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.

An investigation of SMEs’ inter-organisational knowledge transfer needs in Internet marketing

Internet marketing, as a key area of e-commerce, plays an important role in SMEs’ e-commerce success. It is the use of Internet technologies in facilitating and supporting marketing activities. Its implementation and success require expert knowledge and extensive experience. SMEs admit that they are willing to embrace Internet marketing to enhance their business competitiveness, but do not know where to start and suffer from a lack of guidance. Evidence suggests that Internet marketing analysis is one of the most needed areas of training in e-commerce for SMEs. It is therefore evident that SMEs need to acquire Internet marketing knowledge from external sources. However, the majority of the literature fails to study what specific knowledge they need and from whom they should acquire the knowledge. This paper has addressed these issues through a questionnaire survey of UK SMEs in the service sector. It identifies SMEs’ specific transfer needs for Internet marketing knowledge, and discusses strategic issues for improving SMEs’ effectiveness of leveraging knowledge.

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.

Sourcing knowledge for innovation:the international dimension

Drawing knowledge from external sources in the UK, or internationally, has become increasingly important to small and medium-sized firms (SMEs). SMEs cannot generate all they need to know to develop new products and processes within their own companies, they need to look elsewhere for new ideas and expertise. This practice is known as knowledge sourcing. This report provides a detailed review of patterns of knowledge sourcing, and the key factors influencing these patterns, particularly from a small business perspective. We present key findings from a survey of 393 UK companies and analyse the results. We also highlight case studies of UK SMEs that work closely with overseas partners and agents to widen their own knowledge.

Expert systems for fault analysis

The initial aim of this research was to investigate the application of expert Systems, or Knowledge Base Systems technology to the automated synthesis of Hazard and Operability Studies. Due to the generic nature of Fault Analysis problems and the way in which Knowledge Base Systems work, this goal has evolved into a consideration of automated support for Fault Analysis in general, covering HAZOP, Fault Tree Analysis, FMEA and Fault Diagnosis in the Process Industries. This thesis described a proposed architecture for such an Expert System. The purpose of the System is to produce a descriptive model of faults and fault propagation from a description of the physical structure of the plant. From these descriptive models, the desired Fault Analysis may be produced. The way in which this is done reflects the complexity of the problem which, in principle, encompasses the whole of the discipline of Process Engineering. An attempt is made to incorporate the perceived method that an expert uses to solve the problem; keywords, heuristics and guidelines from techniques such as HAZOP and Fault Tree Synthesis are used. In a truly Expert System, the performance of the system is strongly dependent on the high quality of the knowledge that is incorporated. This expert knowledge takes the form of heuristics or rules of thumb which are used in problem solving. This research has shown that, for the application of fault analysis heuristics, it is necessary to have a representation of the details of fault propagation within a process. This helps to ensure the robustness of the system - a gradual rather than abrupt degradation at the boundaries of the domain knowledge.

Developing an intervention to equip nurses for acute life threatening events (ALTEs) in hospital:a phenomenological approach to healthcare research

Objectives: To understand staff's experiences of acute life threatening events (ALTEs) in a pediatric hospital setting. These data will inform an intervention to equip nurses with clinical and emotional skills for dealing with ALTEs. Method: A mixed design was used in the broader research program; this paper focuses on phenomenon-focused interviews analyzed using interpretative phenomenological analysis (IPA). Results: Emerging themes included staff's relationships with patients and the impact of personhood on their ability to perform competently in an emergency. More experienced nurses described "automatic" competence generated through increased exposure to ALTEs and were able to recognize "fumbling and shaking" as a normal stress response. Designating a role was significant to staff experience of effectiveness. Key to nurses' learning experience was reflection and identifying experiences as "teachable moments." Findings were considered alongside existing theories of self-efficacy, reflective thought, and advocacy inquiry to create an experiential learning intervention involving a series of clinical and role-related scenarios. Conclusion: The phenomenological work facilitated an in-depth reading of experience. It accentuated the importance of exposure to ALTEs giving nurses experiential knowledge to prepare them for the impact of these events. Challenges included bracketing the personhood of child patients, shifting focus to clinical tasks during the pressured demands of managing an ALTE, normalizing the physiological stress response, and the need for a forum and structure for reflection and learning. An intervention will be designed to provide experiential learning and encourage nurses to realize and benefit from their embodied knowledge.

The application of knowledge based expert systems to mechanical engineering design

Investigation of the different approaches used by Expert Systems researchers to solve problems in the domain of Mechanical Design and Expert Systems was carried out. The techniques used for conventional formal logic programming were compared with those used when applying Expert Systems concepts. A literature survey of design processes was also conducted with a view to adopting a suitable model of the design process. A model, comprising a variation on two established ones, was developed and applied to a problem within what are described as class 3 design tasks. The research explored the application of these concepts to Mechanical Engineering Design problems and their implementation on a microcomputer using an Expert System building tool. It was necessary to explore the use of Expert Systems in this manner so as to bridge the gap between their use as a control structure and for detailed analytical design. The former application is well researched into and this thesis discusses the latter. Some Expert System building tools available to the author at the beginning of his work were evaluated specifically for their suitability for Mechanical Engineering design problems. Microsynics was found to be the most suitable on which to implement a design problem because of its simple but powerful Semantic Net Knowledge Representation structure and the ability to use other types of representation schemes. Two major implementations were carried out. The first involved a design program for a Helical compression spring and the second a gearpair system design. Two concepts were proposed in the thesis for the modelling and implementation of design systems involving many equations. The method proposed enables equation manipulation and analysis using a combination of frames, semantic nets and production rules. The use of semantic nets for purposes other than for psychology and natural language interpretation, is quite new and represents one of the major contributions to knowledge by the author. The development of a purpose built shell program for this type of design problems was recommended as an extension of the research. Microsynics may usefully be used as a platform for this development.

