986 resultados para Knowledge demand
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La idea del marketing público se genera durante el siglo XX estableciendo un intercambio entre Estado y Sociedad. La Administración Pública diseña programas, bienes y servicios, como contraparte, los ciudadanos ofrecen apoyos mediante impuestos y costos de desplazamiento, tiempo y oportunidad. El marketing universitario, propone un intercambio entre las universidades y los alumnos para satisfacer las demandas de conocimiento y formación técnica-profesional. La problemática abordada en esta propuesta es la satisfacción de necesidades públicas a través del marketing público y, en este contexto, el marketing universitario y las demandas de conocimiento de la sociedad.
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This paper presents the results of the analysis focused on scientific-technological KT in four Mexican firms and carried out by the case study approach. The analysis highlights the use of KT mechanisms as a means to obtain scientific-technological knowledge, learning, building S&T capabilities, and achieve the results of the R&D and innovation by firms.
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The critical impact of innovation on national and the global economies has been discussed at length in the literature. Economic development requires the diffusion of innovations into markets. It has long been recognised that economic growth and development depends upon a constant stream of innovations. Governments have been keenly aware of the need to ensure this flow does not dry to a trickle and have introduced many and varied industry policies and interventions to assist in seeding, supporting and diffusing innovations. In Australia, as in many countries, Government support for the transfer of knowledge especially from publicly funded research has resulted in the creation of knowledge exchange intermediaries. These intermediaries are themselves service organisations, seeking innovative service offerings for their markets. The choice for most intermediaries is generally a dichotomous one, between market-pull and technology-push knowledge exchange programmes. In this article, we undertake a case analysis of one such innovative intermediary and its flagship programme. We then compare this case with other successful intermediaries in Europe. We put forward a research proposition that the design of intermediary programmes must match the service type they offer. That is, market-pull programmes require market-pull design, in close collaboration with industry, whereas technology programmes can be problem-solving innovations where demand is latent. The discussion reflects the need for an evolution in knowledge transfer policies and programmes beyond the first generation ushered in with the US Bayh-Dole Act (1980) and Stevenson-Wydler Act (1984). The data analysed is a case study comparison of market-pull and technology-push programmes, focusing on primary and secondary socio-economic benefits (using both Australian and international comparisons).
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The concept of moving block signallings (MBS) has been adopted in a few mass transit railway systems. When a dense queue of trains begins to move from a complete stop, the trains can re-start in very close succession under MBS. The feeding substations nearby are likely to be overloaded and the service will inevitably be disturbed unless substations of higher power rating are used. By introducing starting time delays among the trains or limiting the trains’ acceleration rate to a certain extent, the peak energy demand can be contained. However, delay is introduced and quality of service is degraded. An expert system approach is presented to provide a supervisory tool for the operators. As the knowledge base is vital for the quality of decisions to be made, the study focuses on its formulation with a balance between delay and peak power demand.
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This chapter focuses on two challenges to science teachers’ knowledge that Fensham identifies as having recently emerged—one a challenge from beyond Science and the other a challenge from within Science. Both challenges stem from common features of contemporary society, namely, its complexity and uncertainty. Both also confront science teachers with teaching situations that contrast markedly with the simplicity and certainty that have been characteristic of most school science education, and hence both present new demands for science teachers’ knowledge and skill. The first, the challenge from without Science, comes from the new world of work and the “knowledge society”. Regardless of their success in traditional school learning, many young persons in many modern economies are now seen as lacking other knowledge and skills that are essential for their personal, social and economic life. The second, the challenge from within Science, derives from changing notions of the nature of science itself. If the complexity and uncertainty of the knowledge society demand new understandings and contributions from science teachers, these are certainly matched by the demands that are posed by the role of complexity and uncertainty in science itself.
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This chapter argues that evolutionary economics should be founded upon complex systems theory rather than neo-Darwinian analogies concerning natural selection, which focus on supply side considerations and competition amongst firms and technologies. It suggests that conceptions such as production and consumption functions should be replaced by network representations, in which the preferences or, more correctly, the aspirations of consumers are fundamental and, as such, the primary drivers of economic growth. Technological innovation is viewed as a process that is intermediate between these aspirational networks, and the organizational networks in which goods and services are produced. Consumer knowledge becomes at least as important as producer knowledge in determining how economic value is generated. It becomes clear that the stability afforded by connective systems of rules is essential for economic flexibility to exist, but that too many rules result in inert and structurally unstable states. In contrast, too few rules result in a more stable state, but at a low level of ordered complexity. Economic evolution from this perspective is explored using random and scale free network representations of complex systems.
