954 resultados para learning capability


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The question of how young firms reconcile the absence of well-established learning routines arising from the “liabilities of newness” with the “learning advantages of newness” has received scant attention in entrepreneurship. While older firms follow established learning routines and sometimes face problems in overcoming inertia, young firms with lower levels of inertia are better poised to explore, search and test unique avenues for their products and services. The process of learning and capability development as well as establishing uniqueness in their product offerings is an important part not only in the early stages of firm growth, but also in firm survival. Given their inexperience, for young firms, these learning processes are iterative and include contrasting learning loops that sometimes progress and at other times digress from initially perceived unique ideas. Such processes are embedded within capabilities that the firm develops and nurtures. Based on this premise and adopting a capabilities-based view, we examine how strategic networks and environmental knowledge affects uniqueness- mediated performance in young firms. We identify firms with digressive learning strategies based on their self-assessment of learning and compare them with other firms to demonstrate a differential effect on performance.

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Regional innovation systems (RISs) literature has emphasized the critical role of interactive learning and knowledge exchange amongst firms and a variety of spatially connected innovation institutions as the foundation of regional innovation. Knowledge intermediaries have been analysed in terms of the technology-transaction services they provide firms and/or knowledge producers such as universities and therefore the role they play in facilitating interaction within the RIS. However, innovation also depends on the capability of the firm to learn. Some studies have suggested that intermediaries also play a role in that regard as participation in intermediary knowledge transfer programmes can contribute to the development of firm capabilities for problem-solving and learning. Our research is based on two case study intermediary programmes involving interviews with facilitators and participants. Our data show that knowledge intermediaries affect organizational learning capabilities by impacting on firms' network relationships, internal and external communication channels and internal learning processes which in turn affect the ability to interpret and use knowledge within the firm. This suggests that the role of knowledge intermediaries might be greater than facilitating interactions in the innovation system, as knowledge intermediation may affect the ability of firms to learn and absorb knowledge from their environment.

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The determination of performance standards and assessment practices in regard to student work placements is an essential and important task. Inappropriate, inadequate, or excessively complex assessment tasks can influence levels of student engagement and the quality of learning outcomes. Critical to determining appropriate standards and assessment tasks is an understanding and knowledge of key elements of the learning environment and the extent to which opportunities are provided for students to engage in critical reflection and judgement of their own performance in the contexts of the work environment. This paper focuses on the development of essential skills and knowledge (capabilities) that provide evidence of learning in work placements by describing an approach taken in the science and technology disciplines. Assessment matrices are presented to illustrate a method of assessment for use within the context of the learning environment centred on work placements in science and technology. This study contributes to the debate on the meaning of professional capability, performance standards and assessment practices in work placement programs by providing evidence of an approach that can be adapted by other programs to achieve similar benefits. The approach may also be valuable to other learning contexts where capability and performance are being judged in situations that are outside a controlled teaching and learning environment i.e. in other life-wide learning contexts.

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Service robots that operate in human environments will accomplish tasks most efficiently and least disruptively if they have the capability to mimic and understand the motion patterns of the people in their workspace. This work demonstrates how a robot can create a humancentric navigational map online, and that this map re ects changes in the environment that trigger altered motion patterns of people. An RGBD sensor mounted on the robot is used to detect and track people moving through the environment. The trajectories are clustered online and organised into a tree-like probabilistic data structure which can be used to detect anomalous trajectories. A costmap is reverse engineered from the clustered trajectories that can then inform the robot's onboard planning process. Results show that the resultant paths taken by the robot mimic expected human behaviour and can allow the robot to respond to altered human motion behaviours in the environment.

