918 resultados para Dynamic Learning Capabilities
Resumo:
Increasingly, academic teachers are designing their own web sites to add value to or replace other forms of university teaching. These web sites are tangible and dynamic constructions that represent the teachers thinking and decisions derived from an implicit belief system about teaching and learning. The emphasis of this study is to explore the potential of the research techniques of concept-mapping and stimulated recall to locate the implicit pedagogies of academic teachers and investigate how they are enacted through the learning designs of their web sites. The rationale behind such an investigation is that once these implicit belief systems are made visible, then conversations can commence about how these beliefs are transformed into practice, providing a potent departure point for academic development.
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Este estudo teve como objetivo principal analisar a relação entre a Liderança Transformacional, a Conversão do Conhecimento e a Eficácia Organizacional. Foram considerados como pressupostos teóricos conceitos consolidados sobre os temas desta relação, além de recentes pesquisas já realizadas em outros países e contextos organizacionais. Com base nisto identificou-se potencial estudo de um modelo que relacionasse estes três conceitos. Para tal considera-se que as organizações que buscam atingir Vantagem Competitiva e incorporam a Knowledge-Based View possam conquistar diferenciação frente a seus concorrentes. Nesse contexto o conhecimento ganha maior destaque e papel protagonista nestas organizações. Dessa forma criar conhecimento através de seus colaboradores, passa a ser um dos desafios dessas organizações ao passo que sugere melhoria de seus indicadores Econômicos, Sociais, Sistêmicos e Políticos, o que se define por Eficácia Organizacional. Portanto os modos de conversão do conhecimento nas organizações, demonstram relevância, uma vez que se cria e se converte conhecimentos através da interação entre o conhecimento existente de seus colaboradores. Essa conversão do conhecimento ou modelo SECI possui quatro modos que são a Socialização, Externalização, Combinação e Internalização. Nessa perspectiva a liderança nas organizações apresenta-se como um elemento capaz de influenciar seus colaboradores, propiciando maior dinâmica ao modelo SECI de conversão do conhecimento. Se identifica então na liderança do tipo Transformacional, características que possam influenciar colaboradores e entende-se que esta relação entre a Liderança Transformacional e a Conversão do Conhecimento possa ter influência positiva nos indicadores da Eficácia Organizacional. Dessa forma esta pesquisa buscou analisar um modelo que explorasse essa relação entre a liderança do tipo Transformacional, a Conversão do Conhecimento (SECI) e a Eficácia Organizacional. Esta pesquisa teve o caráter quantitativo com coleta de dados através do método survey, obtendo um total de 230 respondentes válidos de diferentes organizações. O instrumento de coleta de dados foi composto por afirmativas relativas ao modelo de relação pesquisado com um total de 44 itens. O perfil de respondentes concentrou-se entre 30 e 39 anos de idade, com a predominância de organizações privadas e de departamentos de TI/Telecom, Docência e Recursos Humanos respectivamente. O tratamento dos dados foi através da Análise Fatorial Exploratória e Modelagem de Equações Estruturais via Partial Least Square Path Modeling (PLS-PM). Como resultado da análise desta pesquisa, as hipóteses puderam ser confirmadas, concluindo que a Liderança Transformacional apresenta influência positiva nos modos de Conversão do Conhecimento e que; a Conversão do Conhecimento influencia positivamente na Eficácia Organizacional. Ainda, concluiu-se que a percepção entre os respondentes não apresenta resultado diferente sobre o modelo desta pesquisa entre quem possui ou não função de liderança.
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In this paper we present a new approach to ontology learning. Its basis lies in a dynamic and iterative view of knowledge acquisition for ontologies. The Abraxas approach is founded on three resources, a set of texts, a set of learning patterns and a set of ontological triples, each of which must remain in equilibrium. As events occur which disturb this equilibrium various actions are triggered to re-establish a balance between the resources. Such events include acquisition of a further text from external resources such as the Web or the addition of ontological triples to the ontology. We develop the concept of a knowledge gap between the coverage of an ontology and the corpus of texts as a measure triggering actions. We present an overview of the algorithm and its functionalities.
