850 resultados para Automotive demand


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This thesis examines the question why the automotive mode and the large technological system it creates, continues to dominate urban transport systems despite the availability of more cost-efficient alternatives. A number of theoretical insights are developed into the way these losses evolve from path dependent growth, and lead to market failure and lock-in. The important role of asymmetries of influence is highlighted. A survey of commuters in Jakarta Indonesia is used to provide a measure of transport modal lock-in (TML) in a developing country conurbation. A discrete choice experiment is used to provide evidence for the thesis central hypothesis that in such conurbations there is a high level of commuter awareness of the negative externalities generated by TML which can produce a strong level of support for its reversal. Why TML nevertheless remains a strong and durable feature of the transport system is examined with reference to the role of asymmetries of influence.

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This thesis demonstrates how patients' perceived urgency affects their decision to use public hospital emergency departments. The findings inform public health policy solutions aimed at reducing rapid growth in emergency department utilisation which results in congestion and affects the safety, satisfaction, and the quality of care. This research identified that patients attending emergency departments did so based on the perception of their own health status and beliefs that emergency departments were the most suitable location for their care. Blaming patients as "frequent flyers" or "inappropriate users" ignores the complex and multi-factorial nature of the genuine need for urgent medical care felt by patients.

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Automotive interactive technologies represent an exemplar challenge for user experience (UX) designers, as the concerns for aesthetics, functionality and usability add up to the compelling issues of safety and cognitive demand. This extended abstract presents a methodology for the user-centred creation and evaluation of novel in-car applications, involving real users in realistic use settings. As a case study, we present the methodologies of an ideation workshop in a simulated environment and the evaluation of six design idea prototypes for in-vehicle head up display (HUD) applications using a semi-naturalistic drive. Both methods rely on video recordings of real traffic situations that the users are familiar with and/or experienced themselves. The extended abstract presents experiences and results from the evaluation and reflection on our methods.

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In an industry worth more than €500 billion annually, producing more than 80 million vehicles worldwide each year and consisting of over 50 major manufacturers worldwide, the automotive industry represents a lucrative but highly competitive manufacturing industry (Deloitte, 2009a; European Automobile Manufacturers Association, 2012). With sales falling in Europe in 2013 for the sixth consecutive year (Boston and Curtin, 2014), automotive manufacturers are increasingly turning to new strategies to retain their share of sales in a contracting market. Some strategies have focused on the industry approach to manufacturing, namely, a technically focused push for a build-toorder process rather than the current build-to-stock approach in order to reduce overall value-chain costs and to increase efficiency (Parry and Roehrich, 2013, p. 13). However, others stress a more customer-orientated approach, striving to develop products that meet customer requirements (Oliver Wyman Group, 2007).

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Supplying peak energy demand in a cost effective, reliable manner is a critical focus for utilities internationally. Successfully addressing peak energy concerns requires understanding of all the factors that affect electricity demand especially at peak times. This paper is based on past attempts of proposing models designed to aid our understanding of the influences on residential peak energy demand in a systematic and comprehensive way. Our model has been developed through a group model building process as a systems framework of the problem situation to model the complexity within and between systems and indicate how changes in one element might flow on to others. It is comprised of themes (social, technical and change management options) networked together in a way that captures their influence and association with each other and also their influence, association and impact on appliance usage and residential peak energy demand. The real value of the model is in creating awareness, understanding and insight into the complexity of residential peak energy demand and in working with this complexity to identify and integrate the social, technical and change management option themes and their impact on appliance usage and residential energy demand at peak times.

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Utilities worldwide are focused on supplying peak electricity demand reliably and cost effectively, requiring a thorough understanding of all the factors influencing residential electricity use at peak times. An electricity demand reduction project based on comprehensive residential consumer engagement was established within an Australian community in 2008, and by 2011, peak demand had decreased to below pre-intervention levels. This paper applied field data discovered through qualitative in-depth interviews of 22 residential households at the community to a Bayesian Network complex system model to examine whether the system model could explain successful peak demand reduction in the case study location. The knowledge and understanding acquired through insights into the major influential factors and the potential impact of changes to these factors on peak demand would underpin demand reduction intervention strategies for a wider target group.

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Peak electricity demand requires substantial investment to update transmission, distribution and generation infrastructure. A successful community peak demand reduction project was examined to identify residential consumer motivational and contextual factors involved in their decision to adopt/not adopt interventions. Energy professionals actively worked to achieve community 'peer' membership and by becoming a trusted information source, facilitated voluntary home energy assessment requests from over 80% of the residential community. By combining and tailoring interventions to the specific needs and motivations of individual householders and the community, interventions promoting energy conservation and efficiency can be effective in achieving sustained reduction in peak demand.

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The use of seafood ecolabels is expanding in the world marketplace, but so are labels indicating other product attributes, such as country of origin and wild vs. farmed. The interactive effects of these labels and attributes in evaluating consumers' preferences for ecolabeled seafood are relatively unexplored. In this paper we investigate (1) the direct and interactive effects of seafood ecolabels with other common fish labels, and (2) how consumers' perceptions about the state of marine stocks and the valuation of ecolabels may be affected by different information. We find moderate interactive effects between ecolabels and country of origin labels, whereas the valuation for seafood ecolabels is fairly high. In terms of information, we find that consumers' perceptions about fish stock levels changed (negatively) after receiving information on declining stock levels, and more sensationalized information led to increased change. However, valuation for a seafood ecolabel increases only when the information was perceived positively (credible/interesting); whereas exaggerated information (which was also perceived less credible) had insignificant effects on WTP.

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The research assessed how best to transition engineering-based automotive firms towards more customer-orientated design and development approaches, whilst identifying the main barriers and concerns facing such a shift. The research investigates the ability of a firm to empower individual engineers with user centred design tools traditionally used by designers, whilst understanding the company-wide needs to facilitate their implementation.

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Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price,managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tick box interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.