203 resultados para Travel demand.
Resumo:
Purpose: There is a lack of theory relating to destination brand performance measurement in the destination branding literature, which emerged in the late 1990s (see for example Dosen, Vransevic, & Prebezac, 1998). Additionally, there is a lack of research about the importance of travel context in consumers’ destination decision making (Hu & Ritchie, 1993). This study develops a structural model to measure destination brand performance across different travel situations. The theory of planned behaviour (TpB) was utilised as a framework to underpin the consumer-based brand equity (CBBE) hierarchy to develop a model of destination brand performance. Research approach: A proposed model of destination brand performance was developed through a review of the literature. The first study was used to identify destination image attributes (the core construct) using an analysis of the literature, a document analysis, and personal interviews using the Repertory Test qualitative technique. Underpinned by Personal Construct Theory (PCT), the Repertory Test enables the elicitation of attributes consumers use to evaluate destinations when considering travel. Data was examined in the first study to i) identify any attribute differences in travel contexts and ii) create a scale for use in a questionnaire. A second study was conducted to test the proposed model using a questionnaire with eight groups of participants to assess four destinations across two travel contexts. The model was tested utilising structural equation modelling. Findings: The first study resulted in a list of 29 destination image attributes for use in a scale index. Attributes were assessed across travel contexts and few differences were identified. The second study assessed the congruence of destination brand identity (the destination marketing organisation’s desired image) and destination brand image (the actual perceptions held by consumers) using importance-performance analyses. Finally, the proposed model of destination brand performance was tested. Overall the data supported the model of destination brand performance across travel contexts and destinations. Additionally, this was compared to consumers’ decision sets, further supporting the model. Value: This research provides a contribution to the destination marketing literature through the development of a measurement of destination brand performance underpinned by TpB. Practically; it will provide destination marketing organisations with a tool to track destination brand performance, relative to key competing places, over time. This is important given the development of a destination brand is a long term endeavour.
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This chapter introduces techniques that are used in travel writing to create a strong sense of place and a meaningful, engaging narrative of a journey. It raises and defines terms of modern rhetoric to show that a distinctive and enduring feature of travel writing lies in the ways it mixes modes of writing. Towards the end, the chapter offers ways of effectively unifying elements of travel writing.
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This study examined physiological and performance effects of pre-cooling on medium-fast bowling in the heat. Ten, medium-fast bowlers completed two randomised trials involving either cooling (mixed-methods) or control (no cooling) interventions before a 6-over bowling spell in 31.9±2.1°C and 63.5±9.3% relative humidity. Measures included bowling performance (ball speed, accuracy and run-up speeds), physical characteristics (global positioning system monitoring and counter-movement jump height), physiological (heart rate, core temperature, skin temperature and sweat loss), biochemical (serum concentrations of damage, stress and inflammation) and perceptual variables (perceived exertion and thermal sensation). Mean ball speed (114.5±7.1 vs. 114.1±7.2 km · h−1; P = 0.63; d = 0.09), accuracy (43.1±10.6 vs. 44.2±12.5 AU; P = 0.76; d = 0.14) and total run-up speed (19.1±4.1 vs. 19.3±3.8 km · h−1; P = 0.66; d = 0.06) did not differ between pre-cooling and control respectively; however 20-m sprint speed between overs was 5.9±7.3% greater at Over 4 after pre-cooling (P = 0.03; d = 0.75). Pre-cooling reduced skin temperature after the intervention period (P = 0.006; d = 2.28), core temperature and pre-over heart rates throughout (P = 0.01−0.04; d = 0.96−1.74) and sweat loss by 0.4±0.3 kg (P = 0.01; d = 0.34). Mean rating of perceived exertion and thermal sensation were lower during pre-cooling trials (P = 0.004−0.03; d = 0.77−3.13). Despite no observed improvement in bowling performance, pre-cooling maintained between-over sprint speeds and blunted physiological and perceptual demands to ease the thermoregulatory demands of medium-fast bowling in hot conditions.
