60 resultados para Knowledge-based development


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The World Knowledge Competitiveness Index 2002 is the first composite and relative measure of the knowledge economies of the globe's best performing regions. It represents an integrated and overall benchmark of the knowledge capacity, capability and sustainability of each region and the extent to which this knowledge is translated into economic value and transferred into the wealth of the citizens of each region. This publication has over 50 pages and covers the following sections: The Economics of Knowledge Competitiveness The Rankings - World Knowledge Competitiveness Index Human Capital Components Knowledge Capital Components Regional Economy Outputs Knowledge Sustainability Components Driving Knowledge-Based Growth

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In this book, Stehr and Grundmann outline the theoretical significance and practical importance of the growing stratum of experts, counsellors and advisors in contemporary society, and claim that the growing spectrum of knowledge-based occupations has led to the pluralisation of expertise. As decision makers in organizations and private citizens, for various reasons, increasingly seek advice from experts, the authors examine the nature of expert activity, and suggest that the role of experts needs to be distinguised from other roles such as professionals, scientists, or intellectuals. Experts, they argue, perform knowledge based activities that mediate between the context of knowledge creation and application. Existing approaches tend to restrict the role of the expert to scientists, or to conflate the roles of professionals with experts. In avoiding such restrictions, this book sets out a framework to understanding the growing role of expertise in a better way. Experts provides thought-provoking discussion that will be of interest to postgraduate students and academics working within the fields of social theory, knowledge, and consumption.

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Knowledge has been a subject of interest and inquiry for thousands of years since at least the time of the ancient Greeks, and no doubt even before that. “What is knowledge” continues to be an important topic of discussion in philosophy. More recently, interest in managing knowledge has grown in step with the perception that increasingly we live in a knowledge-based economy. Drucker (1969) is usually credited as being the first to popularize the knowledge-based economy concept by linking the importance of knowledge with rapid technological change in Drucker (1969). Karl Wiig coined the term knowledge management (hereafter KM) for a NATO seminar in 1986, and its popularity took off following the publication of Nonaka and Takeuchi’s book “The Knowledge Creating Company” (Nonaka & Takeuchi, 1995). Knowledge creation is in fact just one of many activities involved in KM. Others include sharing, retaining, refining, and using knowledge. There are many such lists of activities (Holsapple & Joshi, 2000; Probst, Raub, & Romhardt, 1999; Skyrme, 1999; Wiig, De Hoog, & Van der Spek, 1997). Both academic and practical interest in KM has continued to increase throughout the last decade. In this article, first the different types of knowledge are outlined, then comes a discussion of various routes by which knowledge management can be implemented, advocating a process-based route. An explanation follows of how people, processes, and technology need to fit together for effective KM, and some examples of this route in use are given. Finally, there is a look towards the future.

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This thesis examines the process of knowledge acquisition by Malaysian manufacturing firms through their involvement in international strategic alliances. The strategic alliances can be with or without equity involvement. Firms involved with a foreign partner with equity involvement are joint venture firms while non-equity involvement are firms that engaged in contractual agreements. Using empirical evidence from 65 international alliances gathered through a survey conducted in high-technology manufacturing sectors, several factors that influence the process of knowledge acquisition are examined. The factors are: learning capacity, experience, goals, active involvement and accessibility to the foreign knowledge. Censored regression analysis and ordered probit analysis are used to analyse the effects of these factors on knowledge acquisition and its determinant parts, and the effects of knowledge acquisition and its determinants on the performance of the alliances. A second questionnaire gathered evidence relating to the factors, which encouraged tacit knowledge transfer between the foreign and Malaysian partners in international alliances. The key findings of the study are: knowledge acquisition in international strategic alliances is influenced by five determining factors; learning capacity, experience, articulated goals, active involvement and accessibility; new technology knowledge, product development knowledge and manufacturing process knowledge are influenced differently by the determining factors; knowledge acquisition and its determinant factors have a significant impact on the firm’s performance; cultural differences tend to moderate the effect on the firm’s performance; acquiring tacit knowledge is not only influenced by the five determinant factors but also by other factors, such as dependency, accessibility, trust, manufacturing control, learning methods and organisational systems; Malaysian firms involved in joint ventures tend to acquire more knowledge than those involved in contractual agreements, but joint ventures also exhibit higher degrees of dependency than contractual agreements; and the presence of R&D activity in the Malaysian partner encourages knowledge acquisition, but the amount of R&D expenditure has no effect on knowledge acquisition.