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Anyone who looks at the title of this special issue will agree that the intent behind the preparation of this volume was ambitious: to predict and discuss “The Future of Manufacturing”. Will manufacturing be important in the future? Even though some sceptics might say not, and put on the table some old familiar arguments, we would strongly disagree. To bring subsidies for the argument we issued the call-for-papers for this special issue of Journal of Manufacturing Technology Management, fully aware of the size of the challenge in our hands. But we strongly believed that the enterprise would be worthwhile. The point of departure is the ongoing debate concerning the meaning and content of manufacturing. The easily visualised internal activity of using tangible resources to make physical products in factories is no longer a viable way to characterise manufacturing. It is now a more loosely defined concept concerning the organisation and management of open, interdependent, systems for delivering goods and services, tangible and intangible, to diverse types of markets. Interestingly, Wickham Skinner is the most cited author in this special issue of JMTM. He provides the departure point of several articles because his vision and insights have guided and inspired researchers in production and operations management from the late 1960s until today. However, the picture that we draw after looking at the contributions in this special issue is intrinsically distinct, much more dynamic, and complex. Seven articles address the following research themes: 1.new patterns of organisation, where the boundaries of firms become blurred and the role of the firm in the production system as well as that of manufacturing within the firm become contingent; 2.new approaches to strategic decision-making in markets characterised by turbulence and weak signals at the customer interface; 3.new challenges in strategic and operational decisions due to changes in the profile of the workforce; 4.new global players, especially China, modifying the manufacturing landscape; and 5.new techniques, methods and tools that are being made feasible through progress in new technological domains. Of course, many other important dimensions could be studied, but these themes are representative of current changes and future challenges. Three articles look at the first theme: organisational evolution of production and operations in firms and networks. Karlsson's and Skold's article represent one further step in their efforts to characterise “the extraprise”. In the article, they advance the construction of a new framework, based on “the network perspective” by defining the formal elements which compose it and exploring the meaning of different types of relationships. The way in which “actors, resources and activities” are conceptualised extends the existing boundaries of analytical thinking in operations management and open new avenues for research, teaching and practice. The higher level of abstraction, an intrinsic feature of the framework, is associated to the increasing degree of complexity that characterises decisions related to strategy and implementation in the manufacturing and operations area, a feature that is expected to become more and more pervasive as time proceeds. Riis, Johansen, Englyst and Sorensen have also based their article on their previous work, which in this case is on “the interactive firm”. They advance new propositions on strategic roles of manufacturing and discuss why the configuration of strategic manufacturing roles, at the level of the network, will become a key issue and how the indirect strategic roles of manufacturing will become increasingly important. Additionally, by considering that value chains will become value webs, they predict that shifts in strategic manufacturing roles will look like a sequence of moves similar to a game of chess. Then, lastly under the first theme, Fleury and Fleury develop a conceptual framework for the study of production systems in general derived from field research in the telecommunications industry, here considered a prototype of the coming information society and knowledge economy. They propose a new typology of firms which, on certain dimensions, complements the propositions found in the other two articles. Their telecoms-based framework (TbF) comprises six types of companies characterised by distinct profiles of organisational competences, which interact according to specific patterns of relationships, thus creating distinct configurations of production networks. The second theme is addressed by Kyläheiko and SandstroÍm in their article “Strategic options based framework for management of dynamic capabilities in manufacturing firms”. They propose a new approach to strategic decision-making in markets characterised by turbulence and weak signals at the customer interface. Their framework for a manufacturing firm in the digital age leads to active asset selection (strategic investments in both tangible and intangible assets) and efficient orchestrating of the global value net in “thin” intangible asset markets. The framework consists of five steps based on Porter's five-forces model, the resources-based view, complemented by means of the concepts of strategic options and related flexibility issues. Thun, GroÍssler and Miczka's contribution to the third theme brings the human dimension to the debate regarding the future of manufacturing. Their article focuses on the challenges brought to management by the ageing of workers in Germany but, in the arguments that are raised, the future challenges associated to workers and work organisation in every production system become visible and relevant. An interesting point in the approach adopted by the authors is that not only the factual problems and solutions are taken into account but the perception of the managers is brought into the picture. China cannot be absent in the discussion of the future of manufacturing. Therefore, within the fourth theme, Vaidya, Bennett and Liu provide the evidence of the gradual improvement of Chinese companies in the medium and high-tech sectors, by using the revealed comparative advantage (RCA) analysis. The Chinese evolution is shown to be based on capabilities developed through combining international technology transfer and indigenous learning. The main implication for the Western companies is the need to take account of the accelerated rhythm of capability development in China. For other developing countries China's case provides lessons of great importance. Finally, under the fifth theme, Kuehnle's article: “Post mass production paradigm (PMPP) trajectories” provides a futuristic scenario of what is already around us and might become prevalent in the future. It takes a very intensive look at a whole set of dimensions that are affecting manufacturing now, and will influence manufacturing in the future, ranging from the application of ICT to the need for social transparency. In summary, this special issue of JMTM presents a brief, but undisputable, demonstration of the possible richness of manufacturing in the future. Indeed, we could even say that manufacturing has no future if we only stick to the past perspectives. Embracing the new is not easy. The new configurations of production systems, the distributed and complementary roles to be performed by distinct types of companies in diversified networked structures, leveraged by the new emergent technologies and associated the new challenges for managing people, are all themes that are carriers of the future. The Guest Editors of this special issue on the future of manufacturing are strongly convinced that their undertaking has been worthwhile.
