledge management. Originality/value - The paper provides a conceptual basis for explaining limitations to the management and transferability of knowledge. © Emerald Group Publishing Limited.

Knowledge management in knowledge intensive service networks:a strategic management approach

Purpose – The main purpose of this paper is to analyze knowledge management in service networks. It analyzes the knowledge management process and identifies related challenges. The authors take a strategic management approach instead of a more technology-oriented approach, since it is believed that managerial problems still remain after technological problems are solved. Design/methodology/approach – The paper explores the literature on the topic of knowledge management as well as the resource (or knowledge) based view of the firm. It offers conceptual insights and provides possible solutions for knowledge management problems. Findings – The paper discusses several possible solutions for managing knowledge processes in knowledge-intensive service networks. Solutions for knowledge identification/generation, knowledge application, knowledge combination/transfer and supporting the evolution of tacit network knowledge include personal and technological aspects, as well as organizational and cultural elements. Practical implications – In a complex environment, knowledge management and network management become crucial for business success. It is the task of network management to establish routines, and to build and regularly refresh meta-knowledge about the competencies and abilities that exist within the network. It is suggested that each network partner should be rated according to the contribution to the network knowledge base. Based on this rating, a particular network partner is a member of a certain knowledge club, meaning that the partner has access to a particular level of network knowledge. Such an established routine provides strong incentives to add knowledge to the network's knowledge base Originality/value – This paper is a first attempt to outline the problems of knowledge management in knowledge-intensive service networks and, by so doing, to introduce strategic management reasoning to the discussion.

Bridging the gap from the general to the specific by linking knowledge management to business process

A phenomenon common to almost all fields is that there is a gap between theory and practical implementation. However, this is a particular problem in knowledge management, where much of the literature consists of general principles written in the context of a ‘knowledge world’ that has few, if any, references to how to carry out knowledge management in organisations. In this chapter, we put forward the view that the best way to bridge this gap between general principles and the specific issues facing a given organisation is to link knowledge management to the organisation’s business processes. After briefly reviewing, and rejecting alternative ways in which this gap might be bridged, the chapter goes on to explain the justification for, and the potential benefits and snags of, linking knowledge management to business processes. Successful and unsuccessful examples are presented. We concentrate especially on the issues of establishing what knowledge is relevant to an organisation at present, the need for organisational learning to cope with the inevitable change, and the additional problems posed by the growing internationalisation of operations. We conclude that linking knowledge management in terms of business processes is the best route for organisations to follow, but that it is not the answer to all knowledge management problems, especially where different cultures and/or cultural change are involved.

Using decision support systems to facilitate the social process of knowledge management

The social processes involved in engaging small groups of 3-15 managers in their sharing, organising, acquiring, creating and using knowledge can be supported with software and facilitator assistance. This paper introduces three such systems that we have used as facilitators to support groups of managers in their social process of decision-making by managing knowledge during face-to-face meetings. The systems include Compendium, Group Explorer (with Decision Explorer) and V*I*S*A. We review these systems for group knowledge management where the aim is for better decision-making, and discuss the principles of deploying each in a group meeting. © 2006 Operational Research Society Ltd. All rights reserved.

A process view of knowledge management:it ain't want you do, it's the way that you do it

Knowledge management needs to consider the three related elements of people, processes and technology. Much existing work has concentrated on either people or technology, often to the exclusion of the other two elements. Yet without thinking about process ? the way people, organisations and even technology actually do things ? any implementation of a knowledge management initiative is at best risky, and at worst doomed to failure. This paper looks at various ways in which a process view has appeared, expl icitly or implicitly, in knowledge management research and practice so far, and reflects on how more 'thinking about process' might improve knowledge management in the future. Consistent with this overall viewpoint, the issues generally centre less on wha t a process view would suggest should be done, but rather on the way that it would be implemented in practice.

A process view of knowledge management:it ain't what you do, it's the way that you do it

Knowledge management needs to consider the three related elements of people, processes and technology. Much existing work has concentrated on either people or technology, often to the exclusion of the other two elements. Yet without thinking about process – the way people, organisations and even technology actually do things – any implementation of a knowledge management initiative is at best risky, and at worst doomed to failure. This presentation looks at various ways in which a process view has appeared, explicitly or implicitly, in knowledge management research and practice so far, and reflects on how more “thinking about process” might improve knowledge management in the future. Consistent with the presentation’s own overall viewpoint, the issues generally centre not on what a process view would suggest should be done, but on the way that it would be implemented in practice.

Reliability modelling and verification of manufacturing processes based on process knowledge management

Reliability modelling and verification is indispensable in modern manufacturing, especially for product development risk reduction. Based on the discussion of the deficiencies of traditional reliability modelling methods for process reliability, a novel modelling method is presented herein that draws upon a knowledge network of process scenarios based on the analytic network process (ANP). An integration framework of manufacturing process reliability and product quality is presented together with a product development and reliability verification process. According to the roles of key characteristics (KCs) in manufacturing processes, KCs are organised into four clusters, that is, product KCs, material KCs, operation KCs and equipment KCs, which represent the process knowledge network of manufacturing processes. A mathematical model and algorithm is developed for calculating the reliability requirements of KCs with respect to different manufacturing process scenarios. A case study on valve-sleeve component manufacturing is provided as an application example of the new reliability modelling and verification procedure. This methodology is applied in the valve-sleeve component manufacturing processes to manage and deploy production resources.

