227 resultados para Travel Choice
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Background This paper examines changing patterns in the utilisation and geographic access to health services in Great Britain using National Travel Survey data (1985-2012). The National Travel Survey (NTS) is a series of household surveys designed to provide data on personal travel and monitor changes in travel behaviour over time. The utilisation rate was derived using the proportion of journeys made to access health services. Geographic access was analysed by separating the concept into its accessibility and mobility dimensions. Methods Variables from the PSU, households, and individuals datasets were used as explanatory variables. Whereas, variables extracted from the journeys dataset were used as dependent variables to identify patterns of utilisation i.e. the proportion of journeys made by different groups to access health facilities in a particular journey distance or time band or by mode of transport; and geographic access to health services. A binary logistic regression analysis was conducted to identify the utilisation rate over the different time periods between different groups. This analysis shows the Odds Ratios (ORs) for different groups making a trip to utilise health services compared to their respective counterparts. Linear multiple regression analyses were conducted to then identify patterns of change in the accessibility and mobility level. Results Analysis of the data has shown that that journey distances to health facilities were signi fi cantly shorter and also gradually reduced over the period in question for Londoners, females, those without a car or on low incomes, and older people. Although rates of utilisation of health services we re Oral Abstracts / Journal of Transport & Health 2 (2015) S5 – S63 S43 signi fi cantly lower because of longer journey times. These fi ndings indicate that the rate of utilisation of health services largely depends on mobility level although previous research studies have traditionally overlooked the mobility dimension. Conclusions This fi nding, therefore, suggests the need to improve geographic access to services together with an enhanced mobility option for disadvantaged groups in order for them to have improved levels of access to health facilities. This research has also found that the volume of car trips to health services also increased steadily over the period 1985-2012 while all other modes accounted for a smaller number of trips. However, it is dif fi cult to conclude from this research whether this increase in the volume of car trips was due to a lack of alternative transport or due to an increase in the level of car-ownership.
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This study focuses on the effects of weather on daily bus ridership in Brisbane, given the dominance of buses in that city. The weather pattern of Brisbane varies by season according to its subtropical climate characteristics. Bus operation is affected by inclement weather conditions, as buses share the road system with general traffic. Moreover, bus stops generally offer little, or sometimes no, protection from adverse weather. Hence, adverse weather conditions such as rain are thought to directly impact on daily travel behaviour patterns. There has been limited Australian research on the impact of weather on daily transit ridership. This study investigates the relationship between rainy days and daily bus ridership for the period 2010 to 2012. Overall, rainfall has a negative effect, with varying impacts on different transit groups. However, this analysis confirmed a positive relationship between consecutive rainy days (rain continuing for 3 or more days). A possible explanation could be that people switch their transport mode to bus to avoid high traffic congestion and higher accident potentiality on rainy days. Also, Brisbane’s segregated busway corridor works favourably towards this mode choice. The findings of our study enhance the fundamental understanding of traveller behaviour, particularly mode-choice behaviour, under adverse weather conditions.
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This research improved the measurement of public transport accessibility by capturing; travellers' behaviour; diversity of public transport mode; and the subjectivity of travellers' decision in the complex transport networks. The results of this research not only highlighted the importance of considering public transport network characteristics but also, revealed the impact of public transport diversity in the modelling of public transport accessibility. The research developed a hybrid discrete choice model with a nested logit structure to treat the correlation among the public transport mode choices and, a logit correction factor to rectify the correlation among the stop choices.
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Electric-motored personal mobility devices (PMDs) are appearing on Australian roads. While legal to import and own, their use is typically illegal for adult riders within the road transport system. However, these devices could provide an answer to traffic congestion by getting people out of cars for short trips (“first-and-last mile” travel). City of Ryde council, Macquarie University, and Transport for NSW examined PMD use within the road transport system. Stage 1 of the project examined PMD use within a controlled pedestrian environment on the Macquarie University campus. Three PMD categories were used: one-wheelers (an electric unicycle, the Solowheel); two-wheelers (an electric scooter, the Egret); and three-wheelers (the Qugo). The two-wheeled PMD was most effective in terms of flexibility. In contrast, the three-wheeled PMD was most effective in terms of speed. One-wheeled PMD riders were very satisfied with their device, especially at speed, but significant training and practice was required. Two-wheeled PMD riders had less difficulty navigating through pedestrian precincts and favoured the manoeuvrability of the device as the relative narrowness of the two-wheeled PMD made it easier to use on a diversity of path widths. The usability of all PMDs was compromised by the weight of the devices, difficulties in ascending steeper gradients, portability, and parking. This was a limited trial, with a small number of participants and within a unique environment. However, agreement has been reached for a Stage 2 extension into the Macquarie Park business precinct for further real-world trials within a fully functional road transport system.