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There are been a resurgence of interest in the neural networks field in recent years, provoked in part by the discovery of the properties of multi-layer networks. This interest has in turn raised questions about the possibility of making neural network behaviour more adaptive by automating some of the processes involved. Prior to these particular questions, the process of determining the parameters and network architecture required to solve a given problem had been a time consuming activity. A number of researchers have attempted to address these issues by automating these processes, concentrating in particular on the dynamic selection of an appropriate network architecture.The work presented here specifically explores the area of automatic architecture selection; it focuses upon the design and implementation of a dynamic algorithm based on the Back-Propagation learning algorithm. The algorithm constructs a single hidden layer as the learning process proceeds using individual pattern error as the basis of unit insertion. This algorithm is applied to several problems of differing type and complexity and is found to produce near minimal architectures that are shown to have a high level of generalisation ability.
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Software development methodologies are becoming increasingly abstract, progressing from low level assembly and implementation languages such as C and Ada, to component based approaches that can be used to assemble applications using technologies such as JavaBeans and the .NET framework. Meanwhile, model driven approaches emphasise the role of higher level models and notations, and embody a process of automatically deriving lower level representations and concrete software implementations. The relationship between data and software is also evolving. Modern data formats are becoming increasingly standardised, open and empowered in order to support a growing need to share data in both academia and industry. Many contemporary data formats, most notably those based on XML, are self-describing, able to specify valid data structure and content, and can also describe data manipulations and transformations. Furthermore, while applications of the past have made extensive use of data, the runtime behaviour of future applications may be driven by data, as demonstrated by the field of dynamic data driven application systems. The combination of empowered data formats and high level software development methodologies forms the basis of modern game development technologies, which drive software capabilities and runtime behaviour using empowered data formats describing game content. While low level libraries provide optimised runtime execution, content data is used to drive a wide variety of interactive and immersive experiences. This thesis describes the Fluid project, which combines component based software development and game development technologies in order to define novel component technologies for the description of data driven component based applications. The thesis makes explicit contributions to the fields of component based software development and visualisation of spatiotemporal scenes, and also describes potential implications for game development technologies. The thesis also proposes a number of developments in dynamic data driven application systems in order to further empower the role of data in this field.
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In this paper we report a comparative analysis of the factors which contribute to the innovation performance of manufacturing firms in the US state of Georgia, and three European regions, the UK regions of Wales and the West Midlands, and the Spanish region of Catalonia. We consider the factors which shape firms’ ability to generate new products and processes and undertake various forms of organisational and structural change. We are particularly concerned with how firms collect the knowledge on which they base their innovation and their effectiveness in translating that knowledge into new innovations. Three main empirical conclusions result. First, US firms have more widespread links to external knowledge sources than those in Europe and notably the universities make a greater contribution to innovation in the US than in Europe. Second, UK firms prove more effective at capturing synergies between their innovation activities than US and Catalan firms. Third, firms’ operating environment proves more conducive to innovation in the US than in either the UK regions or Catalonia. Our results suggest the potential for mutual learning. For the UK there are lessons in terms of the way in which the universities in Georgia are supporting innovation. For firms in Georgia and in Catalonia the potential lessons are more strategic or organisational and relate to how they can better capture potential synergies between their innovation activities.