User-centred ontology learning for knowledge management

Automatic ontology building is a vital issue in many fields where they are currently built manually. This paper presents a user-centred methodology for ontology construction based on the use of Machine Learning and Natural Language Processing. In our approach, the user selects a corpus of texts and sketches a preliminary ontology (or selects an existing one) for a domain with a preliminary vocabulary associated to the elements in the ontology (lexicalisations). Examples of sentences involving such lexicalisation (e.g. ISA relation) in the corpus are automatically retrieved by the system. Retrieved examples are validated by the user and used by an adaptive Information Extraction system to generate patterns that discover other lexicalisations of the same objects in the ontology, possibly identifying new concepts or relations. New instances are added to the existing ontology or used to tune it. This process is repeated until a satisfactory ontology is obtained. The methodology largely automates the ontology construction process and the output is an ontology with an associated trained leaner to be used for further ontology modifications.

Knowledge acquisition for knowledge management: position paper

With this paper, we propose a set of techniques to largely automate the process of KA, by using technologies based on Information Extraction (IE) , Information Retrieval and Natural Language Processing. We aim to reduce all the impeding factors mention above and thereby contribute to the wider utility of the knowledge management tools. In particular we intend to reduce the introspection of knowledge engineers or the extended elicitations of knowledge from experts by extensive textual analysis using a variety of methods and tools, as texts are largely available and in them - we believe - lies most of an organization's memory.

Knowledge management applied to enterprise risk management

Risk and knowledge are two concepts and components of business management which have so far been studied almost independently. This is especially true where risk management (RM) is conceived mainly in financial terms, as for example, in the financial institutions sector. Financial institutions are affected by internal and external changes with the consequent accommodation to new business models, new regulations and new global competition that includes new big players. These changes induce financial institutions to develop different methodologies for managing risk, such as the enterprise risk management (ERM) approach, in order to adopt a holistic view of risk management and, consequently, to deal with different types of risk, levels of risk appetite, and policies in risk management. However, the methodologies for analysing risk do not explicitly include knowledge management (KM). This research examines the potential relationships between KM and two RM concepts: perceived quality of risk control and perceived value of ERM. To fulfill the objective of identifying how KM concepts can have a positive influence on some RM concepts, a literature review of KM and its processes and RM and its processes was performed. From this literature review eight hypotheses were analysed using a classification into people, process and technology variables. The data for this research was gathered from a survey applied to risk management employees in financial institutions and 121 answers were analysed. The analysis of the data was based on multivariate techniques, more specifically stepwise regression analysis. The results showed that the perceived quality of risk control is significantly associated with the variables: perceived quality of risk knowledge sharing, perceived quality of communication among people, web channel functionality, and risk management information system functionality. However, the relationships of the KM variables to the perceived value of ERM are not identified because of the low performance of the models describing these relationships. The analysis reveals important insights into the potential KM support to RM such as: the better adoption of KM people and technology actions, the better the perceived quality of risk control. Equally, the results suggest that the quality of risk control and the benefits of ERM follow different patterns given that there is no correlation between both concepts and the distinct influence of the KM variables in each concept. The ERM scenario is different from that of risk control because ERM, as an answer to RM failures and adaptation to new regulation in financial institutions, has led organizations to adopt new processes, technologies, and governance models. Thus, the search for factors influencing the perceived value of ERM implementation needs additional analysis because what is improved in RM processes individually is not having the same effect on the perceived value of ERM. Based on these model results and the literature review the basis of the ERKMAS (Enterprise Risk Knowledge Management System) is presented.

Using a simulation model for knowledge elicitation and knowledge management

The work reported in this paper is part of a project simulating maintenance operations in an automotive engine production facility. The decisions made by the people in charge of these operations form a crucial element of this simulation. Eliciting this knowledge is problematic. One approach is to use the simulation model as part of the knowledge elicitation process. This paper reports on the experience so far with using a simulation model to support knowledge management in this way. Issues are discussed regarding the data available, the use of the model, and the elicitation process itself. © 2004 Elsevier B.V. All rights reserved.

Knowledge management sans frontières

Knowledge management is a topic that crosses borders of various kinds, such as those between departments, between organisations or between countries. In this paper we will consider various issues relating to knowledge management, in the context where more than one department/organisation/country is involved. To do this, we place an emphasis on knowledge management as a process, rather than as an organisational system or, worse, as a piece of technology. This process involves trust, negotiation—and indeed some technological support. In this paper we wish to introduce the concept of ‘triangles of trust’, and to focus on where ‘the top meets the bottom’ in terms of knowledge management and organisational learning. Partial examples will be offered in support of our views, but no full and complete examples—knowledge management simply is not well enough understood or documented for that yet. Our overall conclusion is that there is no one best way to “do” knowledge management, but there are principles that ought to be applied.

Proposing a systems vision of knowledge management in emergency care

This paper makes a case for taking a systems view of knowledge management within health-care provision, concentrating on the emergency care process in the UK National Health Service. It draws upon research in two casestudy organizations (a hospital and an ambulance service). The case-study organizations appear to be approaching knowledge (and information) management in a somewhat fragmented way. They are trying to think more holistically, but (perhaps) because of the ways their organizations and their work are structured, they cannot ‘see’ the whole of the care process. The paper explores the complexity of knowledge management in emergency health care and draws the distinction for knowledge management between managing local and operational knowledge, and global and clinical knowledge.