479 resultados para Interdisciplinary approach to knowledge


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Australian preschool teachers’ use of Web-searching in their classroom practice was examined (N = 131). Availability of Internet-enabled digital technology and the contribution of teacher demographic characteristics, comfort with digital technologies and beliefs about their use were assessed. Internet-enabled technologies were available in 53% (n = 69) of classrooms. Within these classrooms, teacher age and beliefs predicted Web-searching practice. Although comfortable with digital access of knowledge in their everyday life, teachers reported less comfort with Web-searching in the context of their classroom practice. The findings identify the provision of Internet-enabled technologies and professional development as actions to support effective and confident inclusion of Web-searching in classrooms. Such actions are necessary to align with national policy documents that define acquisition of digital literacies as a goal and assert digital access to knowledge as an issue of equity.

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Electricity businesses across Australia are facing many market disruptions, such as the increasing demand from the rapid uptake of domestic air conditioners and the contrasting problematic generation from solar power connections to the grid. In this context, the opportunity to proactively leverage forthcoming technological advances in battery storage and electric vehicles to address the steeply rising cost of electricity supply has emerged. This research explores a design approach to support a business to navigate such disruptions in the current market.This study examines a design-led approach to innovation conducted over a ten month action research study within a large, risk-averse firm in the Australian energy sector. This article presents results describing a current foresight gap within the business; the response of the business to using design-led innovation to address this issue; and the tools, approaches and processes used. The business responses indicate their perception of the value of qualitative customer engagement as a path to addressing, and potentially benefiting from, disruptive innovation. It is anticipated that these results will further business model development within the company, and assist in leveraging disruptive innovations for this industry participant, thus limiting future increases in the cost of electricity supply for customers in Australia.

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This paper explores that application of evolutionary approaches to the study of entrepreneurship. It is argued an evolutionary theory of entrepreneurship must give as much concern to the foundations of evolutionary thought as it does the nature entrepreneurship. The central point being that we must move beyond a debate or preference of the natural selection and adaptationist viewpoints. Only then can the interrelationships between individuals, firms, populations and the environments within which they interact be better appreciated.

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Management and business literature affirm the role played by stakeholders in corporate social responsibility (CSR) practices as crucial, but what constitutes a true business–society partnership remains relatively unexplored. This paper aims to improve scholarly and management understanding beyond the usual managers’ perceptions on salience attributes, to include how stakeholders can acquire missing attributes to inform a meaningful partnership. In doing this, a model is proposed which conceptualises CSR practices and outcomes within the frameworks of stakeholder salience via empowerment, sustainable corporate social performances and partnership quality. A holistic discussion leads to generation of propositions on stakeholder salience management, corporate social performance, corporate–community partnership systems and CSR practices, which have both academic and management implications.

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Symposium co-ordinated by The International Network for Food and Obesity/NCDs Research, Monitoring and Action Support (INFORMAS) Purpose Global monitoring of the price and affordability of foods, meals and diets is urgently needed. There are major methodological challenges in developing robust, cost-effective, standardized, and policy relevant tools, pertinent to nutrition, obesity, and diet-related non-communicable diseases and their inequalities. There is increasing pressure to take into account environmental sustainability. Changes in price differentials and affordability need to be comparable between and within countries and over time. Robust tools could provide baseline data for monitoring and evaluating structural, economic and social policies at the country/regional and household levels. INFORMAS offers one framework for consideration.

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Stochastic volatility models are of fundamental importance to the pricing of derivatives. One of the most commonly used models of stochastic volatility is the Heston Model in which the price and volatility of an asset evolve as a pair of coupled stochastic differential equations. The computation of asset prices and volatilities involves the simulation of many sample trajectories with conditioning. The problem is treated using the method of particle filtering. While the simulation of a shower of particles is computationally expensive, each particle behaves independently making such simulations ideal for massively parallel heterogeneous computing platforms. In this paper, we present our portable Opencl implementation of the Heston model and discuss its performance and efficiency characteristics on a range of architectures including Intel cpus, Nvidia gpus, and Intel Many-Integrated-Core (mic) accelerators.

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Online groups rely on contributions from their members to flourish, but in the context of behaviour change individuals are typically reluctant to participate actively before they have changed successfully. We took inspiration from CSCW research on objects to address this problem by shifting the focus of online participation from the exchange of personal experiences to more incidental interactions mediated by objects that offer support for change. In this article we describe how we designed, deployed and studied a smartphone application that uses different objects, called distractions and tips, to facilitate social interaction amongst people trying to quit smoking. A field study with 18 smokers revealed different forms of interaction: purely instrumental interactions with the objects, subtle engagement with other users through receptive and covert interactions, as well as explicit interaction with other users through disclosure and mutual support. The distraction objects offered a stepping-stone into interaction, whereas the tips encouraged interaction with the people behind the objects. This understanding of interaction through objects complements existing frameworks of online participation and adds to the current discourse on object-centred sociality. Furthermore, it provides an alternative approach to the design of online support groups, which offers the users enhanced control about the information they share with other users. We conclude by discussing how researchers and practitioners can apply the ideas of interaction around objects to other domains where individuals may have a simultaneous desire and reluctance to interact.