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This dissertation investigates the very important and current problem of modelling human expertise. This is an apparent issue in any computer system emulating human decision making. It is prominent in Clinical Decision Support Systems (CDSS) due to the complexity of the induction process and the vast number of parameters in most cases. Other issues such as human error and missing or incomplete data present further challenges. In this thesis, the Galatean Risk Screening Tool (GRiST) is used as an example of modelling clinical expertise and parameter elicitation. The tool is a mental health clinical record management system with a top layer of decision support capabilities. It is currently being deployed by several NHS mental health trusts across the UK. The aim of the research is to investigate the problem of parameter elicitation by inducing them from real clinical data rather than from the human experts who provided the decision model. The induced parameters provide an insight into both the data relationships and how experts make decisions themselves. The outcomes help further understand human decision making and, in particular, help GRiST provide more accurate emulations of risk judgements. Although the algorithms and methods presented in this dissertation are applied to GRiST, they can be adopted for other human knowledge engineering domains.
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Technological capabilities in Chinese manufacturing have been transformed in the last three decades. However, the extent to which and how domestic market oriented state owned enterprises (SOEs) have developed their capabilities remain important questions. The East Asian latecomer model has been adapted to study six Chinese SOEs in the automotive, steel and machine tools sectors to assess capability levels attained and the role of external sources and internal efforts in developing them. All six enterprises demonstrate high competence in operating established technology, managing investment and making product and process improvements but differ in innovative capability. While the East Asian latecomer model in which linking, leveraging and learning explain technological capability development is relevant for the companies studied, it needs to be adapted for Chinese SOEs to take account of types of external links and leverage of enterprises, the role of government, enterprise level management motives and means of financing development.
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The World Wide Web provides plentiful contents for Web-based learning, but its hyperlink-based architecture connects Web resources for browsing freely rather than for effective learning. To support effective learning, an e-learning system should be able to discover and make use of the semantic communities and the emerging semantic relations in a dynamic complex network of learning resources. Previous graph-based community discovery approaches are limited in ability to discover semantic communities. This paper first suggests the Semantic Link Network (SLN), a loosely coupled semantic data model that can semantically link resources and derive out implicit semantic links according to a set of relational reasoning rules. By studying the intrinsic relationship between semantic communities and the semantic space of SLN, approaches to discovering reasoning-constraint, rule-constraint, and classification-constraint semantic communities are proposed. Further, the approaches, principles, and strategies for discovering emerging semantics in dynamic SLNs are studied. The basic laws of the semantic link network motion are revealed for the first time. An e-learning environment incorporating the proposed approaches, principles, and strategies to support effective discovery and learning is suggested.
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Purpose – The collapse of world economic systems brought the interconnectedness between business and global events sharply into focus. As Starkey points out: “leading business schools need to overcome their fascination with a particular form of finance and economics […] to broaden their intellectual horizons […] (and to) look at the lessons of history and other disciplines”. The purpose of this paper is to provide evidence from three years of research on the Aston MBA suggesting that an emphasis on developing capabilities within a far broader, connected and reflexive business curriculum is what business students and practitioners now recognise as an essential way forward for responsible management education. Design/methodology/approach – This research paper examines the reflective accounts of 300 MBA students undertaking a transdisciplinary Business Ethics, Responsibility and Sustainability core module. Findings – As Klein argues, transdisciplinarity is simultaneously an attitude and a form of action. The student reflections provide powerful discourses of individual learning and report a range of outcomes from finding “the vocabulary or the confidence” to raise issues to acting as “change agents” in the workplace. Originality/value – As responsibility and sustainability requires learners, researchers and educators to engage with real world complexity, uncertainty and risk, conventional disciplinary study, especially within business, often proves inadequate and partial. This paper demonstrates that creative and exploratory frames need to be developed to facilitate the development of more connected knowledge – informed by multiple stakeholders, able to contribute heterogeneous skills, perspectives and expertise.
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In the editorial of this special issue we argue that knowledge flows, learning and development are becoming increasingly important in all organisations operating in an international context. The possession of capabilities relating to acquisition, configuration and transfer of relevant knowledge effectively within and across different organisational units, teams, and countries is integrally related to superior organisational performance. In mastering such capabilities, internationalised organisations need to grapple with the inherent challenges relating to contextual variation and different work modes between subsidiaries, partners or team members. The papers in this special issue cast light on crucial aspects of knowledge flows, learning and development in internationalised organisations. Their contribution varies from the provision of frameworks to systematise investigation of these issues, to empirical evidence about effective mechanisms, as well as enabling and constraining forces, in facilitating knowledge transfer, learning and human capital development. © 2012 Inderscience Enterprises Ltd.