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This study was concerned with the computer automation of land evaluation. This is a broad subject with many issues to be resolved, so the study concentrated on three key problems: knowledge based programming; the integration of spatial information from remote sensing and other sources; and the inclusion of socio-economic information into the land evaluation analysis. Land evaluation and land use planning were considered in the context of overseas projects in the developing world. Knowledge based systems were found to provide significant advantages over conventional programming techniques for some aspects of the land evaluation process. Declarative languages, in particular Prolog, were ideally suited to integration of social information which changes with every situation. Rule-based expert system shells were also found to be suitable for this role, including knowledge acquisition at the interview stage. All the expert system shells examined suffered from very limited constraints to problem size, but new products now overcome this. Inductive expert system shells were useful as a guide to knowledge gaps and possible relationships, but the number of examples required was unrealistic for typical land use planning situations. The accuracy of classified satellite imagery was significantly enhanced by integrating spatial information on soil distribution for Thailand data. Estimates of the rice producing area were substantially improved (30% change in area) by the addition of soil information. Image processing work on Mozambique showed that satellite remote sensing was a useful tool in stratifying vegetation cover at provincial level to identify key development areas, but its full utility could not be realised on typical planning projects, without treatment as part of a complete spatial information system.

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Component-based development (CBD) has become an important emerging topic in the software engineering field. It promises long-sought-after benefits such as increased software reuse, reduced development time to market and, hence, reduced software production cost. Despite the huge potential, the lack of reasoning support and development environment of component modeling and verification may hinder its development. Methods and tools that can support component model analysis are highly appreciated by industry. Such a tool support should be fully automated as well as efficient. At the same time, the reasoning tool should scale up well as it may need to handle hundreds or even thousands of components that a modern software system may have. Furthermore, a distributed environment that can effectively manage and compose components is also desirable. In this paper, we present an approach to the modeling and verification of a newly proposed component model using Semantic Web languages and their reasoning tools. We use the Web Ontology Language and the Semantic Web Rule Language to precisely capture the inter-relationships and constraints among the entities in a component model. Semantic Web reasoning tools are deployed to perform automated analysis support of the component models. Moreover, we also proposed a service-oriented architecture (SOA)-based semantic web environment for CBD. The adoption of Semantic Web services and SOA make our component environment more reusable, scalable, dynamic and adaptive.

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Lean is usually associated with the ‘operations’ of a manufacturing enterprise; however, there is a growing awareness that these principles may be transferred readily to other functions and sectors. The application to knowledge-based activities such as engineering design is of particular relevance to UK plc. Hence, the purpose of this study has been to establish the state-of-the-art, in terms of the adoption of Lean in new product development, by carrying out a systematic review of the literature. The authors' findings confirm the view that Lean can be applied beneficially away from the factory; that an understanding and definition of value is key to success; that a set-based (or Toyota methodology) approach to design is favoured together with the strong leadership of a chief engineer; and that the successful implementation requires organization-wide changes to systems, practices, and behaviour. On this basis it is felt that this review paper provides a useful platform for further research in this topic.

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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.

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With the buzzwords of knowledge-based economy and knowledge-driven economy, policy-makers, as well as journalists and management consultants, are pushing forward a vision of change that transforms the way advanced economies work. Yet little is understood about how the knowledge-based economy differs from the old, traditional economy. It is generally agreed that the phenomenon has grown out of the branch of economic thought known as new growth theory. Digesting up-to-date thinking in economics, management, innovation studies and economic geography, this significant volume provides an account of these developments and how they have transformed advanced economies.

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Purpose: The paper aims to explore the nature and purpose of higher education (HE) in the twenty-first century, focussing on how it can help fashion a green knowledge-based economy by developing approaches to learning and teaching that are social, networked and ecologically sensitive. Design/methodology/approach: The paper presents a discursive analysis of the skills and knowledge requirements of an emerging green knowledge-based economy using a range of policy focussed and academic research literature. Findings: The business opportunities that are emerging as a more sustainable world is developed requires the knowledge and skills that can capture and move then forward but in a complex and uncertain worlds learning needs to non-linear, creative and emergent. Practical implications: Sustainable learning and the attributes graduates will need to exhibit are prefigured in the activities and learning characterising the work and play facilitated by new media technologies. Social implications: Greater emphasis is required in higher learning understood as the capability to learn, adapt and direct sustainable change requires interprofessional co-operation that must utlise the potential of new media technologies to enhance social learning and collective intelligence. Originality/value: The practical relationship between low-carbon economic development, social sustainability and HE learning is based on both normative criteria and actual and emerging projections in economic, technological and skills needs.