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This paper proposes an efficient and online learning control system that uses the successful Model Predictive Control (MPC) method in a model based locally weighted learning framework. The new approach named Locally Weighted Learning Model Predictive Control (LWL-MPC) has been proposed as a solution to learn to control complex and nonlinear Elastic Joint Robots (EJR). Elastic Joint Robots are generally difficult to learn to control due to their elastic properties preventing standard model learning techniques from being used, such as learning computed torque control. This paper demonstrates the capability of LWL-MPC to perform online and incremental learning while controlling the joint positions of a real three Degree of Freedom (DoF) EJR. An experiment on a real EJR is presented and LWL-MPC is shown to successfully learn to control the system to follow two different figure of eight trajectories.

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The focus of knowledge management (KM) in the construction industry is moving towards capability building for value creation. The study reported by this paper is motivated by recent assertions about the genesis and evolution of knowledge management capability (KMC) in the strategic management field. It attempts to shed light on the governance of learning mechanisms that develop KMC within the context of construction firms. A questionnaire survey was administered to a sample of construction contractors operating in the very dynamic Hong Kong market to elicit opinions on the learning mechanisms and business outcomes of targeted firms. On the basis of a total of 149 usable responses, structural equation modeling (SEM) analysis identified relationships among knowledge-governance mechanisms, knowledge processes, and business performance, thereby supporting the existence of strategic learning loops. The study findings provide evidence from the construction context for capability assertions that knowledge-governance mechanisms and processes form learning mechanisms that carry out strategic learning to create value, effect performance outcomes, and ultimately drive the evolution of KMC. The findings imply that it is feasible for managing construction firms to govern learning mechanisms through managing the capability-based holistic KM system, thereby reconfiguring KMC to match needs in the dynamic market environment over time.

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A firm, as a dynamic, evolving, and quasi-autonomous system of knowledge production and application, develops knowledge management capability (KMC) through strategic learning in order to sustain competitive advantages in a dynamic environment. Knowledge governance mechanisms and knowledge processes connect and interact with each other forming learning mechanisms, which carry out double loop learning that drives genesis and evolution of KMC to modify operating routines that effect desired performance. This paper reports a study that was carried out within a context of construction contractors, a type of project-based firms, operating within the dynamic Hong Kong construction market. A multiple-case design was used to incorporate evidence from the literature and interviews, with the help of system dynamics modeling, to visualize the evolution of KMC. The study demonstrates the feasibility to visualize how a firm's KMC matches its operating environment over time. The findings imply that knowledge management (KM) applications can be better planned and controlled through evaluation of KM performance over time from a capability perspective.

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As universities worldwide begin to appreciate the value of authentic learning experiences, so they struggle with methods of assessing the outcomes from such experiences. This chapter describes the application of an assessment matrix developed by Queensland University of Technology (QUT) in Australia, to the assessment requirements and practices relating to work integrated learning at the University of Surrey in the UK. Despite the very different institutional contexts and independent way in which the assessment regimes have developed, it was found that the values and outcomes being assessed and the methods used to assess them were similar. The most important feature of assessing work integrated learning experiences is fitness for purpose; hence the learning objectives and assessment of outcomes for a WIL experience must be explicitly aligned to this objective.

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Corporate business and management are embracing design thinking for its potential to deliver competitive advantage through helping them be more innovative, differentiate their brands, and bring more customer centric products and services to market (Brown, 2008). As consumers continue to expect more personalisation and customisation from their service providers, the use of design thinking for innovation within organisations is a logical progression. To date however, there is little empirical literature discussing how organisations are setting about integrating design thinking into their culture and innovation practices. This paper is a first step in initiating a scholarly discussion on the integration of design thinking within organisational culture. Deloitte Australia is a large professional services firm employing over 5700 staff in 12 offices across Australia. The company provides a range of services to clients in the areas of audit, tax, financial advisory and consulting. In early 2011 the company made a strategic commitment to introducing design thinking into the organisation’s practices. While it already maintains a strong innovation culture, to date it had largely been operating within an analytical business environment. For Deloitte, design thinking is an opportunity to create better outcomes for the people they serve – both internal and external stakeholders (Brown and Wyatt, 2010). Research was conducted using case study methodology and ethnographic methods from June to September 2011 at the Melbourne Deloitte office. It involved three methods of data collection: semi structured interviews, participant observation and artifact analysis. This paper presents preliminary case study findings of Deloitte’s approach to building awareness and a consistent understanding of design thinking, as well as large scale capability, across the firm. Deloitte’s commitment to transforming its culture to one of design thinking poses significant potential for understanding how design thinking is comprehended, enabled and integrated within a complex organisational environment.