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Purpose Ethnic entrepreneurship is, and always has been, a means of survival. However, there is limited literature on ethnic entrepreneurship in Australia and therefore, an understanding of ethnic entrepreneurs’ motivations to become self-employed. The purpose of this paper is to report the influential factors in the decision to engage in self-employment through case studies of members of Melbourne’s Sri Lankan community informed by the mixed embeddedness approach. Design/methodology/approach The mixed embeddedness approach frames the study where the authors examine the motivations for business of five Sri Lankan entrepreneurs. Narratives are used to construct individual case studies, which are then analyzed in terms of the motivations for, resources used and challenges faced on the entrepreneurial journey. Findings For these ethnic entrepreneurs, their entrepreneurial activity results from a dynamic match between local market opportunities and the specific ethnic resources available to them at the time of founding. The self-employment decision was not prompted by a lack of human capital but an inability to use that human capital in alternative means of employment at specific points in time. Moreover the authors highlight the importance of social and cultural capital as resources used to overcome challenges on the entrepreneurial journey. Originality/value In this community, entrepreneurship was not a result of a lack of human capital but how it was utilized in combination with social and cultural capitals in the given opportunity structure. The mixed embeddedness approach enables the uncovering of how ethnic network ties were used in light of the opportunities available to build entrepreneurial activity.
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Objective To discuss generalized estimating equations as an extension of generalized linear models by commenting on the paper of Ziegler and Vens "Generalized Estimating Equations. Notes on the Choice of the Working Correlation Matrix". Methods Inviting an international group of experts to comment on this paper. Results Several perspectives have been taken by the discussants. Econometricians have established parallels to the generalized method of moments (GMM). Statisticians discussed model assumptions and the aspect of missing data Applied statisticians; commented on practical aspects in data analysis. Conclusions In general, careful modeling correlation is encouraged when considering estimation efficiency and other implications, and a comparison of choosing instruments in GMM and generalized estimating equations, (GEE) would be worthwhile. Some theoretical drawbacks of GEE need to be further addressed and require careful analysis of data This particularly applies to the situation when data are missing at random.
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This paper investigates quality of service (QoS) and resource productivity implications of transit route passenger loading and travel time. It highlights the value of occupancy load factor as a direct passenger comfort QoS measure. Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia, is used to investigate time series correlation between occupancy load factor and passenger average travel time. Correlation is strong across the entire span of service in both directions. Passengers tend to be making longer, peak direction commuter trips under significantly less comfortable conditions than off-peak. The Transit Capacity and Quality of Service Manual uses segment based load factor as a measure of onboard loading comfort QoS. This paper provides additional insight into QoS by relating the two route based dimensions of occupancy load factor and passenger average travel time together in a two dimensional format, both from the passenger’s and operator’s perspectives. Future research will apply Value of Time to QoS measurement, reflecting perceived passenger comfort through crowding and average time spent onboard. This would also assist in transit service quality econometric modeling. The methodology can be readily applied in a practical setting where AFC data for fixed scheduled routes is available. The study outcomes also provide valuable research and development directions.