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Successful identification and exploitation of opportunities has been an area of interest to many entrepreneurship researchers. Since Shane and Venkataraman’s seminal work (e.g. Shane and Venkataraman, 2000; Shane, 2000), several scholars have theorised on how firms identify, nurture and develop opportunities. The majority of this literature has been devoted to understanding how entrepreneurs search for new applications of their technological base or discover opportunities based on prior knowledge (Zahra, 2008; Sarasvathy et al., 2003). In particular, knowledge about potential customer needs and problems that may present opportunities is vital (Webb et al., 2010). Whereas the role of prior knowledge of customer problems (Shane, 2003; Shepherd and DeTienne, 2005) and positioning oneself in a so-called knowledge corridor (Fiet, 1996) has been researched, the role of opportunity characteristics and their interaction with customer-related mechanisms that facilitate and hinder opportunity identification has received scant attention.
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Nowadays, Workflow Management Systems (WfMSs) and, more generally, Process Management Systems (PMPs) are process-aware Information Systems (PAISs), are widely used to support many human organizational activities, ranging from well-understood, relatively stable and structures processes (supply chain management, postal delivery tracking, etc.) to processes that are more complicated, less structured and may exhibit a high degree of variation (health-care, emergency management, etc.). Every aspect of a business process involves a certain amount of knowledge which may be complex depending on the domain of interest. The adequate representation of this knowledge is determined by the modeling language used. Some processes behave in a way that is well understood, predictable and repeatable: the tasks are clearly delineated and the control flow is straightforward. Recent discussions, however, illustrate the increasing demand for solutions for knowledge-intensive processes, where these characteristics are less applicable. The actors involved in the conduct of a knowledge-intensive process have to deal with a high degree of uncertainty. Tasks may be hard to perform and the order in which they need to be performed may be highly variable. Modeling knowledge-intensive processes can be complex as it may be hard to capture at design-time what knowledge is available at run-time. In realistic environments, for example, actors lack important knowledge at execution time or this knowledge can become obsolete as the process progresses. Even if each actor (at some point) has perfect knowledge of the world, it may not be certain of its beliefs at later points in time, since tasks by other actors may change the world without those changes being perceived. Typically, a knowledge-intensive process cannot be adequately modeled by classical, state of the art process/workflow modeling approaches. In some respect there is a lack of maturity when it comes to capturing the semantic aspects involved, both in terms of reasoning about them. The main focus of the 1st International Workshop on Knowledge-intensive Business processes (KiBP 2012) was investigating how techniques from different fields, such as Artificial Intelligence (AI), Knowledge Representation (KR), Business Process Management (BPM), Service Oriented Computing (SOC), etc., can be combined with the aim of improving the modeling and the enactment phases of a knowledge-intensive process. The 1st International Workshop on Knowledge-intensive Business process (KiBP 2012) was held as part of the program of the 2012 Knowledge Representation & Reasoning International Conference (KR 2012) in Rome, Italy, in June 2012. The workshop was hosted by the Dipartimento di Ingegneria Informatica, Automatica e Gestionale Antonio Ruberti of Sapienza Universita di Roma, with financial support of the University, through grant 2010-C26A107CN9 TESTMED, and the EU Commission through the projects FP7-25888 Greener Buildings and FP7-257899 Smart Vortex. This volume contains the 5 papers accepted and presented at the workshop. Each paper was reviewed by three members of the internationally renowned Program Committee. In addition, a further paper was invted for inclusion in the workshop proceedings and for presentation at the workshop. There were two keynote talks, one by Marlon Dumas (Institute of Computer Science, University of Tartu, Estonia) on "Integrated Data and Process Management: Finally?" and the other by Yves Lesperance (Department of Computer Science and Engineering, York University, Canada) on "A Logic-Based Approach to Business Processes Customization" completed the scientific program. We would like to thank all the Program Committee members for the valuable work in selecting the papers, Andrea Marrella for his valuable work as publication and publicity chair of the workshop, and Carola Aiello and the consulting agency Consulta Umbria for the organization of this successful event.
