32 resultados para knowledge strategies

em Aston University Research Archive


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Inter-organisational knowledge transfer is very important for SMEs. However, compared to knowledge transfer within an organisation, its ‘boundary paradox’ makes its process more complicated and difficult to understand. In order to solve the ‘paradox’, inter-organisational knowledge transfer strategies need to be developed for SMEs. Through a review of the literature on knowledge transfer, this paper proposes an inter-organisational knowledge transfer process model that contains four stages (initiation, selection, interaction and conversion). It classifies three situations in which an SME exchanges knowledge with a customer (whether a larger company or an SME). It then applies a coordinating mechanism to analyse knowledge transfer strategies for the SME when it is a knowledgegiving firm and knowledge-receiving firm respectively, in the different stages of each situation.

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External partnerships play an important role in firms’ acquisition of the knowledge inputs to innovation. Such partnerships may be interactive – involving exploration and mutual learning by both parties – or non-interactive – involving exploitative activity and learning by only one party. Examples of non-interactive partnerships are copying or imitation. Here, we consider how firms’ innovation objectives influence their choice of interactive and/or non-interactive connections. We conduct a comparative analysis for the economies of Spain and the UK, which have contrasting innovation eco-systems and regulation burdens.

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Knowledge maintenance is a major challenge for both knowledge management and the Semantic Web. Operating over the Semantic Web, there will be a network of collaborating agents, each with their own ontologies or knowledge bases. Change in the knowledge state of one agent may need to be propagated across a number of agents and their associated ontologies. The challenge is to decide how to propagate a change of knowledge state. The effects of a change in knowledge state cannot be known in advance, and so an agent cannot know who should be informed unless it adopts a simple ‘tell everyone – everything’ strategy. This situation is highly reminiscent of the classic Frame Problem in AI. We argue that for agent-based technologies to succeed, far greater attention must be given to creating an appropriate model for knowledge update. In a closed system, simple strategies are possible (e.g. ‘sleeping dog’ or ‘cheap test’ or even complete checking). However, in an open system where cause and effect are unpredictable, a coherent cost-benefit based model of agent interaction is essential. Otherwise, the effectiveness of every act of knowledge update/maintenance is brought into question.

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In a series of studies, I investigated the developmental changes in children’s inductive reasoning strategy, methodological manipulations affecting the trajectory, and driving mechanisms behind the development of category induction. I systematically controlled the nature of the stimuli used, and employed a triad paradigm in which perceptual cues were directly pitted against category membership, to explore under which circumstances children used perceptual or category induction. My induction tasks were designed for children aged 3-9 years old using biologically plausible novel items. In Study 1, I tested 264 children. Using a wide age range allowed me to systematically investigate the developmental trajectory of induction. I also created two degrees of perceptual distractor – high and low – and explored whether the degree of perceptual similarity between target and test items altered children’s strategy preference. A further 52 children were tested in Study 2, to examine whether children showing a perceptual-bias were in fact basing their choice on maturation categories. A gradual transition was observed from perceptual to category induction. However, this transition could not be due to the inability to inhibit high perceptual distractors as children of all ages were equally distracted. Children were also not basing their strategy choices on maturation categories. In Study 3, I investigated category structure (featural vs. relational category rules) and domain (natural vs. artefact) on inductive preference. I tested 403 children. Each child was assigned to either the featural or relational condition, and completed both a natural kind and an artefact task. A further 98 children were tested in Study 4, on the effect of using stimuli labels during the tasks. I observed the same gradual transition from perceptual to category induction preference in Studies 3 and 4. This pattern was stable across domains, but children developed a category-bias one year later for relational categories, arguably due to the greater demands on executive function (EF) posed by these stimuli. Children who received labels during the task made significantly more category choices than those who did not receive labels, possibly due to priming effects. Having investigated influences affecting the developmental trajectory, I continued by exploring the driving mechanism behind the development of category induction. In Study 5, I tested 60 children on a battery of EF tasks as well as my induction task. None of the EF tasks were able to predict inductive variance, therefore EF development is unlikely to be the driving factor behind the transition. Finally in Study 6, I divided 252 children into either a comparison group or an intervention group. The intervention group took part in an interactive educational session at Twycross Zoo about animal adaptations. Both groups took part in four induction tasks, two before and two a week after the zoo visits. There was a significant increase in the number of category choices made in the intervention condition after the zoo visit, a result not observed in the comparison condition. This highlights the role of knowledge in supporting the transition from perceptual to category induction. I suggest that EF development may support induction development, but the driving mechanism behind the transition is an accumulation of knowledge, and an appreciation for the importance of category membership.