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Traffic incidents are recognised as one of the key sources of non-recurrent congestion that often leads to reduction in travel time reliability (TTR), a key metric of roadway performance. A method is proposed here to quantify the impacts of traffic incidents on TTR on freeways. The method uses historical data to establish recurrent speed profiles and identifies non-recurrent congestion based on their negative impacts on speeds. The locations and times of incidents are used to identify incidents among non-recurrent congestion events. Buffer time is employed to measure TTR. Extra buffer time is defined as the extra delay caused by traffic incidents. This reliability measure indicates how much extra travel time is required by travellers to arrive at their destination on time with 95% certainty in the case of an incident, over and above the travel time that would have been required under recurrent conditions. An extra buffer time index (EBTI) is defined as the ratio of extra buffer time to recurrent travel time, with zero being the best case (no delay). A Tobit model is used to identify and quantify factors that affect EBTI using a selected freeway segment in the Southeast Queensland, Australia network. Both fixed and random parameter Tobit specifications are tested. The estimation results reveal that models with random parameters offer a superior statistical fit for all types of incidents, suggesting the presence of unobserved heterogeneity across segments. What factors influence EBTI depends on the type of incident. In addition, changes in TTR as a result of traffic incidents are related to the characteristics of the incidents (multiple vehicles involved, incident duration, major incidents, etc.) and traffic characteristics.
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While the popularity of destination image research has increased exponentially in the literature, there has been relatively little published about perceptions held by international consumers of destinations in South America. The purpose of this paper is to report the findings of a research project that aimed to identify the baseline market perceptions of Brazil, Argentina and Chile amongst Australian residents, at the time of the emergence of this long haul market. Of interest was the extent to which Australians differentiate the three distinct countries versus perceiving the continent as a gestalt. These baseline perceptions enable the effectiveness of future marketing communications in Australia by the three national tourism offices to be monitored over time. Importance-Performance Analysis (IPA) is used as a practical analytical tool to guide decision makers. In terms of operationalising destination image, a key research finding was the very high ratio or participants using the ‘Don’t know’ (DK) option for each destination performance scale item. This finding has practical implications for the destination marketers, as well as for researchers engaged in destination image research in long haul and/or emerging markets.
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BACKGROUND OR CONTEXT The higher education sector plays an important role in encouraging students into the STEM pipeline through fostering partnerships with schools, building on universities long tradition in engagement and outreach to secondary schools. Numerous activities focus on integrated STEM learning experiences aimed at developing conceptual scientific and mathematical knowledge with opportunities for students to show and develop skills in working with each other and actively engaging in discussion, decision making and collaborative problem solving. (NAS, 2013; AIG, 2015; OCS, 2014). This highlights the importance of the development and delivery of engaging integrated STEM activities connected to the curriculum to inspire the next generation of scientists and engineers and generally preparing students for post-secondary success. The broad research objective is to gain insight into which engagement activities and to what level they influence secondary school students’ selection of STEM-related career choices at universities. PURPOSE OR GOAL To evaluate and determine the effectiveness of STEM engagement activities impacting student decision making in choosing a STEM-related degree choice at university. APPROACH A survey was conducted with first-year domestic students studying STEM-related fieldswithin the Science and Engineering Faculty at Queensland University of Technology. Of the domestic students commencing in 2015, 29% responded to the survey. The survey was conducted using Survey Monkey and included a variety of questions ranging from academic performance at school to inspiration for choosing a STEM degree. Responses were analysed on a range of factors to evaluate the influence on students’ decisions to study STEM and whether STEM high school engagement activities impacted these decisions. To achieve this the timing of decision making for students choice in study area, degree, and university is compared with the timing of STEM engagement activities. DISCUSSION Statistical analysis using SPSS was carried out on survey data looking at reasons for choosing STEM degrees in terms of gender, academic performance and major influencers in their decision making. It was found that students choose their university courses based on what subjects they enjoyed and exceled at in school. These results found a high correlation between enjoyment of a school subject and their interest in pursuing this subject at university and beyond. Survey results indicated students are heavily influenced by their subject teachers and parents in their choice of STEM-related disciplines. In terms of career choice and when students make their decision, 60% have decided on a broad area of study by year 10, whilst only 15% had decided on a specific course and 10% had decided on which university. The timing of secondary STEM engagement activities is seen as a critical influence on choosing STEM disciplines or selection of senior school subjects with 80% deciding on specific degree between year 11 and 12 and 73% making a decision on which university in year 12. RECOMMENDATIONS/IMPLICATIONS/CONCLUSION Although the data does not support that STEM engagement activities increase the likelihood of STEM-related degree choice, the evidence suggests the students who have participated in STEM activities associate their experiences with their choice to pursue a STEM-related course. It is important for universities to continue to provide quality engaging and inspirational learning experiences in STEM, to identify and build on students’ early interest and engagement, increase STEM knowledge and awareness, engage them in interdisciplinary project-based STEM practices, and provide them with real-world application experiences to sustain their interest.