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The cultural and creative industries contribute to the knowledge economy by their role in reproducing cultural knowledge and through provision of entertainment, experience and leisure goods with cultural content, for which they are widely acknowledged as suffering serious market failure problems (Baumol and Bowen, 1966; Throsby and Withers, 1979). But they also contribute to the innovation process, an aspect that has only recently been appreciated. Specifically, the creative industries are a driver of the knowledge economy by their contribution to the innovation process on the demand side of consumer uptake of new ideas and by their facilitation of consumer-producer interaction. The creative industries are, in this respect, a legitimate part of the innovation system of a knowledge economy.
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Globalization stimulated demand for transnational higher education. However, little is known about how transnational programs can facilitate knowledge transfer between the partner universities—something that is often implied in the partnership arrangement. For the purpose of this paper transnational programs will be limited to dual degree programs between Indonesian and Australian universities, which, in recent years have been rising. Nevertheless, the discussion and synthesis may have value to other transnational programs. Situating the knowledge transfer in the wider context of globalization of higher education and the current reforms in Indonesian education, the paper acknowledges the tension between the need to generate revenue and the ideals of facilitating knowledge transfer and capacity development for Indonesian universities. Drawing on a detailed review of research findings in the business and education sector literature, this paper presents a conceptual framework that may be used to analyze knowledge transfer between Indonesian and Australian universities. Such investigations delineate the significant drivers underlying transnational programs for supporting knowledge transfer. The proposed framework incorporates the types of knowledge, knowledge transfer mechanisms, and the processes. It also considers how the inter-university antecedents may affect the potential for knowledge transfer between the universities. A discussion of how the framework may be used to implemented knowledge transfer concludes this paper.
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Background: General practitioners (GPs) and nurses are ideally placed to address the significant unmet demand for the treatment of cannabis-related problems given the numbers of people who regularly seek their care. The aim of this study was to evaluate differences between GPs and nurses’ perceived knowledge, beliefs, and behaviors toward cannabis use and its screening and management. Methods: This study involved 161 nurses and 503 GPs who completed a survey distributed via conference satchels to delegates of Healthed seminars focused on topics relevant to women and children’s health. Differences between GPs and nurses were analyzed using χ2- tests and two-sample t-tests, while logistic regression examined predictors of service provision. Results: GPs were more likely than nurses to have engaged in cannabis-related service provision, but also more frequently reported barriers related to time, interest, and having more important issues to address. Nurses reported less knowledge, skills, and role legitimacy. Perceived screening skills predicted screening and referral to alcohol and other drug (AOD) services, while knowing a regular user increased the likelihood of referrals only. Conclusions: Approaches to increase cannabis-related screening and intervention may be improved by involving nurses, and by leveraging the relationship between nurses and doctors, in primary care.
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This paper reviews electricity consumption feedback literature to explore the potential of electricity feedback to affect residential consumers’ electricity usage patterns. The review highlights a substantial amount of literature covering the debate over the effectiveness of different feedback criteria to residential customer acceptance and overall conservation and peak demand reduction. Researchers studying the effects of feedback on everyday energy use have observed substantial variation in effect size, both within and between studies. Although researchers still continue to question the types of feedback that are most effective in encouraging conservation and peak load reduction, some trends have emerged. These include that feedback be received as quickly as possible to the time of consumption; be related to a standard; be clear and meaningful and where possible both direct and indirect feedback be customised to the customer. In general, the literature finds that feedback can reduce electricity consumption in homes by 5 to 20 per cent, but that significant gaps remain in our knowledge of the effectiveness and cost benefit of feedback.
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Knowledge about customers is vital for supply chains in order to ensure customer satisfaction. In an ideal supply chain environment, supply chain partners are able to perform planning tasks collaboratively, because they share information. However, customers are not always able or willing to share information with their suppliers. End consumers, on the one hand, do not usually provide a retail company with demand information. On the other hand, industrial customers might consciously hide information. Wherever a supply chain is not provided with demand forecast information, it needs to derive these demand forecasts by other means. Customer Relationship Management provides a set of tools to overcome informational uncertainty. We show how CRM and SCM information can be integrated on the conceptual as well as technical levels in order to provide supply chain managers with relevant information.