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Objective. To determine the impact of the introduction of universal access to ambulance services via the implementation of the Community Ambulance Cover (CAC) program in Queensland in 2003–04. Method. The study involved a 10-year (2000–01 to 2009–10) retrospective analysis of routinely collected data reported by the Queensland Ambulance Service (QAS) and by the Council of Ambulance Authorities. The data were analysed for the impact of policy changes that resulted in universal access to ambulance services in Queensland. Results. QASis a statewide, publically funded ambulance service. In Queensland, ambulance utilisation rate (AUR)per 1000 persons grew by 41% over the decade or 3.9% per annum (10-year mean = 149.8, 95% CI: 137.3–162.3). The AUR mean after CAC was significantly higher for urgent incidents than for non-urgent ones. However projection modelling demonstrates that URs after the introduction of CAC were significantly lower than the projected utilisation for the same period. Conclusions. The introduction of universal access under the Community Ambulance Cover program in Queensland has not had any significant independent long-term impact on demand overall. There has been a reduction in the long-term growth rate, which may have been contributed to by an ‘appropriate use’ public awareness program.
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Emergency health is a critical component of Australia’s health system and one which is increasingly congested from growing demand and blocked access to inpatient beds. The Emergency Health Services Queensland (EHSQ) study aims to identify the factors driving increased demand for emergency health and to evaluate strategies which may safely reduce the future demand growth. This monograph addresses the characteristics of users of emergency health services with an aim to identify those that appear to contribute to demand growth. This study utilises data on patients treated by Emergency Departments (ED) and Queensland Ambulance Service (QAS) across Queensland. ED data was derived from the Emergency Department Information System (EDIS) for the period 2001-02 through to 2010-11. Ambulance data was extracted from the QAS’ Ambulance Information Management System (AIMS) and electronic Ambulance Report Form (eARF) for the period 2001-02 through to 2009-10. Due to discrepancies and comparability issues for ED data, this monograph compares data from the 2003-04 time period with 2010-11 data for 21 of the reporting EDs. Also a snapshot of users for the 2010-11 financial year for 31 reporting EDs is used to describe the characteristics of users and to compare those characteristics with population demographics. For QAS data, the 2002-03 and 2009-10 time periods were selected for detailed analyses to identify trends. • Demand for emergency health care services is increasing, representing both increased population and increased relative utilisation. Per capita demand for ED attention has increased by 2% per annum over the last decade and for ambulance attention by 3.7% per annum. • The growth in ED demand is prominent in more urgent triage categories with actual decline in less urgent patients. An estimated 55% of patients attend hospital EDs outside of normal working hours. There is no evidence that patients presenting out of hours are significantly different to those presenting within working hours; they have similar triage assessments and outcomes. • Patients suffering from injuries and poisoning comprise 28% of the ED workload (an increase of 65% in the study period), whilst declines of 32% in cardiovascular and circulatory conditions, and musculoskeletal problems have been observed. • 25.6% of patients attending EDs are admitted to hospital. 19% of admitted patients and 7% of patients who die in the ED are triage category 4 or 5 on arrival. • The average age of ED patients is 35.6 years. Demand has grown in all age groups and amongst both men and women. Men have higher utilisation rates for ED in all age groups. The only group where the growth rate in women has exceeded men is in the 20-29 age group; this growth is particularly in the injury and poisoning categories. • Considerable attention has been paid publicly to ED performance criteria. It is worth noting that 50% of all patients were treated within 33 minutes of arrival. • Patients from lower socioeconomic areas appear to have higher utilisation rates and the utilisation rate for indigenous people appears to exceed those of European and other backgrounds. The utilisation rates for immigrant people is generally less than that of Australian born however it has not been possible to eliminate the confounding impact of different age and socioeconomic profiles. • Demand for ambulance service is also increasing at a rate that exceeds population growth. Utilisation rates have increased by an average of 5% per annum in Queensland compared to 3.6% nationally, and the utilisation rate in Queensland is 27% higher than the national average. • The growth in ambulance utilisation has also been amongst the more urgent categories of dispatch and utilisation rates are higher in rural and regional areas than in the metropolitan area. The demand for ambulance increases with age but the growth in demand for ambulance service has been more prominent in younger age groups. These findings contribute significantly to an understanding of the growth in demand for emergency health. It shows that the growth is amongst patients in genuine need of emergency healthcare and public rhetoric that the congestion of emergency health services is due to inappropriate attendees is unable to be substantiated. The consistency of the growth in demand over the last decade reflects not only the changing demographics of the Australian population but also the changes in health status, standards of acute health care and other social factors. The growth is also amongst patients with acute injury and poisoning which is inconsistent with rates of chronic disease as a fundamental driver. We have also interviewed patients in regard to their decision making choices for acute health care and the factors that influence these decisions and this will be the subject of a third Monograph and publications.
