876 resultados para patronage forecasting


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We quantify the conditions that might trigger wide spread adoption of alternative fuel vehicles (AFVs) to support energy policy. Empirical review shows that early adopters are heterogeneous motivated by financial benefits, environmental appeal, new technology, and vehicle reliability. A probabilistic Monte Carlo simulation model is used to assess consumer heterogeneity for early and mass market adopters. For early adopters full battery electric vehicles (BEVs) are competitive but unable to surpass diesels or hybrids due to purchase price premium and lack of charging availability. For mass adoption, simulations indicate that if the purchase price premium of a BEV closes to within 20% of an in-class internal combustion engine (ICE) vehicle, combined with a 60% increase in refuelling availability relative to the incumbent system, BEVs become competitive. But this depends on a mass market that values the fuel economy and CO2 reduction benefits associated with BEVs. We also find that the largest influence on early adoption is financial benefit rather than pro-environmental behaviour suggesting that AFVs should be marketed by appealing to economic benefits combined with pro-environmental behaviour to motivate adoption. Monte Carlo simulations combined with scenarios can give insight into diffusion dynamics for other energy demand-side technologies. © 2012 Elsevier Inc.

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When considering the potential uptake and utilization of technology management tools by industry, it must be recognized that companies face the difficult challenges of selecting, adopting and integrating individual tools into a toolkit that must be implemented within their current organizational processes and systems. This situation is compounded by the lack of sound advice on integrating well-founded individual tools into a robust toolkit that has the necessary degree of flexibility such that they can be tailored for application to specific problems faced by individual organizations. As an initial stepping stone to offering a toolkit with empirically proven utility, this paper provides a conceptual foundation to the development of toolkits by outlining an underlying philosophical position based on observations from multiple research and commercial collaborations with industry. This stance is underpinned by a set of operationalized principles that can offer guidance to organizations when deciding upon the appropriate form, functions and features that should be embodied by any potential tool/toolkit. For example, a key objective of any tool is to aid decision-making and a core set of powerful, flexible, scaleable and modular tools should be sufficient to allow users to generate, explore, shape and implement possible solutions across a wide array of strategic issues. From our philosophical stance, the preferred mode of engagement is facilitated workshops with a participatory process that enables multiple perspectives and structures the conversation through visual representations in order to manage the cognitive load in the collaborative environment. The generic form of the tools should be configurable for the given context and utilized in a lightweight manner based on the premise of 'start small and iterate fast'. © 2012 Elsevier Inc.

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Technological investment is a key driver of innovation and the evaluation of technology potential is becoming increasingly important in this context. There is a range of approaches and tools for developing an understanding of the value of technology. However the process of communicating this potential to possible customers is not well documented in terms of theory and practice and falls outside the skill set of many technologists. This paper seeks to integrate the concepts of marketing and consultative selling into making business cases for new technologies. It describes an exploratory study which results in an outline process activity model for technologists wishing to build an effective business case for securing investment internally or when selling a technology externally. Following a review of literature, we suggest that there is potential to learn from market research and consultative sales techniques, and propose a five step process. The work has been industrially validated and forms a novel foundation for further development. © 2012 Elsevier Inc.

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Within strategic technology management and innovation, often stakeholders extrapolate past industry dynamics, trends and patterns into the future. One frequently used concept is that of 'lifecycles' - an analogy of a sequence of stages encountered by living organisms. Lifecycle terms - such as technology, product, industry - are frequently used interchangeably and without clear definition. Within the interdisciplinary context of technology management and forecasting, this juxtaposition of dynamics can create confusion rather than simplification. This paper explores some of the dynamics typically associated with technology-based industries, illustrated with data from the early US automotive industry. A wide range of dimensions are seen to have potential to influence the path of industry development, and technology roadmapping architecture is used to present a simplified visualisation of some of these. Stakeholders need to consider the units of analysis, causality and synchronicity of relevant different dynamics, rather than isolated lifecycles. Some graphical curves represent simple aggregation of components; other dynamics have significant impact, but incur time lags, rather than being superimposed. To optimise alignment of the important dimensions within any technology development, and for future strategy decisions, understanding these interactions is critical. © 2012 Elsevier Inc.