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An organisation’s ability to internalise external knowledge and learn from various sources in undertaking new product development and/or entering a new market is crucial to its competitive performance. Nevertheless, little attention has been paid to how growth-oriented small firms identify and exploit entrepreneurial opportunities, i.e. take entrepreneurial action, related to such methods of development, in a mature, contracting industry. The latter is particularly relevant to recent discussion and debate in academic and policy-making circles concerning the salvage of the clothing manufacture industry in developed industrialised countries, by intensifying efforts relating to diversification into high value manufacturing sectors. This paper, based on an instrumental case-firm, demonstrates analytically how learning as entrepreneurial action relating to diversifying into /technical clothing – i.e. a high value manufacturing/innovatory sector - takes place, drawing on situated learning theory. It is argued that learning relating to such entrepreneurial action is dynamic in nature and is founded on specific organising principles that foster both inter- and intracommunal learning.
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This paper develops and tests a learning organization model derived from HRM and dynamic capability literatures in order to ascertain the model's applicability across divergent global contexts. We define a learning organization as one capable of achieving on-going strategic renewal, arguing based on dynamic capability theory that the model has three necessary antecedents: HRM focus, developmental orientation and customer-facing remit. Drawing on a sample comprising nearly 6000 organizations across 15 countries, we show that learning organizations exhibit higher performance than their less learning-inclined counterparts. We also demonstrate that innovation fully mediates the relationship between our conceptualization of the learning organization and organizational performance in 11 of the 15 countries we examined. It is the first time in our knowledge that these questions have been tested in a major, cross-global study, and our work contributes to both HRM and dynamic capability literatures, especially where the focus is the applicability of best practice parameters across national boundaries.
Learning and change in interorganizational networks:the case for network learning and network change
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The ALBA 2002 Call for Papers asks the question ‘How do organizational learning and knowledge management contribute to organizational innovation and change?’. Intuitively, we would argue, the answer should be relatively straightforward as links between learning and change, and knowledge management and innovation, have long been commonly assumed to exist. On the basis of this assumption, theories of learning tend to focus ‘within organizations’, and assume a transfer of learning from individual to organization which in turn leads to change. However, empirically, we find these links are more difficult to articulate. Organizations exist in complex embedded economic, political, social and institutional systems, hence organizational change (or innovation) may be influenced by learning in this wider context. Based on our research in this wider interorganizational setting, we first make the case for the notion of network learning that we then explore to develop our appreciation of change in interorganizational networks, and how it may be facilitated. The paper begins with a brief review of lite rature on learning in the organizational and interorganizational context which locates our stance on organizational learning versus the learning organization, and social, distributed versus technical, centred views of organizational learning and knowledge. Developing from the view that organizational learning is “a normal, if problematic, process in every organization” (Easterby-Smith, 1997: 1109), we introduce the notion of network learning: learning by a group of organizations as a group. We argue this is also a normal, if problematic, process in organizational relationships (as distinct from interorganizational learning), which has particular implications for network change. Part two of the paper develops our analysis, drawing on empirical data from two studies of learning. The first study addresses the issue of learning to collaborate between industrial customers and suppliers, leading to the case for network learning. The second, larger scale study goes on to develop this theme, examining learning around several major change issues in a healthcare service provider network. The learning processes and outcomes around the introduction of a particularly controversial and expensive technology are described, providing a rich and contrasting case with the first study. In part three, we then discuss the implications of this work for change, and for facilitating change. Conclusions from the first study identify potential interventions designed to facilitate individual and organizational learning within the customer organization to develop individual and organizational ‘capacity to collaborate’. Translated to the network example, we observe that network change entails learning at all levels – network, organization, group and individual. However, presenting findings in terms of interventions is less meaningful in an interorganizational network setting given: the differences in authority structures; the less formalised nature of the network setting; and the importance of evaluating performance at the network rather than organizational level. Academics challenge both the idea of managing change and of managing networks. Nevertheless practitioners are faced with the issue of understanding and in fluencing change in the network setting. Thus we conclude that a network learning perspective is an important development in our understanding of organizational learning, capability and change, locating this in the wider context in which organizations are embedded. This in turn helps to develop our appreciation of facilitating change in interorganizational networks, both in terms of change issues (such as introducing a new technology), and change orientation and capability.