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The paper illustrates the role of world knowledge in comprehending and translating texts. A short news item, which displays world knowledge fairly implicitly in condensed lexical forms, was translated by students from English into German. It is shown that their translation strategies changed from a first draft which was rather close to the surface structure of the source text to a final version which took situational aspects, texttypological conventions and the different background knowledge of the respective addressees into account. Decisions on how much world knowledge has to be made explicit in the target text, however, must be based on the relevance principle. Consequences for teaching and for the notions of semantic knowledge and world knowledge are discussed.

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This chapter begins by reviewing the history of software engineering as a profession, especially the so-called software crisis and responses to it, to help focus on what it is that software engineers do. This leads into a discussion of the areas in software engineering that are problematic as a basis for considering knowledge management issues. Some of the previous work on knowledge management in software engineering is then examined, much of it not actually going under a knowledge management title, but rather “learning” or “expertise”. The chapter goes on to consider the potential for knowledge management in software engineering and the different types of knowledge management solutions and strategies that might be adopted, and it touches on the crucial importance of cultural issues. It concludes with a list of challenges that knowledge management in software engineering needs to address.

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The performance of most operations systems is significantly affected by the interaction of human decision-makers. A methodology, based on the use of visual interactive simulation (VIS) and artificial intelligence (AI), is described that aims to identify and improve human decision-making in operations systems. The methodology, known as 'knowledge-based improvement' (KBI), elicits knowledge from a decision-maker via a VIS and then uses AI methods to represent decision-making. By linking the VIS and AI representation, it is possible to predict the performance of the operations system under different decision-making strategies and to search for improved strategies. The KBI methodology is applied to the decision-making surrounding unplanned maintenance operations at a Ford Motor Company engine assembly plant.

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Purpose – The purpose of this paper is to analyze the way in which the knowledge competitiveness of regions is measured and further introduces the World Knowledge Competitiveness Index (WKCI) benchmarking tool. Design/methodology/approach – The methodology consists of an econometric analysis of key indicators relating to the concept of knowledge competitiveness for 125 regions from across the globe consisting of 55 representatives from North America, 45 from Europe and 25 from Asia and Oceania. Findings – The key to winning the super competitive race in the knowledge-based economy is investment in the future: research and development, and education and training. It is found that the majority of the high-performing regional economies in the USA have a knowledge competitive edge over their counterparts in Europe and Asia. Research limitations/implications – To an extent, the research is limited by the availability of comparable indicators and metrics at the regional level that extend across the globe. Whilst comparative data are often accessible at the national level, regional data sources remain underdeveloped. Practical implications – The WKCI has become internationally recognized as an important instrument for economic development policymakers and regional investment promotion agents as they create and refine their strategies and targets. In particular, it has provided a benchmark that allows regions to compare their knowledge competitiveness with other regions for around the world and not only their own nation or continent. Originality/value – The WKCI is the first composite and relative measure of the knowledge competitiveness of the globe's best performing regions.

