Doctor of Philosophy (PhD) / Changing the behaviour of firms to take environmental concerns into account is seen as unlikely without effective regulations. However, corporations are increasingly keen to represent themselves as ‘green’, including those in the world’s largest manufacturing sector: the car industry. Given rising concern for the environment and environmental sustainability since the 1990s this thesis asks: what motivates car firms to actually make environmental commitments? Answering this question has implications for whether these commitments are ‘real’ and if so whether they are occurring in response to material factors (e.g. state regulations and consumer demand) versus normative factors (e.g. social attitudes and internal company strategies). In order to answer it, the thesis applies the insights of the institutional varieties of capitalism approach to the German, United States and Japanese car industries, and specific firms within them, in respect of the environmental issue of climate change from 1990 to 2004. Empirical national data is analysed, as well the environmental reporting of individual firms and interviews with key personnel. The main findings are that what leads the car industry to see environmental issues as central to their business interests hinges on the impact of differing national institutional factors. Specifically, it is a matter of whether firms have a liberal market economy (LME) as their home base, in the case of US firms, or a coordinated market economy (CME) as their home base, in the case of German and Japanese firms. US car firms react more to the material imperatives of consumer demand and state regulations. German and Japanese firms are more mindful of normative factors for their initiatives, such as social attitudes (especially for German firms) and internal company strategies (especially for Japanese firms). They have more of a partnership approach with government. Therefore, car firms have very distinct ‘lenses’ through which they see the environmental performance of the cars they produce. As such, the thesis concludes that the variety of capitalism of nations has implications not just for the type of products that economic actors such as car firms produce, and the competitive advantages they develop, but also the way they address related issues arising as a result of their activities, including environmental issues.

Following World War Two, land use and transport policy and practice in most major Australian cities was modelled on the US experience. As such, these cities have become characterised by urban sprawl (indicated by segregated zoning and low development densities) and car dependence. In Perth, Western Australia, these characteristics are particularly evident despite, or perhaps because, the city has a strong regional planning system unlike most American cities. Car dependence and sprawl are in turn linked to dependence on fossil fuels for transport energy. Increasingly, too, links are being found between conventional planning outcomes and public health. For example, research has linked car dependence with a variety of health conditions including respiratory illness, overweight and obesity. Moreover, research is increasingly linking sprawl and car dependence with social justice issues because people on limited income and with decreased mobility struggle to undertake their life’s work. In response to these concerns the Western Australian planning system introduced Liveable Neighbourhoods, a new design code, which was meant to reduce car dependence and sprawl. This code has its roots in New Urbanism and appears to have been taken up more rapidly in Perth than elsewhere. No large-scale evaluation of New Urbanism has previously been conducted anywhere. This thesis reports on an extensive literature review, travel survey (n=211), perceptual study (n=992) and environmental study, which together sought to evaluate whether the Liveable Neighbourhoods (LN) design code is contributing to a sustainable transport agenda. In total, 46 neighbourhoods (11 LNs and 35 CNs) were compared. The research found that despite residents of Liveable Neighbourhoods driving less and walking more than residents of conventional neighbourhoods (CNs) (a switch of 9% with some associated health advantages), there was little else to indicate that LN is achieving its goals as transport VKT and fuel use was identical due to regional transport requirements diminishing any local walkability advantages. There was strong supportive evidence that LNs were not significantly different to CNs. For example, there were few differences in perception of opportunity for more sustainable travel and residents of CNs actually had better access, on average, to key destinations, including shops (i.e. the average distance to key destinations was 2.2 kilometres compared with 2.5 kilometres in LNs). Also, residential lot densities were well below what were intended by LN and in both LNs and CNs the time for public transport to get people to work was over 90 minutes compared with around 30 minutes by car. The results reveal that there must be significant revisions to the LN code and how it is applied, because there is no evidence that new neighbourhoods are improving regional transport sustainability. In particular, residential densities and land use mix appear to be too low to encourage community self-sufficiency, indicated by few neighbourhoods being anchored by key destinations. These matters are not mandated in the LN guidelines making them powerless to bring significant change. More generally, the thesis questions the extent to which New Urbanism can promote a sustainable transport agenda wherever it is applied unless it mandates real changes in land use and transit not just local walkability.

