395 resultados para Business Model Adaption .
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This paper introduces the smooth transition logit (STL) model that is designed to detect and model situations in which there is structural change in the behaviour underlying the latent index from which the binary dependent variable is constructed. The maximum likelihood estimators of the parameters of the model are derived along with their asymptotic properties, together with a Lagrange multiplier test of the null hypothesis of linearity in the underlying latent index. The development of the STL model is motivated by the desire to assess the impact of deregulation in the Queensland electricity market and ascertain whether increased competition has resulted in significant changes in the behaviour of the spot price of electricity, specifically with respect to the occurrence of periodic abnormally high prices. The model allows the timing of any change to be endogenously determined and also market participants' behaviour to change gradually over time. The main results provide clear evidence in support of a structural change in the nature of price events, and the endogenously determined timing of the change is consistent with the process of deregulation in Queensland.
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Purpose This paper aims to set out a new hierarchical and differentiated model of social marketing principles, concepts and techniques that builds on, but supersedes, the existing lists of non-equivalent and undifferentiated benchmark criteria. Design/methodology/approach This is a conceptual paper that proposes a hierarchical model of social marketing principles, concepts and techniques. Findings This new delineation of the social marketing principle, its four core concepts and five techniques, represents a new way to conceptualize and recognize the different elements that constitute social marketing. This new model will help add to and further the development of the theoretical basis of social marketing, building on the definitional work led by the International Social Marketing Association (iSMA), Australian Association of Social Marketing (AASM) and European Social Marketing Association (ESMA). Research limitations/implications This proposed model offers a foundation for future research to expand upon. Further research is recommended to empirically test the proposed model. Originality/value This paper seeks to advance the theoretical base of social marketing by making a reasoned case for the need to differentiate between principles, concepts and techniques when seeking to describe social marketing.
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This work is a MATLAB/Simulink model of a controller for a three-phase, four-wire, grid-interactive inverter. The model provides capacity for simulating the performance of power electroinic hardware, as well as code generation for an embedded controller. The implemented hardware topology is a three-leg bridge with a neutral connection to the centre-tap of the DC bus. An LQR-based current controller and MAF-based phase detector are implemented. The model is configured for code generation for a Texas Instruments TMS320F28335 Digital Signal Processor (DSP).
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A wide range of decision-making models have been offered to assist in making ethical decisions in the workplace. Those that are based on normative moral frameworks typically include elements of traditional moral philosophy such as consequentialist and/or deontologicalethics. This paper suggests an alternative model drawing on Jean-Paul Sartres existentialism. Accordingly, the model focuses on making decisions in full awareness of ones freedom and responsibility. The steps of the model are intended to encourage reflection of ones projects and ones situation and the possibility of refusing the expectations of others. A case study involving affirmative action in South Africa is used to demonstrate the workings of the model and a number of strengths and weaknesses are identified. Despite several weaknesses that can be raised regarding existential ethics, the models success lies in the way that it reframes ethical dilemmas in terms of individual freedom and responsibility, and in its acceptance and analysis of subjective experiences and personal situations
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Over the past decades, universities have increasingly become ambidextrous organizations reconciling scientific and commercial missions. In order to manage this ambidexterity, technology transfer offices (TTOs) were established in most universities. This paper studies a specific, often implemented, but rather understudied type of TTO, namely a hybrid TTO model uniting centralized and decentralized levels. Employing a qualitative research design, we examine how and why the two TTO levels engage in diverse boundary spanning activities to help nascent spin-off companies move through the pre-spin-off process. Our research identifies differences in the types of boundary spanning activities that centralized and decentralized TTOs perform and in the parties they engage with. We find geographical, technological and organizational proximity to be important antecedents of the TTOs engagement in external and internal boundary spanning activities. These results have important implications for both academics and practitioners interested in university technology transfer through spin-off creation.