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The generational approach to conceptualising first year student learning behaviour has made a useful contribution to understanding student engagement. It has an explicit focus on student behaviour and we suggest that a capability maturity model interpretation may provide a complementary extension of that understanding as it builds on the generational approach by allowing an assessment of institutional capability to initiate, plan, manage, evaluate and review institutional student engagement practices. The development of a Student Engagement, Success and Retention Maturity Model (SESR-MM) is discussed along with its application in an Australian higher education institution. In this case study, the model identified first, second and third generation approaches and in addition achieved a ‘complementary extension’ of the generational approach, building on it by identifying additional practices not normally considered within the generational concept and indicating the capability of the institution to provide and implement the practices.

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Over the last decade, the majority of existing search techniques is either keyword- based or category-based, resulting in unsatisfactory effectiveness. Meanwhile, studies have illustrated that more than 80% of users preferred personalized search results. As a result, many studies paid a great deal of efforts (referred to as col- laborative filtering) investigating on personalized notions for enhancing retrieval performance. One of the fundamental yet most challenging steps is to capture precise user information needs. Most Web users are inexperienced or lack the capability to express their needs properly, whereas the existent retrieval systems are highly sensitive to vocabulary. Researchers have increasingly proposed the utilization of ontology-based tech- niques to improve current mining approaches. The related techniques are not only able to refine search intentions among specific generic domains, but also to access new knowledge by tracking semantic relations. In recent years, some researchers have attempted to build ontological user profiles according to discovered user background knowledge. The knowledge is considered to be both global and lo- cal analyses, which aim to produce tailored ontologies by a group of concepts. However, a key problem here that has not been addressed is: how to accurately match diverse local information to universal global knowledge. This research conducts a theoretical study on the use of personalized ontolo- gies to enhance text mining performance. The objective is to understand user information needs by a \bag-of-concepts" rather than \words". The concepts are gathered from a general world knowledge base named the Library of Congress Subject Headings. To return desirable search results, a novel ontology-based mining approach is introduced to discover accurate search intentions and learn personalized ontologies as user profiles. The approach can not only pinpoint users' individual intentions in a rough hierarchical structure, but can also in- terpret their needs by a set of acknowledged concepts. Along with global and local analyses, another solid concept matching approach is carried out to address about the mismatch between local information and world knowledge. Relevance features produced by the Relevance Feature Discovery model, are determined as representatives of local information. These features have been proven as the best alternative for user queries to avoid ambiguity and consistently outperform the features extracted by other filtering models. The two attempt-to-proposed ap- proaches are both evaluated by a scientific evaluation with the standard Reuters Corpus Volume 1 testing set. A comprehensive comparison is made with a num- ber of the state-of-the art baseline models, including TF-IDF, Rocchio, Okapi BM25, the deploying Pattern Taxonomy Model, and an ontology-based model. The gathered results indicate that the top precision can be improved remarkably with the proposed ontology mining approach, where the matching approach is successful and achieves significant improvements in most information filtering measurements. This research contributes to the fields of ontological filtering, user profiling, and knowledge representation. The related outputs are critical when systems are expected to return proper mining results and provide personalized services. The scientific findings have the potential to facilitate the design of advanced preference mining models, where impact on people's daily lives.