The conventional information used to guide automobile drivers in selecting their driving routes is the shortest-distance path (SDP). As several researchers have pointed out, driver route selection is a multiple criteria decision process. This research proposes a multiobjective path optimisation (MOPO) decision model to make a more precise simulation of the decision-making behaviour of driver route selection. Seven single-objective path optimisation (SOPO) decision models are taken into account to establish the MOPO decision model. They relate to travel time, travel cost, cumulative distance, roadway capacity, roadway grade, passed intersections and number of turns. To solve the MOPO problem, a two-stage technique which incorporates shortest path (SP) algorithms and techniques for solving the multiobjective programming problem and a path genetic algorithm (PGA) are proposed. In addition, algorithms such as Dijkstra, A* and GA are reviewed and algorithms that are applicable for solving the MOPO problems are suggested. Furthermore, new algorithms for solving least-node path (LNP) problem, corresponding to the objective of passed intersections, as well as minimum-turn path (MTP) problem, corresponding to the objective of number of turns, are developed. To conduct the empirical study, a software tool - the multiobjective path optimisation analysis tool (MOPOAT) - was implemented. It contains tools for constructing a road network and its corresponding network topology, the environment of coding techniques for solving the MOPO problems and tools for the manipulation, statistics, analysis and display of experimental results. The purpose of implementing the MOPOAT software is to provide more efficient, convenient and user-friendly tools for solving MOPO and SOPO problems so that an empirical study of real road networks can be carried out more easily. To demonstrate the advantages of the proposed model in supporting more diverse information to drivers to assist in route selection, several experiments were conducted utilising three real road networks with different roadway types and numbers of nodes and links. Techniques and algorithms such as the two-stage approach, Dijkstra and the PGA for solving the MOPO problem, and the Dijkstra, LNP and MTP algorithms for solving the SOPO problems were applied. Finally, to deal with improvements in computational efficiency for identifying SPs in a large road network and for population initialisation of the PGA, the critical-section (CS) approach and the seed-path expansion (SPE) approach are proposed. To compare the run time between the conventional SP and CS algorithms as well as the PGA and the SPE algorithms, tools were implemented with commercial GIS, and experimental tests were conducted using road networks with a large amount of nodes and links and different roadway types. Through these theoretical and empirical studies, several useful contributions and conclusions were obtained. Some of the most significant findings are: 1. The experimental results demonstrate the advantages of integration with commercial GIS packages in supporting both spatial and attribute data displays. It can be safely said that, assisted by the MOPOAT software, it is easy for automobile drivers to obtain the optimal paths of the SDP, LNP, MTP and MOPO problems in seconds, despite these problems being highly complex and difficult to resolve manually. 2. According to the experimental results, the proposed LNP, MTP and MOPO decision models give automobile drivers richer information for choosing their driving routes in a more diverse way. 3. It is shown by the experimental results that the SDP and LNP mostly locate different paths in both radial-circumferential and grid-type road networks, and that the total passed intersections by the SDP are greater than passed by the LNP. Moreover, it is revealed that ambiguous turns might occur in both radial-circumferential and grid-type road networks. 4. It is found that the number of nodes of the SDP is in general greater than the number of nodes of the LNP and MTP irrespective of the type of road network. 5. A sensitivity analysis for weights shows that as the weighting value of the SDP objective incrementally increases by 0.1 units, the corresponding SDP??s objective value varies either low or high. The same results also occur for the LNP and MTP objectives. This verifies the fact that the weighting coefficients do not reflect proportionally the relative importance of the objectives. Moreover, the MTP objective has the higher sensitivity in comparison with the other two objectives. 6. Despite utilising Dijkstra or PGA algorithms for solving the MOPO problem, the LNP and MTP algorithms have to be employed to solve the non-commeasurable problem, whereby the standardisation objective value can be obtained. In addition, without any assisting information the PGA might fail to reach the best-compromise solution. 7. It is found that the total run time for solving the MOPO problem by applying the Dijkstra algorithm is much faster than by the PGA. However, if the run time excludes the time needed for population initialisation, the PGA is much faster than the Dijkstra algorithm. 8. Based on calculated bottlenecks, the proposed CS approach partitions a SP into many critical sections in advance, with the result that a long SP can be obtained by combining all SPs of all CSs. The experimental results show that the run time of the CS algorithm is much faster than Dijkstra??s algorithm. Moreover, the test result for the P-pointer indicates that if the total number of nodes of a SP grows the computational efficiency of the CS algorithm becomes significantly better than the Dijkstra algorithm, and that the CS approach has the best performance. 9. The experimental result for the E-pointer reveals that the computational efficiency of the CS algorithm will decrease gradually as the number of selected CSs increases. Therefore, the total percentage of selected CSs suggested by the experimental result is no more than 30 percent. 10. According to the experimental results, the performance order among SDP, LNP and MTP algorithms from fast to slow is SDP, MTP and LNP, and the LNP algorithm requires much more time than the other two algorithms. 11. As the total nodes of a path increase, most of the run time for SDP and LNP also increases. However, there are still some paths that violate the above rule. This result verifies that the run time needed for solving SDP and LNP is not only affected by the node numbers but also depends on the network topology. 12. Run time for solving the MOPO problem by applying the PGA is faster than applying the Dijkstra algorithm, if the run time of the former algorithm does not take into account the population initialisation time. Nevertheless, if the run time of the former algorithm does take into account the population initialisation time, the latter algorithm is much faster than the former algorithm. 13. In comparing the run time for population initialisation, the run time of the evolution process by applying the PGA is quite small, and the bottleneck of the run time for solving MOPO problem by applying the PGA is the population initialisation. 14. The population initialisation time is reduced significantly by applying the SPE algorithm, and increases at a very slow rate as the number of nodes of a path increases. As the total nodes of a path grow ever larger, the computing time is reduced more noticeably.