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Purpose Performance heterogeneity between collaborative infrastructure projects is typically examined by considering procurement systems and their governance mechanisms at static points in time. The literature neglects to consider the impact of dynamic learning capability, which is thought to reconfigure governance mechanisms over time in response to evolving market conditions. This conceptual paper proposes a new model to show how continuous joint learning of participant organisations improves project performance. Design/methodology/approach There are two stages of conceptual development. In the first stage, the management literature is analysed to explain the Standard Model of dynamic learning capability that emphasises three learning phases for organisations. This Standard Model is extended to derive a novel Circular Model of dynamic learning capability that shows a new feedback loop between performance and learning. In the second stage, the construction management literature is consulted, adding project lifecycle, stakeholder diversity and three organisational levels to the analysis, to arrive at the Collaborative Model of dynamic learning capability. Findings The Collaborative Model should enable construction organisations to successfully adapt and perform under changing market conditions. The complexity of learning cycles results in capabilities that are imperfectly imitable between organisations, explaining performance heterogeneity on projects. Originality/value The Collaborative Model provides a theoretically substantiated description of project performance, driven by the evolution of procurement systems and governance mechanisms. The Models empirical value will be tested in future research.
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The motivation for this analysis is the recently developed Excellence in Research for Australia (ERA) program developed to assess the quality of research in Australia. The objective is to develop an appropriate empirical model that better represents the underlying production of higher education research. In general, past studies on university research performance have used standard DEA models with some quantifiable research outputs. However, these suffer from the twin maladies of an inappropriate production specification and a lack of consideration of the quality of output. By including the qualitative attributes of peer-reviewed journals, we develop a procedure that captures both quality and quantity, and apply it using a network DEA model. Our main finding is that standard DEA models tend to overstate the research efficiency of most Australian universities.
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A study was undertaken to examine further the effects of perceived work control on employee adjustment. On the basis of the stress antidote model, it was proposed that high levels of prediction, understanding, and control of work-related events would have direct, indirect, and interactive effects on levels of employee adjustment. These hypotheses were tested in a short-term longitudinal study of 137 employees of a large retail organization. The stress antidote measures appeared to be indirectly related to employee adjustment, via their effects on perceptions of work stress. There was weak evidence for the proposal that prediction, understanding, and control would buffer the negative effects of work stress. Additional analyses indicated that the observed effects of prediction, understanding, and control were independent of employees' generalized control beliefs. However, there was no support for the proposal that the effects of the stress antidote measures would be dependent on employees' generalized control beliefs.
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There is widespread agreement that entrepreneurial skills are crucial for young people today, yet there are few studies of high school students engaging in entrepreneurship education that might prepare them for music industry careers. This study has been developed in response to these challenges. It explores a group of high school students (15 17 years) who alongside their teacher, have co-designed, developed and driven a new business venture, Youth Music Industries (YMI) since 2010. This venture staged cycles of differently scaled events featuring young artists for a young audience. The project was designed to give students a real business situation for developing their project management skills and a broader understanding of working in the music industry. Informed by concepts of social capital and communities of practice, the study examines the process of learning with and through others. This high-stakes environment increased their sense of presence and participation and made it possible for these young people to distribute expertise and learn from each other in a reciprocal and more democratic way. The ongoing success of this organisation can be attributed to the entrepreneurial competencies students developed. The resulting model and design principles talk to an ongoing challenge that has been identified in music education, and creative industries more generally. These principles offer a way forward for other music and creative industries educators or researchers interested in developing models of, and designs for, nurturing an entrepreneurial mindset.
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In this paper we illustrate a set of features of the Apromore process model repository for analyzing business process variants. Two types of analysis are provided: one is static and based on differences on the process control flow, the other is dynamic and based on differences in the process behavior between the variants. These features combine techniques for the management of large process model collections with those for mining process knowledge from process execution logs. The tool demonstration will be useful for researchers and practitioners working on large process model collections and process execution logs, and specifically for those with an interest in understanding, managing and consolidating business process variants both within and across organizational boundaries.
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The air transport industry is a complex environment facing many challenges while coping with changing global imperatives. International airport passenger facilitation is a part of the socio-technical system where these challenges manifest, impacting businesses in terms of time, cost and quality. This research inductively develops an extensible configurable reference model by capturing and merging the cross-organisational facilitation process from five Australian airports. The reference model can be filtered according to the contextual needs of airport users to inform relevant and accurate business process design. The domain and methodological contributions constitute the first reported application of questionnaire-based configurability to airport processes.