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Purpose - Managers at the company attempt to implement a knowledge management information system in an attempt to avoid loss of expertise while improving control and efficiency. The paper seeks to explore the implications of the technological solution to employees within the company. Design/methodology/approach - The paper reports qualitative research conducted in a single organization. Evidence is presented in the form of interview extracts. Findings - The case section of the paper presents the accounts of organizational participants. The accounts reveal the workers' reactions to the technology-based system and something of their strategies of resistance to the system. These accounts also provide glimpses of the identity construction engaged in by these knowledge workers. The setting for the research is in a knowledge-intensive primary industry. Research was conducted through observation and interviews. Research limitations/implications - The issues identified are explored in a single case-study setting. Future research could look at the relevance of the findings to other settings. Practical implications - The case evidence presented indicates some of the complexity of implementation of information systems in organizations. This could certainly be seen as more evidence of the uncertainty associated with organizational change and of the need for managers not to expect an easy adoption of intrusive IT solutions. Originality/value - This paper adds empirical insight to a largely conceptual literature. © Emerald Group Publishing Limited.

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Purpose: This paper sets out to contribute to the advancement of knowledge, particularly with regard to the processes of implementation and the role of managers engaged in such high commitment strategies and work practices. Design/methodology/approach: This study is part of a research project investigating the extent to which employee involvement predicts job performance (as well as job satisfaction, wellbeing and organisational commitment) in the NHS, using both quantitative and qualitative methods. The main focus of this paper is to present evidence from four of the 20 case studies to show the barriers to implementing employee involvement as well as highlighting the techniques and practices that have proven to be most successful. Findings: Employee involvement is used successfully by management and has enabled frontline staff to contribute their knowledge to their work. Research limitations/implications: The ethical issues of confidentiality and anonymity permeated the research process throughout. Practical implications: The link between "high commitment" strategies and organisational performance is of great interest to academics and practitioners alike. One of these "high commitment" strategies, namely employee involvement, has been an important HR strategy for the NHS in the UK. Originality/value: Other organisations can learn from the findings by implementing the successful parts. © Emerald Group Publishing Limited.

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Enterprise Risk Management (ERM) and Knowledge Management (KM) both encompass top-down and bottom-up approaches developing and embedding risk knowledge concepts and processes in strategy, policies, risk appetite definition, the decision-making process and business processes. The capacity to transfer risk knowledge affects all stakeholders and understanding of the risk knowledge about the enterprise's value is a key requirement in order to identify protection strategies for business sustainability. There are various factors that affect this capacity for transferring and understanding. Previous work has established that there is a difference between the influence of KM variables on Risk Control and on the perceived value of ERM. Communication among groups appears as a significant variable in improving Risk Control but only as a weak factor in improving the perceived value of ERM. However, the ERM mandate requires for its implementation a clear understanding, of risk management (RM) policies, actions and results, and the use of the integral view of RM as a governance and compliance program to support the value driven management of the organization. Furthermore, ERM implementation demands better capabilities for unification of the criteria of risk analysis, alignment of policies and protection guidelines across the organization. These capabilities can be affected by risk knowledge sharing between the RM group and the Board of Directors and other executives in the organization. This research presents an exploratory analysis of risk knowledge transfer variables used in risk management practice. A survey to risk management executives from 65 firms in various industries was undertaken and 108 answers were analyzed. Potential relationships among the variables are investigated using descriptive statistics and multivariate statistical models. The level of understanding of risk management policies and reports by the board is related to the quality of the flow of communication in the firm and perceived level of integration of the risk policy in the business processes.

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Retrospective clinical data presents many challenges for data mining and machine learning. The transcription of patient records from paper charts and subsequent manipulation of data often results in high volumes of noise as well as a loss of other important information. In addition, such datasets often fail to represent expert medical knowledge and reasoning in any explicit manner. In this research we describe applying data mining methods to retrospective clinical data to build a prediction model for asthma exacerbation severity for pediatric patients in the emergency department. Difficulties in building such a model forced us to investigate alternative strategies for analyzing and processing retrospective data. This paper describes this process together with an approach to mining retrospective clinical data by incorporating formalized external expert knowledge (secondary knowledge sources) into the classification task. This knowledge is used to partition the data into a number of coherent sets, where each set is explicitly described in terms of the secondary knowledge source. Instances from each set are then classified in a manner appropriate for the characteristics of the particular set. We present our methodology and outline a set of experiential results that demonstrate some advantages and some limitations of our approach. © 2008 Springer-Verlag Berlin Heidelberg.