The conventional information used to guide automobile drivers in selecting their driving routes is the shortest-distance path (SDP). As several researchers have pointed out, driver route selection is a multiple criteria decision process. This research proposes a multiobjective path optimisation (MOPO) decision model to make a more precise simulation of the decision-making behaviour of driver route selection. Seven single-objective path optimisation (SOPO) decision models are taken into account to establish the MOPO decision model. They relate to travel time, travel cost, cumulative distance, roadway capacity, roadway grade, passed intersections and number of turns. To solve the MOPO problem, a two-stage technique which incorporates shortest path (SP) algorithms and techniques for solving the multiobjective programming problem and a path genetic algorithm (PGA) are proposed. In addition, algorithms such as Dijkstra, A* and GA are reviewed and algorithms that are applicable for solving the MOPO problems are suggested. Furthermore, new algorithms for solving least-node path (LNP) problem, corresponding to the objective of passed intersections, as well as minimum-turn path (MTP) problem, corresponding to the objective of number of turns, are developed. To conduct the empirical study, a software tool - the multiobjective path optimisation analysis tool (MOPOAT) - was implemented. It contains tools for constructing a road network and its corresponding network topology, the environment of coding techniques for solving the MOPO problems and tools for the manipulation, statistics, analysis and display of experimental results. The purpose of implementing the MOPOAT software is to provide more efficient, convenient and user-friendly tools for solving MOPO and SOPO problems so that an empirical study of real road networks can be carried out more easily. To demonstrate the advantages of the proposed model in supporting more diverse information to drivers to assist in route selection, several experiments were conducted utilising three real road networks with different roadway types and numbers of nodes and links. Techniques and algorithms such as the two-stage approach, Dijkstra and the PGA for solving the MOPO problem, and the Dijkstra, LNP and MTP algorithms for solving the SOPO problems were applied. Finally, to deal with improvements in computational efficiency for identifying SPs in a large road network and for population initialisation of the PGA, the critical-section (CS) approach and the seed-path expansion (SPE) approach are proposed. To compare the run time between the conventional SP and CS algorithms as well as the PGA and the SPE algorithms, tools were implemented with commercial GIS, and experimental tests were conducted using road networks with a large amount of nodes and links and different roadway types. Through these theoretical and empirical studies, several useful contributions and conclusions were obtained. Some of the most significant findings are: 1. The experimental results demonstrate the advantages of integration with commercial GIS packages in supporting both spatial and attribute data displays. It can be safely said that, assisted by the MOPOAT software, it is easy for automobile drivers to obtain the optimal paths of the SDP, LNP, MTP and MOPO problems in seconds, despite these problems being highly complex and difficult to resolve manually. 2. According to the experimental results, the proposed LNP, MTP and MOPO decision models give automobile drivers richer information for choosing their driving routes in a more diverse way. 3. It is shown by the experimental results that the SDP and LNP mostly locate different paths in both radial-circumferential and grid-type road networks, and that the total passed intersections by the SDP are greater than passed by the LNP. Moreover, it is revealed that ambiguous turns might occur in both radial-circumferential and grid-type road networks. 4. It is found that the number of nodes of the SDP is in general greater than the number of nodes of the LNP and MTP irrespective of the type of road network. 5. A sensitivity analysis for weights shows that as the weighting value of the SDP objective incrementally increases by 0.1 units, the corresponding SDP??s objective value varies either low or high. The same results also occur for the LNP and MTP objectives. This verifies the fact that the weighting coefficients do not reflect proportionally the relative importance of the objectives. Moreover, the MTP objective has the higher sensitivity in comparison with the other two objectives. 6. Despite utilising Dijkstra or PGA algorithms for solving the MOPO problem, the LNP and MTP algorithms have to be employed to solve the non-commeasurable problem, whereby the standardisation objective value can be obtained. In addition, without any assisting information the PGA might fail to reach the best-compromise solution. 7. It is found that the total run time for solving the MOPO problem by applying the Dijkstra algorithm is much faster than by the PGA. However, if the run time excludes the time needed for population initialisation, the PGA is much faster than the Dijkstra algorithm. 8. Based on calculated bottlenecks, the proposed CS approach partitions a SP into many critical sections in advance, with the result that a long SP can be obtained by combining all SPs of all CSs. The experimental results show that the run time of the CS algorithm is much faster than Dijkstra??s algorithm. Moreover, the test result for the P-pointer indicates that if the total number of nodes of a SP grows the computational efficiency of the CS algorithm becomes significantly better than the Dijkstra algorithm, and that the CS approach has the best performance. 9. The experimental result for the E-pointer reveals that the computational efficiency of the CS algorithm will decrease gradually as the number of selected CSs increases. Therefore, the total percentage of selected CSs suggested by the experimental result is no more than 30 percent. 10. According to the experimental results, the performance order among SDP, LNP and MTP algorithms from fast to slow is SDP, MTP and LNP, and the LNP algorithm requires much more time than the other two algorithms. 11. As the total nodes of a path increase, most of the run time for SDP and LNP also increases. However, there are still some paths that violate the above rule. This result verifies that the run time needed for solving SDP and LNP is not only affected by the node numbers but also depends on the network topology. 12. Run time for solving the MOPO problem by applying the PGA is faster than applying the Dijkstra algorithm, if the run time of the former algorithm does not take into account the population initialisation time. Nevertheless, if the run time of the former algorithm does take into account the population initialisation time, the latter algorithm is much faster than the former algorithm. 13. In comparing the run time for population initialisation, the run time of the evolution process by applying the PGA is quite small, and the bottleneck of the run time for solving MOPO problem by applying the PGA is the population initialisation. 14. The population initialisation time is reduced significantly by applying the SPE algorithm, and increases at a very slow rate as the number of nodes of a path increases. As the total nodes of a path grow ever larger, the computing time is reduced more noticeably.