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Proxy reports from parents and self-reported data from pupils have often been used interchangeably to identify factors influencing school travel behaviour. However, few studies have examined the validity of proxy reports as an alternative to self-reported data. In addition, despite research that has been conducted in a different context, little is known to date about the impact of different factors on school travel behaviour in a sectarian divided society. This research examines these issues using 1624 questionnaires collected from four independent samples (e.g. primary pupils, parent of primary pupils, secondary pupils, and parent of secondary pupils) across Northern Ireland. An independent sample t test was conducted to identify the differences in data reporting between pupils and parents for different age groups using the reported number of trips for different modes as dependent variables. Multivariate multiple regression analyses were conducted to then identify the impacts of different factors (e.g. gender, rural–urban context, multiple deprivations, and school management type, net residential density, land use diversity, intersection density) on mode choice behaviour in this context. Results show that proxy report is a valid alternative to self-reported data, but only for primary pupils. Land use diversity and rural–urban context were found to be the most important factors in influencing mode choice behaviour.
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An advanced rule-based Transit Signal Priority (TSP) control method is presented in this paper. An on-line transit travel time prediction model is the key component of the proposed method, which enables the selection of the most appropriate TSP plans for the prevailing traffic and transit condition. The new method also adopts a priority plan re-development feature that enables modifying or even switching the already implemented priority plan to accommodate changes in the traffic conditions. The proposed method utilizes conventional green extension and red truncation strategies and also two new strategies including green truncation and queue clearance. The new method is evaluated against a typical active TSP strategy and also the base case scenario assuming no TSP control in microsimulation. The evaluation results indicate that the proposed method can produce significant benefits in reducing the bus delay time and improving the service regularity with negligible adverse impacts on the non-transit street traffic.
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For the evaluation, design, and planning of traffic facilities and measures, traffic simulation packages are the de facto tools for consultants, policy makers, and researchers. However, the available commercial simulation packages do not always offer the desired work flow and flexibility for academic research. In many cases, researchers resort to designing and building their own dedicated models, without an intrinsic incentive (or the practical means) to make the results available in the public domain. To make matters worse, a substantial part of these efforts pertains to rebuilding basic functionality and, in many respects, reinventing the wheel. This problem not only affects the research community but adversely affects the entire traffic simulation community and frustrates the development of traffic simulation in general. For this problem to be addressed, this paper describes an open source approach, OpenTraffic, which is being developed as a collaborative effort between the Queensland University of Technology, Australia; the National Institute of Informatics, Tokyo; and the Technical University of Delft, the Netherlands. The OpenTraffic simulation framework enables academies from geographic areas and disciplines within the traffic domain to work together and contribute to a specific topic of interest, ranging from travel choice behavior to car following, and from response to intelligent transportation systems to activity planning. The modular approach enables users of the software to focus on their area of interest, whereas other functional modules can be regarded as black boxes. Specific attention is paid to a standardization of data inputs and outputs for traffic simulations. Such standardization will allow the sharing of data with many existing commercial simulation packages.
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A novel intelligent online demand side management system is proposed for peak load management in low-voltage distribution networks. This method uses low-cost controllers with low-bandwidth two-way communication installed in custumers’ premises and at distribution transformers to manage the peak load while maximising customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified by simulation of three different feeder types.