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Quality, production and technological innovation management rank among the most important matters of concern to modern manufacturing organisations. They can provide companies with the decisive means of gaining a competitive advantage, especially within industries where there is an increasing similarity in product design and manufacturing processes. The papers in this special issue of International Journal of Technology Management have all been selected as examples of how aspects of quality, production and technological innovation can help to improve competitive performance. Most are based on presentations made at the UK Operations Management Association's Sixth International Conference held at Aston University at which the theme was 'Getting Ahead Through Technology and People'. At the conference itself over 80 papers were presented by authors from 15 countries around the world. Among the many topics addressed within the conference theme, technological innovation, quality and production management emerged as attracting the greatest concern and interest of delegates, particularly those from industry. For any new initiative to be implemented successfully, it should be led from the top of the organization. Achieving the desired level of commitment from top management can, however, be a difficulty. In the first paper of this issue, Mackness investigates this question by explaining how systems thinking can help. In the systems approach, properties such as 'emergence', 'hierarchy', 'commnication' and 'control' are used to assist top managers in preparing for change. Mackness's paper is then complemented by Iijima and Hasegawa's contribution in which they investigate the development of Quality Information Management (QIM) in Japan. They present the idea of a Design Review and demonstrate how it can be used to trace and reduce quality-related losses. The next paper on the subject of quality is by Whittle and colleagues. It relates to total quality and the process of culture change within organisations. Using the findings of investigations carried out in a number of case study companies, they describe four generic models which have been identified as characterising methods of implementing total quality within existing organisation cultures. Boaden and Dale's paper also relates to the management of quality, but looks specifically at the construction industry where it has been found there is still some confusion over the role of Quality Assurance (QA) and Total Quality Management (TQM). They describe the results of a questionnaire survey of forty companies in the industry and compare them to similar work carried out in other industries. Szakonyi's contribution then completes this group of papers which all relate specifically to the question of quality. His concern is with the two ways in which R&D or engineering managers can work on improving quality. The first is by improving it in the laboratory, while the second is by working with other functions to improve quality in the company. The next group of papers in this issue all address aspects of production management. Umeda's paper proposes a new manufacturing-oriented simulation package for production management which provides important information for both design and operation of manufacturing systems. A simulation for production strategy in a Computer Integrated Manufacturing (CIM) environment is also discussed. This paper is then followed by a contribution by Tanaka and colleagues in which they consider loading schedules for manufacturing orders in a Material Requirements Planning (MRP) environment. They compare mathematical programming with a knowledge-based approach, and comment on their relative effectiveness for different practical situations. Engstrom and Medbo's paper then looks at a particular aspect of production system design, namely the question of devising group working arrangements for assembly with new product structures. Using the case of a Swedish vehicle assembly plant where long cycle assembly work has been adopted, they advocate the use of a generally applicable product structure which can be adapted to suit individual local conditions. In the last paper of this particular group, Tay considers how automation has affected the production efficiency in Singapore. Using data from ten major industries he identifies several factors which are positively correlated with efficiency, with capital intensity being of greatest interest to policy makers. The two following papers examine the case of electronic data interchange (EDI) as a means of improving the efficiency and quality of trading relationships. Banerjee and Banerjee consider a particular approach to material provisioning for production systems using orderless inventory replenishment. Using the example of a single supplier and multiple buyers they develop an analytical model which is applicable for the exchange of information between trading partners using EDI. They conclude that EDI-based inventory control can be attractive from economic as well as other standpoints and that the approach is consistent with and can be instrumental in moving towards just-in-time (JIT) inventory management. Slacker's complementary viewpoint on EDI is from the perspective of the quality relation-ship between the customer and supplier. Based on the experience of Lucas, a supplier within the automotive industry, he concludes that both banks and trading companies must take responsibility for the development of payment mechanisms which satisfy the requirements of quality trading. The three final papers of this issue relate to technological innovation and are all country based. Berman and Khalil report on a survey of US technological effectiveness in the global economy. The importance of education is supported in their conclusions, although it remains unclear to what extent the US government can play a wider role in promoting technological innovation and new industries. The role of technology in national development is taken up by Martinsons and Valdemars who examine the case of the former Soviet Union. The failure to successfully infuse technology into Soviet enterprises is seen as a factor in that country's demise, and it is anticipated that the newly liberalised economies will be able to encourage greater technological creativity. This point is then taken up in Perminov's concluding paper which looks in detail at Russia. Here a similar analysis is made of the concluding paper which looks in detail at Russia. Here a similar analysis is made of the Soviet Union's technological decline, but a development strategy is also presented within the context of the change from a centralised to a free market economy. The papers included in this special issue of the International Journal of Technology Management each represent a unique and particular contribution to their own specific area of concern. Together, however, they also argue or demonstrate the general improvements in competitive performance that can be achieved through the application of modern principles and practice to the management of quality, production and technological innovation.