<p>The aim of this study was to understand injury mechanisms behind fractures of the upper extremities in car accidents. Volvo Car Corporation initiated this project based on the fact that no safety system today focuses on preventing injuries to the upper extremity. A literature study was undertaken focusing on the basic anatomy of the upper extremity, different fracture types and fracture mechanisms. Three subsets, from 1998 – January 2009, were selected from Volvo’s statistical accident database: 1) all occupants involved in an accident 2) all occupants with a MAIS2+ injury 3) all occupants with an upper extremity fracture. These subsets were used in a comparison, using frequency analyses. The comparison analysis showed that frontal impact is the dominating accident type for all three subsets. The comparison analysis also indicated that the risk for upper extremity fractures follows the pattern of MAIS2+ injury risk. An in-depth study using 92 selected cases, including 80 occupants, was also performed. All available information, such as medical records, questionnaires completed by the occupants and photographs from the accident scene was collected and analysed. The analysis of the in-depth study, together with knowledge retrieved from the literature study, resulted in six different mechanism groups that were used to categorise fractures. The groups were then analysed individually in regard to accident type and fractured segment of the upper extremity. Analysis of the mechanism groups showed that frontal impact is the dominating accident type in these subsets as well. It could also be seen that the fractures occurring in the in-depth study are quite evenly distributed along the upper extremities. Upper extremity injuries are relatively infrequent in car accidents but may result in long-term disability, including chronic deformity, pain, weakness and loss of motion. More attention is therefore necessary in order to develop a safer environment for car occupants.</p>