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Objective The aim of this study was to gather patients' perceptions regarding their choice between public and private hospital EDs for those who hold private health insurance. The findings of this study will contribute to knowledge regarding patients' decision-making processes and therefore may contribute to the development of evidence based public policies. Methods An in-depth semi-structured guide was used to interview participants at public and private hospital EDs. Questions sought to identify the issues that were considered by the participants to decide to attend that hospital ED, previous ED experience, expectations of ED services and perceived benefits and barriers to accessing services. Interviews were audio recorded, transcribed verbatim and analysed using content and thematic approaches. Results Four core themes emerged: prior good experience with the hospital, perceived quality of care, perceived waiting times and perceived costs that may explain patients' choice. Patients' choice between public and private EDs can be explained by the interaction of these core themes. The principal issues appear to be concern for gap payments at private hospital ED and waiting times at public hospital ED. Conclusions Patients who choose to attend public EDs appear to value financial concern over waiting time; those who choose to attend private EDs appear to value waiting time ahead of financial concerns.
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In this note, we shortly survey some recent approaches on the approximation of the Bayes factor used in Bayesian hypothesis testing and in Bayesian model choice. In particular, we reassess importance sampling, harmonic mean sampling, and nested sampling from a unified perspective.
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Improved forecasting of urban rail patronage is essential for effective policy development and efficient planning for new rail infrastructure. Past modelling and forecasting of urban rail patronage has been based on legacy modelling approaches and often conducted at the general level of public transport demand, rather than being specific to urban rail. This project canvassed current Australian practice and international best practice to develop and estimate time series and cross-sectional models of rail patronage for Australian mainland state capital cities. This involved the implementation of a large online survey of rail riders and non-riders for each of the state capital cities, thereby resulting in a comprehensive database of respondent socio-economic profiles, travel experience, attitudes to rail and other modes of travel, together with stated preference responses to a wide range of urban travel scenarios. Estimation of the models provided a demonstration of their ability to provide information on the major influences on the urban rail travel decision. Rail fares, congestion and rail service supply all have a strong influence on rail patronage, while a number of less significant factors such as fuel price and access to a motor vehicle are also influential. Of note, too, is the relative homogeneity of rail user profiles across the state capitals. Rail users tended to have higher incomes and education levels. They are also younger and more likely to be in full-time employment than non-rail users. The project analysis reported here represents only a small proportion of what could be accomplished utilising the survey database. More comprehensive investigation was beyond the scope of the project and has been left for future work.
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In this study, we investigate the qualitative and quantitative effects of an R&D subsidy for a clean technology and a Pigouvian tax on a dirty technology on environmental R&D when it is uncertain how long the research takes to complete. The model is formulated as an optimal stopping problem, in which the number of successes required to complete the R&D project is finite and learning about the probability of success is incorporated. We show that the optimal R&D subsidy with the consideration of learning is higher than that without it. We also find that an R&D subsidy performs better than a Pigouvian tax unless suppliers have sufficient incentives to continue cost-reduction efforts after the new technology success-fully replaces the old one. Moreover, by using a two-project model, we show that a uniform subsidy is better than a selective subsidy.
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We study the effect of affirmative action on effort in an experiment conducted in high schools in socioeconomically disadvantaged areas in Queensland, Australia. All participating schools have a large representation of indigenous Australians, a population group that is frequently targeted by affirmative action. Our participants perform a simple real-effort task in a competitive setting. Those ranked in the top third receive a high piece-rate payment and all the others receive a low payment. We introduce affirmative action by providing the lowest (bottom third) performers with a positive handicap increasing their chances to achieve the high payment target. Our findings show that the policy increases effort of those that it aims to favour, without discouraging effort of those who are indirectly penalized by affirmative action.