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Liposome-protamine-DNA nanoparticles (LPD) are safe, effective, and non-toxic adjuvants that induce Th1-like immune responses. We hypothesized that encapsulation of allergens into liposomes could be an appropriate option for immunotherapy. The present study evaluated the immunotherapeutic potential of a recombinant hybrid molecule (rHM) encapsulated in LPD nanoparticles in a murine model of Chenopodium album allergy. BALB/c mice were sensitized with the allergen in alum, and the immunotherapy procedure was performed by subcutaneous injections of LPD-rHM, rHM, or empty LPD at weekly intervals. Sensitized mice developed a Th2-biased immune response characterized by strong specific IgG1 and IgE production, IL-4, and the transcription factor GATA3 in spleen cell cultures. Treatment with the LPD-rHM resulted in a reduction in IgE and a marked increase in IgG2a. The LPD-rHM induced allergen-specific responses with relatively high interferon-gamma production, as well as expression of the transcription factor T-bet in stimulated splenocytes. In addition, lymphoproliferative responses were higher in the LPD-rHM-treated mice than in the other groups. Removal of the nanoparticles from the rHM resulted in a decrease in the allergen's immunogenicity. These results indicate that the rHM complexed with LPD nanoparticles has a marked suppressive effect on the allergic response and caused a shift toward a Th1 pathway.
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Stochastic (or random) processes are inherent to numerous fields of human endeavour including engineering, science, and business and finance. This thesis presents multiple novel methods for quickly detecting and estimating uncertainties in several important classes of stochastic processes. The significance of these novel methods is demonstrated by employing them to detect aircraft manoeuvres in video signals in the important application of autonomous mid-air collision avoidance.
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Nondeclarative memory and novelty processing in the brain is an actively studied field of neuroscience, and reducing neural activity with repetition of a stimulus (repetition suppression) is a commonly observed phenomenon. Recent findings of an opposite trend specifically, rising activity for unfamiliar stimuliquestion the generality of repetition suppression and stir debate over the underlying neural mechanisms. This letter introduces a theory and computational model that extend existing theories and suggests that both trends are, in principle, the rising and falling parts of an inverted U-shaped dependence of activity with respect to stimulus novelty that may naturally emerge in a neural network with Hebbian learning and lateral inhibition. We further demonstrate that the proposed model is sufficient for the simulation of dissociable forms of repetition priming using real-world stimuli. The results of our simulation also suggest that the novelty of stimuli used in neuroscientific research must be assessed in a particularly cautious way. The potential importance of the inverted-U in stimulus processing and its relationship to the acquisition of knowledge and competencies in humans is also discussed
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Objective: The aim of this study was to develop a model capable of predicting variability in the mental workload experienced by frontline operators under routine and nonroutine conditions. Background: Excess workload is a risk that needs to be managed in safety-critical industries. Predictive models are needed to manage this risk effectively yet are difficult to develop. Much of the difficulty stems from the fact that workload prediction is a multilevel problem. Method: A multilevel workload model was developed in Study 1 with data collected from an en route air traffic management center. Dynamic density metrics were used to predict variability in workload within and between work units while controlling for variability among raters. The model was cross-validated in Studies 2 and 3 with the use of a high-fidelity simulator. Results: Reported workload generally remained within the bounds of the 90% prediction interval in Studies 2 and 3. Workload crossed the upper bound of the prediction interval only under nonroutine conditions. Qualitative analyses suggest that nonroutine events caused workload to cross the upper bound of the prediction interval because the controllers could not manage their workload strategically. Conclusion: The model performed well under both routine and nonroutine conditions and over different patterns of workload variation. Application: Workload prediction models can be used to support both strategic and tactical workload management. Strategic uses include the analysis of historical and projected workflows and the assessment of staffing needs. Tactical uses include the dynamic reallocation of resources to meet changes in demand.