<p>Effektiva marknadshypotesen (EMH) utvecklades av Eugene Fama under 1960- och 1970-talet. Grundtanken var att prisbildningen alltid reflekterar den information som finns tillgänglig för marknaden. Fama skiljde på tre former av effektivitet: svaga, semistarka och starka formen. I denna uppsats studerar vi den semistarka formen av effektivitet, vilken omfattar all offentligt tillgänglig information. Syftet är att undersöka effektiviteten i samband med att ny information tillfaller den svenska aktiemarknaden. I de fall aktiemarknaden är effektiv finns ingen möjlighet till onormal avkastning. Vår studie omfattar de 39 största företagen noterade på den svenska aktiemarknaden, vilket motsvarar 81,5 procent av det totala värdet. Vi kunde i vår undersökning dra slutsatsen att Stockholmsbörsen inte är fullständigt effektiv när ny information offentliggörs.</p>

The trend of vehicle industry has been changed due to well development of electronic and information technology , the electronic industry has become an important part of vehicle innovation and research. Taiwan has pivotal status of electric industry in the world, while the opportunity of car electronic was bloomimg, what stratage should Taiwan's electronics company take to hold out the important role ? The mainly research discusses was below: 1. Taiwan has superiority ability of design and production on the semiconductor and the electronic industry, and has the high design flexibility as well as the formidable conformity ability, how the Taiwan electronics industry call into play the core ability and connects with the mainstream of global vehicle industrial, strides in the vehicle to use the electronic industry? 2. By increase of installs the electronic component on vehicle year by year, the vehicle industry push the electronic market growth fast, simultaneously, it provides an oportunity for Taiwan electronic industry; How does the Taiwan electronic industry grasp the opportunity, adopts corresponding ways to enters the global car electronic market? In view of the above questions, this research was doing by collectiing secondary data and the market analysis information, auxiliary to interview several company whom develops automotive electronic products, induces what countermeasures Taiwan electronics company takes by extend their advantage to enter the car electrics industry. The result of this research is found is no matter how ability that company obtain or take what kind of stratage, but the key factor to success was doing daily work practically.

Effektiva marknadshypotesen (EMH) utvecklades av Eugene Fama under 1960- och 1970-talet. Grundtanken var att prisbildningen alltid reflekterar den information som finns tillgänglig för marknaden. Fama skiljde på tre former av effektivitet: svaga, semistarka och starka formen. I denna uppsats studerar vi den semistarka formen av effektivitet, vilken omfattar all offentligt tillgänglig information. Syftet är att undersöka effektiviteten i samband med att ny information tillfaller den svenska aktiemarknaden. I de fall aktiemarknaden är effektiv finns ingen möjlighet till onormal avkastning. Vår studie omfattar de 39 största företagen noterade på den svenska aktiemarknaden, vilket motsvarar 81,5 procent av det totala värdet. Vi kunde i vår undersökning dra slutsatsen att Stockholmsbörsen inte är fullständigt effektiv när ny information offentliggörs.

Rates of car ownership in the United States exceed that of all other large nations in the world. This high rate contributes to the unexpressed demand for road space that renders highway expansion useless as a strategy for decreasing traffic congestion. It also necessitates the provision of on-site parking in residential buildings, decreasing the affordability of housing in urban areas. Furthermore, the curb-side parking needed to make room for the high number of cars in the country takes away space that could be used for bike lanes, transit lanes, or widened sidewalks. Therefore, the United States could benefit from a reduction in rates of household car ownership. In this paper, I use cross-sectional data from the National Highway Transportation Survey to determine the impact on heavy and light rail on car ownership in American cities. I find that the presence of heavy rail is associated with a lower rate of car ownership, while the presence of light rail is not.

No description available.