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In this article we develop a hierarchical framework of ordinary capabilities, dynamic functional capabilities, and dynamic learning capabilities. These three levels of capabilities differ across four interdependent internal dimensions of predominant resources, routine patterning, learning, and strategic intent. The levels are also influenced by external environmental velocity. This framework progresses the ongoing debate surrounding the capability hierarchy and offers a novel view of capabilities. We also provide direction regarding how the framework can lead future research toward a validated measurable model that contributes to solving the definitional and associated measurement debates around ordinary and dynamic capabilities.

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Beginning in the second half of the 20th century, ICTs transformed many societies from industrial societies in which manufacturing was the central focus, into knowledge societies in which dealing effectively with data and information has become a central element of work (Anderson, 2008). To meet the needs of the knowledge society, universities must reinvent their structures and processes, their curricula and pedagogic practices. In addition to this, of course higher education is itself subject to the sweeping influence of ICTs. But what might effective higher education look like in the 21st century? In designing higher education systems and learning experiences which are responsive to the learning needs of the future and exploit the possibilities offered by ICTs, we can learn much from the existing professional development strategies of people who are already successful in 21st century fields, such as digital media. In this study, I ask: (1) what are the learning challenges faced by digital media professionals in the 21st century? (2) what are the various roles of formal and informal education in their professional learning strategies at present? (3) how do they prefer to acquire needed capabilities? In-depth interviews were undertaken with successful Australian digital media professionals working in micro businesses and SMEs to answer these questions. The strongest thematic grouping that emerged from the interviews related to the need for continual learning and relearning because of the sheer rate of change in the digital media industries. Four dialectical relationships became apparent from the interviewees’ commentaries around the learning imperatives arising out of the immense and continual changes occurring in the digital content industries: (1) currency vs best practice (2) diversification vs specialisation of products and services (3) creative outputs vs commercial outcomes (4) more learning opportunities vs less opportunity to learn. These findings point to the importance of ‘learning how to learn’ as a 21st century capability. The interviewees were ambivalent about university courses as preparation for professional life in their fields. Higher education was described by several interviewees as having relatively little value-add beyond what one described as “really expensive credentialling services.” For all interviewees in this study, informal learning strategies were the preferred methods of acquiring the majority of knowledge and skills, both for ongoing and initial professional development. Informal learning has no ‘curriculum’ per se, and tends to be opportunistic, unstructured, pedagogically agile and far more self-directed than formal learning (Eraut, 2004). In an industry impacted by constant change, informal learning is clearly both essential and ubiquitous. Inspired by the professional development strategies of the digital media professionals in this study, I propose a 21st century model of the university as a broad, open learning ecology, which also includes industry, professionals, users, and university researchers. If created and managed appropriately, the university learning network becomes the conduit and knowledge integrator for the latest research and industry trends, which students and professionals alike can access as needed.

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This paper proposes an online learning control system that uses the strategy of Model Predictive Control (MPC) in a model based locally weighted learning framework. The new approach, named Locally Weighted Learning Model Predictive Control (LWL-MPC), is proposed as a solution to learn to control robotic systems with nonlinear and time varying dynamics. This paper demonstrates the capability of LWL-MPC to perform online learning while controlling the joint trajectories of a low cost, three degree of freedom elastic joint robot. The learning performance is investigated in both an initial learning phase, and when the system dynamics change due to a heavy object added to the tool point. The experiment on the real elastic joint robot is presented and LWL-MPC is shown to successfully learn to control the system with and without the object. The results highlight the capability of the learning control system to accommodate the lack of mechanical consistency and linearity in a low cost robot arm.

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We investigate the enablers of early internationalization of the firm. We posit that for firms to internationalize early in their lifecycles, sets of capabilities must be present at the firm’s formative stage and that these capabilities build upon routines that the founders bring into the new firm. These capabilities are aligned to establish a platform for internationalization unencumbered by the administrative heritage often observed in well-established firms. We model this phenomenon, testing it in a cross-national setting of early internationalizing firms in Australia and the United States. To do so, we draw upon a dynamic capabilities framing, conceptualizing and measuring the dynamic capabilities that founders apply in their early internationalization activities.