776 resultados para Situated learning and knowledge
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Purpose – The purpose of this paper is to demonstrate analytically how entrepreneurial action as learning relating to diversifying into technical clothing – i.e. a high-value manufacturing sector – can take place. This is particularly relevant to recent discussion and debate in academic and policy-making circles concerning the survival of the clothing manufacture industry in developed industrialised countries. Design/methodology/approach – Using situated learning theory (SLT) as the major analytical lens, this case study examines an episode of entrepreneurial action relating to diversification into a high-value manufacturing sector. It is considered on instrumentality grounds, revealing wider tendencies in the management of knowledge and capabilities requisite for effective entrepreneurial action of this kind. Findings – Boundary events, brokers, boundary objects, membership structures and inclusive participation that addresses power asymmetries are found to be crucial organisational design elements, enabling the development of inter- and intracommunal capacities. These together constitute a dynamic learning capability, which underpins entrepreneurial action, such as diversification into high-value manufacturing sectors. Originality/value – Through a refinement of SLT in the context of entrepreneurial action, the paper contributes to an advancement of a substantive theory of managing technological knowledge and capabilities for effective diversification into high-value manufacturing sectors.
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Mode of access: Internet.
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Thesis (Ph.D.)--University of Washington, 2016-06
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Thesis (Ph.D.)--University of Washington, 2016-03
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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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Purpose - The purpose of this paper is to demonstrate analytically how entrepreneurial action as learning relating to diversifying into technical clothing - i.e. a high-value manufacturing sector - can take place. This is particularly relevant to recent discussion and debate in academic and policy-making circles concerning the survival of the clothing manufacture industry in developed industrialised countries. Design/methodology/approach - Using situated learning theory (SLT) as the major analytical lens, this case study examines an episode of entrepreneurial action relating to diversification into a high-value manufacturing sector. It is considered on instrumentality grounds, revealing wider tendencies in the management of knowledge and capabilities requisite for effective entrepreneurial action of this kind. Findings - Boundary events, brokers, boundary objects, membership structures and inclusive participation that addresses power asymmetries are found to be crucial organisational design elements, enabling the development of inter- and intracommunal capacities. These together constitute a dynamic learning capability, which underpins entrepreneurial action, such as diversification into high-value manufacturing sectors. Originality/value - Through a refinement of SLT in the context of entrepreneurial action, the paper contributes to an advancement of a substantive theory of managing technological knowledge and capabilities for effective diversification into high-value manufacturing sectors. Copyright © 2014 Emerald Group Publishing Limited. All rights reserved.
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ACM Computing Classification System (1998): K.3.1, K.3.2.
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The rapid progression of biomedical research coupled with the explosion of scientific literature has generated an exigent need for efficient and reliable systems of knowledge extraction. This dissertation contends with this challenge through a concentrated investigation of digital health, Artificial Intelligence, and specifically Machine Learning and Natural Language Processing's (NLP) potential to expedite systematic literature reviews and refine the knowledge extraction process. The surge of COVID-19 complicated the efforts of scientists, policymakers, and medical professionals in identifying pertinent articles and assessing their scientific validity. This thesis presents a substantial solution in the form of the COKE Project, an initiative that interlaces machine reading with the rigorous protocols of Evidence-Based Medicine to streamline knowledge extraction. In the framework of the COKE (“COVID-19 Knowledge Extraction framework for next-generation discovery science”) Project, this thesis aims to underscore the capacity of machine reading to create knowledge graphs from scientific texts. The project is remarkable for its innovative use of NLP techniques such as a BERT + bi-LSTM language model. This combination is employed to detect and categorize elements within medical abstracts, thereby enhancing the systematic literature review process. The COKE project's outcomes show that NLP, when used in a judiciously structured manner, can significantly reduce the time and effort required to produce medical guidelines. These findings are particularly salient during times of medical emergency, like the COVID-19 pandemic, when quick and accurate research results are critical.