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Idea Competitions (ICs) are becoming a popular mechanism chosen by firms to perform Open Innovation. They are a way to engage with external sources of knowledge such as individual entrepreneurs and small firms who are asked to submit ideas and compete for a prize. However, little is known about the success of ICs as acquisition mechanisms. The researchers conducted interviews in five multinational companies to evaluate the effects of using ICs as an acquisition mechanism. Although still preliminary, the results of this study show that the success of ICs as an acquisition mechanism remains uncertain because their output (i.e. the number of ideas acquired) is often low compared to the input (i.e. the number of ideas submitted) and effort required to run them (e.g. to vet ideas). Across the cases observed, ICs appear to be more successful at identifying and acquiring early-stage ideas, particularly those outside the current business focus. The study shows that ICs deliver other functional benefits such as improved intelligence and public relations and that these need to be considered as part of the evaluation of the IC's success. The paper concludes by discussing the conditions in which ICs are implemented and the implications for Open Innovation theory. © 2013 Elsevier Inc.

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The paper demonstrates the nonstationarity of algal population behaviors by analyzing the historical populations of Nostocales spp. in the River Darling, Australia. Freshwater ecosystems are more likely to be nonstationary, instead of stationary. Nonstationarity implies that only the near past behaviors could forecast the near future for the system. However, nonstionarity was not considered seriously in previous research efforts for modeling and predicting algal population behaviors. Therefore the moving window technique was incorporated with radial basis function neural network (RBFNN) approach to deal with nonstationarity when modeling and forecasting the population behaviors of Nostocales spp. in the River Darling. The results showed that the RBFNN model could predict the timing and magnitude of algal blooms of Nostocales spp. with high accuracy. Moreover, a combined model based on individual RBFNN models was implemented, which showed superiority over the individual RBFNN models. Hence, the combined model was recommended for the modeling and forecasting of the phytoplankton populations, especially for the forecasting.

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本文用黄土高原长武农业生态试验站的冬小麦长期定位试验资料对改进的随机动力学水平衡模型进行了准确性检验 .从模型对参数反映的敏感性分析和模型计算值与数值模型WAVES的比较 ,以及模型对黄土区旱作高生产力的水分环境效应的评价结果 ,均证明改进的随机动力学水平衡模型能比较准确地预测一定生产力水平、特定生态系统平衡体系水均衡要素的定量分配和土壤含水量的动态变化 .

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Beijing University of Technology (BJUT); Beijing Municipal Lab of Brain Informatics; Chinese Society of Radiology; National Natural Science Foundation of China (NSFC); State Administration of Foreign Experts Affairs

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鉴于多重分形理论在定量描述复杂系统非线性运行规律方面具有的独特优势,将多重分形理论引入到工况特征识别研究中来,确认了水泥回转窑窑电流信号的多重分形特性。在此基础上,研究了窑电流多重分形谱参数随工况变化的情况,发现多重分形谱参数的变化趋势与回转窑内工况状态的变化趋势之间具有较强的关联性,进而提出了基于多重分形谱参数进行水泥回转窑异常工况特征提取的新方法,为水泥生产过程中工况状态的在线监控和预报提供了有力支持。

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采用多种科学预测方法与财政经济实际相结合的方式建立了一个综合的财政收支系统动力学模型.这个模型集中了时间序列分析模型,灰色系统预测模型的参数综合性强和系统动力学模型结构分明,用动态反馈方式预测系统发展变化的特点,对东北两大城市预算内财政收支“八五”计划指标进行了全面定量的预测与分析,得到了很好的应用效果。

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本文提出了一种简化的多变量随机系统状态模型参数在线辨识方法。与最小二乘自适应递推算法比较,不仅需要辨识的参数减少,而且针对一类模型参数缓慢变化的系统,可以通过选择不同的遗忘因子序列来控制参数变化的幅度,解决了电力系统负荷预报中季节模型的老化问题。本方法基于带有随机噪声状态模型的典范型,大大节省了计算机的运算量和存贮容量,适于微处理机的在线应用。