AKTive Food:semantic web based knowledge conduits for the organic food industry

We present a vision and a proposal for using Semantic Web technologies in the organic food industry. This is a very knowledge intensive industry at every step from the producer, to the caterer or restauranteur, through to the consumer. There is a crucial need for a concept of environmental audit which would allow the various stake holders to know the full environmental impact of their economic choices. This is a di?erent and parallel form of knowledge to that of price. Semantic Web technologies can be used e?ectively for the calculation and transfer of this type of knowledge (together with other forms of multimedia data) which could contribute considerably to the commercial and educational impact of the organic food industry. We outline how this could be achieved as our essential ob jective is to show how advanced technologies could be used to both reduce ecological impact and increase public awareness.

Knowledge representation with ontologies:the present and future

Recently, we have seen an explosion of interest in ontologies as artifacts to represent human knowledge and as critical components in knowledge management, the semantic Web, business-to-business applications, and several other application areas. Various research communities commonly assume that ontologies are the appropriate modeling structure for representing knowledge. However, little discussion has occurred regarding the actual range of knowledge an ontology can successfully represent.

Block GTM: Incorporating prior knowledge of covariance structure in data visualisation

Visualising data for exploratory analysis is a big challenge in scientific and engineering domains where there is a need to gain insight into the structure and distribution of the data. Typically, visualisation methods like principal component analysis and multi-dimensional scaling are used, but it is difficult to incorporate prior knowledge about structure of the data into the analysis. In this technical report we discuss a complementary approach based on an extension of a well known non-linear probabilistic model, the Generative Topographic Mapping. We show that by including prior information of the covariance structure into the model, we are able to improve both the data visualisation and the model fit.

The National Literacy Strategy and knowledge about language in the English school curriculum

In “The English Patient: English Grammar and teaching in the Twentieth Century”, Hudson and Walmsley (2005) contend that the decline of grammar in schools was linked to a similar decline in English universities, where no serious research or teaching on English grammar took place. This article argues that such a decline was due not only to a lack of research, but also because it suited educational policies of the time. It applies Bernstein’s theory of pedagogic discourse (1990 & 1996) to the case study of the debate surrounding the introduction of a national curriculum in English in England in the late 1980s and the National Literacy Strategy in the 1990s, to demonstrate the links between academic theory and educational policy.

The unique complexity of social phenomena and the uses of social science knowledge

The assertion about the peculiarly intricate and complex character of social phenomena has, in much of social discourse, a virtually uncontested tradition. A significant part of the premise about the complexity of social phenomena is the conviction that it complicates, perhaps even inhibits the development and application of social scientific knowledge. Our paper explores the origins, the basis and the consequences of this assertion and asks in particular whether the classic complexity assertion still deserves to be invoked in analyses that ask about the production and the utilization of social scientific knowledge in modern society. We refer to one of the most prominent and politically influential social scientific theories, John Maynard Keynes' economic theory as an illustration. We conclude that, the practical value of social scientific knowledge is not necessarily dependent on a faithful, in the sense of complete, representation of (complex) social reality. Practical knowledge is context sensitive if not project bound. Social scientific knowledge that wants to optimize its practicality has to attend and attach itself to elements of practical social situations that can be altered or are actionable by relevant actors. This chapter represents an effort to re-examine the relation between social reality, social scientific knowledge and its practical application. There is a widely accepted view about the potential social utility of social scientific knowledge that invokes the peculiar complexity of social reality as an impediment to good theoretical comprehension and hence to its applicability.

Outlier detection with partial information:Application to emergency mapping

This paper, addresses the problem of novelty detection in the case that the observed data is a mixture of a known 'background' process contaminated with an unknown other process, which generates the outliers, or novel observations. The framework we describe here is quite general, employing univariate classification with incomplete information, based on knowledge of the distribution (the 'probability density function', 'pdf') of the data generated by the 'background' process. The relative proportion of this 'background' component (the 'prior' 'background' 'probability), the 'pdf' and the 'prior' probabilities of all other components are all assumed unknown. The main contribution is a new classification scheme that identifies the maximum proportion of observed data following the known 'background' distribution. The method exploits the Kolmogorov-Smirnov test to estimate the proportions, and afterwards data are Bayes optimally separated. Results, demonstrated with synthetic data, show that this approach can produce more reliable results than a standard novelty detection scheme. The classification algorithm is then applied to the problem of identifying outliers in the SIC2004 data set, in order to detect the radioactive release simulated in the 'oker' data set. We propose this method as a reliable means of novelty detection in the emergency situation which can also be used to identify outliers prior to the application of a more general automatic mapping algorithm. © Springer-Verlag 2007.

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.

Neuromarketing and the perceptions of knowledge

The emerging field of neuromarketing reveals that knowledge has plasticity. In other words, different stakeholders, marketing researchers and practitioners, perceive the development and application of neuromarketing knowledge in different ways. Having different perceptions of knowledge is not a new issue, but finding new interconnections between those perceptions is beneficial to knowledge creation and diffusion. The research-practice gap in neuromarketing is briefly discussed and then resolved through the contribution of this commentary, the proposal of a novel Neuromarketing Research Model. The Model interconnects basic research reporting, applied research reporting, media reporting and power processes.