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Background - Modelling the interaction between potentially antigenic peptides and Major Histocompatibility Complex (MHC) molecules is a key step in identifying potential T-cell epitopes. For Class II MHC alleles, the binding groove is open at both ends, causing ambiguity in the positional alignment between the groove and peptide, as well as creating uncertainty as to what parts of the peptide interact with the MHC. Moreover, the antigenic peptides have variable lengths, making naive modelling methods difficult to apply. This paper introduces a kernel method that can handle variable length peptides effectively by quantifying similarities between peptide sequences and integrating these into the kernel. Results - The kernel approach presented here shows increased prediction accuracy with a significantly higher number of true positives and negatives on multiple MHC class II alleles, when testing data sets from MHCPEP [1], MCHBN [2], and MHCBench [3]. Evaluation by cross validation, when segregating binders and non-binders, produced an average of 0.824 AROC for the MHCBench data sets (up from 0.756), and an average of 0.96 AROC for multiple alleles of the MHCPEP database. Conclusion - The method improves performance over existing state-of-the-art methods of MHC class II peptide binding predictions by using a custom, knowledge-based representation of peptides. Similarity scores, in contrast to a fixed-length, pocket-specific representation of amino acids, provide a flexible and powerful way of modelling MHC binding, and can easily be applied to other dynamic sequence problems.

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Machine breakdowns are one of the main sources of disruption and throughput fluctuation in highly automated production facilities. One element in reducing this disruption is ensuring that the maintenance team responds correctly to machine failures. It is, however, difficult to determine the current practice employed by the maintenance team, let alone suggest improvements to it. 'Knowledge based improvement' is a methodology that aims to address this issue, by (a) eliciting knowledge on current practice, (b) evaluating that practice and (c) looking for improvements. The methodology, based on visual interactive simulation and artificial intelligence methods, and its application to a Ford engine assembly facility are described. Copyright © 2002 Society of Automotive Engineers, Inc.

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Modelling human interaction and decision-making within a simulation presents a particular challenge. This paper describes a methodology that is being developed known as 'knowledge based improvement'. The purpose of this methodology is to elicit decision-making strategies via a simulation model and to represent them using artificial intelligence techniques. Further to this, having identified an individual's decision-making strategy, the methodology aims to look for improvements in decision-making. The methodology is being tested on unplanned maintenance operations at a Ford engine assembly plant

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In present day knowledge societies political decisions are often justified on the basis of scientific expertise. Traditionally, a linear relation between knowledge production and application was postulated which would lead, with more and better science, to better policies. Empirical studies in Science and Technology studies have essentially demolished this idea. However, it is still powerful, not least among practitioners working in fields where decision making is based on large doses of expert knowledge. Based on conceptual work in the field of Science and Technology Studies (STS) I shall examine two cases of global environmental governance, ozone layer protection and global climate change. I will argue that hybridization and purification are important for two major forms of scientific expertise. One is delivered though scientific advocacy (by individual scientists or groups of scientists), the other through expert committees, i.e. institutionalized forms of collecting and communicating expertise to decision makers. Based on this analysis lessons will be drawn, also with regard to the stalling efforts at establishing an international forestry regime.