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Affordance is an important concept in the field of human–computer interaction. There are various interpretations of affordances, often extending the original notion of James J. Gibson. Often the treatment of affordances in the current human–computer interaction literature has been a one-to-one relationship between a user and an artefact. We believe that the social and cultural contexts within which an artefact is situated affect the way in which the artefact is used and the notion of affordance needs to be seen as a dynamic, always emerging relationship between people and their environment. Using a Structuration Theory approach, we conceptualize the notion of affordance at a much broader level, encompassing social and cultural aspects. We suggest that affordances should be seen at three levels: single user, organizational (or work group) and societal. Focusing on the organizational level affordances, we provide details of several important factors that affect the emergence of affordances. - This article provides a new perspective on the discourse of affordance with the use of Structuration Theory. - It shows how affordance can be understood as ‘use’ in situated practices (i.e. ‘technology-in-practice’) - The Structuration Theory approach to affordances is showcased using two case studies.

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- Purpose This paper aims to investigate how direct mail consumption contributes to brand relationship quality. Store flyers and other direct mailings continue to play a significant role in many companies’ communication strategies. Research on this topic predominantly investigates driving store traffic and sales. Less is known regarding the consumer side, such as the value that consumers may derive from the consumption of direct mailings and the effects of such a value on brand relationship quality. To address this limitation, this paper tests a causal model of the contribution of direct mail value to brand commitment, drawing on a value framework that integrates social theory of engagement regimes and literature on experiential customer value. - Design/methodology/approach The empirical work of this paper is based on a rigorous four-study mixed methods design, involving qualitative study, confirmatory factor analysis and partial least squares structural modeling. - Findings The authors develop two second-order formatively designed scales – familiar value and planned value scales – that illustrate the role of engagement regimes in consumer behavior. Although both types of value contribute equally to direct mail attachment, they exert contrasting effects on other mediational consumer responses, such as reading and gratitude. Finally, the proposed theoretical model appears to be robust in predicting customers’ brand commitment. - Research limitations/implications This study provides new insights into the research on consumer value and brand relational communication. - Originality/value This study is the first to consider consumer benefits from the social perspective of engagement regimes.

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Gas fermentation using acetogenic bacteria offers a promising route for the sustainable production of low carbon fuels and commodity chemicals from abundant, inexpensive C1 feedstocks including industrial waste gases, syngas, reformed methane or methanol. Clostridium autoethanogenum is a model gas fermenting acetogen that produces fuel ethanol and 2,3-butanediol, a precursor for nylon and rubber. Acetogens have already been used in large scale industrial fermentations, they are ubiquitous and known to play a prominent role in the global carbon cycle. Still, they are considered to live on the thermodynamic edge of life and potential energy constraints when growing on C1 gases pose a major challange for the commercial production of fuels and chemicals. We have developed a systematic platform to investigate acetogenic energy metabolism, exemplified here by experiments contrasting heterotrophic and autotrophic metabolism. The platform is built from complete omics technologies, augmented with genetic tools and complemented by a manually curated genome-scale mathematical model. Together the tools enable the design and development of new, energy efficient pathways and strains for the production of chemicals and advanced fuels via C1 gas fermentation. As a proof-of-platform, we investigated heterotrophic growth on fructose versus autotrophic growth on gas that demonstrate the role of the Rnf complex and Nfn complex in maintaining growth using the Wood–Ljungdahl pathway. Pyruvate carboxykinase was found to control the rate-limiting step of gluconeogenesis and a new specialized glyceraldehyde-3-phosphate dehydrogenase was identified that potentially enhances anabolic capacity by reducing the amount of ATP consumed by gluconeogenesis. The results have been confirmed by the construction of mutant strains.

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The problem of unsupervised anomaly detection arises in a wide variety of practical applications. While one-class support vector machines have demonstrated their effectiveness as an anomaly detection technique, their ability to model large datasets is limited due to their memory and time complexity for training. To address this issue for supervised learning of kernel machines, there has been growing interest in random projection methods as an alternative to the computationally expensive problems of kernel matrix construction and sup-port vector optimisation. In this paper we leverage the theory of nonlinear random projections and propose the Randomised One-class SVM (R1SVM), which is an efficient and scalable anomaly detection technique that can be trained on large-scale datasets. Our empirical analysis on several real-life and synthetic datasets shows that our randomised 1SVM algorithm achieves comparable or better accuracy to deep auto encoder and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.

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In this manuscript, we consider the impact of a small jump-type spatial heterogeneity on the existence of stationary localized patterns in a system of partial dierential equations in one spatial dimension...