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This paper reviews electricity consumption feedback literature to explore the potential of electricity feedback to affect residential consumers’ electricity usage patterns. The review highlights a substantial amount of literature covering the debate over the effectiveness of different feedback criteria to residential customer acceptance and overall conservation and peak demand reduction. Researchers studying the effects of feedback on everyday energy use have observed substantial variation in effect size, both within and between studies. Although researchers still continue to question the types of feedback that are most effective in encouraging conservation and peak load reduction, some trends have emerged. These include that feedback be received as quickly as possible to the time of consumption; be related to a standard; be clear and meaningful and where possible both direct and indirect feedback be customised to the customer. In general, the literature finds that feedback can reduce electricity consumption in homes by 5 to 20 per cent, but that significant gaps remain in our knowledge of the effectiveness and cost benefit of feedback.
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The field of destination image has been widely discussed in the destination literature since the early 1970s (see Mayo, 1973). However the extent to which travel context impacts on an individual’s destination image evaluation, and therefore destination choice, has received scant attention (Hu & Ritchie, 1993). This study, utilising expectancy-value theory, sought to elicit salient destination attributes from consumers across two travel contexts: short-break holidays and longer getaways. Using the Repertory Test technique, attributes elicited as being salient for short-break holidays were consistent with those elicited for longer getaways. While this study was limited to Brisbane’s near-home destinations, the results will be of interest to destination marketers and researchers interested in the challenge of positioning a destination in diverse markets.
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This paper presents a methodology for real-time estimation of exit movement-specific average travel time on urban routes by integrating real-time cumulative plots, probe vehicles, and historic cumulative plots. Two approaches, component based and extreme based, are discussed for route travel time estimation. The methodology is tested with simulation and is validated with real data from Lucerne, Switzerland, that demonstrate its potential for accurate estimation. Both approaches provide similar results. The component-based approach is more reliable, with a greater chance of obtaining a probe vehicle in each interval, although additional data from each component is required. The extreme-based approach is simple and requires only data from upstream and downstream of the route, but the chances of obtaining a probe that traverses the entire route might be low. The performance of the methodology is also compared with a probe-only method. The proposed methodology requires only a few probes for accurate estimation; the probe-only method requires significantly more probes.
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Bus travel time estimation and prediction are two important modelling approaches which could facilitate transit users in using and transit providers in managing the public transport network. Bus travel time estimation could assist transit operators in understanding and improving the reliability of their systems and attracting more public transport users. On the other hand, bus travel time prediction is an important component of a traveller information system which could reduce the anxiety and stress for the travellers. This paper provides an insight into the characteristic of bus in traffic and the factors that influence bus travel time. A critical overview of the state-of-the-art in bus travel time estimation and prediction is provided and the needs for research in this important area are highlighted. The possibility of using Vehicle Identification Data (VID) for studying the relationship between bus and cars travel time is also explored.
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Travel time in an important transport performance indicator. Different modes of transport (buses and cars) have different mechanical and operational characteristics, resulting in significantly different travel behaviours and complexities in multimodal travel time estimation on urban networks. This paper explores the relationship between bus and car travel time on urban networks by utilising the empirical Bluetooth and Bus Vehicle Identification data from Brisbane. The technologies and issues behind the two datasets are studied. After cleaning the data to remove outliers, the relationship between not-in-service bus and car travel time and the relationship between in-service bus and car travel time are discussed. The travel time estimation models reveal that the not-in-service bus travel time are similar to the car travel time and the in-service bus travel time could be used to estimate car travel time during off-peak hours
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This report is the second deliverable of the Real Time and Predictive Traveller Information project and the first deliverable of the Freeway Travel Time Information sub-project in the Integrated Traveller Information research Domain of the Smart Transport Research Centre. The primary objective of the Freeway Travel Time Information sub-project is to develop algorithms for real-time travel time estimation and prediction models for Freeway traffic. The objective of this report is to review the literature pertaining to travel time estimation and prediction models for freeway traffic.