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The thesis begins with a conceptual model of the way that language diversity affects the strategies, organisation and subsidiary control policies of multinational companies. The model is based solely on the researcher'’ personal experience of working in a variety of international management roles, but in Chapter 2 a wide-ranging review of related academic literature finds evidence to support the key ideas. The model is developed as a series of propositions which are tested in a comparative case study, refined and then re-tested in a global survey of multinational subsidiaries. The principal findings of the empirical phases of the thesis endorse the main tenets of the model: - That language difference between parent and subsidiary will impair communication, create mistrust and impede relationship development. - That subsequently the feelings of uncertainty, suspicion and mistrust will influence the decisions taken by the parent company. - They will have heightened sensitivity to language issues and will implement policies to manage language differences. - They will adopt low-risk strategies in host countries where they are concerned about language difference. - They will use organisational and manpower strategies to minimise the consequences and risks of the communications problems with the subsidiary. - As a consequence the level of integration and knowledge flow between parent and subsidiary will be curtailed. - They will adopt styles of control that depend least on their ability to communicate with their subsidiary. Although there is adequate support for all of the above conclusions, on some key points the evidence of the Case Studies and Survey is contradictory. The thesis, therefore, closes with an agenda for further research that would address these inconsistencies.

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This research project focused upon the design strategies adopted by expert and novice designers. It was based upon a desire to compare the design problem solving strategies of novices, in this case key stage three pupils studying technolgy within the United Kingdom National Curriculum, with designers who could be considered to have developed expertise. The findings helped to provide insights into potential teaching strategies to suit novice designers. Verbal protocols were made as samples of expert and novice designers solved a design problem and talked aloud as they worked. The verbalisations were recorded on video tape. The protocols were transcribed and segmented, with each segment being assigned to a predetermined coding system which represented a model of design problem solving. The results of the encoding were analysed and consideration was also given to the general design strategy and heuristics used by the expert and novice designers. The drawings and models produced during the generation of the protocols were also analysed and considered. A number of significant differences between the problem solving strategies adopted by the expert and novice designers were identified. First of all, differences were observed in the way expert and novice designers used the problem statement and solution validation during the process. Differences were also identified in the way holistic solutions were generated near the start of the process, and also in the cycles of exploration and the processes of integration. The way design and technological knowledge was used provided further insights into the differences between experts and novices, as did the role of drawing and modelling during the process. In more general terms, differences were identified in the heuristics and overall design strategies adopted by the expert and novice designers. The above findings provided a basis for discussing teaching strategies appropriate for novice designers. Finally, opportunities for future research were discussed.

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This thesis is organised into three parts. In Part 1 relevant literature is reviewed and three critical components in the development of a cognitive approach to instruction are identified. These three components are considered to be the structure of the subject-matter, the learner's cognitive structures, and the learner's cognitive strategies which act as control and transfer devices between the instructional materials and the learner's cognitive structures. Six experiments are described in Part 2 which is divided into two methodologically distinct units. The three experiments of Unit 1 examined how learning from materials constructed from concept name by concept attribute matrices is influenced by learner or experimenter controlled sequence and organisation. The results suggested that the relationships between input organisation, output organisation and recall are complex and highlighted the importance of investigating organisational strategies at both acquisition and recall. The role of subjects previously acquired knowledge and skills in relation to the instructional material was considered to be an important factor. The three experiments of Unit 2 utilised a "diagramming relationships methodology" which was devised as one means of investigating the processes by which new information is assimilated into an individual's cognitive structure. The methodology was found to be useful in identifying cognitive strategies related to successful task performance. The results suggested that errors could be minimised and comprehension improved on the diagramming relationships task by instructing subjects in ways which induced successful processing operations. Part 3 of this thesis highlights salient issues raised by the experimental work within the framework outlined in Part 1 and discusses potential implications for future theoretical developments and research.